Search published articles
Showing 67 results for Momeni
Volume 23, Issue 2 (5-2023)
Abstract
Core testing is the most direct method to assess the in-situ concrete compressive strength in an existing structure, generally related to suspected construction malpractice or deficiency of concrete supply, to carry out the condition assessment of buildings before taking up repair and upgrading work. Although this test is quite simple to conduct, the results obtained may sometimes contain considerable errors because of the great variety of parameters involved. The general problems of core testing are well known. The factors including core diameter, length-to-diameter ratio (L/D), concrete age, aggregate characteristics, direction of coring and the moisture condition at the time of testing are known which affect the relationship between core strength and the corresponding standard cube or cylinder strength are fully reported by researchers. Another potential factor influencing the testing of cores is the presence of reinforcing bars within the core. The effects of the presence of steel bars on the strength of cores have been investigated by only a few researchers. Reinforcement bars passing through a core will increase the uncertainty of results and should be avoided wherever possible. Regression analysis and generalized GMDH network, whose structure is investigated using genetic algorithm and single-particle number optimization method for predicting the compressive strength of concrete using the results of coring tests with and without fittings. The form and ability of the multivariate linear regression models and the importance of regression coefficients based on the experimental data obtained for samples in two different processing conditions, in order to predict the cubic compressive strength of the concrete and using the input parameters including (1) the length to diameter ratio Core, (2) core diameter, (3) diameter, (4) number and (5) axial axial axis of the rebar in the core, (6) reinforcement of the rebar, and (7) core compressive strength as independent and input variables, as well as resistance Concrete pressure is evaluated as the response variable (or output of the models). This method is used for the GMDH neural network. The objective of the GMDH neural network method is to obtain a polynomial function that can be used to retrieve the output parameter by the input of the considered variables. The GMDH neural network can, after training, estimate the relationship between inputs and outputs in a polynomial, which depends on the accuracy of this polynomial on the data and structure of the network. The single-particle decomposition (SVD) method in the GMDH structure for the case where the number of equations is greater than that of unknowns, uses the least squares error method to solve such devices. The results showed that the models used have high ability to express the problem, since more than 95% of variations of response variables with fitted models in regression models and about 99% of changes in the response variable values in the GMDH model can be expressed. But in a comparative position, GMDH model with a general structure optimized with Genetic Algorithm and SVD has shown the best performance, with this superiority becoming noticeable, considering that about 75% of the data is involved in training the neural model. Subsequently, nonlinear regression models show a certain advantage over linear models.
Volume 23, Issue 3 (autumn 2023)
Abstract
Aims and Introduction:
No economic variable like inflation confronts the society with social, cultural, political and even national security disturbances. Inflation greatly reduces trust in the economic, social and political structure and causes a significant reduction in social control.
Therefore, it is reasonable that in the field of economic and social policies on a global scale, sensitivity is applied to the effects of economic policies on inflation. In looking at the issue of inflation from the level of development, for numerous reasons, no approach will have a high explanatory ability as the approach of political economy. The political economy approach to development is an ultimatum approach that identifies and analyzes the main root of problems by focusing on the final winners and losers of the flawed policy cycles in the economy. The main goal of this research is to explain why the economic policymaking field of Iran's economy tends to adopt inflationary policies from the perspective of political economy with emphasis on the level of development.
Methodology:
In this research, using the analytical approach of the political economy of development, we have looked for the reason for the adoption of inflationary policies and their continuation and strengthening in the Iranian economy during 1989-2019. In this research, using the analytical and descriptive method and official data, an attempt has been made to investigate why the will of economic policymaking in Iran tends to adopt has inflationary policies and to evaluate the effects of inflation on the radius of trust and social cooperation based on trust. This research focuses on cognitive aspect of the causes of inflation in Iran and relies on political economy of inflation.
Findings:
In this research, by correcting the view of the causes of inflation in Iran's economy, it has been tried to investigate why the will of economic policy-making in Iran tends to adopt inflationary policies, And the main question of the research was explained under the three axes of dominant culture of rent, wrong incentives for policy makers and political economy of interest groups.
Disregarding science and preferring everyday considerations, a specific mindset and benefit ruling the policy-making system and the discussion of the beneficial and unproductive groups whose interests are in line with unproductive policies, the bottlenecks of political economy and the wrong incentives of politicians in the field of political and economic are main causes of inflation persistency.
Discussion and Conclusion:
Finally, it can be concluded that with a correct inflation targeting logic, it is possible to design a plan under the title of production-oriented based on the reduction of corruption and the evolution of the reward system, along with ensuring the security of property rights. In fact, with the aim of focusing on the issue of production from two angles, changing the mechanism of the reward system and controlling corruption through reorganizing the mental and thought structures governing the society, especially the policy-making and decision-making system, we may move towards an institutional structure that promotes correct thinking in the policy-making arena. This idea comes out of the heart of that development; such a program definitely needs help from a correct logic of targeting in the policy field. The most important result of such program will definitely be the reduction of the general level of prices.
