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Background: Streptococcus agalactiae, also known as Group B Streptococcus (GBS) is a commensal organism in the urogenital tract and rectum in approximately 25% of the healthy adult female population. The bacterium is the leading cause of bacterial meningitis, pneumonia, and sepsis in human infants.
Materials and Methods: Our study was performed over a three - month period from April to June 2014. Midstream specimens of urine were collected from outpatients suspected of having a bacterial urinary tract infection, which had not received any antibiotics. Group B Streptococci isolates were confirmed by typical colony morphology and identified by differential tests. Antibiotic susceptibility testing was carried out by disk diffusion method on Mueller Hinton agar (Merck, Germany) based on (CLSI) Guidelines 2012.
Results: GBS strains were isolated from 264 (21.1%) cases (out of 1249 positive bacterial urine cultures). The higher prevalence was recorded in the 15-44 and 45-64 age groups. Antibiotic susceptibility tests revealed that vancomycin, penicillin, and linezolid had the lowest, and tetracycline had the highest resistance rate.
Conclusion: In conclusion, the results of the present study confirm the universal susceptibility of GBS strains to the penicillin family and assert the use of penicillin or ampicillin as the first drug of choice for treatment and prophylaxis against GBS infections. However, it is important to perform antibiotic susceptibility testing whenever penicillin could not be prescribed.

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Backgrounds: Carbapenem resistance among Pseudomonas aeruginosa strains is alarming. This study aimed to investigate the relative frequency of carbapenem-resistant P. aeruginosa strains by phenotypic and genotypic methods.
Materials & Methods: The antibiotic susceptibility pattern of 60 P. aeruginosa isolates was determined by disk diffusion method (Kirby-Bauer). BD Phoenix automated microbiology system was used to identify carbapenem-resistant isolates, and the minimum inhibitory concentration (MIC) was determined using E-Test. In addition, mCIM (modified carbapenem inactivation method) phenotypic test was performed to evaluate carbapenem resistance genes in P. aeruginosa isolates. The prevalence of metallo-beta-lactamase (MβL) genes in carbapenem-resistant P. aeruginosa isolates was determined using conventional polymerase chain reaction (PCR).
Findings: The frequency of carbapenem-resistant P. aeruginosa isolates was 36% (22 of 60). The highest resistance was observed to imipenem and meropenem (36.6%), and the highest sensitivity was observed to amikacin (75%). All carbapenem-resistant P. aeruginosa isolates were confirmed by the BD Phoenix automated system (MIC> 8 µg/mL for imipenem and meropenem), E-test (MIC ˂32 µg/mL), and mCIM assay (the growth inhibition zone diameter was 6-8 mm).  In carbapenem-resistant P. aeruginosa isolates, the frequency of bla_VIM, bla_IMP, and bla_SPM genes was 9.1% (2 of 22), 4.5% (1 of 22), and 4.5% (1 of 22), respectively. Bla_KPC and bla_NDM genes were not found in any of the isolates.
Conclusion: Based on the present study results, all phenotypic tests used to identify carbapenemase-producing isolates had the same sensitivity (100%) and specificity (100%).

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Backgrounds: Delay in the diagnosis of tuberculosis (TB) leads to poor response to treatment and the disease transmission to susceptible individuals. The Xpert MTB/RIF assay efficiently detects Mycobacterium tuberculosis (MTB). The present study aimed to compare acid-fast bacilli (AFB) microscopy, culture, and Xpert MTB/RIF assay in the diagnosis of pulmonary and extrapulmonary tuberculosis cases.
Materials & Methods: This retrospective study was conducted in the Department of Microbiology, Government Medical College, Srinagar, India over 18 months from February 2019 to July 2020. Samples were processed and evaluated using AFB microscopy, culture, and Xpert MTB/RIF assay.
Findings: Among the 1862 samples evaluated, 224 samples were found to be positive using AFB microscopy, culture, and Xpert MTB/RIF assay. The overall sensitivity and specificity of the Xpert MTB/RIF assay in diagnosing pulmonary TB cases was 98.23 and 97.69%, respectively. Among the smear-negative extrapulmonary samples, 52 (5.75%) and 86 (9.6%) samples were positive in culture and the Xpert MTB/RIF assay, respectively. The maximum recovery of MTB by Xpert MTB/RIF assay was from tissue biopsy specimens. Rifampicin resistance was observed in six samples.
Conclusion: Both culture and Xpert MTB/RIF methods were sensitive in detecting smear-positive samples. Although both techniques missed some smear-negative pulmonary and extrapulmonary TB cases, the Xpert MTB/RIF assay enhanced the detection rate of MTB compared to culture. The Xpert MTB/RIF assay enabled the accurate diagnosis of tuberculosis cases with a rapid turnaround time; therefore, it could assist clinicians to start timely therapeutic interventions for these patients.

