s. a. hosseini

In clinical trials, Computed Tomography (CT) is widely used for diagnosis and treatment guidance. With the increasing use of CT in clinical practice, the issue of high radiation dose has become a significant concern. One way to reduce the dose in CT is by utilizing sparse view imaging. However, sparse view imaging often leads to artifacts in the reconstructed images due to the lack of data. This paper aims to examine and evaluate image reconstruction methods to introduce effective algorithms for sparse view studies. Common image reconstruction algorithms such as Maximum Likelihood Expectation Maximization (MLEM), Algebraic Reconstruction Technique (ART), and Filtered Back Projection (FBP) were reviewed. FBP and MLEM algorithms perform well when there is complete data, but due to the high speed of the FBP algorithm, it is best suited for such cases. However, when data is limited, FBP performs poorly, leading to a comparison between the ART and MLEM algorithms. The results indicate that MLEM performs better in sparse view studies. Quantitative parameters such as Peak Signal-to-Noise Ratio (PSNR), Root Mean Square Error (RMSE), and Structural Similarity Index (SSIM) were evaluated to assess the results. The findings suggest that FBP and MLEM algorithms perform better when data is complete, while MLEM algorithm excels in sparse view studies.

Dynamic Positron Emission Tomography (PET) imaging has significant potential for extracting kinetic parameters of tracers, particularly the Ki parameter. This study evaluates the use of the Dual Time Point (DTP) technique to generate parametric Ki images from two 3-minute static PET scans. A simulation study was conducted using the XCAT phantom, generating six realistic heterogeneous tumors embedded in lung and liver tissues with various levels of [18F] FDG uptake. Parametric Ki images were generated and evaluated using Patlak analysis and a population-based input function (PBIF). Additionally, TBR and CNR parameters in SUV images and parametric images produced by DTP and full dynamic methods were compared and analyzed. The results showed a significant correlation (> 0.9) between the Ki parameter derived from DTP and full dynamic imaging methods. Moreover, the high TBR parameter in DTP images compared to SUV images (70% for lung tumors, 35% for liver tumors) indicates improved contrast and image quality. Consequently, DTP images can be a suitable alternative to complete dynamic PET and SUV images in clinical settings.

In this research, the behavior of a buried reinforced concrete tank against explosion has been investigated using Abacus software. The results of this study show that for this buried tank under explosion, the junction of the wall with the roof of the tank is most exposed to damage.

The paper reports the production of liquid fuels from waste plastics' thermal and catalytic pyrolysis, including polypropylene (PP), high-density polyethylene (HDPE), low-density polyethylene (LDPE), and polystyrene (PS). For this purpose, three different types of zeolites (4A, ZSM-5, and 13X) and Cu/4A, Cu/ZSM-5, and Cu/13X were used in catalytic pyrolysis. The acidity and textural properties of the catalysts are the main parameters in the decomposition of polymers. The order of acidity of the catalysts was as follows: Cu/13X> Cu/4A> Cu/ZSM-5. The main product of thermal pyrolysis was liquid, mostly linear heavy hydrocarbons, whereas catalytic pyrolysis by copper/zeolite catalysts produced liquid products containing more branched hydrocarbons at lower temperatures. The liquid products carried out analysis through the use of FTIR and GC/MS techniques. The results indicated the presence of paraffin, olefins, and aromatic hydrocarbons in the liquid products. It was also found that light liquid hydrocarbons and gaseous products were produced over Cu/13X (higher acidity, large pore size, and high surface area). For Cu/4A, Cu/13X, and Cu/ZSM-5 catalysts, the main liquid products of catalytic pyrolysis were in the range of diesel, gasoline, and kerosene, respectively.

