The effect of self-awareness and self-regulation on organizational commitment employees of islamic azad university of mashhad with mediating role of job satisfaction

Optimal utilization of employees and facilities is the primary goal of any organization and creation of a commitment and satisfaction in employees can have a major role to realize the goals. The aim of this study is to investigate The Effect of Self-awareness and Self-regulation on Organizational Commitment Employees of Islamic Azad University of Mashhad with Mediating Role of Job Satisfaction. The statistical sample of the study is the employees of Islamic Azad University of Mashhad which is obtained through simple random sampling according to the sample size of Cochran’s formula, 190 questionnaires were collected. The collected data from the questionnaires were analyzed with structural equation modeling method using LISREL software. Also Spss software was used to express the descriptive statistics data. The results of this study showed that self-awareness and self-regulation has a positive effect on organizational commitment and job  satisfaction. Also job satisfaction has a positive effect on organizational  commitment and finally the results suggest the effectiveness of Self-awareness and Selfregulation on organizational commitment job satisfaction with mediating role of job satisfaction.Keywords: Self-awareness, Self-regulation, Job Satisfaction, Organizational Commitmen

Histomorphometrical study of silver carp fish testis in two age classes

In this research, morphological and histomorphometrical structure of testis of 20 silver male carp fish were studied in two classes or groups. Group1 was composed of 10 fish with average (±SD) weight of 1.247+0.656kg and average(±SD) length of 43.675+1.414cm with about 2 years age, Group2 was composed of 10 fish with average(±SD) weight of 5.716+0.519kg and average(±SD) length of 81.5+1.643cm. Average (±SD) weight of testis were 2.34+1.47gr and 83.33+25.81gr with average (±SD) GSI of 0.187+0.224 and 1.457+4.974 in groups 1 and 2 respectively. Samples from testis were taken by maximum thickness of 0.5cm and after fixation in bouin , s fixative and 5-6µm thickness section were made routine paraffin embedding method and stained by Hematoxylin-Eosin and PAS staining. The microscopic results showed that the silver carp testis was lobular and cystic type in two groups. In group 1, there was no spermatozoon activity and PGCs were only germ cells in the cysts. But in group2, the numbers of PGCs were decreased significantly and spermatogenic cells were seen in different phases including spermatogonia, primary and secondary spermatocysts, early and late spermatid, and spermatozoa which each one was located in a separated cyst. There was no significant difference in nucleus diameter of PGCs in testis of group1 (6.97+0.438µ) and group (6.13+0.438µ). In group2, the nucleolus diameter of spermatogonia was 2.97+0.112µm, primary spermatocyt 3.59+0.107µ, early spermatid 1.59+0.761µ, late spermatid 1.24+0.132µ, spermatozoa 1.16+0.054µ, and the length of spermatozoia 17.412+1.946µ. The interesting finding was immature testis in fish of group 1 with average weigh (1.247+0.656kg) and average length (43.675+1.414cm) in about 2 years age and mature testis in fish of group 2 with average weight of (5.716+0.519kg) and average length of (81.5+1.643cm) with about 4 years age in Khuzestan climate conditions

On the formation of crack networks in high cycle fatigue

International audienceA probabilistic model based on an initial distribution of sites is proposed to describe different aspects of the formation, propagation and coalescence of crack networks in thermomechanical fatigue. The interaction between cracks is modeled by considering shielding effects

Predicting Audit Opinion by a new Metaheuristic Algorithm: Water Cycle Algorithm

An auditor evaluates if financial statements which the firms issue in public, present fairly and are free from material misstatement. The audit report is a written letter containing independent verification of the quality of financial statements used for making economic decisions. Hence, the issuance of such a report can lead to the transmission news and information about the firm and to enhance the degree of confidence in the financial statements. This study predicts audit opinion of the firms listed in Tehran Stock Exchange during 2018-2020 by a new metaheuristic algorithm named Water Cycle Algorithm (WCA) and compares its results with one of the most popular methods called logistic regression (LG). 24 variables were extracted from the literature and used for this prediction. 4 evaluating criteria were used to compare the predictions of two methods. According to findings, the superiority of the criteria in the WCA was confirmed in comparison to LG. Since WCA was more appropriate, users of financial reports can use it to predict the type of audit opinion in the unaudited interim financial statements, and also, auditors can use it while evaluating and accepting clients and achieving an acceptable level of audit risk, as a quality control tool

