Beyond the Margins: Analyzing Social Exclusion with a Homeless Client Dataset

A great share of literature on social exclusion has been based mainly on the analysis of official survey data. Whereas these efforts have provided insights into the characteristics and conditions of those people living at the margins of mainstream social relations, they have however failed to encompass those who live beyond these very margins. Meanwhile, research on these hidden subpopulations, such as homeless and other vulnerable groups, remains generally less abundant and is significantly detached from the theoretical core of the debate on social exclusion. The concern about these shortcomings lies at the heart of our research. We seek to bring some light to the area by using data made available by an organization that provides services to people experiencing homelessness in Barcelona (Spain). The data sample contains clients in early stages of exclusion and others in chronic situations. Thus, we attempt to identify some of the variables that operate in preventing the "chronification" of those individuals in situation of social exclusion. Our findings suggest that certain variables such as educational level, income and housing type, which are considered to be central predictors in the analysis of poverty, behave differently when analyzing differences between stages of social exclusion. Although these results cannot be extrapolated to the whole Spanish or European reality, they could provide useful insight for future investigations on this topic.

The MIRELA framework: modeling and analyzing mixed reality applications using timed automata

Mixed Reality (MR) aims to link virtual entities with the real world and has many applications such as military and medical domains [JBL+00, NFB07]. In many MR systems and more precisely in augmented scenes, one needs the application to render the virtual part accurately at the right time. To achieve this, such systems acquire data related to the real world from a set of sensors before rendering virtual entities. A suitable system architecture should minimize the delays to keep the overall system delay (also called end-to-end latency) within the requirements for real-time performance. In this context, we propose a compositional modeling framework for MR software architectures in order to specify, simulate and validate formally the time constraints of such systems. Our approach is first based on a functional decomposition of such systems into generic components. The obtained elements as well as their typical interactions give rise to generic representations in terms of timed automata. A whole system is then obtained as a composition of such defined components. To write specifications, a textual language named MIRELA (MIxed REality LAnguage) is proposed along with the corresponding compilation tools. The generated output contains timed automata in UPPAAL format for simulation and verification of time constraints. These automata may also be used to generate source code skeletons for an implementation on a MR platform. The approach is illustrated first on a small example. A realistic case study is also developed. It is modeled by several timed automata synchronizing through channels and including a large number of time constraints. Both systems have been simulated in UPPAAL and checked against the required behavioral properties.

Critical Control Points for Profitability in the Cow-Calf Enterprise

Financial, economic, and biological data collected from cow-calf producers who participated in the Illinois and Iowa Standardized Performance Analysis (SPA) programs were used in this study. Data used were collected for the 1996 through 1999 calendar years, with each herd within year representing one observation. This resulted in a final database of 225 observations (117 from Iowa and 108 from Illinois) from commercial herds with a range in size from 20 to 373 cows. Two analyses were conducted, one utilizing financial cost of production data, the other economic cost of production data. Each observation was analyzed as the difference from the mean for that given year. The independent variable utilized in both the financial and economic models as an indicator of profit was return to unpaid labor and management per cow (RLM). Used as dependent variables were the five factors that make up total annual cow cost: feed cost, operating cost, depreciation cost, capital charge, and hired labor, all on an annual cost per cow basis. In the economic analysis, family labor was also included. Production factors evaluated as dependent variables in both models were calf weight, calf price, cull weight, cull price, weaning percentage, and calving distribution. Herd size and investment were also analyzed. All financial factors analyzed were significantly correlated to RLM (P < .10) except cull weight, and cull price. All economic factors analyzed were significantly correlated to RLM (P < .10) except calf weight, cull weight and cull price. Results of the financial prediction equation indicate that there are eight measurements capable of explaining over 82 percent of the farm-to-farm variation in RLM. Feed cost is the overriding factor driving RLM in both the financial and economic stepwise regression analyses. In both analyses over 50 percent of the herd-to-herd variation in RLM could be explained by feed cost. Financial feed cost is correlated (P < .001) to operating cost, depreciation cost, and investment. Economic feed cost is correlated (P < .001) with investment and operating cost, as well as capital charge. Operating cost, depreciation, and capital charge were all negatively correlated (P < .10) to herd size, and positively correlated (P < .01) to feed cost in both analyses. Operating costs were positively correlated with capital charge and investment (P < .01) in both analyses. In the financial regression model, depreciation cost was the second critical factor explaining almost 9 percent of the herd-to-herd variation in RLM followed by operating cost (5 percent). Calf weight had a greater impact than calf price on RLM in both the financial and economic regression models. Calf weight was the fourth indicator of RLM in the financial model and was similar in magnitude to operating cost. Investment was not a significant variable in either regression model; however, it was highly correlated to a number of the significant cost variables including feed cost, depreciation cost, and operating cost (P < .001, financial; P < .10, economic). Cost factors were far more influential in driving RLM than production, reproduction, or producer controlled marketing factors. Of these cost factors, feed cost had by far the largest impact. As producers focus attention on factors that affect the profitability of the operation, feed cost is the most critical control point because it was responsible for over 50 percent of the herd-to-herd variation in profit.