Fire and explosion are often synergistic. A fire may occur after an explosion or a fire may occur first and then an explosion occurs. The consequences of a combined fire and explosion scenario about each component must be considered in the design or evaluation of the structure. The analysis of fire and explosion should be done together and the effects of one on the other should be carefully analyzed. In most researches and design guidelines, fire and explosion phenomena are investigated independently and their interaction is less considered. In this research, this issue is addressed and the fire after the explosion and the interaction and synergy of these two phenomena are studied together. The studied structure is a two-story steel structure with different occupancy (dwelling, office, etc.). which is subject to various explosions and as a result fire caused by the equipment inside the building. Explosive loading has been calculated using UFC 3-340-02 instruction charts and fire load using the concept of fire density and relationships of EUROCODE 1 and EUROCODE 3 regulations. In order to simulate explosive and thermal loading, Abaqus finite element software and combined thermal-deformation dynamic analysis have been used. The temperature caused by the fire has been used as a natural fire, and the cooling and post-cooling stages of the fire have also been investigated. After validating the proposed simulation with two valid laboratory works, the analysis of the structure's response against various types of explosive loads and subsequent fires was performed by a numerical model. The results of these investigations showed that the response and deformation of the structure in the chain combined analysis (applying the interaction of explosion and fire on the structure) compared to the independent combined analysis (independent analysis of the structure against explosion and fire and collecting the responses together) It increases by 15%, and considering the interaction of explosion and fire is not only important but also necessary, and not considering this interaction in most cases will cause the response of the structure to be less than the reality, and as a result, it will cause an unsafe design.

The impacts of nanoparticles in radiation therapy have been investigated during the recent decades. The present study was conducted with the aim of investigating the effect of different physical interaction models on dose calculations using gold, hafnium and gadolinium nanoparticles. A nanoparticle with a diameter of 50 nm was simulated in a cubic water phantom and irradiated by protons with the energies of 5, 50 and 150 MeV using Geant4 Monte Carlo toolkit. The current study has considered various parameters, including the energy spectrum of secondary electrons and photons, radial dose distribution (RDD), dose enhancement factor (DEF), around the nanoparticle with three different materials and two physical interaction models. The obtained data showed that for gold nanoparticles, the Penelope model generated a greater number of secondary electrons than the Livermore model; however, for the other two nanoparticles, the Livermore model produced a greater number of secondary electrons than the Penelope model. In the RDD graphs, the Penelope model presents a 10% difference compared to the Livermore model up to a distance of 6 nm from the nanoparticle’s surface (along the radial axis in water). Furthermore, the Livermore model indicates a 16% and 10% increase in dose compared to the Penelope model up to a distance of 9 nm from the surface of hafnium and gadolinium nanoparticles, respectively. In the case of DEF, the dose deposited around the gold nanoparticle was increased by 14, the highest amount compared to DEF of hafnium and gadolinium nanoparticles which is 10 and 6, respectively

In this study, using the MCNP Monte Carlo code, the gamma-ray protection properties of the glass system with the composition of (55-x)Bi2O3-15Pb3O4-20Al2O3-10ZnO-xTiO2 with certain concentrations (35, 30, 25, 20, 15, 10, 5 = mol percent) were examined by calculating the several parameters related to photon attenuation such as half-value layer (HVL), mean free path (MFP), mass attenuation coefficient (𝜇m), effective atomic number (Zeff) and buildup factor (BF) for different energies in the range of 1500-100 keV. To verify the simulation results, a comparison was made with the XCOM database. It was observed that the data extracted from the NIST-XCOM database and the MCNP simulation results are in reasonable agreement with each other. The percentage deviation (PD) between the data extracted from the NIST-XCOM database and the results obtained from the MCNP simulations was less than 0.59% in most cases. The results show that compared to conventional protective materials such as concrete and lead, the new composition shows more effective attenuation parameters in addition to physical properties. The glass with the highest concentration of TiO2 has the most favorable properties in terms of density compared to the investigated protective materials. In this study, one of the variance reduction methods was used in order to reduce the error in MCNP calculations. The agreement between the data extracted from the NIST-XCOM database and the results of the simulations of this study shows that Monte Carlo modeling is an effective method to investigate gamma-ray shielding characteristics.

