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In this paper, based on the slab method and focusing on the rate-dependent flow condition, asymmetrical thermomechanical rolling (ATMR) is investigated to establish a new model for calculation of the rolling force. Unlike the former models where the rate-dependent condition of the yield shear stress has not been considered, in this study, a visco-plastic flow stress formulation of material is used for applying the rate and temperature sensitivity parameters and kinetic of work hardening and softening of the material. Comparison of the present analytical model with experimental data and other models reveals the precision of calculation. An asymmetrical rolling index (ARI) is introduced to evaluate the effects of rolling parameters on asymmetrical conditions of the rolling process. Using the response surface methodology (RSM), the interaction effects and contribution of rolling parameters are studied. Investigations indicate that the speed rate plays a role as an intensifier of the parameters' effect on the ARI. Furthermore, the occurrence of high value of speed rate with a low percent of thickness reduction leads to the restricted rise of the ARI levels. The verification of the statistical models indicates an acceptable competency of results. [ABSTRACT FROM AUTHOR]

Background and Objective: Bacterial resistance to Imipenem is increased in bacterial infections in Iran. In regard to the importance of Imipenem in the treatment of nosocomial infections and the key role of disc diffusion method as a major antibiotic susceptibility testing assay, this study was done to determine the prevalency of imipenem-resistant bacterial strains isolated from hospital and accuracy of Iranian imipenem disc product. Methods: In this descriptive-analytic study, 241 bacteria were isolated from patients in different wards of the Baqyatallah hospital in Tehran, Iran during 2013-14. After streaking of the organisms, identification was performed by all conventional biochemical tests. The bacterial resistance to imipenem was determined by disk diffusion method using Iranian and Mast imipenem discs. True imipenem-resistant isolates were examined for susceptibility to six different antibiotic including Ciprofloxacin, Gentamicin, Cephalexin, Azitromysin, Tetracycline and Ceftazidim, using disk diffusion method. Results: The most prevalent isolates organisms were gram-negative bacilli (Klebsiella, Escherichia coli, and Pseudomonas aeruginosa, respectively). The common clinical source was urine and wound samples, respectively. Resistant to Imipenem was 68 (25.7 %) and 19 (7.8 %) based on the results of Iranian and Mast Imipenem discs, respectively. False results for Iranian Imipenem discs was higher than Mast Imipenem discs (P<0.05). Among the 19 true Imipenem resistant isolates, 17 micro organisms were Pseudomonas aeruginosa. 57% of isolated resistant to Imipenem were isolated from ICU ward. The most resistance was seen to Gentamicin (84%) and the lowest was seen to Ciprofloxacin (63%). 84% of isolated samples were multi drug resistance. Conclusion: Although a small percentage of the isolates obtained as important nosocomial pathogens were resistant to Imipenem, but the rate of multiple resistance and high rate of isolates obtained from ICU was noticeable. [ABSTRACT FROM AUTHOR]

The article presents a study on an adaptive tracking control system in the robot controller's task space that is anchored in a dynamical positioning scheme and can address uncertainties in the dynamics and kinematics of rigid-link robots. The study applied the control system to a two-link elbow robot controller to test its performance. Results show that the system was effective as the trajectory tracking errors are directly detected by sensor without the employment of inverse kinematic.

