m zangeneh

To successfully provide and distribute agricultural services throughout the supply chain and enhance efficiency in this sector, selecting the right locations for service centers is a crucial and complex challenge. One of the ways to develop rice mechanization infrastructure is to establish rice seedling banks. A rice seedling bank is a specialized facility dedicated to the large-scale industrial production of rice seedlings, utilizing seedling trays to optimiz space, resources, and labor. The primary aim of this research is to identify the most suitable location for establishing a rice seed bank by employing multiple-criteria decision-making (MCDM) methods.

The present research was conducted in Fuman County, Guilan Province, Iran. The main objective of identifying a location for the seedling bank in the studied area is to minimize transportation costs for the seedling trays while selecting a site with the greatest potential for successfully establishing the seedling bank. To achieve this, we analyzed the location criteria for the seedling bank at the district level during the early stages of the research. The selection criteria for identifying a suitable district include several factors, such as the number of farmers, land leveling, area under cultivation, the number of agricultural machines, the level of mechanized transplanting and harvesting, and the number of seed banks in each district. Subsequently, the best village in the district, chosen in the prior step, was evaluated using several key criteria: total cultivated area, number of farmers, cultivated area per farmer, and total distance from other villages within the district. Shannon's entropy method was employed to estimate the weight and rank for the location criteria in both stages. The districts were ranked using the Fuzzy VIKOR method, while the TOPSIS method was used to prioritize villages within the selected district.

According to the results of the Fuzzy VIKOR method, among the five studied districts in Fuman County, Lulaman rural district stands out as the best location for establishing a seedling bank. Furthermore, based on the results obtained from the TOPSIS method, Khoshknudhan-e Bala village is identified as the most favorable site for establishing a seedling bank within the Lulaman district, among the fifteen alternatives considered. The VIKOR model excels in ranking alternatives due to its ability to generate ideal positive and negative maps, making it particularly well-suited for location and spatial analysis. By utilizing this model, we can assess not only the locations themselves but also evaluate how each alternative measures up against both positive and negative ideals. In contrast, other models lack this capability, as they merely identify the optimal location without providing a comprehensive understanding of each alternative's standing.

The purpose of this research is to provide a suitable algorithm for locating a seedling bank in Fuman County. Given the numerous influencing factors and available options, the integration of the VIKOR MCDM model with fuzzy numbers to identify the most suitable district, followed by the TOPSIS MCDM model to determine the best village, yielded promising results. The findings indicate that several factors play a crucial role in identifying the optimal location for the seedling bank. However, integrating all these elements through traditional methods—such as manual map analysis—proves impractical due to the sheer volume of data involved. Furthermore, neglecting these factors in site selection leads to substantial waste of material resources, energy, and environmental resources. Overall, the results of the Fuzzy VIKOR analysis revealed that Khoshknudhan-e Bala village in the Lulaman district is the best option for establishing a seedling bank in Fuman County.

Agricultural mechanization plays a crucial role in driving agricultural development and is considered one of the most capital-intensive inputs in the agricultural sector. Effective supply chain management is a crucial necessity for improving the quality of agricultural machinery and reducing operational expenses in agricultural mechanization. This is imperative for the advancement of agricultural mechanization. The present research aims to identify the primary structures of the supply chain for rice agricultural machinery in the provinces of Gilan and Mazandaran in Iran. The study also examined the important functional aspects of the chain members, including manufacturers, importers, retailers, and farmers who serve as the ultimate consumers of the chain's products. Furthermore, the research delved into the processes that govern the supply chain.

Measuring supply chain performance involves utilizing the Supply Chain Operations Reference model (SCOR) with five distinct dimensions: cost (12 questions), responsiveness (22 questions), flexibility (16 questions), assets (13 questions), and reliability (30 questions). The study data were analyzed using SPSS software. Additionally, latent variables were generated at each level of the hierarchy by using the variables from the aforementioned model. The normality of the variables was assessed using the Kolmogorov-Smirnov test. The evaluation of normal variables was conducted through a one-sample t-test, while abnormal variables were evaluated with a one-sample Wilcoxon test. Furthermore, descriptive analysis of the expectations and constraints of manufacturers and importers regarding rice machines was carried out.

The Wilcoxon test results indicate the impact of commitment, cost management, and communication on the average test value. The variables of normal distribution such as human resource management, quality management, strategic organization, flexibility, responsiveness, performance, and reliability in stores, exhibit significant deviation from the mean value. The majority of store managers and agricultural rice machinery dealers lack formal education in the field of agricultural machinery. Including individuals with educational backgrounds in agricultural machinery at various stages of the supply chain will likely improve the dissemination of information throughout the chain. Employing dependable techniques for transmitting accurate information regarding consumers' quality requirements can assist suppliers in manufacturing or importing superior-quality machinery. This approach not only minimizes uncertainty in the supply chain and streamlines inventory management but also reduces the lead time for meeting consumer demands.

