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In 2011-2012 surveys for phytoplasma diseases, eggplant )Solanum melongena L.( plants with phyllody symptoms were observed in eggplant fields of Roodan (Hormozgan province of Iran). Agent of Roodan Eggplant Phyllody (REP) was transmitted from phyllody affected eggplant to eggplant and tomato by grafting and to periwinkle via dodder inoculation inducing phytoplasma-type symptoms. Phytoplasmal infection also was demonstrated by positive direct PCR reaction with phytoplasma universal primer pair P₁/P₇ and nested PCR using P1/P7 and R16F2n/R16R2 primer pairs.A P₁/P₇ primed PCR product from a naturally phyllody affected eggplant was cloned and sequenced and submitted to GenBank under accession number JX464669. Restriction fragment length polymorphism (RFLP) analysis of P1/P7-primed PCR product indicated the presence of a pigeon pea witches'-broom (16SrIX) group related phytoplasma in naturally phyllody affected eggplants. Using 16S rRNA and SR sequences, Blast search, phylogenetic and virtual RFLP analyses and nucleotide homology percent revealed that REP associated phytoplasma is classified with members of 16SrIX-C subgroup. To our knowledge eggplant is reported for the first time as a host for a 16SrIX group related phytoplasma.

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The issue of "victimless crimes" or "consensual crimes" is a new issue, and at the same time a very important one in the realm of the studies regarding "victimology", as a now branch of criminal sciences. The novelty of the issue, specifically in the Iranian criminal law, its vagueness, and the relationship of victimless crimes with some criminal policy issues like criminal proceeding, criminal statistics, fear of crime, crime prevention and restorative justice reveal the significance of the point. This article deals with the most important issues in this regard, namely defining and realizing samples of this kind of crimes, in order to get a better understanding and recognition of the concept of "victimless crimes" or in other words "crimes without direct victim", and also to determine the samples of this kind of crimes. The article deals also with the basic elements mentioned in the definition particularly the triple elements, that is victim, damage and consensus Finally, the article examines the relation between morality and victimless crimes and compares them.

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Aims: This study aimed to investigate the impact of specific socio-economic factors and eating habits on attention, working memory, and academic performance among high school students.
Instrument & Methods: The sample of this quantitative study comprised high school teenagers aged 15 to 22 years from both rural and urban areas. Eating habits were assessed using a questionnaire covering student demographics and dietary behaviors. Attention and working memory were evaluated using the computer-based Rey complex figure (RCF) test, while academic achievement was determined based on students' overall grades.
Findings: The results revealed correlations between certain dietary habits and RCF test parameters. Specifically, we observed a correlation between breakfast consumption frequency and attentional performance (χ²=6.599; p=0.037), as well as working memory (χ²=6.053, p=0.048). Additionally, we found associations between weekly consumption of fish and attentional performance, as well as between the consumption of milk and its derivatives, Argan oil, and attentional performance. Furthermore, a correlation was observed between weekly fruit consumption and students' memory performance.
Conclusion: Our findings underscore the significant impact of dietary habits on students' attention and working memory capacities. Adopting healthy eating habits enhances these neurocognitive skills, thereby contributing to improved academic success among adolescents.

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In this paper the creep behavior of a functionally graded (FG) rotating disc made of Aluminum 6061 and Silicon Carbide is investigated and the optimum volume fraction of FG disc and its profile has been obtained. For this purpose, the temperature gradiant along the disc radius is obtained by solving the govering heat transfer differential equation. All the thermal properties of the material are assumed to be the function of temperature and volume fraction. To obtain material properties, two models of Mori-Tanaka and Hashin-Schtrickman are used. To validate the results, they are compared with those given in the literature. Two solution methods: semi-analytical and closed form are employed and the results are compared. The optimum design is carried out with one, and multi-objective methods which are based on genetic algorithm. The objectives are increasing the factor of safety, reducing the weight of the disc and reducing the range between minimum and maximum safety factors. The design variables are percentage of volume fraction, the power of material distribution formula, and the thickness of the disc. The results show that two solution methods compare well. Also, it has been shown that high fraction of Silicon Carbide in the outer side the disc provide optimum results. Also, contradiction of the objectives is reviled, hence the results are presented as Pareto front.

