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Successful export sectors in manufacturing and agribusiness are important drivers of structural transformation in Sub-Sahara African countries. Backed by industrial policies and active state involvement, a small number of successful productive export sectors has emerged in Sub-Saharan Africa. This thesis asks the question: How do politics shape the promotion of export-driven industrialisation and firm-level upgrading in Sub-Saharan Africa? It exemplifies this question with an in-depth, qualitative study of the cashew processing industry in Mozambique in the period from 1991 until 2019. Mozambique used to be one of the world’s largest producers and processors of cashew nuts in the 1960s and 1970s. At the end of the 20th century, the cashew processing industry broke down completely but has re-emerged as one of the country’s few successful agro-processing exports.
The thesis draws on theoretical approaches from the fields of political science, notably the political settlements framework, global value chain analysis and the research on technological capabilities to explore why the Mozambican Government supported the cashew processing industry and how Mozambican cashew processors acquired the technological capabilities needed to access the global cashew value chain and to upgrade. It makes an important theoretical contribution by linking the political settlements framework and the literature on upgrading in global value chains to study how politics shaped productive sector promotion and upgrading in the Mozambican cashew processing industry. The findings of the thesis are based on extensive primary data, including 58 expert interviews and 10 firm surveys, that was collected in Mozambique in 2018 as well as a broad base of secondary literature.
The thesis argues that the Mozambican Government supported the cashew processing industry because it became important for the Government’s political survival. Promoting the cashew sector formed part of an electoral strategy for the ruling FRELIMO coalition and a means to keep FRELIMO factions united by offering economic opportunities to key constituencies. In 1999, it adopted a protectionist cashew law that created strong incentives for cashew processing in Mozambique. This not only facilitated the re-emergence of the cashew processing industry after its breakdown. The law and the active involvement of the National Cashew Institute (INCAJU) also affected the governance of the local cashew value chain, the creation of backward linkages, and the upgrading paths of cashew processors. The findings of the thesis suggest that the cashew law reduced the pressure on the cashew processing industry to upgrade. The law further created opportunities for formal and informal rent creation for members of the political elite and lower level FRELIMO officials that prevented a far-reaching reform of the law. The thesis shows that international buyers do not promote upgrading among Sub-Sahara African firms in global value chains with market-based or modular governance. Moreover, firms that operate in countries where industrial policies are not enforced effectively cannot draw on the support of government institutions to enhance their capabilities and to upgrade. Firms therefore mainly depended on costly learning channels at firm level, e.g. learning by doing or hiring skilled labour, and/or on technical assistance from donors to build the technological capabilities needed to access global value chains and to remain competitive.
The findings of the thesis suggest that researchers, governments, development practitioners and consultants need to rethink their understanding of upgrading in GVCs in four ways. First, they need to move away from understanding upgrading in terms of moving towards more complex, higher value-added activities in GVCs (functional upgrading). Instead, it is important to consider the potential of other, more realistic types of upgrading for firms in low-income countries, such reducing risks by diversifying suppliers and buyers or increasing rewards by making production processes more efficient. Second, they need to replace an overly positive view on upgrading that neglects possible side-effects at sector and/or country level. Third, GVC participation on its own does not promote upgrading among local supplier firms in Sub-Saharan Africa. The interests of lead firms and Sub-Sahara African supplier firms may not be aligned or even conflicting. Targeted industrial policies and the creation of institutions that effectively promote capability building among firms therefore become even more important. Finally, upgrading needs to be understood as a process that is not only shaped by interactions between firms, but also by local domestic politics.
The findings of the thesis are highly relevant for scholars from the fields of political science, development studies, and economics. Its practical implications and tools, e.g. a technological capabilities matrix for the cashew industry, are of interest for development practitioners, members of public institutions in Sub-Sahara African countries, local entrepreneurs, and representatives of local business associations that are involved in promoting export sectors and upgrading among local firms.
Water is used in a way as if it were available infinitely. Droughts, increased rainfall or flooding already lead to water shortages and, thus, deprive entire population groups of the basis of their livelihoods. There is a growing fear that conflicts over water will increase, especially in arid climate zones, because life without water - whether for humans, animals or plants - is not possible.
More than 60 % of the African population depend on land and water resources for their livelihoods through pastoralism, fishing and farming. The water levels of rivers and lakes are decreasing. Hence, the rural population which is dependent on land and water move towards water-rich and humid areas. This internal migration increases the pressure on available water resources. Driven by the desire to strengthen the economic development, African governments align their political agendas with the promotion of macro international and national economic projects.
This doctoral thesis examines the complex interrelationships between water shortages, governance, vulnerability, adaptive capacity and violent and non-violent conflicts at Lake Naivasha in Kenya and Lake Wamala in Uganda. In order to satisfy the overall complexity, this doctoral thesis combines various theoretical and empirical aspects in which a variety of methods are applied to different geographical regions, across disciplines, and cultural and political boundaries.
The investigation reveals that Lake Naivasha is more affected by violent conflicts than Lake Wamala. Reasons for this include population growth, historically grown ethnic conflicts, corruption and the preferential treatment of national and international economic actors. The most common conflict response tools are raiding and the blockage of water access. However, deathly encounters, destruction of property and cattle slaughtering are increasingly used to gain access to water and land.
The insufficient implementation of the political system and the governments’ prioritization to foster economic development results, on the one hand, in the commercialization of water resources and increases, on the other hand, non-violent conflict between national and sub-national political actors. While corruption, economic favours and patronage defuse this conflict, resource access becomes more difficult for the local population. Resulting thereof, a final hypothesis is developed which states that the localization of the political conflict aggravates the water situation for the local population and, thereby, favours violent conflicts over water access and water use in water-rich areas.
Within the field of Business Process Management, business rules are commonly used to model company decision logic and govern allowed company behavior. An exemplary business rule in the financial sector could be for example:
”A customer with a mental condition is not creditworthy”. Business rules are
usually created and maintained collaboratively and over time. In this setting,
modelling errors can occur frequently. A challenging problem in this context is
that of inconsistency, i.e., contradictory rules which cannot hold at the same
time. For instance, regarding the exemplary rule above, an inconsistency would
arise if a (second) modeller entered an additional rule: ”A customer with a mental condition is always creditworthy”, as the two rules cannot hold at the same
time. In this thesis, we investigate how to handle such inconsistencies in business
rule bases. In particular, we develop methods and techniques for the detection,
analysis and resolution of inconsistencies in business rule bases
Rivers play an important role in the global water cycle, support biodiversity and ecological integrity. However, river flow and thermal regimes are heavily altered in dammed rivers. These impacts are being exacerbated and become more apparent in rivers fragmented by multiple dams. Recent studies mainly focused on evaluating the cumulative impact of cascade reservoirs on flow or thermal regimes, but the role of upstream reservoirs in shaping the hydrology and hydrodynamics of downstream reservoirs remains poorly understood. To improve the understanding of the hydrodynamics in cascade reservoirs, long-term observational data are used in combination with numerical modeling to investigate the changes in flow and thermal regime in three cascade reservoirs at the upper reach of the Yangtze River. The three studied reservoirs are Xiluodu (XLD), Xiangjiaba (XJB) and Three Gorges Reservoir (TGR). In addition, the effects of single reservoir operation (at seasonal/daily time scale) on hydrodynamics are examined in a large tributary of TGR. The results show that the inflow of TGR has been substantially altered by the two upstream reservoirs with a higher discharge in spring and winter and a reduced peak flow in summer. XJB had no obvious contribution to the variations in inflow of TGR. The seasonal water temperature of TGR was also widely affected by the upstream two reservoirs, i.e., an increase in winter and decrease in spring, associated with a delay in water temperature rise and fall. These effects will probably be intensified in the coming years due to the construction of new reservoirs. The study also underlines the importance of reservoir operation in shaping the hydrodynamics of TGR. The seasonal dynamics of density currents in a tributary bay of TGR are closely related to seasonal reservoir operations. In addition, high-frequency water level fluctuations and flow velocity variations were observed in response to periodic tributary bay oscillations, which are driven by the diurnal discharge variations caused by the operation of TGR. As another consequence of operation of cascade reservoirs, the changes in TGR inflow weakened spring thermal stratification and caused warming in spring, autumn and winter. In response to this change, the intrusions from TGR occurred more frequently as overflow and earlier in spring, which caused a sharp reduction in biomass and frequency of phytoplankton blooms in tributary bays of TGR. This study suggests that high-frequency bay oscillations can potentially be used as an efficient management strategy for controlling algal blooms, which can be included in future multi-objective ecological conservation strategies.
Method development for the quantification of pharmaceuticals in aqueous environmental matrices
(2021)
As a consequence of the world population increase and the resulting water scarcity, water quality is the object of growing attention. In that context, organic anthropogenic molecules — often defined as micropollutants— represent a threat for water resources. Among them, pharmaceuticals are the object of particular concerns due to their permanent discharge, their increasing consumption and their effect-based structures. Pharmaceuticals are mainly introduced in the environment via wastewater treatment plants (WWTPs), along with their metabolites and the on-site formed transformation products (TPs). Once in the aquatic environment, they partition between the different environmental compartments in particular the aqueous phase, suspended particulate matter(SPM) and biota. In the last decades, pharmaceuticals have been widely investigated in the water phase. However, extreme polar pharmaceuticals have rarely been monitored due to the lack of robust analytical methods. Moreover, metabolites and TPs have seldom been included in routine analysis methods although their environmental relevance is proven. Furthermore, pharmaceuticals have been only sporadically investigated in SPM and biota and adequate multi-residue methods are lacking to obtain comprehensive results about their occurrence in these matrices. This thesis endeavors to cover these gaps of knowledge by the development of generic multi-residue methods for pharmaceuticals determination in the water phase, SPM and biota and to evaluate the occurrence and partition of pharmaceuticals into these compartments. For a complete overview, a particular focus was laid on extreme polar pharmaceuticals, pharmaceutical metabolites and TPs. In total, three innovative multi-residue methods were developed, they include analytes covering a broad range of physico-chemical properties. First, a reliable multi-residue method was developed for the analysis of extreme polar pharmaceuticals, metabolites and TPs dissolved in water. The selected analytes covered a significant range of elevated polarity and the method would be easily expendable to further analytes. This versatility could be achieved by the utilization of freeze-drying as sample preparation and zwitterionic hydrophilic interaction liquid chromatography (HILIC) in gradient elution mode. The suitability of HILIC chromatography to simultaneously quantify a large range of micropollutants in aqueous environmental samples was thoroughly studied. Several limitations were pointed out: a very complex and time-consuming method development, a very high sensitivity with regards to modification of the acetonitrile to water ratio in the eluent or the diluent and high positive matrix effects for certain analytes. However, these limitations can be overcome by the utilization of a precise protocol and appropriate labeled internal standards. They are overmatched by the benefits of HILIC which permits the chromatographic separation of extreme polar micropollutants. Investigation of environmental samples showed elevated concentrations of the analytes in the water phase. In particular, gabapentin, metformin, guanylurea and oxypurinol were measured at concentrations in the µg/L range in surface water. Subsequently, a reliable multi-residue method was established for the determination of 57 pharmaceuticals, 47 metabolites and TPs sorbed to SPM down to the low ng/g range. This method was conceived to cover a large range of polarity in particular with the inclusion of extreme polar pharmaceuticals. The extraction procedure was based on pressurized liquid extraction (PLE) followed by a clean-up via solvent exchange and detection via direct injection-reversed-phase LC-MS/MS and freeze-drying HILIC-MS/MS. Pharmaceutical sorption was examined using laboratory experiments. Derived distribution coefficients Kd varied by five orders of magnitude among the analytes and confirmed a high sorption potential for positively charged and nonpolar pharmaceuticals. The occurrence of pharmaceuticals in German rivers SPM was evaluated by the investigation of annual composite SPM samples taken at four sites at the river Rhine and one site at the river Saar between the years 2005 and 2015. It revealed the ubiquitous presence of pharmaceuticals sorbed to SPM in these rivers. In particular, positively charged analytes, even very polar and nonpolar pharmaceuticals showed appreciable concentrations. For many pharmaceuticals, a distinct correlation was observed between the annual quantities consumed in Germany and the concentrations measured in SPM. Studies of composite SPM spatial distribution permitted to get hints about specific industrial discharge by comparing the pollution pattern along the river. For the first time, these results showed the potential of SPM for the monitoring of positively charged and nonpolar pharmaceuticals in surface water. Finally, a reliable and generic multi residue method was developed to investigate 35 pharmaceuticals and 28 metabolites and TPs in fish plasma, fish liver and fish fillet. For this matrix, it was very challenging to develop an adequate clean-up allowing for the sufficient separation of the matrix disturbances from the analytes. In the final method, fish tissue extraction was performed by cell disruption followed by a non-discriminating clean-up based on silica gel solid-phase extraction(SPE) and restrictive access media (RAM) chromatography. Application of the developed method to the measurement of bream and carp tissues from German rivers revealed that even polar micropollutants such as pharmaceuticals are ubiquitously present in fish tissues. In total, 17 analytes were detected for the first time in fish tissues, including 10 metabolites/TPs. The importance of monitoring metabolites and TPs in fish tissues was confirmed with their detection at similar concentrations as their parents. Liver and fillet were shown to be appropriate for the monitoring of pharmaceuticals in fish, whereas plasma is more inconvenient due to very low concentrations and collection difficulties. Elevated concentrations of certain metabolites suggest possible formation of human metabolites in fish. Measured concentrations indicate a low bioaccumulation potential for pharmaceuticals in fish tissues.
Real-time operating systems for mixed-criticality systems
must support different types of software, such as
real-time applications and general purpose applications,
and, at the same time, must provide strong spatial and
temporal isolation between independent software components.
Therefore, state-of-the-art real-time operating systems
focus mainly on predictability and bounded worst-case behavior.
However, general purpose operating systems such as Linux
often feature more efficient---but less deterministic---mechanisms
that significantly improve the average execution time.
This thesis addresses the combination of the two contradicting
requirements and shows thread synchronization mechanisms
with efficient average-case behavior, but without sacrificing
predictability and worst-case behavior.
This thesis explores and evaluates the design space of fast paths
in the implementation of typical blocking synchronization
mechanisms, such as mutexes, condition variables, counting
semaphores, barriers, or message queues. The key technique here
is to avoid unnecessary system calls, as system calls have high
costs compared to other processor operations available in user
space, such as low-level atomic synchronization primitives.
In particular, the thesis explores futexes, the state-of-the-art
design for blocking synchronization mechanisms in Linux
that handles the uncontended case of thread synchronization
by using atomic operations in user space and calls into the
kernel only to suspend and wake up threads. The thesis also
proposes non-preemptive busy-waiting monitors that use an
efficient priority ceiling mechanism to prevent the lock holder
preemption problem without using system calls, and according
low-level kernel primitives to construct efficient wait and
notify operations.
The evaluation shows that the presented approaches
improve the average performance comparable
to state-of-the-art approaches in Linux.
At the same time, a worst-case timing analysis shows
that the approaches only need constant or bounded temporal
overheads at the operating system kernel level.
Exploiting these fast paths is a worthwhile approach
when designing systems that not only have to fulfill
real-time requirements, but also best-effort workloads.
Although most plastic pollution originates on land, current research largely remains focused on aquatic ecosystems. Studies pioneering terrestrial microplastic research have adapted analytical methods from aquatic research without acknowledging the complex nature of soil. Meanwhile, novel methods have been developed and further refined. However, methodical inconsistencies still challenge a comprehensive understanding of microplastic occurrence and fate in and on soil. This review aims to disentangle the variety of state-of-the-art sample preparation techniques for heterogeneous solid matrices to identify and discuss best-practice methods for soil-focused microplastic analyses. We show that soil sampling, homogenization, and aggregate dispersion are often neglected or incompletely documented. Microplastic preconcentration is typically performed by separating inorganic soil constituents with high-density salt solutions. Not yet standardized but currently most used separation setups involve overflowing beakers to retrieve supernatant plastics, although closed-design separation funnels probably reduce the risk of contamination. Fenton reagent may be particularly useful to digest soil organic matter if suspected to interfere with subsequent microplastic quantification. A promising new approach is extraction of target polymers with organic solvents. However, insufficiently characterized soils still impede an informed decision on optimal sample preparation. Further research and method development thus requires thorough validation and quality control with well-characterized matrices to enable robust routine analyses for terrestrial microplastics.
Schizophrenia is a chronic mental health disorder, which changes rapidly the life of the persons and their families, who suffer from it. It causes high biological and psychological vulnerability as well as cognitive, emotional and behavioral disorders. Nowadays, evidence-based pharmacotherapy and psychotherapy are available aiming the rehabilitation and recovery of individuals with schizophrenia. A democratic society is obliged to give these people the opportunity to have an access to those treatments.
The following three published studies present this dissertation thesis and have a common focus on the implementation of evidence-based psychotherapy in individuals with schizophrenia.
The first study evaluates the efficacy of the Integrated Psychological Therapy (IPT) in Greece, one of the most evaluated rehabilitation programs. IPT was compared to
Treatment as Usual (TAU) in a randomized controlled trial (RCT) with 48 individuals with schizophrenia. Significant effects favouring IPT were found in working memory,
in social perception, in negative symptoms, in general psychopathology and in insight. This study supports evidence for the efficacy of IPT in Greece.
The second study evaluates a second hypothesis, when IPT is more and less effective regarding treatment resistant schizophrenia (TRS) and non treatment resistant
schizophrenia (NTRS). It is a part of the first paper. Significant effects favouring NTRS were found for verbal memory, for symptoms, for functioning and quality of
life. Effect sizes showed superiority of NTRS in comparison to TRS. IPTTRS showed on the other side some significant improvements. This study presents the initial findings of a larger study to be conducted internationally for the first time.
The third study is a systematic review, which aims to evaluate the efficacy of Cognitive Behavioral Therapy (CBT), of Meta Cognitive Therapy (MCT), Metacognitive Training (MCTR), Metacognitive Reflection and Insight Therapy
(MERIT), of various Rehabilitation Programs and Recovery Programs in individuals with schizophrenia. 41 RCTs and 12 Case Studies were included. The above interventions are efficacious in the improvement of cognitions, symptoms, functional outcome, insight, self-esteem, comorbid disorders and metacognitive capacity.
The three studies provide insight regarding the importance of evidence-based psychotherapy in persons with schizophrenia leading to recovery and reintegration into
society. Future RCTs with larger samples and long-term follow up, combining evidence-based psychotherapies for individuals with schizophrenia need to be done.
This thesis examined two specific cases of point and diffuse pollution, pesticides and salinisation, which are two of the most concerning stressors of Germany’s freshwater bodies. The findings of this thesis were organized into three major components, of which the first component presents the contribution of WWTPs to pesticide toxicity (Chapter 2). The second component focuses on the current and future background salt ion concentrations under climate change with the absence of anthropogenic activities (Chapter 3). Finally, the third major component shows the response of invertebrate communities in terms of species turnover to levels of salinity change, considered as a proxy for human-driven salinisation (Chapter 4).
The Material Point Method (MPM) has proven to be a very capable simulation method in computer graphics that is able to model materials that were previously very challenging to animate [1, 2]. Apart from simulating singular materials, the simulation of multiple materials that interact with each other introduces new challenges. This is the focus of this thesis. It will be shown that the self-collision capabilities of the MPM can naturally handle multiple materials interacting in the same scene on a collision basis, even if the materials use distinct constitutive models. This is then extended by porous interaction of materials as in[3], which also integrates easily with MPM.It will furthermore be shown that regular single-grid MPM can be viewed as a subset of this multi-grid approach, meaning that its behavior can also be achieved if multiple grids are used. The porous interaction is generalized to arbitrary materials and freely changeable material interaction terms, yielding a flexible, user-controllable framework that is independent of specific constitutive models. The framework is implemented on the GPU in a straightforward and simple way and takes advantage of the rasterization pipeline to resolve write-conflicts, resulting in a portable implementation with wide hardware support, unlike other approaches such as [4].
In this thesis we examined the question whether personality traits of early child care workers influence process quality in preschool.
