Reactions to Morphological Deviance: A Comparison of Japanese and American Children and Adolescents

Fifth and eleventh graders in the United States (n = 175) and Japan (n = 257) were asked to describe and explain their reactions to obesity and facial disfigurement, both as a deviant member (one having these forms of morphological deviance) and as an interactant member (a normal child interacting with the deviant peer) of a group of 5 children. In the obesity scenario, the group was going shopping for clothes. In the facial disfigurement scenario, the group was having their photographs taken for the school yearbook. In both cultures for both scenarios, negative emotions predominated when students took the deviant role. As interactants, more Japanese than American respondents expressed positive and inclusive attitudes toward the deviant child. Developmental differences varied by culture. Most notable was the tendency of Japanese eleventh graders to become similar to their American counterparts in their decreasing willingness to participate with, include, and be influenced by their peers. Results are discussed in terms of Goffman's (1963) model of 'stigma' and the individualism-collectivism paradigm.     

多西他赛联合CBP治疗晚期老年非小细胞肺癌疗效分析

目的观察多西他赛联合CBP治疗晚期老年非小细胞肺癌的疗效及毒副作用。方法34例晚期老年肺癌采用多西他赛联合卡铂方案治疗2～3周期,按照WHO标准进行评价。结果34例中CR0例,PR14例,NC12例,PD6例,总有效率（RR）为41.18%（14/34）;初治组RR为57.14%（3/7）;复治组RR为40.74%（11/27）。两组RR比较差异有统计学意义,P=0.04。结论多西他赛联合卡铂治疗晚期老年肺癌疗效确切,毒副作用可以耐受,可广泛应用。     

Solving the Multidimensional Assignment Problem by a Cross-Entropy method

The Multidimensional Assignment Problem (MAP) is a higher dimensional version of the linear assignment problem, where we find tuples of elements from given sets, such that the total cost of the tuples is minimal. The MAP has many recognized applications such as data association, target tracking, and resource planning. While the linear assignment problem is solvable in polynomial time, the MAP is NP-hard. In this work, we develop a new approach based on the Cross-Entropy (CE) methods for solving the MAP. Exploiting the special structure of the MAP, we propose an appropriate family of discrete distributions on the feasible set of the MAP that allow us to design an efficient and scalable CE algorithm. The efficiency and scalability of our method are proved via several tests on large-scale problems with up to 5 dimensions and 20 elements in each dimension, which is equivalent to a 0–1 linear program with 3.2 millions binary variables and 100 constraints.     

Robust linear clustering

Summary.  Non-hierarchical clustering methods are frequently based on the idea of forming groups around 'objects'. The main exponent of this class of methods is the k -means method, where these objects are points. However, clusters in a data set may often be due to certain relationships between the measured variables. For instance, we can find linear structures such as straight lines and planes, around which the observations are grouped in a natural way. These structures are not well represented by points. We present a method that searches for linear groups in the presence of outliers. The method is based on the idea of impartial trimming. We search for the 'best' subsample containing a proportion 1− α of the data and the best k affine subspaces fitting to those non-discarded observations by measuring discrepancies through orthogonal distances. The population version of the sample problem is also considered. We prove the existence of solutions for the sample and population problems together with their consistency. A feasible algorithm for solving the sample problem is described as well. Finally, some examples showing how the method proposed works in practice are provided.     

What Colleges Are Doing About Student Binge Drinking A Survey of College Administrators

Abstract

In 1999, the Harvard School of Public Health College Alcohol Study surveyed 734 US college administrators to learn what colleges were doing to prevent binge drinking. Respondents rated the severity of student alcohol-abuse problems and described prevention efforts and institutional investments in prevention infrastructure. Prevention practices were widespread in the areas of general education about alcohol, use of policy controls to limit access to alcohol, restricting advertising at home-game sporting events, and allocation of living space to alcohol-free dormitories. Programming was less prevalent for more targeted alcohol education, outreach, and restrictions on alcohol advertising in campus media. Nationally, most of the surveyed colleges reported having a campus alcohol specialist, many had task forces, and about half were performing in-house data collection. Less common were program evaluations, community agreements, or neighborhood exchanges. Prevention practices varied with institutional characteristics and the surveyed administrators' perceptions of the severity of alcohol problems.     

A modified two-stage approach for joint modelling of longitudinal and time-to-event data

Joint models for longitudinal and time-to-event data have been applied in many different fields of statistics and clinical studies. However, the main difficulty these models have to face with is the computational problem. The requirement for numerical integration becomes severe when the dimension of random effects increases. In this paper, a modified two-stage approach has been proposed to estimate the parameters in joint models. In particular, in the first stage, the linear mixed-effects models and best linear unbiased predictorsare applied to estimate parameters in the longitudinal submodel. In the second stage, an approximation of the fully joint log-likelihood is proposed using the estimated the values of these parameters from the longitudinal submodel. Survival parameters are estimated bymaximizing the approximation of the fully joint log-likelihood. Simulation studies show that the approach performs well, especially when the dimension of random effects increases. Finally, we implement this approach on AIDS data.     

Generalised additive mixed models analysis via gammSlice

We demonstrate the use of our R package, gammSlice, for Bayesian fitting and inference in generalised additive mixed model analysis. This class of models includes generalised linear mixed models and generalised additive models as special cases. Accurate Bayesian inference is achievable via sufficiently large Markov chain Monte Carlo (MCMC) samples. Slice sampling is a key component of the MCMC scheme. Comparisons with existing generalised additive mixed model software shows that gammSlice offers improved inferential accuracy, albeit at the cost of longer computational time.     

Contents of Volume 16, 2000

Volume Contents

Contents of Volume 16, 2000     

A model of collaborative programming to address wildlife issues: The northeast wildlife damage management research and outreach cooperative

Wildlife abundance has grown for several species that are adapted to human-dominated landscapes. Overabundant wildlife may cause nuisance concerns and property damage, or spread zoonotic diseases such as West Nile virus, particularly at the suburban-rural interface of many communities. Consequently, wildlife damage management has become an important component of the wildlife profession. The complicated biological and human dimensions of human-wildlife conflicts often require partnerships between state and federal agencies, universities, local governments, communities, and private wildlife control professionals. The Northeast Wildlife Damage Management Research and Outreach Cooperative (WDM Coop) was formed to enhance coordination and collaboration among wildlife agencies, universities, and other cooperators to promote consistent, multi-state approaches for resolving wildlife-related concerns. During 2001–2004, 12 projects have been funded to examine issues associated with white-tailed deer (Odocoileus virginianus), black bear (Ursus americanus), Canada geese (Branta canadensis), and beaver (Castor canadensis). These projects have focused on a diverse array topics from community-based efforts to control deer populations, to aversive conditioning techniques for black bears. The Northeast Fish and Wildlife Agency Directors decided to exclude projects focusing on zoonotic diseases and human health issues from the list of WDM Coop activities. There have been focused efforts concerning human dimensions inquiry and outreach publications for wildlife management professionals. As state fish and wildlife agency budgets grow tighter and staff numbers are reduced, we believe more regional centers or wildlife management cooperatives will be formed to meet the increasing demand for services from multiple states with shared issues and concerns.