A Deprivation Analysis for Andalusia (Spain): An Approach Based on Structural Equations

The study of deprivation, as a social indicator, is basic in the design and development of public policies because it allows decision makers to identify and analyse needy areas in order to improve their citizens’ well-being. The methodological approach proposed for the development of a new deprivation index is based on the Causal Theory whose conceptual model is analysed using Structural Equations. The domains selected for the deprivation index are: education, employment, income, housing, infrastructures and health. A structural equation model based on variance is the exploratory method used to obtain the indices pertaining to the above mentioned areas; the results obtained are seen to be quite reliable. There is a positive connection between the areas of education, employment and income while the relations between infrastructures and health are found to be negative. The results can be projected at a local level and show basic territorial deficiencies. The spatial units studied are the Andalusian (south of Spain) municipalities (770). The spatial projection of the indices obtained for the domains of deprivation highlights the existence of geographical areas which could be a potential target for public action.     

Bayesian Classifiers Applied to the Tennessee Eastman Process

Fault diagnosis includes the main task of classification. Bayesian networks (BNs) present several advantages in the classification task, and previous works have suggested their use as classifiers. Because a classifier is often only one part of a larger decision process, this article proposes, for industrial process diagnosis, the use of a Bayesian method called dynamic Markov blanket classifier that has as its main goal the induction of accurate Bayesian classifiers having dependable probability estimates and revealing actual relationships among the most relevant variables. In addition, a new method, named variable ordering multiple offspring sampling capable of inducing a BN to be used as a classifier, is presented. The performance of these methods is assessed on the data of a benchmark problem known as the Tennessee Eastman process. The obtained results are compared with naive Bayes and tree augmented network classifiers, and confirm that both proposed algorithms can provide good classification accuracies as well as knowledge about relevant variables.     

Coaching und Mentoring

The program “Mentoring for female junior executives at schools” in Hamburg has the goal of recruiting more female executives for schools in Hamburg. As a headmaster of a high school the author has attended this program as a mentor. She discusses the following questions: What are the differences between mentoring and coaching? Where are the limits of mentoring? When is coaching the better method? The main result is, that the mentor has to be very attentively of his position as a member of the organization. He has to decide, if he can advise the mentee for example in conflicts with superiors or if a coach could do a better job. A missing link in the mentoring program is the analysis of the culture of organizations, because this is an important factor for a successful start into the new function.     

Optimal RSUs deployment with delay bound along highways in VANET

In order to broadcast an alert message from the accident site to the control center as soon as possible, the roadside units (RSUs) act as the critical component in vehicular ad hoc networks (VANETs). It is not possible to make a pervasive RSU deployment due to the huge cost and market requirement. Hence, how to deploy a minimum number of RSUs in a given region becomes a challenge problem. In this paper, we present an analysis for the total delay of broadcasting alert messages in VANETs along highways. Based on the analysis, the relationship between optimal number of RSUs with the highway distance is given. Moreover, the experiment results verifies the delay analysis and the optimization of RSUs deployment.     

Bats in urban areas of Brazil: roosts,food resources and parasites in disturbed environments

Urbanization is a widespread intense land use that generally results in biodiversity decline. Among the taxa capable to adapt to urban landscapes, bats are particularly ubiquitous. Brazil has one of the world’s largest diversity of bat species and one of the highest urbanization rates of the world. Yet, few studies have synthesized the biology of bats in urban environments, especially in Brazil. To fill this gap, we systematically reviewed the published scientific literature on the bat fauna found in urban areas of Brazil. The knowledge of urban bats is still incipient and heterogeneously spatially distributed, mostly concentrated in the southeastern region of the country. The assembled list of 84 urban species, of which nineteen are new species records for urban areas (including one new family), represents 47% of the bat richness registered in the country. Thirty-one bat species (37%) were captured exclusively inside forest fragments. Moreover, we provide information on the resources used within the urban matrix by summarizing the roosting sites for 38 bat species, as well as 31 plants consumed by at least twelve bat species. Regarding parasitological aspects, we listed eleven zoonotic parasites hosted by 27 bat species and discussed their potential to become a public health threat. Likewise, we considered the different features linked to urbanization, including impacts on immunity, body condition and susceptibility to acquiring parasites, as possible bat conservation issues. Finally, we defined an agenda for bat studies in urban areas of Brazil.     

Introductory Statistics Textbooks and the GAISE Recommendations

The six recommendations made by the Guidelines for Assessment and Instruction in Statistics Education (GAISE) committee were first communicated in 2005 and more formally in 2010. In this article, 25 introductory statistics textbooks are examined to assess how well these textbooks have incorporated the three GAISE recommendations most relevant to implementation in textbooks (statistical literacy and thinking; use of real data; stress concepts over procedures). The implementation of another recommendation (using technology) is described but not assessed. In general, most textbooks appear to be adopting the GAISE recommendations reasonably well in both exposition and exercises. The textbooks are particularly adept at using real data, using real data well, and promoting statistical literacy. Textbooks are less adept—but still rated reasonably well, in general—at explaining concepts over procedures and promoting statistical thinking. In contrast, few textbooks have easy-usable glossaries of statistical terms to assist with understanding of statistical language and literacy development. Supplementary materials for this article are available online.     

Social network effects on academic achievement

How peer groups contribute to educational outcomes has long interested researchers. However, the possibility that peer groups dominated by either low- or high-achieving youth can have substantively different effects on achievement has been largely ignored. In this paper, we show that while being embedded in a high-achieving network of friends is not associated with increased own achievement, being embedded in a low-achieving network is associated with decreased own achievement. In additional analyses, we present evidence that these associations are at least in part due to influence, as opposed to only selection effects or shared environment. We also examine whether the structure of the network in which a student is embedded might affect their educational achievement. We show that achieving at higher levels positively predicts how centrally located a student is in their network, but being more centrally located does not predict concurrent achievement. This finding suggests that the behavior of individuals is affecting the formation of network structure and not the reverse.     

Restructuring of the Financial Industry: The Disappearance of Locally Owned Traditional Financial Services in Rural America

Restructuring in the financial services industry has altered the relationship between small business owners and capital. In the past small businesses have relied on relational, or soft data, lending from locally owned banks for capital. The proliferation of absentee‐owned local branch networks brought standardized practices, thus eliminating the autonomy of local loan officers to utilize soft data in loan decisions. In this article we examine the changes in the percentage of traditional financial services that are locally owned in three county types: metropolitan, micropolitan, and noncore. We utilize the Longitudinal Business Database at the U.S. Census Bureau Center for Economic Studies. We examine changes in local ownership of traditional financial services between 1976 and 2007. We find that the rate of decline of local ownership has been greatest in the noncore (most rural) counties. We also explore to what extent these patterns are related to the emergence of alternative financial services during the same period. We find that such alternative services are growing in all three county types, but at rates not significantly different than the population growth for these county types. We supplement our analysis with data from qualitative interviews with small business owners throughout rural Texas. We conclude with a discussion of implications and plans for future research.