No economic variable like inflation confronts the society with social, cultural, political and even national security disturbances. Inflation greatly reduces trust in the economic, social and political structure and causes a significant reduction in social control.
Therefore, it is reasonable that in the field of economic and social policies on a global scale, sensitivity is applied to the effects of economic policies on inflation. In looking at the issue of inflation from the level of development, for numerous reasons, no approach will have a high explanatory ability as the approach of political economy. The political economy approach to development is an ultimatum approach that identifies and analyzes the main root of problems by focusing on the final winners and losers of the flawed policy cycles in the economy. The main goal of this research is to explain why the economic policymaking field of Iran's economy tends to adopt inflationary policies from the perspective of political economy with emphasis on the level of development.
Methodology:
In this research, using the analytical approach of the political economy of development, we have looked for the reason for the adoption of inflationary policies and their continuation and strengthening in the Iranian economy during 1989-2019. In this research, using the analytical and descriptive method and official data, an attempt has been made to investigate why the will of economic policymaking in Iran tends to adopt has inflationary policies and to evaluate the effects of inflation on the radius of trust and social cooperation based on trust. This research focuses on cognitive aspect of the causes of inflation in Iran and relies on political economy of inflation.
Findings:
In this research, by correcting the view of the causes of inflation in Iran's economy, it has been tried to investigate why the will of economic policy-making in Iran tends to adopt inflationary policies, And the main question of the research was explained under the three axes of dominant culture of rent, wrong incentives for policy makers and political economy of interest groups.
Disregarding science and preferring everyday considerations, a specific mindset and benefit ruling the policy-making system and the discussion of the beneficial and unproductive groups whose interests are in line with unproductive policies, the bottlenecks of political economy and the wrong incentives of politicians in the field of political and economic are main causes of inflation persistency.
Discussion and Conclusion:
Finally, it can be concluded that with a correct inflation targeting logic, it is possible to design a plan under the title of production-oriented based on the reduction of corruption and the evolution of the reward system, along with ensuring the security of property rights. In fact, with the aim of focusing on the issue of production from two angles, changing the mechanism of the reward system and controlling corruption through reorganizing the mental and thought structures governing the society, especially the policy-making and decision-making system, we may move towards an institutional structure that promotes correct thinking in the policy-making arena. This idea comes out of the heart of that development; such a program definitely needs help from a correct logic of targeting in the policy field. The most important result of such program will definitely be the reduction of the general level of prices.
Volume 24, Issue 3 (5-2022)
Abstract
The aim of this study was to design an Adaptive Neuro-Fuzzy Inference Mechanism (ANFIS) and a Polynomial Neural-Network (PNN) to improve modeling and identification of some climate variables within a greenhouse. Furthermore, a Stable Deviation Quantum-Behaved Particle Swarm Optimization (SD-QPSO) algorithm was employed as a learning algorithm to train the constant parameters of ANFIS and PNN structures. To denoise measured data, a wavelet transform method was applied to ensure that no measured data exceeds a predefined interval. Moreover, to show the modeling performance, a set of differential equations were derived as a dynamical model based on the computation of energy and mass balance in a specified greenhouse. The results of modeling and simulation were evaluated with the experimental results of an experimental arch greenhouse. The results showed that the proposed models were more accurate in predicting greenhouse climate and could be used more easily. Moreover, this study showed that the PNN model with less pop-size and evaluation function was more effective than the ANFIS structure to predict the temperatures of inside air and inside roof cover. In this study, an on-line identification system is also proposed for real time identification of experimental data. The obtained simulation results show that performance of the proposed modeling structures and identification system are effective to predict and identify the soil surface, internal air, and roof cover temperatures of the greenhouse. This study shows that the identification algorithm can be used to predict and confirm the results of the model.
