PREVENTION OF CHILLING INJURY IN 'TOMMY ATKINS' MANGOES PREVIOUSLY STORED AT 5 ºC, USING HEAT TREATMENT AND RADIATION UV (UV-C)

ABSTRACT The objective of this study was to evaluate the effect of heat treatment and ultraviolet radiation (UV-C) in the prevention of chilling injury in mangoes cv. Tommy Atkins previously stored or not under injury condition after their transference to ambient condition. Fruits were divided into groups: two were hydrothermally treated (46.1 ºC/90 min; 55 ºC/5 min) and two were exposed to UV-C radiation (1.14 kJ m-2; 2.28 kJ m-2). These groups were stored under chilling injury conditions (5 ºC for 14 days), as established in preliminary tests. Other untreated groups were stored at 12 ºC or 5 ºC. After the storage period, they were transferred to ambient conditions (21.9 ºC; 55% RH) and the quality was evaluated. All the data were submitted to multivariate analysis as the tool to verify the simultaneous effect of the treatments under the quality parameters. The multivariate analysis indicated that the hydrothermal treatments at 46.1 °C/90 min and 55 °C/5 min and the UV-C radiation at doses of 1.14 kJ m-2 and 2.28 kJ m-2 were effective in minimized the symptoms of chilling injury in mangoes ‘Tommy Atkins’ stored at 5 °C for 14 days. However, after their transference to environmental condition at 21.9 °C, only the UV-C kept this control, especially at a dose of 2.28 kJ m-2. This treatment did not prevent the development of the characteristic color or affected the normal ripening and allowed the conservation of fruit for a period of 14 days at 5 °C, plus seven days of storage at environmental condition, which corresponds to the shipping transportation plus the time for sale.

Performance of diagnostic centers in the classification of opportunistic screening mammograms from the Brazilian public health system (SUS)

Objective To evaluate the performance of diagnostic centers in the classification of mammography reports from an opportunistic screening undertaken by the Brazilian public health system (SUS) in the municipality of Goiânia, GO, Brazil in 2010. Materials and Methods The present ecological study analyzed data reported to the Sistema de Informação do Controle do Câncer de Mama (SISMAMA) (Breast Cancer Management Information System) by diagnostic centers involved in the mammographic screening developed by the SUS. Based on the frequency of mammograms per BI-RADS® category and on the limits established for the present study, the authors have calculated the rate of conformity for each diagnostic center. Diagnostic centers with equal rates of conformity were considered as having equal performance. Results Fifteen diagnostic centers performed mammographic studies for SUS and reported 31,198 screening mammograms. The performance of the diagnostic centers concerning BI-RADS classification has demonstrated that none of them was in conformity for all categories, one center presented conformity in five categories, two centers, in four categories, three centers, in three categories, two centers, in two categories, four centers, in one category, and three centers with no conformity. Conclusion The results of the present study demonstrate unevenness in the diagnostic centers performance in the classification of mammograms reported to SISMAMA from the opportunistic screening undertaken by SUS.

Data mining techniques for identification of spectrally homogeneous areas using NDVI temporal profiles of soybean crop

The aim of this study was to group temporal profiles of 10-day composites NDVI product by similarity, which was obtained by the SPOT Vegetation sensor, for municipalities with high soybean production in the state of Paraná, Brazil, in the 2005/2006 cropping season. Data mining is a valuable tool that allows extracting knowledge from a database, identifying valid, new, potentially useful and understandable patterns. Therefore, it was used the methods for clusters generation by means of the algorithms K-Means, MAXVER and DBSCAN, implemented in the WEKA software package. Clusters were created based on the average temporal profiles of NDVI of the 277 municipalities with high soybean production in the state and the best results were found with the K-Means algorithm, grouping the municipalities into six clusters, considering the period from the beginning of October until the end of March, which is equivalent to the crop vegetative cycle. Half of the generated clusters presented spectro-temporal pattern, a characteristic of soybeans and were mostly under the soybean belt in the state of Paraná, which shows good results that were obtained with the proposed methodology as for identification of homogeneous areas. These results will be useful for the creation of regional soybean "masks" to estimate the planted area for this crop.

Prediction of free-stall occupancy rate in dairycattle barns through fuzzy sets

The goal of this study was to develop a fuzzy model to predict the occupancy rate of free-stalls facilities of dairy cattle, aiding to optimize the design of projects. The following input variables were defined for the development of the fuzzy system: dry bulb temperature (Tdb, °C), wet bulb temperature (Twb, °C) and black globe temperature (Tbg, °C). Based on the input variables, the fuzzy system predicts the occupancy rate (OR, %) of dairy cattle in free-stall barns. For the model validation, data collecting were conducted on the facilities of the Intensive System of Milk Production (SIPL), in the Dairy Cattle National Research Center (CNPGL) of Embrapa. The OR values, estimated by the fuzzy system, presented values of average standard deviation of 3.93%, indicating low rate of errors in the simulation. Simulated and measured results were statistically equal (P>0.05, t Test). After validating the proposed model, the average percentage of correct answers for the simulated data was 89.7%. Therefore, the fuzzy system developed for the occupancy rate prediction of free-stalls facilities for dairy cattle allowed a realistic prediction of stalls occupancy rate, allowing the planning and design of free-stall barns.

