Real time traffic models, decision support for traffic management

Reliable and accurate short-term traffic state prediction can improve the performance of real-time traffic management systems significantly. Using this short-time prediction based on current measurements delivered by advanced surveillance systems will support decision-making processes on various control strategies and enhance the performance of the overall network. By taking proactive action deploying traffic management measures, congestion may be prevented or its effects limited. An approach of short-term traffic state prediction is presented and implemented in a real life case for the city of Assen in the Netherlands. This prediction is based on connecting online traffic measurements with a real time traffic model using the macroscopic dynamic traffic assignment model StreamLine in a rolling horizon implementation. Different monitoring data sources consisting of both fixed-point and floating car data are used. The advantage of the rolling horizon approach is that no warming-up period is needed for the dynamic traffic assignment taking less computation time while keeping results consistent. Further, the current traffic state estimation is done by combining model estimates of previous predictions and current measurements. The results of predictions made in the real life case are presented as well as several tested methods for improving the current state estimations showing promising results

Understanding and Estimating Effective Population Size for Practical Application in Marine Species Management

Effective population size (Ne) determines the strength of genetic drift in a population and has long been recognized as an important parameter for evaluating conservation status and threats to genetic health of populations. Specifically, an estimate of Ne is crucial to management because it integrates genetic effects with the life history of the species, allowing for predictions of a population’s current and future viability. Nevertheless, compared with ecological and demographic parameters, Ne has had limited influence on species management, beyond its application in very small populations. Recent developments have substantially improved Ne estimation; however, some obstacles remain for the practical application of Ne estimates. For example, the need to define the spatial and temporal scale of measurement makes the concept complex and sometimes difficult to interpret. We reviewed approaches to estimation of Ne over both long-term and contemporary time frames, clarifying their interpretations with respect to local populations and the global metapopulation. We describe multiple experimental factors affecting robustness of contemporary Ne estimates and suggest that different sampling designs can be combined to compare largely independent measures of Ne for improved confidence in the result. Large populations with moderate gene flow pose the greatest challenges to robust estimation of contemporary Ne and require careful consideration of sampling and analysis to minimize estimator bias. We emphasize the practical utility of estimating Ne by highlighting its relevance to the adaptive potential of a population and describing applications in management of marine populations, where the focus is not always on critically endangered populations. Two cases discussed include the mechanisms generating Ne estimates many orders of magnitude lower than census N in harvested marine fishes and the predicted reduction in Ne from hatchery-based population supplementation

Understanding and Estimating Effective Population Size for Practical Application in Marine Species Management

Effective population size (Ne) determines the strength of genetic drift in a population and has long been recognized as an important parameter for evaluating conservation status and threats to genetic health of populations. Specifically, an estimate of Ne is crucial to management because it integrates genetic effects with the life history of the species, allowing for predictions of a population’s current and future viability. Nevertheless, compared with ecological and demographic parameters, Ne has had limited influence on species management, beyond its application in very small populations. Recent developments have substantially improved Ne estimation; however, some obstacles remain for the practical application of Ne estimates. For example, the need to define the spatial and temporal scale of measurement makes the concept complex and sometimes difficult to interpret. We reviewed approaches to estimation of Ne over both long-term and contemporary time frames, clarifying their interpretations with respect to local populations and the global metapopulation. We describe multiple experimental factors affecting robustness of contemporary Ne estimates and suggest that different sampling designs can be combined to compare largely independent measures of Ne for improved confidence in the result. Large populations with moderate gene flow pose the greatest challenges to robust estimation of contemporary Ne and require careful consideration of sampling and analysis to minimize estimator bias. We emphasize the practical utility of estimating Ne by highlighting its relevance to the adaptive potential of a population and describing applications in management of marine populations, where the focus is not always on critically endangered populations. Two cases discussed include the mechanisms generating Ne estimates many orders of magnitude lower than census N in harvested marine fishes and the predicted reduction in Ne from hatchery-based population supplementation

Direct Classification of Type 2 Diabetes From Retinal Fundus Images in a Population-based Sample From The Maastricht Study