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Abstract In this paper the effect of two types of common initial geometric imperfections on the reliability of steel frames is investigated. These imperfections are the coordinates of connection nodes and crookedness of members. Most finite element reliability analyses in past literature neglect this source of uncertainty. For this purpose static nonlinear pushover structural analysis is used from which reliabilities are estimated based on FORM and Monte Carlo sampling methods. Furthermore to investigate the importance of uncertain parameters, reliability sensitivity analysis is performed by use of the direct differentiation method which has been implemented in the object oriented software framework Open Sees. It is demonstrated that some of these geometric imperfections have significant influence on reliability assessment of steel frames.

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Aims: Diabetic Neuropathy Pain (DNP) is a chronic condition that arises from nerve damage caused by prolonged hyperglycemia. It leads to burning, tingling, and sharp pain, primarily in the extremities. This study examines the effectiveness of Cognitive-Behavioral Therapy (CBT) in mitigating recurrent negative thoughts, reducing anxiety sensitivity, and enhancing emotional adjustment in individuals with DNP.
Method and Materials: The study employed a quasi-experimental pre-test-post-test design with a control group, involving 36 patients with DNP from Ardabil clinics located in Ardabil, Iran in 2024. Patients were purposively sampled and randomly assigned to intervention (n = 18) and control (n = 18) groups. The intervention group underwent eight 90-minute CBT sessions, while the control group received no intervention. Data were gathered using the Repetitive Negative Thinking Questionnaire, Anxiety Sensitivity Index-3, and Emotional Adjustment Measure. The collected data were analyzed using MANCOVA in SPSS-27.
Findings: The results demonstrated that CBT significantly improves emotional adjustment (F = 49.46) and reduces recurrent negative thoughts (F = 45.41), as well as physical (F = 52.27), cognitive (F = 59.61), and social dimensions of anxiety sensitivity (F = 38.34) in individuals with DNP (P < 0.001).
Conclusion: The findings highlight CBT's transformative impact on the psychological resilience of DNP patients, fostering adaptive emotional regulation and diminishing maladaptive thought patterns. By addressing the interconnected dimensions of anxiety sensitivity and emotional adjustment, CBT offers a pathway to holistic pain management, emphasizing its potential as a cornerstone in the psychological care of chronic pain conditions.


 

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Double layer ZnO/SnO2 thin film resistive gas sensors were fabricated by successive PVD of those oxides onto porcelain substrates. The metallic contacts were provided by electron beam evaporation of platinum onto substrates prior to deposition of the gas sensitive layers. Deposits were thermally annealed at different temperatures. It was shown that the activation energy of electrical conduction in the double layer depends on the annealing temperature. Higher annealing temperatures result in larger activation energies. The sensitivity of the double layer devices to ethanol vapor was measured and compared to that of single layer SnO2 sensors fabricated at similar conditions. It was shown for the first time that the gas sensitivity of ZnO/SnO2 thin film gas sensors can be adjusted by controlling parameters of the thermal annealing process.

