922 resultados para Intergenerational resource allocation
Resumo:
The Mara River Basin (MRB) is endowed with pristine biodiversity, socio-cultural heritage and natural resources. The purpose of my study is to develop and apply an integrated water resource allocation framework for the MRB based on the hydrological processes, water demand and economic factors. The basin was partitioned into twelve sub-basins and the rainfall runoff processes was modeled using the Soil and Water Assessment Tool (SWAT) after satisfactory Nash-Sutcliff efficiency of 0.68 for calibration and 0.43 for validation at Mara Mines station. The impact and uncertainty of climate change on the hydrology of the MRB was assessed using SWAT and three scenarios of statistically downscaled outputs from twenty Global Circulation Models. Results predicted the wet season getting more wet and the dry season getting drier, with a general increasing trend of annual rainfall through 2050. Three blocks of water demand (environmental, normal and flood) were estimated from consumptive water use by human, wildlife, livestock, tourism, irrigation and industry. Water demand projections suggest human consumption is expected to surpass irrigation as the highest water demand sector by 2030. Monthly volume of water was estimated in three blocks of current minimum reliability, reserve (>95%), normal (80–95%) and flood (40%) for more than 5 months in a year. The assessment of water price and marginal productivity showed that current water use hardly responds to a change in price or productivity of water. Finally, a water allocation model was developed and applied to investigate the optimum monthly allocation among sectors and sub-basins by maximizing the use value and hydrological reliability of water. Model results demonstrated that the status on reserve and normal volumes can be improved to ‘low’ or ‘moderate’ by updating the existing reliability to meet prevailing demand. Flow volumes and rates for four scenarios of reliability were presented. Results showed that the water allocation framework can be used as comprehensive tool in the management of MRB, and possibly be extended similar watersheds.
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The rapid growth of virtualized data centers and cloud hosting services is making the management of physical resources such as CPU, memory, and I/O bandwidth in data center servers increasingly important. Server management now involves dealing with multiple dissimilar applications with varying Service-Level-Agreements (SLAs) and multiple resource dimensions. The multiplicity and diversity of resources and applications are rendering administrative tasks more complex and challenging. This thesis aimed to develop a framework and techniques that would help substantially reduce data center management complexity. We specifically addressed two crucial data center operations. First, we precisely estimated capacity requirements of client virtual machines (VMs) while renting server space in cloud environment. Second, we proposed a systematic process to efficiently allocate physical resources to hosted VMs in a data center. To realize these dual objectives, accurately capturing the effects of resource allocations on application performance is vital. The benefits of accurate application performance modeling are multifold. Cloud users can size their VMs appropriately and pay only for the resources that they need; service providers can also offer a new charging model based on the VMs performance instead of their configured sizes. As a result, clients will pay exactly for the performance they are actually experiencing; on the other hand, administrators will be able to maximize their total revenue by utilizing application performance models and SLAs. This thesis made the following contributions. First, we identified resource control parameters crucial for distributing physical resources and characterizing contention for virtualized applications in a shared hosting environment. Second, we explored several modeling techniques and confirmed the suitability of two machine learning tools, Artificial Neural Network and Support Vector Machine, to accurately model the performance of virtualized applications. Moreover, we suggested and evaluated modeling optimizations necessary to improve prediction accuracy when using these modeling tools. Third, we presented an approach to optimal VM sizing by employing the performance models we created. Finally, we proposed a revenue-driven resource allocation algorithm which maximizes the SLA-generated revenue for a data center.