Research has shown that in educational settings such as preschool, pedagogical quality affects children’s developmental outcome (e.g. NICHD, 2002; Peisner-Feinberg et al., 1999). A substantial part of pedagogical quality known to be vital in this respect is the interaction between teacher and children (e.g., Tietze, 2008). Results of prior classroom research indicate that the teachers’ personality might be an important factor for good teacher-child-interaction (Mayr, 2011). Thus, personality traits might play a vital role for the interaction in preschool. Therefore, the aims of this thesis were to a) identify pivotal personality traits of child care workers, b) assess ideal levels of the identified personality traits and c) examine the relationship between pivotal personality traits and process quality. On that account, we conducted two requirement analyses and a video study. The results of these studies showed that subject matter experts (parents, child care workers, lecturers) partly agreed as to which personality traits are pivotal for child care workers. Furthermore, the experts showed high consensus with regard to the minimum, ideal and maximum personality trait profiles. Furthermore, child care workers whose profiles lay closer to the experts’ ideal also showed higher process quality. In addition, regression analyses showed that the child care workers’ levels of the Big Two (Communion and Agency) related significantly to their process quality.
In Western personnel psychology, competence- and control beliefs (CCB) are of widespread use to predict typical work-related outcomes such as well-being, achievement motivation and job performance. The predictive value and comprehension of CCB in East Africa is examined, comparing a Kenyan target with a German source sample (N=143). Responses to personality tests included qualitative interviews on items capturing control orientations (self concept of ability, internality, powerful others, and chance). Linear regression analyses,
explorative factor analyses, and a procrustean target rotation showed comparable, but not fully congruent predictability for the connection of CCB with outcome variables. Factor structures of control responses did not resemble each other sufficiently. Content analyses including scale intercorrelations, quantitative and qualitative item information served for an explanation of this predictability gap, specifying differences between the German and Kenyan samples that are associated with the social-relational domain of personality. Results
fit in the picture depicted by the African Ubuntu philosophy and the South African Personality Inventory project (SAPI), both emphasizing social-relational aspects. In particular, the powerful others control orientation diverges the most between the cultures. Being perceived as a negative and external factor in the German sample with its individualistic culture, powerful others is of mixed emotional quality and just as well internal, when asked for in the Kenyan sample with its Ubuntu-worldview. An uncritical transfer of CCB measures from one culture to another is assumed to be inappropriate. More emic-etic based research is demanded concerning intra- and intercultural variability of CCB to depict a
transcultural applicable model.
The history of human kind is characterized by social conflict. Every conflict can be the starting point of social change or the escalation into more destructive forms. The social conflict in regard to rising numbers of refugees and their acceptance that arose in most host countries in 2015 already took on destructive forms – in Germany, right-wing extremists attacked refugee shelters and even killed multiple people, including political leaders who openly supported refugees. Thus, incompatible expectancies and values of different parts of the society led to violent action tendencies, which tremendously threaten intergroup relations. Psychological research has developed several interventions in past decades to improve intergroup relations, but they fall short, for example, when it comes to the inclusion of people with extreme attitudes and to precisely differentiate potential prosocial outcomes of the interventions. Thus, this dissertation aimed to a) develop psychological interventions, that could also be applied to people with more extreme attitudes, thereby putting a special emphasis on collecting a diverse sample; b) gain knowledge about target- and outcome specific effects: Who benefits from which intervention and how can specific prosocial actions be predicted in order to develop interventions that guide needs-based actions; and c) shed light on potential underlying mechanisms of the interventions.
The dissertation will be introduced by the socio-political background that motivated the line of research pursued, before providing an overview of the conceptualization of social conflicts and potential psychological inhibitors and catalyzers for conflict transformation. Based on past research on socio-psychological interventions and their limitations, the aims of the dissertation will be presented in more detail, followed by a short summary of each manuscript. Overall, the present thesis comprises four manuscripts that were summarized in the general discussion into a road map for social-psychological interventions to put them into a broader perspective. The road map aspires to provide recommendations for increasing – either approach-oriented or support-oriented actions – by the socio-psychological interventions for a variety of host society groups depending on their pre-existing attitude towards refugees.
A Paradoxical Intervention targeting central beliefs of people with negative attitudes towards refugees influenced inhibitory and catalyzing factors for conflict transformation over the course of three experiments – thereby providing an effective tool to establish approach-oriented action tendencies, such as the willingness to get in contact with refugees. Further, the dissertation presents a novel mechanism – namely Cognitive Flexibility – which could explain the Paradoxical Interventions’ effect of past research. By positively affecting a context-free mindset, the Paradoxical Intervention could impact more flexible thought processes in general, irrespective of the topic tackled in the Paradoxical Intervention itself. For people with rather positive attitudes addressing emotions may increase specific support-oriented action tendencies. The dissertation provides evidence of a positive relation between moral outrage and hierarchy-challenging actions, such as solidarity-based collective action, and sympathy with prosocial hierarchy-maintaining support-oriented actions, such as dependency-oriented helping. These exclusive relations between specific emotions and action intentions provide important implications for the theorizing of emotion-behavior relations, as well as for practical considerations. In addition, a diversity workshop conducted with future diplomats showed indirect effects on solidarity-based collective action via diversity perception and superordinate group identification, thereby extending past research by including action intentions and going beyond the focus on grassroot-initiatives by presenting an implementable intervention for future leaders in a real world context.
Taken together, this dissertation provides important insights for the development of socio-psychological interventions. By integrating a diverse sample, including members of institutions on meso- and macro-levels (non-governmental organizations and future politicians) of our society, this dissertation presents a unique multi-perspective of host society members on the social conflict of refugee acceptance and support. Thereby, this work contributes to theoretical and practical advancement of how social psychology can contribute not only to negative peace – by for example (indirectly) reducing support of violence against refugees – but also to positive peace – by for example investigating precursors of hierarchy-challenging actions that enable equal rights.
Interest in crowdfunding has been increasing in recent years, both from the economy and the scientific community. Besides artists and entrepreneurs, researchers are now also funding their projects through many small contributions from the crowd. However, the perceived use in Germany does not reflect the benefits of a crowdfunding campaign, especially in international comparison. This study investigates this issue by identifying the motives and barriers for crowdfunding in order to formulate recommendations for research institutions to encourage the use of crowdfunding.
By means of a literature review, first insights are gained which are then used to conduct qualitative interviews with eleven researchers who successfully completed a crowdfunding campaign. The results indicate that researchers in Germany use crowdfunding primarily to raise awareness for the subject and the scientific community in general. The initial assumption of the speed of crowdfunding as a motive was contradicted by the experts. The major barriers are the immense effort involved in a campaign and the lack of reputation for the concept of crowdfunding by German scientists. In addition, only subjects and projects with a high public relevance and funding volume of up to five digits are recommended for crowdfunding. Furthermore, the public exposure of the experts during the campaign was identified as an additional barrier.
These findings lead to three recommendations for research institutions to increase the use of crowdfunding: Firstly, universities should raise awareness for the subject of crowdfunding as an additional form of research funding and highlight the benefits of a crowdfunding campaign. Secondly, universities should cooperate with crowdfunding partners and utilize the networking capacities of a university. Lastly, universities should provide support to distribute the workload among interdisciplinary teams in order to enhance the effortreturn ratio of a crowdfunding campaign.
The chosen methodology and the scope of the thesis enable further research that might examine the perspective of the universities and the conditions in other countries. In addition, a largescale quantitative survey is required to validate the identified concepts statistically.
Social media platforms such as Twitter or Reddit allow users almost unrestricted access to publish their opinions on recent events or discuss trending topics. While the majority of users approach these platforms innocently, some groups have set their mind on spreading misinformation and influencing or manipulating public opinion. These groups disguise as native users from various countries to spread frequently manufactured articles, strong polarizing opinions in the political spectrum and possibly become providers of hate-speech or extremely political positions. This thesis aims to implement an AutoML pipeline for identifying second language speakers from English social media texts. We investigate style differences of text in different topics and across the platforms Reddit and Twitter, and analyse linguistic features. We employ feature-based models with datasets from Reddit, which include mostly English conversation from European users, and Twitter, which was newly created by collecting English tweets from selected trending topics in different countries. The pipeline classifies language family, native language and origin (Native or non-Native English speakers) of a given textual input. We evaluate the resulting classifications by comparing prediction accuracy, precision and F1 scores of our classification pipeline to traditional machine learning processes. Lastly, we compare the results from each dataset and find differences in language use for topics and platforms. We obtained high prediction accuracy for all categories on the Twitter dataset and observed high variance in features such as average text length especially for Balto-Slavic countries.
Initial goal of the current dissertation was the determination of image-based biomarkers sensitive for neurodegenerative processes in the human brain. One such process is the demyelination of neural cells characteristic for Multiple sclerosis (MS) - the most common neurological disease in young adults for which there is no cure yet. Conventional MRI techniques are very effective in localizing areas of brain tissue damage and are thus a reliable tool for the initial MS diagnosis. However, a mismatch between the clinical fndings and the visualized areas of damage is observed, which renders the use of the standard MRI diffcult for the objective disease monitoring and therapy evaluation. To address this problem, a novel algorithm for the fast mapping of myelin water content using standard multiecho gradient echo acquisitions of the human brain is developed in the current work. The method extents a previously published approach for the simultaneous measurement of brain T1, T∗ 2 and total water content. Employing the multiexponential T∗ 2 decay signal of myelinated tissue, myelin water content is measured based on the quantifcation of two water pools (myelin water and rest) with different relaxation times. Whole brain in vivo myelin water content maps are acquired in 10 healthy controls and one subject with MS. The in vivo results obtained are consistent with previous reports. The acquired quantitative data have a high potential in the context of MS. However, the parameters estimated in a multiparametric acquisition are correlated and constitute therefore an ill-posed, nontrivial data analysis problem. Motivated by this specific problem, a new data clustering approach is developed called Nuclear Potential Clustering, NPC. It is suitable for the explorative analysis of arbitrary dimensional and possibly correlated data without a priori assumptions about its structure. The developed algorithm is based on a concept adapted from nuclear physics. To partition the data, the dynamic behavior of electrically even charged nucleons interacting in a d-dimensional feature space is modeled. An adaptive nuclear potential, comprised of a short-range attractive (Strong interaction) and a long-range repulsive term (Coulomb potential), is assigned to each data point. Thus, nucleons that are densely distributed in space fuse to build nuclei (clusters), whereas single point clusters are repelled (noise). The algorithm is optimized and tested in an extensive study with a series of synthetic datasets as well as the Iris data. The results show that it can robustly identify clusters even when complex configurations and noise are present. Finally, to address the initial goal, quantitative MRI data of 42 patients are analyzed employing NPC. A series of experiments with different sets of image-based features show a consistent grouping tendency: younger patients with low disease grade are recognized as cohesive clusters, while those of higher age and impairment are recognized as outliers. This allows for the definition of a reference region in a feature space associated with phenotypic data. Tracking of the individual's positions therein can disclose patients at risk and be employed for therapy evaluation.
Stream ecosystems are one of the most threatened ecosystems worldwide due to their exposure to diverse anthropogenic stressors. Pesticides appear to be the most relevant stressor for agricultural streams. Due to the current mismatch of modelled and measured pesticide concentrations, monitoring is necessary to inform risk assessment or improve future pesticide approvals. Knowing if biotic stress responses are similar across large scales and long time frames could ultimately help in estimating protective stressor thresholds.
This thesis starts with an overview of entry pathways of pesticides to streams as well as the framework of current pesticide monitoring and gives an outline of the objectives of the thesis. In chapter 2, routine monitoring data based on grab sampling from several countries is analysed to identify the most frequently occurring pesticide mixtures. These mixtures are comprised of relatively low numbers of pesticides, of which herbicides are dominating. The detected pesticide mixtures differ between regions and countries, due to differences in the spectrum of analysed compounds and limits of quantification. Current routine monitoring does not include sampling during pesticide peaks associated with heavy rainfall events which likely influences the detected pesticide mixtures. In chapter 3, sampling rates of 42 organic pesticides for passive sampling are provided together with recommendations for the monitoring of field-relevant peaks. Using this information, in chapter 4 a pesticide gradient is established in an Eastern European region where agricultural intensity adjacent to sampled streams ranges from low to high. In contrast to current routine monitoring, rainfall events were sampled and a magnitude of pesticides were analysed. This led to the simultaneous detection of numerous pesticides of which one to three drive the pesticide toxicity. The toxicity, however, showed no relationship to the agricultural intensity. Using microcosms, the stress responses of fungal communities, the hyphomycetes, and the related ecosystem function of leaf decomposition, is investigated in chapter 5. Effects of a field-relevant fungicide mixture are examined across three biogeographical regions for three consecutive cycles of microbial leaf colonisation and decomposition. Despite different initial communities, stress responses as well as recoveries were similar across biogeographical regions, indicating a general pattern.
Overall, this thesis contributes to an improved understanding of occurrence and concentrations of pesticides mixtures in streams, their monitoring and impact on an ecosystem function. We showed that estimated pesticide toxicities reach levels that affect non-target organisms and thereby potentially whole ecosystems. Routine monitoring, however, likely underestimates the threat by pesticides. Effects leading to a loss in biodiversity or functions in streams ecosystems can be reduced by reassessing approved pesticides with ongoing targeted monitoring and increased knowledge of effects caused by these pesticides.
The three biodegradable polymers polylactic acid (PLA), polyhydroxybutyrate (PHB) and polybutylene adipate terephthalate (PBAT) were coated with hydrogenated amorphous carbon layers (a-C:H) in the context of this thesis. A direct alignment of the sample surface to the source was chosen, resulting in the deposition of a robust, r-type a-C:H. At the same time, a partly covered silicon wafer was placed together with the polymers in the coating chamber and was coated. Silicon is a hard material and serves as a reference for the applied layers. Due to the hardness of the material, no mixed phase occurs between the substrate and the applied layer (no interlayer formation). In addition, the thickness of the applied layer can be estimated with the help of the silicon sample.
The deposition of the layer was realized by radio frequency plasma enhanced chemical vapor deposition (RF-PECVD). For the coating the samples were pre-treated with an oxygen plasma. Acetylene was used as precursor gas for the plasma coating. Coatings with increasing thickness in 50 nm steps from 0-500 nm were realised.
The surface analysis was performed using several techniques: The morphology and layer stability were analyzed with scanning electron microscopy (SEM) measurements. The wettability was determined by contact angle technique. In addition, the contact angles provide macroscopic information about the bond types of the carbon atoms present on the surface. For microscopic analysis of the chemical composition of the sample and layer surfaces, diffuse reflectance Fourier transform infrared spectroscopy (DRIFT) as well as synchrotron based X-ray photon spectroscopy (XPS) and near edge X-ray absorption fine structure spectroscopy (NEXAFS) were used.
All coated polymers showed several cases of layer failure due to internal stress in the layers. However, these were at different layer thicknesses, so there was a substrate effect. In addition, it is visible in the SEM images that the coatings of PLA and PHB can cause the applied layer to wave, the so-called cord buckling. This does not occur with polymer PBAT, which indicates a possible better bonding of the layer to the polymer. The chemical analyses of the layer surfaces show for each material a layer thickness dependent ratio of sp² to sp³ bonds of carbon, which alternately dominate the layer. In all polymers, the sp³ bond initially dominates, but the sp² to sp³ ratio changes at different intervals. Although the polymers were coated in the same plasma, i.e. the respective layer thicknesses (50 nm, 100 nm, ...) were applied in the same plasma process, the respective systems differed considerably from each other. A substrate effect is therefore demonstrably present. In addition, it was found that a change in the dominant bond from sp³ to sp² is an indication ofan upcoming layer failure of the a-C:H layer deposited on the polymer. In the case of PLA, this occurs immediately with change to sp² as the dominant bond; in the case of PHB and PBAT, this occurs with different delay to increased layer thicknesses (at PHB 100 nm, at PBAT approx. 200 nm.
Overall, this thesis shows that there is a substrate effect in the coating of the biodegradable polymers PLA, PHB and PBAT, since despite the same coating there is a different chemical composition of the surface at the respective layer thicknesses. In addition, a layer failure can be predicted by analyzing the existing bond.
Data-minimization and fairness are fundamental data protection requirements to avoid privacy threats and discrimination. Violations of data protection requirements often result from: First, conflicts between security, data-minimization and fairness requirements. Second, data protection requirements for the organizational and technical aspects of a system that are currently dealt with separately, giving rise to misconceptions and errors. Third, hidden data correlations that might lead to influence biases against protected characteristics of individuals such as ethnicity in decision-making software. For the effective assurance of data protection needs,
it is important to avoid sources of violations right from the design modeling phase. However, a model-based approach that addresses the issues above is missing.
To handle the issues above, this thesis introduces a model-based methodology called MoPrivFair (Model-based Privacy & Fairness). MoPrivFair comprises three sub-frameworks: First, a framework that extends the SecBPMN2 approach to allow detecting conflicts between security, data-minimization and fairness requirements. Second, a framework for enforcing an integrated data-protection management throughout the development process based on a business processes model (i.e., SecBPMN2 model) and a software architecture model (i.e., UMLsec model) annotated with data protection requirements while establishing traceability. Third, the UML extension UMLfair to support individual fairness analysis and reporting discriminatory behaviors. Each of the proposed frameworks is supported by automated tool support.
We validated the applicability and usability of our conflict detection technique based on a health care management case study, and an experimental user study, respectively. Based on an air traffic management case study, we reported on the applicability of our technique for enforcing an integrated data-protection management. We validated the applicability of our individual fairness analysis technique using three case studies featuring a school management system, a delivery management system and a loan management system. The results show a promising outlook on the applicability of our proposed frameworks in real-world settings.
Amphibian populations are declining worldwide for multiple reasons such as habitat destruction and climate change. An example for an endangered European amphibian is the yellow-bellied toad Bombina variegata. Populations have been declining for decades, particularly at the northern and western range margin. One of the extant northern range centres is the Westerwald region in Rhineland-Palatinate, Germany. To implement informed conservation activities on this threatened species, knowledge of its life-history strategy is crucial. This study therefore focused on different developmental stages to test predictions of life-history theory. It addressed (1) developmental, (2) demographic and (3) genetic issues of Bombina variegata as a model organism: (1) Carry-over effects from larval environment to terrestrial stages and associated vulnerability to predators were investigated using mesocosm approaches, fitness tests and predation trials. (2) The dynamics and demography of B. variegata populations were studied applying a capture-mark-recapture analysis and skeletochronology. The study was complemented through (3) an analysis of genetic diversity and structuring of B. variegata populations using 10 microsatellite loci. In order to reveal general patterns and characteristics among B. variegata populations, the study focused on three geographical scales: local (i.e. a former military training area), regional (i.e. the Westerwald region) and continental scale (i.e. the geographical range of B. variegata). The study revealed carry-over effects of larval environment on metamorph phenotype and behaviour causing variation in fitness in the early terrestrial stage of B. variegata. Metamorph size and condition are crucial factors for survival, as small-sized individuals were particularly prone to predator attacks. Yellow-bellied toads show a remarkable fast-slow continuum of the life-history trait longevity. A populations’ position within this continuum may be determined by local environmental stochasticity, i.e. an extrinsic source of variation, and the efficiency of chemical antipredator protection, i.e. an intrinsic source of variation. Extreme longevity seems to be an exception in B. variegata. Senescence was absent in this study. Weather variability affected reproductive success and thus population dynamics. The dispersal potential was low and short-term fragmentation of populations caused significant genetic differentiation at the local scale. Long-term isolation resulted in increased genetic distance at the regional scale. At the continental scale, populations inhabiting the marginal regions were deeply structured with reduced allelic richness. As consequence of environmental changes, short-lived and isolated B. variegata populations at the range margin may face an increased risk of extinction. Conservation measures should thus improve the connectivity among local populations and reinforce annual reproductive success. Further research on the intraspecific variation in B. variegata skin toxins is required to reveal potential effects on palatability and thus longevity.
Despite widespread plans of big companies like Amazon and Google to develop unmanned delivery drones, scholarly research in this field is scarce, especially in the information systems field. From technical and legal perspectives, drone delivery in last-mile scenarios is in a quite mature state. However, estimates of user acceptance are varying between high skepticism and exaggerated optimism. This research follows a mixed method approach consisting both qualitative and quantitative research, to identify and test determinants of consumer delivery drone service adoption. The qualitative part rests on ten interviews among average consumers, who use delivery services on a regular basis. Insights gained from the qualitative part were used to develop an online survey and to assess the influence of associated risks on adoption intentions. The quantitative results show that especially financial and physical risks impede drone delivery service adoption. Delivery companies who are currently thinking about providing a delivery drone service may find these results useful when evaluating usage behaviors in the future market for delivery drones.