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The new competitive environment changes the paradigm of power system operation. In the transmission area, open access process provides fair accessibility for all market participants. Congestion management is one of the most important side effects of this new process. This paper proposes a new approach for congestion management which is based on both active and reactive re-dispatch of the network critical buses. The critical buses including both generation and interruptible loads, are determined through a sensitivity analysis. Due to the important effects of the market pricing rules on the congestion cost and its allocation, two types of these rules, namely uniform and pay as bid pricing are investigated in the paper. The numerical results of case studies show the effectiveness of the proposed approach.

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Our study aims to evaluate the physicochemical mechanism involved in the adhesion of Fusarium oxysporum f. sp. albedinis (Foa) on date palm root of resistant (Aziza M) and susceptible (Boufegouss) varieties by determining their surface properties. Hydrophobicity of Date palm root and Foa was evaluated by contact angle measurement (θ_w) and free energy of interaction determination (∆Giwi). Our results showed that Foa surface is hydrophilic (θ_w = 30.57° and ΔG_iwi = 15.51 mj/m²) and has an important electron donor character (γ^- = 53,99mj/m²), whereas its electron acceptor property is low (γ⁺ = 8.95 mj/m²). Regarding date palm, the surface of sensitive variety’s root is hydrophilic (θ_w = 62.97°), while that of resistant variety is hydrophobic (θ_w = 69.50°). This character was confirmed by quantitative approach (ΔG_iwi = 6.84 mj/m² for sensitive variety and ΔG_{iwi =} -20.61 mj/m² for resistant variety). Also, it was noted that both resistant and sensitive varieties are weak electron acceptors (γ ⁺ = 0.15 mj/m² and γ ⁺ = 0.08 mj/m² for resistant and sensitive varieties respectively). The two varieties are relatively important electron donors, but the sensitive variety is more donor (γ^- = 30.5 mj/m²) than the resistant one (γ^- = 16.57 mj/m²). These results suggest that hydrophilic character and electron donor/acceptor character may be responsible for the adhesion of Foa on sensitive date palm root and therefore causes its susceptibility to bayoud disease. In contrast, the hydrophobic character of the resistant variety could explain its resistance.

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Abstract: The effect of two types of common initial geometric imperfections on the reliability of steel frames was investigated. These imperfections are the coordinates of connection nodes and crookedness of members. Most of the finite element reliability analyses in the past haveneglect this source of uncertainty. For this purpose, static non-linear pushover structural analysis was used in the present work from which reliabilities were estimated based on the FORM and Monte Carlo sampling methods. Furthermore, to investigate the importance of uncertain parameters, reliability sensitivity analysis was performed by the use of direct differentiation method, which was implemented in the object oriented framework of OpenSees software. It was demonstrated that some of these geometric imperfections have significant influence on the reliability assessment of steel frames.

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An extended octagonal ring (EOR) transducer was designed and developed to measure forces inside the compression chamber of a large square baler in different directions. The transducer was calibrated by applying forces in three directions simultaneously and independently. The sensor revealed excellent linearity along with small cross sensitivities. Horizontal and vertical primary sensitivities of the sensor were 1,479.7 and 1387.8 μVkN-1V-1, while horizontal and vertical cross sensitivities were 0.64 and 2.85% of the sensor primary sensitivities, respectively. The sensor was used to measure the forces inside the compression chamber of a large square baler in different directions.

