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Social group is a type of mesoscopic structure that connects human individuals in microscopic level and the global structure of society. In this paper, we propose a tag-based model considering that social groups expand along the edge that connects two neighbors with a similar tag of interest. The model runs on a real-world friendship network, and its simulation results show that various properties of simulated group network can well fit the empirical analysis on real-world social groups, indicating that the model catches the major mechanism driving the evolution of social groups and successfully reconstructs the social group network from a friendship network and throws light on digging of relationships between social functional organizations. [ABSTRACT FROM AUTHOR]

Abstract: From the birth of multi-spectral imaging techniques, there has been a tendency to consider and process this new type of data as a set of parallel gray-scale images, instead of an ensemble of an n-D realization. However, it has been proved that using vector-based tools leads to a more appropriate understanding of color images and thus more efficient algorithms for processing them. Such tools are able to take into consideration the high correlation of the color components and thus to successfully carry out energy compaction. In this paper, a novel method is proposed to utilize the principal component analysis in the neighborhoods of an image in order to extract the corresponding eigenimages. These eigenimages exhibit high levels of energy compaction and thus are appropriate for such operations as compression and watermarking. Subsequently, two such methods are proposed in this paper and their comparison with available approaches is presented. [Copyright &y& Elsevier]

Abstract: The paper develops a sociological model to explain collisions between two drivers or more. The “Social Accident” model presented here integrates empirical findings from prior studies and extant sociological theories. Sociological theory posits that social groups have unique cultural characteristics, which include a distinctive world view and ways of operating that influence its members. These cultural characteristics may cause drivers in different groups to interpret a given situation differently; therefore, they will make conflicting decisions that may possibly lead to road accidents. The proposed model may contribute to an understanding of the social mechanism related to interactions and communication among drivers by presenting new directions for understanding accidents and collisions. The paper concludes with suggestions for future research that will employ the model to assess its predictive and practical utility. [Copyright &y& Elsevier]

Abstract: The purpose of this paper is to explain why low-wage workers with identical qualifications to higher-wage workers are more exposed to unemployment. Each worker is considered to belong to a social group (defined according to his/her gender, age, and nationality). We assume that workers experience both productive interdependencies and social interactions within the firm. Also inter- and intra-group interactions determine worker productivity, and frictions on the labor market limit the hiring of the most productive workers. Consequently, externalities acting both within the firm and in the labor market can lead to a higher rate of unemployment for low-wage workers. [Copyright &y& Elsevier]

Abstract: In this paper, we discuss a possible discrete approximation of non-metrical Minkowski distances. The existing approaches for Minkowski metrics considering distance functions based on local neighborhoods are not suitable for this task in their present form. We can overcome this difficulty with considering the minimum of such distance functions. In this way, we can take full advantage of the former theoretical and applied results. We consider several possibilities to measure the error of approximation and propose corresponding distance functions for optimal approximation. A fast chamfering algorithm is also provided to generate the approximate distance values for applications in digital domains. [Copyright &y& Elsevier]

Abstract: It is well known that a wide-neighborhood interior-point algorithm for linear programming performs much better in implementation than its small-neighborhood counterparts. In this paper, we provide a unified way to enlarge the neighborhoods of predictor–corrector interior-point algorithms for linear programming. We prove that our methods not only enlarge the neighborhoods but also retain the so-far best known iteration complexity and superlinear (or quadratic) convergence of the original interior-point algorithms. The idea of our methods is to use the global minimizers of proximity measure functions. [Copyright &y& Elsevier]

Abstract: We make a correction to the paper “How people make friends in social networking sites—A microscopic perspective”, Hu, H., Wang, X., Physica A, 391 (2012) 1877–1886. [Copyright &y& Elsevier]

Abstract: Numerous factors play a part in health disparities. Although health disparities are manifested at the level of the individual, other contexts should be considered when investigating the associations of disparities with clinical outcomes. These contexts include families, neighborhoods, social organizations, and healthcare facilities. This paper reports on health disparities research as a multilevel research domain from the perspective of a large national initiative. The Centers for Population Health and Health Disparities (CPHHD) program was established by the NIH to examine the highly dimensional, complex nature of disparities and their effects on health. Because of its inherently transdisciplinary nature, the CPHHD program provides a unique environment in which to perform multilevel health disparities research. During the course of the program, the CPHHD centers have experienced challenges specific to this type of research. The challenges were categorized along three axes: sources of subjects and data, data characteristics, and multilevel analysis and interpretation. The CPHHDs collectively offer a unique example of how these challenges are met; just as importantly, they reveal a broad range of issues that health disparities researchers should consider as they pursue transdisciplinary investigations in this domain, particularly in the context of a large team science initiative. [Copyright &y& Elsevier]