Parameterization and Evaluation of Predictions of DSSAT/CANEGRO for Brazilian Sugarcane

The DSSAT/CANEGRO model was parameterized and its predictions evaluated using data from five sugarcane (Sacchetrum spp.) experiments conducted in southern Brazil. The data used are from two of the most important Brazilian cultivars. Some parameters whose values were either directly measured or considered to be well known were not adjusted. Ten of the 20 parameters were optimized using a Generalized Likelihood Uncertainty Estimation (GLUE) algorithm using the leave-one-out cross-validation technique. Model predictions were evaluated using measured data of leaf area index (LA!), stalk and aerial dry mass, sucrose content, and soil water content, using bias, root mean squared error (RMSE), modeling efficiency (Eff), correlation coefficient, and agreement index. The Decision Support System for Agrotechnology Transfer (DSSAT)/CANEGRO model simulated the sugarcane crop in southern Brazil well, using the parameterization reported here. The soil water content predictions were better for rainfed (mean RMSE = 0.122mm) than for irrigated treatment (mean RMSE = 0.214mm). Predictions were best for aerial dry mass (Eff = 0.850), followed by stalk dry mass (Eff = 0.765) and then sucrose mass (Eff = 0.170). Number of green leaves showed the worst fit (Eff = -2.300). The cross-validation technique permits using multiple datasets that would have limited use if used independently because of the heterogeneity of measures and measurement strategies.

On compliance of business processes with business contracts

This paper addresses the problem of ensuring compliance of business processes, implemented within and across organisational boundaries, with the constraints stated in related business contracts. In order to deal with the complexity of this problem we propose two solutions that allow for a systematic and increasingly automated support for addressing two specific compliance issues. One solution provides a set of guidelines for progressively transforming contract conditions into business processes that are consistent with contract conditions thus avoiding violation of the rules in contract. Another solution compares rules in business contracts and rules in business processes to check for possible inconsistencies. Both approaches rely on a computer interpretable representation of contract conditions that embodies contract semantics. This semantics is described in terms of a logic based formalism allowing for the description of obligations, prohibitions, permissions and violations conditions in contracts. This semantics was based on an analysis of typical building blocks of many commercial, financial and government contracts. The study proved that our contract formalism provides a good foundation for describing key types of conditions in contracts, and has also given several insights into valuable transformation techniques and formalisms needed to establish better alignment between these two, traditionally separate areas of research and endeavour. The study also revealed a number of new areas of research, some of which we intend to address in near future.

DR-NEGOTIATE - A system for automated agent negotiation with defeasible logic-based strategies

This paper reports on a system for automated agent negotiation, based on a formal and executable approach to capture the behavior of parties involved in a negotiation. It uses the JADE agent framework, and its major distinctive feature is the use of declarative negotiation strategies. The negotiation strategies are expressed in a declarative rules language, defeasible logic, and are applied using the implemented system DR-DEVICE. The key ideas and the overall system architecture are described, and a particular negotiation case is presented in detail.

Predicting sprint running times from isokinetic and squat lift tests: A regression analysis

This study examined the relationship between isokinetic hip extensor/hip flexor strength, 1-RM squat strength, and sprint running performance for both a sprint-trained and non-sprint-trained group. Eleven male sprinters and 8 male controls volunteered for the study. On the same day subjects ran 20-m sprints from both a stationary start and with a 50-m acceleration distance, completed isokinetic hip extension/flexion exercises at 1.05, 4.74, and 8.42 rad.s(-1), and had their squat strength estimated. Stepwise multiple regression analysis showed that equations for predicting both 20-m maximum velocity nm time and 20-m acceleration time may be calculated with an error of less than 0.05 sec using only isokinetic and squat strength data. However, a single regression equation for predicting both 20-m acceleration and maximum velocity run times from isokinetic or squat tests was not found. The regression analysis indicated that hip flexor strength at all test velocities was a better predictor of sprint running performance than hip extensor strength.

