The new mobility paradigm: transformation of value chain and business models

We would like to thank Philipp Schwarz and Julia Gückel for their dedicated support in preparing this paper and our colleagues and students of the School of Engineering and the Business School for our fruitful discussions.

Participatory Surveillance and Mathematical Models in Epidemiologic Research: Successes and Challenges

Theoretical epidemiology aims to understand the dynamics of diseases in populations and communities. Biological and behavioral processes are abstracted into mathematical formulations which aim to reproduce epidemiological observations. In this thesis a new system for the self-reporting of syndromic data — Influenzanet — is introduced and assessed. The system is currently being extended to address greater challenges of monitoring the health and well-being of tropical communities.(...)

Chimpanzees and supporting models in the study of malaria pre-erythrocytic stages

Chimpanzees are being used in the study of immune response to Plasmodium falciparum malaria pre-erythrocytic stages (MPES). Responses induced by immunisation with recombinant/synthetic antigens and by irradiated sporozoites are being evaluated in a model system that is phylogenetically close to humans and that is amenable to limited manipulation not possible in humans. The value of chimpanzees for the in-depth study of immunological mechanisms at work in MPES-induced protection are discussed. A total number of 7 chimpanzees have been used to evaluate the immune response to recombinant antigens, and 5 have been challenged with large numbers of sporozoites, followed by surgical liver-wedge resection, in order to generate infected liver tissue for histological and immunological studies. As a complementary model, SCID mice carrying live, transplanted human and primate hepatocytes have been inoculated with sporozoites and infection of transplanted cells has been monitored by histological and immunological methods. In ongoing experiments chimpanzees are being immunised with MPES-derived lipopeptides that have been shown to overcome MHC restriction in mice, and with irradiated sporozoites.

Estimation of parametric and nonparametric models for univariate claim severity distributions - an approach using R

This paper presents an analysis of motor vehicle insurance claims relating to vehicle damage and to associated medical expenses. We use univariate severity distributions estimated with parametric and non-parametric methods. The methods are implemented using the statistical package R. Parametric analysis is limited to estimation of normal and lognormal distributions for each of the two claim types. The nonparametric analysis presented involves kernel density estimation. We illustrate the benefits of applying transformations to data prior to employing kernel based methods. We use a log-transformation and an optimal transformation amongst a class of transformations that produces symmetry in the data. The central aim of this paper is to provide educators with material that can be used in the classroom to teach statistical estimation methods, goodness of fit analysis and importantly statistical computing in the context of insurance and risk management. To this end, we have included in the Appendix of this paper all the R code that has been used in the analysis so that readers, both students and educators, can fully explore the techniques described

Binary classification of dyslipidemia from the waist-to-hip ratio and body mass index: a comparison of linear, logistic, and CART models.

BACKGROUND: We sought to improve upon previously published statistical modeling strategies for binary classification of dyslipidemia for general population screening purposes based on the waist-to-hip circumference ratio and body mass index anthropometric measurements. METHODS: Study subjects were participants in WHO-MONICA population-based surveys conducted in two Swiss regions. Outcome variables were based on the total serum cholesterol to high density lipoprotein cholesterol ratio. The other potential predictor variables were gender, age, current cigarette smoking, and hypertension. The models investigated were: (i) linear regression; (ii) logistic classification; (iii) regression trees; (iv) classification trees (iii and iv are collectively known as "CART"). Binary classification performance of the region-specific models was externally validated by classifying the subjects from the other region. RESULTS: Waist-to-hip circumference ratio and body mass index remained modest predictors of dyslipidemia. Correct classification rates for all models were 60-80%, with marked gender differences. Gender-specific models provided only small gains in classification. The external validations provided assurance about the stability of the models. CONCLUSIONS: There were no striking differences between either the algebraic (i, ii) vs. non-algebraic (iii, iv), or the regression (i, iii) vs. classification (ii, iv) modeling approaches. Anticipated advantages of the CART vs. simple additive linear and logistic models were less than expected in this particular application with a relatively small set of predictor variables. CART models may be more useful when considering main effects and interactions between larger sets of predictor variables.

The role of chemokines in Schistosoma mansoni infection: insights from human disease and murine models

Chemokines are a superfamily of low-molecular-weight cytokines that were initially described for their chemoattractant activity. It is now clear chemokines have several other activities that modulate immune processes. More than 50 chemokines ligands and at least 19 receptors have been described to date. Depending on the number of N-terminal cysteine residues, chemokines are grouped in the subfamilies CXC, CC, C or CX3C. A growing body of evidence suggests a role for chemokines in the pathogenesis of several inflammatory diseases. Our studies involving mice and humans infected with Schistosoma mansoni suggest an important role of the chemokine CCL3 and its receptors (CCR1 and CCR5) in the pathogenesis of severe schistosomiasis. We suggest that the differential activation of CCR1 or CCR5 during the course of schistosomiasis may dictate the outcome of the disease.

