9 research outputs found

    A new scheduling method based on sequential time windows developed to distribute first-aid medicine for emergency logistics following an earthquake.

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    After an earthquake, affected areas have insufficient medicinal supplies, thereby necessitating substantial distribution of first-aid medicine from other supply centers. To make a proper distribution schedule, we considered the timing of supply and demand. In the present study, a "sequential time window" is used to describe the time to generate of supply and demand and the time of supply delivery. Then, considering the sequential time window, we proposed two multiobjective scheduling models with the consideration of demand uncertainty; two multiobjective stochastic programming models were also proposed to solve the scheduling models. Moreover, this paper describes a simulation that was performed based on a first-aid medicine distribution problem during a Wenchuan earthquake response. The simulation results show that the methodologies proposed in this paper provide effective schedules for the distribution of first-aid medicine. The developed distribution schedule enables some supplies in the former time windows to be used in latter time windows. This schedule increases the utility of limited stocks and avoids the risk that all the supplies are used in the short-term, leaving no supplies for long-term use

    Energy-theft detection issues for advanced metering infrastructure in smart grid

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    Maternal Body Mass Index, Gestational Weight Gain, and Risk of Cancer in Offspring: A Systematic Review and Meta-Analysis

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    Background: Mounting evidence suggests that maternal obesity and gestational weight gain (GWG) may increase the risk of cancer in their offspring; however, results are inconsistent. The purpose of this research is to determine the association between maternal body mass index (BMI) and GWG and the risk of cancer in offspring through a systematic and comprehensive meta-analysis. Methods: A systematic literature search of several databases was conducted on 1 October 2022 to identify relevant studies. The quality of the included studies was evaluated using the Newcastle–Ottawa scale. The overall risk estimates were pooled using a random-effects meta-analysis. Results: Twenty-two studies with more than 8 million participants were included. An increased risk of total cancer was found in offspring whose mothers had a high GWG (odds ratio [OR]: 1.10; 95% CI: 1.01–1.19; p: 0.040) but not in offspring whose mothers had a low GWG (OR: 1.06; 95% CI: 0.96–1.17; p: 0.030), when compared with offspring whose mothers had a suitable GWG. In addition, no statistically significant association was found between maternal underweight (OR: 1.05; 95% CI: 0.97–1.13; p: 0.630), overweight/obesity (OR: 1.07; 95% CI: 0.99–1.16; p: 0.020), and risk of total cancer in offspring. Conclusions: Our study proposes evidence that maternal BMI and GWG may be associated with the risk of cancer in offspring, although statistical significance was found only for high GWG. Further well-designed research is required to clarify the potential relevance of maternal BMI and GWG on offspring cancer, especially for specific cancers
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