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Nowadays, optimization is becoming one of the most important techniques in engineering and industry to provide competing products in design and manufacturing. Therefore, it is a necessity to search for optimum designs with productibility. In aerospace industry reducing weight and improving reliability of the products are major concerns. As regards the gearbox is one of the most important parts in the helicopter propulsion system, these objects should be more considered. However, most of the existing designs consider only one object, hence, it is vital to implement optimization techniques to include different objectives to improve the existing designs and provide optimum products. In this paper, optimum design parameters including module and face width of gears for the main gearbox of Sikorsky ASH-3D helicopter have been determined (modified) using single and multi-objective mixed discrete- continuous optimization method to minimize weight of the gearbox, increase the safety factor and reduce the difference between safety factors of different gears. The results show that the weight of the gears can be reduced by 27.24% comparing with the existing gearbox. The results of the multiobjective optimization have also been presented as Pareto front diagram wich can be used by the manufacturers to satisfy the prefered requiments.

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In this paper a method has been developed to obtain an optimum material distribution for a cylindrical shell with Functionally Graded (FG) material and additional piezoelectric outer layer. The objective of the optimization is to satisfy full stress loading criterion. For this purpose; firstly, a solution method has been outlined in which, the governing equations are developrd by combining First order Shear Deformation Theory (FSDT) and Maxwell equations, with the use of Hamilton principle. Dynamic analysis is a major concern in this solution method because of the significant dynamic displacements, strains and stresses due to the effect of moving load. Hence, the time dependent transient responses of the structure and stress distribution have been obtained. At the next stage, a methodology has been introduced to obtain the optimum material distribution. In this method, instead of using pre-assumed material distribution functions which impose limitations to the manufacturing of the shell and also to the optimization solution, control points with Hermite functions are used. The thickness of the shell and volume fraction of the FG material at these points have been regarded as optimization variables. The optimization method is based on the genetic algorithm and to reduce the solution time, calculations are carried out using parallel processing in four cores. The results show that the developed method is capable of analyzing the FG structures and provide optimum solution. The major advantage of this method is its flexibility in providing volume fraction distribution of the material.

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Creep behavior of butt-welded joints in pressurized steel pipes operating at high temperature is one of the major concerns in industry. The creep behavior of 1.25Cr0.5Mo weldment has been investigated in this paper. Three different layers: Base Metal (BM), Heat Affected Zone (HAZ) and Weld Metal (WM) have been considered and the creep behavior of each layer has been modeled using constitutive equations. Constitutive parameters have been determined using the results of uniaxial constant load creep tests. A numerical approach based on least square method has been used to calculate optimum values of the constitutive parameters. The results have been compared with those provided in the literature for different alloys and good agreement has been observed. Creep tests have been carried out at 30, 35, 40 and 50 MPa and temperature levels of 670, 700, 725, 750 and 800 °C. Specimens have been machined out from Base and Weld Metal. Since machining specimens with appropriate size from HAZ is impossible, a method is proposed to obtain constitutive parameters for this layer. This method is validated by comparing the constitutive parameters which have been calculated for WM with those obtained using creep tests. Micrographical and microhardness tests show that there are significant differences in the microstructure of the layers. Consequently, the creep behavior of layers is different. The results show that steady state creep strain rate for WM is higher than the rates for BM and HAZ; also at low stress levels, creep strain rate of HAZ is larger than BM.

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Creep failure is one of the most common mechanisms which determine the life of mechanical components operating at high temperature. Gas turbine blades are among the components which operate at high temperature under mechanical loads. In new designs, cooling flow passes through the inner channels of the blade to decrease blade temperature. One of the main parameters of the cooling system is the coolant’s heat transfer coefficient. In this paper, the effect of wall roughness of the cooling channels and coolant’s specific humidity on the cooling heat transfer coefficient has been investigated. The blade body and cooling channels are regarded as a heat exchanger with a thermal barrier coating and convective- film cooling. For this purpose, the physical properties of the coolant have been considered as a function of temperature and humidity. Then, the influence of the channel’s roughness on the heat transfer coefficient has been investigated and an analytical method has been used to obtain the temperature distribution. The results show that in the rough channels, coolant receives more heat from the blade body and consequently decreases its temperature especially in the critical section. Also, it has been shown that with increasing humidity; the coolant temperature reduces along the blade span comparing with the case of using dry air and consequently, the blade metal temperature reduces with about 2.5 percent. It has been shown that by increasing coolant’s humidity and roughness of the channels in a reasonable range, blade’s creep lifetime can be increased by up to 3.18 times.