From deep seated slope deformation to rock avalanche: Destabilization and transportation models of the Sierre landslide (Switzerland)

Sackung is a widespread post-glacial morphological feature affecting Alpine mountains and creating characteristic geomorphological expression that can be detected from topography. Over long time evolution, internal deformation can lead to the formation of rapidly moving phenomena such as a rock-slide or rock avalanche. In this study, a detailed description of the Sierre rock-avalanche (SW Switzerland) is presented. This convex-shaped postglacial instability is one of the larger rock-avalanche in the Alps, involving more than 1.5 billion m3 with a run-out distance of about 14 km and extremely low Fahrböschung angle. This study presents comprehensive analyses of the structural and geological characteristics leading to the development of the Sierre rock-avalanche. In particular, by combining field observations, digital elevation model analyses and numerical modelling, the strong influence of both ductile and brittle tectonic structures on the failure mechanism and on the failure surface geometry is highlighted. The detection of pre-failure deformation indicates that the development of the rock avalanche corresponds to the last evolutionary stage of a pre-existing deep seated gravitational slope instability. These analyses accompanied by the dating and the characterization of rock avalanche deposits, allow the proposal of a destabilization model that clarifies the different phases leading to the development of the Sierre rock avalanche.

Redox dysregulation and oxidative stress in schizophrenia: genetic and functional anomalies of glutathione synthesis in patients and experimental models involving GABA interneurons and NMDA receptors

Objective: Converging evidence speak in favor of an abnormal susceptibility to oxidative stress in schizophrenia. A decreased level of glutathione (GSH), the principal non-protein antioxidant and redox regulator, was observed both in cerebrospinal-fluid and prefrontal cortex of schizophrenia patients (Do et al., 2000). Results: Schizophrenia patients have an abnormal GSH synthesis most likely of genetic origin: Two independent case-control studies showed a significant association between schizophrenia and a GAG trinucleotide repeat (TNR) polymorphism in the GSH key synthesizing enzyme glutamate-cysteine-ligase (GCL) catalytic subunit (GCLC) gene. The most common TNR genotype 7/7 was more frequent in controls, whereas the rarest TNR genotype 8/8 was three times more frequent in patients. The disease-associated genotypes correlated with a decrease in GCLC protein expression, GCL activity and GSH content. Such a redox dysregulation during development could underlie the structural and functional anomalies in connectivity: In experimental models, GSH deficit induced anomalies similar to those observed in patients. (a) morphology: In animal models with GSH deficit during the development we observed in prefrontal cortex a decreased dendritic spines density in pyramidal cells and an abnormal development of parvalbumine (but not of calretinine) immunoreactive GABA interneurones in anterior cingulate cortex. (b) physiology: GSH depletion in hippocampal slices induces NMDA receptors hypofunction and an impairment of long term potentiation. In addition, GSH deficit affected the modulation of dopamine on NMDA-induced Ca 2+ response in cultured cortical neurons. While dopamine enhanced NMDA responses in control neurons, it depressed NMDA responses in GSH-depleted neurons. Antagonist of D2-, but not D1-receptors, prevented this depression, a mechanism contributing to the efficacy of antipsychotics. The redox sensitive ryanodine receptors and L-type calcium channels underlie these observations. (c) cognition: Developing rats with low [GSH] and high dopamine lead deficit in olfactory integration and in object recognition which appears earlier in males that females, in analogy to the delay of the psychosis onset between man and woman. Conclusion: These clinical and experimental evidence, combined with the favorable outcome of a clinical trial with N-Acetyl Cysteine, a GSH precursor, on both the negative symptoms (Berk et al., submitted) and the mismatch negativity in an auditory oddball paradigm supported the proposal that a GSH synthesis impairment of genetic origin represent, among other factors, one major risk factor in schizophrenia.

Historical Development and Applications of the EPIC and APEX Models, June 2005

The development of the field-scale Erosion Productivity Impact Calculator (EPIC) model was initiated in 1981 to support assessments of soil erosion impacts on soil productivity for soil, climate, and cropping conditions representative of a broad spectrum of U.S. agricultural production regions. The first major application of EPIC was a national analysis performed in support of the 1985 Resources Conservation Act (RCA) assessment. The model has continuously evolved since that time and has been applied for a wide range of field, regional, and national studies both in the U.S. and in other countries. The range of EPIC applications has also expanded greatly over that time, including studies of (1) surface runoff and leaching estimates of nitrogen and phosphorus losses from fertilizer and manure applications, (2) leaching and runoff from simulated pesticide applications, (3) soil erosion losses from wind erosion, (4) climate change impacts on crop yield and erosion, and (5) soil carbon sequestration assessments. The EPIC acronym now stands for Erosion Policy Impact Climate, to reflect the greater diversity of problems to which the model is currently applied. The Agricultural Policy EXtender (APEX) model is essentially a multi-field version of EPIC that was developed in the late 1990s to address environmental problems associated with livestock and other agricultural production systems on a whole-farm or small watershed basis. The APEX model also continues to evolve and to be utilized for a wide variety of environmental assessments. The historical development for both models will be presented, as well as example applications on several different scales.

Downregulation of cannabinoid receptor 1 from neuropeptide Y interneurons in the basal ganglia of patients with Huntington's disease and mouse models.