Aggressive environment reduces the mechanical and durability-related properties of concrete. In this study, the effects of exposing the concrete containing crumbed tire rubber (CTR) to aggressive environmental conditions, including hydrochloric acid (HCl) is investigated. For this purpose, 5, 10, and 15% of the fine aggregate of the mixing design were partially replaced with the CTR, and then at the age of 7 days, when the concrete reached almost 70% of the initial strength, the samples were placed in water containing 2% HCl for 28 and 90 days. In this study, the effect of using Nano-SiO2(NS) in the rubberized concrete and its behavior in acidic environments by replacing 5 and 10% by weight of cement with NS was also studied. Compressive strength and mass loss were evaluated at 28 and 90 days after casting. The results showed that the detrimental effects of HCl on the compressive strength of concrete significantly increased with an increasing in CTR content of concrete. The results also indicated that the impact of HCl acid on mass loss is improved by increasing the percentage of CTR so that the sample with the 15% crumbed tire showed a 7% lower weight reduction than the control sample.

Collapsible soils pose significant challenges due to their open structure, which causes settlement when exposed to moisture. Failure to identify these soil types can lead to structural damage when they become saturated or experience changes in moisture content. The presence of such soils in various regions, including Iran, necessitates greater attention and investigation into their behavior and properties. This study examines the impact of butadiene rubber on the stabilization of these soils. Fine-grained soil samples were collected from two different sites in Kerman province (Kerman City). The samples were injected with 2%, 3%, 4%, 5%, 6%, and 7% butadiene rubber for stabilization periods of 4, 7, 14, and 28 days, resulting in a total of 72 tests. The stabilized soils were evaluated using a double consolidation test (ASTM D5333) on intact soil samples. The penetration of butadiene rubber and the resulting rubber columns reduced the degree of collapse. In all cases, the collapse was reduced by more than 88%. The highest reduction was observed with a 7% additive after 28 days of stabilization. Given the increasing use of intelligent systems in predicting the behavior of stabilized collapsible soils, a model was developed to predict the degree of collapse for samples stabilized with butadiene rubber using an adaptive network fuzzy inference system (ANFIS). The accuracy of the model was evaluated, and it successfully predicted the collapse degree. Addition of styrene butadiene rubber additive in the tested soils led to a decrease in the plasticity index of clays with high liquid limits and an increase in the plasticity index of silts with low liquid limits. These changes varied depending on the mineral type. Subsequently, a model was developed to predict the plastic properties of the soil using a fuzzy inference system. The results demonstrate acceptable consistency between the training and prediction data (R2=0.93).

Managing Hyrcanian Forests in Iran requires a well-designed and constructed network of roads that are appropriately distributed and aligned with the silviculture method. These roads enable access to protection, support, and tourism activities, as well as facilitate the execution of all necessary measures. Around 10,000 kilometers of roads have been built in Iranian forestry projects. Constructing roads in forests has both positive and negative consequences on nature and its natural functioning, including impacts on biodiversity, grass and plant cover, and physical and chemical soil properties. The design and construction of these structures should adhere to the principles and technical-engineering standards of forestry to minimize adverse reactions. To ensure compliance with road construction technical instructions (Publications 131 and 148 of the technical deputy in the Management and Planning Organization of Iran), it is recommended that the Natural Resources and Watershed Management Organization of Iran supervise their implementation in all forest areas, alongside forestry plans. Furthermore, the organization should increase its direct supervision of the country's entire natural resource field to improve project outcomes.

In recent decades, geomatics science has made significant progress, and these advances are due to advanced measurement tools and innovative technologies in the field of geometric and spatial data acquisition. In this context, mobile laser scanners have been introduced as a basic and efficient tool that has the ability to perform accurate and fast measurements of various objects and environments, including urban spaces. These devices automatically record all the details of the urban space in the form of point cloud. To extract the geometric information of buildings from these details, it is necessary to use machine vision methods. In order to achieve accurate and reliable models of buildings, a sequence of post-processing operations is implemented when processing point cloud data. One of the most important stages of these processes is the segmentation of point cloud. These steps transform point cloud data into more conceptual and analyzable information. One of the important issues in processing point cloud data is the ability to extract planar surfaces of building facades (walls). These planar surfaces are of special importance as basic components in modeling and analyzing the condition of buildings. Accuracy in the information related to these planar surfaces allows for a more accurate and complete distinction between different components of buildings. This is important in several applications including urban planning, construction management, and energy consumption analysis of buildings.

