Motion and wake structure of spherical particles

This paper presents results from a flow visualization study of the wake structures behind solid spheres rising or falling freely in liquids under the action of gravity. These show remarkable differences to the wake structures observed behind spheres held fixed. The two parameters controlling the rise or fall velocity (i.e., the Reynolds number) are the density ratio between sphere and liquid and the Galileo number.Comment: 9 pages, 8 figures. Higher resolution on demand. To appear in Nonlinearity January 200

Worst-Case Morphs Using Wasserstein ALI and Improved MIPGAN

A morph is a combination of two separate facial images and contains the identity information of two different people. When used in an identity document, both people can be authenticated by a biometric face recognition (FR) system. Morphs can be generated using either a landmark-based approach or approaches based on deep learning, such as generative adversarial networks (GANs). In a recent paper, we introduced a worst-case upper bound on how challenging morphing attacks can be for an FR system. The closer morphs are to this upper bound, the bigger the challenge they pose to FR. We introduced an approach with which it was possible to generate morphs that approximate this upper bound for a known FR system (white box) but not for unknown (black box) FR systems. In this paper, we introduce a morph generation method that can approximate worst-case morphs even when the FR system is not known. A key contribution is that we include the goal of generating difficult morphs during training. Our method is based on adversarially learned inference (ALI) and uses concepts from Wasserstein GANs trained with gradient penalty, which were introduced to stabilise the training of GANs. We include these concepts to achieve a similar improvement in training stability and call the resulting method Wasserstein ALI (WALI). We finetune WALI using loss functions designed specifically to improve the ability to manipulate identity information in facial images and show how it can generate morphs that are more challenging for FR systems than landmark- or GAN-based morphs. We also show how our findings can be used to improve MIPGAN, an existing StyleGAN-based morph generator

Weather radar for urban hydrological applications: lessons learnt and research needs identified from 4 pilot catchments in North-West Europe

International audienceThis study investigates the impact of rainfall estimates of different spatial resolutions on the hydraulic outputs of the models of four of the EU RainGain project’s pilot locations (the Cranbrook catchment (UK), the Herent catchment (Belgium), the Morée-Sausset catchment (France) and the Kralingen District (The Netherlands)). Two storm events, one convective and one stratiform, measured by a polarimetric X-band radar located in Cabauw (The Netherlands) were selected for analysis. The original radar estimates, at 100 m and 1 min resolutions, were aggregated to a spatial resolution of 1000 m. These estimates were then applied to the high-resolution semi-distributed hydraulic models of the four urban catchments, all of which have similar size (between 5 and 8 km2), but different morphological, hydrological and hydraulic characteristics. When doing so, methodologies for standardising rainfall inputs and making results comparable were implemented. The response of the different catchments to rainfall inputs of varying spatial resolution is analysed in the light of model configuration, catchment and storm characteristics. Rather surprisingly, the results show that for the two events under consideration the spatial resolution (i.e. 100 m vs 1000 m) of rainfall inputs does not have a significant influence on the outputs of urban drainage models. The present study will soon be extended to more storms as well as model structures and resolutions, with the final aim of identifying critical spatial-temporal resolutions for urban catchment modelling in relation to catchment and storm event characteristics

Research on alcohol and other drug (AOD) use among sexual minority women: A global scoping review

Until the 1980s, the limited research on alcohol and other drug (AOD) use among sexual minority women (SMW) focused on alcohol and used samples recruited from gay bars, resulting in inflated estimates of hazardous drinking. Over the past several decades the number of AOD studies with SMW has increased dramatically. To characterize this literature, we conducted a scoping review to answer the following questions: What do we know, and what are the gaps in research about AOD use among SMW? We searched multiple electronic databases (Medline [PubMed], CINAHL, PsycInfo, and Web of Science) for peer-reviewed research articles about AOD use among adult SMW published between January 1, 2000 and May 31, 2017. After duplicates were removed the search identified 4,204 articles. We reviewed the titles and abstracts and removed articles that did not meet inclusion criteria. We used full-text review of the remaining 229 articles to make a final determination regarding inclusion and we retained 181 articles for review. Although the quantity of AOD research with SMW has grown substantially, the great majority of studies have been conducted in the United States (US) and most focus on hazardous drinking; relatively little research has focused on other drugs. In addition, although there has been marked improvement in theories and methods used in this research, many gaps and limitations remain. Examples are the lack of longitudinal research; reliance on samples that tend to over-represent white, well-educated, and relatively young women; sparse attention to mechanisms underlying the disproportionately high rates of AOD use among SMW; and the absence of intervention research. In general, more high-quality research on SMW\u27s use of AODs is needed, but gaps and limitations are particularly large in non-western countries. Addressing these research gaps and limitations is essential for providing information that can be used to develop more effective prevention and early intervention strategies, as well as for informing policies that can help to reduce risky drinking and drug misuse among SMW

G protein-coupled receptors are dynamic regulators of digestion and targets for digestive diseases

G protein-coupled receptors (GPCRs) are the largest family of transmembrane signaling proteins. Within the gastrointestinal tract, GPCRs expressed by epithelial cells sense contents of the lumen, and GPCRs expressed by epithelial cells, myocytes, neurons, and immune cells participate in communication amongst cells. GPCRs control digestion, mediate digestive diseases, and coordinate repair and growth. GPCRs are the target of over one third of therapeutic drugs, including many drugs used to treat digestive diseases. Recent advances in structural, chemical, and cell biology research have revealed that GPCRs are not static binary switches that operate from the plasma membrane to control a defined set of intracellular signals. Rather, GPCRs are dynamic signaling proteins that adopt distinct conformations and subcellular distributions when associated with different ligands and intracellular effectors. An understanding of the dynamic nature of GPCRs has provided insights into the mechanism of activation and signaling of GPCRs, and has revealed opportunities for drug discovery. We review the allosteric modulation, biased agonism, oligomerization, and compartmentalized signaling of GPCRs that control digestion and digestive diseases. We highlight the implications of these concepts for the development of selective and effective drugs to treat diseases of the gastrointestinal tract

From Sensing to Action: Quick and Reliable Access to Information in Cities Vulnerable to Heavy Rain

Cities need to constantly monitor weather to anticipate heavy storm events and reduce the impact of floods. Information describing precipitation and ground conditions at high spatio-temporal resolution is essential for taking timely action and preventing damages. Traditionally, rain gauges and weather radars are used to monitor rain events, but these sources provide low spatial resolutions and are subject to inaccuracy. Therefore, information needs to be complemented with data from other sources: from citizens' phone calls to the authorities, to relevant online media posts, which have the potential of providing timely and valuable information on weather conditions in the city. This information is often scattered through different, static, and not-publicly available databases. This makes it impossible to use it in an aggregate, standard way, and therefore hampers efficiency of emergency response. In this paper, we describe information sources relating to a heavy rain event in Rotterdam on October 12-14, 2013. Rotterdam weather monitoring infrastructure is composed of a number of rain gauges installed at different locations in the city, as well as a weather radar network. This sensing network is currently scarcely integrated and logged data are not easily accessible during an emergency. Therefore, we propose a reliable, efficient, and low-cost ICT infrastructure that takes information from all relevant sources, including sensors as well as social and user contributed information and integrates them into a unique, cloud-based interface. The proposed infrastructure will improve efficiency in emergency responses to extreme weather events and, ultimately, guarantee more safety to the urban population