Development of a near-wall Reynolds-stress closure based on the SSG model for the pressure strain

In this research, a near-wall second-order closure based on the Speziable et al.(1991) or SSG model for the pressure-strain term is proposed. Unlike the LRR model, the SSG model is quasi-nonlinear and yields better results when applied to calculate rotating homogeneous turbulent flows. An asymptotic analysis near the wall is applied to both the exact and modeled, equations so that appropriate near-wall corrections to the SSG model and the modeled dissipation-rate equation can be derived to satisfy the physical wall boundary conditions as well as the asymptotic near-wall behavior of the exact equations. Two additional model constants are introduced and they are determined by calibrating against one set of near-wall channel flow data. Once determined, their values are found to remain constant irrespective of the type of flow examined. The resultant model is used to calculate simple turbulent flows, near separating turbulent flows, complex turbulent flows and compressible turbulent flows with a freestream Mach number as high as 10. In all the flow cases investigated, the calculated results are in good agreement with data. This new near-wall model is less ad hoc, physically and mathematically more sound and eliminates the empiricism introduced by Zhang. Therefore, it is quite general, as demonstrated by the good agreement achieved with measurements covering a wide range of Reynolds numbers and Mach numbers

Can policy analysis theories predict and inform policy change? Reflections on the battle for legal abortion in Indonesia

The relevance and importance of research for understanding policy processes and influencing policies has been much debated, but studies on the effectiveness of policy theories for predicting and informing opportunities for policy change (i.e. prospective policy analysis) are rare

<i>Trypanosoma brucei rhodesiense</i> transmitted by a single tsetse fly bite in vervet monkeys as a model of human African trypanosomiasis

Sleeping sickness is caused by a species of trypanosome blood parasite that is transmitted by tsetse flies. To understand better how infection with this parasite leads to disease, we provide here the most detailed description yet of the course of infection and disease onset in vervet monkeys. One infected tsetse fly was allowed to feed on each host individual, and in all cases infections were successful. The characteristics of infection and disease were similar in all hosts, but the rate of progression varied considerably. Parasites were first detected in the blood 4-10 days after infection, showing that migration of parasites from the site of fly bite was very rapid. Anaemia was a key feature of disease, with a reduction in the numbers and average size of red blood cells and associated decline in numbers of platelets and white blood cells. One to six weeks after infection, parasites were observed in the cerebrospinal fluid (CSF), indicating that they had moved from the blood into the brain; this was associated with a white cell infiltration. This study shows that fly-transmitted infection in vervets accurately mimics human disease and provides a robust model to understand better how sleeping sickness develops

Properties of 42 Solar-type Kepler Targets from the Asteroseismic Modeling Portal

Recently the number of main-sequence and subgiant stars exhibiting solar-like oscillations that are resolved into individual mode frequencies has increased dramatically. While only a few such data sets were available for detailed modeling just a decade ago, the Kepler mission has produced suitable observations for hundreds of new targets. This rapid expansion in observational capacity has been accompanied by a shift in analysis and modeling strategies to yield uniform sets of derived stellar properties more quickly and easily. We use previously published asteroseismic and spectroscopic data sets to provide a uniform analysis of 42 solar-type Kepler targets from the Asteroseismic Modeling Portal (AMP). We find that fitting the individual frequencies typically doubles the precision of the asteroseismic radius, mass and age compared to grid-based modeling of the global oscillation properties, and improves the precision of the radius and mass by about a factor of three over empirical scaling relations. We demonstrate the utility of the derived properties with several applications.Comment: 12 emulateapj pages, 9 figures, 1 online-only extended figure, 1 table, ApJS accepted (typo corrected in Eq.8

keynote 412 phase iii study of pembrolizumab plus chemoradiation vs chemoradiation alone for locally advanced head and neck squamous cell carcinoma hnscc

n/

Using Web Search Query Data to Monitor Dengue Epidemics: A New Model for Neglected Tropical Disease Surveillance

A variety of obstacles, including bureaucracy and lack of resources, delay detection and reporting of dengue and exist in many countries where the disease is a major public health threat. Surveillance efforts have turned to modern data sources such as Internet usage data. People often seek health-related information online and it has been found that the frequency of, for example, influenza-related web searches as a whole rises as the number of people sick with influenza rises. Tools have been developed to help track influenza epidemics by finding patterns in certain web search activity. However, few have evaluated whether this approach would also be effective for other diseases, especially those that affect many people, that have severe consequences, or for which there is no vaccine. In this study, we found that aggregated, anonymized Google search query data were also capable of tracking dengue activity in Bolivia, Brazil, India, Indonesia and Singapore. Whereas traditional dengue data from official sources are often not available until after a long delay, web search query data is available for analysis within a day. Therefore, because it could potentially provide earlier warnings, these data represent a valuable complement to traditional dengue surveillance

Pancreatic cancer intrinsic PI3Kα activity accelerates metastasis and rewires macrophage component.

Pancreatic ductal adenocarcinoma (PDAC) patients frequently suffer from undetected micro-metastatic disease. This clinical situation would greatly benefit from additional investigation. Therefore, we set out to identify key signalling events that drive metastatic evolution from the pancreas. We searched for a gene signature that discriminate localised PDAC from confirmed metastatic PDAC and devised a preclinical protocol using circulating cell-free DNA (cfDNA) as an early biomarker of micro-metastatic disease to validate the identification of key signalling events. An unbiased approach identified, amongst actionable markers of disease progression, the PI3K pathway and a distinctive PI3Kα activation signature as predictive of PDAC aggressiveness and prognosis. Pharmacological or tumour-restricted genetic PI3Kα-selective inhibition prevented macro-metastatic evolution by hindering tumoural cell migratory behaviour independently of genetic alterations. We found that PI3Kα inhibition altered the quantity and the species composition of the produced lipid second messenger PIP3 , with a selective decrease of C36:2 PI-3,4,5-P3 . Tumoural PI3Kα inactivation prevented the accumulation of pro-tumoural CD206-positive macrophages in the tumour-adjacent tissue. Tumour cell-intrinsic PI3Kα promotes pro-metastatic features that could be pharmacologically targeted to delay macro-metastatic evolution