Comparing measures of general and abdominal adiposity as predictors of blood pressure in college students

Objective: To compare anthropometric measures of body mass index (BMI), waist circumference (WC), waist-to-height ratio (WHtR), and sagittal abdominal diameter (SAD) as predictors of blood pressure in college students. Participants: Students (N = 116) were recruited from November 2012 to May 2014 at an urban university and rural community colleges. Methods: Students underwent a brief physical examination during which anthropometric measures were obtained and blood pressure was measured. Covariates were measured using self-reported questionnaires. Hierarchical multiple linear regressions were used for the data analysis. Results: All anthropometric measures were predictive of systolic (SBP) and diastolic blood pressure (DBP). WC was the strongest predictor of SBP (β = .582, p < .01) explaining an additional 3–4% of the variance than BMI, WHtR, or SAD. The measures were similar in predicting DBP. WC predicted SBP independent of BMI. Conclusions: Clinicians should consider using WC to assess the risk for hypertension in college students.     

Discrimination,mental health,and body image among transgender and gender-non-binary individuals: Constructing a multiple mediational path model

The purpose of the current study was to examine the relationships among discrimination, mental health, and body image in a national sample of transgender adults. Participants (N = 78) identified as transgender, genderqueer, or other gender-non-binary identities and were recruited via a national online survey. Harassment/rejection, work/school, and other discrimination explained 10.4% of the variance in body appreciation, while satisfaction with life, anxiety, self-esteem, and depression explained 60.7%. Within these models, harassment/rejection was inversely associated with body appreciation, while self-esteem and satisfaction with life were positively associated. A series of path models moving from a measurement model to a more parsimonious and excellent-fitting model found that the effect of harassment/rejection on body appreciation was fully mediated by self-esteem and satisfaction with life, resulting in a multiple mediation.     

Producing ‘internal suspect bodies’: divisive effects of UK counter‐terrorism measures on Muslim communities in Leeds and Bradford

Research on UK government counter‐terrorism measures has claimed that Muslims are treated as a ‘suspect community’. However, there is limited research exploring the divisive effects that membership of a ‘suspect community’ has on relations within Muslim communities. Drawing from interviews with British Muslims living in Leeds or Bradford, I address this gap by explicating how co‐option of Muslim community members to counter extremism fractures relations within Muslim communities. I reveal how community members internalize fears of state targeting which precipitates internal disciplinary measures. I contribute the category of ‘internal suspect body’ which is materialized through two intersecting conditions within preventative counter‐terrorism: the suspected extremist for Muslims to look out for and suspected informer who might report fellow Muslims. I argue that the suspect community operates through a network of relations by which terrors of counter‐terrorism are reproduced within Muslim communities with divisive effects.     

Multivariate Return Decomposition: Theory and Implications

In this paper, we propose a model based on multivariate decomposition of multiplicative – absolute values and signs – components of asset returns. In the m-variate case, the marginals for the m absolute values and the binary marginals for the m directions are linked through a 2m-dimensional copula. The approach is detailed in the case of a bivariate decomposition. We outline the construction of the likelihood function and the computation of different conditional measures. The finite-sample properties of the maximum likelihood estimator are assessed by simulation. An application to predicting bond returns illustrates the usefulness of the proposed method.     

竖屏短视频中的身体呈现与身体消费

随着应用平台的不断完善和用户习惯的逐渐养成，竖屏短视频俨然成为身体视觉形象荷载和身体审美的绝佳场域，用户也在表演与欣赏的过程中实现自身表达，获得价值认同。不仅如此，竖屏短视频还利用单手竖持、影像竖制及大数据反馈实现身体在场和人机交互的升级，进一步收割用户注意力并成为新一轮互联网商业模式演进新入口。值得注意的是，当前在改变用户消费观念和方式的同时，竖屏短视频也被消费主义裹挟，一度陷入媒介伦理失范、传播生态失衡的发展阵痛之中。     

“生存”与“自由”:“感性活动”的辩证实质与时代价值

“感性活动”是马克思主义唯物史观的基本范畴。经创造性继承费尔巴哈“感性对象”原则与黑格尔否定的辩证法，马克思阐发了“感性活动”的物质基础与能动原则，赋予其三重规定：为生存资料需要的物质生产活动、形成社会关系社会矛盾的物质交往活动、为个性自由推翻现实矛盾的革命改造活动。马克思将人的“需要”机制作为推动和创造原则论证了感性活动从“生存”到“自由”的辩证运动过程，从而揭开了整个社会历史形成与发展之谜，确立了其哲学的实践基础，实现了对唯心主义和直观唯物主义的整体超越。而对感性活动进行生存、反思与自由的当代诠释，是为新时代中国特色社会主义主要矛盾论断找到重要哲学支撑，这既从学理上丰富了马克思主义，印证了不平衡不充分发展的特殊历史性，又在实践层面预示了实现美好生活需要的必然性，为社会创造活动提供了精神动力。     

Discriminant coordinates analysis for multivariate functional data

Abstract

One of the basic statistical methods of dimensionality reduction is analysis of discriminant coordinates given by Fisher (1936 Fisher, R. A. 1936. The use of multiple measurements in taxonomic problem. Annals of Eugenics 7 (2):179–88. doi:10.1111/j.1469-1809.1936.tb02137.x.[Crossref] , [Google Scholar]) and Rao (1948). The space of discriminant coordinates is a space convenient for presenting multidimensional data originating from multiple groups and for the use of various classification methods (methods of discriminant analysis). In the present paper, we adapt the classical discriminant coordinates analysis to multivariate functional data. The theory has been applied to analysis of textural properties of apples of six varieties, measured over a period of 180?days, stored in two types of refrigeration chamber.     

Product partition latent variable model for multiple change-point detection in multivariate data

The product partition model (PPM) is a well-established efficient statistical method for detecting multiple change points in time-evolving univariate data. In this article, we refine the PPM for the purpose of detecting multiple change points in correlated multivariate time-evolving data. Our model detects distributional changes in both the mean and covariance structures of multivariate Gaussian data by exploiting a smaller dimensional representation of correlated multiple time series. The utility of the proposed method is demonstrated through experiments on simulated and real datasets.