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Organic substances play an essential role for the formation of stable soil structures. In this context, their physico-chemical properties, interactions with mineral soil constituents and soil-water interactions are particu-larly important. However, the underlying mechanisms contributing to soil particle cementation by swollen or-ganic substances (hydrogels) remains unclear. Up to now, no mechanistic model is available which explains the mechanisms of interparticulate hydrogel swelling and its contribution to soil-water interactions and soil structur-al stability. This mainly results from the lack of appropriate testing methods to study hydrogel swelling in soil as well as from the difficulties of adapting available methods to the system soil/hydrogel.
In this thesis, 1H proton nuclear magnetic resonance (NMR) relaxometry was combined with various soil micro- and macrostructural stability testing methods in order to identify the contribution of hydrogel swelling-induced soil-water interactions to the structural stability of water-saturated and unsaturated soils. In the first part, the potentials and limitations of 1H NMR relaxometry to enlighten soil structural stabilization mechanism and vari-ous water populations were investigated. In the second part, 1H-NMR relaxometry was combined with rheologi-cal measurements of soil to assess the contribution of interparticulate hydrogel swelling and various polymer-clay interactions on soil-water interactions and soil structural stability in an isolated manner. Finally, the effects of various organic and mineral soil fractions on soil-water interactions and soil structural stability was assessed in more detail for a natural, agriculturally cultivated soil by soil density fractionation and on the basis of the experiences gained from the previous experiments.
The increased experiment complexity in the course of this thesis enabled to link physico-chemical properties of interparticulate hydrogel structures with soil structural stability on various scales. The established mechanistic model explains the contribution of interparticulate hydrogels to the structural stability of water-saturated and unsaturated soils: While swollen clay particles reduce soil structural stability by acting as lubricant between soil particles, interparticulate hydrogel structures increase soil structural stability by forming a flexible polymeric network which interconnects mineral particles more effectively than soil pore- or capillary water. It was appar-ent that soil structural stability increases with increasing viscosity of the interparticluate hydrogel in dependence on incubation time, soil texture, soil solution composition and external factors in terms of moisture dynamics and agricultural management practices. The stabilizing effect of interparticulate hydrogel structures further in-crease in the presence of clay particles which is attributed to additional polymer-clay interactions and the incor-poration of clay particles into the three-dimensional interparticulate hydrogel network. Furthermore, the simul-taneous swelling of clay particles and hydrogel structures results in the competition for water and thus in a mu-tual restriction of their swelling in the interparticle space. Thus, polymer-clay interactions not only increase the viscosity of the interparticulate hydrogel and thus its ability to stabilize soil structures but further reduce the swelling of clay particles and consequently their negative effects on soil structural stability. The knowledge on these underlying mechanisms enhance the knowledge on the formation of stable soil structures and enable to take appropriate management practices in order to maintain a sustainable soil structure. The additionally out-lined limitations and challenges of the mechanistic model should provide information on areas with optimization and research potential, respectively.
The content aggregator platform Reddit has established itself as one of the most popular websites in the world. However, scientific research on Reddit is hindered as Reddit allows (and even encourages) user anonymity, i.e., user profiles do not contain personal information such as the gender. Inferring the gender of users in large-scale could enable the analysis of gender-specific areas of interest, reactions to events, and behavioral patterns. In this direction, this thesis suggests a machine learning approach of estimating the gender of Reddit users. By exploiting specific conventions in parts of the website, we obtain a ground truth for more than 190 million comments of labeled users. This data is then used to train machine learning classifiers to use them to gain insights about the gender balance of particular subreddits and the platform in general. By comparing a variety of different approaches for classification algorithm, we find that character-level convolutional neural network achieves performance with an 82.3% F1 score on a task of predicting a gender of a user based on his/her comments. The score surpasses 85% mark for frequent users with more than 50 comments. Furthermore, we discover that female users are less active on Reddit platform, they write fewer comments and post in fewer subreddits on average, when compared to male users.
