An introduction experiment of an herbivorous lady beetle: Characteristics of the adult population

In May 1971, 45 adults of an herbivorous lady beetleEpilachna niponica (Coleoptera: Coccinellidae) from Asiu Experimental Forest were introduced into a botanical garden of Kyoto University, where is 10 km south of the southern limits of its distribution with being 3–5°C warmer than the original site. The introduced population of the lady beetle was thus investigated from 1975 to 1981. Mark-release-recapture experiments were applied to individual adult beetles, to estimate population size and daily survival rate. Overwintering adults emerged from hibernation around early April, reaching peak numbers in late April to early May, then gradually declined to late June. No adults remained at the end of June. Adult survival was maintained at a high level to early May, and declined consistently until late in the reproductive season. New adults began to emerge in late June and quickly reached a peak in early July; thereafter they decreased in number and had entered hibernation by late October. In spite of seasonally deteriorating food resources and heat stress in summer, new adults showed moderately high survival during the inimical period. New adults which emerged later in the season tended to be smaller in body size than those that emerged early. The proportion of females in the new adult population gradually increased throughout the pre-hibernating period, suggesting that male-biased mortality occurred during this period. When compared to the source population, the introduced population had a higher rate of population growth. Coupled with the improved population growth, heavy leaf damage during the larval period suggested that intensive intraspecific competition was most likely to occur among larvae in the introduced population.     

Statistical problems in environmental research

Growing concern about the health effects of exposure to pollutants and other chemicals in the environment has stimulated new research to detect and quantify environmental hazards. This research has generated many interesting and challenging methodological problems for statisticians. One type of statistical research develops new methods for the design and analysis of individual studies. Because current research of this type is too diverse to summarize in a single article, we discuss current work in two areas of application: the carcinogen bioassay in small rodents and epidemiologic studies of air pollution. To assess the risk of a potentially harmful agent, one must frequently combine evidence from different and often quite dissimilar studies. Hence, this paper also discusses the central role of data synthesis in risk assessment, reviews some of the relevant statistical literature, and considers the role of statisticians in evaluating and combining evidence from diverse sources.     

Exposure Stratified Case-Cohort Designs

A variant of the case-cohort design is proposed for the situation in which a correlate of the exposure (or prognostic factor) of interest is available for all cohort members, and exposure information is to be collected for a case-cohort sample. The cohort is stratified according to the correlate, and the subcohort is selected by stratified random sampling. A number of possible methods for the analysis of such exposure stratified case-cohort samples are presented, some of their statistical properties developed, and approximate relative efficiency and optimal allocation to the strata discussed. The methods are compared to each other, and to randomly sampled case-cohort studies, in a limited computer simulation study. We found that all of the proposed analysis methods performed well and were more efficient than a randomly sampled case-cohort study.     

Bayesian Methods for a Growth-Curve Degradation Model with Repeated Measures

The increasingreliability of some manufactured products has led to fewer observedfailures in reliability testing. Thus, useful inference on thedistribution of failure times is often not possible using traditionalsurvival analysis methods. Partly as a result of this difficulty,there has been increasing interest in inference from degradationmeasurements made on products prior to failure. In the degradationliterature inference is commonly based on large-sample theoryand, if the degradation path model is nonlinear, their implementationcan be complicated by the need for approximations. In this paperwe review existing methods and then describe a fully Bayesianapproach which allows approximation-free inference. We focuson predicting the failure time distribution of both future unitsand those that are currently under test. The methods are illustratedusing fatigue crack growth data.     

What Difference Does the Dependence Between Durations Make? Insights for Population Studies of Aging

The interpretation of age-specific changes in hazards, relative risks, genetic parameters and other indicators of aging calculated from data on related individuals should take into account the regularities of bivariate selection. Due to such selection the hazard rate calculated for twins who have survived to a certain age may be lower than for singletons, even if marginal chances of survival for all individuals are the same. In a mixed population of relatives the proportion of pairs with closer family links increases with age, even if all marginal individual chances of survival are the same. The proportion of chronic conditions for MZ twins observed in a cross-sectional study may be different from that of DZ twins. The age-dependence of relative risks calculated in genetic-epidemiological studies of twins does not necessarily reflect changes in genetic influence on individual susceptibility to disease and death during the aging process. The age-related changes in heritability of susceptibility estimated in twin studies may have nothing to do with changes in the genetic determination of diseases with age. These issues are illustrated by empirical graphs together with the results of modeling and statistical analysis.     