Exploratory Approach to the use of Techniques of Regression Analysis and Pooled Analysis in Studies of Consumer Behavior

This paper is part of a large study to assess the adequacy of the use of multivariate statistical techniques in theses and dissertations of some higher education institutions in the area of marketing with theme of consumer behavior from 1997 to 2006. The regression and conjoint analysis are focused on in this paper, two techniques with great potential of use in marketing studies. The objective of this study was to analyze whether the employement of these techniques suits the needs of the research problem presented in as well as to evaluate the level of success in meeting their premisses. Overall, the results suggest the need for more involvement of researchers in the verification of all the theoretical precepts of application of the techniques classified in the category of investigation of dependence among variables.

Depression in women living with HIV: clinical and psychosocial correlates

The number of Brazilian women living with HIV has increased significantly in past years, rendering studies of their particular care demands including psychiatric issues. This study measures the prevalence of major depression, using the Structured Clinical Interview for DSM-IV Axis I Disorders, in a sample of 120 women living with HIV in treatment at a reference centre in So Paulo. Socio-demographic variables, HIV-related clinical and laboratory data, including CD4+ cell counts and HIV plasma viral loads, as well as psychosocial features (intimate relationships, disclosure of HIV serostatus, partner`s serostatus and patient`s emotional and financial support) were investigated as factors potentially associated with depression. The prevalence of major depression at the time of evaluation was 25.8% (95% CI 18.2-33.4%). Clinical status (p = 0.002), lack of emotional support (p = 0.02), use of antidepressants (p = 0.028) and length of time since HIV diagnosis (p = 0.05) were associated with major depression in univariate analysis. In multivariate multiple-regression model, HIV clinical status, lack of emotional support and higher plasma viral loads were associated with depression. Sixty per cent of the women have a major depression diagnosis during lifetime. We conclude that major depression is highly prevalent among women living with HIV, but it is still underdiagnosed and undertreated.

Echocardiographic predictors of functional capacity in endomyocardial fibrosis patients

Endomyocardial fibrosis (EMF) is a restrictive cardiomyopathy manifested mainly by diastolic heart failure. It is recognized that diastole is an important determinant of exercise capacity. The purpose of this study was to determine whether resting echocardiographic parameters might predict oxygen consumption (VO(2p)) by ergoespirometry and the prognostic role of functional capacity in EMF patients. A total of 32 patients with biventricular EMF (29 women, 55.3 +/- 11.4 years) were studied by echocardiography and ergoespirometry. The relationship between the echocardiographic indexes and the percentage of predicted VO(2p) (%VO(2p)) was investigated by the `stepwise` linear regression analysis. The median VO(2p) was 11 +/- 3 mL/kg/min and the %VO(2p) was 53 +/- 9%. There was a correlation of %VO(2p) with an average of A` at four sites of the mitral annulus (A` peak, r = 0.471, P = 0.023), E`/A` of the inferior mitral annulus (r = -0.433, P = 0.044), and myocardial performance index (r = -0.352, P = 0.048). On multiple regression analysis, only A` peak was an independent predictor of %VO(2p) (%VO(2p)= 26.34 + 332.44 x A` peak). EMF patients with %VO(2p)< 53% had an increased mortality rate with a relative risk of 8.47. In EMF patients, diastolic function plays an important role in determining the limitations to exercise and %VO(2p) has a prognostic value.

Characteristics and Predictors of Obstructive Sleep Apnea in Patients With Systemic Hypertension

