Seasonal changes in the diving performance of the bimodally respiring freshwater turtle Rheodytes leukops in a natural setting

The objective of this study was to investigate how seasonally fluctuating environmental conditions influence the diving performance of the highly aquatic, bimodally respiring turtle Rheodytes leukops in a natural setting. Over four consecutive seasons (Austral autumn 2000 to summer 2001), the diving behaviour of adult turtles was recorded via pressure-sensitive time-depth recorders within Marlborough Creek, central Queensland, Australia. Short surfacing intervals recorded for R. leukops in winter suggest that the species utilizes aquatic respiration as an overwintering strategy to prevent the development of a metabolic acidosis during the long inactive dives observed during the season. As water temperature increases and aquatic P-O 2 decreases, R. leukops switches from facultative to obligate air-breathing, presumably because of the increased metabolic cost associated with aquatic respiration under summer conditions. Increases in mean surfacing time from winter to spring and summer are attributed to seasonal changes in behaviour possibly associated with foraging rather than to the physiological state of the turtle, given that no difference in median surfacing time among seasons was observed.

On measuring quality of a probabilistic commodity forecast for a system that incorporates seasonal climate forecasts

Regional commodity forecasts are being used increasingly in agricultural industries to enhance their risk management and decision-making processes. These commodity forecasts are probabilistic in nature and are often integrated with a seasonal climate forecast system. The climate forecast system is based on a subset of analogue years drawn from the full climatological distribution. In this study we sought to measure forecast quality for such an integrated system. We investigated the quality of a commodity (i.e. wheat and sugar) forecast based on a subset of analogue years in relation to a standard reference forecast based on the full climatological set. We derived three key dimensions of forecast quality for such probabilistic forecasts: reliability, distribution shift, and change in dispersion. A measure of reliability was required to ensure no bias in the forecast distribution. This was assessed via the slope of the reliability plot, which was derived from examination of probability levels of forecasts and associated frequencies of realizations. The other two dimensions related to changes in features of the forecast distribution relative to the reference distribution. The relationship of 13 published accuracy/skill measures to these dimensions of forecast quality was assessed using principal component analysis in case studies of commodity forecasting using seasonal climate forecasting for the wheat and sugar industries in Australia. There were two orthogonal dimensions of forecast quality: one associated with distribution shift relative to the reference distribution and the other associated with relative distribution dispersion. Although the conventional quality measures aligned with these dimensions, none measured both adequately. We conclude that a multi-dimensional approach to assessment of forecast quality is required and that simple measures of reliability, distribution shift, and change in dispersion provide a means for such assessment. The analysis presented was also relevant to measuring quality of probabilistic seasonal climate forecasting systems. The importance of retaining a focus on the probabilistic nature of the forecast and avoiding simplifying, but erroneous, distortions was discussed in relation to applying this new forecast quality assessment paradigm to seasonal climate forecasts. Copyright (K) 2003 Royal Meteorological Society.

The social adjustment of patients with schizophrenia: implications to the mental health policy in Brazil

A sample (n=124) of schizophrenic patients from a defined catchment area of the city os S.Paulo, Brazil, who had been consecutively admitted to hospital, was assessed for psychopathological status and social adjustment levels. Sociodemographic, socio-economic and occupational characteristics were recorded: almost 30% of the subjects had no occupation and received no social benefit, more than two-thirds had a monthly per capita income of US$ 100.00 or less. Sixty-five percent presented with Schneiderian firstrank symptoms. Nearly half the sample showed poor or very poor social adjustment in the month prior to admission. The most affected areas of social functioning were participation in the household activities, work and social withdrawal. The current mental health policy of promoting extra-mural care as an alternative to the previous hospital-based model will then mean the investment in a network of new community-based services, that give effective treatment and support to patients and their families. The need of further research into the current picture of mental disorders in the country is stressed.

