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The establishment of aquatic alien species can strongly affect community and food web structure of the invaded systems and thus represents a major threat to native biodiversity. One of the most important aquatic invasive species in European rivers is the Ponto-Caspian amphipod Dikerogammarus villosus. The species invaded most of the major European waterways within two decades, often associated with a decline of many other macroinvertebrate species, including other amphipods. Based on laboratory results predation by the so called ‘killer shrimp’ is often regarded as the key driver for observed displacement effects, but recent studies indicated a minor relevance of predation by D. villosus in the field. To allow the determination of exact predator-prey interactions from field samples, I established 22 group-specific rDNA primers for freshwater taxa suitable for prey species identification in dietary samples (Chapter II) and an approach for the screening of D. villosus gut contents using 16 of these primers. Combining genetic gut content analyses, with one of these primers, and stable isotope analyses, I examined the importance of intraguild predation (IGP) by D. villosus, which is often assumed the key driver for the displacement of native amphipod species, at an invasion front of the species in Switzerland (Chapter III). The results of this study revealed a low importance of IGP during this particular D. villosus invasion and indicated an overall sparsely predacious feeding behaviour of the species. As the feeding behaviour of D. villosus is supposed to differ between habitats and this study was only conducted at a few sampling sites of one river, I also investigated the role of predation by D. villosus at multiple sites of the River Rhine system, covering a broad range of microhabitats (Chapter IV). In keeping with the results from the invasion front results of this study strongly indicated a sparsely predacious feeding but rather a flexible feeding behaviour of D. villosus even within the same microhabitat.
However, established populations of D. villosus have changed aquatic food webs and can be expected to affect aquatic-terrestrial energy fluxes. In Chapter V of my thesis, I present a field study investigating the impact of D. villosus on the diet of two riparian spider taxa. The results of this study indicate an effect of D. villosus on the terrestrial food web via cross-ecosystem resource flow.
In conclusion, D. villosus influences terrestrial food webs by altering cross-ecosystem resource fluxes, but it is rather an opportunistic omnivore than a predator in the field.
The application of pesticides to agricultural areas can result in transport to adjacent non-target environments. In particular, surface water systems are likely to receive agricultural pesticide input. When pesticides enter aquatic environments, they may pose a substantial threat to the ecological integrity of surface water systems. To minimize the risk to non-target ecosystems the European Union prescribes an ecotoxicological risk assessment within the registration procedure of pesticides, which consists of an effect and an exposure assessment.
This thesis focuses on the evaluation of the exposure assessment and the implications to the complete regulatory risk assessment, and is based on four scientific publications. The main part of the thesis focuses on evaluation of the FOCUS modelling approach, which is used in regulatory risk assessment to predict pesticide surface water concentrations. This was done by comparing measured field concentrations (MFC) of agricultural insecticides (n = 466) and fungicides (n = 417) in surface water to respective predicted environmental concentrations (PEC) calculated with FOCUS step 1 to step 4 at two different levels of field relevance. MFCs were extracted from the scientific literature and were measured in field studies conducted primarily in Europe (publications 1 and 3).
In addition, an alternative fugacity-based multimedia mass-balance model, which needs fewer input parameters and less computing effort, was used to calculate PECs for the same insecticide MFC dataset and compared to the FOCUS predictions (publication 3). Furthermore, FOCUS predictions were also conducted for veterinary pharmaceuticals in runoff from an experimental plot study, to assess the FOCUS predictions for a different class of chemicals with a different relevant entry pathway (publication 2).
In publication 4, the FOCUS step-3 approach was used to determine relevant insecticide exposure patterns. These patterns were analysed for different monitoring strategies and the implications for the environmental risk assessment (publication 4).
The outcome of this thesis showed that the FOCUS modelling approach is neither protective nor appropriate in predicting insecticide and fungicide field concentrations. Up to one third of the MFCs were underpredicted by the model calculations, which means that the actual risk might be underestimated. Furthermore, the results show that a higher degree of realism even reduces the protectiveness of model results and that the model predictions are worse for highly hydrophobic and toxic pyrethroids.
