宁夏银川平原沙化土地不同人工林土壤质量评价

沙化土地土壤贫瘠、生产力低,人工植被恢复是重要的土壤改良措施。为研究宁夏银川平原沙地不同人工林栽植对土壤的影响,以银川腹部沙地银川植物园沙化土壤恢复区的2017年3月种植的文冠果(Xanthoceras sorbifolium)和欧李(Cerasus humilis)人工林地为研究对象,以邻近的长期撂荒地为对照,对土壤质量进行了研究。2020年7—8月采集土样并测定了土壤物理、化学、生物学等20个指标作为土壤质量评价的总数据集,方差分析筛选出差异显著性的9个指标作为重要数据集指标,采用主成分分析法和Norm值建立土壤质量评价指标最小数据集(MDS),利用线性和非线性两种评分方法计算土壤质量指数(SQI)。结果表明：与长期撂荒地相比,银川平原沙化土壤恢复区人工文冠果、欧李林地的土壤理化性质较好,土壤砂粒百分比减少、粉粒和黏粒百分比有所增加,pH降低;有机质、全氮、全磷、全钾等主要养分指标提高,蔗糖酶、脲酶、纤维素酶等主要生物酶活性也高于撂荒地,筛选出的研究区土壤质量评价MDS指标为土壤粉粒百分比和全磷。2种评价方法下,文冠果和欧李人工恢复林地的SQI高于撂荒地,但提高不显著(P>0...     

基于主体功能区的长江经济带绿色发展评价与问题区域识别

长江经济带已成为我国推进绿色发展的重要阵地。基于主体功能区视角,构建以水系统为纽带的长江经济带绿色发展评价指标体系,采用综合加权法、空间自相关、耦合协调度模型等方法探究2018年长江经济带130个城市绿色发展及各子系统耦合协调水平的空间格局,并对绿色发展的问题区域进行分类识别。结果表明：(1)长江经济带绿色发展水平呈由下游、中游至上游递减趋势;各主体功能区绿色发展指数表现为优化开发区>限制开发区>重点开发区。(2)绿色发展各子系统耦合协调度值位于0.365—0.656之间,多处于濒临失调和勉强协调的临界区间,耦合协调水平整体偏低。(3)从长江经济带整体来看,长江中上游地区绝大部分城市绿色发展主要受资源利用和产业发展水平偏低,及由此带来的生态和生活问题限制,且长江中上游地区各省会或直辖市对区域内其他城市绿色发展带动能力不足。从主体功能区视角来看,优化开发区以生态问题为主,仅上海和嘉兴两市;重点开发区以生态和生产问题为主,集中于武汉都市圈和成渝双城经济圈内部;限制开发区以生产和生活问题为主,主要位于省际边界型城市地区。最后综合问题识别结果,分别对长江经济带各主要问题区域绿色发展...     

盘鮈属鱼类的分类研究及两新种记述(鲤形目:鲤科)

盘鮈属是我国鲤科鱼类的一个特有属,过去已记录7种,因早期发表的云南盘鮈原始描述简略,国内又无人察看过模式标本,造成一些种名归属混乱。本工作在核对多数种的模式标木或地模标本的基础上,对盘鮈属鱼类的分类性状重新估价,认为多鳞盘鮈 D.polylepis Huang不能成立,为长鳔盘鮈 D.macrophysallidos Huang的同物异名,予以归并,经整理本属鱼类可分为8个种,其中具2个新种,文中给出了分种检索表,还就过去分类中存在的其他问题进行了讨论。     

中国省域生态文明建设进程区域差异化

中国生态文明理论体系和示范实践为我国各地全面推进生态文明建设奠定了基础,区域差异化研究希望通过探究不同区域生态文明建设特征、潜力以及与经济发展的联系,为我国各地区全面推进生态文明实践提供的支持。构建“社会、经济、政治、文化和生态”生态文明指数五维度评价指标体系,运用2005、2010、2015和2019年我国面板数据,刻画31个省份(统计数据尚未包含我国港澳台)生态文明建设的前期、初期、快速发展期和当前各时段时空变化,提出区域的发展速度和发展加速度概念描述各省份建设能力差异,基于各省份生态文明五维度预期目标和历史发展速度探究各省份的发展潜势差异,并初步探究各省份生态文明差异与经济发展的关系。研究结果表明：(1)总体上,各省份的生态文明指数反映出生态文明建设效果显著;时间序列变化上,各省份生态文明建设整体水平和过程存在较大差异性,尽管增长速度都呈现出先快后慢的特点,各省份生态文明水平差距仍然持续拉大;在空间上,明显呈现出东部地区好于西部地区、南部地区好于北部地区的特征,通过分析31个省份所属的六个地区的生态文明等级,发现华东地区和中南地区生态文明等级领先于其他地区,且在各阶段进步最大,而...     