In this article, MSAC and G-DBSCAN algorithms are used to extract planar surfaces from point cloud data. These two algorithms are executed sequentially. First, the most probable planar surfaces in the study area are extracted using MSAC, and then G-DBSCAN is used to separate the walls from these planar surfaces. In this article, the GeoSLAM ZEB-HORIZON mobile laser scanner device is used to collect data, and the area chosen for this purpose is the buildings of the Faculty of Engineering of Bo Ali Sina University in Hamedan. Because this place has features such as architectural diversity, the presence of non-planar and planar facades, different positions of the walls relative to each other with different dimensions, and challenges related to the diverse architecture of the space around the buildings.

Comprehensive evaluation of this research that includes three separate buildings. The results show an average precision of over 93%, which guarantees accurate data extraction. In addition, it has achieved an average recall of over 94%, which captures the majority of elements in the view. As a result, F1 score with an average value of 94% has been obtained. This research contributes to the progress in the field of accurate building data extraction and architectural modeling. Of course, when dealing with buildings and more complex environments, the algorithm faces challenges. Among the challenges that can be mentioned are various architectural features of buildings and external obstacles. For example, in buildings with large glass doors and windows, these algorithms may incorrectly extract interior walls. Also, the presence of dense vegetation around the facade can create obstacles that hinder the laser scanner's ability to fully capture the facade.

However, the results show that the algorithm in general was able to provide a significant performance in extracting the facade information of buildings, especially in challenging architectural scenarios. These developments are promising and create new possibilities in the field of spatial data analysis and building modeling. This innovative approach can be used in various applications and help to develop modern and data-based architectural models.

 Tomato, scientifically known as Solanum lycopersicum L., belongs to the Solanaceae family and is susceptible to various diseases, resulting in reduced yield. Among the diseases, the Tomato spotted wilt virus (TSWV), which belongs to the Tospovirus genus and Bunyaviridae family, causes significant damage to tomato crops and other greenhouse plants. Therefore, it is crucial to find ways to increase plant resistance and control viral infections. One effective method is through proper plant nutrition, which can enhance plant resistance by balancing fertilizer consumption and nutrient supply. Iron (Fe) is an essential element for plants and plays a significant role in increasing their tolerance to various stresses. In Order to evaluate the interaction effects of Tomato spotted wilt virus and Fe on some biochemical traits of Mobil and RioGrand tomato cultivars, a study was conducted in Birjand Faculty of Agriculture.

 Experiment in a Random complete design with greenhouse conditions, with 3 replications and 4 treatments Done. Experimental factors include cultivar with two levels (Mobil cultivar and Rio Grand cultivar) and Fe foliar application in the presence of virus with these three (zero, 1.5 and three milliliter of Fe fertilizer per liter of water). First, two varieties of RioGrand and Mobil tomato seeds were prepared and planted in seedlings. Then, in the two-leaf stage, they were transferred to pots filled with sterile soil and kept in greenhouse conditions. After seedling establishment, the first foliar application of Fe fertilizer was done and in the five to seven leaf stage, the virus was inoculated on all leaves. Then, the second stage of fertilizer was applied 10 days after the first fertilizer and finally, after the last stage of foliar application, the samples were transferred to the laboratory. In Order to accurately investigate the effect of Fe on important plant factors, extracts were taken from the samples. Then, the amount of antioxidants, carbohydrates, Flavonoids, Chlorophyll (a, b and total chlorophyll) and phenol was measured. Finally, the final data analysis was performed using SAS statistical software.