Railway safety is a topic which gains the public attention only if major railway accidents happen. This is because railway is considered as a safe mode of travel by the public. However, to ensure the safety of the railway system railway companies as well as universities conduct a broad spectrum of research. An overview of this research has not yet been provided in the scholarly literature. Therefore, this thesis follows two objectives. First an overview and ranking of railway safety research universities should be provided. Second, based on these universities, it should be identified which are the most relevant and influential research topics. The ranking is based on the research method “literature review” which forms the methodical basis for this thesis. To evaluate the universities based on a measurable and objective criterion, the number of citations of the researchers from each university is gathered. As a result, the University of Leuven for the civil engineering, Milan Politechnico for mechanical enginering and the University of Loughborough for electrical engineering are identified as the leading university in their field of railway safety research. The top universities for each discipline are distributed all over Europe, North America and Asia. However, a clear focus on the US and British universities is observed. For identification of the most relevant and influential topics the keywords from the publications which are considered in the ranking procedure are analyzed. Focus areas among these keywords are revealed by calculating the count of each keyword. High-speed trains as well as maintenance are recognized as the highly relevant topics in both civil and mechanical engineering. Furthermore, the topic of railway dynamics for mechanical engineering and noise and vibration for civil engineering are identified as the leading topics in the respective discipline. Achieving both research goals required exploratory approaches. Therefore, this thesis leaves open space for future research to deepen the individual topics which are approached in each section. A validation of the results through experts interviews as well as a deepening of the analysis through increasing the number of analyzed universities as well as applying statistical methods is recommended.
Microbial pollution of surface waters poses substantial risks for public health, amongst others during recreational use. Microbial pollution was studied at selected sampling sites in rivers Rhine, Moselle and Lahn (Germany) on the basis of commonly used fecal indicator organisms (FIO) indicating bacterial (Escherichia coli, intestinal enterococci) and viral (somatic coliphages) fecal contamination. In addition, blaCTX-Mantibiotic resistance genes (ARG) were quantified at twosites in river Lahn and were used as markers for tracking the spread of antibiotic resistance in the aquatic environment. The impact of changes in climate-related parameters on FIO was examined by studying monitoring results of contrasting flow conditions at rivers Rhine and Moselle. Analyses at all studied river sites clearly indicate that high discharge and precipitation enhance the influx of FIO, ARG and thus potentially (antibiotic resistant) pathogens into rivers. In contrast, a decrease in hygienic microbial pollution was observed under high solar irradiation and increasing water temperatures. Based on identified contributing key factors, multiple linear regression (MLR) models for five sites at a stretch of river Lahn were established that allow a timely assessment of fecal indicator abundances. An interaction between abiotic and biotic factors (i.e. enhanced grazing pressure) considerably contributed to the formation of seasonal patterns among FIO abundances. This was enhanced during extraordinary low flow conditions in rivers with pronounced trophic interactions, clearly hampering a transfer of model approaches between rivers of different biological and hydrological characteristics. Bacterial indicatorswere stronger influenced by grazing pressure than phages. Hence, bacterial indicators alone do not sufficiently describe viral pollution in rivers. BlaCTX-Mgenes were omnipresent in Lahn River water and corresponded to distribution patterns of FIO, indicating fecal sources. Agriculture and waste watertreatment plant effluents contributed to ARG loads and participants in non-bathing water sports were found to be at risk of ingesting antibiotic resistant bacteria (ARB) including ARG, bearing the risk of infection or colonization. Results of the present study highlight the need to be aware of such risks not only in designated bathing waters. ARG abundance at both riverine sampling sites could largely be explained by E. coliabundance and may thus also be incorporated into multiple regression models using E. colispecific environmental predictors. It can be expected that the frequency of short-term microbial pollution events will increase over the next decades due to climate change. Several challenges were identified with regard to the implementation of early warning systems to protect the public from exposure to pathogens in rivers. Most importantly, the concept of the Bathing Water Directive (Directive 2006/7/EC) itself as well as the lack of harmonization in the regulatory framework at European Union (EU) level are major drawbacks and require future adjustments to reliably manage health risks related to microbial water pollution in waters used in multifunctional ways.
The industry standard Decision Model and Notation (DMN) has enabled a new way for the formalization of business rules since 2015. Here, rules are modeled in so-called decision tables, which are defined by input columns and output columns. Furthermore, decisions are arranged in a graph-like structure (DRD level), which creates dependencies between them. With a given input, the decisions now can be requested by appropriate systems. Thereby, activated rules produce output for future use. However, modeling mistakes produces erroneous models, which can occur in the decision tables as well as at the DRD level. According to the Design Science Research Methodology, this thesis introduces an implementation of a verification prototype for the detection and resolution of these errors while the modeling phase. Therefore, presented basics provide the needed theoretical foundation for the development of the tool. This thesis further presents the architecture of the tool and the implemented verification capabilities. Finally, the created prototype is evaluated.
Because silver nanoparticles (Ag NPs) are broadly applied in consumer products, their leaching will result in the continuous release of Ag NPs into the natural aquatic environment. Therefore, bacterial biofilms, as the prominent life form of microorganisms in the aquatic environment, are most likely confronted with Ag NPs as a pollutant stressor. Notwithstanding the significant ecological relevance of bacterial biofilms in aquatic systems, and though Ag NPs are expected to accumulate within these biofilms in the environment, the knowledge on the environmental and ecological impact of Ag NPs, is still lagging behind the industrial growth of nanotechnology. Consequently, aim of this thesis was to perform effect assessment of Ag NP exposure on bacterial biofilms with ambient Ag NPs concentrations and under environmentally relevant conditions. Therefore, a comprehensive set of methods was applied in this work to study if and how Ag NPs of two different sizes (30 and 70 nm) affect bacterial biofilms i.e. both monospecies biofilms and freshwater biofilms in environmentally relevant concentrations (600 - 2400 µg l-1). Within the first part of this work, a newly developed assay to test the mechanical stability of
monospecies biofilms of the freshwater model bacterium Aquabacterium citratiphilum was validated. In the first study, to investigate the impact of Ag NPs on the mechanical stability of bacterial biofilms, sublethal effects on the mechanical stability of the biofilms were observed with negative implications for biostabilization. Furthermore, as it is still challenging to monitor the ecotoxicity of Ag NPs in natural freshwater environments, a mesocosm study was performed in this work to provide the possibility for the detailed investigation of effects of Ag NPs on freshwater biofilms under realistic environmental conditions. By applying several approaches to analyze biofilms as a whole in response to Ag NP treatment, insights into the resilience of bacterial freshwater biofilms were obtained. However, as revealed by t-RFLP fingerprinting combined with phylogenetic studies based on the 16S gene, a shift in the bacterial community composition, where Ag NP-sensitive bacteria were replaced by more Ag NP-tolerant species with enhanced adaptability towards Ag NP stress was determined. This shift within the bacterial community may be associated with potential detrimental effects on the functioning of these biofilms with respect to nutrient loads, transformation and/or degradation of pollutants, and biostabilization. Overall, bringing together the key findings of this thesis, 4 general effect mechanisms of Ag NP treatment have been identified, which can be extrapolated to natural freshwater biofilms i.e. (i) the identification of Comamonadaceae as Ag NP-tolerant, (ii) a particular resilient behaviour of the biofilms, (iii) the two applied size fractions of Ag NPs exhibited similar effects independent of their sizes and their synthesis method, and (iv) bacterial biofilms show a high uptake capacity for Ag NPs, which indicates cumulative enrichment.
Bio-medical data comes in various shapes and with different representations.
Domain experts use such data for analysis or diagnosis,
during research or clinical applications. As the opportunities to obtain
or to simulate bio-medical data become more complex and productive,
the experts face the problem of data overflow. Providing a
reduced, uncluttered representation of data, that maintains the data’s
features of interest falls into the area of Data Abstraction. Via abstraction,
undesired features are filtered out to give space - concerning the
cognitive and visual load of the viewer - to more interesting features,
which are therefore accentuated. To address this challenge, the dissertation
at hand will investigate methods that deal with Data Abstraction
in the fields of liver vasculature, molecular and cardiac visualization.
Advanced visualization techniques will be applied for this purpose.
This usually requires some pre-processing of the data, which will also
be covered by this work. Data Abstraction itself can be implemented
in various ways. The morphology of a surface may be maintained,
while abstracting its visual cues. Alternatively, the morphology may
be changed to a more comprehensive and tangible representation.
Further, spatial or temporal dimensions of a complex data set may
be projected to a lower space in order to facilitate processing of the
data. This thesis will tackle these challenges and therefore provide an
overview of Data Abstraction in the bio-medical field, and associated
challenges, opportunities and solutions.
On-screen interactive presentations have got immense popularity in the domain of attentive interfaces recently. These attentive screens adapt their behavior according to the user's visual attention. This thesis aims to introduce an application that would enable these attentive interfaces to change their behavior not just according to the gaze data but also facial features and expressions. The modern era requires new ways of communications and publications for advertisement. These ads need to be more specific according to people's interests, age, and gender. When advertising, it's important to get a reaction from the user but not every user is interested in providing feedback. In such a context more, advance techniques are required that would collect user's feedback effortlessly. The main problem this thesis intends to resolve is, to apply advanced techniques of gaze and face recognition to collect data about user's reactions towards different ads being played on interactive screens. We aim to create an application that enables attentive screens to detect a person's facial features, expressions, and eye gaze. With eye gaze data we can determine the interests and with facial features, age and gender can be specified. All this information will help in optimizing the advertisements.
Molecular dynamics (MD) as a field of molecular modelling has great potential to revolutionize our knowledge and understanding of complex macromolecular structures. Its field of application is huge, reaching from computational chemistry and biology over material sciences to computer-aided drug design. This thesis on one hand provides insights into the underlying physical concepts of molecular dynamics simulations and how they are applied in the MD algorithm, and also briefly illustrates different approaches, as for instance the molecular mechanics and molecular quantum mechanics approaches.
On the other hand an own all-atom MD algorithm is implemented utilizing and simplifying a version of the molecular mechanics based AMBER force field published by \big[\cite{cornell1995second}\big]. This simulation algorithm is then used to show by the example of oxytocin how individual energy terms of a force field function. As a result it has been observed, that applying the bond stretch forces alone caused the molecule to be compacted first in certain regions and then as a whole, and that with adding more energy terms the molecule got to move with increasing flexibility.
Blockchain in Healthcare
(2020)
The underlying characteristics of blockchain can facilitate data provenance, data integrity, data security, and data management. It has the potential to transform the healthcare sector. Since the introduction of Bitcoin in the fintech industry, the blcockhain technology has been gaining a lot of traction and its purpose is not just limited to finance. This thesis highlights the inner workings of blockchain technology and its application areas with possible existing solutions. Blockchain could lay the path for a new revolution in conventional healthcare systems. We presented how individual sectors within the healthcare industry could use blockchain and what solution persists. Also, we have presented our own concept to improve the existing paper-based prescription management system which is based on Hyperledger framework. The results of this work suggest that healthcare can benefit from blockchain technology bringing in the new ways patients can be treated.
The European landscape is dominated by intensive agriculture which leads to widespread impact on the environment. The frequent use of agricultural pesticides is one of the major causes of an ongoing decline in flower-visiting insects (FVIs). The conservation of this ecologically diverse assemblage of mobile, flying insect species is required by international and European policy. To counteract the decrease in species numbers and their abundances, FVIs need to be protected from anthropogenic stressors. European pesticide risk assessment was devised to prevent unacceptable adverse consequences of pesticide use on FVIs. However, there is an ongoing discussion by scientists and policy-makers if the current risk assessment actually provides adequate protection for FVI species.
The first main objective of this thesis was to investigate pesticide impact on FVI species. The scientific literature was reviewed to identify groups of FVIs, summarize their ecology, and determine their habitat. This was followed by a synthesis of studies about the exposure of FVIs in their habitat and subsequent effects. In addition, the acute sensitivity of one FVI group, bee species, to pesticides was studied in laboratory experiments.
The second main objective was to evaluate the European risk assessment for possible deficits and propose improvements to the current framework. Regulatory documents were screened to assess the adequacy of the guidance in place in light of the scientific evidence. The suitability of the honey bee Apis mellifera as the currently only regulatory surrogate species for FVIs was discussed in detail.
The available scientific data show that there are far more groups of FVIs than the usually mentioned bees and butterflies. FVIs include many groups of ecologically different species that live in the entire agricultural landscape. Their habitats in crops and adjacent semi-natural areas can be contaminated by pesticides through multiple pathways. Environmentally realistic exposure of these habitats can lead to severe effects on FVI population parameters. The laboratory studies of acute sensitivity in bee species showed that pesticide effects on FVIs can vary greatly between species and pesticides.
The follow-up critical evaluation of the European FVI risk assessment revealed major shortcomings in exposure and effect assessment. The honey bee proved to be a sufficient surrogate for bee species in lower tier risk assessment. Additional test species may be chosen for higher tier risk assessment to account for ecological differences. This thesis shows that the ecology of FVIs should generally be considered to a greater extent to improve the regulatory process. Data-driven computational approaches could be used as alternative methods to incorporate ecological trait data in spatio-temporal scenarios. Many open questions need to be answered by further research to better understand FVI species and promote necessary changes to risk assessment. In general, other FVI groups than bees need to be investigated. Furthermore, comprehensive data on FVI groups and their ecology need to be collected. Contamination of FVI habitat needs to be linked to exposure of FVI individuals and ecologically complex effects on FVI populations should receive increased attention. In the long term, European FVI risk assessment would benefit from shifting its general principles towards more scientifically informed regulatory decisions. This would require a paradigm shift from arbitrary assumptions and unnecessarily complicated schemes to a substantiated holistic framework.
Since the invention of U-net architecture in 2015, convolutional networks based on its encoder-decoder approach significantly improved results in image analysis challenges. It has been proven that such architectures can also be successfully applied in different domains by winning numerous championships in recent years. Also, the transfer learning technique created an opportunity to push state-of-the-art benchmarks to a higher level. Using this approach is beneficial for the medical domain, as collecting datasets is generally a difficult and expensive process.
In this thesis, we address the task of semantic segmentation with Deep Learning and make three main contributions and release experimental results that have practical value for medical imaging.
First, we evaluate the performance of four neural network architectures on the dataset of the cervical spine MRI scans. Second, we use transfer learning from models trained on the Imagenet dataset and compare it to randomly initialized networks. Third, we evaluate models trained on the bias field corrected and raw MRI data. All code to reproduce results is publicly available online.
Environmental processes transforming inorganic nanoparticles: implications on aquatic invertebrates
(2020)
Engineered inorganic nanoparticles (EINPs) are produced and utilized on a large scale and will end up in surface waters. Once in surface waters, EINPs are subjected to transformations induced by environmental processes altering the particles’ fate and inherent toxicity. UV irradiation of photoactive EINPs is defined as one effect-inducing pathway, leading to the formation of reactive oxygen species (ROS), increasing EINP toxicity by exerting oxidative stress in aquatic life. Simultaneously, UV irradiation of photoactive EINP alters the toxicity of co-occurring micropollutants (e.g. pesticides) by affecting their degradation. The presence of natural organic matter (NOM) reduces the agglomeration and sedimentation of EINPs, extending the exposure of pelagic species, while delaying the exposure of benthic species living in and on the sediment, which is suggested as final sink for EINPs. However, the joint impact of NOM and UV irradiation on EINP-induced toxicity, but also EINP-induced degradation of micropollutants, and the resulting risk for aquatic biota, is poorly understood. Although potential effects of EINPs on benthic species are increasingly investigated, the importance of exposure pathways (waterborne or dietary) is unclear, along with the reciprocal pathway of EINPs, i.e. the transport back from aquatic to terrestrial ecosystems. Therefore, this thesis investigates: (i) how the presence of NOM affects the UV-induced toxicity of the model EINP titanium dioxide (nTiO2) on the pelagic organism Daphnia magna, (ii) to which extent UV irradiation of nTiO2 in the presence and absence of NOM modifies the toxicity of six selected pesticides in D. magna, (iii) potential exposure pathway dependent effects of nTiO2 and silver (nAg) EINPs on the benthic organism Gammarus fossarum, and (iv) the transport of nTiO2 and gold EINPs (nAu) via the merolimnic aquatic insect Chaetopteryx villosa back to terrestrial ecosystems. nTiO2 toxicity in D. magna increased up to 280-fold in the presence of UV light, and was mitigated by NOM up to 12-fold. Depending on the pesticide, UV irradiation of nTiO2 reduced but also enhanced pesticide toxicity, by (i) more efficient pesticide degradation, and presumably (ii) formation of toxic by-products, respectively. Likewise, NOM reduced and increased pesticide toxicity, induced by (i) protection of D. magna against locally acting ROS, and (ii) mitigation of pesticide degradation, respectively. Gammarus’ energy assimilation was significantly affected by both EINPs, however, with distinct variation in direction and pathway dependence between nTiO2 and nAg. EINP presence delayed C. villosa emergence by up to 30 days, and revealed up to 40% reduced lipid reserves, while the organisms carried substantial amounts of nAu (~1.5 ng/mg), and nTiO2 (up to 2.7 ng/mg). This thesis shows, that moving test conditions of EINPs towards a more field-relevant approach, meaningfully modifies the risk of EINPs for aquatic organisms. Thereby, more efforts need to be made to understand the relative importance of EINP exposure pathways, especially since a transferability between different types of EINPs may not be given. When considering typically applied risk assessment factors, adverse effects on aquatic systems might already be expected at currently predicted environmental EINP concentrations in the low ng-µg/L range.
The distributed setting of RDF stores in the cloud poses many challenges. One such challenge is how the data placement on the compute nodes can be optimized to improve the query performance. To address this challenge, several evaluations in the literature have investigated the effects of existing data placement strategies on the query performance. A common drawback in theses evaluations is that it is unclear whether the observed behaviors were caused by the data placement strategies (if different RDF stores were evaluated as a whole) or reflect the behavior in distributed RDF stores (if cloud processing frameworks like Hadoop MapReduce are used for the evaluation). To overcome these limitations, this thesis develops a novel benchmarking methodology for data placement strategies that uses a data-placement-strategy-independent distributed RDF store to analyze the effect of the data placement strategies on query performance.
With this evaluation methodology the frequently used data placement strategies have been evaluated. This evaluation challenged the commonly held belief that data placement strategies that emphasize local computation, such as minimal edge-cut cover, lead to faster query executions. The results indicate that queries with a high workload may be executed faster on hash-based data placement strategies than on, e.g., minimal edge-cut covers. The analysis of the additional measurements indicates that vertical parallelization (i.e., a well-distributed workload) may be more important than horizontal containment (i.e., minimal data transport) for efficient query processing.
Moreover, to find a data placement strategy with a high vertical parallelization, the thesis tests the hypothesis that collocating small connected triple sets on the same compute node while balancing the amount of triples stored on the different compute nodes leads to a high vertical parallelization. Specifically, the thesis proposes two such data placement strategies. The first strategy called overpartitioned minimal edge-cut cover was found in the literature and the second strategy is the newly developed molecule hash cover. The evaluation revealed a balanced query workload and a high horizontal containment, which lead to a high vertical parallelization. As a result these strategies showed a better query performance than the frequently used data placement strategies.
Nowadays, almost any IT system involves personal data processing. In
such systems, many privacy risks arise when privacy concerns are not
properly addressed from the early phases of the system design. The
General Data Protection Regulation (GDPR) prescribes the Privacy by
Design (PbD) principle. As its core, PbD obliges protecting personal
data from the onset of the system development, by effectively
integrating appropriate privacy controls into the design. To
operationalize the concept of PbD, a set of challenges emerges: First, we need a basis to define privacy concerns. Without such a basis, we are not able to verify whether personal data processing is authorized. Second, we need to identify where precisely in a system, the controls have to be applied. This calls for system analysis concerning privacy concerns. Third, with a view to selecting and integrating appropriate controls, based on the results of system analysis, a mechanism to identify the privacy risks is required. Mitigating privacy risks is at the core of the PbD principle. Fourth, choosing and integrating appropriate controls into a system are complex tasks that besides risks, have to consider potential interrelations among privacy controls and the costs of the controls.
