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In the study, predictive models for predicting therapy outcome are created using the dataset from E-COMPARED project, which belongs to the so-called type 3 models that use data from the intervention and preintervention phases to predict treatment outcomes, which can help to adapt intervention to maximize treatment. The predictive models aim to classify patients into two groups, improved and nonimproved. Since it is important to determine whether the models contribute to improvement of treatment, research questions that can contribute to the usage of type 3 models are established. The study focuses on the following three questions: (1) How accurately can the therapy outcome be predicted by various machine learning algorithms? Answering this question can let the people concerned obtain information about the reliability of contemporary predictive models. In addition, if the predictive power of the models is good, it is more likely to be used to assist therapists’ decisions. (2) Which kind of data is more important in predicting the therapy outcome? The answer to this question can show which dataset should be considered first to make better predictive models. Therefore, it can be helpful for researchers who want to make predictive models in the future and eventually help to facilitate personalized therapy. (3) What are the features with strong predictive power? The answer to this question can affect the people concerned, especially therapists. Therapists can use the most influential features revealed to adjust and improve future treatments.
To respond to the challenges of the Anthropocene, scholars from various disciplines increasingly emphasize that a mere outer transformation is insufficient and that we also need an inner transformation that addresses deep leverage points. Yet, the open questions are how the inner and outer dimensions relate to each other and how inner transformation might lead to outer transformation. How we attempt to answer these questions is determined by our dominant paradigm. Paradigms define how we understand and shape the world, and thus, they define how we conceptualize challenges, such as inner and outer transformation. Various authors argue that the dominant paradigm, which is characterized by reductionism, empiricism, dualism, and determinism, might be a root cause for insufficiently addressing sustainability challenges. As an alternative, many argue for a relational paradigm, which understands complex phenomena in terms of constitutive processes and relations. A relational paradigm might offer possibilities to reconceptualize inner and outer transformation in the Anthropocene and might shed new light on how to integrate both in sustainability science. Yet, it is still being determined how a relational paradigm can contribute to the understanding of inner and outer transformations towards sustainability in the Anthropocene. Therefore, this dissertation's overarching scope is to contribute to systems change towards a more social-ecological future by generating insights into and exploring possibilities of a relational paradigm for inner and outer transformation in the Anthropocene. This thesis is divided into three sub-questions. The first research question aims to increase the theoretical understanding of a relational paradigm. The second research question aims to develop a transformative educational case study grounded in a relational, justice-oriented approach. The third research question aims to analyze how a relational paradigm might contribute to policies and practices for sustainable lifestyles. The results indicate that inner and outer transformation in the Anthropocene can be reconceptualized as paradigm-ing relationality in the Ecocene. "Paradigm-ing" as an active verb, reconceptualizes inner and outer transformation into ontologies, epistemologies, ethics, and socialecological realities that are ongoing, nonhierarchical, nonlinear, dynamic, co-creative processes of intra-action. The Ecocene decenters the human and attends to what we might be able to intra-actand become-with. These insights can offer unexplored perspectives to address sustainability challenges and increase our capacities to respond in novel ways.
This research report presents a transdisciplinary student research project on developing climate resilience of communities in Marine Protected Areas in the Lesser Antilles. For the second time, the Leuphana University Lüneburg and the Sustainable Marine Financing Programme (SMF) of the Deutsche Gesellschaft für internationale Zusammenarbeit (GIZ) partnered up. The first project on the Caribbean Island Dominica showed that community resilience is a complex concept that is not yet well understood. Building on these findings, this year’s project broadened the scope in addressing the effect of varying local conditions on climate resilience on four different Caribbean islands: Dominica, Grenada, St Lucia, and St. Vincent and the Grenadines. For the GIZ, the research project aimed at improving the understanding of the socio-ecological resilience framework for tackling problems of Marine Managed Areas (MMA) and Marine Protected Areas (MPA). Also, it enabled new thoughts on how the GIZ and other development agencies can more effectively assist island states to better cope with the challenges of climate change. The role of the students from the “Global Environmental and Sustainability Sciences” programme of Leuphana University included the design of four transdisciplinary research projects to study the effect of varying local conditions in disaster-prone regions in the Southern Caribbean on climate resilience. The developing island states in the Caribbean are extremely vulnerable to more frequent and intense natural hazards while relying on ecosystem services that are threatened by extreme weather events, in particular Hurricanes. After such adverse events, low economic stability leads to a dependency of the states on international assistance. To decrease the vulnerability to shocks, counteracting measures that encourage learning and adaptation can increase the resilience against extreme weather events and their consequences. Concepts that were considered during the design of the transdisciplinary research projects were the adaptation of systems, diversity and stakeholder participation and resilience-focused management systems. Building on the results from last year in Dominica, the establishment of a four islands design allowed for greater comparison to better understand community approaches to solve a concrete sustainability problem: securing livelihoods while protecting natural and cultural resources. The research methods of a literature review, stakeholder mapping, semi-structured interviews, scenario development and visioning were used in the projects. A comparison of the four TD projects revealed four overarching lessons. First, all countries recognise a need for restoration and conservation projects, i.e., nature-based solutions implemented and managed by the local community in the MPA. Furthermore, all four cases show that the limited participation of local people in the management and organisation of the MPA is a factor constraining community resilience. Third, this TD project highlights the importance to distinguish climate change as an event or as a process. When climate change occurs as a series of disaster events (e.g., hurricanes, floodings, and heatwaves) in combination with s gradual degradation of natural ecosystems (e.g., coral bleaching and ocean warming), people in MPA communities show highly adaptive and restorative behaviour. Finally, this project was an attempt to realize a cross-cultural and virtual transdisciplinary project. The research approach of transdisciplinarity links different academic disciplines and concepts, and non-scientific stakeholders are included to find solutions for societal and related scientific problems. A major learning was that in virtual TD projects particular attention needs to be paid to setting clear boundaries and be explicit about success criteria. Nonetheless, the findings of the projects provide valuable learning lessons to be applied in practice and that can prove useful for future research.
