Notes

Security look at crosslinked polyacrylic acidity polymers (carbomer) as a new foodstuff additive.
Researchers should continue to share lessons learned from conducting web-based trials of web-based interventions to benefit future studies. International registered report RR2-10.1136/bmjopen-2017-016965.Background The prevalence of obesity and diabetes among middle-aged and older adults is on the rise, and with an increase in the world population of adults aged 60 years and older, the demand for health interventions across age groups is growing. Noom is an mHealth behavior change lifestyle intervention that provides users with tracking features for food and exercise logging and weighing-in as well as access to a virtual 11 behavior change coach, support group, and daily curriculum that includes diet-, exercise-, and psychology-based content. Limited research has observed the effect of age on a mobile health (mHealth) lifestyle intervention. Objective The goal of the research was to analyze engagement of middle-aged and older adults using a mobile lifestyle or diabetes prevention intervention. Methods A total of 14,767 adults (aged 35 to 85 years) received one of two curricula via an mHealth intervention in a quasi-experimental study the Healthy Weight program (HW) by Noom (84%) or the Noom-developed Diabeteson compared with younger adults, despite their engagement. These preliminary findings suggest further clinical implications for adapting the program to older adults' needs.Background Late HIV-diagnoses foster HIV-transmission and may nurture hidden HIV-epidemics. In Belgium, mathematical modelling indicates high prevalence of undiagnosed HIV-infections among men who have sex with men (MSM) of non-Belgian origin and among sub-Saharan African Migrants (SAM). Promotion of HIV-testing facilitates early diagnoses, but diagnostic opportunities are being missed in primary care. This protocol presents the conceptual development, implementation and evaluation of an HIV-testing intervention for Flemish general practitioners (GPs). Objective The intervention study intends to enhance provider-initiated HIV-testing by GPs. Methods Guided by a simplified intervention mapping approach, an evidence-based intervention was developed in collaboration guided by an interdisciplinary advisory board (AB). The intervention consists of an evidence-based tool (i.e. 'HIV-testing advice for primary care') to support GP's in provider-initiated HIV testing. A mixed methods evaluation design is used A modifitober 2019 and was the starting point for the ongoing data analysis. A publication on its results is expected in the second half of 2020. selleck inhibitor Conclusions Results of the intervention study will provide useful information on the intervention's effectiveness among Flemish GPs and can inform further development of official testing guidelines. Limitation of this real-life intervention approach are potential spill-over effects, delay in access to surveillance data and little detailed information on HIV-testing practices among GPs. Clinicaltrial ClinicalTrials.gov, Identifier NCT04056156, August 14, 2019, Retrospectively registered. International registered report DERR1-10.2196/16486.This article presents a distributed, efficient, scalable, and real-time motion planning algorithm for a large group of agents moving in 2-D or 3-D spaces. This algorithm enables autonomous agents to generate individual trajectories independently with only the relative position information of neighboring agents. Each agent applies a force-based control that contains two main terms 1) collision avoidance and 2) navigational feedback. The first term keeps two agents separate with a certain distance, while the second term attracts each agent toward its goal location. Compared with existing collision-avoidance algorithms, the proposed force-based motion planning (FMP) algorithm can find collision-free motions with lower transition time, free from velocity state information of neighboring agents. It leads to less computational overhead. The performance of proposed FMP is examined over several dense and complex 2-D and 3-D benchmark simulation scenarios, with results outperforming existing methods.One-shot image semantic segmentation poses a challenging task of recognizing the object regions from unseen categories with only one annotated example as supervision. In this article, we propose a simple yet effective similarity guidance network to tackle the one-shot (SG-One) segmentation problem. We aim at predicting the segmentation mask of a query image with the reference to one densely labeled support image of the same category. To obtain the robust representative feature of the support image, we first adopt a masked average pooling strategy for producing the guidance features by only taking the pixels belonging to the support image into account. We then leverage the cosine similarity to build the relationship between the guidance features and features of pixels from the query image. In this way, the possibilities embedded in the produced similarity maps can be adopted to guide the process of segmenting objects. Furthermore, our SG-One is a unified framework that can efficiently process both support and query images within one network and be learned in an end-to-end manner. We conduct extensive experiments on Pascal VOC 2012. In particular, our SG-One achieves the mIoU score of 46.3%, surpassing the baseline methods.In applications of domain adaptation, there may exist multiple source domains, which can provide more or less complementary knowledge for pattern classification in the target domain. In order to improve the classification accuracy, a decision-level combination method is proposed for the multisource domain adaptation based on evidential reasoning. The classification results obtained from different source domains usually have different reliabilities/weights, which are calculated according to domain consistency. Therefore, the multiple classification results are discounted by the corresponding weights under belief functions framework, and then, Dempster's rule is employed to combine these discounted results. In order to reduce errors, a neighborhood-based cautious decision-making rule is developed to make the class decision depending on the combination result. The object is assigned to a singleton class if its neighborhoods can be (almost) correctly classified. Otherwise, it is cautiously committed to the disjunction of several possible classes.
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