Obstructive sleep apnea (OSA) is a secondary cause of hypertension and independently associated with target-organ damage in hypertensive patients. However, OSA remains largely underdiagnosed and undertreated. The aim of the present study was to evaluate the characteristics and clinical predictors of OSA in a consecutive series of patients followed up in a hypertension unit. A total of 99 patients (age 46 +/- 11 years, body mass index 28.8 kg/m(2), range 25.1 to 32.9) underwent polysomnography. The clinical parameters included age, gender, obesity, daytime sleepiness, snoring, Berlin Questionnaire, resistant hypertension, and metabolic syndrome. Of the 99 patients, 55 (56%) had OSA (apnea-hypopnea index >5 events/hour). Patients with OSA were older and more obese, had greater levels of blood pressure, and presented with more diabetes, dyslipidemia, resistant hypenension, and metabolic syndrome than the patients without OSA. Of the patients with OSA, 51% had no excessive daytime sleepiness. The Berlin Questionnaire and patient age revealed a high sensitivity (0.93 and 0.91, respectively) but low specificity (0.59 and 0.48, respectively), and obesity and resistant hypertension revealed a low sensitivity (0.58 and 0.44, respectively) but high specificity (0.75 and 0.91, respectively) for OSA. Metabolic syndrome was associated with high sensitivity and specificity for OSA (0.86 and 0.85, respectively). Multiple regression analysis showed that age of 40 to 70 years (odds ratio 1.09, 95% confidence interval 1.03 to 1.16), a high risk of OSA on the Berlin Questionnaire (odds ratio 8.36, 95% confidence interval 1.67 to 41.85), and metabolic syndrome (odds ratio 19.04, 95% confidence interval 5.25 to 69.03) were independent variables associated with OSA. In conclusion, more important than the typical clinical features that characterize OSA, including snoring and excessive daytime sleepiness, the presence of the metabolic syndrome is as an important marker of OSA among patients with hypertension. (C) 2010 Elsevier Inc. All rights reserved. (Am J Cardiol 2010;105:1135-1139)

Amygdala hyperactivation in untreated depressed individuals

The amygdala participates in the detection and control of affective states, and has been proposed to be a site of dysfunction in affective disorders. To assess amygdala processing in individuals with unipolar depression, we applied a functional MRI (fMRI) paradigm previously shown to be sensitive to amygdala function. Fourteen individuals with untreated DSM-IV major depression and 15 healthy subjects were studied using fMRI with a standardized emotion face recognition task. Voxel-level data sets were subjected to a multiple-regression analysis, and functionally defined regions of interest (ROI), including bilateral amygdala, were analyzed with MANOVA. Pearson correlation coefficients between amygdala activation and HAM-D score also were performed. While both depressed and healthy groups showed increased amygdala activity when viewing emotive faces compared to geometric shapes, patients with unipolar depression showed relatively more activity than healthy subjects, particularly on the left. Positive Pearson correlations between amygdala activation and HAM-D score were found for both left and right ROIs in the patient group. This study provides in vivo imaging evidence to support the hypothesis of abnormal amygdala functioning in depressed individuals. (C) 2009 Elsevier Ireland Ltd. All rights reserved.

Coupling 3D visualisation to qualitative assessment of built environment designs

Geographical information systems (GIS) coupled to 3D visualisation technology is an emerging tool for urban planning and landscape design applications. The utility of 3D GIS for realistically visualising the built environment and proposed development scenarios is much advocated in the literature. Planners assess the merits of proposed changes using visual impact assessment (VIA). We have used Arcview GIS and visualisation software: called PolyTRIM from the University of Toronto, Centre for Landscape Research (CLR) to create a 3D scene for the entrance to a University campus. The paper investigates the thesis that to facilitate VIA in planning and design requires not only visualisation, but also a structured evaluation technique (Delphi) to arbitrate the decision-making process. (C) 2001 Elsevier Science B.V. All rights reserved.

Adjustment to chronic obstructive pulmonary disease: the importance of psychological factors

Research has indicated a weak relationship between the degree of physical problems and quality of life in patients with chronic obstructive pulmonary disease (COPD). The importance of adaptive psychological functioning to maintain optimum quality of life has long been recognized, but there is a lack of empirical evidence concerning the nature of psychological factors involved in adjustment to COPD. Ninety-two males completed questionnaires to determine their coping strategies, levels of self-efficacy of symptom management and social support. Adjustment was measured in terms of depression, anxiety and quality of life. Symptom severity, socioeconomic status, duration of disease and age, which have been demonstrated to be of consequence in COPD, were used as control variables in hierarchical multiple regression analyses. Higher levels of catastrophic withdrawal coping strategies and lower levels of self-efficacy of symptom management were associated with higher levels of depression, anxiety and a reduced quality of life. Higher levels of positive social support were linked to lower levels of depression and anxiety, while higher levels of negative social support were linked to higher levels of depression and anxiety. To maximize quality of life in patients with chronic obstructive pulmonary disease, psychological factors need to be carefully assessed and addressed.