This thesis introduces a model-based privacy by design methodology to handle the above challenges. Our methodology relies on a precise definition of privacy concerns and comprises three sub-methodologies: model-based privacy analysis, modelbased privacy impact assessment and privacy-enhanced system design modeling. First, we introduce a definition of privacy preferences, which provides a basis to specify privacy concerns and to verify whether personal data processing is authorized. Second, we present a model-based methodology to analyze a system model. The results of this analysis denote a set of privacy design violations. Third, taking into account the results of privacy analysis, we introduce a model-based privacy impact assessment methodology to identify concrete privacy risks in a system model. Fourth, concerning the risks, and taking into account the interrelations and the costs of the controls, we propose a methodology to select appropriate controls and integrate them into a system design. Using various practical case studies, we evaluate our concepts, showing a promising outlook on the applicability of our methodology in real-world settings.
Constituent parsing attempts to extract syntactic structure from a sentence. These parsing systems are helpful in many NLP applications such as grammar checking, question answering, and information extraction. This thesis work is about implementing a constituent parser for German language using neural networks. Over the past, recurrent neural networks have been used in building a parser and also many NLP applications. In this, self-attention neural network modules are used intensively to understand sentences effectively. With multilayered self-attention networks, constituent parsing achieves 93.68% F1 score. This is improved even further by using both character and word embeddings as a representation of the input. An F1 score of 94.10% was the best achieved by constituent parser using only the dataset provided. With the help of external datasets such as German Wikipedia, pre-trained ELMo models are used along with self-attention networks achieving 95.87% F1 score.
Gel effect induced by mucilage in the pore space and consequences on soil physical properties
(2020)
Water uptake, respiration and exudation are some of the biological functions fulfilled by plant roots. They drive plant growth and alter the biogeochemical parameters of soil in the vicinity of roots, the rhizosphere. As a result, soil processes such as water fluxes, carbon and nitrogen exchanges or microbial activity are enhanced in the rhizosphere in comparison to the bulk soil. In particularly, the exudation of mucilage as a gel-like substance by plant roots seems to be a strategy for plants to overcome drought stress by increasing soil water content and soil unsaturated hydraulic conductivity at negative water potentials. Although the variations of soil properties due to mucilage are increasingly understood, a comprehensive understanding of the mechanisms in the pore space leading to such variations is lacking.
The aim of this work was to elucidate the gel properties of mucilage in the pore space, i.e. interparticulate mucilage, in order to link changes of the physico-chemical properties in the rhizosphere to mucilage. The fulfilment of this goal was confronted to the three following challenges: The lack of methods for in situ detection of mucilage in soil; The lack of knowledge concerning the properties of interparticulate mucilage; The unknown relationship between the composition and the properties of model substances and root mucilage produced by various species. These challenges are addressed in several chapters.
In a first instance, a literature review picked information from various scientific fields about methods enabling the characterization of gels and gel phases in soil. The variation of soil properties resulting from biohydrogel swelling in soil was named the gel effect. The combined study of water entrapment of gels and gel phases in soil and soil structural properties in terms of mechanical stability or visual structures proved promising to disentangle the gel effect in soil.
The acquired methodical knowledge was used in the next experiments to detect and characterize the properties of interparticulate gel. 1H NMR relaxometry allows the non-invasive measure of water mobility in porous media. A conceptual model based on the equations describing the relaxation of water protons in porous media was developed to integrate the several gel effects into the NMR parameters and quantify the influence of mucilage on proton relaxation. Rheometry was additionally used to assess mucilage viscosity and soil microstructural stability and ESEM images to visualize the network of interparticulate gel. Combination of the results enabled to identify three main interparticulate gel properties: The spider-web effect restricts the elongation of the polymer chains due to the grip of the polymer network to the surface of soil particles. The polymer network effect illustrates the organization of the polymer network in the pore space according to the environment. The microviscosity effect describes the increased viscosity of interparticulate gel in contrast to free gel. The impact of these properties on soil water mobility and microstructural stability were investigated. Consequences on soil hydraulic and soil mechanical properties found in the literature are further discussed.
The influence of the chemical properties of polymers on gel formation mechanism and gel properties was also investigated. For this, model substances with various uronic acid content, degree of esterification and amount of calcium were tested and their amount of high molecular weight substances was measured. The substances investigated included pectic polysaccharides and chia seed mucilage as model polymers and wheat and maize root mucilage. Polygalacturonic acid and low-methoxy pectin proved as non-suitable model polymers for seed and root mucilage as ionic interactions with calcium control their properties. Mucilage properties rather seem to be governed by weak electrostatic interactions between the entangled polymer chains. The amount of high molecular weight material varies considerably depending on mucilage´s origin and seems to be a straight factor for mucilage’s gel effect in soil. Additionally to the chemical characterization of the high molecular weight compounds, determination of their molecular weight and of their conformation in several mucilages types is needed to draw composition-property profiles. The variations measured between the various mucilages also highlight the necessity to study how the specific properties of the various mucilages fulfill the needs of the plant from which they are exuded.
Finally, the integration of molecular interactions in gel and interparticulate gel properties to explain the physical properties of the rhizosphere was discussed. This approach offers numerous perspectives to clarify for example how water content or hydraulic conductivity in the rhizosphere vary according to the properties of the exuded mucilage. The hypothesis that the gel effect is general for all soil-born exudates showing gel properties was considered. As a result, a classification of soil-born gel phases including roots, seeds, bacteria, hyphae and earthworm’s exuded gel-like material according to their common gel physico-chemical properties is recommended for future research. An outcome could be that the physico-chemical properties of such gels are linked with the extent of the gel effect, with their impact on soil properties and with the functions of the gels in soil.
The bio-insecticide Bacillus thuringiensis israelensis (Bti) has worldwide become the most commonly used agentin mosquito control programs that pursue two main objectives: the control of vector-borne diseases and the reduction of nuisance, mainly coming frommosquitoes that emerge in large quantities from seasonal wetlands. The Upper Rhine Valley, a biodiversity hotspot in Germany, has been treated withBti for decades to reduce mosquito-borne nuisance and increase human well-being.Although Btiis presumed to be an environmentally safe agent,adverse effects on wetland ecosystems are still a matter of debate especially when it comes to long-term and indirect effects on non-target organisms. In light of the above, this thesis aims at investigating direct and indirect effects of Bti-based mosquito control on non-target organisms within wetland food chains.Effects were examinedin studies with increasingeco(toxico)logical complexity, ranging from laboratory over mesocosm to field approaches with a focus on the non-biting Chironomidae and amphibian larvae (Rana temporaria, Lissotriton sp.).In addition, public acceptance of environmentally less invasive alternative mosquito control methods was evaluated within surveys among the local population.
Chironomids were the most severely affected non-target aquatic invertebrates. Bti substantially reduced larval and adult chironomid abundances and modified their species composition. Repeated exposures to commonly used Bti formulations induced sublethal alterations of enzymatic biomarkers activityin frog tadpoles. Bti-induced reductions of chironomid prey availability indirectly decreased body size of newts at metamorphosis and increased predation on newt larvae in mesocosm experiments. Indirect effects of severe reductions in midge biomassmight equally be passed through aquatic but also terrestrial food chains influencing predators of higher trophic levels. The majority ofaffectedpeople in the Upper Rhine Valley expressed a high willingness to contributefinancially to environmentally less harmful mosquito control.Alternative approaches could still include Bti applications excepting treatment of ecologically valuable areas. Potentially rising mosquito levels could be counteracted with local acting mosquito traps in domestic and urban areas because mosquito presence was experienced as most annoying in the home environment.
As Bti-based mosquito control can adversely affect wetland ecosystems, its large-scale applications, including nature conservation areas, should be considered more carefully to avoid harmful consequences for the environmentat the Upper Rhine Valley.This thesis emphasizesthe importance to reconsiderthe current practice of mosquito control and encourage research on alternative mosquito control concepts that are endorsed by the local population. In the context ofthe ongoing amphibian and insect declinesfurther human-induced effects onwetlands should be avoided to preserve biodiversity in functioning ecosystems.
Thesis is devoted to the topic of challenges and solutions for human resources management (HRM) in international organizations. The aim is to investigate methodological approaches to assessment of HRM challenges and solutions, and to apply them on practice, to develop ways of improvement of HRM of a particular enterprise. The practical research question investigated is “Is the Ongoing Professional Development – Strategic HRM (OPD-SHRM) model a better solution for HRM system of PrJSC “Philip Morris Ukraine”?”
To achieve the aim of this work and to answer the research question, we have studied theoretical approaches to explaining and assessing HRM in section 1, analyzed HRM system of an international enterprise in section 2, and then synthesized theory and practice to find intersection points in section 3.
Research findings indicate that the main challenge of HRM is to balance between individual and organizational interests. Implementation of OPD-SHRM is one of the solutions. Switching focus from satisfaction towards success will bring both tangible and intangible benefits for individuals and organization. In case of PrJSC “Philip Morris Ukraine”, the maximum forecasted increase is 330% in net profit, 350% in labor productivity, and 26% in Employee Development and Engagement Index.
Current political issues are often reflected in social media discussions, gathering politicians and voters on common platforms. As these can affect the public perception of politics, the inner dynamics and backgrounds of such debates are of great scientific interest. This thesis takes user generated messages from an up-to-date dataset of considerable relevance as Time Series, and applies a topic-based analysis of inspiration and agenda setting to it. The Institute for Web Science and Technologies of the University Koblenz-Landau has collected Twitter data generated beforehand by candidates of the European Parliament Election 2019. This work processes and analyzes the dataset for various properties, while focusing on the influence of politicians and media on online debates. An algorithm to cluster tweets into topical threads is introduced. Subsequently, Sequential Association Rules are mined, yielding wide array of potential influence relations between both actors and topics. The elaborated methodology can be configured with different parameters and is extensible in functionality and scope of application.
This paper describes the robots TIAGo and Lisa used by
team homer@UniKoblenz of the University of Koblenz-Landau, Germany,
for the participation at the RoboCup@Home 2019 in Sydney,
Australia. We ended up first at RoboCup@Home 2019 in the Open Platform
League and won the competition in our league now three times
in a row (four times in total) which makes our team the most successful
in RoboCup@Home. We demonstrated approaches for learning from
demonstration, touch enforcing manipulation and autonomous semantic
exploration in the finals. A special focus is put on novel system components
and the open source contributions of our team. We have released
packages for object recognition, a robot face including speech synthesis,
mapping and navigation, speech recognition interface, gesture recognition
and imitation learning. The packages are available (and new packages
will be released) on http://homer.uni-koblenz.de.
This dissertation deals with the opportunities and restrictions that parties face in an election campaign at the supranational level of the EU. Using communication science concepts of agenda-setting (focus: media) and agenda-building (focus: political parties), the first part of the study is based on the election campaign for the European Parliament (EP) in 2014. It analyses to what extent political parties put the EU on the agenda. Second, it is examined whether parties have used their structural advantage of being able to influence the media agenda at the supranational level during the election campaign in the context of the EP election campaign. Third, it is examined whether parties can gain an advantage for the visibility of their campaigns by rejecting EU integration and the associated conflictual communication. Fourth and final, it will be explored whether agenda-building can influence the rankings of specific policy issues on the media agenda in the European context.
First, the analyses show that a European political focus of election campaign communication can no longer be found only on the part of the small (eurosceptic) parties. Second, parties have a good chance of being present in media coverage if the they pursue a European political focus in their campaign communication. Third, a negative tone in party communication turns out not to be decisive for the parties' visibility in the election campaign. Fourth, a clear positioning on political issues also prepares parties for restrictions of the further development of a European thematic agenda. After a discussion of these results, the paper concludes with an assessment of the analysis limitations and an outlook on further research approaches.
Software systems have an increasing impact on our daily lives. Many systems process sensitive data or control critical infrastructure. Providing secure software is therefore inevitable. Such systems are rarely being renewed regularly due to the high costs and effort. Oftentimes, systems that were planned and implemented to be secure, become insecure because their context evolves. These systems are connected to the Internet and therefore also constantly subject to new types of attacks. The security requirements of these systems remain unchanged, while, for example, discovery of a vulnerability of an encryption algorithm previously assumed to be secure requires a change of the system design. Some security requirements cannot be checked by the system’s design but only at run time. Furthermore, the sudden discovery of a security violation requires an immediate reaction to prevent a system shutdown. Knowledge regarding security best practices, attacks, and mitigations is generally available, yet rarely integrated part of software development or covering evolution.
This thesis examines how the security of long-living software systems can be preserved taking into account the influence of context evolutions. The goal of the proposed approach, S²EC²O, is to recover the security of model-based software systems using co-evolution.
An ontology-based knowledge base is introduced, capable of managing common, as well as system-specific knowledge relevant to security. A transformation achieves the connection of the knowledge base to the UML system model. By using semantic differences, knowledge inference, and the detection of inconsistencies in the knowledge base, context knowledge evolutions are detected.
A catalog containing rules to manage and recover security requirements uses detected context evolutions to propose potential co-evolutions to the system model which reestablish the compliance with security requirements.
S²EC²O uses security annotations to link models and executable code and provides support for run-time monitoring. The adaptation of running systems is being considered as is round-trip engineering, which integrates insights from the run time into the system model.
S²EC²O is amended by prototypical tool support. This tool is used to show S²EC²O’s applicability based on a case study targeting the medical information system iTrust.
This thesis at hand contributes to the development and maintenance of long-living software systems, regarding their security. The proposed approach will aid security experts: It detects security-relevant changes to the system context, determines the impact on the system’s security and facilitates co-evolutions to recover the compliance with the security requirements.
Belief revision is the subarea of knowledge representation which studies the dynamics of epistemic states of an agent. In the classical AGM approach, contraction, as part of the belief revision, deals with the removal of beliefs in knowledge bases. This master's thesis presents the study and the implementation of concept contraction in the Description Logic EL. Concept contraction deals with the following situation. Given two concept C and D, assuming that C is subsumed by D, how can concept C be changed so that it is not subsumed by D anymore, but is as similar as possible to C? This approach of belief change is different from other related work because it deals with contraction in the level of concepts and not T-Boxes and A-Boxes in general. The main contribution of the thesis is the implementation of the concept contraction. The implementation provides insight into the complexity of contraction in EL, which is tractable since the main inference task in EL is also tractable. The implementation consists of the design of five algorithms that are necessary for concept contraction. The algorithms are described, illustrated with examples, and analyzed in terms of time complexity. Furthermore, we propose an new approach for a selection function, adapt for the concept contraction. The selection function uses metadata about the concepts in order to select the best from an input set. The metadata is modeled in a framework that we have designed, based on standard metadata frameworks. As an important part of the concept contraction, the selection function is responsible for selecting the best concepts that are as similar as possible to concept C. Lastly, we have successfully implemented the concept contraction in Python, and the results are promising.
To construct a business process model manually is a highly complex and error-prone task which takes a lot of time and deep insights into the organizational structure, its operations and business rules. To improve the output of business analysts dealing with this process, different techniques have been introduced by researchers to support them during construction with helpful recommendations. These supporting recommendation systems vary in their way of what to recommend in the first place as well as their calculations taking place under the hood to recommend the most fitting element to the user. After a broad introduction into the field of business process modeling and its basic recommendation structures, this work will take a closer look at diverse proposals and descriptions published in current literature regarding implementation strategies to effectively and efficiently assist modelers during their business process model creation. A critical analysis of presentations in the selected literature will point out strengths and weaknesses of their approaches, studies and descriptions of those. As a result, the final concept matrix in this work will give a precise and helpful overview about the key features and recommendation methods used and implemented in previous research studies to pinpoint an entry into future works without the downsides already spotted by fellow researchers.
Commonsense reasoning can be seen as a process of identifying dependencies amongst events and actions. Understanding the circumstances surrounding these events requires background knowledge with sufficient breadth to cover a wide variety of domains. In the recent decades, there has been a lot of work in extracting commonsense knowledge, a number of these projects provide their collected data as semantic networks such as ConceptNet and CausalNet. In this thesis, we attempt to undertake the Choice Of Plausible Alternatives (COPA) challenge, a problem set with 1000 questions written in multiple-choice format with a premise and two alternative choices for each question. Our approach differs from previous work by using shortest paths between concepts in a causal graph with the edge weight as causality metric. We use CausalNet as primary network and implement a few design choices to explore the strengths and drawbacks of this approach, and propose an extension using ConceptNet by leveraging its commonsense knowledge base.
The Internet of Things is still one of the most relevant topics in the field of economics and research powered by the increasing demand of innovative services. Cost reductions in manufacturing of IoT hardware and the development of completely new communication ways has led to the point of bil-lions of devices connected to the internet. But in order to rule this new IoT landscape a standardized solution to conquer these challenges must be developed, the IoT Architecture.
This thesis examines the structure, purpose and requirements of IoT Architecture Models in the global IoT landscape and proposes an overview across the selected ones. For that purpose, a struc-tured literature analysis on this topic is conducted within this thesis, including an analysis on three existing research approaches trying to frame this topic and a tool supported evaluation of IoT Archi-tecture literature with over 200 accessed documents.
Furthermore, a coding of literature with the help of the specialised coding tool ATLAS.ti 8 is conduct-ed on 30 different IoT Architecture Models. In a final step these Architecture Models are categorized and compared to each other showing that the environment of IoT and its Architectures gets even more complex the further the research goes.
Implementation of Agile Software Development Methodology in a Company – Why? Challenges? Benefits?
(2019)
The software development industry is enhancing day by day. The introduction of agile software development methodologies was a tremendous structural change in companies. Agile transformation provides unlimited opportunities and benefits to the existing and new developing companies. Along with benefits, agile conversion also brings many unseen challenges. New entrants have the advantage of being flexible and cope with the environmental, consumer, and cultural changes, but existing companies are bound to rigid structure.
The goal of this research is to have deep insight into agile software development methodology, agile manifesto, and principles behind the agile manifesto. The prerequisites company must know for agile software development implementation. The benefits a company can achieve by implementing agile software development. Significant challenges that a company can face during agile implementation in a company.
The research objectives of this study help to generate strong motivational research questions. These research questions cover the cultural aspects of company agility, values and principles of agile, benefits, and challenges of agile implementation. The project management triangle will show how benefits of cost, benefits of time, and benefits of quality can be achieved by implementing agile methodologies. Six significant areas have been explored, which shows different challenges a company can face during implementation agile software development methodology. In the end, after the in depth systematic literature review, conclusion is made following some open topics for future work and recommendations on the topic of implementation of agile software development methodology in a company.
Ecological assessment approaches based on benthic invertebrates in Euphrates tributaries in Turkey
(2019)
Sustainable water management requires methods for assessing ecological stream quality. Many years of limnological research are needed to provide a basis for developing such methods. However, research of this kind is still lacking in Turkey. Therefore, the aim of this doctoral thesis was to provide basic research in the field of aquatic ecology and to present methods for the assessment of ecological stream quality based on benthic invertebrates. For this purpose, I selected 17 tributaries of the Euphrates with a similar typology/water order and varying levels of pollution or not affected by pollution at all. The characterisation of the natural mountain streams was the first important step in the analysis of ecological quality. Based on community indices, I found that the five selected streams had a very good ecological status. I also compared the different biological indications, collected on two occasions ¬– once in spring (May) and once in autumn (September) – to determine the optimal sampling time. The macroinvertebrate composition differed considerably between the two seasons, with the number of taxa and Shannon index being significantly higher in autumn than in spring. In the final step, I examined the basal resources of the macroinvertebrates in the reference streams with an isotope analysis. I found that FPOM and biofilm were the most relevant basal resources of benthic invertebrates. Subsequently, based on the similarity of their community structures, I divided the 17 streams into three quality classes, supported by four community indices (EPT [%], EPTCBO [%], number of individuals, evenness). In this process, 23 taxa were identified as indicators for the three quality classes. In the next step, I presented two new or adapted indices for the assessment of quality class. Firstly, I adapted the Hindu Kush-Himalaya biotic index to the catchment area of the Euphrates and created a new, ecoregion-specific score list (Euph-Scores) for 93 taxa. The weighted ASPT values, which were renamed the Euphrates Biotic Score (EUPHbios) in this study, showed sharper differentiations of quality classes compared to the other considered ASPT values. Thus, this modified index has proved to be very effective and easy to implement in practical applications. As a second biological index, I suggested the proportion of habitat specialists. To calculate this index, the habitat preferences of the 20 most common benthic invertebrates were identified using the new habitat score. The proportion of habitat specialists differed significantly among the three quality classes with higher values in natural streams than in polluted streams. The methods and results presented in this doctoral thesis can be used in a multi-metric index for a Turkish assessment programme.