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In this paper, experimental data have been used to develop a semi empirical relationship for double-ellipsoidal heat source to model the welding process of a T-shape fillet weld of carbon steel AISI 1020 and stainless steel 304. This model is used in a finite element based computer code to simulate the three dimensional welding process and obtain the temperature profile around the weldment. Experimental data in the form of temperature for certain points have been recorded during the welding process using a computerized data processing system which has been designed for this purpose. Also, the thickness of the weldment layers has been compared by observing their hardness and crystallography. By comparing experimental data with numerical result, the coefficient of the model has been determined using “model updating” process. The effects of material properties and welding parameters have been studied to insure the generality of the model. This model can be used to evaluate the quality of the welding and thickness of the heat affected zone as well as the risks during the welding process such as burn-through and hot cracking. The main advantage of this model is that the number of coefficients is reduced to only one parameter and the rest have been related to the physical and geometrical characteristics of the weld. Results of the numerical simulation obtained using this model show that the major factors which affect the temperature distribution around the weldment are material conductivity, plate thickness, input heating and welding speed.

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For half a century, the limitations of obtaining cross-combinations in lilies because of the incompatibility and incongruity between different varieties have been known. Somatic hybridization is one of the most powerful tools for achieving distant interspecific hybrids. For this purpose, protoplast preparation is a first and important step in efficient system for the regeneration of plants from protoplasts. Protoplast isolation method was previously developed in Lilium ledebourii (Baker) Boiss. In this study, several valuable experiments were done based on completely randomized design with 3 replications and also each experiment was repeated twice. The results revealed that cell wall and colony formation were better in a liquid medium than those on a semi-solid medium. The highest plating efficiency (1.34×10⁶ per gr FW) and callus formation was obtained by using a medium containing 1 mg L^-1 2,4-D, 0.2 mg L^-1 Kin and 2 g L^-1 Yeast extract. Micro calli were formed after one month of culture. Many plantlets were formed on the calli after transfer of the proliferated calli to regeneration medium. The highest plantlet regeneration (91.66%) was obtained by using a medium containing 0.5mg L^-1 NAA, 1.5 mg L^-1 BA. Means comparison revealed that the semi- solid MS medium containing 0.5 mg L^-1 NAA and 1.5 mg L^-1 BA had the highest percentage of regeneration (91.66%), bulb number (8.83), and length (0.7366 cm), root length (0.421cm) and leaf number (13.66) and length (0.5052cm).

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The main objective of this research is to employ Imperialist Competitive Algorithm (ICA) to determine the optimum condition for an FG cylindrical shell with outer piezoelectric layer. Design parameters in this problem are thickness and volume fraction of the material. The shell is subjected to outer radial moving load and internal pressurized fluid. To formulate the problem, First Order Shear Deformation theory and Maxwell’s equation have been combined to develop governing equations and by solving these equations using analytical-numerical methods, the dynamic deformation has been obtained. Then, by adopting displacement-strain and stress-strain relationships, distribution of the dynamic stresses within the shell has been calculated. Due to the moving of the external load, the use of dynamic analysis is necessary so that the dynamic and transient response is significant comparing with the static one. To validate the dynamic analysis, the results are compared with those provided in the literature based on other solution methods or experimental measurements. Finally, a computer code has been developed to link the dynamic solution method with the optimization algorithm based on ICA to obtain the optimum values of the design parameters. The major advantage of this method is using control points along the thickness to define volume fraction rather than using predefined functions which usually impose unnecessary restriction. The volume fraction between these control points is obtained by Hermite interpolation method. The results show the efficiency of the method and its major strength which is the flexibility and higher convergence rate to determine the optimum configuration.