Homonegative discrimination such as the denial of leadership qualities and higher salaries concern not only lesbians and gay men but also individuals who were perceived as lesbian or gay (Fasoli et al., 2017). Hence, it is assumed that especially straight people become victims of homonegative discrimination (Plöderl, 2014). The perception of sexual orientation is indeed stereotype-driven (e.g., Cox et al., 2015) but there is a lack of knowledge on how accurate stereotypes are – particularly those referring to speech. Despite a variety of sociophonetic and social psychological research related to sexual orientation and gender, an encompassing understanding is missing on how sexual orientation is expressed and perceived.
The present thesis aims to fill these gaps. The two major aims of the present work are a) the examination of the accuracy of speech stereotypes in the context of sexual orientation and b) the development of a model on how sexual orientation is interpersonally construed. Overall, the present thesis comprises five manuscripts with the following aspects in common: They integratively deal with social psychological and sociophonetic perspectives, share a social identity approach, and primarily center speech instead of facial appearance. Moreover, mostly German and German native speaking participants, respectively, have been investigated.
Manuscript 1 establishes the Traditional Masculinity/Femininity-Scale as a reliable and valid instrument for assessing gender-role self-concept. The invention was necessary because existing scales insufficiently represented the self-ascribed masculinity/femininity yet (e.g., Abele, 2003; Evers & Sieverding, 2014). Manuscripts 2, 3, and 4 address the (in)accuracy of speech stereotypes regarding stereotypic content and suggested within-group homogeneity. This is carried out by the application of different methodological approaches. On the one hand, relevant acoustic parameters of lesbian/gay and straight women and men were averaged for each group. On the other hand, voice morphing was applied in order to create prototypical and naturally sounding voice averages (Kawahara et al., 2008). Lesbians and straight women differed in none, gay and straight men in one of the analyzed acoustic parameters only. In contrast, a fine-grained psychological analysis yielded various evidence for acoustic within-group heterogeneity. In particular, the exclusivity of sexual orientation and gender-role self-concept have been acoustically indexicalized which suggests that speech stereotypes are inaccurate. However, voice averages do carry perceivable sexual orientation information. Hence, speech stereotypes can be considered as exaggerations of tiny kernels of truth. In Manuscript 5, previous literature on the interpersonal construction of sexual orientation is integrated in a model: The Expression and Perception of Sexual Orientation Model (EPSOM). This model postulates an indirect route and describes how sexual orientation information is transmitted from producer to perceiver by proposing three mediating components. Thereby, the model is able to offer an explanation why sexual orientation can be perceived with above-chance but far-away-from-perfect accuracy.
Overall, the present thesis provides meaningful impulses for enhancements of research on social markers of sexual orientation and gender. This thesis offers a model on how sexual orientation is expressed and perceived, shows the benefits of combining sociophonetic and social psychological approaches, and points out the value of applying novel methods and technologies. Beyond that, the present thesis offers useful implications for practice. Speech stereotypes in the context of sexual orientation can be rejected as inaccurate – for example, native German straight men do not nasalize more or less than gay men. Thereby, the present thesis contributes to an erosion of stereotypes and a potential reduction of homonegative discrimination.
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.
This paper describes the robot Lisa used by team homer@UniKoblenz of the University of Koblenz Landau, Germany, for the participation at the RoboCup@Home 2017 in Nagoya, Japan. 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 via android and a GUI. The packages are available (and new packages will be released) on
http://wiki.ros.org/agas-ros-pkg.
With 47% land coverage in 2016, agricultural land was one of the largest terrestrial biomes in Germany. About 70% of the agricultural land was cropped area with associated pesticide applications. Agricultural land also represents an essential habitat for amphibians. Therefore, exposure of amphibians to agrochemicals, such as fertilizers and pesticides, seems likely. Pesticides can be highly toxic for amphibians, even a fraction of the original application rate may result in high amphibian mortality.