Analyzing PL/1 Legacy Ecosystems: An Experience Report

This paper presents a case study of analyzing a legacy PL/1 ecosystem that has grown for 40 years to support the business needs of a large banking company. In order to support the stakeholders in analyzing it we developed St1-PL/1 — a tool that parses the code for association data and computes structural metrics which it then visualizes using top-down interactive exploration. Before building the tool and after demonstrating it to stakeholders we conducted several interviews to learn about legacy ecosystem analysis requirements. We briefly introduce the tool and then present results of analysing the case study. We show that although the vision for the future is to have an ecosystem architecture in which systems are as decoupled as possible the current state of the ecosystem is still removed from this. We also present some of the lessons learned during our experience discussions with stakeholders which include their interests in automatically assessing the quality of the legacy code.

Analyzing the Role of αvβ8 Integrin in Glioma-Induced Angiogenesis

In this study we aimed to determine the functional roles for αvβ8 integrin in astrocytoma-induced angiogenesis. These studies originate from our analyses of αvβ8 integrin in developmental brain angiogenesis. αv and β8 knockout (KO) mice develop brain-specific vascular phenotypes that resemble vascular pathologies observed in the malignant astrocytoma, glioblastoma multiforme (GBM). Indeed, a murine xenograft model of astrocytoma suggested a role for the integrin in glioma-induced angiogenesis. Primary mouse astroglia were cultured from wild type (WT) and β8 KO neonates and were immortalized (HPV:E6/E7) and transformed (HRas:G12V). WT and β8 KO transformed astroglia were intracranially injected into athymic mice. WT tumors displayed pathological features of grade III astrocytomas, whereas β8 KO tumors resembled grade IV GBMs. KO tumors contained widespread edema and hemorrhage as well as pathological angiogenesis, as assessed by quantitation of microvascular density and blood vessel morphology. Additionally, exogenous expression of β8 integrin in β8 KO transformed astroglia resolved the pathologies observed in KO tumors giving further credence to the idea that loss of αvβ8 integrin expression correlates with tumorigenic potential of oncogene-transformed astroglia. To compliment our mouse model, several established human glioma cell lines were characterized for expression of αvβ8 integrin protein. Some of the cell lines displayed low expression of αvβ8 integrin, whereas others showed high levels, as compared to non-malignant human astrocytes. Intracranial implantation of high and low β8 integrin-expressing human glioma cell lines resulted in tumors exhibiting similar phenotypes to those observed in the mouse model; low expressers were marked by vascular pathologies indicative of β8 KO mouse tumors. Upon overexpression of β8 integrin in a low β8 integrin-expressing human glioma cell line, angiogenic pathologies were largely resolved. Moreover, intracranially injected αvHI- and αvLO-sorted GBM stem cells (GSCs) resulted in significantly different tumor sizes, where those GSCs endogenously expressing low levels of αv integrin formed two to three fold larger tumors. Furthermore, lentiviral knockdown of β8 integrin in transformed human astrocytes formed tumors that strikingly recapitulated the characteristics of the murine β8-/- tumors, exhibiting a significant increase in microvascular density leading to decreased overall survival. A paracrine mechanism was discovered involving endothelial cell homeostatic control governed by canonical TGFβ signaling initiated by αvβ8 integrin’s role in the latent cytokine’s activation. Diminished TGFβ signaling in tumor-associated endothelial cells promoted increased angiogenesis and decreased overall survival as a result of αvβ8 integrin’s loss on the tumor cell. Collectively, these data suggest an important functional role for αvβ8 integrin in glioma angiogenesis.