论文化哲学的历史视域和当代走势

人是历史的存在,也是文化的存在。无论是历史和文化都承载和蕴涵着一种厚重而深邃的生存价值。文化哲学正是从这一历史视域出发来理解文化发展的当代意蕴的,那便是文化的生存意义、文化的批判性功能和文化的综合进化趋势。     

知识论研究的问题与实质

现代西方知识论研究特别明显地表现了形而上学的特征:哲学家们对知识的研究不是从知识的获得过程和知识的最终形式上探究其中的思维活动内容,而主要是研究知识的基本性质、知识成为可能的条件以及知识表达的形式与世界之间的关系。这些不仅构成了现代知识论的基本内容,同时也体现了知识论与认识论的不同。在当代,西方知识论发展的一个明显的变化是随着分析哲学作为主流哲学的登场,"形而上学"遭到无情的批判与摒弃。为知识寻求形而上学根据之类的努力,被斥为无意义的东西。哲学、知识论回到经验论。虽然如此,知识论寻求知识根据的努力依然在进行着,只不过这样的根据表现为知识的诸种条件,包括真、确证(理由)与信念等,尤其是"确证"这一条件,构成当代知识论的核心部分。     

数字化竞争、媒介环境与报媒融合路径

报媒是互联网时代媒体的最大输家,其传统经营模式面临彻底崩溃危机。基于PEST分析模型,采用最新数据对报媒组织外部环境进行研究,探讨政治、法律环境、经济环境、社会文化环境和技术环境的变化如何改变报业的生存环境。在此基础上,以《华尔街日报》为例,详细分析其数字化生存路径：品牌内容的延伸和整合、推出多样化视频服务、数字平台建设及多元化营销战略。最后,文章提出国内报媒应该从树立“内容第一、数字第一、受众第一”理念、品牌融合经营以及重视平台融合等几方面应对来自互联网等新兴媒体的冲击。     

A Self-help Website for Obsessive Compulsive Disorder: Who is Accessing the Website?

The OCD Challenge is an interactive self-help website for obsessive compulsive disorder (OCD). OCD is often untreated and many barriers prohibit access to an evidence-based intervention including cost, lack of providers, and stigma. Analysis of 436 website participant's demographic data revealed that 63.1% were female, 80.5% were Caucasian, the mean age was 33.37 and the mean age of onset was 15.37. Results of the 436 website users showed a significant positive correlation between Yale-Brown Obsessive Compulsive Scale (YBOCS) assessment scores and disability as well as anxiety and stress scores. Future studies should examine the feasibility of the OCD Challenge at decreasing OCD, disability, depression, anxiety, and stress scores.     

Reducing Hospital Readmissions by Integrating Empirical Prediction with Resource Optimization

Hospital readmissions present an increasingly important challenge for health‐care organizations. Readmissions are expensive and often unnecessary, putting patients at risk and costing $15 billion annually in the United States alone. Currently, 17% of Medicare patients are readmitted to a hospital within 30 days of initial discharge with readmissions typically being more expensive than the original visit to the hospital. Recent legislation penalizes organizations with a high readmission rate. The medical literature conjectures that many readmissions can be avoided or mitigated by post‐discharge monitoring. To develop a good monitoring plan it is critical to anticipate the timing of a potential readmission and to effectively monitor the patient for readmission causing conditions based on that knowledge. This research develops new methods to empirically generate an individualized estimate of the time to readmission density function and then uses this density to optimize a post‐discharge monitoring schedule and staffing plan to support monitoring needs. Our approach integrates classical prediction models with machine learning and transfer learning to develop an empirical density that is personalized to each patient. We then transform an intractable monitoring plan optimization with stochastic discharges and health state evolution based on delay‐time models into a weakly coupled network flow model with tractable subproblems after applying a new pruning method that leverages the problem structure. Using this multi‐methodologic approach on two large inpatient datasets, we show that optimal readmission prediction and monitoring plans can identify and mitigate 40–70% of readmissions before they generate an emergency readmission.