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As in many other cities of the Global South, in Accra and its Greater Metropolitan Area (GAMA) water provision for drinking, domestic and productive uses is coproduced by multiple provisioning and delivery modalities. This paper contributes to the overall understanding of sociospatial conditions of urban water (in)security in GAMA. By looking at the geography of infrastructure and inequalities in water access, it seeks to identify patterns of uneven access to water. The first part provides an overview of urban water supply in GAMA, focusing on water infrastructure and the perspective of water providers. In the second part, households’ access strategies are discussed by combining both quantitative and qualitative perspectives. The paper brings together literature research and empirical material collected during fieldwork in the Ghanaian capital city.
External capital plays an important role in financing entrepreneurial ventures, due to limited internal capital sources. An important external capital provider for entrepreneurial ventures are venture capitalists (VCs). VCs worldwide are often confronted with thousands of proposals of entrepreneurial ventures per year and must choose among all of these companies in which to invest. Not only do VCs finance companies at their early stages, but they also finance entrepreneurial companies in their later stages, when companies have secured their first market success. That is why this dissertation focuses on the decision-making behavior of VCs when investing in later-stage ventures. This dissertation uses both qualitative as well as quantitative research methods in order to provide answer to how the decision-making behavior of VCs that invest in later-stage ventures can be described.
Based on qualitative interviews with 19 investment professionals, the first insight gained is that for different stages of venture development, different decision criteria are applied. This is attributed to different risks and goals of ventures at different stages, as well as the different types of information available. These decision criteria in the context of later-stage ventures contrast with results from studies that focus on early-stage ventures. Later-stage ventures possess meaningful information on financials (revenue growth and profitability), the established business model, and existing external investors that is not available for early-stage ventures and therefore constitute new decision criteria for this specific context.
Following this identification of the most relevant decision criteria for investors in the context of later-stage ventures, a conjoint study with 749 participants was carried out to understand the relative importance of decision criteria. The results showed that investors attribute the highest importance to 1) revenue growth, (2) value-added of products/services for customers, and (3) management team track record, demonstrating differences when compared to decision-making studies in the context of early-stage ventures.
Not only do the characteristics of a venture influence the decision to invest, additional indirect factors, such as individual characteristics or characteristics of the investment firm, can influence individual decisions. Relying on cognitive theory, this study investigated the influence of various individual characteristics on screening decisions and found that both investment experience and entrepreneurial experience have an influence on individual decision-making behavior. This study also examined whether goals, incentive structures, resources, and governance of the investment firm influence decision making in the context of later-stage ventures. This study particularly investigated two distinct types of investment firms, family offices and corporate venture capital funds (CVC), which have unique structures, goals, and incentive systems. Additional quantitative analysis showed that family offices put less focus on high-growth firms and whether reputable investors are present. They tend to focus more on the profitability of a later-stage venture in the initial screening. The analysis showed that CVCs place greater importance on product and business model characteristics than other investors. CVCs also favor later-stage ventures with lower revenue growth rates, indicating a preference for less risky investments. The results provide various insights for theory and practice.
A basic assumption of standard small area models is that the statistic of interest can be modelled through a linear mixed model with common model parameters for all areas in the study. The model can then be used to stabilize estimation. In some applications, however, there may be different subgroups of areas, with specific relationships between the response variable and auxiliary information. In this case, using a distinct model for each subgroup would be more appropriate than employing one model for all observations. If no suitable natural clustering variable exists, finite mixture regression models may represent a solution that „lets the data decide“ how to partition areas into subgroups. In this framework, a set of two or more different models is specified, and the estimation of subgroup-specific model parameters is performed simultaneously to estimating subgroup identity, or the probability of subgroup identity, for each area. Finite mixture models thus offer a fexible approach to accounting for unobserved heterogeneity. Therefore, in this thesis, finite mixtures of small area models are proposed to account for the existence of latent subgroups of areas in small area estimation. More specifically, it is assumed that the statistic of interest is appropriately modelled by a mixture of K linear mixed models. Both mixtures of standard unit-level and standard area-level models are considered as special cases. The estimation of mixing proportions, area-specific probabilities of subgroup identity and the K sets of model parameters via the EM algorithm for mixtures of mixed models is described. Eventually, a finite mixture small area estimator is formulated as a weighted mean of predictions from model 1 to K, with weights given by the area-specific probabilities of subgroup identity.
