774 resultados para Healthcare improvement


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Using Wireless Sensor Networks (WSNs) in healthcare systems has had a lot of attention in recent years. In much of this research tasks like sensor data processing, health states decision making and emergency message sending are done by a remote server. Many patients with lots of sensor data consume a great deal of communication resources, bring a burden to the remote server and delay the decision time and notification time. A healthcare application for elderly people using WSN has been simulated in this paper. A WSN designed for the proposed healthcare application needs efficient MAC and routing protocols to provide a guarantee for the reliability of the data delivered from the patients to the medical centre. Based on these requirements, A cross layer based on the modified versions of APTEEN and GinMAC has been designed and implemented, with new features, such as a mobility module and routes discovery algorithms have been added. Simulation results show that the proposed cross layer based protocol can conserve energy for nodes and provide the required performance such as life time of the network, delay and reliability for the proposed healthcare application.

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Using Wireless Sensor Networks (WSNs) in healthcare systems has had a lot of attention in recent years. In much of this research tasks like sensor data processing, health states decision making and emergency message sending are done by a remote server. Many patients with lots of sensor data consume a great deal of communication resources, bring a burden to the remote server and delay the decision time and notification time. A healthcare application for elderly people using WSN has been simulated in this paper. A WSN designed for the proposed healthcare application needs efficient Medium Access Control (MAC) and routing protocols to provide a guarantee for the reliability of the data delivered from the patients to the medical centre. Based on these requirements, the GinMAC protocol including a mobility module has been chosen, to provide the required performance such as reliability for data delivery and energy saving. Simulation results show that this modification to GinMAC can offer the required performance for the proposed healthcare application.

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Using Wireless Sensor Networks (WSNs) in healthcare systems has had a lot of attention in recent years. In much of this research tasks like sensor data processing, health states decision making and emergency message sending are done by a remote server. Many patients with lots of sensor data consume a great deal of communication resources, bring a burden to the remote server and delay the decision time and notification time. A healthcare application for elderly people using WSN has been simulated in this paper. A WSN designed for the proposed healthcare application needs efficient MAC and routing protocols to provide a guarantee for the reliability of the data delivered from the patients to the medical centre. Based on these requirements, the GinMAC protocol including a mobility module has been chosen, to provide the required performance such as reliability for data delivery and energy saving. Simulation results show that this modification to GinMAC can offer the required performance for the proposed healthcare application.