Volume 24, Issue 3 (8-2024)
Abstract
In steel shear wall, to avoid nonlinearization of boundary elements, capacity-based design is performed, which results in a significant increase in the amount of steel used in boundary elements. To reduce the boundary element steel, a semi-supported steel shear wall (SSSW) has been proposed and its efficiency has been proven in previous studies. In addition, it seemed that the use of concrete coating on steel plates could improve the strength and ductility of the SSSW system. For this purpose, an 8-storey building equipped with SSSW was first designed and its most critical opening was converted to a composite model (SSCSW) and its finite element model was produced. This model was presented against near and far fault cycle loading analysis and cyclic curve, capacity, dissipation energy, von Mises stress distribution and compressive damage of concrete. The results showed that Adding concrete to the SSSW model (converting the model to SSCSW) increased the initial in-plane stiffness by 4.5 times. Of course, this increase in stiffness is not unexpected because of the concrete on both sides of the steel plate. A very important point is that with the creation of cracks in the concrete, the stiffness quickly decreases and the slope of the post yielding area of the capacity curve is first negative and then experiences a slight increase due to the strain hardening of the steel plate. By adding concrete to the steel model, the ductility increases in two states near and far from the fault. The size of the increase is about 2.5 times and this increase does not depend much on the type of loading pattern. Of course, it should be noted that in the models of this article, the effects of steel plate tearing have not been modeled, so the ductility calculated in this study is with real capacity.The ductility is different and requires more accurate supplementary models to obtain a more comprehensive result. In terms of ultimate strength (peak of the cyclic diagram), the comparison of the results shows that regardless of the type of cyclic loading pattern, the calculated value for SSCSW is 28% higher than SSSW. It should be noted that the increase obtained as a result of pushover loading was estimated at 35%. For the pattern near the fault, the transformation of the model from SSSW to SSCSW led to estimate 67% more cumulative wasted energy. This value was about 73% for the far-fault protocol. This difference can be justified by the fact that in the close protocol, there was a significant increase in the loading cycle at the beginning of the protocol, and the issue of low cycle fatigue is excluded. While for the loading corresponding to the far fault, the gradual increase of the loading protocol is associated with low cycle fatigue and the input energy is depleted in more cycles. It is suggested that the designer pays special attention to the main elements (frame columns) in the near-fault protocol. In addition, considering that a part of the beam between the sub-column and the main column can somehow evoke the behavior of the link beam, it is suggested to evaluate the nonlinear behavior of this part of the beam in the future supplementary studies.
Volume 25, Issue 1 (1-2023)
Abstract
Wheat is the main crop in the world. Tan spot caused by Pyrenophora tritici-repentis (Ptr) is a destructive disease in wheat-producing areas. Accumulation of phenolic acids at the onset of the fungal infection induces plant’s resistance to tan spot. This study evaluated the effect of phenolic compound accumulation on the resistance to tan spot in wheat–pathogen interactions. Five different wheat cultivars including Glenlea, Salamouni, Moghan 3, Morvarid, and Bolani were studied at three different time points after inoculation with Ptr. The composition and concentration of phenolic acid including ferulic acid, p-coumaric acids, vanillic acid, chlorogenic acid, and rutin were detected using high-performance liquid chromatography and analyzed according to standard curves. Results showed considerable accumulation of ferulic acid, p-coumaric acids, vanillic acid, chlorogenic acid, and rutin in treatment with Ptr during 7 days post-inoculation in resistant and partially resistant cultivars compared with the susceptible ones. Ferulic acid was the most abundant phenolic compound in Salamouni (16.77±0.16 mg g−1 dw), Moghan 3 (17.76±0.00 mg g−1 dw), and Morvarid (23.11±0.00 mg g−1 dw) at 7 dpi. The obtained data indicated that the identified phenolic acids had enhanced and improved the wheat resistance to the fungal pathogen. Linear Pearson’s coefficient analysis showed a positive correlation between some phenolic acids concentration and also between them and flavonoid rutin in wheat cultivars during infection. These findings highlighted the capacity of phenolic compounds as potential tools for the identification of resistance in wheat–pathogen interactions.
Volume 25, Issue 1 (Winter 2022)
Abstract
Background:
SARS-CoV-2 which first was observed in Wuhan region, China in December 2019 has affected many organs, such as central nervous system. We describe a case of a 57-year-old male patient, in the hospital with the loss of consciousness, in the form of lack of verbal and visual communication. He got a seizure attack for about 3 minutes in the form of generalized tonic-clonic seizure (GTS) and admitted to the neurological department and was intubated. Since, the patient was not aware, awake, did not obey, corneal reflexes test was positive and his pupils were isochoric and reactive therefore, the primary diagnosis was cerebrovascular accident (CVA). On the second day after admission, although the brain computed tomography (CT) did not show brain lesion, but the chest X-ray (CXR) revealed lung involvement. In addition, on third day the RT-PCR test for coronavirus RNA in and the cerebrospinal fluid and nasopharyngeal swap done and the result was positive for both of them. Therefore, treatment for the covid-19 was started.
Results:
Since, the treatment for the covid-19 was started with Atazanavir, Clindamycin and Ceftriaxone. Ten days after hospitalization, the lung involvement and general condition of patient got better and after two weeks he was released from the hospital.
Conclusion:
GTS should be considered as a neurological outcome of COVID-19 and medications against the coronavirus, such as Atazanavir, Clindamycin and ceftriaxone can recover the neurological deficits in these patients.