Resumo:
With the exponential growth of the usage of web-based map services, the web GIS application has become more and more popular. Spatial data index, search, analysis, visualization and the resource management of such services are becoming increasingly important to deliver user-desired Quality of Service. First, spatial indexing is typically time-consuming and is not available to end-users. To address this, we introduce TerraFly sksOpen, an open-sourced an Online Indexing and Querying System for Big Geospatial Data. Integrated with the TerraFly Geospatial database [1-9], sksOpen is an efficient indexing and query engine for processing Top-k Spatial Boolean Queries. Further, we provide ergonomic visualization of query results on interactive maps to facilitate the user’s data analysis. Second, due to the highly complex and dynamic nature of GIS systems, it is quite challenging for the end users to quickly understand and analyze the spatial data, and to efficiently share their own data and analysis results with others. Built on the TerraFly Geo spatial database, TerraFly GeoCloud is an extra layer running upon the TerraFly map and can efficiently support many different visualization functions and spatial data analysis models. Furthermore, users can create unique URLs to visualize and share the analysis results. TerraFly GeoCloud also enables the MapQL technology to customize map visualization using SQL-like statements [10]. Third, map systems often serve dynamic web workloads and involve multiple CPU and I/O intensive tiers, which make it challenging to meet the response time targets of map requests while using the resources efficiently. Virtualization facilitates the deployment of web map services and improves their resource utilization through encapsulation and consolidation. Autonomic resource management allows resources to be automatically provisioned to a map service and its internal tiers on demand. v-TerraFly are techniques to predict the demand of map workloads online and optimize resource allocations, considering both response time and data freshness as the QoS target. The proposed v-TerraFly system is prototyped on TerraFly, a production web map service, and evaluated using real TerraFly workloads. The results show that v-TerraFly can accurately predict the workload demands: 18.91% more accurate; and efficiently allocate resources to meet the QoS target: improves the QoS by 26.19% and saves resource usages by 20.83% compared to traditional peak load-based resource allocation.
Resumo:
Sendo as necessidades de saúde mais amplas que os recursos disponíveis, escolhas têm de ser feitas. Disto resulta ser preciso que se estabeleçam limites, critérios e parâmetros para priorizar o que vai ser ofertado e a quem os serviços e os cuidados de saúde serão oferecidos. Discute-se alternativas éticas para a priorização e racionamento de cuidados de saúde, enfocando os princípios da eqüidade e da utilidade social.
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Governmental programmes should be developed to collect and analyse data on healthcare associated infections (HAIs). This study describes the healthcare setting and both the implementation and preliminary results of the Programme for Surveillance of Healthcare Associated Infections in the State of Sao Paulo (PSHAISP), Brazil, from 2004 to 2006. Characterisation of the healthcare settings was carried out using a national database. The PSHAISP was implemented using components for acute care hospitals (ACH) or long term care facilities (LTCF). The components for surveillance in ACHs were surgical unit, intensive care unit and high risk nursery. The infections included in the surveillance were surgical site infection in clean surgery, pneumonia, urinary tract infection and device-associated bloodstream infections. Regarding the LTCF component, pneumonia, scabies and gastroenteritis in all inpatients were reported. In the first year of the programme there were 457 participating healthcare settings, representing 51.1% of the hospitals registered in the national database. Data obtained in this study are the initial results and have already been used for education in both surveillance and the prevention of HAI. The results of the PSHAISP show that it is feasible to collect data from a large number of hospitals. This will assist the State of Sao Paulo in assessing the impact of interventions and in resource allocation. (C) 2010 The Hospital Infection Society. Published by Elsevier Ltd. All rights reserved.
Resumo:
Scheduling parallel and distributed applications efficiently onto grid environments is a difficult task and a great variety of scheduling heuristics has been developed aiming to address this issue. A successful grid resource allocation depends, among other things, on the quality of the available information about software artifacts and grid resources. In this article, we propose a semantic approach to integrate selection of equivalent resources and selection of equivalent software artifacts to improve the scheduling of resources suitable for a given set of application execution requirements. We also describe a prototype implementation of our approach based on the Integrade grid middleware and experimental results that illustrate its benefits. Copyright (C) 2009 John Wiley & Sons, Ltd.