The loss of biodiversity is recognised on a global scale and also in the anthropogenic landscapes used for agriculture, now covering almost 50% of the global terrestrial land surface. In agriculture pesticides, biologically active chemicals are deliberately distributed to control pests, disease and weeds in the cropped areas. The quantification of remaining semi-naturals structures such as field margins and hedges is a prerequisite to understand the impact of pesticides on biodiversity, since these structures represent habitats for many organisms in agricultural landscapes. The presence of organisms in these habitats and crops is required to obtain an estimate of their potential pesticide exposure. In this text I provide studies on animal groups so far not addressed in risk assessment procedures for the regulation of pesticides such as amphibians, moths and bats. For all groups it becomes apparent that they are present in agricultural landscapes and potentially coincide with pesticide applications indicating a risk. Risk quantification also requires data on the sensitivity of organisms and here data for plants, amphibians and bees are presented. Effects translating to community level were studied for herbicide, insecticide and fertiliser effects in a natural system. After three years the treatments resulted in simplified plant communities with lower species numbers and a reduction in flowering plants. This reduction of flowers is used as an example for an indirect effect and was especially obvious for the effect of an herbicide on the common buttercup. Sublethal herbicide effects for a plant translated in an impact on feeding caterpillars, indicating a reduction in food quality. Insecticide inputs realistic for field margins also reduced moth pollination of white champion flowers by 30%. These indirect effects by distortions of food web characteristics are playing a critical role to understand declines in organism groups, however so far are not accounted for in pesticide risk assessment schemes. The current intense use of pesticides in agriculture and their inherent toxicity may lead to a chemical landscape fragmentation, where populations may not be connected anymore. Source-sink dynamics are important ecological processes and as a final result not only population size but also genetic population structure might be affected. Including potential pesticide impacts as costs in a model for amphibians migrating to breeding ponds in vineyards in Rhineland-Palatinate indicated the isolation of investigated populations. A first validation by analyzing the population structure of the European common frog confirmed the model prediction for some sites. For the regulation of pesticides in Europe a risk assessment is required and for the organisms of the terrestrial habitat a multitude of guidance documents is in place or is recently developed or improved. The results of the presented research indicate that wild plants and especially their reproductive flower stage are highly sensitive and risks are underestimated. Population recovery of arthropods needs a reevaluation at landscape scale and the addition of amphibian risk assessment in regulation procedures is suggested. However, developing or adopting risk assessment procedures and test systems is a time consuming task and therefore the establishment of risk management options is a pragmatic alternative with immediate effects. Artificial wetlands in the agricultural landscape proved to be important foraging sites for bats and their creation could mitigate negative pesticide effects. The integration of direct and indirect effects in a risk assessment scheme for all organism groups addressing also landscape scale and pesticide mixtures requires a long developing time. The establishment of model landscapes where management options and integrated pest management are applied on a larger scale would allow us to study pesticide effects in a realistic scenario and to develop an approach for the agriculture of the future.
Streams are coupled with their riparian area. Emerging insects from streams can be an important prey in the riparian area. Such aquatic subsidies can cause predators to switch prey or increase predator abundances. This can impact the whole terrestrial food web. Stressors associated with agricultural land use can alter insect communities in water and on land, resulting in complex response patterns of terrestrial predators that rely on prey from both systems.
This thesis comprises studies on the impact of aquatic nsects on a terrestrial model ecosystem (Objective 1, hapter 2), the influence of agricultural land use on riparian spiders’ traits and community (Objective 2, Chapter 3), and on the impact of agricultural land use on the contribution of different prey to spider diet (Objective 3, Chapter 4).
In chapter 2, I present a study where we conducted a mesocosm experiment to examine the effects of aquatic subsidies on a simplified terrestrial food web consisting of two types of herbivores (leafhoppers and weevils), plants and predators (spiders). I focused on the prey choice of the spiders by excluding predator immigration and reproduction. In accordance with predator switching, survival of leafhoppers increased in the presence of aquatic subsidies. By contrast, the presence of aquatic subsidies indirectly reduced weevils and herbivory.
In chapter 3, I present the results on the taxonomic and trait response of riparian spider communities to gradients of agricultural stressors and environmental variables, with a particular emphasis on pesticides. To capture spiders with different traits and survival strategies, we used multiple collection methods. Spider community composition was best explained by in-stream pesticide toxicity and shading of the stream bank, a proxy for the quality of the habitat. Species richness and the number of spider individuals, as well as community ballooning ability, were negatively associated with in-stream pesticide toxicity. In contrast, mean body size and shading preference of spider communities responded strongest to shading,
whereas mean niche width (habitat preference for moisture and shading) responded strongest to other environmental variables.
In chapter 4, I describe aquatic-terrestrial predator-prey relations with gradients of agricultural stressors and environmental variables. I sampled spiders, as well as their aquatic and terrestrial prey along streams with an assumed pesticide pollution gradient and determined their stable carbon and nitrogen signals. Potential aquatic prey biomass correlated positively with an increasing aquatic prey contribution of T. montana. The contribution of aquatic prey to the diet of P. amentata showed a positive relationship with increasing toxicity in streams.
Overall, this thesis contributes to the emerging discipline of cross-ecosystem ecology and shows that aquatic-terrestrial linkages and riparian food webs can be influenced by land use related stressors. Future manipulative field studies on aquatic-terrestrial linkages are required that consider the quality of prey organisms, fostering mechanistic understanding of such crossecosystem effects. Knowledge on these linkages is important to improve understanding of consequences of anthropogenic stressors and to prevent further losses of ecosystems and their biodiversity.
Business Process Querying (BPQ) is a discipline in the field of Business Process Man- agement which helps experts to understand existing process models and accelerates the development of new ones. Its queries can fetch and merge these models, answer questions regarding the underlying process, and conduct compliance checking in return. Many languages have been deployed in this discipline but two language types are dominant: Logic-based languages use temporal logic to verify models as finite state machines whereas graph-based languages use pattern matching to retrieve subgraphs of model graphs directly. This thesis aims to map the features of both language types to features of the other to identify strengths and weaknesses. Exemplarily, the features of Computational Tree Logic (CTL) and The Diagramed Modeling Language (DMQL) are mapped to one another. CTL explores the valid state space and thus is better for behavioral querying. Lacking certain structural features and counting mechanisms it is not appropriate to query structural properties. In contrast, DMQL issues structural queries and its patterns can reconstruct any CTL formula. However, they do not always achieve exactly the same semantic: Patterns treat conditional flow as sequential flow by ignoring its conditions. As a result, retrieved mappings are invalid process execution sequences, i.e. false positives, in certain scenarios. DMQL can be used for behavioral querying if these are absent or acceptable. In conclusion, both language types have strengths and are specialized for different BPQ use cases but in certain scenarios graph-based languages can be applied to both. Integrating the evaluation of conditions would remove the need for logic-based languages in BPQ completely.
Data visualization is an effective way to explore data. It helps people to get a valuable insight of the data by placing it in a visual context. However, choosing a good chart without prior knowledge in the area is not a trivial job. Users have to manually explore all possible visualizations and decide upon ones that reflect relevant and desired trend in the data, are insightful and easy to decode, have a clear focus and appealing appearance. To address these challenges we developed a Tool for Automatic Generation of Good viSualizations using Scoring (TAG²S²). The approach tackles the problem of identifying an appropriate metric for judging visualizations as good or bad. It consists of two modules: visualization detection: given a data-set it creates a list of combination of data attributes for scoring and visualization ranking: scores each chart and decides which ones are good or bad. For the later, an utility metric of ten criteria was developed and each visualization detected in the first module is evaluated on these criteria. Only those visualizations that received enough scores are then presented to the user. Additionally to these data parameters, the tool considers user perception regarding the choice of visual encoding when selecting a visualization. To evaluate the utility of the metric and the importance of each criteria, test cases were developed, executed and the results presented.
The erosion of the closed innovation paradigm in conjunction with increasing competitive pressure has boosted the interest of both researchers and organizations in open innovation. Despite such rising interest, several companies remain reluctant to open their organizational boundaries to practice open innovation. Among the many reasons for such reservation are the pertinent complexity of transitioning toward open innovation and a lack of understanding of the procedures required for such endeavors. Hence, this thesis sets out to investigate how organizations can open their boundaries to successfully transition from closed to open innovation by analyzing the current literature on open innovation. In doing so, the transitional procedures are structured and classified into a model comprising three phases, namely unfreezing, moving, and institutionalizing of changes. Procedures of the unfreezing phase lay the foundation for a successful transition to open innovation, while procedures of the moving phase depict how the change occurs. Finally, procedures of the institutionalizing phase contribute to the sustainability of the transition by employing governance mechanisms and performance measures. Additionally, the individual procedures are characterized along with their corresponding barriers and critical success factors. As a result of this structured depiction of the transition process, a guideline is derived. This guideline includes the commonly employed actions of successful practitioners of open innovation, which may serve as a baseline for interested parties of the paradigm. With the derivation of the guideline and concise depiction of the individual transitional phases, this thesis consequently reduces the overall complexity and increases the comprehensibility of the transition and its implications for organizations.
Abstract
This bachelor thesis delivers a comprehensive overview of the topic Internet of Things (IoT). With the help of a first literature review, important characteristics, architectures, and properties have been identified. The main aim of this bachelor thesis is to determine whether the use of IoT in the transport of food, considering the compliance with the cold chain, can provide advantages for companies to reduce food waste. For this purpose, a second literature review has been carried out with food transport systems without the use, as well as with the use of IoT. Based on the literature review, it is possible at the end to determine a theoretical ‘ideal’ system for food transport in refrigerated trucks. The respective used technologies are also mentioned. The findings of several authors have shown that often significant improvements can be achieved in surveillance, transport in general, or traceability of food, and ultimately food waste can be reduced. However, benefits can also be gained using new non-IoT-based technologies. Thus, the main knowledge of this bachelor thesis is that a theoretical ‘ideal’ transport system contains a sensible combination of technologies with and without IoT. This system includes the use of a Wireless Sensor Network (WSN) for real-time food monitoring, as well as an alarm function when the temperature exceeds a maximum. Real-time monitoring with GPS coupled with a monitoring center to prevent traffic jams is another task. Smart and energy-efficient packaging, and finally the use of the new supercooling-technology, make the system significantly more efficient in reducing food waste. These highlights, that when choosing a transport system, which is as efficient and profitable as possible for food with refrigerated transport, companies need not just rely on the use of IoT. On this basis, it is advisable to combine the systems and technologies used so far with IoT in order to avoid as much food waste as possible.
The development of a game engine is considered a non-trivial problem. [3] The architecture of such simulation software must be able to manage large amounts of simulation objects in real-time while dealing with “crosscutting concerns” [3,p. 36] between subsystems. The use of object oriented paradigms to model simulation objects in class hierarchies has been reported as incompatible with constantly changing demands during game development [2, p. 9], resulting in anti-patterns and eventual, messy refactoring.[13]
Alternative architectures using data oriented paradigms revolving around object composition and aggregation have been proposed as a result. [13, 9, 1, 11]
This thesis describes the development of such an architecture with the explicit goals to be simple, inherently compatible with data oriented design, and to make reasoning about performance characteristics possible. Concepts are formally defined to help analyze the problem and evaluate results. A functional implementation of the architecture is presented together with use cases common to simulation software.
Deformable Snow Rendering
(2019)
Accurate snow simulation is key to capture snow's iconic visuals. Intricate
methods exist that attempt to grasp snow behaviour in a holistic manner. Computational complexity prevents them from reaching real-time performance. This thesis presents three techniques making use of the GPU that focus on the deformation of a snow surface in real-time. The approaches are examined by their ability to scale with an increasing number of deformation actors and their visual portrayal of snow deformation. The findings indicate that the approaches maintain real-time performance well into several hundred individual deformation actors. However, these approaches each have their individual restrictions handicapping the visual results. An experimental approach is to combine the techniques at reduced deformation actor count to benefit from the detailed, merged deformation pattern.
With the appearance of modern virtual reality (VR) headsets on the consumer market, there has been the biggest boom in the history of VR technology. Naturally, this was accompanied by an increasing focus on the problems of current VR hardware. Especially the control in VR has always been a complex topic.
One possible solution is the Leap Motion, a hand tracking device that was initially developed for desktop use, but with the last major software update it can be attached to standard VR headsets. This device allows very precise tracking of the user’s hands and fingers and their replication in the virtual world.
The aim of this work is to design virtual user interfaces that can be operated with the Leap Motion to provide a natural method of interaction between the user and the VR environment. After that, subject tests are performed to evaluate their performance and compare them to traditional VR controllers.
Groundwater is essential for the provision of drinking water in many areas around the world. The ecosystem services provided by groundwater-related organisms are crucial for the quality of groundwater-bearing aquifers. Therefore, if remediation of contaminated groundwater is necessary, the remediation method has to be carefully selected to avoid risk-risk trade-offs that might impact these valuable ecosystems. In the present thesis, the ecotoxicity of the in situ remediation agent Carbo-Iron (a composite of zero valent nano-iron and active carbon) was investigated, an estimation of its environmental risk was performed, and the risk and benefit of a groundwater remediation with Carbo-Iron were comprehensively analysed.
At the beginning of the work on the present thesis, a sound assessment of the environmental risks of nanomaterials was impeded by a lack of guidance documents, resulting in many uncertainties on selection of suitable test methods and a low comparability of test results from different studies with similar nanomaterials. The reasons for the low comparability were based on methodological aspects of the testing procedures before and during the toxicity testing. Therefore, decision trees were developed as a tool to systematically decide on ecotoxicity test procedures for nanomaterials. Potential effects of Carbo-Iron on embryonic, juvenile and adult life stages of zebrafish (Danio rerio) and the amphipod Hyalella azteca were investigated in acute and chronic tests. These tests were based on existing OECD and EPA test guidelines (OECD, 1992a, 2013a, 2013b; US EPA, 2000) to facilitate the use of the obtained effect data in the risk assessment. Additionally, the uptake of particles into the test organisms was investigated using microscopic methods. In zebrafish embryos, effects of Carbo-Iron on gene expression were investigated. The obtained ecotoxicity data were complemented by studies with the waterflea Daphnia magna, the algae Scenedesmus vacuolatus, larvae of the insect species Chironomus riparius and nitrifying soil microorganisms.
In the fish embryo test, no passage of Carbo-Iron particles into the perivitelline space or the embryo was observed. In D. rerio and H. azteca, Carbo-Iron was detected in the gut at the end of exposure, but no passage into the surrounding tissue was detected. Carbo-Iron had no significant effect on soil microorganisms and on survival and growth of fish. However, it had significant effects on the growth, feeding rate and reproduction of H. azteca and on survival and reproduction in D. magna. Additionally, the development rate of C. riparius and the cell volume of S. vacuolatus were negatively influenced.
A predicted no effect concentration of 0.1 mg/L was derived from the ecotoxicity studies based on the no-effect level determined in the reproduction test with D. magna and an assessment factor of 10. It was compared to measured and modelled environmental concentrations for Carbo-Iron after application to an aquifer contaminated with chlorohydrocarbons in a field study. Based on these concentrations, risk quotients were derived. Additionally, the overall environmental risk before and after Carbo-Iron application was assessed to verify whether the chances for a risk-risk trade-off by the remediation of the contaminated site could be minimized. With the data used in the present study, a reduced environmental risk was identified after the application of Carbo-Iron. Thus, the benefit of remediation with Carbo-Iron outweighs potential negative effects on the environment.
Despite the inception of new technologies at a breakneck pace, many analytics projects fail mainly due to the use of incompatible development methodologies. As big data analytics projects are different from software development projects, the methodologies used in software development projects could not be applied in the same fashion to analytics projects. The traditional agile project management approaches to the projects do not consider the complexities involved in the analytics. In this thesis, the challenges involved in generalizing the application of agile methodologies will be evaluated, and some suitable agile frameworks which are more compatible with the analytics project will be explored and recommended. The standard practices and approaches which are currently applied in the industry for analytics projects will be discussed concerning enablers and success factors for agile adaption. In the end, after the comprehensive discussion and analysis of the problem and complexities, a framework will be recommended that copes best with the discussed challenges and complexities and is generally well suited for the most data-intensive analytics projects.
The Internet of Things (IoT) is a fast-growing, technological concept, which aims to integrate various physical and virtual objects into a global network to enable interaction and communication between those objects (Atzori, Iera and Morabito, 2010). The application possibilities are manifold and may transform society and economy similarly to the usage of the internet (Chase, 2013). Furthermore, the Internet of Things occupies a central role for the realisation of visionary future concepts, for example, Smart City or Smart Healthcare. In addition, the utilisation of this technology promises opportunities for the enhancement of various sustainability aspects, and thus for the transformation to a smarter, more efficient and more conscious dealing with natural resources (Maksimovic, 2017). The action principle of sustainability increasingly gains attention in the societal and academical discourse. This is reasoned by the partly harmful consumption and production patterns of the last century (Mcwilliams et al., 2016). Relating to sustainability, the advancing application of IoT technology also poses risks. Following the precautionary principle, these risks should be considered early (Harremoës et al., 2001). Risks of IoT for sustainability include the massive amounts of energy and raw materials which are required for the manufacturing and operation of IoT objects and furthermore, the disposal of those objects (Birkel et al., 2019). The exact relations in the context of IoT and sustainability are insufficiently explored to this point and do not constitute a central element within the discussion of this technology (Behrendt, 2019). Therefore, this thesis aims to develop a comprehensive overview of the relations between IoT and sustainability.
To achieve this aim, this thesis utilises the methodology of Grounded Theory in combination with a comprehensive literature review. The analysed literature primarily consists of research contributions in the field of Information Technology (IT). Based on this literature, aspects, solution approaches, effects and challenges in the context of IoT and sustainability were elaborated. The analysis revealed two central perspectives in this context. IoT for Sustainability (IoT4Sus) describes the utilisation and usage of IoT-generated information to enhance sustainability aspects. In contrast, Sustainability for IoT (Sus4IoT) fo-cuses on sustainability aspects of the applied technology and highlights methods to reduce negative impacts, which are associated with the manufacturing and operation of IoT. Elaborated aspects and relations were illustrated in the comprehensive CCIS Framework. This framework represents a tool for the capturing of relevant aspects and relations in this context and thus supports the awareness of the link between IoT and sustainability. Furthermore, the framework suggests an action principle to optimise the performance of IoT systems regarding sustainability.
The central contribution of this thesis is represented by the providence of the CCIS Framework and the contained information regarding the aspects and relations of IoT and sustainability.
Sediment transport contributes to the movement of inorganic and organic material in rivers. The construction of a dam interrupts the continuity of this sediment transport through rivers, causing sediments to accumulate within the reservoir. Reservoirs can also act as carbon sinks and methane can be released when organic matter in the sediment is degraded under anoxic conditions. Reservoir sedimentation poses a great threat to the sustainability of reservoirs worldwide, and can emit the potent greenhouse gas methane into the atmosphere. Sediment management measures to rehabilitate silted reservoirs are required to achieve both better water quantity and quality, as well as to mitigate greenhouse gas emissions.
This thesis aims at the improvement of sediment sampling techniques to characterize sediment deposits as a basis for accurate and efficient water jet dredging and to monitor the dredging efficiency by measuring the sediment concentration. To achieve this, we investigated freeze coring as a method to sample (gas-bearing) sediment in situ. The freeze cores from three reservoirs obtained were scanned using a non-destructive X-Ray CT scan technique. This allows the determination of sediment stratification and character-ization of gas bubbles to quantify methane emissions and serve as a basis for the identi-fication of specific (i.e. contaminated) sediment layers to be dredged. The results demon-strate the capability of freeze coring as a method for the characterization of (gas-bearing) sediment and overcomes certain limitations of commonly used gravity cores. Even though the core’s structure showed coring disturbances related to the freezing process, the general core integrity seems to not have been disturbed. For dredging purposes, we analyzed the impact pressure distribution and spray pattern of submerged cavitating wa-ter jets and determined the effects of impinging distances and angles, pump pressures and spray angles. We used an adapted Pressure Measurement Sensing technique to enhance the spatial distribution, which proved to be a comparatively easy-to-use meas-urement method for an improved understanding of the governing factors on the erosional capacity of cavitating water jets. Based on this data, the multiple linear regression model can be used to predict the impact pressure distribution of those water jets to achieve higher dredging accuracy and efficiency. To determine the dredging operational efficien-cy, we developed a semi-continuous automated measurement device to measure the sediment concentration of the slurry. This simple and robust device has lower costs, compared to traditional and surrogate sediment concentration measurement technolo-gies, and can be monitored and controlled remotely under a wide range of concentrations and grain-sizes, unaffected by entrained gas bubbles
In this work the Navier-Stokes equations for non-stationary incompressible
flow of the Newtonian fluid in time dependent domain are studied. The geometry of the flow domain changes in time according to fluid properties such as stress tensor. The motivation for our study comes from medicine—the simulation of blood flow in arteries and veins.