Cannabinoid receptor 1 (CB(1) receptor) controls several neuronal functions, including neurotransmitter release, synaptic plasticity, gene expression and neuronal viability. Downregulation of CB(1) expression in the basal ganglia of patients with Huntington's disease (HD) and animal models represents one of the earliest molecular events induced by mutant huntingtin (mHtt). This early disruption of neuronal CB(1) signaling is thought to contribute to HD symptoms and neurodegeneration. Here we determined whether CB(1) downregulation measured in patients with HD and mouse models was ubiquitous or restricted to specific striatal neuronal subpopulations. Using unbiased semi-quantitative immunohistochemistry, we confirmed previous studies showing that CB(1) expression is downregulated in medium spiny neurons of the indirect pathway, and found that CB(1) is also downregulated in neuropeptide Y (NPY)/neuronal nitric oxide synthase (nNOS)-expressing interneurons while remaining unchanged in parvalbumin- and calretinin-expressing interneurons. CB(1) downregulation in striatal NPY/nNOS-expressing interneurons occurs in R6/2 mice, Hdh(Q150/Q150) mice and the caudate nucleus of patients with HD. In R6/2 mice, CB(1) downregulation in NPY/nNOS-expressing interneurons correlates with diffuse expression of mHtt in the soma. This downregulation also occludes the ability of cannabinoid agonists to activate the pro-survival signaling molecule cAMP response element-binding protein in NPY/nNOS-expressing interneurons. Loss of CB(1) signaling in NPY/nNOS-expressing interneurons could contribute to the impairment of basal ganglia functions linked to HD.

On heuristic and linear models of judgment: Mapping the demand for knowledge

Research on judgment and decision making presents a confusing picture of human abilities. For example, much research has emphasized the dysfunctional aspects of judgmental heuristics, and yet, other findings suggest that these can be highly effective. A further line of research has modeled judgment as resulting from as if linear models. This paper illuminates the distinctions in these approaches by providing a common analytical framework based on the central theoretical premise that understanding human performance requires specifying how characteristics of the decision rules people use interact with the demands of the tasks they face. Our work synthesizes the analytical tools of lens model research with novel methodology developed to specify the effectiveness of heuristics in different environments and allows direct comparisons between the different approaches. We illustrate with both theoretical analyses and simulations. We further link our results to the empirical literature by a meta-analysis of lens model studies and estimate both human andheuristic performance in the same tasks. Our results highlight the trade-off betweenlinear models and heuristics. Whereas the former are cognitively demanding, the latterare simple to use. However, they require knowledge and thus maps of when andwhich heuristic to employ.

Lipid metabolism in myelinating glial cells: lessons from human inherited disorders and mouse models.

The integrity of central and peripheral nervous system myelin is affected in numerous lipid metabolism disorders. This vulnerability was so far mostly attributed to the extraordinarily high level of lipid synthesis that is required for the formation of myelin, and to the relative autonomy in lipid synthesis of myelinating glial cells because of blood barriers shielding the nervous system from circulating lipids. Recent insights from analysis of inherited lipid disorders, especially those with prevailing lipid depletion and from mouse models with glia-specific disruption of lipid metabolism, shed new light on this issue. The particular lipid composition of myelin, the transport of lipid-associated myelin proteins, and the necessity for timely assembly of the myelin sheath all contribute to the observed vulnerability of myelin to perturbed lipid metabolism. Furthermore, the uptake of external lipids may also play a role in the formation of myelin membranes. In addition to an improved understanding of basic myelin biology, these data provide a foundation for future therapeutic interventions aiming at preserving glial cell integrity in metabolic disorders.

Generalizing sample tree information with semiparametric and parametric models

Summary

Calibration of the century, apsim and ndicea models of decomposition and n mineralization of plant residues in the humid tropics

The aim of this study was to calibrate the CENTURY, APSIM and NDICEA simulation models for estimating decomposition and N mineralization rates of plant organic materials (Arachis pintoi, Calopogonium mucunoides, Stizolobium aterrimum, Stylosanthes guyanensis) for 360 days in the Atlantic rainforest bioma of Brazil. The models´ default settings overestimated the decomposition and N-mineralization of plant residues, underlining the fact that the models must be calibrated for use under tropical conditions. For example, the APSIM model simulated the decomposition of the Stizolobium aterrimum and Calopogonium mucunoides residues with an error rate of 37.62 and 48.23 %, respectively, by comparison with the observed data, and was the least accurate model in the absence of calibration. At the default settings, the NDICEA model produced an error rate of 10.46 and 14.46 % and the CENTURY model, 21.42 and 31.84 %, respectively, for Stizolobium aterrimum and Calopogonium mucunoides residue decomposition. After calibration, the models showed a high level of accuracy in estimating decomposition and N- mineralization, with an error rate of less than 20 %. The calibrated NDICEA model showed the highest level of accuracy, followed by the APSIM and CENTURY. All models performed poorly in the first few months of decomposition and N-mineralization, indicating the need of an additional parameter for initial microorganism growth on the residues that would take the effect of leaching due to rainfall into account.