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Background Cognitive–behavioural therapy (CBT) for childhood anxiety disorders is associated with modest outcomes in the context of parental anxiety disorder. Objectives This study evaluated whether or not the outcome of CBT for children with anxiety disorders in the context of maternal anxiety disorders is improved by the addition of (i) treatment of maternal anxiety disorders, or (ii) treatment focused on maternal responses. The incremental cost-effectiveness of the additional treatments was also evaluated. Design Participants were randomised to receive (i) child cognitive–behavioural therapy (CCBT); (ii) CCBT with CBT to target maternal anxiety disorders [CCBT + maternal cognitive–behavioural therapy (MCBT)]; or (iii) CCBT with an intervention to target mother–child interactions (MCIs) (CCBT + MCI). Setting A NHS university clinic in Berkshire, UK. Participants Two hundred and eleven children with a primary anxiety disorder, whose mothers also had an anxiety disorder. Interventions All families received eight sessions of individual CCBT. Mothers in the CCBT + MCBT arm also received eight sessions of CBT targeting their own anxiety disorders. Mothers in the MCI arm received 10 sessions targeting maternal parenting cognitions and behaviours. Non-specific interventions were delivered to balance groups for therapist contact. Main outcome measures Primary clinical outcomes were the child’s primary anxiety disorder status and degree of improvement at the end of treatment. Follow-up assessments were conducted at 6 and 12 months. Outcomes in the economic analyses were identified and measured using estimated quality-adjusted life-years (QALYs). QALYS were combined with treatment, health and social care costs and presented within an incremental cost–utility analysis framework with associated uncertainty. Results MCBT was associated with significant short-term improvement in maternal anxiety; however, after children had received CCBT, group differences were no longer apparent. CCBT + MCI was associated with a reduction in maternal overinvolvement and more confident expectations of the child. However, neither CCBT + MCBT nor CCBT + MCI conferred a significant post-treatment benefit over CCBT in terms of child anxiety disorder diagnoses [adjusted risk ratio (RR) 1.18, 95% confidence interval (CI) 0.87 to 1.62, p = 0.29; adjusted RR CCBT + MCI vs. control: adjusted RR 1.22, 95% CI 0.90 to 1.67, p = 0.20, respectively] or global improvement ratings (adjusted RR 1.25, 95% CI 1.00 to 1.59, p = 0.05; adjusted RR 1.20, 95% CI 0.95 to 1.53, p = 0.13). CCBT + MCI outperformed CCBT on some secondary outcome measures. Furthermore, primary economic analyses suggested that, at commonly accepted thresholds of cost-effectiveness, the probability that CCBT + MCI will be cost-effective in comparison with CCBT (plus non-specific interventions) is about 75%. Conclusions Good outcomes were achieved for children and their mothers across treatment conditions. There was no evidence of a benefit to child outcome of supplementing CCBT with either intervention focusing on maternal anxiety disorder or maternal cognitions and behaviours. However, supplementing CCBT with treatment that targeted maternal cognitions and behaviours represented a cost-effective use of resources, although the high percentage of missing data on some economic variables is a shortcoming. Future work should consider whether or not effects of the adjunct interventions are enhanced in particular contexts. The economic findings highlight the utility of considering the use of a broad range of services when evaluating interventions with this client group. Trial registration Current Controlled Trials ISRCTN19762288. Funding This trial was funded by the Medical Research Council (MRC) and Berkshire Healthcare Foundation Trust and managed by the National Institute for Health Research (NIHR) on behalf of the MRC–NIHR partnership (09/800/17) and will be published in full in Health Technology Assessment; Vol. 19, No. 38.

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Pervasive healthcare aims to deliver deinstitutionalised healthcare services to patients anytime and anywhere. Pervasive healthcare involves remote data collection through mobile devices and sensor network which the data is usually in large volume, varied formats and high frequency. The nature of big data such as volume, variety, velocity and veracity, together with its analytical capabilities com-plements the delivery of pervasive healthcare. However, there is limited research in intertwining these two domains. Most research focus mainly on the technical context of big data application in the healthcare sector. Little attention has been paid to a strategic role of big data which impacts the quality of healthcare services provision at the organisational level. Therefore, this paper delivers a conceptual view of big data architecture for pervasive healthcare via an intensive literature review to address the aforementioned research problems. This paper provides three major contributions: 1) identifies the research themes of big data and pervasive healthcare, 2) establishes the relationship between research themes, which later composes the big data architecture for pervasive healthcare, and 3) sheds a light on future research, such as semiosis and sense-making, and enables practitioners to implement big data in the pervasive healthcare through the proposed architecture.

