Effects of key enabling technologies for seru production on sustainable performance

Demand uncertainty, economic globalization, and environmental deterioration force factories to innovate their manufacturing systems for achieving sustainable performance. Seru production, which is the latest manufacturing mode developed in Japan, attracts broad attention from both academia and practitioners. The overwhelming majority of existing works on seru production focus on economic performance unilaterally, while neglecting the environmental and social performance. This paper investigates the effects of key enabling technologies for seru production on sustainable performance. Firstly, four key enabling technologies for seru production are identified through systematic review, and an evaluation indicator system of sustainable performance in the context of seru production is developed. Then, the hypotheses about the effects of the identified key enabling technologies for seru production on sustainable performance are proposed on the basis of previous research achievements, theoretical analysis, and practical observations. Finally, the hypotheses are tested through structural equation modeling. Except for two hypotheses which are not supported and one which is indirectly supported, all other hypotheses are verified. The research results show that the four key enabling technologies for seru production have different effects on the three dimensions of sustainable performance. The achievements of this work are of significance to improve the comprehensive understanding of seru production, as well as to develop practical methods to implement sustainable operations.     

A Blueprint for Full Collective Flood Risk Estimation: Demonstration for European River Flooding

Floods are a natural hazard evolving in space and time according to meteorological and river basin dynamics, so that a single flood event can affect different regions over the event duration. This physical mechanism introduces spatio‐temporal relationships between flood records and losses at different locations over a given time window that should be taken into account for an effective assessment of the collective flood risk. However, since extreme floods are rare events, the limited number of historical records usually prevents a reliable frequency analysis. To overcome this limit, we move from the analysis of extreme events to the modeling of continuous stream flow records preserving spatio‐temporal correlation structures of the entire process, and making a more efficient use of the information provided by continuous flow records. The approach is based on the dynamic copula framework, which allows for splitting the modeling of spatio‐temporal properties by coupling suitable time series models accounting for temporal dynamics, and multivariate distributions describing spatial dependence. The model is applied to 490 stream flow sequences recorded across 10 of the largest river basins in central and eastern Europe (Danube, Rhine, Elbe, Oder, Waser, Meuse, Rhone, Seine, Loire, and Garonne). Using available proxy data to quantify local flood exposure and vulnerability, we show that the temporal dependence exerts a key role in reproducing interannual persistence, and thus magnitude and frequency of annual proxy flood losses aggregated at a basin‐wide scale, while copulas allow the preservation of the spatial dependence of losses at weekly and annual time scales.     

大学数学基础课教学中融入数学建模思想的实践

数学建模不仅限于解决实际问题,也可以是数学发展过程中提出的理论问题。基于近年来在大学数学基础课教学中融入数学建模思想的教学实践,论述了其主要思路与做法。介绍了将数学建模思想融入数学基础课教学的两个教学案例,即微积分方法的本质和从方程组出发引入线性相关与线性无关概念。     

Models for the analysis of C-reactive protein in statin trials

Elevation in C-reactive protein (CRP) is an independent risk factor for cardiovascular disease progression and levels are reduced by treatment with statins. However, on-treatment CRP, given baseline CRP and treatment, is not normally distributed and outliers exist even when transformations are applied. Although classical non-parametric tests address some of these issues, they do not enable straightforward inclusion of covariate information. The aims of this study were to produce a model that improved efficiency and accuracy of analysis of CRP data. Estimation of treatment effects and identification of outliers were addressed using controlled trials of rosuvastatin. The robust statistical technique of MM-estimation was used to fit models to data in the presence of outliers and was compared with least-squares estimation. To develop the model, appropriate transformations of the response and baseline variables were selected. The model was used to investigate how on-treatment CRP related to baseline CRP and estimated treatment effects with rosuvastatin. On comparing least-squares and MM-estimation, MM-estimation was superior to least-squares estimation in that parameter estimates were more efficient and outliers were clearly identified. Relative reductions in CRP were higher at higher baseline CRP levels. There was also evidence of a dose-response relationship between CRP reductions from baseline and rosuvastatin. Several large outliers were identified, although there did not appear to be any relationships between the incidence of outliers and treatments. In conclusion, using robust estimation to model CRP data is superior to least-squares estimation and non-parametric tests in terms of efficiency, outlier identification and the ability to include covariate information.     