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Prediction of stress-strain behavior of geotechnical material is one of the major efforts of engineers and researchers in the field of geomechanics. Experimental tests like tri-axial shear strength tests are the most effective apparatus to prepare the mechanical characteristics of gravelly material; but due to difficulties in preparing test samples and costs of the tests, only several tests will be done in a new project. Artificial neural network is a kind of method, in which engineer could judge the results based on numerous data from other similar projects, which enable the engineer to have a good judgment on the material properties. In this research, the behavior of gravelly material was simulated by use of multi-layer perceptron neural network, which is the most useful kind of artificial neural networks in the field of geotechnical engineering. For instance, first exact information was provided from laboratory tests of various barrow areas of embankment dams in the country and effective parameters on shear strength of coarse-grained material were studied. After omitting incorrect or weak data, 95, 20 and 23 sets of data were used for learning, testing and evaluating data, respectively. Input parameters for the model were as follows: particle-size distribution curve, dry density, relative density, Los-angles abrasion percent, confining pressure, axial strain; and outputs were selected as deviator stress. In order to reach a steady state in the model and force the model to behave homogenous to the all inputs, data was normalized to the value between .05 and 0.95. In the simulation, back-propagation algorithm was used for learning or error reduction. The aim of the simulations was defined to reduce error between real data and predicted values; for instance root mean square error (RMS) was used to be minimized through simulation and predicted versus real graphs were used to observe the global error of the model. After modeling the data based on some criteria, it was shown that curves of stress-strain from simulation tests were in good agreement with those from laboratory. These close coherencies were observed in all training, testing and evaluation data, in which the RMS errors were 0.038, 0.037 and 0.026, respectively. To reach this ultimate step, a 10*19*1 multilayer perceptron was used via trial and error. In order to determine quality and quantity of the effect of inputs on outputs, and prove that the results were in good agreement with soil mechanic principles, sensitivity analyses were done on the average data of the inputs. Results show that confine pressure, uniformity coefficient and relative density of the material were the most effective parameters on the stress-strain curves; thus the model has enough capability to predict the stress-strain behavior of gravelly soils.

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In the present paper, the parameters of Johnson - Cook (JC) constitutive model for two steels have been identified, based on the Hopkinson pressure bar test results. The experimental data has been taken from the split Hopkinson pressure bar data found in the literature. Using the measured strain pulses, the experimental stress - strain and deformation - time curves can be extracted. The experimental data have been processed using two different methods. In the first method strain rate assume to be constant during deformation and in the other one the deformation has been applied to a modeled specimen. In each method, an optimal set of material constants for JC constitutive model have been computed by minimizing the standard deviation of the numerically obtained stress - strain curve from the experimental data. Also a sensitivity analysis has been performed on JC constitutive model parameters and temperature changes during test have been investigated. The obtained results show that using constant strain rate method, leads to considerable error in results; for example in this study the minimum error is about 14%.

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Ramsey model is one of the most important basic models to study intertemporal resource allocation. This model is derived from microeconomic optimal principle so it has a key role in macroeconomics with micro foundations. Hence, in many economic researches it is considered as a reference theory. Application of this model in economy of Iran will provide an appropriate theorem framework for explaining empirical facts of the Iranian economy and will introduce a new approach to researchers. The main idea of this study is generalizing Ramsey model through including terms of trade and its calibration in the economy of Iran. For this purpose first, the model is explained. Then, the first order condition is derived and mathematical optimal path of variables is solved.  Finally, the model is calibrated by GAMS package for economy of Iran in time period (2006-2036). The results indicate that there is a feasible solution for model and the optimal path of variables can be observed. The optimal path of Gross National Production and Consumption are increasing but the optimal path of capital stock and investment is primarily increasing then decreasing. In the final section of this paper a sensitivity analysis is presented. Some scenarios are designed for the important parameters of model like time preferences rate, intertemporal substitution elasticity of consumption, labour growth rate and output elasticity of capital. Sensitivity analysis shows that output elasticity of capital and labour growth rate increased the social welfare and shifted optimal path of variables upward. But time preferences rate and intertemporal substitution elasticity of consumption had inverse effect on social welfare and optimal path of variables.

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Creating and supporting small and medium-sized industries in economic development programs and the emphasis on improving efficiency and productivity in the policies adopted, shows the vital position of such industries in developed as well as developing economies. In general, the most important role of these industries in the economic development process can be summarized as; effective employment, production and supply chain management, creating value added and reducing dependence on unnecessary commodity imports. Since any improvement in the efficiency of small scale industries will bring more equitable distribution of income, the main purpose of this study is to measure the performance of various technical, management and scale efficiencies in subsectors of small scale industries and provide policy recommendations to the inefficient industries. For this purpose, the principal component analysis (PCA) and factor analysis is used to determine the variables of the model and the DEA is used for evaluation and sensitivity analysis of the factors affecting the efficiency and productivity of small scale industries during the period 2002 - 2007. The results show that out of 22 industries, only 8 ones are found to be perfectly efficient. Productivity measurement of these industries according to the "Malmquist" index reveals that, the trend of productivity enjoys positive growth.

