Statistical model identification : dynamical processes and large-scale networks in systems biology

Magdeburg, Univ., Fak. für Verfahrens- und Systemtechnik, Diss., 2014

Statistical model identification : dynamical processes and large-scale networks in systems biology

Magdeburg, Univ., Fak. für Verfahrens- und Systemtechnik, Diss., 2014

Computational methods for model reduction of large-scale sparse structured descriptor systems

Magdeburg, Univ., Fak. für Mathematik, Diss., 2015

Increasing quasiconcave production and utility functions with diminishing returns to scale

In microeconomic analysis functions with diminishing returns to scale (DRS) have frequently been employed. Various properties of increasing quasiconcave aggregator functions with DRS are derived. Furthermore duality in the classical sense as well as of a new type is studied for such aggregator functions in production and consumer theory. In particular representation theorems for direct and indirect aggregator functions are obtained. These involve only small sets of generator functions. The study is carried out in the contemporary framework of abstract convexity and abstract concavity.

Multi-Scale Integrated Analysis of Societal and Ecosystem Metabolism (MUSIASEM): an outline of rationale and theory

This paper presents an outline of rationale and theory of the MuSIASEM scheme (Multi-Scale Integrated Analysis of Societal and Ecosystem Metabolism). First, three points of the rationale behind our MuSIASEM scheme are discussed: (i) endosomatic and exosomatic metabolism in relation to Georgescu-Roegen’s flow-fund scheme; (2) the bioeconomic analogy of hypercycle and dissipative parts in ecosystems; (3) the dramatic reallocation of human time and land use patterns in various sectors of modern economy. Next, a flow-fund representation of the MUSIASEM scheme on three levels (the whole national level, the paid work sectors level, and the agricultural sector level) is illustrated to look at the structure of the human economy in relation to two primary factors: (i) human time - a fund; and (ii) exosomatic energy - a flow. The three levels representation uses extensive and intensive variables simultaneously. Key conceptual tools of the MuSIASEM scheme - mosaic effects and impredicative loop analysis - are explained using the three level flow-fund representation. Finally, we claim that the MuSIASEM scheme can be seen as a multi-purpose grammar useful to deal with sustainability issues.

Harmonization guidelines for HLA-peptide multimer assays derived from results of a large scale international proficiency panel of the Cancer Vaccine Consortium.

PURPOSE: The Cancer Vaccine Consortium of the Cancer Research Institute (CVC-CRI) conducted a multicenter HLA-peptide multimer proficiency panel (MPP) with a group of 27 laboratories to assess the performance of the assay. EXPERIMENTAL DESIGN: Participants used commercially available HLA-peptide multimers and a well characterized common source of peripheral blood mononuclear cells (PBMC). The frequency of CD8+ T cells specific for two HLA-A2-restricted model antigens was measured by flow cytometry. The panel design allowed for participants to use their preferred staining reagents and locally established protocols for both cell labeling, data acquisition and analysis. RESULTS: We observed significant differences in both the performance characteristics of the assay and the reported frequencies of specific T cells across laboratories. These results emphasize the need to identify the critical variables important for the observed variability to allow for harmonization of the technique across institutions. CONCLUSIONS: Three key recommendations emerged that would likely reduce assay variability and thus move toward harmonizing of this assay. (1) Use of more than two colors for the staining (2) collect at least 100,000 CD8 T cells, and (3) use of a background control sample to appropriately set the analytical gates. We also provide more insight into the limitations of the assay and identified additional protocol steps that potentially impact the quality of data generated and therefore should serve as primary targets for systematic analysis in future panels. Finally, we propose initial guidelines for harmonizing assay performance which include the introduction of standard operating protocols to allow for adequate training of technical staff and auditing of test analysis procedures.

Multi-scale support vector algorithms for hot spot detection and modelling

The algorithmic approach to data modelling has developed rapidly these last years, in particular methods based on data mining and machine learning have been used in a growing number of applications. These methods follow a data-driven methodology, aiming at providing the best possible generalization and predictive abilities instead of concentrating on the properties of the data model. One of the most successful groups of such methods is known as Support Vector algorithms. Following the fruitful developments in applying Support Vector algorithms to spatial data, this paper introduces a new extension of the traditional support vector regression (SVR) algorithm. This extension allows for the simultaneous modelling of environmental data at several spatial scales. The joint influence of environmental processes presenting different patterns at different scales is here learned automatically from data, providing the optimum mixture of short and large-scale models. The method is adaptive to the spatial scale of the data. With this advantage, it can provide efficient means to model local anomalies that may typically arise in situations at an early phase of an environmental emergency. However, the proposed approach still requires some prior knowledge on the possible existence of such short-scale patterns. This is a possible limitation of the method for its implementation in early warning systems. The purpose of this paper is to present the multi-scale SVR model and to illustrate its use with an application to the mapping of Cs137 activity given the measurements taken in the region of Briansk following the Chernobyl accident.