Resumo:
A dissociation between two putative measures of resource allocation skin conductance responding, and secondary task reaction time (RT), has been observed during auditory discrimination tasks. Four experiments investigated the time course of the dissociation effect with a visual discrimination task. participants were presented with circles and ellipses and instructed to count the number of longer-than-usual presentations of one shape (task-relevant) and to ignore presentations of the other shape (task-irrelevant). Concurrent with this task, participants made a speeded motor response to an auditory probe. Experiment 1 showed that skin conductance responses were larger during task-relevant stimuli than during task-irrelevant stimuli, whereas RT to probes presented at 150 ms following shape onset was slower during task-irrelevant stimuli. Experiments 2 to 4 found slower RT during task-irrelevant stimuli at probes presented at 300 ms before shape onset until 150 ms following shape onset. At probes presented 3,000 and 4,000 ms following shape onset probe RT was slower during task-relevant stimuli. The similarities between the observed time course and the so-called psychological refractory period (PRF) effect are discussed.
Resumo:
The effect that the difficulty of the discrimination between task-relevant and task-irrelevant stimuli has on the relationship between skin conductance orienting and secondary task reaction time (RT) was examined. Participants (N = 72) counted the number of longer-than-usual presentations of one shape (task-relevant) and ignored presentations of another shape (task-irrelevant). The difficulty of discriminating between the two shapes varied across three groups (low, medium, and high difficulty). Simultaneous with the primary counting task, participants performed a secondary RT task to acoustic probes presented 50, 150, and 2000 ms following shape onset. Skin conductance orienting was larger, and secondary RT at the 2000 ms probe position was slower during task-relevant shapes than during task-irrelevant shapes in the low-difficulty group. This difference declined as the discrimination difficulty was increased, such that there was no difference in the high-difficulty group. Secondary RT was slower during task-irrelevant shapes than during task-relevant shapes only in the medium-difficulty group-and only at the 150 ms probe position in the first half of the experiment. The close relationship between autonomic orienting and secondary RT at the 2000 ms probe position suggests that orienting reflects the resource allocation that results from the number of matching features between a stimulus input and a mental representation primed as significant.
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Objective: To assess from a health sector perspective the incremental cost-effectiveness of cognitive behavioural therapy (CBT) and selective serotonin reuptake inhibitors (SSRIs) for the treatment of major depressive disorder (MDD) in children and adolescents, compared to 'current practice'. Method: The health benefit is measured as a reduction in disability-adjusted life years (DALYs), based on effect size calculations from meta-analysis of randomised controlled trials. An assessment on second stage filter criteria ('equity'; 'strength of evidence', 'feasibility' and 'acceptability to stakeholders') is also undertaken to incorporate additional factors that impact on resource allocation decisions. Costs and benefits are tracked for the duration of a new episode of MDD arising in eligible children (age 6-17 years) in the Australian population in the year 2000. Simulation-modelling techniques are used to present a 95% uncertainty interval (UI) around the cost-effectiveness ratios. Results: Compared to current practice, CBT by public psychologists is the most cost-effective intervention for MDD in children and adolescents at A$9000 per DALY saved (95% UI A$3900 to A$24 000). SSRIs and CBT by other providers are less cost-effective but likely to be less than A$50 000 per DALY saved (> 80% chance). CBT is more effective than SSRIs in children and adolescents, resulting in a greater total health benefit (DALYs saved) than could be achieved with SSRIs. Issues that require attention for the CBT intervention include equity concerns, ensuring an adequate workforce, funding arrangements and acceptability to various stakeholders. Conclusions: Cognitive behavioural therapy provided by a public psychologist is the most effective and cost-effective option for the first-line treatment of MDD in children and adolescents. However, this option is not currently accessible by all patients and will require change in policy to allow more widespread uptake. It will also require 'start-up' costs and attention to ensuring an adequate workforce.
