Simulation of three-component two-phase flow in porous media using method of lines

Numerical simulation of compositional flow problems commonly involves the use of 1st- or 2nd-order Euler time stepping. Method of lines (MOL), using highly accurate and efficient ODE solvers, is an alternative technique which, although frequently applied to the solution of two-phase, two-component flow problems, has generally been overlooked for problems concerning more than two components. This article presents the development of a numerical simulator for 1D, compressible, two-phase, three-component, radially symmetric flow using the method of lines (MOL) and a 3rd-order accurate spatial discretization using a weighted essentially non-oscillatory (WENO) scheme. The MOL implementation enables application of the MATLAB ODE solver, ODE15s, for time integration. Simulation examples are presented in the context of CO2CO2 injection into a reservoir containing a mixture of CH4CH4 and H2OH2O. Following an assumption of constant equilibrium ratios for CO2CO2 and CH4CH4, a ternary flash calculator is developed providing closed-form relationships for exact interpolation between equations of state for CO2CO2–H2OH2O and CH4CH4–H2OH2O binary mixtures. The numerical code is successfully tested and verified for a range of scenarios by comparison with an existing analytical solution

Short view of leukemia diagnosis and treatment in Iran

Background: Early diagnosis and treatment of leukemia patients remains a fundamental aim in clinical oncology, especially in developing country. Present study highlights the basic requirements of these patients in Iran. Better understanding of these issues may lead to improve the healthcare standards toward leukemia diagnosis and treatment. Methods: This descriptive study included 101 specialists in hematology-oncology and pathology serving in oncology centers. The participants were then asked to fill out a standard questionnaire on the issues around diagnosis and treatment of blood malignancies. Results: According to specialists, unfair distribution of facilities across the country, delayed diagnosis of disease, absence of psychological support for patients, and insufficient financial support were the main reasons of inappropriate diagnosis and treatment in leukemia patients. Conclusions: Our results show that making an amendment to health policies by preparing well-equipped medical centers in all provinces, improving the morale of patients through consultation during the process of treatment, and above all, subsiding leukemia patients' financial problems will promote the health standard regarding the leukemia diagnosis and treatment in Iran. © 2015, Tehran University of Medical Sciences (TUMS). All rights reserved

Self-Organizing Traffic Flow Prediction with an Optimized Deep Belief Network for Internet of Vehicles

To assist in the broadcasting of time-critical traffic information in an Internet of Vehicles (IoV) and vehicular sensor networks (VSN), fast network connectivity is needed. Accurate traffic information prediction can improve traffic congestion and operation efficiency, which helps to reduce commute times, noise and carbon emissions. In this study, we present a novel approach for predicting the traffic flow volume by using traffic data in self-organizing vehicular networks. The proposed method is based on using a probabilistic generative neural network techniques called deep belief network (DBN) that includes multiple layers of restricted Boltzmann machine (RBM) auto-encoders. Time series data generated from the roadside units (RSUs) for five highway links are used by a three layer DBN to extract and learn key input features for constructing a model to predict traffic flow. Back-propagation is utilized as a general learning algorithm for fine-tuning the weight parameters among the visible and hidden layers of RBMs. During the training process the firefly algorithm (FFA) is applied for optimizing the DBN topology and learning rate parameter. Monte Carlo simulations are used to assess the accuracy of the prediction model. The results show that the proposed model achieves superior performance accuracy for predicting traffic flow in comparison with other approaches applied in the literature. The proposed approach can help to solve the problem of traffic congestion, and provide guidance and advice for road users and traffic regulators

Detection of ISPa1328 and ISPpu21, Two Novel Insertion Sequences in the OprD Porin and bla_IMP-1 Gene Among Metallo-Beta-Lactamase-Producing Pseudomonas aeruginosa Isolated From Burn Patients

Background: Carbapenemes are a good choice for treatment of infections caused by multidrug resistant Pseudomonads aeruginosa. The emergence of carbapenem resistance has become a major problem in treatment of this organism especially among immunocompromised patients including burn patients. Objectives: The aim of this study was to investigate carbapenem-resistance mechanisms among burn patients in Tehran, Iran, during 2014 - 2015. Methods: The antibiotic resistance phenotypic test was accomplished by the Kirby Bauer disk diffusion method. The phenotypic investigation of metallo-beta-lactamase (MBL) producers was evaluated by the combined disk diffusion test (CDDT) method. The prevalence of MBL genes, including blaIMP-1 and blaVIM-1 was evaluated by polymerase chain reaction (PCR) and sequencing methods. Amplification of oprD was performed by PCR and the results of sequencing were aligned with wild-type P. aeruginosa strain PAO1. Results: A total of 100 P. aeruginosa were investigated, of which, 95 were resistance to imipenem. Out Of 95 imipenem resistant isolates,, 81 (85.2%) were MBL producers. Among all isolates, 13 strains carried the blaIMP-1 gene, whereas all of the strains were negative for the blaVIM-1 gene. Amplification of OprD porin was performed for all 100 P. aeruginosa strains. Two insertion sequences (ISs) including ISPpu21 and ISPa1328 were detected in PCR products of OprD gene, that were larger than expected. Conclusions: The prevalence of β-lactamase-producing isolates and their isolation from life-threatening infections in burn patients is increasing at an alarming rate worldwide. Also, we have identified two novel IS elements, ISPa1328 and ISPpu21, in P. aeruginosa isolates from hospitals in Tehran, Iran. In most of the isolates, insertional inactivation of oprD by ISPa1328 and ISPpu21 were associated with carbapenem resistance

A Generalized Multistep Dynamic (GMD) TOPMODEL

There is a lack of Ordinary Differential Equation (ODE) formulations in numerical hydrology, contributing to the lack of application of canned adaptive timestep solvers; hence the continued dominance of fixed (e.g., Euler) timestep techniques despite their fundamental problems. In this paper, we reformulate Dynamic-TOPMODEL into a constraint-handling ODE form and use MATLAB's advanced adaptive ODE-solvers to solve the resulting system of equations. For wider applicability, but based on existing research and/or first principles, we developed Generalized Multistep Dynamic TOPMODEL which includes: iso-basin spatial discretization, diffusion wave routing, depth-dependent overland flow velocity, relaxing the assumption of water-table parallelism to the ground surface, a power-law hydraulic conductivity profile, new unsaturated zone flux, and a reference frame adjustment. To demonstrate the model we calibrate it to a peat catchment case study, for which we also test sensitivity to spatial discretization. Our results suggest that (a) a five-fold improvement in model runtime can result from adaptive timestepping; (b) the additional iso-basin discretization layer, as a way to further constrain spatial information where needed, also improves performance; and (c) the common-practice arbitrary Topographic Index (TI) discretization substantially alters calibrated parameters. More objective and physically constrained (e.g., top-down) approaches to TI classification may be needed

Pulmonary embolism in pregnancy with COVID-19 infection: A case report

Pregnant women in the third trimester are at the highest risk. Contracting COVID-19 increases the complications. Hence, it is critical for pregnant women, especially during the third trimester, with slightest COVID-19 symptoms to visit as soon as possible. Early diagnosis considerably contributes to saving both the mother and the fetus. © 2020 The Authors. Clinical Case Reports published by John Wiley & Sons Ltd