Building a bicycle suitability map for Coimbra

The adoption of faster modes of transportation (mainly the private car) has changed profoundly the spatial organisation of cities. The increase in distance covered due to increased speed of travel and to urban sprawl leads to an increase in energy consumption, being the transportation sector a huge consumer responsible for 61.5% of total world oil consumption and a global final energy consumption of 31.6% in EU-27 (2007). Due to unsustainable transportation conditions, many cities suffer from congestion and various other traffic problems. Such situations get worse with solutions mostly seen in the development of new infrastructure for motorized modes of transportation, and construction of car parking structures. The bicycle, considered the most efficient among all modes of transportation including walking, is a travel mode that can be adopted in most cities contributing for urban sustainability given the associated environmental, economic and social advantages. In many nations a large number of policy initiatives have focused on discouraging the use of private cars, encouraging the use of sustainable modes of transportation, like public transportation and other forms such as bicycling. Given the importance of developing initiatives that favour the use of bicycle as an urban transportation mode, an analysis of city suitability, including distances and slopes of street network, is crucial in order to help decision-makers to plan the city for bicycle. In this research Geographical Information Systems (GIS) technology was used for this purpose and some results are presented concerning the city of Coimbra.

Multi-attribute classification of housing conservation status in urban regeneration actions

Urban regeneration is more and more a “universal issue” and a crucial factor in the new trends of urban planning. It is no longer only an area of study and research; it became part of new urban and housing policies. Urban regeneration involves complex decisions as a consequence of the multiple dimensions of the problems that include special technical requirements, safety concerns, socio-economic, environmental, aesthetic, and political impacts, among others. This multi-dimensional nature of urban regeneration projects and their large capital investments justify the development and use of state-of-the-art decision support methodologies to assist decision makers. This research focuses on the development of a multi-attribute approach for the evaluation of building conservation status in urban regeneration projects, thus supporting decision makers in their analysis of the problem and in the definition of strategies and priorities of intervention. The methods presented can be embedded into a Geographical Information System for visualization of results. A real-world case study was used to test the methodology, whose results are also presented.

Estudo da qualidade organizacional da unidade de rastreio da retinopatia diabética do Alentejo central: projecto de intervenção comunitária em saúde

Mestrado em Intervenção Sócio-Organizacional na Saúde - Área de especialização: Políticas de Gestão e Administração dos Serviços de Saúde.

ANN-Based LMP forecasting in a distribution network with large penetration of DG

In recent years, power systems have experienced many changes in their paradigm. The introduction of new players in the management of distributed generation leads to the decentralization of control and decision-making, so that each player is able to play in the market environment. In the new context, it will be very relevant that aggregator players allow midsize, small and micro players to act in a competitive environment. In order to achieve their objectives, virtual power players and single players are required to optimize their energy resource management process. To achieve this, it is essential to have financial resources capable of providing access to appropriate decision support tools. As small players have difficulties in having access to such tools, it is necessary that these players can benefit from alternative methodologies to support their decisions. This paper presents a methodology, based on Artificial Neural Networks (ANN), and intended to support smaller players. In this case the present methodology uses a training set that is created using energy resource scheduling solutions obtained using a mixed-integer linear programming (MIP) approach as the reference optimization methodology. The trained network is used to obtain locational marginal prices in a distribution network. The main goal of the paper is to verify the accuracy of the ANN based approach. Moreover, the use of a single ANN is compared with the use of two or more ANN to forecast the locational marginal price.