Protected areas are an essential tool for conserving biodiversity. However, their ecological effectiveness is contested and their capacity to resist human pressures differ. This dissertation aimed to assess the ecological effectiveness of different protection levels (from strict to less strictly protected: national park, game reserve, forest reserve, game-controlled area, and unprotected areas) in biodiversity (both mega diverse butterflies and mammals), maintaining habitat connectivity, and reducing anthropogenic threats at the wider landscape in the Katavi-Rukwa Ecosystem of southwestern Tanzania. To achieve this overarching goal, the researcher employed an interdisciplinary approach. First, he analyzed butterfly diversity and community composition patterns across protection levels in the Katavi-Rukwa Ecosystem. He found that species richness and abundance were highest in the game reserves and game-controlled areas, intermediate in the forest reserves, national park and unprotected areas. Species composition differed significantly among protection levels. Landscape heterogeneity, forest cover, and primary productivity influenced species composition. Land-use, burned areas, forest cover, and primary productivity explained the richness of species and functional traits. Game reserves hosted most indicator species. Second, the author modelled the spatial distribution of six large mammal target species (buffalo Syncerus caffer, elephant Loxodonta africana, giraffe Giraffa camelopardalis, hartebeest Alcelaphus buselaphus, topi Damaliscus korrigum, and zebra Equus burchellii) across environmental and protection gradients in the Katavi-Rukwa Ecosystem. Based on species-specific density surface models, he found relatively consistent effects of protection level and land-use variables on the spatial distribution of the target mammal species: relative densities were highest in the national park and game reserves, intermediate in forest reserves and game-controlled areas and lowest in un-protected areas. Beyond species-specific environmental predictors for relative densities, the results highlight consistent negative associations between relative densities of the target species and distance to cropland and avoidance of areas in proximity to houses. Third, the author examined temporal changes in land-use, population densities and distribution of six large mammal target species across protection levels between 1991 and 2018. During the surveyed period, cropland increased. Wildlife densities of most, but not all target species declined across the entire landscape. Based on logistic regression models, target species preferred the national park over less strictly protection levels and areas distant to cropland. Fourth, he quantified land-use changes, modelled habitat suitability and connectivity of elephant over time across a large protected area network in southwestern Tanzania. Based on analyses of remotely-sensed data, cropland increased from 7% in 2000 to 13% in 2019. Based on ensemble models, distance from cropland influenced survey-specific habitat suitability for elephant the most. Despite cropland expansion, the locations of the modelled elephant corridors (n=10) remained similar throughout the survey period. Based on circuit theory, the author prioritizes three corridors for protected area connectivity. Key indicators of corridor quality varied over time, whereas elephant movement through some corridors appears to have increased over time. Overall, this dissertation underpins differences in ecological effectiveness of protected areas within one ecosystem. It highlights the need to utilize a landscape conservation approach to guide effective conservation across the entire protection gradient. It also suggests the need to enforcing land use plans and having alternative and sustainable forms for generating income from the land without impairing wildlife habitat.
The significance of selecting suitable talent
A company’s success is significantly influenced by the professionalism and quality of decision-making, especially selecting decisions to hire suitable talent. The term “talent” can be taken to mean as someone who has talent (talent as the sum of one’s abilities) and someone who is a talent. Leadership talent makes a difference in organizational success, has the potential to succeed as a leader, and thus will
hold corresponding pivotal positions. In this book, we focus on the selection and acquisition of leadership talent, since such talent is more difficult to find in the market and, at the same time, more challenging to select. Selecting these talented individuals is one of the most critical components of effective organizations. Hardly any other corporate decision has such significant effects on corporate success as talent selection. Recruiting and personnel selection are also the first steps in promoting capability building and creating successful teams. For example, Warren Buffet, renowned for his investing prowess, says, “I have only two jobs. One is to attract and keep outstanding managers to run our various operations”. This highlights the need for an effective and efficient personnel selection process and to improve the diagnostic performance of such procedures. In addition, the increasing diversity of applicants, global competitiveness, and the lack of qualified personnel in specific labor and job markets also increase the importance of high-quality personnel selection processes.