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This thesis considers Participatory Crop Improvement (PCI) methodologies and examines the reasons behind their continued contestation and limited mainstreaming in conventional modes of crop improvement research within National Agricultural Research Systems (NARS). In particular, it traces the experiences of a long-established research network with over 20 years of experience in developing and implementing PCI methods across South Asia, and specifically considers its engagement with the Indian NARS and associated state-level agricultural research systems. In order to address the issues surrounding PCI institutionalisation processes, a novel conceptual framework was derived from a synthesis of the literatures on Strategic Niche Management (SNM) and Learning-based Development Approaches (LBDA) to analyse the socio-technical processes and structures which constitute the PCI ‘niche’ and NARS ‘regime’. In examining the niche and regime according to their socio-technical characteristics, the framework provides explanatory power for understanding the nature of their interactions and the opportunities and barriers that exist with respect to the translation of lessons and ideas between niche and regime organisations. The research shows that in trying to institutionalise PCI methods and principles within NARS in the Indian context, PCI proponents have encountered a number of constraints related to the rigid and hierarchical structure of the regime organisations; the contractual mode of most conventional research, which inhibits collaboration with a wider group of stakeholders; and the time-limited nature of PCI projects themselves, which limits investment and hinders scaling up of the innovations. It also reveals that while the niche projects may be able to induce a ‘weak’ form of PCI institutionalisation within the Indian NARS by helping to alter their institutional culture to be more supportive of participatory plant breeding approaches and future collaboration with PCI researchers, a ‘strong’ form of PCI institutionalisation, in which NARS organisations adopt participatory methodologies to address all their crop improvement agenda, is likely to remain outside of the capacity of PCI development projects to deliver.

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The aim of this study was to assess and improve the accuracy of biotransfer models for the organic pollutants (PCBs, PCDD/Fs, PBDEs, PFCAs, and pesticides) into cow’s milk and beef used in human exposure assessment. Metabolic rate in cattle is known as a key parameter for this biotransfer, however few experimental data and no simulation methods are currently available. In this research, metabolic rate was estimated using existing QSAR biodegradation models of microorganisms (BioWIN) and fish (EPI-HL and IFS-HL). This simulated metabolic rate was then incorporated into the mechanistic cattle biotransfer models (RAIDAR, ACC-HUMAN, OMEGA, and CKow). The goodness of fit tests showed that RAIDAR, ACC-HUMAN, OMEGA model performances were significantly improved using either of the QSARs when comparing the new model outputs to observed data. The CKow model is the only one that separates the processes in the gut and liver. This model showed the lowest residual error of all the models tested when the BioWIN model was used to represent the ruminant metabolic process in the gut and the two fish QSARs were used to represent the metabolic process in the liver. Our testing included EUSES and CalTOX which are KOW-regression models that are widely used in regulatory assessment. New regressions based on the simulated rate of the two metabolic processes are also proposed as an alternative to KOW-regression models for a screening risk assessment. The modified CKow model is more physiologically realistic, but has equivalent usability to existing KOW-regression models for estimating cattle biotransfer of organic pollutants.

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Considering the sea ice decline in the Arctic during the last decades, polynyas are of high research interest since these features are core areas of new ice formation. The determination of ice formation requires accurate retrieval of polynya area and thin-ice thickness (TIT) distribution within the polynya.We use an established energy balance model to derive TITs with MODIS ice surface temperatures (Ts) and NCEP/DOE Reanalysis II in the Laptev Sea for two winter seasons. Improvements of the algorithm mainly concern the implementation of an iterative approach to calculate the atmospheric flux components taking the atmospheric stratification into account. Furthermore, a sensitivity study is performed to analyze the errors of the ice thickness. The results are the following: 1) 2-m air temperatures (Ta) and Ts have the highest impact on the retrieved ice thickness; 2) an overestimation of Ta yields smaller ice thickness errors as an underestimation of Ta; 3) NCEP Ta shows often a warm bias; and 4) the mean absolute error for ice thicknesses up to 20 cm is ±4.7 cm. Based on these results, we conclude that, despite the shortcomings of the NCEP data (coarse spatial resolution and no polynyas), this data set is appropriate in combination with MODIS Ts for the retrieval of TITs up to 20 cm in the Laptev Sea region. The TIT algorithm can be applied to other polynya regions and to past and future time periods. Our TIT product is a valuable data set for verification of other model and remote sensing ice thickness data.