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Computed tomography perfusion (CTP) is a dynamic 4-dimensional imaging technique (3-dimensional volumes captured over approximately 1 min) in which cerebral blood flow is quantified by tracking the passage of a bolus of intravenous contrast with serial imaging of the brain. To diagnose and assess acute ischemic stroke, the standard method relies on summarizing acquired CTPs over the time axis to create maps that show different hemodynamic parameters, such as the timing of the bolus arrival and passage (Tmax and MTT), cerebral blood flow (CBF), and cerebral blood volume (CBV). However, producing accurate CTP maps requires the selection of an arterial input function (AIF), i.e. a time-concentration curve in one of the large feeding arteries of the brain, which is a highly error-prone procedure. Moreover, during approximately one minute of CT scanning, the brain is exposed to ionizing radiation that can alter tissue composition, and create free radicals that increase the risk of cancer. This paper proposes a novel end-to-end deep neural network that synthesizes CTP images to generate CTP maps using a learned LSTM Generative Adversarial Network (LSTM-GAN). Our proposed method can improve the precision and generalizability of CTP map extraction by eliminating the error-prone and expert-dependent AIF selection step. Further, our LSTM-GAN does not require the entire CTP time series and can produce CTP maps with a reduced number of time points. By reducing the scanning sequence from about 40 to 9 time points, the proposed method has the potential to minimize scanning time thereby reducing patient exposure to CT radiation. Our evaluations using the ISLES 2018 challenge dataset consisting of 63 patients showed that our model can generate CTP maps by using only 9 snapshots, without AIF selection, with an accuracy of 84.37 % ., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Acute ischemic stroke is one of the leading causes of death and long-term disability worldwide. It occurs when a blood clot blocks an artery that supplies blood to the brain tissue. Segmentation of acute ischemic stroke lesions plays a vital role to improve diagnosis, outcome assessment, and treatment planning. The current standard approach of ischemic stroke lesion segmentation is simply thresholding the Computed Tomography Perfusion (CTP) maps, i.e., quantitative feature maps created by summarizing CTP time sequence scans. However, this approach is not precise enough (its Dice similarity score is only around 50%) to be used in practice. Numerous machine learning-based techniques have recently been proposed to improve the accuracy of ischemic stroke lesion segmentation. Although they have achieved remarkable results, they still need to be improved before they can be used in actual practice. This paper presents a novel deep learning-based technique, MutiRes U-Net, for the segmentation of ischemic stroke lesions in CTP maps. MultiRes U-Net is a modified version of the original U-Net that is re-designed to be robust to segment the objects in different scales and unusual appearances. Additionally, in this paper, we propose to enrich the input CTP maps by using their contra-lateral and corresponding Tmax images. We evaluated the proposed method using the ISLES challenge 2018 dataset. As compared to the state-of-the-art methods, the results show an improvement in segmentation task accuracy. The dice similarity score (DSC) was 68%, the Jaccard score was 57.13%, and the mean absolute volume error was 22.62(ml)., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

A non-enzymatic glucose sensor based on pencil graphite electrode (PGE) modified by copper oxide nanoparticles decorated reduced graphene oxide (CuO(NP)/rGO-PGE) was prepared. XRD patterns showed partially electrochemically reduction of GO and monoclinic structure of CuO on the PGE. The prepared CuO(NP)/rGO exhibited a nanoporous structure by scanning electron microscopy (SEM). Transmittance electron microscopy (TEM) revealed copper oxide nanoparticles were well distributed on rGO and had semispherical shapes with diameter 3-5 nm. Cyclic voltammetry at CuO(NP)/rGO-PGE showed the immobilized CuO(NP)s were highly stable in alkaline solutions and had high electrocatalytic activity toward glucose oxidation. Using amperometry, the detection limit of [0.091 (±0.003) μM] and concentration sensitivity of [4760 (±3.2) μA mM -1  cm -2 ] for glucose was obtained at optimum conditions. The applicability of the sensor was evaluated to determine the glucose concentration in human blood serum samples and the experimental results were comparable with those measured by traditional spectrophotometric methods. The preparation of CuO(NP)/rGO-PGE was reproducible, very simple, fast and inexpensive for practical application., (Copyright © 2018 Elsevier B.V. All rights reserved.)

