In this paper,we establish and study a single-species logistic model with impulsive age-selective harvesting.First,we prove the ultimate boundedness of the solutions of the system.Then,we obtain conditions for the asy...In this paper,we establish and study a single-species logistic model with impulsive age-selective harvesting.First,we prove the ultimate boundedness of the solutions of the system.Then,we obtain conditions for the asymptotic stability of the trivial solution and the positive periodic solution.Finally,numerical simulations are presented to validate our results.Our results show that age-selective harvesting is more conducive to sustainable population survival than non-age-selective harvesting.展开更多
目的构建留守与非留守中学生自伤的风险预测模型,为制定针对性的干预措施提供科学依据。方法2021年9月―2023年6月采用多阶段抽样方法,在留守儿童分布相对集中的6个省份中抽取14623名<18岁的中学生(留守8471名,非留守6152名)作为研...目的构建留守与非留守中学生自伤的风险预测模型,为制定针对性的干预措施提供科学依据。方法2021年9月―2023年6月采用多阶段抽样方法,在留守儿童分布相对集中的6个省份中抽取14623名<18岁的中学生(留守8471名,非留守6152名)作为研究对象。通过问卷调查收集研究对象的一般情况、创伤性事件和自伤发生情况。分析不同特征留守与非留守中学生自伤的发生情况。采用R 4.3.0软件按照7∶3的比例分别将留守与非留守中学生随机划分为训练集与测试集,构建logistic回归分析模型和随机森林模型,通过受试者工作特征曲线、灵敏度、特异度等指标评估模型性能。结果中学生自伤总体发生率为25.7%,留守中学生自伤发生率高于非留守中学生(χ^(2)=59.266,P<0.001)。Logistic回归分析模型分析结果显示,留守与非留守中学生预测模型训练集的曲线下面积(area under the curve,AUC)分别为0.745和0.756,测试集的AUC分别为0.721和0.726,Hosmer-Lemshow拟合优度检验P>0.05。随机森林模型中,留守中学生自伤的主要预测因素为经历创伤性事件、家庭氛围、和父亲/母亲关系等,模型的灵敏度、特异度、阳性预测值、阴性预测值和F1指数分别为0.740、0.591、0.822、0.470和0.779,Brier分数为0.212,训练集和测试集的AUC分别为0.800和0.729。非留守中学生则以经历创伤性事件、家庭氛围、父母感情状况等为主,模型的灵敏度、特异度、阳性预测值、阴性预测值和F1指数分别为0.785、0.519、0.850、0.411和0.816,Brier分数为0.188,训练集和测试集的AUC分别为0.845和0.724。结论留守中学生自伤风险高于非留守中学生,二者的预测因素虽有不同,但存在高度重叠,其中创伤经历和家庭因素是关键预测变量。两种模型对自伤的识别能力良好,但随机森林模型综合性能更优,本研究构建的预测模型可为早期识别高危人群提供科学依据。展开更多
Bangladesh has a denser population in comparison with many other countries. Though the rate of population increase has been regarded as a concerning issue, estimation of the population instability in the upcoming year...Bangladesh has a denser population in comparison with many other countries. Though the rate of population increase has been regarded as a concerning issue, estimation of the population instability in the upcoming years may be useful for national planning. To predict Bangladesh’s future population, this study compares the estimated populations of two popular population models, the Malthusian and the logistic population models, with the country’s census population published by BBS. We also tried to find out which model gives a better approximation for forecasting the past, present, and future population between these two models.展开更多
基金Supported by the National Natural Science Foundation of China(12261018)Universities Key Laboratory of Mathematical Modeling and Data Mining in Guizhou Province(2023013)。
文摘In this paper,we establish and study a single-species logistic model with impulsive age-selective harvesting.First,we prove the ultimate boundedness of the solutions of the system.Then,we obtain conditions for the asymptotic stability of the trivial solution and the positive periodic solution.Finally,numerical simulations are presented to validate our results.Our results show that age-selective harvesting is more conducive to sustainable population survival than non-age-selective harvesting.
文摘目的构建留守与非留守中学生自伤的风险预测模型,为制定针对性的干预措施提供科学依据。方法2021年9月―2023年6月采用多阶段抽样方法,在留守儿童分布相对集中的6个省份中抽取14623名<18岁的中学生(留守8471名,非留守6152名)作为研究对象。通过问卷调查收集研究对象的一般情况、创伤性事件和自伤发生情况。分析不同特征留守与非留守中学生自伤的发生情况。采用R 4.3.0软件按照7∶3的比例分别将留守与非留守中学生随机划分为训练集与测试集,构建logistic回归分析模型和随机森林模型,通过受试者工作特征曲线、灵敏度、特异度等指标评估模型性能。结果中学生自伤总体发生率为25.7%,留守中学生自伤发生率高于非留守中学生(χ^(2)=59.266,P<0.001)。Logistic回归分析模型分析结果显示,留守与非留守中学生预测模型训练集的曲线下面积(area under the curve,AUC)分别为0.745和0.756,测试集的AUC分别为0.721和0.726,Hosmer-Lemshow拟合优度检验P>0.05。随机森林模型中,留守中学生自伤的主要预测因素为经历创伤性事件、家庭氛围、和父亲/母亲关系等,模型的灵敏度、特异度、阳性预测值、阴性预测值和F1指数分别为0.740、0.591、0.822、0.470和0.779,Brier分数为0.212,训练集和测试集的AUC分别为0.800和0.729。非留守中学生则以经历创伤性事件、家庭氛围、父母感情状况等为主,模型的灵敏度、特异度、阳性预测值、阴性预测值和F1指数分别为0.785、0.519、0.850、0.411和0.816,Brier分数为0.188,训练集和测试集的AUC分别为0.845和0.724。结论留守中学生自伤风险高于非留守中学生,二者的预测因素虽有不同,但存在高度重叠,其中创伤经历和家庭因素是关键预测变量。两种模型对自伤的识别能力良好,但随机森林模型综合性能更优,本研究构建的预测模型可为早期识别高危人群提供科学依据。
文摘Bangladesh has a denser population in comparison with many other countries. Though the rate of population increase has been regarded as a concerning issue, estimation of the population instability in the upcoming years may be useful for national planning. To predict Bangladesh’s future population, this study compares the estimated populations of two popular population models, the Malthusian and the logistic population models, with the country’s census population published by BBS. We also tried to find out which model gives a better approximation for forecasting the past, present, and future population between these two models.