To evaluate the potential risk of pesticide exposure for amphibians, the temporal coincidence of amphibian presence on agricultural land and pesticide applications (N = 331) was analyzed for the fire-bellied toad (Bombina bombina), moor frog (Rana arvalis), spadefoot toad (Pelobates fuscus) and crested newt (Triturus cristatus) during spring migration. In 2007 and 2008, up to 80% of the migrating amphibians temporally coincided with pesticide applications in the study area of Müncheberg, about 50 km east of Berlin. Pesticide interception by plants ranged between 50 to 90% in winter cereals and 80 to 90% in winter rape. The highest coincidence was observed for the spadefoot toad, where 86.6% of the reproducing population was affected by a single pesticide in winter rape during stem elongation with 80% pesticide interception by plants. Late migrating species, such as the fire-bellied toad and the spadefoot toad, overlapped more with pesticide applications than early migrating species, such as the moor frog, did. Under favorable circumstances, the majority of early migrants may not coincide with the pesticide applications of arable fields during spring migration.
To evaluate the potential effect of pesticide applications on populations of the common frog (Rana temporaria), a landscape genetic study was conducted in the vinicultural area of Southern Palatinate. Due to small sample sizes at breeding sites within viniculture, several DNA sampling methods were tested. Furthermore, the novel repeated randomized selection of genotypes approach was developed to utilize genetic data from siblings for more reliable estimates of genetic parameters. Genetic analyses highlighted three of the breeding site populations located in viniculture as isolated from the meta-population. Genetic differentiation among breeding site populations in the viniculture (median pairwise FST=0.0215 at 2.34 km to 0.0987 at 2.39 km distance) was higher compared to genetic differentiation among breeding site populations in the Palatinate Forest (median pairwise FST=0.0041 at 5.39 km to 0.0159 at 9.40 km distance).
The presented studies add valuable information about the risk of pesticide exposure for amphibians in the terrestrial life stage and possible effects of agricultural land on amphibian meta-populations. To conserve endemic amphibian species and their (genetic) diversity in the long run, the risk assessment of pesticides and applied agricultural management measures need to be adjusted to protect amphibians adequately. In addition, other conservation measures such as the creation of new suitable breeding site should be considered to improve connectivity between breeding site populations and ensure the persistence of amphibians in the agricultural land.
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.
This Master Thesis is an exploratory research to determine whether it is feasible to construct a subjectivity lexicon using Wikipedia. The key hypothesis is that that all quotes in Wikipedia are subjective and all regular text are objective. The degree of subjectivity of a word, also known as ''Quote Score'' is determined based on the ratio of word frequency in quotations to its frequency outside quotations. The proportion of words in the English Wikipedia which are within quotations is found to be much smaller as compared to those which are not in quotes, resulting in a right-skewed distribution and low mean value of Quote Scores.
The methodology used to generate the subjectivity lexicon from text corpus in English Wikipedia is designed in such a way that it can be scaled and reused to produce similar subjectivity lexica of other languages. This is achieved by abstaining from domain and language-specific methods, apart from using only readily-available English dictionary packages to detect and exclude stopwords and non-English words in the Wikipedia text corpus.
The subjectivity lexicon generated from English Wikipedia is compared against other lexica; namely MPQA and SentiWordNet. It is found that words which are strongly subjective tend to have high Quote Scores in the subjectivity lexicon generated from English Wikipedia. There is a large observable difference between distribution of Quote Scores for words classified as strongly subjective versus distribution of Quote Scores for words classified as weakly subjective and objective. However, weakly subjective and objective words cannot be differentiated clearly based on Quote Score. In addition to that, a questionnaire is commissioned as an exploratory approach to investigate whether subjectivity lexicon generated from Wikipedia could be used to extend the coverage of words of existing lexica.
