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

Coffee and shade trees show complementary use of soil water in a traditional agroforestry ecosystem

Financial support. This research has been supported by the PAPIIT-UNAM (Mexico) (grant nos. IB100313 and IB100113), the CONACyT (Mexico) (grant no. 187646), the National Science Foundation (US) (grant no. 1313804), and the Scottish Funding Council (UK) (grant no. SF10192). Author contributions. LEMV designed the experiment. LEMV, MSAB and FH collected the field data. MSAB performed all the Bayesian mixing model analysis. JG contributed in the data analysis. LEMV prepared the first draft of the manuscript. FH, MSAB and JG edited and commented on the manuscript several times, and TED carried out the final revision. Later, all the co-authors contributed with revisions. Data can be accessed at https://doi.org/10.5063/F1MS3R3J (Muñoz-Villers et al., 2020).Peer reviewedPublisher PD

A strategy for the robust forecasting of gas turbine health subjected to fouling

Fouling represents a major problem for Gas Turbines (GTs) in both heavy-duty and aeropropulsion applications. Solid particles entering the engine can stick to the internal surfaces and form deposits. Components' lifetime and performance can dramatically vary as a consequence of this phenomenon. These effects impact the whole engine in terms of residual life, operating stability, and maintenance costs. In the High-Pressure Turbine (HPT), in particular, the high temperatures soft the particles and promote their adhesion, especially in the short term. Unfortunately, predicting the GT response to this detrimental issue is still an open problem for scientists. Furthermore, the stochastic variations of the components operating conditions increase the uncertainty of the forecasting results. In this work, a strategy to predict the effects of turbine fouling on the whole engine is proposed. A stationary Gas Path Analysis (GPA) has been performed for this scope to predict the GT health parameters. Their alteration as a consequence of fouling has been evaluated by scaling the turbine map. The scaling factor has been found by performing Computational Fluid Dynamic (CFD) simulations of a HPT nozzle with particle injection. Being its operating conditions strongly uncertain, a stochastic analysis has been conducted. The uncertainty sources considered are the circumferential hot core location and the turbulence level at the inlet. The study enables to build of confidence intervals on the GT health parameters predictions and represents a step forward towards a robust forecasting tool

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

Older Age and Dietary Folate Are Determinants of Genomic and p16-Specific DNA Methylation in Mouse Colon

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Off-line washing effectiveness on a multistage axial compressor

The interaction between gas turbines and airborne particles determines detrimental effects on the performance, efficiency, and reliability of the power unit. When it is possible, the interaction is reduced by the use of inlet separators and filtration systems. In an aero engine, these barriers are difficult to implement, and only bigger particles (usually greater than 10 µm) are separated from the airflow. Small units, especially those equips helicopters, are usually affected by fouling issues, especially when the aircraft is employed in harsh environments such as firefighting and rescue activities. To recover this contamination, the unit is washed after the mission by ground operations to restore the unit performance by removing the deposits. This operation occurs during a sub-idle unit operation, and the washing process has to be effective when the engine operates in this off-design condition. In this paper, the evaluation of the washing performance during a sub-idle unit operation is carried out. The compressor unit is a multistage axial compressor that equips the Allison 250-C18 engine. The washing operation was performed by water, and a sensitivity analysis is carried out to discover the capability of water droplets to remove the contaminants. The experimental analysis involves the contamination of the unit by micro-sized soot particles and a washing operation by micro-sized water droplets. These experimental results are compared to numerical simulations to discover the effects of the washing operation on a small power unit during sub-idle operating conditions. The off-design regime imposes a specific evaluation of the proper setup of the washing strategy: flow separations involve wider regions in the compressor unit, and the removal capability is strongly related to the droplet path through the stages. The results show how in the off-design washing operation, the droplet diameter has greater importance than the water flow rate for reducing the deposits over the compressor stages. © The Authors, published by EDP Sciences. This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0 (http://creativecommons.org/licenses/by/4.0/

Potential role of gut microbiota, the proto-oncogene PIKE (Agap2) and cytochrome P450 CYP2W1 in promotion of liver cancer by alcoholic and nonalcoholic fatty liver disease and protection by dietary soy protein

We have previously demonstrated promotion of diethylnitrosamine (DEN) initiated liver tumorigenesis after feeding diets high in fat or ethanol (EtOH) to male mice. This was accompanied by hepatic induction of the proto-oncogene PIKE (Agap2). Switch of dietary protein from casein to soy protein isolate (SPI) significantly reduced tumor formation in these models. We have linked EtOH consumption in mice to microbial dysbiosis. Adoptive transfer studies demonstrate that microbiota from mice fed ethanol can induce hepatic steatosis in the absence of ethanol suggesting that microbiota or the microbial metabolome play key roles in development of fatty liver disease. Feeding SPI significantly changed gut bacteria in mice increasing alpha diversity (P < 0.05) and levels of Clostidiales spp. Feeding soy formula to piglets also resulted in significant changes in microbiota, the pattern of bile acid metabolites and in inhibition of the intestinal-hepatic FXR/FGF19-SHP pathway which has been linked to both steatosis and hepatocyte proliferation. Moreover, feeding SPI also resulted in induction of hepatic PPAR alpha signaling and inhibition of PIKE mRNA expression coincident with inhibition of steatosis and cancer prevention. Feeding studies in the DEN model with differing dietary fats demonstrated tumor promotion specific to the saturated fat, cocoa butter relative to diets containing olive oil or corn oil associated with microbial dysbiosis including dramatic increases in Lachnospiraceae particularly from the genus Coprococcus. Immunohistochemical analysis demonstrated that tumors from EtOH-fed mice and patients with alcohol-associated HCC also expressed high levels of a novel cytochrome P450 enzyme CYP2W1. Additional adoptive transfer experiments and studies in knockout mice are required to determine the exact relationship between soy effects on the microbiota, expression of PIKE, CYP2W1, PPAR alpha activation and prevention of tumorigenesis

DNA methylation determination by liquid chromatography–tandem mass spectrometry using novel biosynthetic [U-15N]deoxycytidine and [U-15N]methyldeoxycytidine internal standards

Methylation of the promoter CpG regions regulates gene transcription by inhibiting transcription factor binding. Deoxycytidine methylation may regulate cell differentiation, while aberrations in the process may be involved in cancer etiology and the development of birth defects (e.g. neural tube defects). Similarly, nutritional deficiency and certain nutragenomic interactions are associated with DNA hypomethylation. While LC-MS has been used previously to measure percentage genomic deoxycytidine methylation, a lack of a secure source of internal standards and the need for laborious and time-consuming DNA digestion protocols constitute distinct limitations. Here we report a simple and inexpensive protocol for the biosynthesis of internal standards from readily available precursors. Using these biosynthetic stable-isotopic [U-15N]-labeled internal standards, coupled with an improved DNA digestion protocol developed in our lab, we have developed a low-cost, high-throughput (>500 samples in 4 days) assay for measuring deoxycytidine methylation in genomic DNA. Inter- and intraassay variation for the assay (%RSD, n = 6) was <2.5%