 The results showed that the simple effect of cultivar on the amount of phenol and flavonoids was significant at the level of one percent and the highest amount of phenol was recorded in Mobil cultivar and the highest amount of flavonoids was recorded in RioGrand cultivar. The effect of treatments on chlorophyll a, total chlorophyll index and antioxidant enzymes was significant at the level of 1% probability and carbohydrate content at the level of 5% probability. The results showed that feeding Fe at a concentration of 1.5 milliliter had a favorable effect on carbohydrate content and increased its amount in infected plants compared to control plants. This Increase effect may be useful for improving tolerance in a variety of tomatoes. According to the results, an increase in foliar application concentration to 3 milliliters led to a decrease in carbohydrate levels. Mechanical inoculation with a positive sample of the virus resulted in plant contamination. However, virus infection increased carbohydrate and antioxidant enzyme levels in tomatoes. The effect of cultivar on treatment was only significant in the amount of antioxidant enzymes at a one percent probability level, with the Mobil cultivar showing the highest response to virus infection treatment. Therefore, it can be concluded that a concentration of 1.5 milliliters of Fe fertilizer could be effective in increasing carbohydrate levels, as well as utilizing enzymatic and non-enzymatic antioxidant components to prevent viral penetration to some extent and reduce symptoms, particularly in the Mobile cultivar. However, the RioGrand cultivar produced less antioxidant components. Different cultivars of the same plant species have been reported to have varying responses to different types of infections, such as viruses, fungi, and bacteria. These differences are attributed to genetic variations among cultivars, which leads to different resistance mechanisms.

 The final results showed that in the early stages of greenhouse tomato growth, Fe nutrition had an effect on the biochemical properties of the plant and had a positive effect on some traits. In total, Fe fertilizer with a concentration of 1.5 milliliter increased carbohydrates in plants infected with Tomato spotted wilt virus and together with phenol and antioxidants affected the spread of the virus, especially in Mobil cultivar.

In the present study, the corrosion behavior of projection friction stir spot welding of 2024 aluminum alloy has been investigated and compared with the corrosion behavior of the base metal. Welding of sample was performed with the rotation speed of 2500 rpm and the dwell time of 12 seconds. The penetration depth of the tool on the surface of the sample was 0.1 mm, the diameter of the tool was 16 mm, and a circular protrusion with a diameter of 10 mm and a height of 0.4 mm was placed below the working table. By using Tafel polarization test method and standard Scanning Kelvin Probe through potential chang of weld surfaces and base metal as well as chang in corrosion current density, the corrosion behavior of projection friction stir spot welding was investigated. The results showed that the corrosion potential of the weld area is reduced compared to the base metal, although this reduction has not led to a significant increase in corrosion current density. Also, the welding zone has higher corrosion current density than the base metal region.

The phenomenon of progressive collapse is very important in the management of structures as well as the discussions related to passive defense. Due to the increasing terrorist threats in recent decades and the prevalence of such issues, this phenomenon has become more pronounced. The soil-structure interaction is also a new science in civil engineering. The structure behavior changes due to interactions with the soil and the literature review reveals various methods that have been presented for modelling this phenomenon in recent years. The main problem of the present study is to determine the critical column in the phenomenon of progressive collapse in steel flexural frame by considering the effect of soil-structure interactions with both the direct and indirect methods. The phenomenon of progressive collapse in the present study has been done with the help of column deletion scenario. In addition, the effect of soil-structure interactions has been modeled using the two direct and indirect methods in both Sap and Plaxis software. The two-dimensional steel frames are made for 5, 10, 15 and 20 story structures and are analyzed by the nonlinear static analysis and examined by the corner and middle column removal scenario. Various parameters such as the coefficient of behavior, base shear, displacement of the operating point and top of the node displacement are removed and the expansion of plastic joints are proposed as evaluation indicators. The results of the present study shows that the corner columns are in a more critical condition and the effect of soil-structure interactions in the direct method is much more significant.