The term “Software Chrestomaty” is defined as a collection of software systems meant to be useful in learning about or gaining insight into software languages, software technologies, software concepts, programming, and software engineering. 101companies software chrestomathy is a community project with the attributes of a Research 2.0 infrastructure for various stakeholders in software languages and technology communities. The core of 101companies combines a semantic wiki and confederated open source repositories. We designed and developed an integrated ontology-based knowledge base about software languages and technologies. The knowledge is created by the community of contributors and supported with a running example and structured documentation. The complete ecosystem is exposed by using Linked Data principles and equipped with the additional metadata about individual artifacts. Within the context of software chrestomathy we explored a new type of software architecture – linguistic architecture that is targeted on the language and technology relationships within a software product and based on the megamodels. Our approach to documentation of the software systems is highly structured and makes use of the concepts of the newly developed megamodeling language MegaL. We “connect” an emerging ontology with the megamodeling artifacts to raise the cognitive value of the linguistic architecture.
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.
Entrepreneurship plays a vital role in scientific literature and in public debates. Especially in these hightech and digitized times it happens more and more frequently that young entrepreneurs with a good idea make the breakthrough and set up an established company. Basically, there are an increasing number of start-ups and a trend towards independence. The economy of a country depends on young entrepreneurs in order to remain economically competitive in international competition. It follows that young entrepreneurs must be encouraged and supported. This support is expressed in various stages of foundation and through various fields of action. In the meantime, there are many offers for start-up support. These networks satisfy different fields of action along a foundation. However, a structured overview of these networks on which a young founder can orient himself and gain easily access to the offers of the networks, is missing until then.
This work attempts to present these offers clearly on a map and to categorize and present the commitment in the respective fields of action. In addition to this main objective, the following three key questions are investigated and answered in this work:
1. How can the Entrepreneurship Networks be assigned to the respective fields of action of Entrepreneurship Education?
2. What is the benefit of such a classification for potential entrepreneurs in detail?
3. Are these Entrepreneurship networks missing an important step? Might they improve their offer? Does the value chain cover every need a young entrepreneur might have?
For this purpose, the respective fields of action of the networks are first separated from each other along a founding and defined individually. Subsequently, a combination of quantitative and qualitative approaches was used to filter and analyze the contents of the websites of the networks. The results of this investigation were transformed in a classification
The aim of this work is to produce a map that displays the existing networks in the world clearly. The map also contains information that is more detailed and the classifica-tion of the networks in the respective fields of action.
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.
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 primary aims of the study are (1) to identify classroom instructional factors which have a crucial effect on the academic growth of ninth-graders in EFL in Vietnam, and (2) to gain insight into their interplay with each other and with context factors. Besides, this study has a strong focus on methodological approaches: (a) using multiple methods in order to deal with the “large p, small n” problem, (b) to understand the relevance of the scaling model used for the results.
Data from a research project carried out in Vietnam during the school year 2006–2007 were used in this study. Besides a longitudinal design with two measurement points (MPs) using adapted English tests and questionnaires from the DESI-study in Germany, a video study was conducted in the middle of the school year between two MPs. The recorded video data were transcribed, micro-analytically coded, and lessons were rated to gain indicators of classroom instruction. Different IRT scaling models were chosen to estimate student ability in the pretest and posttest. For the C-test, the unidimensional 1PL and 2PL models, the Rasch testlet model, and testlet 2PL model were selected to model student ability. To estimate student ability via the listening comprehension test (LC-test), the Rasch model, the unidimensional 2PL, and 3PL models were applied. The student ability estimates at the two MPs were linked to one common scale using the concurrent calibration approach with different a priori ability distributions. The plausible values (PVs) were generated and treated as student ability estimates for all analyses. To understand the relationship between the instructional variables and student growth, we explored the hypothesized linear and nonlinear, additive and interactive effects of classroom instructional factors. To examine these hypothetical effects, OLS and regularized regression models using lasso (least absolute shrinkage and selection operators) were applied, including main effects as well as quadratic and interaction terms of instructional variables. Initial student ability and the socioeconomic status of students were treated as context variables.
The results show, on the one hand, a positive view of important general instructional quality dimensions of teaching effectiveness and, on the other hand, a strongly teacher-centered and textbook-driven instruction and poor instructional quality from the point of view of EFL didactics. The most important instructional factors of student growth in the C-test were quality aspects of motivation in instruction as well as aspects related to the teaching language. Regarding the LC-test results, language-related aspects together with the relative frequency of repeated questions were the most important predictors of student growth. While the findings confirmed all the hypothesized instructional effects on student growth, aptitude treatment interaction effects of instruction were only confirmed with regard to student growth in the C-test. The different scaling models produced significant differences in the results regarding instructional effects on student growth.