Die räumliche Entwicklung von Städten und Regionen wird durch Trends wie Klimawandel, demographische Veränderungen und Strukturwandel beeinflusst, welche nicht an Verwaltungsgrenzen aufhören, sondern die Entwicklung großflächiger Gebiete bestimmen. Außerdem weisen Grenzräume häufig funktionale und thematische Verflechtungen auf, die über die nationalen Grenzen hinweg bestehen. Damit verbunden sind ein regelmäßiger Austausch und Abhängigkeiten zwischen Grenzräumen und deren Bewohnern. Daher ist die Koordination der grenzüberschreitenden Raumentwicklung entscheidend für eine zukunftsorientierte und nachhaltige räumliche Entwicklung. Aufgrund seiner hohen Bedeutung wird dieses Thema von europäischen Wissenschaftlern in der ersten Ausgabe der Themenhefte Borders in Perspective aus verschiedenen Perspektiven beleuchtet.
This thesis considers the general task of computing a partition of a set of given objects such that each set of the partition has a cardinality of at least a fixed number k. Among such kinds of partitions, which we call k-clusters, the objective is to find the k-cluster which minimises a certain cost derived from a given pairwise difference between objects which end up the same set. As a first step, this thesis introduces a general problem, denoted by (||.||,f)-k-cluster, which models the task to find a k-cluster of minimum cost given by an objective function computed with respect to specific choices for the cost functions f and ||.||. In particular this thesis considers three different choices for f and also three different choices for ||.|| which results in a total of nine different variants of the general problem. Especially with the idea to use the concept of parameterised approximation, we first investigate the role of the lower bound on the cluster cardinalities and find that k is not a suitable parameter, due to remaining NP-hardness even for the restriction to the constant 3. The reductions presented to show this hardness yield the even stronger result which states that polynomial time approximations with some constant performance ratio for any of the nine variants of (||.||,f)-k-cluster require a restriction to instances for which the pairwise distance on the objects satisfies the triangle inequality. For this restriction to what we informally refer to as metric instances, constant-factor approximation algorithms for eight of the nine variants of (||.||,f)-k-cluster are presented. While two of these algorithms yield the provably best approximation ratio (assuming P!=NP), others can only guarantee a performance which depends on the lower bound k. With the positive effect of the triangle inequality and applications to facility location in mind, we discuss the further restriction to the setting where the given objects are points in the Euclidean metric space. Considering the effect of computational hardness caused by high dimensionality of the input for other related problems (curse of dimensionality) we check if this is also the source of intractability for (||.||,f)-k-cluster. Remaining NP-hardness for restriction to small constant dimensionality however disproves this theory. We then use parameterisation to develop approximation algorithms for (||.||,f)-k-cluster without restriction to metric instances. In particular, we discuss structural parameters which reflect how much the given input differs from a metric. This idea results in parameterised approximation algorithms with parameters such as the number of conflicts (our name for pairs of objects for which the triangle inequality is violated) or the number of conflict vertices (objects involved in a conflict). The performance ratios of these parameterised approximations are in most cases identical to those of the approximations for metric instances. This shows that for most variants of (||.||,f)-k-cluster efficient and reasonable solutions are also possible for non-metric instances.
Background and rationale: Changing working conditions demand adaptation, resulting in higher stress levels in employees. In consequence, decreased productivity, increasing rates of sick leave, and cases of early retirement result in higher direct, indirect, and intangible costs. Aims of the Research Project: The aim of the study was to test the usefulness of a novel translational diagnostic tool, Neuropattern, for early detection, prevention, and personalized treatment of stress-related disorders. The trial was designed as a pilot study with a wait list control group. Materials and Methods: In this study, 70 employees of the Forestry Department Rhineland-Palatinate, Germany, were enrolled. Subjects were block-randomized according to the functional group of their career field, and either underwent Neuropattern diagnostics immediately, or after a waiting period of three months. After the diagnostic assessment, their physicians received the Neuropattern Medical Report, including the diagnostic results and treatment recommendations. Participants were informed by the Neuropattern Patient Report, and were eligible to an individualized Neuropattern Online Counseling account. Results: The application of Neuropattern diagnostics significantly improved mental health and health-related behavior, reduced perceived stress, emotional exhaustion, overcommitment and possibly, presenteeism. Additionally, Neuropattern sensitively detected functional changes in stress physiology at an early stage, thus allowing timely personalized interventions to prevent and treat stress pathology. Conclusion: The present study encouraged the application of Neuropattern diagnostics to early intervention in non-clinical populations. However, further research is required to determine the best operating conditions.