Resumo:
Objective: To analyze from a health sector perspective the cost-effectiveness of dexamphetamine (DEX) and methylphenidate (MPH) interventions to treat childhood attention deficit hyperactivity disorder (ADHD), compared to current practice. Method: Children eligible for the interventions are those aged between 4 and 17 years in 2000, who had ADHD and were seeking care for emotional or behavioural problems, but were not receiving stimulant medication. To determine health benefit, a meta-analysis of randomized controlled trials was performed for DEX and MPH, and the effect sizes were translated into utility values. An assessment on second stage filter criteria ('equity', 'strength of evidence', 'feasibility' and 'acceptability to stakeholders') is also undertaken to incorporate additional factors that impact on resource allocation decisions. Simulation modelling techniques are used to present a 95% uncertainty interval (UI) around the incremental cost-effectiveness ratio (ICER), which is calculated in cost (in A$) per DALY averted. Results: The ICER for DEX is A$4100/DALY saved (95% UI: negative to A$14 000) and for MPH is A$15 000/DALY saved (95% UI: A$9100-22 000). DEX is more costly than MPH for the government, but much less costly for the patient. Conclusions: MPH and DEX are cost-effective interventions for childhood ADHD. DEX is more cost-effective than MPH, although if MPH were listed at a lower price on the Pharmaceutical Benefits Scheme it would become more cost-effective. Increased uptake of stimulants for ADHD would require policy change. However, the medication of children and wider availability of stimulants may concern parents and the community.
Resumo:
Objective: To assess from a health sector perspective the incremental cost-effectiveness of interventions for generalized anxiety disorder (cognitive behavioural therapy [CBT] and serotonin and noradrenaline reuptake inhibitors [SNRIs]) and panic disorder (CBT, selective serotonin reuptake inhibitors [SSRIs] and tricyclic antidepressants [TCAs]). Method: The health benefit is measured as a reduction in disability-adjusted life years (DALYs), based on effect size calculations from meta-analyses of randomised controlled trials. An assessment on second stage filters ('equity', 'strength of evidence', 'feasibility' and 'acceptability to stakeholders') is also undertaken to incorporate additional factors that impact on resource allocation decisions. Costs and benefits are calculated for a period of one year for the eligible population (prevalent cases of generalized anxiety disorder/panic disorder identified in the National Survey of Mental Health and Wellbeing, extrapolated to the Australian population in the year 2000 for those aged 18 years and older). Simulation modelling techniques are used to present 95% uncertainty intervals (UI) around the incremental cost-effectiveness ratios (ICERs). Results: Compared to current practice, CBT by a psychologist on a public salary is the most cost-effective intervention for both generalized anxiety disorder (A$6900/DALY saved; 95% UI A$4000 to A$12 000) and panic disorder (A$6800/DALY saved; 95% UI A$2900 to A$15 000). Cognitive behavioural therapy results in a greater total health benefit than the drug interventions for both anxiety disorders, although equity and feasibility concerns for CBT interventions are also greater. Conclusions: Cognitive behavioural therapy is the most effective and cost-effective intervention for generalized anxiety disorder and panic disorder. However, its implementation would require policy change to enable more widespread access to a sufficient number of trained therapists for the treatment of anxiety disorders.
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Psychosocial manifestations of erectile dysfunction (ED) differ across cultures. Understanding the treatment response to ED medications within cultural groups can aid in resource allocation and in developing treatment strategies. Evaluate the effect of sildenafil treatment on self-esteem, confidence, and sexual relationship satisfaction in Brazilian men with ED. The Self-Esteem and Relationship (SEAR) questionnaire, a validated, 14-question instrument developed to specifically address self-esteem and relationship issues within the context of ED. Men aged 18 years or older with a clinical diagnosis of ED (<= 21 on the Sexual Health Inventory for Men) and in a stable relationship with a partner during the study were eligible. The primary end point was a change from baseline in the self-esteem subscale of the SEAR questionnaire. Thirteen Brazilian sites participated in a randomized, double-blind, placebo-controlled trial of sildenafil treatment for ED. Patients were randomized to receive either 50 mg of sildenafil (adjustable to 25 mg or 100 mg based on patient response) or matching placebo approximately 1 hour before anticipated sexual activity but not more than once a day. At the end of double-blind treatment, 63 and 66 patients in the placebo and sildenafil groups, respectively, from 13 Brazilian sites were assessed for efficacy. Brazilian patients receiving sildenafil had significantly greater improvements in their scores on the SEAR self-esteem subscale (42.9 [95% confidence interval 35.7-50.0]) compared with placebo (21.1 [95% confidence interval 13.7-28.6]; P < 0.0001). Effect sizes ranged from 0.91 to 1.25 for individual SEAR components. The psychosocial parameters in Brazilian men with ED assessed by the SEAR questionnaire showed significant improvements in self-esteem, confidence, and relationships after treatment with sildenafil. Glina S, Damiao R, Abdo C, Afif-Abdo J, Tseng L-J, and Stecher V. Self-esteem, confidence, and relationships in Brazilian men with erectile dysfunction receiving sildenafil citrate: A randomized, parallel-group, double-blind, placebo-controlled study in Brazil. J Sex Med 2009;6:268-275.