Fuzzy modeling of broiler performance, raised from 1 to 21 days, subject to heat stress

ABSTRACT Given the need to obtain systems to better control broiler production environment, we performed an experiment with broilers from 1 to 21 days, which were submitted to different intensities and air temperature durations in conditioned wind tunnels and the results were used for validation of afuzzy model. The model was developed using as input variables: duration of heat stress (days), dry bulb air temperature (°C) and as output variable: feed intake (g) weight gain (g) and feed conversion (g.g-1). The inference method used was Mamdani, 20 rules have been prepared and the defuzzification technique used was the Center of Gravity. A satisfactory efficiency in determining productive responses is evidenced in the results obtained in the model simulation, when compared with the experimental data, where R2 values ​​calculated for feed intake, weight gain and feed conversion were 0.998, 0.981 and 0.980, respectively.

DNA fingerprinting of Mycobacterium tuberculosis from patients with and without AIDS in Rio de Janeiro

Isolates of Mycobacterium tuberculosis derived from patients with AIDS from a single hospital in Rio de Janeiro were typed using a standardized RFLP technique detecting IS6110 polymorphism. Nineteen isolates were obtained from 15 different patients. Eleven distinct IS6110 patterns were found, with 4 banding patterns shared by 2 patients. The clustering value of 53% was much higher in comparison with clustering of M. tuberculosis strains from TB patients without clinical signs for HIV infection from randomly selected health centers. We present these results as preliminary data on M. tuberculosis strain polymorphism in Brazil and on the higher risk for recent transmission amongst patients with AIDS

Effect of race, genetic population structure, and genetic models in two-locus association studies: clustering of functional renin-angiotensin system gene variants in hypertension association studies

Previous genetic association studies have overlooked the potential for biased results when analyzing different population structures in ethnically diverse populations. The purpose of the present study was to quantify this bias in two-locus association studies conducted on an admixtured urban population. We studied the genetic structure distribution of angiotensin-converting enzyme insertion/deletion (ACE I/D) and angiotensinogen methionine/threonine (M/T) polymorphisms in 382 subjects from three subgroups in a highly admixtured urban population. Group I included 150 white subjects; group II, 142 mulatto subjects, and group III, 90 black subjects. We conducted sample size simulation studies using these data in different genetic models of gene action and interaction and used genetic distance calculation algorithms to help determine the population structure for the studied loci. Our results showed a statistically different population structure distribution of both ACE I/D (P = 0.02, OR = 1.56, 95% CI = 1.05-2.33 for the D allele, white versus black subgroup) and angiotensinogen M/T polymorphism (P = 0.007, OR = 1.71, 95% CI = 1.14-2.58 for the T allele, white versus black subgroup). Different sample sizes are predicted to be determinant of the power to detect a given genotypic association with a particular phenotype when conducting two-locus association studies in admixtured populations. In addition, the postulated genetic model is also a major determinant of the power to detect any association in a given sample size. The present simulation study helped to demonstrate the complex interrelation among ethnicity, power of the association, and the postulated genetic model of action of a particular allele in the context of clustering studies. This information is essential for the correct planning and interpretation of future association studies conducted on this population.

Clinical signs of pneumonia in children: association with and prediction of diagnosis by fuzzy sets theory

The present study compares the performance of stochastic and fuzzy models for the analysis of the relationship between clinical signs and diagnosis. Data obtained for 153 children concerning diagnosis (pneumonia, other non-pneumonia diseases, absence of disease) and seven clinical signs were divided into two samples, one for analysis and other for validation. The former was used to derive relations by multi-discriminant analysis (MDA) and by fuzzy max-min compositions (fuzzy), and the latter was used to assess the predictions drawn from each type of relation. MDA and fuzzy were closely similar in terms of prediction, with correct allocation of 75.7 to 78.3% of patients in the validation sample, and displaying only a single instance of disagreement: a patient with low level of toxemia was mistaken as not diseased by MDA and correctly taken as somehow ill by fuzzy. Concerning relations, each method provided different information, each revealing different aspects of the relations between clinical signs and diagnoses. Both methods agreed on pointing X-ray, dyspnea, and auscultation as better related with pneumonia, but only fuzzy was able to detect relations of heart rate, body temperature, toxemia and respiratory rate with pneumonia. Moreover, only fuzzy was able to detect a relationship between heart rate and absence of disease, which allowed the detection of six malnourished children whose diagnoses as healthy are, indeed, disputable. The conclusion is that even though fuzzy sets theory might not improve prediction, it certainly does enhance clinical knowledge since it detects relationships not visible to stochastic models.

Estimating the average length of hospitalization due to pneumonia: a fuzzy approach

Exposure to air pollutants is associated with hospitalizations due to pneumonia in children. We hypothesized the length of hospitalization due to pneumonia may be dependent on air pollutant concentrations. Therefore, we built a computational model using fuzzy logic tools to predict the mean time of hospitalization due to pneumonia in children living in São José dos Campos, SP, Brazil. The model was built with four inputs related to pollutant concentrations and effective temperature, and the output was related to the mean length of hospitalization. Each input had two membership functions and the output had four membership functions, generating 16 rules. The model was validated against real data, and a receiver operating characteristic (ROC) curve was constructed to evaluate model performance. The values predicted by the model were significantly correlated with real data. Sulfur dioxide and particulate matter significantly predicted the mean length of hospitalization in lags 0, 1, and 2. This model can contribute to the care provided to children with pneumonia.