Marginal proportional hazards models for clustered interval-censored data with time-dependent covariates

The Botswana Combination Prevention Project was a cluster-randomized HIV prevention trial whose follow-up period coincided with Botswana's national adoption of a universal test and treat strategy for HIV management. Of interest is whether, and to what extent, this change in policy modified the preventative effects of the study intervention. To address such questions, we adopt a stratified proportional hazards model for clustered interval-censored data with time-dependent covariates and develop a composite expectation maximization algorithm that facilitates estimation of model parameters without placing parametric assumptions on either the baseline hazard functions or the within-cluster dependence structure. We show that the resulting estimators for the regression parameters are consistent and asymptotically normal. We also propose and provide theoretical justification for the use of the profile composite likelihood function to construct a robust sandwich estimator for the variance. We characterize the finite-sample performance and robustness of these estimators through extensive simulation studies. Finally, we conclude by applying this stratified proportional hazards model to a re-analysis of the Botswana Combination Prevention Project, with the national adoption of a universal test and treat strategy now modeled as a time-dependent covariate.     

Integrating sample similarities into latent class analysis: a tree-structured shrinkage approach

This paper is concerned with using multivariate binary observations to estimate the probabilities of unobserved classes with scientific meanings. We focus on the setting where additional information about sample similarities is available and represented by a rooted weighted tree. Every leaf in the given tree contains multiple samples. Shorter distances over the tree between the leaves indicate a priori higher similarity in class probability vectors. We propose a novel data integrative extension to classical latent class models with tree-structured shrinkage. The proposed approach enables (1) borrowing of information across leaves, (2) estimating data-driven leaf groups with distinct vectors of class probabilities, and (3) individual-level probabilistic class assignment given the observed multivariate binary measurements. We derive and implement a scalable posterior inference algorithm in a variational Bayes framework. Extensive simulations show more accurate estimation of class probabilities than alternatives that suboptimally use the additional sample similarity information. A zoonotic infectious disease application is used to illustrate the proposed approach. The paper concludes by a brief discussion on model limitations and extensions.     

Forest resistance to drought in a humid tropical dipterocarp forest in the Western Ghats of India

Droughts are linked to tree die-offs in the biodiverse humid tropics. We assessed drought response of a Dipterocarp Forest and found a marginal decrease in tree survival, indicating drought resistance. Understory and emergent species were sensitive to drought. Urgent focus is needed to understand drought impacts and plant physiological responses in South Asian forests.     

Chiral symmetry breaking: Experimental results and computer analysis of a liquid-phase autoxidation

The autoxidation of tetralin is treated as a model reaction system to define the applicability of stereospecific autocatalysis. This concept, predicting a spontaneous amplification of enantiomeric excess generated by an autocatalytic chemical reaction, is used in several theoretical models as an explanation for the origin of natural optical activity. The reaction system investigated obeys the basic criteria of these models: a chiral intermediate (tetralin hydroperoxide) is produced from an achiral substrate (tetralin) via an autocatalytic pathway where the feedback mechanism is expected to generate a state of broken chiral symmetry. In order to test the amplification capacity of this reaction a computer analysis of the kinetic scheme is performed. This simulation is derived from the known kinetic scheme of autoxidation and is validated by fitting the experimentally observed data of hydroperoxide evolution. Calculations show that this model allows powerful amplification of enantiomeric excess and a transient amplification of the optical rotation. It is also demonstrated that the model system exhibits pronounced sensitivity toward any loss of absolute configuration of the involved chiral species. Since an amplification effect results exclusively at a high degree of stereoselectivity, it is concluded that stereospecific autocatalysis is possible in systems which show template reactions, crystallization, or colloidal effects. © 1993 Wiley-Liss, Inc.     

制药工程“微生物学实验”课程的项目化教学探索与实践

为了培养学生的自主学习能力和实践创新能力,按照工程教育专业认证要求基于成果导向教育(outcome based education, OBE)理念设计课程教学,将制药工程微生物学实验课实验教学项目设置成入门、进阶和自主3种项目等级。实验项目内容由浅入深、逐级递进、层层相关,教学过程以学生为中心,并结合线上教学手段和竞赛机制的支持。实践结果表明,经过项目化教学改革,在教师教学和学生学习成效两个方面均得到明显提升,学生在论文撰写能力、动手能力等方面也有了明显的进步,值得后续进一步总结和推广。     

A mechanistic spatio-temporal modeling of COVID-19 data

Understanding the evolution of an epidemic is essential to implement timely and efficient preventive measures. The availability of epidemiological data at a fine spatio-temporal scale is both novel and highly useful in this regard. Indeed, having geocoded data at the case level opens the door to analyze the spread of the disease on an individual basis, allowing the detection of specific outbreaks or, in general, of some interactions between cases that are not observable if aggregated data are used. Point processes are the natural tool to perform such analyses. We analyze a spatio-temporal point pattern of Coronavirus disease 2019 (COVID-19) cases detected in Valencia (Spain) during the first 11 months (February 2020 to January 2021) of the pandemic. In particular, we propose a mechanistic spatio-temporal model for the first-order intensity function of the point process. This model includes separate estimates of the overall temporal and spatial intensities of the model and a spatio-temporal interaction term. For the latter, while similar studies have considered different forms of this term solely based on the physical distances between the events, we have also incorporated mobility data to better capture the characteristics of human populations. The results suggest that there has only been a mild level of spatio-temporal interaction between cases in the study area, which to a large extent corresponds to people living in the same residential location. Extending our proposed model to larger areas could help us gain knowledge on the propagation of COVID-19 across cities with high mobility levels.