Type 2 Diabetes (T2D) is a chronic metabolic disorder that can lead to blindness and cardiovascular disease. Information about early stage T2D might be present in retinal fundus images, but to what extent these images can be used for a screening setting is still unknown. In this study, deep neural networks were employed to differentiate between fundus images from individuals with and without T2D. We investigated three methods to achieve high classification performance, measured by the area under the receiver operating curve (ROC-AUC). A multi-target learning approach to simultaneously output retinal biomarkers as well as T2D works best (AUC = 0.746 [$\pm$0.001]). Furthermore, the classification performance can be improved when images with high prediction uncertainty are referred to a specialist. We also show that the combination of images of the left and right eye per individual can further improve the classification performance (AUC = 0.758 [$\pm$0.003]), using a simple averaging approach. The results are promising, suggesting the feasibility of screening for T2D from retinal fundus images.Comment: to be published in the proceeding of SPIE - Medical Imaging 2020, 6 pages, 1 figur

Statistical certification of software systems

Abstract Common software release procedures based on statistical techniques try to optimise the trade-off between further testing costs and costs due to remaining errors. We propose new software release procedures where the aim is to certify that the software does not contain errors. The underlying model is a new discrete-time model similar to the JelinskiMoranda model. The decisions are based on a mix of classical and Bayesian approaches to sequential testing and do not require any assumption on the initial number of errors

Polymorphisms of methylenetetrahydrofolate reductase (MTHFR) and susceptibility to pediatric acute lymphoblastic leukemia in a German study population

BACKGROUND: Methylenetetrahydrofolate reductase (MTHFR) has a major impact on the regulation of the folic acid pathway due to conversion of 5,10-methylenetetrahydrofolate (methylene-THF) to 5-methyl-THF. Two common polymorphisms (677C>T and 1298A>C) in the gene coding for MTHFR have been shown to reduce MTHFR enzyme activity and were associated with the susceptibility to different disorders, including vascular disease, neural tube defects and lymphoid malignancies. Studies on the role of these polymorphisms in the susceptibility to acute lymphoblastic leukemia (ALL) led to discrepant results. METHODS: We retrospectively evaluated the association of the MTHFR 677C>T and 1298A>C polymorphisms with pediatric ALL by genotyping a study sample of 443 ALL patients consecutively enrolled onto the German multicenter trial ALL-BFM 2000 and 379 healthy controls. We calculated odds ratios of MTHFR genotypes based on the MTHFR 677C>T and 1298A>C polymorphisms to examine if one or both of these polymorphisms are associated with pediatric ALL. RESULTS: No significant associations between specific MTHFR variants or combinations of variants and risk of ALL were observed neither in the total patient group nor in analyses stratified by gender, age at diagnosis, DNA index, immunophenotype, or TEL/AML1 rearrangement. CONCLUSION: Our findings suggest that the MTHFR 677C>T and 1298A>C gene variants do not have a major influence on the susceptibility to pediatric ALL in the German population

A member of the Whirly family is a multifunctional RNA- and DNA-binding protein that is essential for chloroplast biogenesis

‘Whirly’ proteins comprise a plant-specific protein family whose members have been described as DNA-binding proteins that influence nuclear transcription and telomere maintenance, and that associate with nucleoids in chloroplasts and mitochondria. We identified the maize WHY1 ortholog among proteins that coimmunoprecipitate with CRS1, which promotes the splicing of the chloroplast atpF group II intron. ZmWHY1 localizes to the chloroplast stroma and to the thylakoid membrane, to which it is tethered by DNA. Genome-wide coimmunoprecipitation assays showed that ZmWHY1 in chloroplast extract is associated with DNA from throughout the plastid genome and with a subset of plastid RNAs that includes atpF transcripts. Furthermore, ZmWHY1 binds both RNA and DNA in vitro. A severe ZmWhy1 mutant allele conditions albino seedlings lacking plastid ribosomes; these exhibit the altered plastid RNA profile characteristic of ribosome-less plastids. Hypomorphic ZmWhy1 mutants exhibit reduced atpF intron splicing and a reduced content of plastid ribosomes; aberrant 23S rRNA metabolism in these mutants suggests that a defect in the biogenesis of the large ribosomal subunit underlies the ribosome deficiency. However, these mutants contain near normal levels of chloroplast DNA and RNAs, suggesting that ZmWHY1 is not directly required for either DNA replication or for global plastid transcription