Acute social and physical stress interact to influence social behavior: the role of social anxiety
(2018)
Stress is proven to have detrimental effects on physical and mental health. Due to different tasks and study designs, the direct consequences of acute stress have been found to be wide-reaching: while some studies report prosocial effects, others report increases in antisocial behavior, still others report no effect. To control for specific effects of different stressors and to consider the role of social anxiety in stress-related social behavior, we investigated the effects of social versus physical stress on behavior in male participants possessing different levels of social anxiety. In a randomized, controlled two by two design we investigated the impact of social and physical stress on behavior in healthy young men. We found significant influences on various subjective increases in stress by physical and social stress, but no interaction effect. Cortisol was significantly increased by physical stress, and the heart rate was modulated by physical and social stress as well as their combination. Social anxiety modulated the subjective stress response but not the cortisol or heart rate response. With respect to behavior, our results show that social and physical stress interacted to modulate trust, trustworthiness, and sharing. While social stress and physical stress alone reduced prosocial behavior, a combination of the two stressor modalities could restore prosociality. Social stress alone reduced nonsocial risk behavior regardless of physical stress. Social anxiety was associated with higher subjective stress responses and higher levels of trust. As a consequence, future studies will need to investigate further various stressors and clarify their effects on social behavior in health and social anxiety disorders.
Early life adversity (ELA) is associated with a higher risk for diseases in adulthood. Changes in the immune system have been proposed to underlie this association. Although higher levels of inflammation and immunosenescence have been reported, data on cell-specific immune effects are largely absent. In addition, stress systems and health behaviors are altered in ELA, which may contribute to the generation of the "ELA immune phenotype". In this thesis, we have investigated the ELA immune phenotype on a cellular level and whether this is an indirect consequence of changes in behavior or stress reactivity. To address these questions the EpiPath cohort was established, consisting of 115 young adults with or without ELA. ELA participants had experienced separation from their parents in early childhood and were subsequently adopted, which is a standard model for ELA, whereas control participants grew up with their biological parents. At a first visit, blood samples were taken for analysis of epigenetic markers and immune parameters. A selection of the cohort underwent a standardized laboratory stress test (SLST). Endocrine, immune, and cardiovascular parameters were assessed at several time points before and after stress. At a second visit, participants underwent structural clinical interviews and filled out psychological questionnaires. We observed a higher number of activated T cells in ELA, measured by HLA-DR and CD25 expression. Neither cortisol levels nor health-risk behaviors explained the observed group differences. Besides a trend towards higher numbers of CCR4+CXCR3-CCR6+ CD4 T cells in ELA, relative numbers of immune cell subsets in circulation were similar between groups. No difference was observed in telomere length or in methylation levels of age-related CpGs in whole blood. However, we found a higher expression of senescence markers (CD57) on T cells in ELA. In addition, these cells had an increased cytolytic potential. A mediation analysis demonstrated that cytomegalovirus infection " an important driving force of immunosenescence " largely accounted for elevated CD57 expression. The psychological investigations revealed that after adoption, family conditions appeared to have been similar to the controls. However, PhD thesis MMC Elwenspoek 18 ELA participants scored higher on a depression index, chronic stress, and lower on self-esteem. Psychological, endocrine, and cardiovascular parameters significantly responded to the SLST, but were largely similar between the two groups. Only in a smaller subset of groups matched for gender, BMI, and age, the cortisol response seemed to be blunted in ELA participants. Although we found small differences in the methylation level of the GR promoter, GR sensitivity and mRNA expression levels GR as well as expression of the GR target genes FKBP5 and GILZ were similar between groups. Taken together, our data suggest an elevated state of immune activation in ELA, in which particularly T cells are affected. Furthermore, we found higher levels of T cells immunosenescence in ELA. Our data suggest that ELA may increase the risk of cytomegalovirus infection in early childhood, thereby mediating the effect of ELA on T cell specific immunosenescence. Importantly, we found no evidence of HPA dysregulation in participants exposed to ELA in the EpiPath cohort. Thus, the observed immune phenotype does not seem to be secondary to alterations in the stress system or health-risk behaviors, but rather a primary effect of early life programming on immune cells. Longitudinal studies will be necessary to further dissect cause from effect in the development of the ELA immune phenotype.
