Gated Ensemble of Spatio-temporal Mixture of Experts for Multi-task Learning in Ride-hailing System

Designing spatio-temporal forecasting models separately in a task-wise and city-wise manner poses a burden for the expanding transportation network companies. Therefore, a multi-task learning architecture is proposed in this study by developing gated ensemble of spatio-temporal mixture of experts network (GESME-Net) with convolutional recurrent neural network (CRNN), convolutional neural network (CNN), and recurrent neural network (RNN) for simultaneously forecasting spatio-temporal tasks in a city as well as across different cities. Furthermore, a task adaptation layer is integrated with the architecture for learning joint representation in multi-task learning and revealing the contribution of the input features utilized in prediction. The proposed architecture is tested with data from Didi Chuxing for: (i) simultaneously forecasting demand and supply-demand gap in Beijing, and (ii) simultaneously forecasting demand across Chengdu and Xian. In both scenarios, models from our proposed architecture outperformed the single-task and multi-task deep learning benchmarks and ensemble-based machine learning algorithms.Comment: arXiv admin note: text overlap with arXiv:2012.0886

Protease activity of some mesophilic streptomycetes isolated from Egyptian habitats

Different streptomycetes (317 isolates) were obtained from several sources and areas in Egypt and were screened for proteolytic activity. Thirty nine of them produced proteases and were subjected to identification. Streptomyces anulatus formed the most abundant portion of the isolates. This species deserves special attention because it is a good candidate for biotechnological applications

Hepatitis D double reflex testing of all hepatitis B carriers in low-HBV- and high-HBV/HDV-prevalence countries

Hepatitis D virus (HDV) infection occurs as a coinfection with hepatitis B and increases the risk of hepatocellular carcinoma, decompensated cirrhosis, and mortality compared to hepatitis B virus (HBV) monoinfection. Reliable estimates of the prevalence of HDV infection and disease burden are essential to formulate strategies to find coinfected individuals more effectively and efficiently. The global prevalence of HBV infections was estimated to be 262,240,000 in 2021. Only 1,994,000 of the HBV infections were newly diagnosed in 2021, with more than half of the new diagnoses made in China. Our initial estimates indicated a much lower prevalence of HDV antibody (anti-HDV) and HDV RNA positivity than previously reported in published studies. Accurate estimates of HDV prevalence are needed. The most effective method to generate estimates of the prevalence of anti-HDV and HDV RNA positivity and to find undiagnosed individuals at the national level is to implement double reflex testing. This requires anti-HDV testing of all hepatitis B surface antigen-positive individuals and HDV RNA testing of all anti-HDV-positive individuals. This strategy is manageable for healthcare systems since the number of newly diagnosed HBV cases is low. At the global level, a comprehensive HDV screening strategy would require only 1,994,000 HDV antibody tests and less than 89,000 HDV PCR tests. Double reflex testing is the preferred strategy in countries with a low prevalence of HBV and those with a high prevalence of both HBV and HDV. For example, in the European Union and North America only 35,000 and 22,000 cases, respectively, will require anti-HDV testing annually

Global prevalence and genotype distribution of hepatitis C virus infection in 2015 : A modelling study

Publisher Copyright: © 2017 Elsevier LtdBackground The 69th World Health Assembly approved the Global Health Sector Strategy to eliminate hepatitis C virus (HCV) infection by 2030, which can become a reality with the recent launch of direct acting antiviral therapies. Reliable disease burden estimates are required for national strategies. This analysis estimates the global prevalence of viraemic HCV at the end of 2015, an update of—and expansion on—the 2014 analysis, which reported 80 million (95% CI 64–103) viraemic infections in 2013. Methods We developed country-level disease burden models following a systematic review of HCV prevalence (number of studies, n=6754) and genotype (n=11 342) studies published after 2013. A Delphi process was used to gain country expert consensus and validate inputs. Published estimates alone were used for countries where expert panel meetings could not be scheduled. Global prevalence was estimated using regional averages for countries without data. Findings Models were built for 100 countries, 59 of which were approved by country experts, with the remaining 41 estimated using published data alone. The remaining countries had insufficient data to create a model. The global prevalence of viraemic HCV is estimated to be 1·0% (95% uncertainty interval 0·8–1·1) in 2015, corresponding to 71·1 million (62·5–79·4) viraemic infections. Genotypes 1 and 3 were the most common cause of infections (44% and 25%, respectively). Interpretation The global estimate of viraemic infections is lower than previous estimates, largely due to more recent (lower) prevalence estimates in Africa. Additionally, increased mortality due to liver-related causes and an ageing population may have contributed to a reduction in infections. Funding John C Martin Foundation.publishersversionPeer reviewe