In addition, the absence of any relationship between measured and predicted concentrations questions the general model performance quality (publication 1 and 3). Further analyses revealed that deficiencies in protectiveness and predictiveness of the environmental exposure assessment might even be higher than shown in this thesis, because actual short-term peak concentrations are only detectable with an event-related sampling strategy (publication 4). However, it was shown that the PECs of a much simpler modelling approach are much more appropriate for the prediction of insecticide MFC, especially for calculations with a higher field relevance (publication 3). The FOCUS approach also failed to predict concentrations of veterinary pharmaceuticals in runoff water (publication 2). In conclusion, the findings of this thesis showed that there is an urgent need for the improvement of exposure predictions conducted in the environmental risk assessment of pesticides as a group of highly relevant environmental chemicals, to ensure that the increasing use of those chemicals does not lead to further harmful effects in aquatic ecosystems.
This thesis presents novel approaches for integrating context information into probabilistic models. Data from social media is typically associated with metadata, which includes context information such as timestamps, geographical coordinates or links to user profiles. Previous studies showed the benefits of using such context information in probabilistic models, e.g.\ improved predictive performance. In practice, probabilistic models which account for context information still play a minor role in data analysis. There are multiple reasons for this. Existing probabilistic models often are complex, the implementation is difficult, implementations are not publicly available, or the parameter estimation is computationally too expensive for large datasets. Additionally, existing models are typically created for a specific type of content and context and lack the flexibility to be applied to other data.
This thesis addresses these problems by introducing a general approach for modelling multiple, arbitrary context variables in probabilistic models and by providing efficient inference schemes and implementations.
In the first half of this thesis, the importance of context and the potential of context information for probabilistic modelling is shown theoretically and in practical examples. In the second half, the example of topic models is employed for introducing a novel approach to context modelling based on document clusters and adjacency relations in the context space. They can cope with areas of sparse observations and These models allow for the first time the efficient, explicit modelling of arbitrary context variables including cyclic and spherical context (such as temporal cycles or geographical coordinates). Using the novel three-level hierarchical multi-Dirichlet process presented in this thesis, the adjacency of ontext clusters can be exploited and multiple contexts can be modelled and weighted at the same time. Efficient inference schemes are derived which yield interpretable model parameters that allow analyse the relation between observations and context.
How entrepreneurs become successful with their business ideas has been a topic of discussion within entrepreneurial research circles for many years. Business success has been related to psychological characteristics and many research findings have explained how people become entrepreneurs and furthermore, how they find success in regards to their business ventures. People always wanted to know what defines an entrepreneur and more importantly, what is needed to become a successful entrepreneur. Curious minds began to search for the recipe for success. Personality Traits have been researched for years, leading to the discovery of many diverse and distinct forms which are still recognized today. Researchers compared the Behavioral Approach or the analysis of demographical characteristics to success.
This raises the question of what an entrepreneur needs to become successful which is made more difficult due to the fact that entrepreneurship and who an entrepreneur is can be difficult do define exactly. Entrepreneurs are diverse and distinct individuals that each possess their own characteristics, behavior and reasons for starting a business. Many people assume that it is just someone who starts their own business. While partially correct, this only scratches the surface of what it is to be an entrepreneur.
This thesis answers the following three research questions: 1. Which personality traits were found in the almost sixty years of researching? 2. What triggers do entrepreneurs need for starting a new business? 3. Which factor makes the entrepreneur successful with their business idea? Also, reading the thesis, one may gain a better understanding of what entrepreneurship is, what defines an entrepreneur and what one needs to become a successful entrepreneur.
In this thesis the reviewing literature method developed by Wolfswinkel et al. (2011) was used to identify suitable literature and references for the main chapters. For that the five stages of the grounded-theory method for reviewing the literature were used in an iterative fashion. In step one inclusion and exclusion criterias for literature were defined. Then literature was searched matching the criterias of step one. In step three the samples were refined. Then in step four the found literature was analyzed and coded before the results of this research was presented in the following text. Many entrepreneurial personality traits were discovered and confirmed during the studies conducted over the last sixty years, these include but are not limited to Need for Achievement, Locus of Control, or risk taking propensity. Motivation is clearly the main trigger to start your own business. During the studies reasons were discovered of how and why an entrepreneur may become successful outside of posessing the right combination of traits. For example: having human, financial and social capital, an entrepreneurial behavior and the right economic conditions to start a business that will survive for more than five years.