A Novel Approach for Analyzing the Effects of Almen Intensity on the Residual Stress and Hardness of Shot-Peened (TiB + TiC)/Ti–6Al–4V Composite: Deep Learning

In the present study, the experimental data of a shot-peened (TiB + TiC)/Ti–6Al–4V composite with two volume fractions of 5 and 8% for TiB + TiC reinforcements were used to develop a neural network based on the deep learning technique. In this regard, the distributions of hardness and residual stresses through the depth of the materials as the properties affected by shot peening (SP) treatment were modeled via the deep neural network. The values of the TiB + TiC content, Almen intensity, and depth from the surface were considered as the inputs, and the corresponding measured values of the residual stresses and hardness were regarded as the outputs. In addition, the surface coverage parameter was assumed to be constant in all samples, and only changes in the Almen intensity were considered as the SP process parameter. Using the presented deep neural network (DNN) model, the distributions of hardness and residual stress from the top surface to the core material were continuously evaluated for different combinations of input parameters, including the Almen intensity of the SP process and the volume fractions of the composite reinforcements

Efficient Strategies for Elimination of Phenolic Compounds During DNA Extraction From Roots of Pistacia Vera L.

Optimization of DNA extraction protocols for plant tissues and including endophytic microorganisms is a critical step of advanced plant-microbe interaction in agricultural studies. Pistachio (Pistacia vera L.) root tissue contains high levels of polyphenols have been known as major extract contaminants and inhibitors of enzymatic activities during amplification. The present study aimed to develop reliable strategies to purify DNA from Pistachio root samples. Inhibiting substances were removed from DNA through a process including extraction with hot detergent contains SDS-Tris- EDTA, AlNH4(SO4)2.12H2O as chemical coagulating factor and CTAB-NaCl. Following typically organic extraction/alcohol precipitation, denaturing agarose electrophoresis performed to purify probable remain contaminants. The purified DNA was enough free of polyphenols based upon loss of color and spectral quality (260/230>1.6) and efficiently amplified during polymerase chain reaction particularly in the present of GC-clamp primers. This method proved well with detection of Glomus sp. (arbuscular mycorrhiza fungi) associated with Pistacia vera L. using denaturing gradient gel electrophoresis (DGGE)

Application of Deep Neural Network to Predict the High-Cycle Fatigue Life of AISI 1045 Steel Coated by Industrial Coatings

In this study, deep learning approach was utilized for fatigue behavior prediction, analysis, and optimization of the coated AISI 1045 mild carbon steel with galvanization, hardened chromium, and nickel materials with different thicknesses of 13 and 19 mu m were used for coatings and afterward fatigue behavior of related specimens were achieved via rotating bending fatigue test. Experimental results revealed fatigue life improvement up to 60% after applying galvanization coat on untreated material. Obtained experimental data were used for developing a Deep Neural Network (DNN) modelling and accuracy of more than 99%.was achieved. Predicted results have a fine agreement with experiments. In addition, parametric analysis was carried out for optimization which indicated that coating thickness of 10-15 mu m had the highest effects on fatigue life improvement

Numerical Simulation of the Performance and Emission of a Diesel Engine with Diesel-biodiesel Mixture

