Assessing cost-effectiveness - Mental health: introduction to the study and methods

Objective: The Assessing Cost-Effectiveness - Mental Health (ACE-MH) study aims to assess from a health sector perspective, whether there are options for change that could improve the effectiveness and efficiency of Australia's current mental health services by directing available resources toward 'best practice' cost-effective services. Method: The use of standardized evaluation methods addresses the reservations expressed by many economists about the simplistic use of League Tables based on economic studies confounded by differences in methods, context and setting. The cost-effectiveness ratio for each intervention is calculated using economic and epidemiological data. This includes systematic reviews and randomised controlled trials for efficacy, the Australian Surveys of Mental Health and Wellbeing for current practice and a combination of trials and longitudinal studies for adherence. The cost-effectiveness ratios are presented as cost (A$) per disability-adjusted life year (DALY) saved with a 95% uncertainty interval based on Monte Carlo simulation modelling. An assessment of interventions on 'second filter' criteria ('equity', 'strength of evidence', 'feasibility' and 'acceptability to stakeholders') allows broader concepts of 'benefit' to be taken into account, as well as factors that might influence policy judgements in addition to cost-effectiveness ratios. Conclusions: The main limitation of the study is in the translation of the effect size from trials into a change in the DALY disability weight, which required the use of newly developed methods. While comparisons within disorders are valid, comparisons across disorders should be made with caution. A series of articles is planned to present the results.

Comparing predictions of extinction risk using models and subjective judgement

Models of population dynamics are commonly used to predict risks in ecology, particularly risks of population decline. There is often considerable uncertainty associated with these predictions. However, alternatives to predictions based on population models have not been assessed. We used simulation models of hypothetical species to generate the kinds of data that might typically be available to ecologists and then invited other researchers to predict risks of population declines using these data. The accuracy of the predictions was assessed by comparison with the forecasts of the original model. The researchers used either population models or subjective judgement to make their predictions. Predictions made using models were only slightly more accurate than subjective judgements of risk. However, predictions using models tended to be unbiased, while subjective judgements were biased towards over-estimation. Psychology literature suggests that the bias of subjective judgements is likely to vary somewhat unpredictably among people, depending on their stake in the outcome. This will make subjective predictions more uncertain and less transparent than those based on models. (C) 2004 Elsevier SAS. All rights reserved.

Nonhuman primate models and the failure of the Merck HIV-1 vaccine in humans

The adenovirus type 5 (Ad5)-based vaccine developed by Merck failed to either prevent HIV-1 infection or suppress viral load in subsequently infected subjects in the STEP human Phase 2b efficacy trial. Analogous vaccines had previously also failed in the simian immunodeficiency virus (SIV) challenge-rhesus macaque model. In contrast, vaccine protection studies that used challenge with a chimeric simian-human immunodeficiency virus (SHIV89.6P) in macaques did not predict the human trial results. Ad5 vector -based vaccines did not protect macaques from infection after SHIV89.6P challenge but did cause a substantial reduction in viral load and a preservation of CD4(+) T cell counts after infection, findings that were not reproduced in the human trials. Although the SIV challenge model is incompletely validated, we propose that its expanded use can help facilitate the prioritization of candidate HIV-1 vaccines, ensuring that resources are focused on the most promising candidates. Vaccine designers must now develop T cell vaccine strategies that reduce viral load after heterologous challenge.

Supersymmetric t-J Gaudin models and KZ equations

Supersymmetric t-J Gaudin models with open boundary conditions are investigated by means of the algebraic Bethe ansatz method. Off-shell Bethe ansatz equations of the boundary Gaudin systems are derived, and used to construct and solve the KZ equations associated with sl (2\1)((1)) superalgebra.

Color Models and Illumination Changes

Color model representation allows characterizing in a quantitative manner, any defined color spectrum of visible light, i.e. with a wavelength between 400nm and 700nm. To accomplish that, each model, or color space, is associated with a function that allows mapping the spectral power distribution of the visible electromagnetic radiation, in a space defined by a set of discrete values that quantify the color components composing the model. Some color spaces are sensitive to changes in lighting conditions. Others assure the preservation of certain chromatic features, remaining immune to these changes. Therefore, it becomes necessary to identify the strengths and weaknesses of each model in order to justify the adoption of color spaces in image processing and analysis techniques. This chapter will address the topic of digital imaging, main standards and formats. Next we will set the mathematical model of the image acquisition sensor response, which enables assessment of the various color spaces, with the aim of determining their invariance to illumination changes.

