995 resultados para Midia support office
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The regular use of the computer in the office contributed to the appearance of many risk factors related with work-related musculoskeletal disorders (WRMSD) such as maintaining static sitting postures for long time and awkward postures of the head, neck and upper limbs, leading to increased muscle activity in the cervical spine and shoulders. The objective of this study was to evaluate the presence of risk factors for WRMSD in an office using the Rapid Assessment Office Strain method (ROSA). Based on the results of this ergonomic evaluation, an occupational gym program was designed and implemented. Thirty-eight workplaces were evaluated using the observation of the tasks and pictures records in order to characterize those tasks in more detail. The ROSA tool was applied by an observer, who selected the appropriate score based on the worker's posture as well as the time spent in each posture. Scores were recorded for the sections of the method, specifically Chair, Monitor and Mouse and Keyboard and Telephone. The scores were recorded in a sheet developed for the method. The mean ROSA final score was 3.61 ± 0.64, for Chair section was 3.45 ± 0.55, to Monitor and Telephone section was 3.11 ± 0.61, and to Mouse and Keyboard section was 2.11 ± 0.31. The results led to understand that the analyzed tasks represent situations of risk of discomfort and, according to the methods guidelines, further research and modifications of the workplace may be necessary. It should be emphasized that these scores may not be related to the poor available equipment but with the need to optimize their use by the workers. It was noticed also that the interaction of workers with the tasks and the adopted sitting posture at the computer throughout the day have effects at a muscular level, essentially for the cervical area and shoulders. ROSA tool is an useful and easy method to assess several risk factors associated with WRMSD, also allowing the design of specific occupational gym programs.
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The occurrence of Barotrauma is identified as a major concern for health professionals, since it can be fatal for patients. In order to support the decision process and to predict the risk of occurring barotrauma Data Mining models were induced. Based on this principle, the present study addresses the Data Mining process aiming to provide hourly probability of a patient has Barotrauma. The process of discovering implicit knowledge in data collected from Intensive Care Units patientswas achieved through the standard process Cross Industry Standard Process for Data Mining. With the goal of making predictions according to the classification approach they several DM techniques were selected: Decision Trees, Naive Bayes and Support Vector Machine. The study was focused on identifying the validity and viability to predict a composite variable. To predict the Barotrauma two classes were created: “risk” and “no risk”. Such target come from combining two variables: Plateau Pressure and PCO2. The best models presented a sensitivity between 96.19% and 100%. In terms of accuracy the values varied between 87.5% and 100%. This study and the achieved results demonstrated the feasibility of predicting the risk of a patient having Barotrauma by presenting the probability associated.
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The observational method in tunnel engineering allows the evaluation in real time of the actual conditions of the ground and to take measures if its behavior deviates considerably from predictions. However, it lacks a consistent and structured methodology to use the monitoring data to adapt the support system in real time. The definition of limit criteria above which adaptation is required are not defined and complex inverse analysis procedures (Rechea et al. 2008, Levasseur et al. 2010, Zentar et al. 2001, Lecampion et al. 2002, Finno and Calvello 2005, Goh 1999, Cui and Pan 2012, Deng et al. 2010, Mathew and Lehane 2013, Sharifzadeh et al. 2012, 2013) may be needed to consistently analyze the problem. In this paper a methodology for the real time adaptation of the support systems during tunneling is presented. In a first step limit criteria for displacements and stresses are proposed. The methodology uses graphics that are constructed during the project stage based on parametric calculations to assist in the process and when these graphics are not available, since it is not possible to predict every possible scenario, inverse analysis calculations are carried out. The methodology is applied to the “Bois de Peu” tunnel which is composed by two tubes with over 500 m long. High uncertainty levels existed concerning the heterogeneity of the soil and consequently in the geomechanical design parameters. The methodology was applied in four sections and the results focus on two of them. It is shown that the methodology has potential to be applied in real cases contributing for a consistent approach of a real time adaptation of the support system and highlight the importance of the existence of good quality and specific monitoring data to improve the inverse analysis procedure.
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Objectives: This study analyzed the moderating role of partners’ support and satisfaction with healthcare services in the relationship between psychological morbidity and adherence to diet in patients with type 2 diabetes (T2DM). Methods: Participants were 387 recently diagnosed T2DM patients that answered the following instruments: Revised Summary of Diabetes Self- Care Activities Measure, Hospital Anxiety and Depression Scales, Multidimensional Diabetes Questionnaire and Patient Satisfaction Questionnaire. Results: Partners’ positive and negative support moderated the relationship between psychological morbidity and adherence to diet. Satisfaction with healthcare services also moderated the relationship between psychological morbidity and adherence to diet. Conclusions: Intervention programs to promote adherence to diet in patients with type 2 diabetes should focus on partners’ support and patient satisfaction with healthcare services.
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Dissertação de mestrado em Engenharia Industrial
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Dissertação de mestrado integrado em Engenharia e Gestão Industrial
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Many funding agencies have Open Access mandates in place, but how often are scientific publications as outputs linked to funding details? The benefits of linking funding information to publications as part of the deposit workflow can assist in adhering to Open Access mandates. This paper examines how OpenAIRE – Open Access Infrastructure for Research in Europe – can ease monitoring Open Access and reporting processes for funders, and presents some results and opportunities. It also outlines how it relies on cleaned and curated repository content, a vital cog in the ever turning wheel of the global scholarly landscape, and the benefits it brings.