After choosing an appropriate mathematical model of the flow in a domain with viscoelastic compliant walls, we deal with its theoretical analysis. We prove the existence of a weak solution using the weak compressible approximation in a moving domain with given deformation function. In our approach the fluid-structure interface condition is treated using a permeable-wall approach decoupling the fluid and the deformable structure.
Finally we present some numerical experiments illustrating the convergence of the iteration with respect to the domain deformation function as well as the behavior of the moving wall for decreased permeability.
Willingness to pay and willingness to accept on a two-sided platform - The use case of DoBeeDo
(2019)
It is widely known that especially for technology-based start-ups, entrepreneurs need to set up the boundaries of the business and define the product/service to offer in order to minimize the risk of failure. The goal of this thesis is to not only emphasize the importance of the business model development and evaluation but also show an example customer validation process for an emerging start-up named DoBeeDo, which is a mobile app operating on a two-sided market. During the process of customer validation a survey has been conducted to evaluate the interest of the target groups as well as the fit of their expectations using the Willingness to Pay and Willingness to Accept measures. The paper includes an analysis and evaluation of the gathered results and assesses whether the execution of the Customer Development Model can be continued.
The status of Business Process Management (BPM) recommender systems is not quite clear as research states. The use of recommenders familiarized itself with the world during the rise of technological evolution in the past decade.Ever since then, several BPM recommender systems came about. However, not a lot of research is conducted in this field. It is not well known to what broad are the technologies used and how are they used. Moreover, this master’s thesis aims at surveying the BPM recommender systems existing. Building on this, the recommendations come in different shapes. They can be positionbased where an element is to be placed at an element’s front, back or to autocomplete a missing link. On the other hand, Recommendations can be textual, to fill the labels of the elements. Furthermore, the literature review for BPM recommender systems took place under the guides of a literature review framework. The framework suggests 5stages of consecutive stages for this sake. The first stage is defining a scope for the research. Secondly, conceptualizing the topic by choosing key terms for literature research. After that in the third stage, comes the research stage.As for the fourth stage, it suggests choosing analysis features over which the literature is to be synthesized and compared. Finally, it recommends defining the research agenda to describe the reason for the literature review. By invoking the mentioned methodology, this master’s thesis surveyed 18 BPM recommender systems. It was found as a result of the survey that there
are not many different technologies for implementing the recommenders. It was also found that the majority of the recommenders suggest nodes that are yet to come in the model, which is called forward recommending. Also, one of the results of the survey indicated the scarce use of textual recommendations to BPM labels. Finally, 18 recommenders are considered less than excepted for a developing field therefore as a result, the survey found a shortage in the number of BPM recommender systems. The results indicate several shortages in several aspects in the field of BPM recommender systems. On this basis, this master’s thesis recommends the future work on it the results.
While the existing literature on cooperative R&D projects between firms and public research institutes (PRI) has made valuable contributions by examining various factors and their influence on different outcome measures, there has been no investigation of cooperative R&D project success between firms and PRI from a product competitive advantage perspective. However, insights into the development of a meaningful and superior product (i.e., product competitive advantage) are particularly important in the context of cooperative R&D projects between PRI and (mainly small and medium-sized) firms in the biotechnology industry in response to increasing competition to raise capital funds necessary for survival.
The objectives of this thesis are: (1) to elaborate the theoretical foundations which explain the achievement of a product competitive advantage in cooperative R&D projects between biotechnology firms and PRI, (2) to identify and empirically evaluate the determining factors for achieving a product competitive advantage in cooperative R&D projects between biotechnology firms and PRI, and (3) to show how cooperative R&D projects between biotechnology firms and PRI should be designed and executed to support the achievement of a product competitive advantage.
To accomplish these objectives, a model of determinants of product competitive advantage in cooperative R&D projects between biotechnology firms and PRI is developed by drawing from the theoretical foundations of resource-based theory and information-processing theory. The model is evaluated using data from 517 questionnaires on cooperative R&D projects between at least one biotechnology firm and one PRI. The data are analyzed using variance-based structural equation modeling (i.e., PLS-SEM) in order to conduct hypotheses testing. The evaluation of the empirical data includes an additional mediation analysis and the comparison of effects in subsamples.
The results demonstrate the importance of available resources and skills, as well as the proficient execution of marketing-related and technical activities for the achievement of a product competitive advantage in cooperative R&D projects between biotechnology firms and PRI. By identifying project-related and process-related factors affecting product competitive advantage and empirically testing their relationships, the research findings should be valuable for both researchers and practitioners. After discussing contributions and implications for research and practice, the present thesis concludes with limitations and avenues for future research.
Carabids, which are frequently distributed in agricultural landscapes, are natural enemies of different pests including slugs. Semi-natural habitats are known to affect carabids and thus, their potential to support natural pest control.
The impact of semi-natural habitats was investigated on carabids and slugs within different non-crop habitats (chapter 2). Most carabids and Deroceras reticulatum showed preferences for herbaceous semi-natural habitats, while Arion spp. occured mainly in woody habitats. An increase of predatory carabid abundance, which was linked to an inclining amount of semi-natural habitats in the landscape, and a decrease of Arion spp. densities, indicated a high potential for slug control in structural rich landscapes.
Effects of semi-natural habitats were investigated on predatory carabids and slugs in 18 wheat fields (chapter 3). Predatory carabid species richness was positively affected by the increasing amount of semi-natural habitats in the landscape, whereas predatory carabid abundance was neither influenced by adjacent habitat type nor by the proportion of semi-natural habitats in the landscape. The target pest species showed divergent patterns, whereas Arion spp. densities were highest in structural poor landscapes near woody margins. D. reticulatum was not affected by habitat type or landscape, reflecting its adaptation to agriculture. Results indicate an increased control of Arion spp. by carabids in landscapes with a high amount of semi-natural habitats.
Effects of semi-natural habitats and the influence of farming system was tested on carabid distribution within 18 pumpkin fields (chapter 4). Carabid species richness generally increased with decreasing distance to the field margins, whereas carabid abundance responded differently according to the adjacent habitat type. Farming system had no effect on carabids and landscape heterogeneity only affected carabids in organic pumpkin fields.
Slug and slug egg predation of three common carabid species was tested in single and double species treatments in the laboratory (chapter 5). Results show additive and synergistic effects depending on the carabid species. In general, semi-natural habitats can enhance the potential of slug control by carabids. This counts especially for Arionid slugs. Semi-natural habitats can support carabid communities by providing shelter, oviposition and overwintering sites as wells as complementary food sources. Therefore, it is important to provide a certain amount of non-crop habitats in agricultural landscapes.
Previous research revealed that teachers hold beliefs about gifted students combining high intellectual ability with deficits in non-cognitive domains, outlined in the so-called disharmony hypothesis. Since teachers’ beliefs about giftedness can influence which students they identify as gifted, the empirical investigation of beliefs is of great practical relevance. This dissertation comprises three research articles that investigated teacher beliefs about gifted students’ characteristics in samples of pre-service teachers using an experimental vignette approach. Chapter I starts with a general introduction into beliefs, and presents the research aims of the present dissertation. The first article (Chapter II) focused on the interaction of beliefs about giftedness and gender in a sample of Australian pre-service teachers and tested if social desirability occurred when using the vignette design. Beside evidence for beliefs in line with the disharmony hypothesis, results revealed typical gender stereotypes. However, beliefs about giftedness appeared not to be gender specific and thus, to be similar for gifted girls and boys. The vignette approach was found to be an adequate design for assessing teacher beliefs. The second article (Chapter III) investigated teacher beliefs and their relationship to motivational orientations for teaching gifted students in a cross-country sample of German and Australian pre-service teachers. Motivational orientations comprise cognitive components (self-efficacy) and affective components (enthusiasm). Findings revealed beliefs in the sense of the disharmony hypothesis for pre-service teachers from both countries. Giftedness when paired with beliefs about high maladjustment was found to be negatively related to teachers’ self-efficacy for teaching gifted students. The third article (Chapter IV) examined the role of teachers’ belief in a just world for the formation of beliefs using a sample of Belgian pre-service teachers. It was found that the stronger pre-service teachers’ belief in a just world was, the more they perceived gifted students’ high intellectual ability as unfair and thus, neutralized that injustice by de-evaluating students’ non-cognitive abilities. In a general discussion (Chapter V), findings of the three articles are combined and reflected. Taken together, the present dissertation showed that teacher beliefs about gifted students’ characteristics are not gender specific, generalizable over countries, negatively related to teacher motivation and can be driven by fairness beliefs.
Grapevine growers have struggled with defending their crops against pests and diseases since the domestication of grapevine over 6000 ears ago. Since then, new growing methods paired with a better nderstanding of the ecological processes in the vineyard ecosystem continue to improve quality and quantity of grape harvests. In this thesis I am describing the effects of two recent innovations in viticulture on pest and beneficial arthropods in vineyards; Fungus-resistant grapevine cultivars (PIWIs) and the pruning system semi-minimal pruned hedge (SMPH). The SMPH pruning system allows for a drastic reduction of manual labor in the vineyard, and PIWIs are resistant to two of the most common fungal diseases of grapevine and therefore allow a drastic reduction of fungicide applications compared to conventional varieties. Heavy use of pesticides is linked to a number of problems, including pollution of waterways, negative effects on human health, and biodiversity loss. Here, I studied the effects of fungicide reduction and minimal pruning on arthropods that are beneficial for natural pest suppression in the vineyard ecosystem such as predatory mites, spiders, ants, earwigs, and lacewings. All of these groups either benefitted from the reduction of fungicide sprayings or were not significantly affected. Structural changes in the canopy of SMPH grapevines altered the microclimate in the canopy which in turn influenced some of the arthropods living in it. Overall, my findings suggest that PIWIs and SMPH, both in combination or separately, improve conditions for natural pest control. This adds to other advantages of these innovative management practices such as a reduction in production cost and a smaller impact on the environment.
Tracking is an integral part of many modern applications, especially in areas like autonomous systems and Augmented Reality. For performing tracking there are a wide array of approaches. One that has become a subject of research just recently is the utilization of Neural Networks. In the scope of this master thesis an application will be developed which uses such a Neural Network for the tracking process. This also requires the creation of training data as well as the creation and training of a Neural Network. Subsequently the usage of Neural Networks for tracking will be analyzed and evaluated. This includes several aspects. The quality of the tracking for different degrees of freedom will be checked as well as the the impact of the Neural Network on the applications performance. Additionally the amount of required training data is investigated, the influence of the network architecture and the importance of providing depth data as part of the networks input. This should provide an insight into how relevant this approach could be for its adoption in future products.
Invasive species often have a significant impact on the biodiversity of ecosystems and the species native to it. One of the worst invaders worldwide is Aphanomyces astaci, the causative agent of the crayfish plague, an often fatal disease to crayfish species not native to North America. Aphanomyces astaci originates from North America and was introduced to Europe in the midst of the 19th century. Since then, it spread throughout Europe diminishing the European crayfish populations. The overall aim of this thesis was to evaluate the threat that A. astaci still poses to European crayfish species more than 150 years after its introduction to Europe. In the first part of the thesis, crayfish specimens, which are available in the German pet trade, were tested for infections with A. astaci. Around 13% of the tested crayfish were clearly infected with A. astaci. The study demonstrated the potential danger the pet trade poses for biodiversity through the import of alien species and their potential pathogens, in general. In the second part of the thesis, the A. astaci infection prevalence of crayfish species in wild populations in Europe was tested. While the stone crayfish, Austropotamobius torrentium, showed high susceptibility to different haplogroups of A. astaci, the narrow-clawed crayfish, Astacus leptodactylus, was able to survive infections, even by haplogroup B, which is considered to be highly virulent. In the last part of the thesis, A. astaci was traced back to its original distribution area of North America. While the crayfish plague never had such a devastating effect on crayfish in North America as it had in Europe, the reasons for the success of invasive crayfish within North America are not yet fully understood. It is possible that A. astaci increases the invasion success of some crayfish species. Several populations of the rusty crayfish, Orconectes rusticus, in the Midwest of North America were confirmed to be infected with A. astaci and a new genotype was identified, possibly indicating that each crayfish host is vector of a unique A. astaci genotype, even in North America. Overall, the present thesis provides evidence that A. astaci is still a major threat to the crayfish species indigenous to Europe. Crayfish mass mortalities still occur in susceptible crayfish species like A. torrentium even 150 years after the first introduction of A. astaci. While there are some indications for increased resistances through processes of co-evolution, the continuous introduction of crayfish species to Europe threatens to cause new outbreaks of the crayfish plague through the parallel introduction of new, highly virulent A. astaci strains.
Business rules have become an important tool to warrant compliance at their business processes. But the collection of these business rules can have various conflicting elements. This can lead to a violation of the compliance to be achieved. This conflicting elements are therefore a kind of inconsistencies, or quasi incon- sistencies in the business rule base. The target for this thesis is to investigate how those quasi inconsistencies in business rules can be detected and analyzed. To this aim, we develop a comprehensive library which allows to apply results from the scientific field of inconsistency measurement to business rule formalisms that are actually used in practice.
Most social media platforms allow users to freely express their opinions, feelings, and beliefs. However, in recent years the growing propagation of hate speech, offensive language, racism and sexism on the social media outlets have drawn attention from individuals, companies, and researchers. Today, sexism both online and offline with different forms, including blatant, covert, and subtle lan- guage, is a common phenomenon in society. A notable amount of work has been done over identifying sexist content and computationally detecting sexism which exists online. Although previous efforts have mostly used peoples’ activities on social media platforms such as Twitter as a public and helpful source for collecting data, they neglect the fact that the method of gathering sexist tweets could be biased towards the initial search terms. Moreover, some forms of sexism could be missed since some tweets which contain offensive language could be misclassified as hate speech. Further, in existing hate speech corpora, sexist tweets mostly express hostile sexism, and to some degree, the other forms of sexism which also appear online was disregarded. Besides, the creation of labeled datasets with manual exertion, relying on users to report offensive comments with a tremendous effort by human annotators is not only a costly and time-consuming process, but it also raises the risk of involving discrimination under biased judgment.
This thesis generates a novel sexist and non-sexist dataset which is constructed via "UnSexistifyIt", an online web-based game that incentivizes the players to make minimal modifications to a sexist statement with the goal of turning it into a non-sexist statement and convincing other players that the modified statement is non-sexist. The game applies the methodology of "Game With A Purpose" to generate data as a side-effect of playing the game and also employs the gamification and crowdsourcing techniques to enhance non-game contexts. When voluntary participants play the game, they help to produce non-sexist statements which can reduce the cost of generating new corpus. This work explores how diverse individual beliefs concerning sexism are. Further, the result of this work highlights the impact of various linguistic features and content attributes regarding sexist language detection. Finally, this thesis could help to expand our understanding regarding the syntactic and semantic structure of sexist and non-sexist content and also provides insights to build a probabilistic classifier for single sentences into sexist or non-sexist classes and lastly find a potential ground truth for such a classifier.
The goal of this thesis is to create a recommender system (RS) for business processes, based on the existing ProM plugin RegPFA. To accomplish this task, firstly an interface must be created that sets up and expands a database receiving probabilistic finite automata (PFA) created by RegPFA in tsml format as input. Secondly, a Java program must be designed that uses said database to recommend the process elements that are most likely to follow a given sequence of process elements.
Student misbehavior and its treatment is a major challenge for teachers and a threat to their well-being. Indeed, teachers are obliged to punish student misbehavior on a regular basis. Additionally, teachers’ punishment decisions are among the most frequently reported situations when it comes to students’ experiences of injustice in school. By implication, it is crucial to understand teachers’ treatment of student misbehavior vis-à-vis students’ perceptions. One key dimension of punishment behavior reflects its underlying motivation and goals. People generally intend to achieve three goals when punishing misbehavior, namely, retribution (i.e., evening out the harm caused), special prevention (i.e., preventing recidivism of the offender), and general prevention (i.e., preventing imitation of others). Importantly, people’s support of these punishment goals is subject to hierarchy and power, implying that teachers’ and students’ punishment goal preferences differ. In this dissertation, I present three research projects that shed first light on teachers’ punishment and its goals along with the students’ perception of classroom intervention strategies pursuing these goals. More specifically, I first examined students’ (i.e., children’s) general support of each of the three punishment goals sketched above. Furthermore, I applied an attributional approach to understand and study the goals teachers intend to achieve when punishing student misbehavior. Finally, I investigated teachers’ and students’ support of the punishment goals regarding the same student misbehavior to directly compare their views on these goals and reactions pursuing them. In sum, the findings show that students generally prefer retribution and special prevention to general prevention, whereas teachers prefer general prevention and special prevention to retribution. This ultimately translates into a "mismatch" of teachers and students in their preferences for specific punishment goals, and the findings suggest that this may indeed enhance students’ perception of injustice. Overall, the results of the present research program may be valuable for the development of classroom intervention strategies that may reduce rather than enhance conflicts in student-teacher-interactions.
This work describes a novel software tool for visualizing anatomical segmentations of medical images. It was developed as part of a bachelor's thesis project, with a view to supporting research into automatic anatomical brain image segmentation. The tool builds on a widely-used visualization approach for 3D image volumes, where sections in orthogonal directions are rendered on screen as 2D images. It implements novel display modes that solve common problems with conventional viewer programs. In particular, it features a double-contour display mode to aid the user's spatial orientation in the image, as well as modes for comparing two competing segmentation labels pertaining to one and the same anatomical region. The tool was developed as an extension to an existing open-source software suite for medical image processing. The visualization modes are, however, suitable for implementation in the context of other viewer programs that follow a similar rendering approach.
The modified code can be found here: soundray.org/mm-segmentation-visualization.tar.gz.
Our work finds the fine grained edits in context of neighbouring tokens in Wikipedia articles. We cluster those edits according to similar neighbouring context. We encode neighbouring context into vector space using word vectors. We evaluate clusters returned by our algorithm on extrinsic and intrinsic metric and compare it with previous work. We analyse the relation between extrinsic and intrinsic measurements of fine grained edit tokens.
Engineering criminal agents
(2019)
This PhD thesis with the title "Engineering Criminal Agents" demonstrates the interplay of three different research fields captured in the title: In the centre are Engineering and Simulation, both set in relation with the application field of Criminology - and the social science aspect of the latter. More precisely,
this work intends to show how specific agent-based simulation models can be created using common methods from software engineering.
Agent-based simulation has proven to be a valuable method for social science since decades, and the trend to increasingly complex simulation models is apparent, not at least due to advancing computational and simulation techniques. An important cause of complexity is the inclusion of 'evidence' as basis of simulation models. Evidence can be provided by various stakeholders, reflecting their different viewpoints on the topic to model.
This poses a particular burden by interrelating the two relevant perspectives on the topic of simulation: on the one hand the user of the simulation model who provides the requirements and is interested in the simulation results, on the other hand the developer of the simulation model who has to program a verified and validated formal model. In order to methodically link these two perspectives, substantial efforts in research and development are needed, where this PhD thesis aims to make a contribution.
The practical results - in terms of software - were achieved by using the multi-faceted approach mentioned above: using methods from software engineering, in order to become able to apply methods from computational social sciences, in order to gain insights into social systems, such as in the internal dynamics of criminal networks.
The PhD thesis shows the research involved to create these practical results, and gives technical details and specifications of the developed software.
The frame for research and development to achieve these results was provided mainly by two research projects: OCOPOMO and GLODERS.