Chilling requirement for seed germination and phenological observations on peach cultivars

In subtropical climate areas, the models and methods proposed to evaluate the chilling requirement of temperate fruit crops often do not provide satisfactory results, thus calling for the development of alternative techniques. The aim of this study was to evaluate the correlations between some phonological traits and chilling requirement for seed germination of 18 peach cultivars and one nectarine cultivar. Two experiments were installed separately for the correlation studies. In experiment 1, the phenological traits were observed in the field, while in experiment 2, the chilling requirement for 50 and 100% seed germination of each cultivar was assessed. The number of days for beginning of bloom (r = 0.70**, 0.61**) and full bloom (r = 0.72**, 0.76**) were both significantly correlated with the number of chilling units for 50% and 100% germination of seeds. The number of days for beginning of budding and dormancy break were both significantly correlated with the number of chilling units for 50% and 100% germination (r = 0.48*, 0.50*, respectively). However, the same significant effect for these phenological traits was not found between chilling units and 50% germination of seeds, as well as between chilling units and harvest dates.

Impacts of vinasse and methods of sugarcane harvesting on the availability of K and carbon stock of an Argisol

ABSTRACT Soils of tropical regions are more weathered and in need of conservation managements to maintain and improve the quality of its components. The objective of this study was to evaluate the availability of K, the organic matter content and the stock of total carbon of an Argisol after vinasse application and manual and mechanized harvesting of burnt and raw sugarcane, in western São Paulo.The data collection was done in the 2012/2013 harvest, in a bioenergy company in Presidente Prudente/SP. The research was arranged out following a split-plot scheme in a 5x5 factorial design, characterized by four management systems: without vinasse application and harvest without burning; with vinasse application and harvest without burning; with vinasse application and harvest after burning; without vinasse application and harvest after burning; plus native forest, and five soil sampling depths (0-10 10-20, 20-30, 30-40, 40-50 cm), with four replications. In each treatment, the K content in the soil and accumulated in the remaining dry biomass in the area, the levels of organic matter, organic carbon and soil carbon stock were determined. The mean values were compared by Tukey test. The vinasse application associated with the harvest without burning increased the K content in soil layers up to 40 cm deep. The managements without vinasse application and manual harvest after burning, and without vinasse application with mechanical harvesting without burning did not increase the levels of organic matter, organic carbon and stock of total soil organic carbon, while the vinasse application and harvest after burning and without burning increased the levels of these attributes in the depth of 0-10 cm.

Preliminary Overview over Requirements Regarding Tools and Methods Derived from LUDA Cases

LUDA is a research project of Key Action 4 "City of Tomorrow & Cultural Heritage" of the programme "Energy, Environment and Sustainable Development" within the Fifth Framework Programme of the European Commission

Model morphisms (MoMo) to enable language independent information models and interoperable business networks

MSc. Dissertation presented at Faculdade de Ciências e Tecnologia of Universidade Nova de Lisboa to obtain the Master degree in Electrical and Computer Engineering

Structural time series models and the Kalman filter: A concise review

The continued increase in availability of economic data in recent years and, more importantly, the possibility to construct larger frequency time series, have fostered the use (and development) of statistical and econometric techniques to treat them more accurately. This paper presents an exposition of structural time series models by which a time series can be decomposed as the sum of a trend, seasonal and irregular components. In addition to a detailled analysis of univariate speci fications we also address the SUTSE multivariate case and the issue of cointegration. Finally, the recursive estimation and smoothing by means of the Kalman filter algorithm is described taking into account its different stages, from initialisation to parameter s estimation.

Internationalization strategies and methods of construction firms – a comparative study between Hong Kong - Chinese and Portuguese – European approaches

Dissertação para obtenção do Grau Mestre em Engenharia Civil – Perfil de Construção

Knowledge management framework based on brain models and human physiology

The life of humans and most living beings depend on sensation and perception for the best assessment of the surrounding world. Sensorial organs acquire a variety of stimuli that are interpreted and integrated in our brain for immediate use or stored in memory for later recall. Among the reasoning aspects, a person has to decide what to do with available information. Emotions are classifiers of collected information, assigning a personal meaning to objects, events and individuals, making part of our own identity. Emotions play a decisive role in cognitive processes as reasoning, decision and memory by assigning relevance to collected information. The access to pervasive computing devices, empowered by the ability to sense and perceive the world, provides new forms of acquiring and integrating information. But prior to data assessment on its usefulness, systems must capture and ensure that data is properly managed for diverse possible goals. Portable and wearable devices are now able to gather and store information, from the environment and from our body, using cloud based services and Internet connections. Systems limitations in handling sensorial data, compared with our sensorial capabilities constitute an identified problem. Another problem is the lack of interoperability between humans and devices, as they do not properly understand human’s emotional states and human needs. Addressing those problems is a motivation for the present research work. The mission hereby assumed is to include sensorial and physiological data into a Framework that will be able to manage collected data towards human cognitive functions, supported by a new data model. By learning from selected human functional and behavioural models and reasoning over collected data, the Framework aims at providing evaluation on a person’s emotional state, for empowering human centric applications, along with the capability of storing episodic information on a person’s life with physiologic indicators on emotional states to be used by new generation applications.