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.
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.
Within aquatic environments sediment water interfaces (SWIs) are the most important areas concerning exchange processes between the water body and the sediment. These spatially restricted regions are characterized by steep biogeochemical gradients that determine the speciation and fate of natural or artificial substances. Apart from biological mediated processes (e.g., burrowing organisms, photosynthesis) the determining exchange processes are diffusion or a colloid-mediated transport. Hence, methods are required enabling to capture the fine scale structures at the boundary layer and to distinguish between the different transport pathways. Regarding emerging substances that will probably reach the aquatic environment engineered nanomaterials (ENMs) are of great concern due to their increased use in many products and applications. Since they are determined based on their size (<100 nm) they include a variety of different materials behaving differently in the environment. Once released, they will inevitable mix with naturally present colloids (< 1 μm) including natural nanomaterials.
With regard to existing methodological gaps concerning the characterization of ENMs (as emerging substances) and the investigation of SWIs (as receiving environmental compartments), the aim of this thesis was to develop, validate and apply suitable analytical tools. The challenges were to i) develop methods that enable a high resolution and low-invasive sampling of sediment pore water. To ii) develop routine-suitable methods for the characterization of metal-based engineered nanoparticles and iii) to adopt and optimize size-fractionation approaches for pore water samples of sediment depth profiles to obtain size-related information on element distributions at SWIs.
Within the first part, an available microprofiling system was combined with a novel micro sampling system equipped with newly developed sample filtration-probes. The system was thoroughly validated and applied to a freshwater sediment proving the applicability for an automatic sampling of sediment pore waters in parallel to microsensor measurements. Thereby, for the first time multi-element information for sediment depth profiles were obtained at a millimeter scale that could directly be related to simultaneously measured sediment parameters.
Due to the expected release of ENMs to the environment the aim was to develop methods that enable the investigation of fate and transport of ENMs at sediment water interfaces. Since standardized approaches are still lacking, methods were developed for the determination of the total mass concentration and the determination of the dissolved fraction of (nano)particle suspensions. Thereby, validated, routine suitable methods were provided enabling for the first time a routine-suitable determination of these two, among the most important properties regarding the analyses of colloidal systems, also urgently needed as a basis for the development of appropriate (future) risk assessments and regulatory frameworks. Based on this methodological basis, approaches were developed enabling to distinguish between dissolved and colloidal fractions of sediment pore waters. This made it possible for the first time to obtain fraction related element information for sediment depth profiles at a millimeter scale, capturing the fine scale structures and distinguishing between diffusion and colloid-mediated transport. In addition to the research oriented parts of this thesis, questions concerning the regulation of ENPs in the case of a release into aquatic systems were addressed in a separate publication (included in the Appendix) discussing the topic against the background of the currently valid German water legislation and the actual state of the research.
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.
Systemic neonicotinoids are one of the most widely used insecticide classes worldwide. In addition to their use in agriculture, they are increasingly applied on forest trees as a protective measure against insect pests. However, senescent leaves containing neonicotinoids might, inter alia during autumn leaf fall, enter nearby streams. There, the hydrophilic neonicotinoids may be remobilized from leaves to water resulting in waterborne exposure of aquatic non-target organisms. Despite the insensitivity of the standard test species Daphnia magna (Crustacea, Cladocera) toward neonicotinoids, a potential risk for aquatic organisms is evident as many other aquatic invertebrates (in particular insects and amphipods) display adverse effects when exposed to neonicotinoids in the ng/L- to low µg/L-range. In addition to waterborne exposure, in particular leaf-shredding invertebrates (= shredders) might be adversely affected by the introduction of neonicotinoid-contaminated leaves into the aquatic environment since they heavily rely on leaf litter as food source. However, dietary neonicotinoid exposure of aquatic shredders has hardly received any attention from researchers and is not considered during aquatic environmental risk assessment. The primary aim of this thesis is, therefore, (1) to characterize foliar neonicotinoid residues and exposure pathways relevant for aquatic shredders, (2) to investigate ecotoxicological effects of waterborne and dietary exposure on two model shredders, namely Gammarus fossarum (Crustacea, Amphipoda) and Chaetopteryx villosa (Insecta, Trichoptera), and (3) to identify biotic and abiotic factors potentially modulating exposure under field conditions.