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Terfenol-D, known as a giant magnetostrictive material, is used in many sensors such as force sensor. In these sensors, external force is measured due to variation of magnetic flux density passing through Terfenol-D. To improve the performance, Terfenol-D is exposed to bias magnetic field and mechanical pre-stress. In this paper, Effects of bias magnetic field and mechanical pre-stress on sensitivity and linear measurement range of a force sensor are studied and optimum values of them are recognized. Initially based on magnetomechanical coupling equations, theoretical model of sensor that includes effective parameters on sensitivity and linear measurement range is developed. Then using experimental set-up, magnetomechanical properties of Terfenol-D are investigated and values of essential parameters for theoretical model are extracted. Finally, employing theoretical model and experimental results, the response of sensor under dynamic external forces is simulated and effects of bias magnetic field and mechanical pre-stress on sensitivity and linear measurement range of the sensor are studied. Based on the obtained results, to increase sensitivity and linear measurement range of sensor, values of bias magnetic field and mechanical pre-stress should be relatively determined considering the amplitude of external force.

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Determining the bearing capacity of piles is an important issue that always Geotechnical engineers focus on. Effect of factors such as environmental dissonance of soil which contains a pile, pile implementation, pile gender and its shape make correct estimation of bearing capacity difficult. Pile load testing as a reliable method could be used in various stages of analysis, design and implementation of piles to determine the axial bearing capacity of piles. On the other hand, pile load testing, despite high accuracy, imposes high cost and long duration for development projects and it causes limitations in this experiment. Thus acceptance of numerical analysis at geotechnical studies is increasing. In this study serious models of multi-layer perception neural network, one of the most commonly used neural networks, was used. In all models four parameters are used as input data which are length and diameter of the pile, the coefficient of elasticity and internal friction angle of soil and the bearing capacity of piles is used as output data. Models have reasonable success in predicting the bearing capacity of piles. To increase the accuracy of predicting bearing capacity, for the network training stage the real tests that has been done at the geotechnical studies of dry dock area Hormozgan by POR Consulting Engineers were used. According to (Because we) need of more data for training and testing network, several tests on pile bearing capacity, in smaller dimensions were performed in the laboratory. To perform these tests the device of pile bearing capacity, made in university of Tarbiat Modarres, was used. Models based on neural networks, unlike traditional models of behavior don’t explain effect of input parameters on output parameters. In this study, by the sensitivity analysis on the optimal structure of introduced models in each stage it has been somewhat trying to answer this question.

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Objective: As we are approaching the global eradication of wild poliovirus, laboratory surveillance of poliovirus by the gold standard cell culture method becomes increasingly important. As there is a lot of concern about accurate and sensitive detection of imported wild and Vaccine Derived Polioviruses (VDPVs) in Polio-Free countries, in this study we assessed and compared the sensitivity of the cell lines used in polio laboratory simultaneously to standard poliovirus and Oral Polio Vaccine (OPV) polioviruses, to ensure the accurate detection of circulating and imported polioviruses in the society. Materials and Methods: Cell sensitivity test was performed according to the World Health Organization (WHO), Polio Laboratory Manual for RD, L20B and Hep2 cell lines using 3 serotypes of standard monovalent and OPV polioviruses. The test was repeated every four passages for all cell lines. Results: The sensitivity of L20B and Hep2 cell lines for standard poliovirus type 1 and 2 is more than sensitivity for the same types of OPV virus but for poliovirus type 3 it is vice versa. Also RD cell line is more sensitive to all 3 types of OPV virus. In addition, the test showed that increasing the passage number will decrease the sensitivity of all cell lines. Conclusion: Using RD & L20B cell lines simultaneously (with low passage number) will assure us of sensitivity and accuracy of the cell lines for detection of circulating and imported polioviruses.