Resumo:
Background Burden-of-illness data, which are often used in setting healthcare policy-spending priorities, are unavailable for mental disorders in most countries. Aims To examine one central aspect of illness burden, the association of serious mental illness with earnings, in the World Health Organization (WHO) World Mental Health (WMH) Surveys. Method The WMH Surveys were carried out in 10 high-income and 9 low- and middle-income countries. The associations of personal earnings with serious mental illness were estimated. Results Respondents with serious mental illness earned on average a third less than median earnings, with no significant between-country differences (chi(2)(9)=5.5-8.1, P=0.5-0.79). These losses are equivalent to 0.3-0.8% of total national earnings. Reduced earnings among those with earnings and the increased probability of not earning are both important components of these associations: Conclusions These results add to a growing body of evidence that mental disorders have high societal costs. Decisions about healthcare resource allocation should take these costs into consideration.
Resumo:
Objective: To develop a model to predict the bleeding source and identify the cohort amongst patients with acute gastrointestinal bleeding (GIB) who require urgent intervention, including endoscopy. Patients with acute GIB, an unpredictable event, are most commonly evaluated and managed by non-gastroenterologists. Rapid and consistently reliable risk stratification of patients with acute GIB for urgent endoscopy may potentially improve outcomes amongst such patients by targeting scarce health-care resources to those who need it the most. Design and methods: Using ICD-9 codes for acute GIB, 189 patients with acute GIB and all. available data variables required to develop and test models were identified from a hospital medical records database. Data on 122 patients was utilized for development of the model and on 67 patients utilized to perform comparative analysis of the models. Clinical data such as presenting signs and symptoms, demographic data, presence of co-morbidities, laboratory data and corresponding endoscopic diagnosis and outcomes were collected. Clinical data and endoscopic diagnosis collected for each patient was utilized to retrospectively ascertain optimal management for each patient. Clinical presentations and corresponding treatment was utilized as training examples. Eight mathematical models including artificial neural network (ANN), support vector machine (SVM), k-nearest neighbor, linear discriminant analysis (LDA), shrunken centroid (SC), random forest (RF), logistic regression, and boosting were trained and tested. The performance of these models was compared using standard statistical analysis and ROC curves. Results: Overall the random forest model best predicted the source, need for resuscitation, and disposition with accuracies of approximately 80% or higher (accuracy for endoscopy was greater than 75%). The area under ROC curve for RF was greater than 0.85, indicating excellent performance by the random forest model Conclusion: While most mathematical models are effective as a decision support system for evaluation and management of patients with acute GIB, in our testing, the RF model consistently demonstrated the best performance. Amongst patients presenting with acute GIB, mathematical models may facilitate the identification of the source of GIB, need for intervention and allow optimization of care and healthcare resource allocation; these however require further validation. (c) 2007 Elsevier B.V. All rights reserved.
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OBJECTIVE: The results of an evaluative longitudinal study, which identified the effects of health care decentralization on health financing in Mexico, Nicaragua and Peru are presented in this article. METHODS: The methodology had two main phases. In the first, secondary sources of data and documents were analyzed with the following variables: type of decentralization implemented, source of financing, funds for financing, providers, final use of resources, mechanisms for resource allocation. In the second phase, primary data were collected by a survey of key personnel in the health sector. RESULTS: Results of the comparative analysis are presented, showing the changes implemented in the three countries, as well as the strengths and weaknesses of each country in matters of financing and decentralization. CONCLUSIONS: The main financing changes implemented and quantitative trends with respect to the five financing indicators are presented as a methodological tool to implement corrections and adjustments in health financing.