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Today, production and improvement of the quality of gluten-free products for Celiac patients are one of the major challenges in the food industry. Physical modification methods such as heat-moisture and microwave treatments can be used to improve the performance of flour and gluten-free products in the baking industry. The goal of this study was to investigate the effects of heat-moisture treatment at three relative humidity (RH) levels of 10, 15, 20% at 90 and 110 °C, to improve the quality of grain millet, and different ratios of of millet flour: rice flour (50:50, 25:75, 15:85) to be used in the formulation of gluten-free cookie. In this regard, physicochemical characteristics of millet (moisture, fat, protein, ash, fiber), flour (water absorption, oil absorption, color) and cookie (diameter, thickness, spread ratio, color, texture) were investigated. The results showed that the heat-moisture treatment had a significant effect on water holding capacity and oil absorption capacity of the samples (p<0.05), in a direct and reverse trend, respectively. Using flour from treated seeds in the gluten-free cookie improved baking loss, water activity, texture parameters, and sensory acceptance. By increasing heat-moisture treatment, the amount of baking loss, water activity and hardness of cookies decreased. Heat-moisture treatment had a significant effect (p˂0.05) on the spreadability and color of the cookies. Increase in the intensity of the treatment led to higher spreadability and darker color with high redness value The Sensory evaluation also showed that texture scores were high for most cookies made from treated millet flour, but the cookie obtained from the 25% replacement level of millet flour under 90 °C and 10% moisture content had the lowest score in the texture.

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Today, with the increasing population of celiac patients worldwide, producing and improving the quality of gluten-free products for celiac patients is one of the major challenges in the food industry. Celiac disease is a type of autoimmune gastrointestinal disease caused by intolerance to gluten protein and currently, the only way to treat it is to use a gluten-free diet. Gluten removal results in major problems including poor quality of mouth feel and poor taste of the product. Finding a suitable alternative to gluten is one of the biggest technological challenges in the production of gluten free products because of the importance of this protein in creating a suitable texture and appearance in the product. As a result, researchers and manufacturers are trying to promote gluten-free products by finding the right way and produce products of similar quality to wheat flour products. The aim of this study was to review different process technologies to improve the quality of gluten-free products. These process technologies include the use of conventional methods such as gums and proteins, biotechnological methods such as the use of enzymes and sourdough and modern methods including thermal and non-thermal treatments in producing gluten-free products.
 

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Today, changing climates, increasing populations, and food security concerns are encouraging researchers and food industry experts to study the feasibility of producing foods from cereals, grains, and other unusual sources. Millet has a short growing season and can be produced in drought conditions compared to the main cereals, resistant to pests and disease. Therefore, due to Iran's climate and continuous decline of water resources, its use is justified. Millet grains have also been attracted by food and nutrition researchers because of their special properties, high nutritional value and health effects. It is rich in dietary fiber, protein, minerals, and vitamins and is comparable to basic grains. On the other hand, millet is one of the grains that because of its lack of gluten proteins, can have a special place in the diet of celiac patients who cannot consume grains such as wheat, barley, rye, and oats. Therefore, in this paper, by introducing millet grain, nutritional value and its products, researchers and artisans are focused on planting and processing this forgotten grain. It is hoped that in the future, this valuable grain, often used as livestock and poultry in Iran, will also be included in the household food basket.
 

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The present study reports an efficient protocol for isolation and regeneration of protoplasts from callus of Fritillaria imperialis L. There is no published method recommended for protoplast isolation and regeneration from Fritillaria imperialis L. A range of factors, which influence the success of isolation and regeneration of F. imperialis protoplasts, were investigated. From the results obtained, callus Fresh Weight (FW) of 0.4 g produced the highest number of viable protoplasts, which was 1.12×10⁵ protoplasts g^-1 FW. The highest amount of viable protoplasts (1.01×10⁵ protoplasts g^-1 FW) was obtained when the mannitol concentration was maintained at 9% (w/v). The best treatment for isolation of F. imperialis protoplast (1.37×10⁵ protoplasts g^-1 FW) was treatment with 2% cellulase and 0.1% pectinase with 9% mannitol for 8 h. For enhancement of the protoplasts division and the percentage of colony formation, different concentrations from Casein Hydrolysate (CH), 2,4-Dichlorophenoxyacetic acid (2,4-D) and Benzyl-Adenine (BA) were used. The results revealed that cell wall and colony formation were better in liquid medium than those on semi-solid medium. The highest plating efficiency (1.26×10⁶ per g FW) and highest callus formation were obtained using the medium containing 0.5 mg L^–1 2,4-D, 1 mg L^–1 BA, and 200 mg L^–1 CH. Micro-calli were formed after one month of culture. Many plantlets were formed on the calli after transfer of the proliferated calli to regeneration medium. The highest plantlet regeneration (100%) was obtained using the medium containing 0.5 mg L^–1 (NaphthaleneAcetic Acid) NAA and 1.5 mg L^–1 BA.

