Electrochemical high temperature membrane reactor for the processing of hydrogen-carbon monoxide gas mixtures

Magdeburg, Univ., Fak. für Verfahrens- und Systemtechnik, Diss., 2013

Electrochemical oxidation of H 2, CO gas mixtures in polymer-electrolyte-membrane fuel cells

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

The differentiation of character state relationships by binary coding and the monothetic subset method / Hymen Marx, George B. Rabb and Harold K. Voris.

v.72:no.1(1977)

Group strategy-proof social choice functions with binary ranges and arbitrary domains: characterization results

We define different concepts of group strategy-proofness for social choice functions. We discuss the connections between the defined concepts under different assumptions on their domains of definition. We characterize the social choice functions that satisfy each one of them and whose ranges consist of two alternatives, in terms of two types of basic properties.

DIP-STR: A new marker for resolving unbalanced DNA mixtures

The genetic characterization of unbalanced mixed stains remains an important area where improvementis imperative. Most cases of aggression, homicide and sexual assault produce biological traces withrelatively large amount of the victim's DNA and small amount of the aggressor's DNA. If this ratio issmaller than 1:10 it is currently not possible to obtain a conventional autosomal DNA profile of the minorcontributor, with potential loss of crucial DNA evidence. Y-STR analysis represents a solution for somecases but has several limitations. We propose here a method based on a new compound genetic markerformed by a Deletion/Insertion Polymorphism (DIP) linked to a Short Tandem Repeat polymorphism(STR), that we name DIP-STR. By means of allele-specific amplifications of DIP-STR haplotypes, we canproduce a high resolution autosomal DNA profile of a donor that contributes less than 0.1% to a DNAmixture. Based on these features DIP-STR markers may outperform conventional Y-STR markers inmixed stain analysis.

DIP-STR: Highly Sensitive Markers for the Analysis of Unbalanced Genomic Mixtures.

Samples containing highly unbalanced DNA mixtures from two individuals commonly occur both in forensic mixed stains and in peripheral blood DNA microchimerism induced by pregnancy or following organ transplant. Because of PCR amplification bias, the genetic identification of a DNA that contributes trace amounts to a mixed sample represents a tremendous challenge. This means that standard genetic markers, namely microsatellites, also referred as short tandem repeats (STR), and single-nucleotide polymorphism (SNP) have limited power in addressing common questions of forensic and medical genetics. To address this issue, we developed a molecular marker, named DIP-STR that relies on pairing deletion-insertion polymorphisms (DIP) with STR. This novel analytical approach allows for the unambiguous genotyping of a minor component in the presence of a major component, where DIP-STR genotypes of the minor were successfully procured at ratios up to 1:1,000. The compound nature of this marker generates a high level of polymorphism that is suitable for identity testing. Here, we demonstrate the power of the DIP-STR approach on an initial set of nine markers surveyed in a Swiss population. Finally, we discuss the limitations and potential applications of our new system including preliminary tests on clinical samples and estimates of their performance on simulated DNA mixtures.

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.

Identifying pesticide use patterns among flower growers to assess occupational exposure to mixtures

Objectives Exposure assessment to a single pesticide does not capture the complexity of the occupational exposure. Recently, pesticide use patterns analysis has emerged as an alternative to study these exposures. The aim of this study is to identify the pesticide use pattern among flower growers in Mexico participating in the study on the endocrine and reproductive effects associated with pesticide exposure. Methods A cross-sectional study was carried out to gather retrospective information on pesticide use applying a questionnaire to the person in charge of the participating flower growing farms. Information about seasonal frequency of pesticide use (rainy and dry) for the years 2004 and 2005 was obtained. Principal components analysis was performed. Results Complete information was obtained for 88 farms and 23 pesticides were included in the analysis. Six principal components were selected, which explained more than 70% of the data variability. The identified pesticide use patterns during both years were: 1. fungicides benomyl, carbendazim, thiophanate and metalaxyl (both seasons), including triadimephon during the rainy season, chlorotalonyl and insecticide permethrin during the dry season; 2. insecticides oxamyl, biphenthrin and fungicide iprodione (both seasons), including insecticide methomyl during the dry season; 3. fungicide mancozeb and herbicide glyphosate (only during the rainy season); 4. insecticides metamidophos and parathion (both seasons); 5. insecticides omethoate and methomyl (only rainy season); and 6. insecticides abamectin and carbofuran (only dry season). Some pesticides do not show a clear pattern of seasonal use during the studied years. Conclusions The principal component analysis is useful to summarise a large set of exposure variables into smaller groups of exposure patterns, identifying the mixtures of pesticides in the occupational environment that may have an interactive effect on a particular health effect.