Over the past few decades society’s dependence on software systems has grown significantly. These systems are utilized in nearly every matter of life today and often handle sensitive, private data. This situation has turned software security analysis into an essential and widely researched topic in the field of computer science. Researchers in this field tend to make the assumption that the quality of the software systems' code directly affects the possibility for security gaps to arise in it. Because this assumption is based on properties of the code, proving it true would mean that security assessments can be performed on software, even before a certain version of it is released. A study based on this implication has already attempted to mathematically assess the existence of such a correlation, studying it based on quality and security metric calculations. The present study builds upon that study in finding an automatic method for choosing well-fitted software projects as a sample for this correlation analysis and extends the variety of projects considered for the it. In this thesis, the automatic generation of graphical representations both for the correlations between the metrics as well as for their evolution is also introduced. With these improvements, this thesis verifies the results of the previous study with a different and broader project input. It also focuses on analyzing the correlations between the quality and security metrics to real-world vulnerability data metrics. The data is extracted and evaluated from dedicated software vulnerability information sources and serves to represent the existence of proven security weaknesses in the studied software. The study discusses some of the difficulties that arise when trying to gather such information and link it to the difference in the information contained in the repositories of the studied projects. This thesis confirms the significant influence that quality metrics have on each other. It also shows that it is important to view them together as a whole and suppose that their correlation could influence the appearance of unwanted vulnerabilities as well. One of the important conclusions I can draw from this thesis is that the visualization of metric evolution graphs, helps the understanding of the values as well as their connection to each other in a more meaningful way. It allows for better grasp of their influence on each other as opposed to only studying their correlation values. This study confirms that studying metric correlations and evolution trends can help developers improve their projects and prevent them from becoming difficult to extend and maintain, increasing the potential for good quality as well as more secure software code.
The mitral valve is one of four human heart valves. It is located in the left heart and acts as a unidirectional passageway for blood between the left atrium and the left ventricle. A correctly functioning mitral valve prevents a backflow of blood into the pulmonary circulation (lungs) and thus constitutes a vital part of the cardiac cycle. Pathologies of the mitral valve can manifest in a variety of symptoms with severity ranging from chest pain and fatigue to pulmonary edema (fluid accumulation in the tissue and air space of lungs), which may ultimately cause respiratory failure.
Malfunctioning mitral valves can be restored through complex surgical interventions, which greatly benefit from intensive planning and pre-operative analysis. Visualization techniques provide a possibility to enhance such preparation processes and can also facilitate post-operative evaluation. The work at hand extends current research in this field, building upon patient-specific mitral valve segmentations developed at the German Cancer Research Center, which result in triangulated 3D models of the valve surface. The core of this work will be the construction of a 2D-view of these models through global parameterization, a method that can be used to establish a bijective mapping between a planar parameter domain and a surface embedded in higher dimensions.
A flat representation of the mitral valve provides physicians with a view of the whole surface at once, similar to a map. This allows assessment of the valve's area and shape without the need for different viewing angles. Parts of the valve that are occluded by geometry in 3D become visible in 2D.
An additional contribution of this work will be the exploration of different visualizations of the 3D and 2D mitral valve representations. Features of the valve can be highlighted by associating them with specified colors, which can for instance directly convey pathology indicators.
Quality and effectiveness of the proposed methods were evaluated through a survey conducted at the Heidelberg University Hospital.
Nanotemplates for the combined structural and functional analysis of membrane-associated proteins
(2019)
Plasma membranes are essential for life because they give cells an identity. Plasma membranes are almost impermeable to fluids and substances. Still, transport between inside and outside needs to be possible. An important transport way is endocytosis. This mechanism relies on membrane-associated proteins that sense and induce curvature to the plasma membrane. However, the physics and structural dynamics behind proteins acting on membranes is not well understood. There is a standard method in vitro to investigate membrane-associated proteins sensing spherical geometries: They are incubated on unilamellar vesicles. This procedure allows to analyze these proteins in their bound state. This approach is inappropriate for GRAF1 (GTPase Regulator Associated with Focal Adhesion Kinase-1), a key player in endocytosis because it senses tubular geometries instead. However, GRAF1 extrudes lipid tubes from vesicles that can be analyzed. Still, this is a limited method because these tubes suffer from inhomogeneity and they do not enable the observation of intermediate and lower concentration binding states. To overcome this issue they can be incubated on pre-tubular structures called nanotemplates. There have been studies using carbon nanotubes and Galactosylceramide lipid tubes as nanotemplates. These approaches require complex chemical modifications or expensive components and they are not necessarily flexible. In this work we present a simple and easy new approach to prepare nanotemplates using Folch lipid mixture. We show on the basis of BPG, a truncate of GRAF1, that our nanotemplates are suitable for Cryo-EM and that it is possible to use IHRSR (Iterative Helical Real Space Reconstruction) to analyze the structure of BPG in its bound state. Moreover, the qualification for Cryo-EM allows to use plunge freezing to interrupt the incubation on our nanotemplates abruptly. This enables the analysis of intermediate binding states to understand the binding process.
In this thesis, I present the results of my studies on taxonomy, systematics, and biogeography of Impatiens (Balsaminaceae) in Madagascar and the Comoro islands.
In Chapter 1 I reviewed the literature on taxonomy and classification of Balsaminaceae, on habitat, world distribution, morphology, molecular phylogenetics and infrageneric classification of the genus Impatiens. In Chapters 2-15 (Fischer & Rahelivololona 2002, 2003, 2004, 2007, 2015a, 2015b, 2015c, 2016, Fischer et al. 2004. 2017, 2018a, b submitted, Rahelivololona et al. 2003) I presented the first results of a revision of Balsaminaceae of Madagascar and the Comoro islands including the description of 78 new species. In Chapter 16 (Yuan et al. 2004) we worked on the phylogeny and biogeography of Balsaminaceae inferred from ITS sequences using combined results from molecular phylogenetic and morphological analyses. In Chapter 17 (Rahelivololona et al. 2018) we conducted a phylogeny and assessment of the infrageneric classification of species in the Malagasy Impatiens (Balsaminaceae) with a particular emphasis on taxa collected from Marojejy.
Below I summarise the most important findings of each chapter and provide an outlook for future studies.
How many species of Impatiens occur in Madagascar and the Comoro islands?
To provide additional information on the taxonomic revision of Impatiens in Madagascar and the Comoro islands, the identification of already described species as well as the description of new species was conducted. Based on herbarium specimens from BR, G, K, NEU, P, TAN and on living plants collected during several field trips, 78 new species and 6 nomina nova have been published and another 70 new taxa are already identified. Actually more than 260 species occur in Madagascar and the Comoro islands and all of them are endemic. For each species, a description of the morphology, phenology, ecology and known distribution range was provided. Apart from new taxa, the delimitation of already described species like Impatiens firmula Baker and Impatiens hildebrandtii Baill. could be clarified by studying the types and by observing the variability in the field.
Are the groups of Impatiens in Madagascar monophyletic, and what is the systematic position of Trimorphopetalum?
Yuan & al. (2004) conducted a molecular phylogenetic study to examine the morphological and karyological evolution, and the historical biogeography of the Balsaminaceae family by using nucleotide sequence data of internal transcribed spacer regions of nuclear ribosomal DNA. The results support the monophyly of the Malagasy endemic section Trimorphopetalum and show that the cleistogamous Impatiens inaperta should be included in the sect. Trimorphopetalum which is the most derived within Impatiens. Therefore, the section Preimpatiens proposed by Perrier de la Bâthie (1934) is paraphyletic.
Rahelivololona & al. (2018) provided a phylogenetic study focused on three subdivisions (based on macromorphological characters) proposed by Perrier de la Bâthie (1934). The analysis was done using two nuclear AP3/DEF homologues (ImpDEF1 and ImpDEF2) and the plastid atpB-rbcL spacer to reassess or assess the monophyly of the Malagasy Impatiens, of the sections Preimpatiens (Humblotianae and Vulgare groups) and Trimorphopetalum. A focus was on the species of Impatiens from the Marojejy National Park and of the morphologically variable species I. elatostemmoides, I. “hammarbyoides”, I. inaperta and I. manaharensis, using monophyly as the primary criterion.
As results the Malagasy Impatiens are paraphyletic and the section Preimpatiens sensu Perrier de la Bâthie (1934) (= subgen. Impatiens sensu Fischer & Rahelivololona 2002) was not resolved as a monophyletic group. The section Trimorphopetalum sensu Perrier de la Bâthie (1934) (= subgen. Trimorphopetalum sensu Fischer & Rahelivololona 2002), however, was strongly confirmed as a monophyletic lineage (BS: 92; BPP: 1). Neither the Humblotianae group nor the Vulgare group was supported as monophyletic. None of the morphologically variable species appeared to be monophyletic and the sampled species of Impatiens from the Marojejy National Park do also not form a monophyletic group.
What are the biogeographical position and the distribution patterns of Impatiens in Madagascar and the Comoro islands?
Investigation of the geographical affinities and species distribution of section Impatiens (including Humblotianae group and Vulgare group) and section Trimorphopetalum were conducted and the origin and evolution as well as species richness and endemism were discussed.
The isolation, the climate and the complex topography of Madagascar have generated the microhabitats and ecological niches favourable to the diversification of Impatiens species. Impatiens of Madagascar with 260 endemic species is actually the largest genus in Madagascar. Therefore, Madagascar and the Comoro islands are among the most species-rich regions in the world for Impatiens.
Future studies
In Impatiens on Madagascar, there remain numerous unresolved questions that need to be adressed:
• A further study based on a much larger molecular data set and sampling from the entire geographic ranges of Impatiens in Madagascar is needed to retest the monophyly of the different subgenera and sections, as well as a molecular dating of the Malagasy Impatiens.
• The study of pollinators as a key for understanding the radiation and species richness is required: Within Impatiens the different shapes of spur are related to pollinators (bees, birds, butterflies and moths). Therefore pollinator observation of specific species need to be done to understand the radiation of species by adaptation and coevolution with these pollinators. A pollination study with a large number of species within section Trimorphopetalum will help to understand the mechanism of complete disappearance of the spur, the shift of pollinators and the evolution of species richness.
• The destruction of the natural habitats of Impatiens and the subsequent reduction of humidity in logged area constitute a severe threat for the survival of many species. The conservation and reforestation of vulnerable areas such as Ankaratra, Daraina, Mandraka and Col des Tapia near Antsirabe is required.
• In terms of conservation and to mitigate the threat on the genus, a study on the ex-situ-conservation of Malagasy Impatiens species is very important as long as some species are suitable for horticultural purposes (e.g. Impatiens mayae-valeriae, Impatiens emiliae and species with broad red spur).
• Finally, the publication of the revision of Impatiens of Madagascar and the Comoro islands will help other botanists to identify the species and will thus increase our knowledge on the group.
The goal of this master thesis was to develop a CRM system for the Assist team of CompuGroup Medical that is aiding in integrating open innovation into the development of the Minerva 2.0 software. To achieve this, CRM methodology has been combined with Social Networking Systems, following the research of Lin and Chen (2010, pp. 11 – 30). To achieve the predefined goals literature has been analyzed on how to successfully im- plement a CRM system as well as an online community. Subsequently the results have been applied to the development of the Minerva Community according to the guidelines of Design Science suggested by Hevner et al. (2004, pp. 75 – 104). The finished product is designed based on customer and management requirements and evaluated from a customer and company perspective.
Lakes and reservoirs are important sources of methane, a potent greenhouse gas. Although freshwaters cover only a small fraction of the global surface, their contribution to global methane emission is significant and this is expected to increase, as a positive feedback to climate warming and exacerbated eutrophication. Yet, global estimates of methane emission from freshwaters are often based on point measurements that are spatio-temporally biased. To better constrain the uncertainties in quantifying methane fluxes from inland waters, a closer examination of the processes transporting methane from sediment to atmosphere is necessary. Among these processes, ebullition (bubbling) is an important transport pathway and is a primary source of uncertainty in quantifying methane emissions from freshwaters. This thesis aims to improve our understanding of ebullition in freshwaters by studying the processes of methane bubble formation, storage and release in aquatic sediments. The laboratory experiments demonstrate that aquatic sediments can store up to ~20% (volumetric content) gas and the storage capacity varies with sediment properties. The methane produced is stored as gas bubbles in sediment with minimal ebullition until the storage capacity is reached. Once the sediment void spaces are created by gas bubble formation, they are stable and available for future bubble storage and transport. Controlled water level drawdown experiments showed that the amounts of gas released from the sediment scaled with the total volume of sediment gas storage and correlated linearly to the drop in hydrostatic pressure. It was hypothesized that not only the timing of ebullition is controlled by sediment gas storage, but also the spatial distribution of ebullition. A newly developed freeze corer, capable of characterizing sediment gas content under in situ environments, enabled the possibility to test the hypothesis in a large subtropical lake (Lake Kinneret, Israel). The results showed that gas content was variable both vertically and horizontally in the lake sediment. Sediment methane production rate and sediment characteristics could explain these variabilities. The spatial distribution of ebullition generally was in a good agreement with the horizontal distribution of depth-averaged (surface 1 m) sediment gas content. While discrepancies were found between sediment depth-integrated methane production and the snapshot ebullition rate, they were consistent in a long term (multiyear average). These findings provide a solid basis for the future development of a process-based ebullition model. By coupling a sediment transport model with a sediment diagenetic model, general patterns of ebullition hotspots can be predicted at a system level and the uncertainties in ebullition flux measurements can be better constrained both on long-term (months to years) and short-term (minutes to hours) scales.
Small headwater streams comprise most of the total channel length and catchment area in fluvial networks. They are tightly connected to their catchments and, thus, are highly vulnerable to changes in catchment hydrologic budgets and land use. Although these small, often fishless streams are of little economic interest, they are vital for the ecological and chemical state of larger water bodies. Although numerous studies investigate the impact of various anthropogenic stressors or altered catchment conditions, we lack an in-depth understanding of the natural conditions and processes in headwater streams. This natural state, however, largely affects how a headwater stream responds to anthropogenic or climatic changes. One of the major threats to aquatic ecosystems is the excessive anthropogenic input of nutrients leading to eutrophication. Nutrients exert a bottom-up effect in the food web, foremost affecting primary producers and their consumers, i.e. periphyton and benthic grazers in headwater streams. The periphyton-grazer link is the main path of autochthonous (in-stream) production into the stream food web and the strength of this link largely determines the effectiveness of this pathway. Therefore, this thesis aims at elucidating important biological processes with the explicit focus on periphyton-grazer interactions. I assessed different aspects of periphyton-grazer interactions using laboratory experiments to solve methodological problems, and using a field study to compare the benthic communities of three morphologically similar, phosphorus-limited, near-natural headwater streams. With the results of the laboratory experiments, I was able to show that periphyton RNA/DNA ratios can be used as proxy for periphyton growth rates in controlled experiments and that the fatty acid composition of grazing mayfly nymphs responds to changes in fatty acids provided by the diet after only two weeks. The use of the RNA/DNA ratio as a proxy for periphyton growth rate allows a comparison of these growth rates even in simple experimental set-ups and thereby permits the inclusion of this important process in ecotoxicological or ecological experiments. The observed fast turnover rates of fatty acids in consumer tissues show that even short-term changes in available primary producers can alter the fatty acid composition of primary consumers with important implications for the supply of higher trophic levels with physiologically important polyunsaturated fatty acids. With the results of the field study, I revealed gaps in the understanding of the linkages between catchment and in-stream phosphorus availability under near-natural conditions and demonstrated that seemingly comparable headwater streams had significantly different benthic communities. These differences most likely affect stream responses to environmental changes.
The purpose of this thesis is to explore the sentiment distributions of Wikipedia concepts.
We analyse the sentiment of the entire English Wikipedia corpus, which includes 5,669,867 articles and 1,906,375 talks, by using a lexicon-based method with four different lexicons.
Also, we explore the sentiment distributions from a time perspective using the sentiment scores obtained from our selected corpus. The results obtained have been compared not only between articles and talks but also among four lexicons: OL, MPQA, LIWC, and ANEW.
Our findings show that among the four lexicons, MPQA has the highest sensitivity and ANEW has the lowest sensitivity to emotional expressions. Wikipedia articles show more sentiments than talks according to OL, MPQA, and LIWC, whereas Wikipedia talks show more sentiments than articles according to ANEW. Besides, the sentiment has a trend regarding time series, and each lexicon has its own bias regarding text describing different things.
Moreover, our research provides three interactive widgets for visualising sentiment distributions for Wikipedia concepts regarding the time and geolocation attributes of concepts.
Navigation is a natural way to explore and discover content in a digital environment. Hence, providers of online information systems such as Wikipedia---a free online encyclopedia---are interested in providing navigational support to their users. To this end, an essential task approached in this thesis is the analysis and modeling of navigational user behavior in information networks with the goal of paving the way for the improvement and maintenance of web-based systems. Using large-scale log data from Wikipedia, this thesis first studies information access by contrasting search and navigation as the two main information access paradigms on the Web. Second, this thesis validates and builds upon existing navigational hypotheses to introduce an adaptation of the well-known PageRank algorithm. This adaptation is an improvement of the standard PageRank random surfer navigation model that results in a more "reasonable surfer" by accounting for the visual position of links, the information network regions they lead to, and the textual similarity between the link source and target articles. Finally, using agent-based simulations, this thesis compares user models that have a different knowledge of the network topology in order to investigate the amount and type of network topological information needed for efficient navigation. An evaluation of agents' success on four different networks reveals that in order to navigate efficiently, users require only a small amount of high-quality knowledge of the network topology. Aside from the direct benefits to content ranking provided by the "reasonable surfer" version of PageRank, the empirical insights presented in this thesis may also have an impact on system design decisions and Wikipedia editor guidelines, i.e., for link placement and webpage layout.
This paper describes the robots TIAGo and Lisa used by team homer@UniKoblenz of the University of Koblenz-Landau, Germany, for the participation at the RoboCup@Home 2018 in Montreal, Canada. Further this paper serves as qualification material for the RoboCup-@Home participation in 2018. A special focus is put on novel system components and the open source contributions of our team. This year the team from Koblenz won the biggest annual scientianc robot competition in Montreal in the RoboCup@Home Open Platform track for the third time and also won the RoboCup@Home German Open for the second time. As a research highlight a novel symbolic imitation learning approach was demonstrated during the annals. The TIAGo robotic research platform was used for the first time by the team. We have released packages for object recognition, a robot face including speech synthesis, mapping and navigation, speech recognition interface via android and a GUI. The packages are available (and new packages will be released) on http://wiki.ros.org/agas-ros-pkg. Further information can be found on our project page http://homer.uni-koblenz.de.
Wikipedia is the biggest, free online encyclopaedia that can be expanded by any-one. For the users, who create content on a specific Wikipedia language edition, a social network exists. In this social network users are categorised into different roles. These are normal users, administrators and functional bots. Within the networks, a user can post reviews, suggestions or send simple messages to the "talk page" of another user. Each language in the Wikipedia domain has this type of social network.
In this thesis characteristics of the three different roles are analysed in order to learn how they function in one language network of Wikipedia and apply them to another Wikipedia network to identify bots. Timestamps from created posts are analysed to reveal noticeable characteristics referring to continuous messages, message rates and irregular behaviour of a user are discovered. Through this process we show that there exist differences between the roles for the mentioned characteristics.
We examine the systematic underrecognition of female scientists (Matilda effect) by exploring the citation network of papers published in the American Physical Society (APS) journals. Our analysis shows that articles written by men (first author, last author and dominant gender of authors) receive more citations than similar articles written by women (first author, last author and dominant gender of authors) after controlling for the journal of publication, year of publication and content of the publication. Statistical significance of the overlap between the lists of references was considered as the measure of similarity between articles in our analysis. In addition, we found that men are less likely to cite articles written by women and women are less likely to cite articles written by men. This pattern leads to receiving more citations by articles written by men than similar articles written by women because the majority of authors who published in APS journals are male (85%). We also observed Matilda effect reduces when articles are published in journals with the highest impact factors. In other words, people’s evaluation of articles published in these journals is not affected by the gender of authors significantly. Finally, we suggested a method that can be applied by editors in academic journals to reduce the evaluation bias to some extent. Editors can identify missing citations using our proposed method to complete bibliographies. This policy can reduce the evaluation bias because we observed papers written by female scholars (first author, last author, the dominant gender of authors) miss more citations than articles written by male scholars (first author, last author, the dominant gender of authors).
The Internet of Things (IoT) is a concept in which connected physical objects are integrated into the virtual world to become active partakers of businesses and everyday processes (Uckelmann, Harrison and Michahelles, 2011; Shrouf, Ordieres and Miragliotta, 2014). It is expected to have a major impact on businesses (Council, Nic and Intelligence, 2008), but small and medium enterprises’ business models are threatened if they do not adopt the new concept (Sommer, 2015). Thus, this thesis aims to showcase a sample implementation of connected devices in a small enterprise, demonstrating its added benefits for the business.