IntroductionIncreasing industrialization, growing energy demand, limited reserves of fossil fuels, and increasing environmental pollution have jointly necessitated for exploration of a substitute for conventional liquid fuels. Vegetable oils can be used as alternatives to petroleum fuels for engine operation. These oils are mixtures of free-fatty acid molecules to contain carbon, hydrogen, and oxygen atoms. The ability to simulate the process of converting chemical energy to heat, energy users of computational fluid dynamics software in the design, analysis, and optimization of high-tech tools. Also, simulation saves time and reduces costs, workforce, and the space required.Materials and MethodsIn this research, a one-dimensional computational fluid dynamics solution with GT-Power software was used to simulate a four-cylinder, four-stroke, direct injection diesel engine to study the performance and exhaust emissions characteristics with different speeds and blends at full load. The engine speeds were chosen to be 1100 to 1400 rpm at an interval of 100 rpm. Also, fuel blends such as diesel (as a base), B5, and B10 biodiesel were selected for engine testing. To model a engine, we should have the dimensions of the engine, input air collection, output gases collection, the amount of sprinkled fuel, valves properties, combustion, and some of the estimates corresponding to the cylinder’s thermodynamic parameters when opening the output and input gate and to exchange the heat inside the cylinder as the input data. The model mainly consisted of an air cleaner, intake valve, exhaust valve, intake and exhaust port, injection nozzle, engine cylinder, and engine. Engine cylinder’s intake and exhaust ports are modeled geometrically with pipes. Before this investigation was carried out, a validation model for evaluation was done by experimental and simulation data. The validation results showed that the software model error is acceptable.Results and DiscussionThe engine performance and emissions were evaluated in terms of engine torque, specific fuel consumption, NOx, and CO emission at different engine speeds and fuels at full load. The results showed that with increasing the engine speeds, torque increased. On the other hand, the maximum engine torque for the diesel engine is slightly lower than the biodiesel-blended that increased by 4.4% because of the higher density and viscosity of biodiesel than diesel. Specific Fuel Consumption (SFC) is a measure of the fuel efficiency of any prime mover that burns fuel and produces rotation, or shaft, power. The results indicated that by increasing engine speeds, the SFC increased. A fuel with a lower heating value should be injected with more mass into the engine. This will increase the SFC. So, the maximum engine SFC for the diesel engine is more than the biodiesel-blended that decreased by 4.45% because of better fuel combustion and more power generation of biodiesel than diesel. The only nitrogen oxide that can be formed in an engine combustion temperature is nitrogen monoxide (NO). This pollutant factor can be converted to nitrogen dioxide (NO2) over the time of exhaust gas. The results showed that with increasing the engine speeds, the NOX emissions decrease steadily and then increases, which is due to the high temperature in the cylinder. The viscosity and density of fuels have an effect on NOX emission, and because of the larger droplets of the fuel, it released NOX. The highest NOx emissions belong B10 biodiesel in 1400 rpm, due to the high oxygen content of this fuel and the lowest NOx emissions belong B10 biodiesel in 1300 rpm, due to the low density of the fuel compared to diesel. CO is a colorless and odorless gas, whose even very low concentrations are dangerous for humans and animals. The results showed that with increasing the engine speeds, the CO emission decreased and the minimum CO emission for diesel engine is more than the biodiesel-blended that decreased by 37.61% because of excess oxygen availability and complete combustion in biodiesel than diesel.ConclusionThe results of this study showed that the B10 blend in high engine speeds, generally had the best performance and emissions characteristics among the three fuels used in this study. Also, this investigation will assist in the development of WCO biodiesel as a viable sustainable fuel source through the use of a CFD model, optimized engine configuration, and technical report

Facile synthesis and characterization of CeMoO4 nanostructure via co-precipitation method and investigate its application supercapacitor

Abstract- Here in, CeMoO4 nanostructure were successfully prepared by a co-precipitation route without capping agent. The characterization and morphological of as-prepared samples were examined by Fourier transform infrared spectroscopy, filed emission scanning electron microscopy, X-ray diffraction, and energy dispersive X-ray spectroscopy. SEM and XRD results show that CeMoO4 nanostructure obtained with average nano-plate thickness 30 nm and average crystal size of 10 nm. The evaluations on CeMoO4-based electrodes revealed the material to have a specific capacitance (SC) of 327 F g�1 at a scan rate of 2 mV s�1, an energy density of 24.5 W h kg�1, and a high rate capability. Continues cyclic voltammetry evaluations using CeMoO4-based electrodes proved the electrodes to be capable of maintaining almost 96.3 of its initial SC after 4000 cycles. To the best of our knowledge, this study is considered as the start point of using lanthanide molybdates as an electrode materials for supercapacitors and the results obviously consent to outstanding properties of CeMoO4 for the mentioned application. © 2019 by CEE (Center of Excellence in Electrochemistry