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Objective: We investigated whether lifestyle-induced changes in dietary fat quality are related to Improvements on glucose metabolism disturbances in Japanese Brazilians at high risk of type 2 diabetes Methods: One hundred forty-eight first- and second-generation subjects with impaired glucose tolerance or impaired fasting glycemia who attended a lifestyle intervention program for 12 mo were studied in the city of Bauru. State of Sao Paulo, Brazil Dietary fatty acid intakes at baseline and after 12 mo were estimated using three 24-h recalls. The effect of dietary fat intake on glucose metabolism was investigated by multiple logistic regression models Results: At baseline, mean standard deviation age and body mass index were 60 II y and 25 5 4.2 kg/m2, respectively After 12 mo. 92 subjects had normal plasma glucose levels and 56 remained in prediabetic conditions. Using logistic regression models adjusted for age, gender, generation, basal intake of explanatory nutrient, energy intake, physical activity, and waist circumference, the odds ratios (95% confidence intervals) for reversion to normoglycemia were 3 14 (1 22-8 10) in the second wrote of total w-3 fatty acid, 4 26 (1.34-13 57) in the second tunic of eicosapentaenoic acid, and 280 (1 10-7.10) in the second tertile of linolenic acid. Similarly. subjects in the highest wrote of w-3.w-6 fatty acid ratio showed a higher chance of improving glucose disturbances (2 51, 1.01-6.37) Conclusions: Our findings support the evidence of an independent protective effect of omega-3 fatty acid and of a higher omega-3:omega-6 fatty acid ratio on the glucose metabolism of high-risk individuals (C) 2010 Elsevier Inc All rights reserved.

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Characteristics of shiftwork schedules have implications for off-shift well-being. We examined the extent to which several shift characteristics (e.g., shift length, working sundays) are associated with three aspects of off-shift well-being: work-to-family conflict, physical well-being, and mental wellbeing. We also investigated whether these relationships differed in four nations. The Survey of Work and Time was completed by 906 healthcare professionals located in Australia, Brazil, Croatia, and the USA. Hierarchical multiple regression analyses supported the hypothesis that shiftwork characteristics account for significant unique variance in all three measures of well-being beyond that accounted for by work and family demands and personal characteristics. The patterns of regression weights indicated that particular shiftwork characteristics have differential relevance to indices of work-to-family conflict, physical well-being, and mental well-being. Our findings suggest that healthcare organizations should carefully consider the implications of shiftwork characteristics for off-shift well-being. Furthermore, although our findings did not indicate national differences in the nature of relationships between shift characteristics and well-being, shiftwork characteristics and demographics for healthcare professionals differ in systematic ways among nations; as such, effective solutions may be context-specific. (c) 2008 Elsevier Ltd. All rights reserved.

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Obesity and insulin resistance are highly correlated with metabolic disturbances. Both the excess and lack of adipose tissue can lead to severe insulin resistance and diabetes. Adipose tissue plays an active role in energy homeostasis, hormone secretion, and other proteins that affect insulin sensitivity, appetite, energy balance, and lipid metabolism. Rats with streptozotocin-induced diabetes during the neonatal period develop the classic diabetic picture of hyperglycemia, hypoinsulinemia, and insulin resistance in adulthood. Low body weight and reduced epididymal (EP) fit mass were also seen in this model. The am) of this study was to investigate the glucose homeostasis and metabolic repercussions on the adipose tissue following chronic treatment with antidiabetic drugs in these animals. In the 4th week post birth, diabetic animals started an 8-week treatment with pioglitazone, metformin, or insulin.

