995 resultados para Statistics Support
Resumo:
In the scientific literature, the term of addiction is currently used to describe a whole range of phenomena characterized by an irresistible urge to engage in a series of behaviors carried out in a repetitive and persistent manner despite accruing adverse somatic, psychological and social consequences for the individual. It has been suggested that subjects presenting such behaviors would share specific features of personality which support the appearance or are associated with these addictive behaviors. Dimensions such as alexithymia and depression have been particularly well investigated. The aim of this study was to explore the hypothesis of a specific psychopathological model relating alexithymia and depression in different addictive disorders such as alcoholism, drug addiction or eating disorders. Alexithymic and depressive dimensions were explored and analyzed through the statistical tool of path analysis in a large clinical sample of addicted patients and controls. The results of this statistical method, which tests unidirectional causal relationships between a certain number of observed variables, showed a good adjustment between the observed data and the ideal model, and support the hypothesis that a depressive dimension can facilitate the development of dependence in vulnerable alexithymic subjects. These results can have clinical implications in the treatment of addictive disorders.
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This study analyses gender inequalities in health among elderly people in Catalonia (Spain) by adopting a conceptual framework that globally considers three dimensions of health determinants : socio-economic position, family characteristics and social support. Data came from the 2006 Catalonian Health Survey. For the purposes of this study a sub-sample of people aged 65–85 years with no paid job was selected (1,113 men and 1,484 women). The health outcomes analysed were self-perceived health status, poor mental health status and long-standing limiting illness. Multiple logistic regression models separated by sex were fitted and a hierarchical model was fitted in three steps. Health status among elderly women was poorer than among the men for the three outcomes analysed. Whereas living with disabled people was positively related to the three health outcomes and confidant social support was negatively associated with all of them in both sexes, there were gender differences in other social determinants of health. Our results emphasise the importance of using an integrated approach for the analysis of health inequalities among elderly people, simultaneously considering socio-economic position, family characteristics and social support, as well as different health indicators, in order fully to understand the social determinants of the health status of older men and women.
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Because of the various matrices available for forensic investigations, the development of versatile analytical approaches allowing the simultaneous determination of drugs is challenging. The aim of this work was to assess a liquid chromatography-tandem mass spectrometry (LC-MS/MS) platform allowing the rapid quantification of colchicine in body fluids and tissues collected in the context of a fatal overdose. For this purpose, filter paper was used as a sampling support and was associated with an automated 96-well plate extraction performed by the LC autosampler itself. The developed method features a 7-min total run time including automated filter paper extraction (2 min) and chromatographic separation (5 min). The sample preparation was reduced to a minimum regardless of the matrix analyzed. This platform was fully validated for dried blood spots (DBS) in the toxic concentration range of colchicine. The DBS calibration curve was applied successfully to quantification in all other matrices (body fluids and tissues) except for bile, where an excessive matrix effect was found. The distribution of colchicine for a fatal overdose case was reported as follows: peripheral blood, 29 ng/ml; urine, 94 ng/ml; vitreous humour and cerebrospinal fluid, < 5 ng/ml; pericardial fluid, 14 ng/ml; brain, < 5 pg/mg; heart, 121 pg/mg; kidney, 245 pg/mg; and liver, 143 pg/mg. Although filter paper is usually employed for DBS, we report here the extension of this alternative sampling support to the analysis of other body fluids and tissues. The developed platform represents a rapid and versatile approach for drug determination in multiple forensic media.
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To detect directional couplings from time series various measures based on distances in reconstructed state spaces were introduced. These measures can, however, be biased by asymmetries in the dynamics' structure, noise color, or noise level, which are ubiquitous in experimental signals. Using theoretical reasoning and results from model systems we identify the various sources of bias and show that most of them can be eliminated by an appropriate normalization. We furthermore diminish the remaining biases by introducing a measure based on ranks of distances. This rank-based measure outperforms existing distance-based measures concerning both sensitivity and specificity for directional couplings. Therefore, our findings are relevant for a reliable detection of directional couplings from experimental signals.
