32 research outputs found

    An End-to-End Time Series Model for Simultaneous Imputation and Forecast

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    Time series forecasting using historical data has been an interesting and challenging topic, especially when the data is corrupted by missing values. In many industrial problem, it is important to learn the inference function between the auxiliary observations and target variables as it provides additional knowledge when the data is not fully observed. We develop an end-to-end time series model that aims to learn the such inference relation and make a multiple-step ahead forecast. Our framework trains jointly two neural networks, one to learn the feature-wise correlations and the other for the modeling of temporal behaviors. Our model is capable of simultaneously imputing the missing entries and making a multiple-step ahead prediction. The experiments show good overall performance of our framework over existing methods in both imputation and forecasting tasks

    Influence of Market Type and Time of Purchase on Bacterial Counts and Salmonella and Listeria Prevalence in Whole Chickens in Vietnam

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    The objective of the current study was to determine the influence of market type and sampling time on Salmonella and Listeria prevalence and bacterial counts of 180 whole chicken carcasses collected from 6 supermarkets (SM), 6 indoor markets (IM), and 6 open markets (OM) in Vietnam, at opening (T0) and 4 h after the opening (T4). Salmonella and Listeria prevalence was at least 25.6% and 42.7%, respectively. Whole birds in IM had greater Salmonella prevalence than birds from both SM and OM by 28.4% and 23.0% (P = 0.006 and 0.022, respectively). Listeria prevalence was lower in whole chickens from SM, at 56.6%, than those in IM and OM (78.6% and 73.2%, P = 0.024 and 0.089, respectively). Whole chicken carcasses had more than 10.1, 7.5, and 9.4 log colony-forming units (CFU)/g of aerobic bacteria, Escherichia coli (E. coli), and coliforms, respectively. Both E. coli and coliform counts were greater in IM than in SM (P = 0.002 and 0.006). However, only E. coli counts differed between SM (7.7 log CFU/g) and OM (8.3 log CFU/g; P = 0.024). These results highlighted high levels of bacteria and high prevalence of Salmonella and Listeria in whole chickens in retail establishments in Vietnam, posing potential food safety and public health risks

    CXCR4 Function Requires Membrane Cholesterol: Implications for HIV Infection

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