Confidentiality, integrity, and availability are often listed as the three major requirements for achieving data security and are collectively referred to as the C-I-A triad. Confidentiality of data restricts the data access to authorized parties only, integrity means that the data can only be modified by authorized parties, and availability states that the data must always be accessible when requested. Although these requirements are relevant for any computer system, they are especially important in open and distributed networks. Such networks are able to store large amounts of data without having a single entity in control of ensuring the data's security. The Semantic Web applies to these characteristics as well as it aims at creating a global and decentralized network of machine-readable data. Ensuring the confidentiality, integrity, and availability of this data is therefore also important and must be achieved by corresponding security mechanisms. However, the current reference architecture of the Semantic Web does not define any particular security mechanism yet which implements these requirements. Instead, it only contains a rather abstract representation of security.
This thesis fills this gap by introducing three different security mechanisms for each of the identified security requirements confidentiality, integrity, and availability of Semantic Web data. The mechanisms are not restricted to the very basics of implementing each of the requirements and provide additional features as well. Confidentiality is usually achieved with data encryption. This thesis not only provides an approach for encrypting Semantic Web data, it also allows to search in the resulting ciphertext data without decrypting it first. Integrity of data is typically implemented with digital signatures. Instead of defining a single signature algorithm, this thesis defines a formal framework for signing arbitrary Semantic Web graphs which can be configured with various algorithms to achieve different features. Availability is generally supported by redundant data storage. This thesis expands the classical definition of availability to compliant availability which means that data must only be available as long as the access request complies with a set of predefined policies. This requirement is implemented with a modular and extensible policy language for regulating information flow control. This thesis presents each of these three security mechanisms in detail, evaluates them against a set of requirements, and compares them with the state of the art and related work.
Die vorliegende Arbeit behandelt Techniken zur interakativen und physikalisch basierten Darstellung von Haaren für Computer-Generated Imagery (CGI). Dafür werden Techniken zur Simulation und Approximierung der Interaktionen von Licht mit Haar hergeleitet und vorgestellt. Des Weiteren wird beschrieben, wie Haare, trotz solch berechnungsintensiver Algorithmen, sehr interaktiv dargestellt werden können. Verfahren zur Berechnung von Schatten in Haaren sowie Ansätze zur effizienten Darstellung von Haar als transparente Geometrie werden ebenfalls vorgestellt. Einen Hauptschwerpunkt der Arbeit bildet dabei der DBK-Buffer, welcher im Rahmen dieser konzeptioniert, implementiert und evaluiert wurde. Mit Hilfe des DBK-Buffers ist es möglich tausende von transparenten Haaren sehr effizient darzustellen ohne auf Funktionalitäten der neusten Grafikkarten-Generation, oder sehr viel Videospeicher, angewiesen zu sein. Darüber hinaus wurde eine umfassende Evaluierung der beschriebenden Techniken bezüglich der visuellen Qualität, der Performanz und des Speicheraufwandes durchgeführt. Dabei wurde gezeigt, dass Haare nicht nur mit interaktiven, sondern sogar mit echtzeitfähigen Bildwiederholungsraten physikalisch basiert dargestellt werden können.
The largest population of the anadromous Allis shad (A. alosa) of the 19th century was found in River Rhine and has to be considered extinct today. To facilitate the return of A. alosa into River Rhine an EU LIFE-project was initiated in 2007. The overall objective of this thesis was to assist aquaculture and stocking-measures at River Rhine, as well as to support restoration and conservation of populations of Allis shad in Europe.
By culturing the free-swimming nematode T. aceti in a solution of cider vinegar we developed a cost-effective live food organism for the larviculture of fish. As indicated by experiments with C. maraena, T. aceti cannot be regarded as an alternative to Artemia nauplii. However it has to be considered a suitable supplemental feed in the early rearing of C. maraena by providing essential fatty acids, thereby optimizing growth.
Also mass-marking practices with Oxytetracycline, as they are applied in the restocking of Allis shad have been evaluated. In experiments with D. rerio we demonstrated that water hardness can detrimentally affect mortality during marking and has to be considered crucial in the development of marking protocols for freshwater fish.
In order to get independent from wild spawners an ex-situ Broodstock-facility for Allis shad was established in 2011. Upon examination of two complete year classes of this broodstock, we found a high prevalence of various malformations, which could be traced back to distinct cysts developing one month post hatch. Despite applying a variety of clinical tests we could not identify any infectious agents causing these malformations. The observed malformations are probably a consequence of suboptimal feeding practices or the properties of the physio-chemical rearing environment.