Over the past few decades, computed tomography (CT) imaging has been merged as one of the leading cross-sectional imaging techniques in a wide range of clinical applications in diagnostic radiology, oncology, and multimodal molecular imaging. Despite the recognized value of this imaging modality, the quality and accuracy of CT images can be compromised by a number of implants. The presence of metal objects such as dental fillings, hip or knee prostheses, heart pacemakers, war fragments, and spinal cages can cause severe image artifacts. These types of artifacts appear as black and white streaks in the CT images, obscuring the structures and tissues around the metal implant which decreases the diagnostic values of the images. Metal artifacts also affect the accuracy of radiation therapy treatment planning, which relies on X-ray images to determine electron density and estimate the relative stopping power of particles. In this regard, different algorithms of the Metal Artifact Reduction (MAR) have been proposed over the decades to address this issue. In this study, five commonly used MAR algorithms in clinical practice have been evaluated using simulated and clinical datasets. These algorithms include linear interpolation (LI_MAR) of the degraded data in the sinogram space, reduction of metal artifacts by normalization method (NMAR), metal deletion technique (MDT), Orthopedic metal artifact reduction (OMAR), and a method based on iteration algorithms (MAP). Clinical CT images in different anatomical regions of the body, with different dimensions and types of metal implants, have been studied to evaluate the performance of the MAR algorithms. In order to quantitatively evaluate the quality of CT images corrected by the different MAR algorithms, the Normalized Root Mean Square Error (NRMSE) metric was employed. The quantitative analysis demonstrated the overall superior performance of the NMAR algorithm in effective metal artifact reduction compared to the other algorithms. The NMAR method exhibited relatively less signal distortion and reasonable processing time which make it a dependable solution in clinical practice.

In this study, we used the Monte Carlo-based software, GATE, to model the spot scanning proton therapy system (SIEMENS IONTRIS spot scanning dedicated nozzle) installed at the Shanghai Proton and Heavy Ion facility. Within the nozzle, apart from entrance and exit windows and the two ion chambers, the beam traverses through the vacuum, allowing for a convergent beam downstream of the nozzle exit. We model the angular, spatial, and energy distributions of the beam phase space at the nozzle exit with single Gaussians, controlled by eight energy-dependent parameters. The parameters were determined from measured profiles and depth dose distributions. Verification of the beam model was done by comparing measured data and GATE acquired relative dose distributions, using plan specific log files from the machine to specify beam spot positions and energy. The MC simulations showed good agreement with measurements for the depth-dose curve and SOBP plans. The absolute comparison of the absorbed dose difference between the MC and the measurement was ±1%. This work describes a method for adapting a MC simulation model for a spot scanning proton delivery system. The excellent agreement between the measurements and simulations shows that the MC modeling in this work is a precise and reputable method.

Thespot-scan based methods are expected to perform better than other methods for proton therapy in delivering the dose to the intended target. In this study, the GATE computer code is used to evaluate important dosimetric quantities in proton therapy, such as Full width at half maximum, peak position, range and peak-to-entrance dose ratio (percentage depth dose) in the proton therapy process under the same conditions based on spot scanning and passive scattering. Water phantom was selected and system energy parameters were measured using a set of depth-dose curve in the energy range of 120 to 235 MeV. Bragg peaks were generated with an accuracy of 0.7 mm in range. Spread out Bragg-peak were produced with 7 cm modulation and 10 mm range accuracy and peak-to-entrance dose ratio difference at an input dose of 8%. To evaluate the versatility of the beam, the Full width at half-maximum was evaluated with a maximum difference of 7% between the two methods. As a result, based on the simulations performed for different beam delivery systems, the ability of the spot scanning method in adapting to the target volume, better control over dose distribution and less extra-tumor dose was demonstrated.