Family expectation, social adjustment and gender differences in a sample of schizophrenic patients

A case series to study factors related to family expectation regarding schizophrenic patients was conducted in an out-patient setting in the city of S. Paulo, Brazil. Patients diagnosed as presenting schizophrenia by the ICD 9th Edition and having had the disease for more than four years were included in the study. Family Expectation was measured by the difference between the Katz Adjustment Scale (R2 and R3) scores based on the relative's expectation and the socially expected activities of the patient (Discrepancy Score), and social adjustment was given by the DSM-III-R Global Assessment Scale (GAS) . Outcome assessments were made independently, and 44 patients comprised the sample (25 males and 19 females). The Discrepancy mean score was twice as high for males as for females (p < 0.02), and there was an inverse relationship between the discrepancy score and social adjustment (r =-0.46, p < 0.001). Moreover, sex and social adjustment exerted independent effects on the discrepancy score when age, age at onset and number of psychiatric admissions were controlled by means of a multiple regression technique. There was an interaction between sex and social adjustment, the inverse relationship between social adjustment and discrepancy score being more pronounced for males. These findings are discussed in the light of the potential association between the family environment, gender and social adjustment of schizophrenic patients, and the need for further research, i.e. ethnographic accounts of interactions between patient and relatives sharing households particularly in less developed countries.

Seasonal variation of total particulate matter and children respiratory diseases at Lisbon primary schools using passive methods

In this work, 14 primary schools of Lisbon city, Portugal, followed a questionnaire of the ISAAC - International Study of Asthma and Allergies in Childhood Program, in 2009/2010. The questionnaire contained questions to identify children with respiratory diseases (wheeze, asthma and rhinitis). Total particulate matter (TPM) was passively collected inside two classrooms of each of 14 primary schools. Two types of filter matrices were used to collect TPM: Millipore (IsoporeTM) polycarbonate and quartz. Three campaigns were selected for the measurement of TPM: Spring, Autumn and Winter. The highest difference between the two types of filters is that the mass of collected particles was higher in quartz filters than in polycarbonate filters, even if their correlation is excellent. The highest TPM depositions occurred between October 2009 and March 2010, when related with rhinitis proportion. Rhinitis was found to be related to TPM when the data were grouped seasonally and averaged for all the schools. For the data of 2006/2007, the seasonal variation was found to be related to outdoor particle deposition (below 10 μm).

Occurrence of suicide and seasonal variation

OBJECTIVE: To review the estimated suicide rates for the Region Metropolitan, the main socio-political center in Chile, for the period 1979-1994, and to determine whether they follow a seasonal pattern. METHOD: Data available for the period 1979-94 at the Forensic Services in Chile was analyzed using ANOVA. RESULTS: It was register 5.386 suicides. While the "warm" months (October, November, December & January) concentrated 39.0% of cases, the so called "cold" months reported 28,7%. This contrast is made even clearer by the month-to-month analysis, showing the highest suicide rate in December (10.9%) against the lowest rate in June (7.0%). Further statistical analysis revealed these differences to be significant. CONCLUSION: The study shows that in Chile, representing as it does the Southern Hemisphere, the suicide rates tend to present a seasonal variation as has elsewhere been determined for in the North Hemisphere.

Criação de valor, gestão de risco e as medidas de performance ajustadas ao risco: aplicação do RAROC - Risk Adjustment Return on Capital - ao grupo crédito agrícola

Mestrado em Contabilidade e Gestão das Instituições Financeiras

Superefficiency and Multiplier Adjustment in Data Envelopment Analysis

Copyright © 2013 Springer Netherlands.

Multiplier adjustment in data envelopment analysis

V Congreso de Eficiencia y Productividad EFIUCO, Córdoba, 19-20 Mayo 2011.