Academic achievement is a central outcome in educational research, both in and outside higher education, has direct effects on individual’s professional and financial prospects and a high individual and public return on investment. Theories comprise cognitive as well as non-cognitive influences on achievement. Two examples frequently investigated in empirical research are knowledge (as a cognitive determinant) and stress (as a non-cognitive determinant) of achievement. However, knowledge and stress are not stable, what raises questions as to how temporal dynamics in knowledge on the one hand and stress on the other contribute to achievement. To study these contributions in the present doctoral dissertation, I used meta-analysis, latent profile transition analysis, and latent state-trait analysis. The results support the idea of knowledge acquisition as a cumulative and long-term process that forms the basis for academic achievement and conceptual change as an important mechanism for the acquisition of knowledge in higher education. Moreover, the findings suggest that students’ stress experiences in higher education are subject to stable, trait-like influences, as well as situational and/or interactional, state-like influences which are differentially related to achievement and health. The results imply that investigating the causal networks between knowledge, stress, and academic achievement is a promising strategy for better understanding academic achievement in higher education. For this purpose, future studies should use longitudinal designs, randomized controlled trials, and meta-analytical techniques. Potential practical applications include taking account of students’ prior knowledge in higher education teaching and decreasing stress among higher education students.
Water-deficit stress, usually shortened to water- or drought stress, is one of the most critical abiotic stressors limiting plant growth, crop yield and quality concerning food production. Today, agriculture consumes about 80-90% of the global freshwater used by humans and about two thirds are used for crop irrigation. An increasing world population and a predicted rise of 1.0-2.5-°C in the annual mean global temperature as a result of climate change will further increase the demand of water in agriculture. Therefore, one of the most challenging tasks of our generation is to reduce the amount water used per unit yield to satisfy the second UN Sustainable Development Goal and to ensure global food security. Precision agriculture offers new farming methods with the goal to improve the efficiency of crop production by a sustainable use of resources. Plant responses to water stress are complex and co-occur with other environmental stresses under natural conditions. In general, water stress causes plant physiological and biochemical changes that depend on the severity and the duration of the actual plant water deficit. Stomatal closure is one of the first responses to plant water stress causing a decrease in plant transpiration and thus an increase in plant temperature. Prolonged or severe water stress leads to irreversible damage to the photosynthetic machinery and is associated with decreasing chlorophyll content and leaf structural changes (e.g., leaf rolling). Since a crop can already be irreversibly damaged by only mild water deficit, a pre-visual detection of water stress symptoms is essential to avoid yield loss. Remote sensing offers a non-destructive and spatio-temporal method for measuring numerous physiological, biochemical and structural crop characteristics at different scales and thus is one of the key technologies used in precision agriculture. With respect to the detection of plant responses to water stress, the current state-of-the-art hyperspectral remote sensing imaging techniques are based on measurements of thermal infrared emission (TIR; 8-14 -µm), visible, near- and shortwave infrared reflectance (VNIR/SWIR; 0.4-2.5 -µm), and sun-induced fluorescence (SIF; 0.69 and 0.76 -µm). It is, however, still unclear how sensitive these techniques are with respect to water stress detection. Therefore, the overall aim of this dissertation was to provide a comparative assessment of remotely sensed measures from the TIR, SIF, and VNIR/SWIR domains for their ability to detect plant responses to water stress at ground- and airborne level. The main findings of this thesis are: (i) temperature-based indices (e.g., CWSI) were most sensitive for the detection of plant water stress in comparison to reflectance-based VNIR/SWIR indices (e.g., PRI) and SIF at both, ground- and airborne level, (ii) for the first time, spectral emissivity as measured by the new hyperspectral TIR instrument could be used to detect plant water stress at ground level. Based on these findings it can be stated that hyperspectral TIR remote sensing offers great potential for the detection of plant responses to water stress at ground- and airborne level based on both TIR key variables, surface temperature and spectral emissivity. However, the large-scale application of water stress detection based on hyperspectral TIR measures in precision agriculture will be challenged by several problems: (i) missing thresholds of temperature-based indices (e.g., CWSI) for the application in irrigation scheduling, (ii) lack of current TIR satellite missions with suitable spectral and spatial resolution, (iii) lack of appropriate data processing schemes (including atmosphere correction and temperature emissivity separation) for hyperspectral TIR remote sensing at airborne- and satellite level.