To investigate the effects of mycorrhizal fungi on growth characteristics, physiology, and essential oil yield of thyme (Thymus vulgaris L.) under lead (Pb) stress, a factorial experiment was conducted in a completely randomized design with three replications in the research greenhouse of University of Mohaghegh Ardabili (UMA) in 2018. Experimental treatments included different levels of Pb heavy metal (0, 200, and 400 ppm) and inoculation with mycorrhizal fungi (without inoculation, inoculation with Funneliformis mosseae, and Claroideoglomus etunicatum). The results showed that in comparison with the control, with increasing Pb concentration in the soil, plant height (40.56%), number of leaves (36.09%), stem dry weight (43.50%), essential oil percentage (40%), and cell membrane stability (16.14%) were significantly decreased, while proline content (51.72%) and catalase activity (45%) of the leaves increased. Inoculation of thyme with the mycorrhizal fungi was effective in increasing the vegetative indices in presence of Pb heavy metal so that both G. mosseae and G. etunicatum increased the number of leaves by 66.20 and 9.55% compared to the control, respectively. Also, inoculation with G. mosseae under severe Pb stress conditions (400 ppm) increased leaf proline content (11.49%), peroxidase enzyme activity (8.8%), chlorophyll b (21%), total chlorophyll (70.43%), carotenoids (19.6%), and essential oil percentage (55%) compared to the control. Overall, both mycorrhizal fungi were effective on alleviation of Pb toxicity effects and F. mosseae had better performance, especially in terms of morphological traits and essential oil yield. Due to the negative effects of heavy elements on human health, the recommendations to use mycorrhizal fungi to reduce the absorption of heavy metals in plants should be done with more consideration of all aspects including the plant and fungus species type and rate and pollution type.

The aim of this study was to investigate the effect of diet supplementation with bindii (Tribulus Terrestris), carob (Ceratonia siliqua) and ginger (Zingiber Officinale) on semen quality and fertility potential of rooster breeders. In this experiment, 30 roosters were assigned into 6 equal groups and fed the following diets during 30 days: 1) the base diet, 2) diet containing bindii, 3) diet containing carob, 4) diet containing ginger, 5) diet containing bindii and ginger, 6) diet containing bindii and carob. Semen samples were collected via abdominal massage once a week and the following parameters were evaluated: semen volume, number of spermatozoa, sperm motility, membrane integrity, morphology, viability and fertility potential. In result, diet supplementation with herbal additives in treatments received groups improved sperm quality and fertility potential compared to control group (P≤0.05). In conclusion, using herbal additives in rooster diet could be an effective method to improve rooster sperm quality and fertility potential.

Using machinery wood extraction in steep slope in the Hyrcanian forests can increase the soil bulk density and soil compaction, decrease the infiltration water into soil of skid trail, which results in an increase runoff and soil loss and has detrimental effects on soil nutrients loss and sedimentation into the downstream infrastructure. The aim of this study was to investigate the optimal distance of water diversion in skid trails to mitigate sthe ediment and runoff in compartments 315 and 316 of Gorazbon district in Kheyrud forest. In this study, 9 plots with length of 20, 30 and 40 m and slope gradient of 15, 25 and 35% were established along the longitudinal slope of the skid trails. A tank was installed to collect runoff at the outlet of each plot. Also, runoff in each rain event as well as soil bulk density, moisture content, organic matter, and soil texture of the plots were measured. The results revealed that the optimal distance among water diversions in the skid trails to suppress the runoff was 30 m and the most appropriate slope for mitigating runoff on the skid trails was up to 25% slope gradient. Runoff had a significant relationship with plot length. The results showed that the amount of rainfall was significantly correlated with runoff at different lengths and slopes. Therefore, it should be avoided to plan the skid trails on steep slopes for mitigating runoff, and some engineering measures such as the installing water diversion structures (by length of 30 m and slope gradient of 20-25%) to decrease the runoff should be done.

Reinforced Concrete (RC) buildings are a common type of structure. Dual systems (containing RC shear walls and moment resisting frame), and moment resisting frame systems are the most common types of RC buildings in Iran. Some researchers have studied the seismic reliability of bridge structures using field data. However, in Iran, real field data is not used to analyze the reliability of RC buildings. In this study, reliability analysis is used to assess the failure of non-structural members in the RC buildings. The probability distribution of the concrete and steel bars strength is gathered by using field tests. The tests were done in 110 RC buildings in Tehran. Afterward, a series of time history analysis were done to determine the probability of failure in non-structural members. Monte Carlo sampling is used for reliability analysis. The reliability of two common RC structural systems are compared under different earthquake records. It is found that the dual system can have a better performance under seismic excitation and it can reduce the damage in an earthquake.