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In hypertension, left ventricular (LV) hypertrophy develops as an adaptive mechanism to compensate for increased afterload and thus preserve systolic function. Associated structural changes such as microvascular disease might potentially interfere with this mechanism, producing pathological hypertrophy. A poorer outcome is expected to occur when LV function is put in jeopardy by impaired coronary reserve. The aim of this study was to evaluate the role of coronary reserve in the long-term outcome of patients with hypertensive dilated cardiomyopathy. Between 1996 and 2000, 45 patients, 30 of them male, with 52 +/- 11 years and LV fractional shortening <30% were enrolled and followed until 2006. Coronary flow velocity reserve was assessed by transesophageal Doppler of the left anterior descending coronary artery. Sixteen patients showed >= 10% improvement in LV fractional shortening after 17 +/- 6 months. Coronary reserve was the only variable independently related to this improvement. Total mortality was 38% in 10 years. The Cox model identified coronary reserve (hazard ratio = 0.814; 95% CI = 0.72-0.92), LV mass, low diastolic blood pressure, and male gender as independent predictors of mortality. In hypertensive dilated cardiomyopathy, coronary reserve impairment adversely affects survival, possibly by interfering with the improvement of LV dysfunction. J Am Soc Hypertens 2010;4(1):14-21. (C) 2010 American Society of Hypertension. All rights reserved.

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In this work, 1 wt % Pd/ZrO(2)-CeO(2) mixed oxide nanotubes with 90 mol % CeO(2) were synthesized following a very simple, high-yield procedure and their properties were characterized by synchrotron radiation X-ray diffraction, X-ray absorption near-edge spectroscopy (XANES), and scanning and high-resolution transmission electron microscopy (SEM and HRTEM). In situ XANES experiments were carried out under reducing conditions to investigate the reduction behavior of these novel nanotube materials. The Pd/CeO(2)-based nanotubes exhibited the cubic phase (Fm3m space group). The nanotube walls were composed of nanoparticles with an average crystallite size of about 7 nm, and the nanotubes exhibited a large specific surface area (85 m(2).g(-1)). SEM and HRTEM studies showed that individual nanotubes were composed of a curved sheet of these nanoparticles. Elemental analysis showed that the Ce:Zr:Pd ratios appeared to be approximately constant across space, suggesting compositional homogeneity in the samples. XANES results indicated that the extent of reduction of these materials is low and that the Ce(4+) state is in the majority over the reduced Ce(3+) state. The results suggest that Pd cations-most likely Pd(2+)-form a Pd-Ce-Zr oxide solid solution and that the Pd(2+) is stabilized against reduction in this phase. However, incorporation of the Pd (1 wt %) into the crystal lattice of the nanotubes also appeared to destabilize Ce(4+) against reduction to Ce(3+) and caused a significant increase in its reducibility.

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Phototherapy improves cellular activation which is an important factor for the treatment of cellulite. The objective of this research was to develop and evaluate the effects of a new (noninvasive and nonpharmacological) clinical procedure to improve body aesthetics: infrared-LED (850 nm) plus treadmill training. Twenty women (25-55 years old) participated in this study. They were separated in two groups: the control group, which carried out only the treadmill training (n = 10), and the LED group, with phototherapy during the treadmill training (n - 10). The training was performed for 45 minutes twice a week over 3 months at intensities between 85% and 90% maximal heart rate (HR(max)). The irradiation parameters were 39 mW/cm(2) and a fluence of 106 J/cm(2). The treatment was evaluated by interpreting body composition parameters, photographs and thermography. This was primarily a treatment for cellulite with a reduction of saddlebag and thigh circumference. At the same time, the treadmill training prevented an increase of body fat, as well as the loss of lean mass. Moreover, thermal images of the temperature modification of the thighs are presented. These positive effects can result in a further improvement of body aesthetics using infrared-LED together with treadmill training.

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This paper presents the use of a multiprocessor architecture for the performance improvement of tomographic image reconstruction. Image reconstruction in computed tomography (CT) is an intensive task for single-processor systems. We investigate the filtered image reconstruction suitability based on DSPs organized for parallel processing and its comparison with the Message Passing Interface (MPI) library. The experimental results show that the speedups observed for both platforms were increased in the same direction of the image resolution. In addition, the execution time to communication time ratios (Rt/Rc) as a function of the sample size have shown a narrow variation for the DSP platform in comparison with the MPI platform, which indicates its better performance for parallel image reconstruction.