Laparoscopy for the impalpable testes. Initial experience of one center

Endoscopic treatment of acute pancreatitis has been proposed in different conditions: acute biliary pancreatitis, pancreatitis related to pancreas divisum or in case of pseudocysts. The efficacy of such endoscopic procedure is discussed.     

Development of artificial neural networks for real time, in situ ellipsometry data reduction

Development of real time in situ monitoring and control of thin film depositions using ellipsometry requires both data acquisition and processing to be rapid. Present speeds of measurement and computation of basic parameters, Ψ and Δ, are sufficient for data acquisition which is essentially real time. However, computation of film parameters, such as thickness and optical properties, generally cannot keep up with the incoming data and must be performed in a batch mode after the deposition.

This work describes the development of enhanced, high speed data reduction algorithms using artificial neural networks (ANN). The networks are trained using computed data and subsequently give values of film parameters in the millisecond time regime. The ANN outputs are used as initial estimates in a variably damped least squares algorithm for accuracy improvement. The combination of these two algorithms provides very accurate solutions in 75 ms per point on a DEC VAX 8800 multiprocessor system running at a combined 12 Mips. This speed is suitable for real time film monitoring and control for growth rates up to 10 nm per second. Results for fixed angle of incidence, single wavelength, in situ data for Ni deposited on BK7 substrates are presented.     

A kinetic study on the reduction of manganese III in presence of citric acid

The rate of reduction of manganese III stabilised by citric acid under variable conditions of Mn(III) concentration, ionic strength, pH and temperature in buffered media was found to obey a second order rate equation, first order with respect to Mn(III) autocatalysed by Mn(II). The reduction was found to proceed to an equilibrium value. The observed rate constants were found to follow a linear relationship with hydrogen ion concentration. Interpretation of results is based on the assumption that there are two reducible species in equilibrium; the aquocomplex and its hydrolysed form. A reaction mechanism is proposed to account for the experimental results. The overall energy (ΔE) and entropy (ΔS) of activation are compared with those for the reduction of Mn(III) in presence of other organic substrates.     

Microfluidic study of surfactant flooding of heavy oil in layered porous media containing fractures

Surfactant injection is a promising method for enhanced oil recovery (EOR) due to its effective micro-displacement mechanisms. However, understanding the interaction of a surfactant solution with heavy oil in porous media is neither straightforward nor well understood, particularly in heterogeneous systems. By enabling in-situ real-time monitoring of flow transport, microfluidic studies have provided novel insights into the underlying multiphase physics of flow at the pore scale. This paper examines the two-phase displacement efficiency of a new surfactant in layered–fractured porous microfluidic patterns, a topic seldom discussed in the literature. To evaluate the performance of the proposed surfactant, we considered several heterogeneous media with varying layer and fracture geometrical characteristics, quantifying displacement efficiency for each case. Based on the analysis of pore-scale snapshots, it was inferred that the primary mechanisms responsible for EOR during surfactant flooding into heavy oil include pore wall transportation, emulsifications, the deformation of residual oil, inter-pore or intra-pore bridging, and wettability alteration. Macroscopic displacement experiments revealed that the width of the swept area from surfactant injection significantly exceeded that of water injection, resulting in a substantially higher oil recovery. Furthermore, it was demonstrated that the direction of fluid flow in relation to fracture orientation plays a critical role in the dynamics of surfactant solution movement and, consequently, the ultimate oil production.     

Applying MLP-ANN as a novel and accurate method to estimate gas density

In the gas industries, to increase the degree of accuracy of calculation and estimation in different processes, the importance of accurate prediction of gas properties is highlighted. The gas density, as one of the key properties in gas engineering, has a major effect in calculations. So, in the present paper, multi-layer perceptron artificial neural network (MLP-ANN) was used to predict the gas density based on molecular weight, critical pressure and critical temperature of gas, pressure, and temperature. To this end, a total number of 1240 reliable data of gas density were gathered from literature for the training and testing phases. The MLP-ANN outputs were compared with the actual data in different manners, such as statistical and graphical analyses. The coefficient of determination (R²), average absolute relative deviation (AARD), and root mean squared error (RMSE) for overall process were calculated as 1, 0.0088444, and 0.0259, respectively. The determined parameters and graphical analysis showed that the MLP-ANN has great potential and high degree of accuracy in gas density estimation.     

Development of a novel ANFIS-GA method for investigation of effect of inhibitors on asphaltene precipitation

Asphaltene precipitation and deposition in different parts of petroleum industry increase considerably cost and problems in oil production. Due to these facts controlling asphaltene precipitation becomes one of valuable topics for research in petroleum engineering. Utilization of Asphaltene inhibitors is known as one of the dominant methods for controlling asphaltene precipitation so in this paper Adaptive neuro-fuzzy inference system (ANFIS) is joint with Genetic Algorithm (GA) to study effectiveness of asphaltene inhibitors on precipitation in terms of oil and inhibitors properties. In order to prepare and evaluate the ANFIS-GA algorithm, some reliable experimental data were gathered. The obtained results from the comparison shows the coefficient of determination (R²) for training and testing phases are 0.98804 and 0.9916 respectively. The determined indexes and graphical comparisons expresses that ANFIS-GA has enough accuracy and potential to estimate effectiveness of inhibitors on asphaltene precipitation reductions.     

Radiation pattern design of photonic crystal LED optimized by using multi-objective grey wolf optimizer

Photonic Network Communications - This paper proposes an effective method for shaping the radiation pattern intensity of photonic crystal (PhC) light-emitting diode (LED). In this method, the...     

Effect of Co addition on microstructural and mechanical properties of WC–B4C–SiC composites

In this study, the effect of Co addition on microstructural and mechanical properties of WC-B₄C–SiC composites sintered by spark plasma sintering (SPS) method was investigated. For this purpose, three batches of WC-B₄C–SiC with different contents of Co (10 vol%, 15 vol%, and 20 Vol %) were sintered at 1400 °C. The results of X-ray diffraction (XRD) analysis of the samples indicated the formation of W₂B₅, W₃CoB₃ as well as the remained C phases and unreacted SiC phase. It was observed that by increasing the Co content, the amount of W₂B₅ phase reduces and W₃CoB₃ and C contents increase. Therefore, W₂B₅ peaks were not detected in the sample containing 20vol% Co. Relative density values above 97% were obtained for all the composites. However, a decrease was observed in relative density by increasing the Co content in the composites. The highest flexural strength (510 ± 42 MPa), fracture toughness (10.34 ± 0.82 MPa m^1/2), and hardness (20.63 ± 0.75 GPa) were also obtained for the sample containing 10vol% Co compared to the other samples. In addition, Transgranular fracture of SiC as well as pulling out of W₃CoB₃ and W₂B₅ particles were observed in the fracture surface micrographs of the samples. The presence of micro-cracks in the SiC grains, fracture of W₃CoB₃ grains, and crack deflection was reported as dominant toughening mechanisms.