An electrochemical phosphate sensor based on zirconium and reduced graphene oxide modified pencil graphite electrode (Zr/rGO-PGE) is proposed. The XRD, CV and EIS confirmed that GO was partially reduced on the PGE. Scanning electron microscopy (SEM) exhibited the layered and wrinkled structures for the rGO-PGE and Zr/rGO-PGE, respectively. Cyclic voltammetry showed the immobilized rGO was highly stable and had high activity toward zirconium adsorption. The prepared electrode was used for the electrochemical determination of phosphate. Based on the optimum condition using differential pulse voltammetry, the limit of detection and sensitivity for phosphate was obtained as [0.011(± 0.004) μM] (S/N = 3) and [622.4(± 9.6) μA μM -1 cm -2 ], respectively. The sensor was successfully evaluated for phosphate determination in human serum samples. In practical terms, the construction of this sensor was exceptionally simple, fast, cost effective and reproducible.

Coronary artery disease (CAD) is considered as a chronic inflammatory disease initiated from early childhood. Nuclear factor κB (NF κB) and κB1A (NF κB1A) are the key regulators of inflammatory responses. The NFKB1 -94ATTG ins/del and NFKB1A -826C/T polymorphisms may contribute to the development of CAD. The aim of the present study was to investigate the association of these polymorphisms with the risk of CAD. The study population included 120 patients with angiographically confirmed CAD and 100 matched controls. Genotyping of NFKB1 -94ATTG ins/del and NFKB1A -826C/T polymorphism was performed using PCR-RFLP method. Lipid level was determined by routine colorimetric methods. Statistical analysis was done by SPSS 16 software. Results indicated that the genotypic (P=0.041) and allelic (P=0.009) distribution of the NFKB1-94ATTG ins/del polymorphism was significantly different between the two groups. In the univariate analysis (ins/ins genotype as reference), the del/del genotype (OR=2.88, 95% CI=1.21-6.84, P=0.015) but not ins/del genotype (OR=1.48, 95% CI=0.83-2.64, P=0.191) was significantly associated with the increased risk of CAD. In the multiple binary logistic regression analysis, diabetes, hypertension, smoking, LDL-cholesterol, total cholesterol, HDL-cholesterol and NFKB1 -94ATTG del/del genotype were identified as significant and independent risk factors for CAD development. The distribution of genotypes and alleles of NFKB1A -826C/T polymorphism was not significantly different between the two groups. In conclusion the present study identified NFKB1 -94ATTG ins/del polymorphism but not NFKB1A -826C/T polymorphism as a significant and independent risk factor for development and severity of CAD.

Introduction: Bone marrow transplantation is a critical approach for the treatment of many hematological disorders. Success of this approach is dependent on many factors the most important of which is the number of hematopoietic stem cells along with an efficient stroma. Co-transplantation of efficient mesenchymal stem cells can greatly improve the outcome of transplantations. Current researches assign a critical role for hypoxia inducible factor (HIF)-1α in protection of various cells and tissues probably through induction of cytokines. To make this feature applicable to human bone marrow-derived mesenchymal stem cells, we manipulated these cells to over express HIF-1α gene., Materials and Methods: Full-length cDNA of human HIF-1α was inserted into human bone marrow mesenchymal stem cells by pcDNA.3.1 non-viral plasmid vector, and the effect of this over expression on production of some hematopoietic growth factors was explored. Moreover, using a co-culture system, the interactive impact of HIF-1α-overexpressed mesenchymal stem cells on hematopoietic stem cells was evaluated. Results Over expression of HIF-1α in mesenchymal stem cells in normoxia increased production of one of the most important hematopoietic growth factors, Stem cell factor (also known as Steel factor or c-kit ligand). HIF-1α overexpression had no effect on production of other hematopoietic growth factors. In co-culture of mesenchymal stem cells-HIF-1α with hematopoietic stem cells, enhancement of colony formation and reduced differentiation of hematopoietic stem cells were observed. Conclusion Over expression of HIF-1α in human bone marrow-derived mesenchymal stem cells can augment the production of some hematopoietic growth factors, and we suggest this response of mesenchymal stem cells could help to improve the outcome of bone marrow transplantation.