During the course of this thesis, ecotoxicologically relevant foliar residues of the neonicotinoids imidacloprid, thiacloprid and acetamiprid were quantified in black alder trees treated at field relevant levels. A worst-case model – developed to simulate imidacloprid water concentrations resulting from an input of contaminated leaves into a stream – predicted only low aqueous imidacloprid concentrations (i.e., ng/L-range). However, the model identified dietary uptake as an additional exposure pathway relevant for shredders up to a few days after the leaves’ introduction into the stream. When test organisms were simultaneously exposed (= combined exposure) to neonicotinoids leaching from leaves into the water and via the consumption of contaminated leaves, adverse effects exceeded those observed under waterborne exposure alone. When exposure pathways were separated using a flow-through system, dietary exposure towards thiacloprid-contaminated leaves caused similar sublethal adverse effects in G. fossarum as observed under waterborne exposure. Moreover, the effect sizes observed under combined exposure were largely predictable using the reference model “independent action”, which assumes different molecular target sites to be affected. Dietary toxicity for shredders might, however, be reduced under field conditions since UV-induced photodegradation and leaching decreased imidacloprid residues in leaves and thereby the toxicity for G. fossarum. In contrast, both shredders were found unable to actively avoid dietary exposure. This thesis thus recommends considering dietary exposure towards systemic insecticides, such as neonicotinoids, already during their registration to safeguard aquatic shredders, associated ecosystem functions (e.g., leaf litter breakdown) and ultimately ecosystem integrity.
Fresh water resources like rivers and reservoirs are exposed to a drastically changing world. In order to safeguard these lentic ecosystems, they need stronger protection in times of global change and population growth. In the last years, the exploitation pressure on drinking water reservoirs has increased steadily worldwide. Besides securing the demands of safe drinking water supply, international laws especially in Europe (EU Water Framework Directive) stipulate to minimize the impact of dams on downstream rivers. In this study we investigate the potential of a smart withdrawal strategy at Grosse Dhuenn Reservoir to improve the temperature and discharge regime downstream without jeopardizing drinking water production. Our aim is to improve the existing withdrawal strategy for operating the reservoir in a sustainable way in terms of water quality and quantity. First, we set-up and calibrated a 1D numerical model for Grosse Dhuenn Reservoir with the open-source community model “General Lake Model” (GLM) together with its water quality module “Aquatic Ecodynamics” library (AED2). The reservoir model reproduced water temperatures and hypolimnetic dissolved oxygen concentrations accurately over a 5 year period. Second, we extended the model source code with a selective withdrawal functionality (adaptive offtake) and added operational rules for a realistic reservoir management. Now the model is able to autonomously determine the best withdrawal height according to the temperature and flow requirements of the downstream river and the raw water quality objectives. Criteria for the determination of the withdrawal regime are selective withdrawal, development of stratification and oxygen content in the deep hypolimnion. This functionality is not available in current reservoir models, where withdrawal heights are generally provided a priori to the model and kept fixed during the simulation. Third, we ran scenario simulations identifying an improved reservoir withdrawal strategy to balance the demands for downstream river and raw water supply. Therefore we aimed at finding an optimal parallel withdrawal ratio between cold hypolimnetic water and warm epilimnetic or metalimnetic water in order to provide a pre-defined temperature in the downstream river. The reservoir model and the proposed withdrawal strategy provide a simple and efficient tool to optimize reservoir management in a multi-objective view for mastering future reservoir management challenges.