The immunopathology of human schistosomiasis-III: immunoglobulin isotype profiles and response to praziquantel

Immunoglobulin (Ig) isotype (IgG, IgG1, IgG2, IgG3, IgG4, IgM, IgD and IgE) levels were investigated, both pre- and post-treatment with praziquantel (PZQ), in 43 adults and children chronically infected with Schistosoma mansoni , by means of a two-site, isotype-specific immunoenzymometric assay. The patients were classified as responders (R) or non-responders (NR) on the basis of their circumoval precipitin test (COPT) results 12 months after treatment. In comparison with controls, pre-treatment R children showed significantly higher levels of IgG, IgG1, IgG4 (p<0.001) and IgE (p<0.01), and diminished IgG2 (p<0.05), while NR children showed significantly elevated levels only of IgE (p<0.05). Twelve months after therapy, R children maintained significantly lower levels of IgG2, but showed significantly decreased levels of IgG, IgG1, IgG4, and IgE, while the Ig isotype profile of NR children was unaltered. Adult R and NR showed similar isotype profiles before chemotherapy, with the exception of significantly elevated IgM levels in R. Twelve months after therapy, R adults showed significantly decreased levels of IgG, IgG1, and IgG4, while NR adults showed only diminshed IgG4 levels. These results reveal different Ig isotype profiles in untreated adults and children chronically infected with S. mansoni. The results further show that the pre-treatment Ig isotype profile may be significantly modified after an effective R to chemotherapy, accounted for by down regulation of the IgG1 isotype in association with negative seroconversion of the COPT in R patients. The COPT reaction has been associated with the highly specific egg glycoprotein antigen w1, which shows a significant reduction in reactivity six months after treatment. IgG1 may thus play a main role in the response against the w1 antigen

Effects of street pattern, traffic, road infrastructure, socioeconomic and demographic characteristics on public transit ridership

Travel demand is increasing in many countries and the transportation sector produces about 14% of the global greenhouse gas emission, which has been linked to the current climate change. As the oil and gas capital of Canada, the City of Calgary has a very high carbon footprint per population. Hence, the increase usage of transit and the reduction of auto dependency is an important policy goal for the city, and understanding the determinants of transit ridership is a critical first step to achieving this goal. The objective of the study is to identify the effects of different street patterns, traffic, road infrastructure, socioeconomic and demographic characteristics on public transit ridership in 185 community areas of the city. Our results suggest that several street patterns have a significant effect on public transit usage and thus should be considered in the development of new communities for promoting public transit. Also, increases in commercial areas, expressways or highways and train stations are associated with greater transit use. In addition to these physical attributes, a number of socioeconomic and demographic characteristics related to income, age, living pattern and minority or immigrant populations are important determinants of public transit use

Urban design and planning influences on the share of trips taken by cycling

This study examines the effect of different street pattern, road infrastructure and other physical attributes on the share of bicycle trips in a community area. Using the 2011 census data and the road infrastructure data of Calgary city, the study finds that different street patterns have significant effects on bicycle usage and thus, should be considered in the development of new communities for promoting active transport. Also, increases in the percentage of green space (agricultural and park areas) and semi-detached houses are associated with greater bicycle use, whereas an increase in the number and/or size (area) of road intersections is associated with reduced bicycle use relative to other modes of transport

Effect of Community Road Infrastructure, Socio-Demographic and Street Pattern in Promoting Walking as Sustainable Transportation Mode

Background: Traffic demand is growing worldwide and the increased carbon emission from transport and travel activities is contributing to greenhouse gas emission and climate change. As the oil and gas capital of Canada, the city of Calgary has a very high carbon footprint per population and the reduction of automobile use is an important policy goal for the city. Walking, a part of active transportation promotes sustainable transportation initiative by reducing greenhouse gas emission. To encourage walking, favorable walking environment should be ensured which largely depends on street pattern and connectivity. However, the effect of street pattern on walking at community level was not explored much in previous studies, particularly at rapidly expanding city such as Calgary&#039;s context. Aims and Objectives: The study identifies the effects of different neighborhood design and planning factors associated with the share of walking in work trips while controlling for differences in social economic characteristics of the neighborhood. Methods: A linear regression model was developed using community-level data from the 2011 census and the road infrastructure data of Calgary. Results: Our study finds that different street patterns and types of land use, length of train tracks, number of train stations and number of schools have significant effect on walking. Conclusion: Thus, different neighbourhood street patterns and land uses should be considered in the development of new communities for promoting active and sustainable transportation