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Landslides are natural disasters that annually inflict great damages to public and private properties which may associate with loss of life. In recent decades, research on developing methods for predicting the time of landslide has been one of the significant attempts made by scientists. Since in some type of material, landslides are preceded by undetectable movements that cannot be recorded and revealed by conventional instruments, recording the chemical changes of the water flowing out from the toe of the slopes susceptible to sliding can provide important and reliable indicators of landslide activities and early warning. In this study, changes in the chemical composition of water seeping out from the toe of an active landslide were investigated. This process was studied in a laboratory physical model, in which a sliding surface was simulated and the changes in the ion concentration of potassium (K), sodium (Na), magnesium (Mg), calcium (Ca), sulfate (SO₄), chlorine (Cl), and bicarbonate as well as EC and pH in both stable state and in the conditions of slight rupture along the sliding surface were investigated. The results indicated that the appreciable chemical changes in the outflowing water, particularly changes in the concentration of some ions, could be used as suitable indicators for early warning of the landslide occurrence.

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Background: Nosocomial infections have high mortality rates because of infective organisms' specific characteristics and the type of patients identified with different comorbid diseases. The aim of this study was to determine the prevalence rate  of different microorganisms and their characteristics in terms of resistance to various antibiotics.
Materials and Methods: Samples of urine, blood, abscess and wound secretion, and septum or tracheal secretions were cultured for 139 patients who were hospitalized during September 2012 to September 2014 and identified with nosocomial infection in different hospital wards. Then the type of microorganism and their antibiotic resistance were determined for each patient using culture antibiogram with disk diffusion method. Results were then analyzed using SPSS software.
Results:  The incidence of nosocomial infections was observed more in men than in women. Fever and purulent discharge from the wound site were the most common symptoms, leading to patient's hospitalization. Most patients were from the transplant and urology wards. Urinary tract, skin, and soft tissue infections (SSTI) had the highest prevalence rate in patients. Escherichia coli was the most common infectious microorganism in patients, which was sensitive to imipenem and meropenem. Kelebsiella as the next most common infectious microorganism was resistant to imipenem.
Conclusion:  The results of this study are consistent with the previous studies. Due to infectious microorganisms' resistance to antibiotics, it is recommended to reduce the consumption of antibiotics. 

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Aim: On the evening of April 1, 1998, in Farsan city, Chaharmahal and Bakhtiari Province, western Iran, the southern edge of the valley of Mt. Kino, along the Labad river, slid down into the river valley, where the moved material sloshed up over hill on the opposite river bank to bury Abikar village. This event followed an exceptional rainfall exceeding 190 mm during a week. In this research, the unexpected behavior of the landslide, the possible causes of the long-runout of debris, and the probable mechanism of such movement are discussed.
Method: This disaster was investigated, we attempted to offer a schematic model for its occurrence using various field data such as structural geology, surface soil layers, local geomorphology, meteorological data, hydrology, and field evidence. The disaster claimed the life of 54 people, and 1300 livestock, and the destruction of 40 hectares of farmlands and orchids.
Finding: The remain of the disaster contains some extraordinary features such as the lack of debris or barrier across the river, high debris flow velocity, the transformation of some debris material by jumping into the far end of debris flow, and a severe air storm in front of the debris flow mass.
Conclusion: We suggest that, when a giant slab of rocks fell down from the opposite flank, the generation of debris avalanche and the formation of an air cushion underneath the debris could be one of the reasons that facilitate the long runout of detrital flows.


 

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One of the most important goals of optimal control of structures is the achieving the desired reduction in responses using minimal control forces. In many research efforts that have been studied over the past few decades in the field of active control, several control algorithms have been proposed that most of them calculates the required control forces by optimizing a second-order performance index. There are simplifying assumptions in formulation of these classic algorithms and constraints in mathematical optimization techniques that have been used in optimizing the performance index, for example, because of unknown nature of earthquakes, the LQR classic controller don’t consider the external forces such as earthquake excitation in calculation of control signal. This may make difficult to finding the optimal solution in optimization process and obtained relatively optimal solutions for optimization problem. Metaheuristic optimization methods, such as differential evolution are modern algorithms and because of their special capabilities in finding global optima are powerful tools that can be used in solving of complex problems. But despite the many advantages, these methods has not been used extensively for solving civil engineering problems especially in field of active control of structures. In this paper we considered the active control of structures as an optimization problem and proposed a controller that used the differential evolution metaheuristic algorithm for finding gain matrix elements of active control problem. The gain matrix elements were globally searched by differential evolution algorithm to minimizing the LQR performance index. Because of the proposed method is repetitive and does not need to solve the Ricatti differential equation; it is possible to consider the effect of external excitation in finding the gain matrix and calculation of control signal. The controller was applied on sample 2DOF and 10DOF structures and responses of these structures under the excitation of several historical earthquake records were obtained by MATLAB programming. In addition to the performance index, the maximum control force and maximum control displacement, 9 benchmark indexes that measured in controlled structures are calculated in this study. These indexes represented the reduction of controlled maximum and average responses of structure in comparison with uncontrolled responses. In order to evaluate the effectiveness of the proposed controller, these 9 performance index for 2DOF and 10DOF examples against 7 historical earthquakes for proposed and LQR controller was calculated and compared. The simulation results indicate that the proposed method is effective in keeping the controlled responses of structures in desired range and reducing the vibrations of structures with lower need to control energy in comparison with LQR algorithm. Because of great capabilities of DE algorithm in searching large spaces and the iterative nature of controller unlike the LQR method, this controller consider the effects of external forces in control process. Numerical simulation showed that the performance of the presented control algorithm is better than the LQR controller approach in finding of optimal displacements and control forces. Therefore, metaheuristic algorithms such as differential evolution can be used in active control of structures to achieving more efficient results in comparison with classic controllers.