A RT-PCR method for selective amplification and phenotypic characterization of all three serotypes of Sabin-related polioviruses from viral mixtures

Outbreaks caused by vaccine-derived polioviruses are challenging the final eradication of paralytic poliomyelitis. Therefore, the surveillance of the acute flaccid paralysis cases based on poliovirus isolation and characterization remains an essential activity. Due to the use of trivalent oral poliovirus vaccine (OPV), mixtures containing more than one serotype of Sabin-related polioviruses are frequently isolated from clinical samples. Because each poliovirus isolate needs to be individually analyzed, we designed polymerase chain reaction primers that can selectively distinguish and amplify a genomic segment of the three Sabin-related poliovirus serotypes present in mixtures, thus, optimizing the diagnosis and providing prompt information to support epidemiologic actions.

Object-oriented Bayesian networks for evaluating DIP-STR profiling results from unbalanced DNA mixtures.

The genetic characterization of unbalanced mixed stains remains an important area where improvement is imperative. In fact, with current methods for DNA analysis (Polymerase Chain Reaction with the SGM Plus™ multiplex kit), it is generally not possible to obtain a conventional autosomal DNA profile of the minor contributor if the ratio between the two contributors in a mixture is smaller than 1:10. This is a consequence of the fact that the major contributor's profile 'masks' that of the minor contributor. Besides known remedies to this problem, such as Y-STR analysis, a new compound genetic marker that consists of a Deletion/Insertion Polymorphism (DIP), linked to a Short Tandem Repeat (STR) polymorphism, has recently been developed and proposed elsewhere in literature [1]. The present paper reports on the derivation of an approach for the probabilistic evaluation of DIP-STR profiling results obtained from unbalanced DNA mixtures. The procedure is based on object-oriented Bayesian networks (OOBNs) and uses the likelihood ratio as an expression of the probative value. OOBNs are retained in this paper because they allow one to provide a clear description of the genotypic configuration observed for the mixed stain as well as for the various potential contributors (e.g., victim and suspect). These models also allow one to depict the assumed relevance relationships and perform the necessary probabilistic computations.

Binary proposal for assessing quality of Open Access Institutional Repositories : the case of Spanish repositories

The reason for this study is to propose a new quantitative approach on how to assess the quality of Open Access University Institutional Repositories. The results of this new approach are tested in the Spanish University Repositories. The assessment method is based in a binary codification of a proposal of features that objectively describes the repositories. The purposes of this method are assessing the quality and an almost automatically system for updating the data of the characteristics. First of all a database was created with the 38 Spanish institutional repositories. The variables of analysis are presented and explained either if they are coming from bibliography or are a set of new variables. Among the characteristics analyzed are the features of the software, the services of the repository, the features of the information system, the Internet visibility and the licenses of use. Results from Spanish universities ARE provided as a practical example of the assessment and for having a picture of the state of the development of the open access movement in Spain.

Subjective health assessments and active labor market participation of older men: evidence from a semiparametric binary choice model with nonadditive correlated individual-specific effects

We use panel data from the U. S. Health and Retirement Study, 1992-2002, to estimate the effect of self-assessed health limitations on the active labor market participation of older men. Self-assessments of health are likely to be endogenous to labor supply due to justification bias and individual-specific heterogeneity in subjective evaluations. We address both concerns. We propose a semiparametric binary choice procedure that incorporates nonadditive correlated individual-specific effects. Our estimation strategy identifies and estimates the average partial effects of health and functioning on labor market participation. The results indicate that poor health plays a major role in labor market exit decisions.