Design Science Research (DSR) is used to develop a prototype based on a use case provided by a carpentry. The prototype comprises a hardware sensor and a web application which can be used by the wood shop to improve their processes. The thesis documents the iterative process of developing a prototype from the grounds up to useable hard- and software.
This contribution provides an example of how IoT can be used and implemented at a small business.
The concept of hard and soft news (HSN) is regarded as one of the most important concepts in journalism research. Despites this popularity, two major research voids can be assigned to the concept. First, it lacks conceptual clarity: the concept gets used interchangeably with related concepts such as sensationalism, which has led to fuzzy demarcations of HSN. Also, it is still not agreed on of which dimensions the concept in composed. Second, little is known about the factors that influence the production of news in terms of their hard or soft nature. The present disserta-tion casts a twofold glance on the HSN concept – it aims to assess the conceptual status of the concept and production of hard and soft news.
At the outset, this dissertation delineates the theoretical base for three manuscripts in total and presented considerations on concepts in social sciences in general and hard and soft news in particular as well as the production of news, particularly of hard and soft news. The first paper proposed a theoretical frame-work model to distinguish HSN and related concepts. Based on a literature review of in total five concepts, this model suggested a hierarchy in which these concepts can be discerned according to their occurrence in media content. The second pa-per focused on the inner coherence of the HSN concept in its most recent academ-ic understanding. The results of a factorial survey with German newspaper jour-nalists showed that, indeed, four out of five dimensions of the HSN concept com-prised what the journalists understood by it. Hence, the most recent academic un-derstanding is to a great extent coherent. The third study shed light on the produc-tion of HSN, focusing on the influence of individual journalists’ and audience’s characteristics on whether news was presented in hard or soft way. The findings of a survey with simulated decision scenarios among German print journalists showed that the HSN dimensions were susceptible to different journalistic influ-ences and that a perceived politically uninterested audience led to a softer cover-age. The dissertation concluded with connecting these findings with the considera-tions on concept evaluation and the production of news. Implications for research on and with the concept of HSN were presented, before concluding with limitations and suggestions for future research.
Estuaries are characterized by a longitudinal salinity gradient. This gradient is one of the main environmental factors responsible for the distribution of organisms. Distinguishing salinity zones is of crucial importance, e.g., for the development of tools for the assessment of ecological quality. The methods most often applied for classifying water according to salinity are the Venice System and the method of Bulger et al. (1993), both of which determine zone boundaries using species occurrences relative to mean salinity. However, although these methods were developed for homoiohaline waters, they have also been routinely applied to poikilohaline systems. I tested the applicability of both methods using salinity and macroinvertebrate data for the poikilohaline Elbe Estuary (Germany). My results showed that the mid-estuary distribution of macro-invertebrates is determined by variation in salinity rather than by mean salinity. Consequently, neither of the two methods is applicable for defining salinity zones in the Elbe Estuary. Cluster analysis combined with a significance test, by contrast, was a better tool for identifying the boundaries of salinity zones in poikilohaline systems.
In many estuaries, such as the Elbe Estuary, a maximum turbidity zone (MTZ) develops, where suspended matter accumulates owing to circulation processes. It is assumed that the MTZ is a stressful environment with an excess of organic matter, high deposition rates, large variations in salinity, and dredging activities. Under such harsh conditions, populations might remain below the carrying capacity, and it is assumed that competition is of little importance, as predicted by the stress gradient hypothesis. I tested whether competition for food is important in the MTZ of the Elbe Estuary using stable isotope analysis of the macroinvertebrate community. The isotopic niches of no two taxa within a feeding group overlapped, which indicated different resource use and the absence of competition. The main reasons for the lack of overlap of isotopic niches were differences in habitat, feeding behavior, and migration behavior.
The Elbe Estuary is nowadays highly industrialized and has long been subjected to a plethora of human-caused alterations. However, it is largely unknown what changes occurred in benthic communities in the last century. Hence, I considered taxonomic and functional aspects of macrobenthic invertebrates of the Elbe Estuary given in data from 1889 (most natural state), 1985 and 1986 (highly polluted state), and 2006 (recent state) to assess benthic community shifts. Beta-diversity analysis showed that taxonomic differences between the sampling dates were mainly due to species turnover, whereas functional differences were predominantly a result of functional nestedness. Species number (S), functional richness (FRic), and functional redundancy reached minimum values in 1985 and 1986 and were highest and rather similar in 1889 and 2006. The decline in FRic from 1889 to 1985/1986 was non-random, consistent with habitat filtering. FRic, functional beta diversity, and S data suggested that the state of the estuary from 1889 was almost re-established in 2006. However, the community in 1889 significantly differed from that in 2006 owing to species replacement. My results indicate that FRic and FR in 1889 could have promoted ecosystem resilience and stability.
This thesis connects the endeavors of the winemaker’s intention in perfect and profitable wine making with an innovative technological application to use Internet of Things. Thereby the winemaker’s work may be supported and enriched – and enables until recent years still unthinkable optimization of managing and planning of his business, including close state control of different areas of his vineyard, and more than that, not ending up with the single grapevine. It is exemplarily shown in this thesis how to measure, transmit, store and make data available, exemplarily demonstrated with “live” temperature, air and soil humidity values from the vineyard. A modular architecture was designed for the system presented, which allows the use of current sensors, and similar low-voltage sensors, which will be developed in the future.
By using IoT devices in the vineyard, the winemaker advances to a new quality of precision of forecasted data, starting from live data of his vineyard. Of more and more importance, the winemaker can start immediate action, when unforeseen heavy weather conditions occur. Immediate use of current data enabled by a Cloud Infrastructure. For this system, an open service infrastructure is employed. In contrast to other published commercial approaches, the described solution is based on open source.
As an alone-standing part of this work, a physical prototype for measuring relevant parameters in the vineyard was de-novo designed and developed until fulfilling the set of specifications. The outlined features and requirements for a functioning data collection and autonomously transmitting device was developed, described, and the fulfilment by the prototype device were demonstrated. Through literature research and supportive orientationally live interviews of winemakers, the theory and the practical application were synchronized and qualified.
For the development of the prototype the general principles of development of an electronic device were followed, in particular the Design Science Research development rules, and principles of Quality Function Deployment. As a characteristic of the prototype, some principles like re-use of approved construction and material price of the building blocks of the device were taken into consideration as well (e.g. housing; Arduino; PCB). Parts reduction principles, decomplexation and simplified assembly, testing and field service were integrated to the development process by the modular design of the functional vineyard device components, e.g. with partial reference to innovative electrical cabinet construction system Modular-3.
The software architectural concept is based on a three-layer architecture inclusive the TTN infrastructure. The front end is realized as a rich web client, using a WordPress plugin. WordPress was chosen due to the wide adoption through the whole internet, enabling fast and easy user familiarization. Relevant quality issues have been tested and discussed in the view of exemplary functionality, extensibility, requirements fulfilment, as usability and durability of the device and the software.
The prototype was characterized and tested with success in the laboratory and in field exposition under different conditions, in order to allow a measurement and analysis of the fulfilment of all requirements by the selected and realized electronic construction and layout.
The solution presented may serve as a basis for future development and application in this special showcase and within similar technologies. A prognosis of future work and applications concludes this work.
Ontologies are valuable tools for knowledge representation and important building blocks of the Semantic Web. They are not static and can change over time. Changing an ontology can be necessary for various reasons: the domain that is represented by an ontology can change or an ontology is reused and must be adapted to the new context. In addition, modeling errors could have been introduced into the ontology which must be found and removed. The non-triviality of the change process has led to the emerge of ontology change as an own field of research. The removal of knowledge from ontologies is an important aspect of this change process, because even the addition of new knowledge to an ontology potentially requires the removal of older, conflicting knowledge. Such a removal must be performed in a thought-out way. A naïve change of concepts within the ontology can easily remove other, unrelated knowledge or alter the semantics of concepts in an unintended way [2]. For these reasons, this thesis introduces a formal operator for the fine-grained retraction of knowledge from EL concepts which is partially based on the postulates for belief set contraction and belief base contraction [3, 4, 5] and the work of Suchanek et al. [6]. For this, a short introduction to ontologies and OWL 2 is given and the problem of ontology change is explained. It is then argued why a formal operator can support this process and why the Description Logic EL provides a good starting point for the development of such an operator. After this, a general introduction to Description Logic is given. This includes its history, an overview of its applications and common reasoning tasks in this logic. Following this, the logic EL is defined. In a next step, related work is examined and it is shown why the recovery postulate and the relevance postulate cannot be naïvely employed in the development of an operator that removes knowledge from EL concepts. Following this, the requirements to the operator are formulated and properties are given which are mainly based on the postulates for belief set and belief base contraction. Additional properties are developed which make up for the non-applicability of the recovery and relevance postulates. After this, a formal definition of the operator is given and it is shown that the operator is applicable to the task of a fine-grained removal of knowledge from EL concepts. In a next step, it is proven that the operator fulfills all the previously defined properties. It is then demonstrated how the operator can be combined with laconic justifications [7] to assist a human ontology editor by automatically removing unwanted consequences from an ontology. Building on this, a plugin for the ontology editor Protégé is introduced that is based on algorithms that were derived from the formal definition of the operator. The content of this work is then summarized and a final conclusion is drawn. The thesis closes with an outlook into possible future work.
Different techniques (weight loss, electrochemical, and spray
corrosion measurements) have been used to evaluate four sarcosine derivatives to inhibit corrosion and one commercial compound as synergist. The basic metal was low carbon steel CR4 tested at different conditions. As working media mainly neutral water and 0.1 M NaCl was applied. The protective film was formed on the steel surface via direct absorption of the tested substances during the immersion process. A highly improved corrosion protection with direct correlation to the molecular weight and carbon chain length of the tested compounds was detected. The protection of steel CR4 against corrosion in 0.1 M NaCl enhanced with increasing concentration of selected sarcosine compounds. The best inhibitor throughout all tested concentrations and all evaluation systems was Oleoylsarcosine (O) with efficiencies up to 97 % in potentiodynamic polarization (PP), 83 % electrochemical impedance spectroscopy (EIS), and 85 % weight loss (WL) at 100 mmol/L as highest concentration tested here. The second best inhibitor was Myristoylsarcosine (M) with efficiencies up to 82 % in PP, 69 % in EIS, and 75 % in WL at highest concentration. The inhibitor with the shortest hydrocarbon chain in this series is Lauroylsarcosine (L). It showed lowest effects to inhibit corrosion compared to O and M. The efficiencies of L were a bit more than 50 % at 75 and 100 mmol/L and less than 50 % at 25 and 50 mmol/L in all used evaluation systems. Furthermore, the overall efficiency is promoted with longer dip coating times during the steel CR4 immersion as shown for 50 mmol/L for all present derivatives. This survey indicated 10 min as best time in respect of cost and protection efficiency. The commercial inhibitor Oley-Imidazole (OI) improved significantly the effectiveness of compound Cocoylsarcosine (C), which contains the naturally mixture of carbon chain lengths from coconut oil (C8 - C18), and enhanced protection when used in combination (C+OI, 1:1 molar ration). In this system the efficiency increased from 47 % to 91 % in PP, from 40 % to 84 % in EIS, and from 45 % to 82 % in WL at highest concentration. Spray corrosion tests were used to evaluate all present sarcosine substances on steel CR4 in a more realistic system. The best inhibitor after a 24 h test was O followed by the combination C+OI and M with efficiencies up to 99 %, 80 %, and 79 %, respectively. The obtained results indicate a good stability of the protective film formed by the present inhibitors even after 24 h. All evaluation systems used in the current investigation were in good agreement and resulted in the same inhibitor sequence. Furthermore, the adsorption process of the tested compounds is assumed to follow the Langmuir type isotherm. Response surface methodology (RSM) is an optimization method depending on Box- Behnken Design (BBD). It was used in the current system to find the optimum efficiency for inhibitor O to protect steel CR4 against corrosion in salt water. Four independent variables were used here: inhibitor concentration (A), dip coating time (B), temperature (C), and NaCl concentration (D); each with three respective levels: lower (-1), mid (0), and upper (+1). According to the present result, temperature has the greatest effect on the protection process as individual parameter followed by the inhibitor concentration itself. In this investigation an optimum efficiency of 99 % is calculated by the following parameter and level combination: upper level (+1) for inhibitor concentration, dip coating time, and NaCl concentration while lower level (-1) for temperature.
This thesis addresses the automated identification and localization of a time-varying number of objects in a stream of sensor data. The problem is challenging due to its combinatorial nature: If the number of objects is unknown, the number of possible object trajectories grows exponentially with the number of observations. Random finite sets are a relatively new theory that has been developed to derive at principled and efficient approximations. It is based around set-valued random variables that contain an unknown number of elements which appear in arbitrary order and are themselves random. While extensively studied in theory, random finite sets have not yet become a leading paradigm in practical computer vision and robotics applications. This thesis explores random finite sets in visual tracking applications. The first method developed in this thesis combines set-valued recursive filtering with global optimization. The problem is approached in a min-cost flow network formulation, which has become a standard inference framework for multiple object tracking due to its efficiency and optimality. A main limitation of this formulation is a restriction to unary and pairwise cost terms. This circumstance makes integration of higher-order motion models challenging. The method developed in this thesis approaches this limitation by application of a Probability Hypothesis Density filter. The Probability Hypothesis Density filter was the first practically implemented state estimator based on random finite sets. It circumvents the combinatorial nature of data association itself by propagation of an object density measure that can be computed efficiently, without maintaining explicit trajectory hypotheses. In this work, the filter recursion is used to augment measurements with an additional hidden kinematic state to be used for construction of more informed flow network cost terms, e.g., based on linear motion models. The method is evaluated on public benchmarks where a considerate improvement is achieved compared to network flow formulations that are based on static features alone, such as distance between detections and appearance similarity. A second part of this thesis focuses on the related task of detecting and tracking a single robot operator in crowded environments. Different from the conventional multiple object tracking scenario, the tracked individual can leave the scene and later reappear after a longer period of absence. Therefore, a re-identification component is required that picks up the track on reentrance. Based on random finite sets, the Bernoulli filter is an optimal Bayes filter that provides a natural representation for this type of problem. In this work, it is shown how the Bernoulli filter can be combined with a Probability Hypothesis Density filter to track operator and non-operators simultaneously. The method is evaluated on a publicly available multiple object tracking dataset as well as on custom sequences that are specific to the targeted application. Experiments show reliable tracking in crowded scenes and robust re-identification after long term occlusion. Finally, a third part of this thesis focuses on appearance modeling as an essential aspect of any method that is applied to visual object tracking scenarios. Therefore, a feature representation that is robust to pose variations and changing lighting conditions is learned offline, before the actual tracking application. This thesis proposes a joint classification and metric learning objective where a deep convolutional neural network is trained to identify the individuals in the training set. At test time, the final classification layer can be stripped from the network and appearance similarity can be queried using cosine distance in representation space. This framework represents an alternative to direct metric learning objectives that have required sophisticated pair or triplet sampling strategies in the past. The method is evaluated on two large scale person re-identification datasets where competitive results are achieved overall. In particular, the proposed method better generalizes to the test set compared to a network trained with the well-established triplet loss.
Social entrepreneurship is a form of entrepreneurship that marries a social mission to a competitive value proposition. Notably, social entrepreneurship fosters a more equitable society by addressing social issues and trying to achieve an ongoing sustainable impact through a social mission rather than purely profit maximization. The topic of social entrepreneurship has appealed considerably to many different streams of research. The focus on understanding how and why entrepreneurs think and act is a significant justification for future research. Nevertheless, the theoretical examination of this phenomenon is in its infancy. Social entrepreneurship research is still largely phenomenon-driven. Specifically, Social Entrepreneurial Intention is in an early stage and lacks quantitative research. Therefore, this thesis proposes to address this need. The thesis’ objectives are twofold: (1) develop a formation model for Social Entrepreneurial Intentions in general and (2) test the model by conducting an empirical study. Based on these objectives, the two research questions guiding the thesis are (1) what factors influence the intention of a person to become a social entrepreneur and (2) what relationships exist among these factors.
In order to answer these two research questions, this thesis uses purposeful research design, which is a combination of literature review and empirical study. The literature review is based on a comprehensive range of books, articles, and research papers published in leading academic journals and conference proceedings in different disciplines such as entrepreneurship, social entrepreneurship, entrepreneurship education, management, social psychology, and social economics. The empirical study is conducted via a survey of 600 last-year students from four universities in three regions in Vietnam: Hanoi, Da Nang, and Ho Chi Minh. The data are analyzed with SPSS-AMOS version 24, using screening data, scale development, exploratory factor analysis, and confirmation factor analysis. The thesis ascertains that Entrepreneurship Experience/Extra-curricular Activity, Role Model, Social Entrepreneurial Self-Efficacy, and Social Entrepreneurial Outcome Expectation directly and positively affect the intention of the Vietnamese students to be social entrepreneurs. Entrepreneurship Education also influences the Social Entrepreneurial Intention, but not directly, otherwise indirectly via Social Entrepreneurial Self-Efficacy and Social Entrepreneurial Outcome Expectation. Similarly, Perceived Support has no direct relationship to Social Entrepreneurial Intention; however, it shows an indirect link via the mediator ‘Social Entrepreneurial Outcome Expectation’. Furthermore, the dissertation brings new insights to the social entrepreneurship literature and provides important implications for practice. Limitations and future directions are also provided in the thesis.
The aquatic environment is exposed to multiple environmental pressures and mixtures of chemical substances, among them petroleum and petrochemicals, metals, and pesticides. Aquatic invertebrate communities are used as bioindicators to reflect long-term and integral effects. Information on the presence of species can be supplemented with information on their traits. SPEAR-type bioindicators integrate such trait information on the community level.
This thesis aimed at enhancing specificity of SPEAR-type bioindicators towards particular groups of chemicals, namely to mixtures of oil sands-derived compounds, hydrocarbons, and metals.
For developing a bioindicator for discontinuous contamination with oil-derived organic toxicants, a field study was conducted in the Canadian oil sands development region in Northern Alberta. The traits ‘physiological sensitivity towards organic chemicals’ and ‘generation time’ were integrated to develop the bioindicator SPEARoil, reflecting the community sensitivity towards oil sands derived contamination in relation to fluctuating hydrological conditions.
According to the SPEARorganic approach, a physiological sensitivity ranking of taxa was developed for hydrocarbon contamination originating from crude oil or petroleum distillates. For this purpose, ecotoxicological information from acute laboratory tests was enriched with rapid and mesocosm test results. The developed Shydrocarbons sensitivity values can be used in SPEAR-type bioindicators.
To specifically reflect metal contamination in streams via bioindicators, Australian field studies were re-evaluated with focus on the traits ‘physiological metal sensitivity’ and ‘feeding type’. Metal sensitivity values, however, explained community effects in the field only weakly. Instead, the trait ‘feeding type’ was strongly related to metal exposure. The fraction of predators in a community can, thus, serve as an indicator for metal contamination in the field.
Furthermore, several metrics reflecting exposure to chemical cocktails in the environment were compared using existing pesticide datasets. Exposure metrics based on the 5% fraction of species sensitivity distributions were found to perform best, however, closely followed by Toxic Unit metrics based on the most sensitive species of a community or Daphnia magna.
Knowledge-based authentication methods are vulnerable to Shoulder surfing phenomenon.
The widespread usage of these methods and not addressing the limitations it has could result in the user’s information to be compromised. User authentication method ought to be effortless to use and efficient, nevertheless secure.
The problem that we face concerning the security of PIN (Personal Identification Number) or password entry is shoulder surfing, in which a direct or indirect malicious observer could identify the user sensitive information. To tackle this issue we present TouchGaze which combines gaze signals and touch capabilities, as an input method for entering user’s credentials. Gaze signals will be primarily used to enhance targeting and touch for selecting. In this work, we have designed three different PIN entry method which they all have similar interfaces. For the evaluation, these methods were compared based on efficiency, accuracy, and usability. The results uncovered that despite the fact that gaze-based methods require extra time for the user to get familiar with yet it is considered more secure. In regards to efficiency, it has the similar error margin to the traditional PIN entry methods.