The availability of current AC electrical power is essential for the safe operation and accident recovery of commercial nuclear power plants. Loss of offsite power (LOOP) considers as one of the significant post-Fukushima accidents. When the onsite diesel generators are not recovered in the power plant, the accident encounters with station blackout (SBO) situation. In this study, the emergency AC power recovery is investigated during SB-LOCA along with LOOP accident for 25 mm, 50 mm, and 100 mm breaks with RELAP5 thermal-hydronic. Likewise, in evaluating the emergency power recovery scenario, the power plant's recovery in the first and second hours has been investigated. The results showed that in the first hour of emergency power recovery, the reactor is not reached the core damage threshold in all three breaks. Meanwhile, in the second hour of emergency power recovery for 25 mm and 50 mm, the reactor core reaches to core damage threshold before the emergency diesel generators are activated. Therefore, the results show that in SB-LOCAs with a lack of emergency power recovery, there is a chance to recover emergency power and safety systems at least until the first hour.

This study aimed to compare the accuracy of artificial neural networks (ANNs) in estimating the weight of broilers using video image processing technology. A total number of 900 broiler chicks from three different strains (Ross 308, Cobb 500, and Arbor Acres) were fed on commercial diets and reared under standard situations for 42 days. Thirty male and female chicks from each strain were weighed randomly using digital scales every day while simultaneously filmed from top view using a Xenon camera (2MP 1080IP lens). In image processing, digital images initially were extracted from films and then each image was processed using GUI of MATLAB software. Sixteen morphological features extracted from images that significantly correlated with the chicks' weight, were used as inputs of the artificial neural network, and multilayer perceptron ANN was trained to predict the weight of chickens of each strain via an error propagation algorithm. The procedure was the same for all three strains. The accuracy of ANN models to predict the weight of chicks were 98.4% (with an average error of 7.9 g), 99.54% (with an average error of 0.37 g), and 99.67% (with an average error of 2 g) for Ross, Cobb, and Arbor Acres strains, respectively. In conclusion, a comprehensive intelligent model can be designed based on artificial neural networks and video image processing technology to estimate the weight of broiler chickens regardless of their strain type.

Conventional analysis and design of reinforced concrete beams under blast load requires a long process. In addition to being time consuming, this method does not determine the extent of the influence of the geometric parameters of the beam and the load. To overcome this problem, in this research, the effect of each parameter is investigated using the mathematics response surface method (RSM) and a direct relation is provided to calculate the beam deflection. A large number of reinforced concrete beams under different explosions were examined in finite element software. The proposed finite element model was validated by a reliable experiment. The rises obtained from reinforced concrete beams were evaluated as input in Design expert software in four models. In each of these models, a relationship was obtained as the beam deflection relationship. By evaluating each of these relationships, the results showed that the cubic RSM model provides the highest accuracy for the beam deflection.

Forest road construction is one of the activities that not only cause a lot of changes in the plant and animal species of forest ecosystem, but also, due to its widespread use in forest management, it is one of the most important projects that should be assesed. The aim of this research was to evaluate the environmental, social, and economical impact of Dohezar road of Tonekabon in the three stages including; before, during and after the road construction. In this study, the Geocybernetic Assessment Matrix (GAM) method, which is the latest method of evaluating effects, was used. In GAM, the parameters selected or determined by the evaluation criteria were examined according to the three aspects of environmental, social and economic. The results showed that the total geocybernetic score before road construction, during road construction, and after road construction was similar (before road construction: -13.33; during road construction: -80.78, and after road construction: -36.47), indicating that the construction of the Dohezar road had negative effects, especially during construction, but social and economic services, especially in the after road construction, have kept the total geocybernetic score constant. By implementing the GAM evaluation method, a suitable tool is obtained to ensure the proper implementation of the project or to stop it, which can be considered as a way to determine, predict and interpret the environmental, social and economic effects of the road construction project on the environment of the study area.