The continuous demand for rice agricultural machinery in Iran has resulted in the bullwhip effect phenomenon being perceived as a less significant challenge in the supply chain. Currently, local manufacturing enterprises have relatively limited knowledge regarding the market and technical needs of rice farmers compared to their foreign counterparts. It is advisable for manufacturing companies to broaden their comprehension of consumer behavior and needs by diversifying their market evaluation techniques.

So far, many studies have been conducted to evaluate the impact of input consumption patterns on energy, economic, and environmental indicators on horticultural and greenhouse crops in Iran. A review of these studies shows that the causes of the current situation in the systems have not been investigated. These studies are mostly reporting the current situation and the interventions and their effect on improving the input consumption pattern in the sustainability of the system have not been considered by researchers. Also, studies showed that the study location and products do not fit well with the volume of production in the horticultural and greenhouse sector of Iran. Therefore, in order to increase the effectiveness and future direction of studies in this field, this review study was conducted. In this article, Iranian horticultural and greenhouse production systems were reviewed and analyzed by reviewing the published articles between 2008 and 2018, using the PRISMA method. The PRISMA method is a well-known method for conducting systematic review studies. The PRISMA method includes the following sections: background; objectives; data sources; study eligibility criteria, participants, and interventions; study appraisal and synthesis methods; results; limitations; conclusions, and implications of key findings. In this article, 16 types of garden products and 6 types of greenhouse products were studied.

In this study, the methods used to determine the status of energy consumption, economic and environmental patterns for horticultural and greenhouse crops were analyzed. For this purpose, the indicators of total energy consumption (TEI), energy efficiency (EUE), net energy (NE), and energy efficiency (EP) were examined in the section of energy. The issue of sensitivity analysis of energy inputs was also examined and the highest values of t-statistic and MPP were reported for products. In some articles, the data envelopment analysis method was used in systems performance analysis. The indicators used included technical efficiency (TE), pure technical efficiency (PTE), scale efficiency (SE), and energy-saving target ratio (ESTR). The results of them were summarized and reported. In some studies, the method of artificial neural networks and the Adaptive Neuro-Fuzzy Inference System were used. In general, in the present article, the challenges and risks in the methods used in previous studies were considered. The issue of sampling in the analysis of agricultural systems was discussed in detail and a new sampling procedure was proposed. To draw a general picture of energy and environmental indicators of orchard and greenhouse systems in Iran, the results published in the articles were reviewed. Not all researchers use the same equivalents in calculating the indices, and this makes the results of the studies slightly different from each other. The existence of such differences causes some deviations in comparing the results of similar articles in the same products. However, to adjust for these differences, averaging was used in the index report.

The study of the share of inputs in the total energy consumption shows that for horticultural products, the share of fertilizer and electricity inputs is very significant. In the case of greenhouse products, fuel input, which is mainly diesel, has the largest share of energy consumption. Walnuts have the lowest energy consumption and strawberries have the highest energy consumption among orchard products. Grapes, apples, and walnuts also have positive net energy, so they have the highest energy efficiency compared to other products. The most important inputs that have the greatest potential for energy savings in most products are diesel fuel and electricity. Among greenhouse crops in cucumber production, diesel fuel has great potential for energy savings that need to be reduced in future research. In the case of strawberry and rose products, electricity input has the greatest potential for energy savings. Knowing the potential of inputs that can be saved can be effective in changing the behavior of producers.

To increase the effectiveness of research in this area, such studies should be done dynamically and for at least two or more years. In the first year, the input consumption pattern should be extracted and after performing the consumption pattern modifying interventions, the effect of these actions should be evaluated in the following years. Data envelopment analysis methods and multi-objective genetic algorithm can be well used to develop solutions to improve input consumption patterns. The review of articles showed that the study of the effect of social factors on the behavior of various production systems has been neglected. Since the pattern of energy consumption in the agricultural sector is significantly dependent on the behavior of users and the characteristics of systems and methods of production, it seems necessary to pay attention to this factor to prepare and design any process improvement strategy in the system. In this study, a new procedure including three stages of analysis, redesign, and evaluation was proposed to complete the studies related to the analysis of agricultural systems.