An empirical examination of relative profitability in the nursing facility industry between ownership form and regionality in the state of Texas

The purpose of this research is to examine the relative profitability of the firm within the nursing facility industry in Texas. An examination is made of the variables expected to affect profitability and of importance to the design and implementation of regulatory policy. To facilitate this inquiry, specific questions addressed are: (1) Do differences in ownership form affect profitability (defined as operating income before fixed costs)? (2) What impact does regional location have on profitability? (3) Do patient case-mix and access to care by Medicaid patients differ between proprietary and non-profit firms and facilities located in urban versus rural regions, and what association exists between these variables and profitability? (4) Are economies of scale present in the nursing home industry? (5) Do nursing facilities operate in a competitive output market characterized by the inability of a single firm to exhibit influence over market price?^ Prior studies have principally employed a cost function to assess efficiency differences between classifications of nursing facilities. The inherent weakness in this approach is that it only considers technical efficiency. Not both technical and price efficiency which are the two components of overall economic efficiency. One firm is more technically efficient compared to another if it is able to produce a given quantity of output at the least possible costs. Price efficiency means that scarce resources are being directed towards their most valued use. Assuming similar prices in both input and output markets, differences in overall economic efficiency between firm classes are assessed through profitability, hence a profit function.^ Using the framework of the profit function, data from 1990 Medicaid Costs Reports for Texas, and the analytic technique of Ordinary Least Squares Regression, the findings of the study indicated (1) similar profitability between nursing facilities organized as for-profit versus non-profit and located in urban versus rural regions, (2) an inverse association between both payor-mix and patient case-mix with profitability, (3) strong evidence for the presence of scale economies, and (4) existence of a competitive market structure. The paper concludes with implications regarding reimbursement methodology and construction moratorium policies in Texas. ^

Analyzing diffuse scattering with supercomputers

Two new approaches to quantitatively analyze diffuse diffraction intensities from faulted layer stacking are reported. The parameters of a probability-based growth model are determined with two iterative global optimization methods: a genetic algorithm (GA) and particle swarm optimization (PSO). The results are compared with those from a third global optimization method, a differential evolution (DE) algorithm [Storn & Price (1997). J. Global Optim. 11, 341–359]. The algorithm efficiencies in the early and late stages of iteration are compared. The accuracy of the optimized parameters improves with increasing size of the simulated crystal volume. The wall clock time for computing quite large crystal volumes can be kept within reasonable limits by the parallel calculation of many crystals (clones) generated for each model parameter set on a super- or grid computer. The faulted layer stacking in single crystals of trigonal three-pointedstar- shaped tris(bicylco[2.1.1]hexeno)benzene molecules serves as an example for the numerical computations. Based on numerical values of seven model parameters (reference parameters), nearly noise-free reference intensities of 14 diffuse streaks were simulated from 1280 clones, each consisting of 96 000 layers (reference crystal). The parameters derived from the reference intensities with GA, PSO and DE were compared with the original reference parameters as a function of the simulated total crystal volume. The statistical distribution of structural motifs in the simulated crystals is in good agreement with that in the reference crystal. The results found with the growth model for layer stacking disorder are applicable to other disorder types and modeling techniques, Monte Carlo in particular.

How do sport clubs recruit volunteers? Analyzing and developing a typology of decision-making processes on recruiting volunteers in sport clubs.

Effective strategies for recruiting volunteers who are prepared to make a long-term commitment to formal positions are essential for the survival of voluntary sport clubs. This article examines the decision-making processes in relation to these efforts. Under the assumption of bounded rationality, the garbage can model is used to grasp these decision-making processes theoretically and access them empirically. Based on case study framework an in-depth analysis of recruitment practices was conducted in nine selected sport clubs. Results showed that the decision-making processes are generally characterized by a reactive approach in which dominant actors try to handle personnel problems of recruitment in the administration and sport domains through routine formal committee work and informal networks. In addition, it proved possible to develop a typology that deliver an overview of different decision-making practices in terms of the specific interplay of the relevant components of process control (top-down vs. bottom-up) and problem processing (situational vs. systematic).

Pangea: A Workbench for Statically Analyzing Multi-Language Software Corpora

Software corpora facilitate reproducibility of analyses, however, static analysis for an entire corpus still requires considerable effort, often duplicated unnecessarily by multiple users. Moreover, most corpora are designed for single languages increasing the effort for cross-language analysis. To address these aspects we propose Pangea, an infrastructure allowing fast development of static analyses on multi-language corpora. Pangea uses language-independent meta-models stored as object model snapshots that can be directly loaded into memory and queried without any parsing overhead. To reduce the effort of performing static analyses, Pangea provides out-of-the box support for: creating and refining analyses in a dedicated environment, deploying an analysis on an entire corpus, using a runner that supports parallel execution, and exporting results in various formats. In this tool demonstration we introduce Pangea and provide several usage scenarios that illustrate how it reduces the cost of analysis.