论高校数字图书馆资源建设与信息服务的创新

高校图书馆不但要针对教学科研需要引进多种电子文献,而且要不断建设和更新 网上信息资源,把高校图书馆建设成为学科资源中心,加强电子阅览室的服务和管理。     

世纪之交中国社会语言热点问题大讨论

20世纪与21世纪之交,随着我国改革开放的全方位深化,尤其是市场经济背景、网络的高速普及以及文化多元化的趋势等因素的影响,现代汉语体系的诸多要素都出现了许多问题。诸如新词新语、外来语、旧词新用、网络语言、语法规范等诸多方面都面临挑战,引起学术界的广泛关注和热烈讨论。但是讨论应该围绕语言的本质即语言是什么的大命题进行;在讨论的过程中应注意吸取历史教训,既然是学术争论,就要心平气和,态度要好;同时,应该时刻牢记讨论的目的是重在建设,尤其是理论建设。     

论失地农民社会保障安全网的构建

在城市化进程中,农村集体土地大量被征用,大量的农民被迫离开土地。农民失去了土地也就丧失了最基本的社会保障,社会也由此倍增了不稳定因素,国外在这方面已有前车之鉴。解决此问题的根本出路在于土地被征用后,政府应为失地农民提供长远的生活保障,真正达到提高农民的生活水平和维护社会稳定的双重目的。因此,为失地农民建立安全有效的社会保障安全网是当前政府亟待解决的重要问题。     

基于资源流网络优化的Max-npv项目调度

活动拖期通过资源流网络的传递会严重影响项目的净现值收益。针对该问题，本文首先在确定性环境下采用模拟退火算法(SA)构建了Max-NPV(Maximize the Net Present Value)非鲁棒性基准调度计划，然后考虑到活动工期的不确定性，设计了MEPC(Minimize Expected Penalty Cost)资源流网络优化算法，通过鲁棒性资源分配实现净现值期望惩罚成本最小化。大规模仿真对比实验结果表明，在活动工期低、中、高三种不确定性程度下，相对于采用随机资源分配算法(SA+RRAS)构建的非鲁棒性调度计划，SA+MEPC算法构建的鲁棒性调度计划在项目净现值实际收益、调度计划的“解”鲁棒性和“质”鲁棒性三个方面都取得了更好的结果，并且应对活动拖期风险的能力也更强。     

Development of a novel machine learning-based weighted modeling approach to incorporate Salmonella enterica heterogeneity on a genetic scale in a dose–response modeling framework

Estimating microbial dose–response is an important aspect of a food safety risk assessment. In recent years, there has been considerable interest to advance these models with potential incorporation of gene expression data. The aim of this study was to develop a novel machine learning model that considers the weights of expression of Salmonella genes that could be associated with illness, given exposure, in hosts. Here, an elastic net-based weighted Poisson regression method was proposed to identify Salmonella enterica genes that could be significantly associated with the illness response, irrespective of serovar. The best-fit elastic net model was obtained by 10-fold cross-validation. The best-fit elastic net model identified 33 gene expression–dose interaction terms that added to the predictability of the model. Of these, nine genes associated with Salmonella metabolism and virulence were found to be significant by the best-fit Poisson regression model (p < 0.05). This method could improve or redefine dose–response relationships for illness from relative proportions of significant genes from a microbial genetic dataset, which would help in refining endpoint and risk estimations.