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A series of colloidal MxFe3-xO4 (M = Mn, Co, Ni; x = 0–1) nanoparticles with diameters ranging from 6.8 to 11.6 nm was synthesized by hydrothermal reaction in aqueous medium at low temperature (200 °C). Energy-dispersive X-ray microa-nalysis and inductively coupled plasma spectrometry confirms that the actual elemental compositions agree well with the nominal ones. The structural properties of obtained nanoparticles were investigated by using powder X-ray diffraction, Raman scattering, Mössbauer spectroscopy, and electron microscopy. The results demonstrate that our synthesis technique leads to the formation of chemically uniform single-phase solid solution nanoparticles with cubic spinel structure, confirming the intrinsic doping. Magnetic studies showed that, in comparison to Fe3O4, the saturation magnetization of MxFe3-xO4 (M = Mn, Ni) decreases with increasing dopant concentration, while Co-doped samples showed similar saturation magnetizations. On other hand, whereas Mn- and Ni-doped nanoparticles exhibits superparamagnetic behavior at room temperature, ferromagnetism emerges for CoxFe3-xO4 nanoparticles, which can be tuned by the level of Co doping.
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In this study, a mathematical model for the production of Fructo-oligosaccharides (FOS) by Aureobasidium pullulans is developed. This model contains a relatively large set of unknown parameters, and the identification problem is analyzed using simulation data, as well as experimental data. Batch experiments were not sufficiently informative to uniquely estimate all the unknown parameters, thus, additional experiments have to be achieved in fed-batch mode to supplement the missing information. © 2015 IEEE.
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Relatório de estágio de mestrado em História
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OBJECTIVE: To evaluate the use of the intraaortic balloon (IAoB) in association with coronary angioplasty in high-risk patients. METHODS: Fourteen high-risk patients unresponsive to clinical therapy and with formal contraindication to surgical revascularization were treated by coronary angioplasty, most of which was followed by stenting. All procedures were performed with circulatory support with the IAoB. This study reports the early results and the late findings after 12 months of follow-up. Six patients had multivessel coronary disease; of these, four had left main equivalent lesions and two had unprotected left main coronary artery disease, one of whom had severe "end-vessel" stenosis and the other was a patient with Chagas' disease with single-vessel lesion. Eleven patients had a left ventricular ejection fraction <30%. RESULTS: In 100% of the patients, the procedures were initially successful. Two patients had severe bleeding during the withdrawal of the left femoral sheath. At the end of twelve months, 4 patients were asymptomatic and the others were clinically controlled. There were two late deaths in the 7th and 11th months. CONCLUSION: The combined use of the intraaortic balloon pump and percutaneous coronary angioplasty in high-risk patients with acute ischemic syndromes provides the necessary hemodynamic stability to successfully perform the procedures.
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OBJECTIVE - To describe clinical observations of marked improvement in ventricular dysfunction in a medical office environment under circumstances differing from those in study protocols and multicenter studies performed in hospital or with outpatient cohorts. METHODS - Eleven cardiac failure patients with marked ventricular dysfunction receiving treatment at a doctors office between 1994 and 1999 were studied. Their ages ranged from 20 and 66 years (mean 39.42±14.05 years); 7 patients were men, 4 were women. Cardiopathic etiologies were arterial hypertension in 5 patients, peripartum cardiomyopathy in 2, nondefined myocarditis in 2, and alcoholic cardiomyopathy in 4. Initial echocardiograms revealed left ventricular dilatation (average diastolic diameter, 69.45±8.15mm), reduced left ventricular ejection fraction (0.38±0.08) and left atrial dilatation (43.36±5.16mm). The therapeutic approach followed consisted of patient orientation, elimination of etiological or causal factors of cardiac failure, and prescription of digitalis, diuretics, and angiotensinconverting enzyme inhibitors. RESULTS - Following treatment, left ventricular ejection fraction changed to 0.63±0.09; left ventricular diameters changed to 57.18±8.13mm, and left atrium diameters changed to 37.27±8.05mm. Maximum improvement was noted after 16.9±8.63 (6 to 36) months. CONCLUSION - Patients with serious cardiac failure and ventricular dysfunction caused by hypertension, alcoholism, or myocarditis can experience marked improvement in ventricular dysfunction after undergoing appropriate therapy within the venue of the doctor's office.
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Football is considered nowadays one of the most popular sports. In the betting world, it has acquired an outstanding position, which moves millions of euros during the period of a single football match. The lack of profitability of football betting users has been stressed as a problem. This lack gave origin to this research proposal, which it is going to analyse the possibility of existing a way to support the users to increase their profits on their bets. Data mining models were induced with the purpose of supporting the gamblers to increase their profits in the medium/long term. Being conscience that the models can fail, the results achieved by four of the seven targets in the models are encouraging and suggest that the system can help to increase the profits. All defined targets have two possible classes to predict, for example, if there are more or less than 7.5 corners in a single game. The data mining models of the targets, more or less than 7.5 corners, 8.5 corners, 1.5 goals and 3.5 goals achieved the pre-defined thresholds. The models were implemented in a prototype, which it is a pervasive decision support system. This system was developed with the purpose to be an interface for any user, both for an expert user as to a user who has no knowledge in football games.
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Patient blood pressure is an important vital signal to the physicians take a decision and to better understand the patient condition. In Intensive Care Units is possible monitoring the blood pressure due the fact of the patient being in continuous monitoring through bedside monitors and the use of sensors. The intensivist only have access to vital signs values when they look to the monitor or consult the values hourly collected. Most important is the sequence of the values collected, i.e., a set of highest or lowest values can signify a critical event and bring future complications to a patient as is Hypotension or Hypertension. This complications can leverage a set of dangerous diseases and side-effects. The main goal of this work is to predict the probability of a patient has a blood pressure critical event in the next hours by combining a set of patient data collected in real-time and using Data Mining classification techniques. As output the models indicate the probability (%) of a patient has a Blood Pressure Critical Event in the next hour. The achieved results showed to be very promising, presenting sensitivity around of 95%.