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Winter maintenance, particularly snow removal and the stress of snow removal materials on public structures, is an enormous budgetary burden on municipalities and nongovernmental maintenance organizations in cold climates. Lately, geospatial technologies such as remote sensing, geographic information systems (GIS), and decision support tools are roviding a valuable tool for planning snow removal operations. A few researchers recently used geospatial technologies to develop winter maintenance tools. However, most of these winter maintenance tools, while having the potential to address some of these information needs, are not typically placed in the hands of planners and other interested stakeholders. Most tools are not constructed with a nontechnical user in mind and lack an easyto-use, easily understood interface. A major goal of this project was to implement a web-based Winter Maintenance Decision Support System (WMDSS) that enhances the capacity of stakeholders (city/county planners, resource managers, transportation personnel, citizens, and policy makers) to evaluate different procedures for managing snow removal assets optimally. This was accomplished by integrating geospatial analytical techniques (GIS and remote sensing), the existing snow removal asset management system, and webbased spatial decision support systems. The web-based system was implemented using the ESRI ArcIMS ActiveX Connector and related web technologies, such as Active Server Pages, JavaScript, HTML, and XML. The expert knowledge on snow removal procedures is gathered and integrated into the system in the form of encoded business rules using Visual Rule Studio. The system developed not only manages the resources but also provides expert advice to assist complex decision making, such as routing, optimal resource allocation, and monitoring live weather information. This system was developed in collaboration with Black Hawk County, IA, the city of Columbia, MO, and the Iowa Department of transportation. This product was also demonstrated for these agencies to improve the usability and applicability of the system.
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The topic of conjugal quality provides an empirical illustration of the relevance of the configurational perspective on families. Based on a longitudinal sample of 1,534 couples living in Switzerland drawn from the study "Social Stratification, Cohesion and Conflict in Contemporary Families", we show that various types of interdependencies with relatives and friends promote distinct conflict management strategies for couples as well as unequal levels of conjugal quality. We find that configurations characterized by supportive and non-interfering relationships with relatives and friends for both partners are associated with higher conjugal quality, while configurations characterized by interference are associated with lower conjugal quality.
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PURPOSE: To explore detainees and staff's attitudes towards tobacco use, in order to assist prison administrators to develop an ethically acceptable tobacco control policy based on stakeholders' opinion. DESIGN: Qualitative study based on in-depth semi-structured interviews with 31 prisoners and 27 staff prior (T1) and after the implementation (T2) of a new smoke-free regulation (2009) in a Swiss male post-trial prison consisting of 120 detainees and 120 employees. RESULTS: At T1, smoking was allowed in common indoor rooms and most working places. Both groups of participants expressed the need for a more uniform and stricter regulation, with general opposition towards a total smoking ban. Expressed fears and difficulties regarding a stricter regulation were increased stress on detainees and strain on staff, violence, riots, loss of control on detainees, and changes in social life. At T2, participants expressed predominantly satisfaction. They reported reduction in their own tobacco use and a better protection against second-hand smoke. However, enforcement was incomplete. The debate was felt as being concentrated on regulation only, leaving aside the subject of tobacco reduction or cessation support. CONCLUSION: Besides an appropriate smoke-free regulation, further developments are necessary in order to have a comprehensive tobacco control policy in prisons.
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Support manual for preventing bullying and harassment in school.
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One of the strategies of Universitat Pompeu Fabra to support Quality Learning has been the creation of Units for the Support of Teaching Quality and Innovation within each faculty. In the seminar we will present the role and activities of the Polytechnic School Unit in charge or coordinating the efforts towards quality learning in the Information and Communication Technologies (ICT) Engineering Studies. We will also discuss how these activities are informed to relevant academic stakeholders.
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Building a personalized model to describe the drug concentration inside the human body for each patient is highly important to the clinical practice and demanding to the modeling tools. Instead of using traditional explicit methods, in this paper we propose a machine learning approach to describe the relation between the drug concentration and patients' features. Machine learning has been largely applied to analyze data in various domains, but it is still new to personalized medicine, especially dose individualization. We focus mainly on the prediction of the drug concentrations as well as the analysis of different features' influence. Models are built based on Support Vector Machine and the prediction results are compared with the traditional analytical models.
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This publication is an historical recording of the most requested statistics on vital events and is a source of information that can be used in further analysis.
Resumo:
This publication is an historical recording of the most requested statistics on vital events and is a source of information that can be used in further analysis.
Resumo:
This publication is an historical recording of the most requested statistics on vital events and is a source of information that can be used in further analysis.