The decline of stocks of A. alosa in Europe has been largely explained with the increase of river temperatures as a consequence of global warming. By investigating the temperature physiology of larval Allis shad we demonstrated that A. alosa ranges among the most thermo-tolerant species in Europe and that correlations between rising temperatures and the disappearance of this species have to be understood in a synecological context and by integrating a variety of stressors other than temperature. By capturing and examining juvenile and adult Allis shad from River Rhine, we demonstrated the first natural reproduction of A. alosa in River Rhine since nearly 100 years and the success of stocking measures within the framework of the LIFE project.
Six and Gimmler have identified concrete capabilities that enable users to use the Internet in a competent way. Their media competence model can be used for the didactical design of media usage in secondary schools. However, the special challenge of security awareness is not addressed by the model. In this paper, the important dimension of risk and risk assessment will be introduced into the model. This is especially relevant for the risk of the protection of personal data and privacy. This paper will apply the method of IT risk analysis in order to select those dimensions of the Six/Gimmler media competence model that are appropriate to describe privacy aware Internet usage. Privacy risk aware decisions for or against the Internet usage is made visible by the trust model of Mayer et al.. The privacy extension of the competence model will lead to a measurement of the existing privacy awareness in secondary schools, which, in turn, can serve as a didactically well-reasoned design of Informatics modules in secondary schools. This paper will provide the privacy-extended competence model, while empirical measurement and module design is planned for further research activities.
Statistical Shape Models (SSMs) are one of the most successful tools in 3Dimage analysis and especially medical image segmentation. By modeling the variability of a population of training shapes, the statistical information inherent in such data are used for automatic interpretation of new images. However, building a high-quality SSM requires manually generated ground truth data from clinical experts. Unfortunately, the acquisition of such data is a time-consuming, error-prone and subjective process. Due to this effort, the majority of SSMs is often based on a limited set of this ground truth training data, which makes the models less statistically meaningful. On the other hand, image data itself is abundant in clinics from daily routine. In this work, methods for automatically constructing a reliable SSM without the need of manual image interpretation from experts are proposed. Thus, the training data is assumed to be the result of any segmentation algorithm or may originate from other sources, e.g. non-expert manual delineations. Depending on the algorithm, the output segmentations will contain errors to a higher or lower degree. In order to account for these errors, areas of low probability of being a boundary should be excluded from the training of the SSM. Therefore, the probabilities are estimated with the help of image-based approaches. By including many shape variations, the corrupted parts can be statistically reconstructed. Two approaches for reconstruction are proposed - an Imputation method and Weighted Robust Principal Component Analysis (WRPCA). This allows the inclusion of many data sets from clinical routine, covering a lot more variations of shape examples. To assess the quality of the models, which are robust against erroneous training shapes, an evaluation compares the generalization and specificity ability to a model build from ground truth data. The results show, that especially WRPCA is a powerful tool to handle corrupted parts and yields to reasonable models, which have a higher quality than the initial segmentations.
We are entering the 26th year from the time the World Wide Web (WWW) became reality. Since the birth of the WWW in 1990, the Internet and therewith websites have changed the way businesses compete, shifting products, services and even entire markets.
Therewith, gathering and analysing visitor traffic on websites can provide crucial information to un- derstand customer behavior and numerous other aspects.
Web Analytics (WA) tools offer a quantity of diverse functionality, which calls for complex decision- making in information management. Website operators implement Web Analytic tools such as Google Analytics to analyse their website for the purpose of identifying web usage to optimise website design and management. The gathered data leads to emergent knowledge, which provides new marketing opportunities and can be used to improve business processes and understand customer behavior to increase profit. Moreover, Web Analytics plays a significant role to measure performance and has therefore become an important component in web-based environments to make business decisions.
However, many small and medium –sized enterprises try to keep up with the web business competi- tion, but do not have the equivalent resources in manpower and knowledge to stand the pace, there- fore some even resign entirely on Web Analytics.
This research project aims to develop a Web Analytics framework to assist small and medium-sized enterprises in making better use of Web Analytics. By identifying business requirements of SMEs and connecting them to the functionality of Google Analytics, a Web Analytics framework with attending guidelines is developed, which guides SMEs on how to proceed in using Google Analytics to achieve actionable outcomes.