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In recent years, increased pollution and traffic in urban has caused the development of underground transport. One conventional approach for urban tunnel ventilation is construction mid-tunnel shafts. These shafts are usually located in high-density urban areas and emissions from them can be harmful for the residents of adjacent buildings. The geometry of these shafts is determined so far based on taste and only for the purpose of compliance standards criteria for tunnel indoor air. In this paper, pollutant dispersion from different and conventional geometries of mid-tunnel shafts with the assumption of a taller downstream building was investigated for the first time. The results can help to reach a better design of these shafts and surrounding buildings to have healthier air for residents of buildings. For this purpose, simulations were done by OpenFOAM. Reynolds-Averaged Navier-Stokes equations method and standard k-ε model were used in simulations. The results showed for the same exhaust velocity, the effect of rectangular and square configuration on front wall depends on dimension of the side which is perpendicular to wind direction. For the exhaust velocity less than 6 m/s, the downstream building prevents pollutants to reach higher altitude and the amount of pollutants will be increased around 100 percent and for exhaust velocity of more than 6m/s, increasing velocity will cause to less changes in pollutant concentration at lower level. In addition, the results showed that exhaust velocity has more effect than geometry configuration on pollutant dispersion and this influence will be decreased by increasing the velocity.

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Non-destructive damage detection methods analyze the output data collected from sensors to track the changes in the dynamic characteristics of the structure and detect the occurrence of damages. continuous recording and analysis of data to be aware of its safety and serviceability requires a network of sensors that are selected optimally and intelligently. Saving the cost of equipping the structure with this optimal sensor network, along with reducing damage detection error, has turned the issue of selecting the number and location of sensors into an optimization problem from an economic and functional point of view. Model order reduction methods along with optimization tools can play an effective role in selecting the master degrees of freedom. These methods divide the degrees of freedom of the structure into two groups of master and slave degrees of freedom. The master degrees of freedom appear in the process of calculating the mode shapes and natural frequencies, and the slave degrees of freedom are excluded from the equations. Finally, using the transfer matrix, the complete mode shapes are calculated using the mode shapes of the master degrees of freedom. In this paper, considering the key role of modal parameter recognition in structural damage detection, the performance and accuracy of different methods of dynamical model order reduction in the optimal sensor placement problem was studied. The 2d truss stucture and two-dimensional shear frame are modeled and analyzed. The sensor placement should be considered in such a way that the mode shape identification is done with sufficient accuracy and proper recognition. One of the effective tools in order to achieve this goal is to use the capabilities of metaheuristic optimization algorithms along with the capability of dynamic model reduction methods in the stage of identifying the mode shapes and before identifying the damages of structure. Combining model order reduction methods with metaheuristic optimization algorithms so that the selection of appropriate degrees of freedom for sensor installation (master degrees of freedom) leads to the most accurate identification of structural modes shapes is one of the main objectives of this study. The objective functions selected based on modal assurance criteria (MAC) and Fisher information matrix (FIM) and the capabilities of multi objective particle swarm optimization algorithm (MOPSO) to achieve the optimal number and proper arrangement of sensors are used to better identify the structural mode shapes and proper arrangement of sensors and obtained for system identification purposes. The results report better performance of SEREP and IDC methods in selection of master degrees of freedom and identifying the mode shapes of 2d truss and shear frame structures. According to the modeling and analysis performed for optimal placement of sensors using different model reduction methods, it can be concluded that the improved dynamic condensation (IDC) method is more accurate than other methods in identifying shear frame mode shapes and gives a smaller maximum non-diagonal MAC matrix element. Also, as the number of sensors increases due to the addition of information to the Fisher matrix, the Fisher matrix determinant increases and second objective function decreases. On the other hand, by reducing the number of available sensors, a limited number of modes can be detected. In this case, the best way to receive the structural modal information would be to place more available sensors on the lower and upper floors of the shear frame. Eventually, it can be concluded that the use of IDC and SEREP methods to select master degrees of freedom for sensor installation leads to better identification of modal parameters of the structure. Therefore, the capabilities of these methods can be used to identify damage in structures with a limited number of sensors.