Use of gamma radiation and artificial neural network techniques to monitor characteristics of polyduct transport of petroleum by-products.

This study presents a methodology based on the dual-mode gamma densitometry technique in combination with artificial neural networks to simultaneously determine type and quantity of four different fluids (Gasoline, Glycerol, Kerosene and Fuel Oil) to assist operators of a fluid transport system in pipelines commonly found in the petrochemical industry, as it is necessary to continuously monitor information about the fluids being transferred. The detection system is composed of a 661.657 keV (137Cs) gamma-ray emitting source and two NaI(Tl) scintillation detectors to record transmitted and scattered photons. The information recorded in both detectors was directly applied as input data for the artificial neural networks. The proposed intelligent system consists of three artificial neural networks capable of predicting the fluid volume percentages (purity level) with 94.6% of all data with errors less than 5% and MRE of 1.12%, as well as identifying the pair of fluids moving in the pipeline with 95.9% accuracy.

Hashtag bone: detrimental effects on bone contrast with metabolic benefits one and five years after Roux-en-Y gastric bypass.

Bone loss is a potential adverse consequence of rapid and sustained weight loss after bariatric surgery. The aim of the present study was to evaluate the bone mass, body fat distribution, and metabolic parameters in women submitted to Roux-en-Y gastric bypass (RYGB). The study included the following three groups: one group of lean women (control [C] group) and two groups of obese women, one evaluated one year (B1) and the other five years (B5) after RYGB. Dual-energy X-ray absorptiometry and magnetic resonance imaging were used to determine bone mineral density (BMD; lumbar spine, total hip, and femoral neck) and abdominal fat content (subcutaneous [SAT] and visceral [VAT] adipose tissues, and intrahepatic lipids [IHL]). The BMD/body mass index ratio was lower in the B5 compared with the C group at all sites. Serum C-terminal telopeptide of type I collagen (CTX) levels were higher in the B1 and B5 groups compared with the C group. Individuals submitted to RYGB showed greater SAT but similar VAT and IHL values compared with those in the C group. However, the B5 group had higher mean parathyroid hormone levels compared with the other two groups. Individuals submitted to RYGB presented increased levels of CTX and low BMD for body weight than those in the C group, suggesting that bone catabolism is a persistent alteration associated with RYGB. In conclusion, the long-lasting metabolic benefits obtained with RYGB in obesity are counterbalanced by a persistent catabolic effect of the procedure on bone and mineral metabolism.

Optimization of a flow regime identification system and prediction of volume fractions in three-phase systems using gamma-rays and artificial neural network.

This study presents a method based on gamma-ray densitometry using only one multilayer perceptron artificial neural network (ANN) to identify flow regime and predict volume fraction of gas, water, and oil in multiphase flow, simultaneously, making the prediction independent of the flow regime. Two NaI(Tl) detectors to record the transmission and scattering beams and a source with two gamma-ray energies comprise the detection geometry. The spectra of gamma-ray recorded by both detectors were chosen as ANN input data. Stratified, homogeneous, and annular flow regimes with (5 to 95%) various volume fractions were simulated by the MCNP6 code, in order to obtain an adequate data set for training and assessing the generalization capacity of ANN. All three regimes were correctly distinguished for 98% of the investigated patterns and the volume fraction in multiphase systems was predicted with a relative error of less than 5% for the gas and water phases.

The comparison of different multilayer perceptron and General Regression Neural Networks for volume fraction prediction using MCNPX code.

This research presents a methodology for volume fraction predictions in water-gas-oil multiphase systems based on gamma-ray densitometry and artificial neural networks. The simulated geometry uses a dual-energy gamma-ray source and dual-modality (transmitted and scattered beams). The Am-241 and Cs-137 sources and two NaI(Tl) detectors have been used in this methodology. Different data from the pulse height distribution were used to train the artificial neural network to evaluate the volume fraction prediction. The MCNPX code has been used to develop the theoretical model for stratified regime and to provide data for the artificial neural network. 5-layers feed-forward multilayer perceptron using backpropagation training algorithm and General Regression Neural Networks has been used with different designs. The artificial neural network design that presented the best results of volume fraction prediction has a mean relative error below 2.0%.

Density prediction for petroleum and derivatives by gamma-ray attenuation and artificial neural networks.

This work presents a new methodology for density prediction of petroleum and derivatives for products' monitoring application. The approach is based on pulse height distribution pattern recognition by means of an artificial neural network (ANN). The detection system uses appropriate broad beam geometry, comprised of a (137)Cs gamma-ray source and a NaI(Tl) detector diametrically positioned on the other side of the pipe in order measure the transmitted beam. Theoretical models for different materials have been developed using MCNP-X code, which was also used to provide training, test and validation data for the ANN. 88 simulations have been carried out, with density ranging from 0.55 to 1.26gcm(-3) in order to cover the most practical situations. Validation tests have included different patterns from those used in the ANN training phase. The results show that the proposed approach may be successfully applied for prediction of density for these types of materials. The density can be automatically predicted without a prior knowledge of the actual material composition.

Role of UCP2 polymorphisms on dietary intake of obese patients who underwent bariatric surgery.

Uncoupling protein 2 ( UCP2 ) plays an important role in body weight and energy metabolism and may be related to the control of food consumption. This study aimed to investigate the contribution of UCP2 gene variants on the dietary intake on a population after bariatric surgery. This study enrolled 150 obese patients (body mass index ≥ 35kg m(-2) ) who submitted to Roux-en-Y gastric bypass. Weight (kg), BMI (kg m(-2) ), energy (kcal d(-1) ) and macronutrients intake (g d(-1) ) of preoperative and 1-year postoperative period were collected from medical records. Ala55Val and -866G>A polymorphisms in the UCP2 gene were genotyped through allelic discrimination method in real-time polymerase chain reaction using the TaqMan pre-designed SNP Genotyping Assays kits. Hardy-Weinberg equilibrium, t-test and regression models were performed in statistical analysis (P<0.05).We found an allelic frequency of 0.44 for allele Val and 0.41 for allele A. In the postoperative period, patients with at least one rare allele for polymorphisms and with at least one rare allele for both polymorphisms together (haplotype) present a greater energy and carbohydrate intake, even after adjusting for gender, age and weight. Genetic variants in UCP2 gene were associated with the dietary consumption after Roux-En-Y gastric bypass.

[Giant cell pneumonia. Complication in one case of acute lymphoblastic leukemia (author's transl)]. / Neumonía de células gigantes. Complicación de un caso de leucosis linfoblástica aguda.

A patient suffering from acute lymphoblastic leukemia, in complete remission for two years, is treated for haematologic relapse with V.P.D. and C.O.A.P. consolidation. After this treatment, develops tiredness, sleepiness, a slight fever and cough, dying some days after, of interstitial pneumonia. Post-mortem anatomic-pathological studies, show giant cell multinucleated pneumopathia, with intranuclear inclusions bodies, that in ultrastructural level resembles paramyxovirus. When this complication took place, the patient had a brother with measles, but he hasn't, the typical symptomatology of said virus disease. According to Siegel, authors point out the frequency of death due to interstitial pneumonia as a complication caused by measles in immunodeficient patients, remarking the importance of an immediate diagnosis and its' prophylaxis.