This study had two main aims. The first one was to investigate the quality of lesson plans. Two important features of lesson plans were used as a basis to determine the quality of lesson plans. These are adaptability to preconditions and cognitive activation of students. The former refers to how the planning teacher considers the diversity of students pre-existing knowledge and skills. The latter refers to how the planning teacher sequences deep learning tasks and laboratory activities to promote the cognitive activation of students.
The second aim of the study was to explore teachers thinking about and explanation of externally generated feedback data on their students’ performance. The emphasis here was to understand how the teachers anticipate planning differentiated lessons to accommodate the variations in students learning outcomes revealed by the feedback data.
The study followed a qualitative approach with multiple sources of data. Concept maps, questionnaires, an online lesson planning tool, standardized tests, and semi-structured interviews were the main data collection instruments used in the study. Participants of this study were four physics teachers teaching different grade levels. For the purpose of generating feedback for the participant teachers, a test was administered to 215 students. Teachers were asked to plan five lessons for their ongoing practices. The analysis showed that the planned lessons were not adapted to the diversity in students pre-existing knowledge and skills. The analysis also indicated that the lessons planned had limitations with regard to cognitive activation of students. The analysis of the interview data also revealed that the participant teachers do not normally consider differentiating lessons to accommodate the differences in students learning, and place less emphasis on the cognitive activation of students. The analysis of the planned lessons showed a variation in teachers approach in integrating laboratory activities in the sequence of the lessons ranging from a complete absence through a demonstrative to an investigative approach. Moreover, the findings from the interviews indicated differences between the participant teachers espoused theory (i.e. what they said during interview) and their theory- in –use (i.e. what is evident from the planned lessons). The analysis of the interview data demonstrated that teachers did not interpret the data, identify learning needs, draw meaningful information from the data for adapting (or differentiating) instruction. They attributed their students’ poor performance to task difficulty, students’ ability, students’ motivation and interest. The teachers attempted to use the item level and subscale data only to compare the relative position of their class with the reference group. However, they did not read beyond the data, like identifying students learning needs and planning for differentiated instruction based on individual student’s performance.
Agriculture covers one third of the world land area and has become a major source of water pollution due to its heavy reliance on chemical inputs, namely fertilisers and pesticides. Several thousands of tonnes of these chemicals are applied worldwide annually and partly reach freshwaters. Despite their widespread use and relatively unspecific modes of action, fungicides are the least studied group of pesticides. It remains unclear whether the taxonomic groups used in pesticide risk assessment are protective for non-target freshwater fungi. Fungi and bacteria are the main microbial decomposers converting allochthonous organic matter (litter) into a more nutritious food resource for leaf-shredding macroinvertebrates. This process of litter decomposition (LD) is central for aquatic ecosystem because it fuels local and downstream food webs with energy and nutrients. Effects of fungicides on decomposer communities and LD have been mainly analysed under laboratory conditions with limited representation of the multiple factors that may moderate effects in the field.
In this thesis a field study was conducted in a German vineyard area to characterise recurrent episodic exposure to fungicides in agricultural streams (chapter 2) and its effects on decomposer communities and LD (chapter 3). Additionally, potential interaction effects of nutrient enrichment and fungicides on decomposer communities and LD were analysed in a mesocosm experiment (chapter 4).
In the field study event-driven water sampling (EDS) and passive sampling with EmporeTM styrene-divinylbenzene reverse phase sulfonated disks (SDB disks) were used to assess exposure to 15 fungicides and 4 insecticides. A total of 17 streams were monitored during 4 rainfall events within the local application period of fungicides in 2012. EDS exceeded the time-weighted average concentrations provided by the SDB disks by a factor of 3, though high variability among compounds was observed. Most compounds were detected in more than half of the sites and mean and maximum peak (EDS) concentrations were under 1 and 3 µg/l, respectively. Besides, SDB disk-sampling rates and a free-software solution to derive sampling rates under time-variable exposure were provided.