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Beji Barsaq is a traditional cake in Ilam, Kermanshah, Kurdistan, and Lorestan cities, made of wheat flour, oil, sugar, eggs, low-fat milk, rose water, baking powder, and various spices (cumin, fennel, and turmeric). The present study aimed to produce a low-fat Beji Barsaq cake with soy protein concentrate (SPC) at the optimal level (3%) and carboxymethyl cellulose (CMC) at the level of 0.3, 0.7, and 1%. The rheological analysis results of dough samples showed a significant increase in their viscosity and consistency with increasing fat substitutes. At the constant level of SPI, the amounts of moisture content, specific volume, porosity, and brightness were significantly increased with increasing CMC levels. In contrast, the fat content was significantly decreased. Moreover, stiffness, cohesiveness, and springiness of the cake samples enhanced with increasing CMC levels at constant SPC level. However, this increase in springiness was not significant. After seven days of storage at room temperature, the stiffness of cake samples increased, and their cohesiveness and springiness decreased significantly, which was attributed to the products’ staleness. Sensory analysis results of cake samples showed that T4 sample (%50% fat replaced with 3% SPC+0.7% CMC ) had the best overall acceptability according to opinion of panelists.

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Civil structures inevitably undergo damage over time due to various reasons such as environmental changes, material aging, load variations, and insufficient maintenance. Monitoring these structures, especially aging ones, is crucial to detect damage early on and implement suitable retrofitting measures, ensuring their continued safe and reliable operation without unexpected failures. Consequently, there has been significant research in this field, focusing on damage detection in both simple and complex structures. Health monitoring of highway bridges is essential for achieving a reliable transportation system. The vibration-based damage detection method uses changes in the vibrational properties of structures to detect damages and ensure a healthy state. In this study, the absolute value of the modal flexibility damage index and the modal strain energy damage index simultaneously are utilized to prevent unsafe decisions.
These absolute values of modal strain energy and flexibility damage indexes are utilized as the bases for training deep neural networks (DNNs). These indexes are applied to provide safe decisions and reliable damage evaluation in steel girder of the highway bridges. The convolution neural network (CNN) is utilized for damage quantification estimation. The CNN is one of the deep learning models that can currently be applied in 2D dominant approaches, such as pattern recognition and speech recognition. In addition, these networks can utilize the 1D time domain and vibrational signal data via the convolutional layer. The initial stage of CNN model comprises combined convolutional and pooling layers that apply different filters to extract features. Following this, fully connected layers, similar to a hidden layer of a multilayer perceptron are incorporated. Ultimately, these layers are classified together with a softmax layer. The convolution layer acts as a filter that convolutes the input layer with a set of weights, adding bias and applying an activation function to the outcome. Gradient descent momentum methods (SGDM) can be employed to optimize the parameters in CNN network architecture. SGDM estimates the gradient with high velocity in any dimension. This method mitigates issues such as jittering and saddle points by utilizing high-velocity inconsistent gradient dimensions and the SGD gradients, respectively. Additionally, when the Current gradient approaches zero, the SGDM provides some momentum.
The convolution neural network is trained to utilize damage indexes obtained from numerical simulation of the validated finite element model of the bridge. The damage indexes as the inputs for the neural network, which are achieved from different damage scenarios. Once network training and validation are completed, a well-trained neural network is used to detect, localize, and quantify the intensity of unknown damages. The proposed method overcomes previous damage detection problems such as false positive indications, the unreliability of a single damage index, and insufficient precision in determining the intensity.  The results revealed that the presented method, based on the dual updated damage indexes and CNN, practically and accurately identified unspecified single damages' location and severity in multi-span beams. The new training method of deep neural network systems overcomes some shortcomings in ANN. Moreever, this deep neural network training scheme can reduce the need for huge amounts of input data and enhance the accuracy of network training. The method is capable in predicting single damage scenarios in steel beam.