Diagnostic ultrasound has been used to detect human disease especially fetus abnormalities in recent decades. Although the harmful effects of diagnostic ultrasound on human have not been established so far, several researchers showed it has had bioeffects in cell lines and in experimental animals. Three-dimensional (3D), four-dimensional (4D), and color Doppler sonography are new techniques which are widely used in diagnostic fetal ultrasonography. The study aims to evaluate some bioeffects of 3D, 4D, and color Doppler sonography in different exposure times according to the acoustic output which is set as ultrasound scanner’s default for fetal sonography in the second trimester on human dermal fibroblast (HDF) cells. Exposure times selected consist of 10, 40, 70, and 100 seconds for 3D sonography, 10, 20, and 30 minutes for 4D sonography, and 10, 30, and 50 seconds for color Doppler. Cell viability, cell proliferation, and apoptosis induction on HDF cells were assessed using MTT assay, immunocytochemistry of Ki-67, and Terminal Transferase-mediated dUTP End-labeling (TUNEL) assay, respectively. Exposure of cells to 3D, 4D, and color Doppler modes led to decreased cell viability and increased proliferation rate of HDF. None of the diagnostic ultrasound modes induced cell apoptosis. . The results indicated that 3D, 4D, and color Doppler techniques may affect the cell viability and proliferation of HDF cells, however, have no effects on the induction of apoptosis probability. Further long-term studies with other molecular endpoints are required.

In this research, a part of the requirements for the establishment of a network of consultancy, agricultural engineering and technical services in the agricultural sector, which is related to the location of these centers, has been reviewed. The location of these centers has been done through the determination of the field of operation and the appropriate establishment of consulting, engineering, and agricultural consulting companies based on regional capacities and taking into account the distance between the types of customers of such centers. In the issue of locating service centers three main types of customer can be classified. First-class customers, which have the largest number among different types of customers, are farms and units that produce agricultural products. Each point of demand for these categories of customers may require different types of services at different times. Due to the large number and dispersion, these category of customers are considered as a focal point for ease of modeling in rural areas where they are located. Also, due to various reasons, including access to various facilities, security, traffic congestion and etc., the nominations for deployment of service centers are also considered in the same rural areas. In order to transport agricultural products from the place of production, the current location is considered to be the distance from the manufacturer's place, and the destination of the product is not studied in this issue. Second and third-type customers are demanding access to services at their own place. These types of customers may exist in some areas and agricultural supply chains. These two groups of customers include refineries, warehouses and silos mainly operating in the post-harvest of agricultural production. To meet the demand for each of the different demand points of different types of customers, the number of different trips from service centers to customer premises or vice versa is required. Each service center does not offer the same type of service to its customers. A total of 127 service packages are available for provision at a service center. The main basis for choosing the optimal location for covering models is the placement of demand points in the defined coverage radius for the candidate points. Different radius were tested to find the perfect coverage radius in each of the studied villages. For this purpose, a radius of five to 160 kilometers was examined. In some coverage radius, not only does the optimal location not change, but the number of served points is also fixed. The location of different types of customers is different, so that the first type of customers are fully located in the village, but second and third type customers are widespread in the Hamedan province. To conclude, it is necessary to consider the demand of customers located in the further distances of the service center due to the nature of the agricultural service, which requires inevitable traffic over long distances, when adjusting the operational plans of the agricultural service centers. To provide sufficient justification for the distance, though within the radius of coverage. Thus, the results of this research show that if all service centers cover 130 kilometers of radius, the largest number of customers will be covered. It should be noted that for the full coverage of all customers, the coverage radius of the service centers varies, but with the same radius, the 130 km radius is the largest coverage of the agricultural service centers in the Razan city.

Quality of life is one of the key concepts of sustainable development. Social capital, on the other hand is considered both as an important variable affecting the success of development programs as well as a social determinant of health. Therefore, this study aimed to explore the relationship between quality of life and social capital among the community health service staff in Malayer city. In this cross-sectional study, conducted in 2017, a sample of 186 participants were selected using stratified sampling method. A standard questionnaire including questions on demographic information (N=5), quality of life (N=36) and social capital (N=36) was used to collect data which were then analysed using one-way ANOVA, Pearson correlation coefficient and independent t-test in SPSS 20. According to the findings, the mean scores of social capital and quality of life were 119/13 ± 3/34 and 68/4 ± 16/71, respectively. There was a positive significant relationship between social capital and the general health (r=0/22, p=0/003), mental health (r=0/24, p=0/001), social functioning (r=0/25, p=0/000), physical functioning (r=0/38, p=0/001), role limitations due to physical pain (r=0/25, p=0/001), role limitations due to mental problems (r=0/20, p=0/007) and vitality and happiness (r=0/23, p=0/001). There was a low but not significant positive relationship between physical pain and social capital (r=0/14, p=0/06) According of the findings the level of social capital can effectively improve the quality of life. It seems that enhancement of social partnerships and collaborative activities, development of social relationships, and reinforcement of a sense of security and trust among employees can improve the quality of life.