Several biotic endpoints related to decomposers and LD were measured in the same sampling sites as the fungicide monitoring, coinciding with the major litter input period. Our results suggest that polar organic fungicides in streams change the structure of the fungal community. Causality of this finding was supported by a subsequent microcosm experiment. Whether other effects observed in the field study, such as reduced fungal biomass, increased bacterial density or reduced microbial LD can be attributed to fungicides remains speculative and requires further investigation. By contrast, neither the invertebrate LD nor in-situ measured gammarid feeding rates correlated with water-borne fungicide toxicity, but both were negatively associated with sediment copper concentrations. The mesocosm experiment showed that fungicides and nutrients affect microbial decomposers differently and that they can alter community structure, though longer experiments are needed to determine whether these changes may propagate to invertebrate communities and LD. Overall, further studies should include representative field surveys in terms of fungicide pollution and physical, chemical and biological conditions. This should be combined with experiments under controlled conditions to test for the causality of field observations.
Aktuelle Schätzungen bestätigten, dass Binnengewässer eine erhebliche Menge Methan (CH4) und Kohlendioxid (CO2) sowohl auf regionaler Ebene, als auch global freisetzen. Jedoch basieren diese Schätzungen auf extrapolierten gemessenen Daten, ungenügender Auflösung der räumlich-zeitlichen Variabilität und es mangelt an Daten aus ariden und semi-ariden Gebieten, sowie den Kohlestoffquellen aus Kläranlagen.
Für die hier vorliegende Studie analysierten wir monatliche hydrologische und meteorologische Daten sowie Daten zur Wasserqualität von drei Stauseen aus dem Gebiet des unteren Jordans, die zur Trinkwassergewinnung und zur Bewässerung genutzt werden, und schätzten damit deren Emissionsrate an CO2 ab. Wir untersuchten den Effekt von Kläranlagen auf die umliegenden Gewässer im Hinblick auf CH4 und CO2-Emissionen indem wir saisonal aufgelöste Daten der Konzentration der beiden gelösten Gase in Kläranlagenauslässen und in Vorflutern von neun Kläranlagen in Deutschland analysierten. Mithilfe von Low-Cost-Methoden die die CO2-Transportrate und die Ausgasungsrate über Gasblasen messen, untersuchten wir die räumliche und zeitliche Variabilität der CH4 und CO2-Emissionen von aquatischen Süßwasser-Ökosystemen.
Unsere Schätzungen zeigen, dass Stauseen in semi-ariden Regionen CO2 übersättigt sind und somit CO2 an die Atmosphäre abgeben, also eine Netto-Quelle sind.
Die Größenordnung der beobachteten Transportraten der drei jordanischen Stauseen ist vergleichbar mit denen von tropischen Stauseen (3,3 g CO2 m-2 Tag-1). Die CO2-Emissionsrate ist abhängig von Änderungen der Wasseroberfläche, welche durch den Betrieb der Stauseen verursacht sind. Kläranlagen entlassen eine beachtlichen Menge an CH4 (30.9±40.7 kg Jahr-1) und CO2 (0.06±0.05 Gg Jahr-1) in ihre umgebenden Flüsse und Bäche. Deren Emissionsraten sind durch diese Einleitung der Kläranlagen um 1,2-fach für CH4 oder 8,6-fach für CO2 erhöht. Unsere Ergebnisse zeigen, dass sowohl die diffusive als auch die Gasblasenemissionsrate räumlich und zeitlich variabel ist, weshalb beide Emissionsraten bei zukünftigen Studien auch in der nötigen Auflösung gemessen werden sollten.
Wir schlussfolgern, dass bei zukünftigen Emissionsmessungen und –schätzungen von Binnengewässern auch die Gewässerbewirtschaftung, die Kohlenstoffquelle von Kläranlagen und die räumliche und zeitliche Variabilität der Emissionen beachtet werden sollten.
Five personality traits commonly known as the “Big Five” have been widely acknowledged as universal. But most available psychological instruments are not necessarily transferable to other cultures. They are referred to as “W.E.I.R.D.” (western, educated, industrial, rich, democratic) and lack the combined emic-etic approach that is necessary for a transcultural perspective. This intercontinental congress brings experts from Kenya and Germany together – thinking out of the box and collecting ideas for a scientific based partnership of East Africa and Europe. Main topics are psychological constructs that prove relevant for Human Resources Management. The Five-Factor Model, core self-evaluations, coping processes and acculturation as well as globalization effects and gender issues are discussed.