Are all jobs created equal? A cross-national analysis of women's employment and child malnutrition in developing countries

Using multi-level models, the analysis examines female employment and child stunting across 49 developing countries. At the country level, female labor force participation is not associated with malnutrition after controlling for economic development. At the individual level, a binary measure of employment is not significantly associated with malnutrition. However, a more nuanced measure of seven occupational categories shows that certain types of employment improve malnutrition. Professional, clerical, sales, and domestic jobs are associated with reduced stunting. These effects are only partially mediated by wealth, perhaps suggesting that some jobs may bring benefits to the household beyond the sheer acquisition of tangible resources. Agricultural jobs are associated with increased malnutrition. Manual labor and service work do not have an effect on malnutrition, compared to unemployment. Thus, women's employment is not necessarily a mechanism for empowerment and wellbeing. Not all jobs are created equal, and many of them do not confer the benefits that are typically associated with working outside the home.     

The effect of different data structures,sample sizes on model fit measures

In this study, our aim was to investigate the changes of different data structures and different sample sizes on the structural equation modeling and the influence of these factors on the model fit measures. Examining the created structural equation modeling under different data structures and sample sizes, the evaluation of model fit measures were performed with a simulation study. As a result of the simulation study, optimization and negative variance estimation problems have been encountered depending on the sample size and changing correlations. It was observed that these problems disappeared either by increasing the sample size or the correlations between the variables in factor. For upcoming studies, the choice of RMSEA and IFI model fit measures can be suggested in all sample sizes and the correlation values for data sets are ensured the multivariate normal distribution assumption.     

Communicative Correlates of Satisfaction,Family Identity,and Group Salience in Multiracial/Ethnic Families

Guided by the Common Ingroup Identity Model ( S. L. Gaertner & J. F. Dovidio, 2000 ) and Communication Accommodation Theory ( C. Shepard, H. Giles, & B. A. LePoire, 2001 ), we examined the role of identity accommodation, supportive communication, and self‐disclosure in predicting relational satisfaction, shared family identity, and group salience in multiracial/ethnic families. Additionally, we analyzed the association between group salience and relational outcomes as well as the moderating roles of multiracial/ethnic identity and marital status. Individuals who have parents from different racial/ethnic groups were invited to complete questionnaires on their family experiences. Participants (N = 139) answered questions about relationships with mothers, fathers, and grandparents. The results of the multilevel modeling analyses are discussed in terms of implications for understanding multiracial/ethnic families and family functioning.     

A flexible semiparametric transformation model for survival data

I suggest an extension of the semiparametric transformation model that specifies a time-varying regression structure for the transformation, and thus allows time-varying structure in the data. Special cases include a stratified version of the usual semiparametric transformation model. The model can be thought of as specifying a first order Taylor expansion of a completely flexible baseline. Large sample properties are derived and estimators of the asymptotic variances of the regression coefficients are given. The method is illustrated by a worked example and a small simulation study. A goodness of fit procedure for testing if the regression effects lead to a satisfactory fit is also suggested.     

文化塑校,以文化人：地方本科高校文化建设刍议

地方本科高校的文化建设从目标而言就是“文化塑校”,就是要以校园特色文化塑造学校的品牌形象,全面提升办学层次。地方本科高校文化建设的核心是“以文化人”,就是要以优秀的校园文化潜移默化地影响人的思想意识与言行举止,从而实现“以德育人、以文化人”的大学功能。按照“文化塑校”的战略,凝炼大学的育人文化,实现校园文化的“以文化人”功能,需要传承校史的根的文化、弘扬校训的励志文化、彰显校友的创业文化和优化校园的环境文化。     

基于ECM的团购网站继续使用行为实证研究

当今网络团购已成为电子商务的新兴力量,大量团购网站涌现。以团购网站为研究对象,基于期望证实模型(ECM)构建了影响团购网站继续使用行为的因素研究模型(该模型包含感知有用、感知经济性、感知愉悦、信任、满意、证实、继续使用意愿等7个因素),并对用户使用团购网站后影响其继续使用行为的因素进行了实证分析和验证。结果显示:用户的预期感受与实际使用后的证实程度对感知经济性、感知有用、满意有显著影响;感知经济性、感知有用、满意等3个因素对用户的继续使用意愿有显著影响,而信任因素对使用意愿的影响不显著。