Qualités psychométriques de la version française de la TAS-20 et prévalence de l'alexithymie chez 264 adolescents tout-venant [The 20-item Toronto alexithymia scale: structural validity, internal consistency and prevalence of alexithymia in a Swiss adolescent sample]

L'objectif de cette étude est d'examiner la structure factorielle et la consistance interne de la TAS-20 sur un échantillon d'adolescents (n = 264), ainsi que de décrire la distribution des caractéristiques alexithymiques dans cet échantillon. La structure à trois facteurs de la TAS-20 a été confirmée par notre analyse factorielle confirmatoire. La consistance interne, mesurée à l'aide d'alpha de Cronbach, est acceptable pour le premier facteur (difficulté à identifier les sentiments (DIF)), bonne pour le second (difficulté à verbaliser les sentiments (DDF)), mais en revanche, faible pour le troisième facteur (pensées orientées vers l'extérieur (EOT)). Les résultats d'une Anova mettent en évidence une tendance linéaire indiquant que plus l'âge augmente plus le niveau d'alexithymie (score total TAS-20), la difficulté à identifier les sentiments et les pensées orientées vers l'extérieur diminuent. En ce qui concerne la prévalence de l'alexithymie, on remarque en effet que 38,5 % des adolescents de moins de 16 ans sont considérés comme alexithymiques, contre 30,1 % des 16-17 ans et 22 % des plus de 17 ans. Notre étude indique donc que la TAS-20 est un instrument adéquat pour évaluer l'alexithymie à l'adolescence, tout en suggérant quelques précautions étant donné l'aspect développemental de cette période.

Adolescent Drug Abuse Diagnosis (ADAD) vs. Health of Nation Outcome Scale for Children and Adolescents (HoNOSCA) in clinical outcome measurement.

BACKGROUND: The Adolescent Drug Abuse Diagnosis (ADAD) and Health of Nation Outcome Scales for Children and Adolescents (HoNOSCA) are both measures of outcome for adolescent mental health services. AIMS: To compare the ADAD with HoNOSCA; to examine their clinical usefulness. METHODS: Comparison of the ADAD and HoNOSCA outcome measures of 20 adolescents attending a psychiatric day care unit. RESULTS: ADAD change was positively correlated with HoNOSCA change. HoNOSCA assesses the clinic's day-care programme more positively than the ADAD. The ADAD detects a group for which the mean score remains unchanged whereas HoNOSCA does not. CONCLUSIONS: A good convergent validity emerges between the two assessment tools. The ADAD allows an evidence-based assessment and generally enables a better subject discrimination than HoNOSCA. HoNOSCA gives a less refined evaluation but is more economic in time and possibly more sensitive to change. Both assessment tools give useful information and enabled the Day-care Unit for Adolescents to rethink the process of care and of outcome, which benefited both the institution and the patients.

Institutions and the Scale Effect

Growth models which imply a scale effect are commonly refuted on the basis of empirical evidence. A focus on the extent of the market as opposed to the scale of the country has led recent studies to reconsider the role that country scale plays when conditioning on other factors. We consider a variant of a simple learning by doing model to account for the potential role for institutions in determining the strength – and direction – of the scale effect. Using cross-country data, we find a significant interaction between property rights institutions and the effect of scale on long-run growth: In countries with poor property rights institutions, scale is positively related with income per capita; where property rights institutions are good, higher scale is associated with lower per capita ncomes. We find no evidence of such role for contracting institutions.

Dimensionality of the Rosenberg self-esteem scale and its relationships with the three- and five-factor personality models

The authors investigated the dimensionality of the French version of the Rosenberg Self-Esteem Scale (RSES; Rosenberg, 1965) using confirmatory factor analysis. We tested models of 1 or 2 factors. Results suggest the RSES is a 1-dimensional scale with 3 highly correlated items. Comparison with the Revised NEO-Personality Inventory (NEO-PI-R; Costa, McCrae, & Rolland, 1998) demonstrated that Neuroticism correlated strongly and Extraversion and Conscientiousness moderately with the RSES. Depression accounted for 47% of the variance of the RSES. Other NEO-PI-R facets were also moderately related with self-esteem.