Neonatal mortality: description and effect of hospital of birth after risk adjustment

OBJECTIVE: To assess the effect of hospital of birth on neonatal mortality. METHODS: A birth cohort study was carried out in Pelotas, Southern Brazil, in 2004. All hospital births were assessed by daily visits to all maternity hospitals and 4558 deliveries were included in the study. Mothers were interviewed regarding potential risk factors. Deaths were monitored through regular visits to hospitals, cemeteries and register offices. Two independent pediatricians established the underlying cause of death based on information obtained from medical records and home visits to parents. Logistic regression was used to estimate the effect of hospital of birth, controlling for confounders related to maternal and newborn characteristics, according to a conceptual model. RESULTS: Neonatal mortality rate was 12.7‰ and it was highly influenced by birthweight, gestational age, and socioeconomic variables. Immaturity was responsible for 65% of neonatal deaths, followed by congenital anomalies, infections and intrapartum asphyxia. Adjusting for maternal characteristics, a three-fold increase in neonatal mortality was seen between similar complexity hospitals. The effect of hospital remained, though lower, after controlling for newborn characteristics. CONCLUSIONS: Neonatal mortality was high, mainly related to immaturity, and varied significantly across maternity hospitals. Further investigations comparing delivery care practices across hospitals are needed to better understand NMR variation and to develop strategies for neonatal mortality reduction.

Comorbidity adjustment index for the international classification of diseases, 10

OBJECTIVE: To develop a Charlson-like comorbidity index based on clinical conditions and weights of the original Charlson comorbidity index. METHODS: Clinical conditions and weights were adapted from the International Classification of Diseases, 10th revision and applied to a single hospital admission diagnosis. The study included 3,733 patients over 18 years of age who were admitted to a public general hospital in the city of Rio de Janeiro, southeast Brazil, between Jan 2001 and Jan 2003. The index distribution was analyzed by gender, type of admission, blood transfusion, intensive care unit admission, age and length of hospital stay. Two logistic regression models were developed to predict in-hospital mortality including: a) the aforementioned variables and the risk-adjustment index (full model); and b) the risk-adjustment index and patient's age (reduced model). RESULTS: Of all patients analyzed, 22.3% had risk scores >1, and their mortality rate was 4.5% (66.0% of them had scores >1). Except for gender and type of admission, all variables were retained in the logistic regression. The models including the developed risk index had an area under the receiver operating characteristic curve of 0.86 (full model), and 0.76 (reduced model). Each unit increase in the risk score was associated with nearly 50% increase in the odds of in-hospital death. CONCLUSIONS: The risk index developed was able to effectively discriminate the odds of in-hospital death which can be useful when limited information is available from hospital databases.

Seasonal variation in hospitalizations due to heart failure in Niterói city, Southeastern Brazil

The objective of the study was to describe seasonality of hospitalizations for heart failure in tropical climate as it has been described in cold climates. Seasonal Auto-regressive Integrated Moving-Average model was applied to time-series data of heart failure hospitalizations between 1996 and 2004 in Niteroi (Southeastern Brazil), collected from the Brazilian National Health Service Database. The standard seasonal variation was obtained by means of moving-average filtering and averaging data. The lowest and the highest annual hospital admissions were 507 (1997) and 849 (2002), respectively; the lowest and the highest monthly rates were 419 (December) and 681 (October), respectively. Peak admission rates were seen during the fall and winter. Although weak, the seasonality observed indicates that slight variations result in increased hospitalizations for heart failure.

A fuzzified systematic adjustment of the robotic Darwinian PSO

The Darwinian Particle Swarm Optimization (DPSO) is an evolutionary algorithm that extends the Particle Swarm Optimization using natural selection to enhance the ability to escape from sub-optimal solutions. An extension of the DPSO to multi-robot applications has been recently proposed and denoted as Robotic Darwinian PSO (RDPSO), benefiting from the dynamical partitioning of the whole population of robots, hence decreasing the amount of required information exchange among robots. This paper further extends the previously proposed algorithm adapting the behavior of robots based on a set of context-based evaluation metrics. Those metrics are then used as inputs of a fuzzy system so as to systematically adjust the RDPSO parameters (i.e., outputs of the fuzzy system), thus improving its convergence rate, susceptibility to obstacles and communication constraints. The adapted RDPSO is evaluated in groups of physical robots, being further explored using larger populations of simulated mobile robots within a larger scenario.