Lentils are one of the most important legumes, which have a high amount of protein and vitamins A and B, fiber, potassium and iron, and are an inexpensive food for low-income people. The objective of this study was the determination of variability, heritability, correlations between yield and yield components in 14 Lentil (Lens culinaris L.) genotypes using a randomized complete block design with three replications. The results showed that secondary stem per plant and productivity degree had the highest GCV and PCV but the lowest GCV and PVC was found for a number of pod/ m2 and number of the plant. Maximum heritability was estimated for 100-seed weight, number two-seed pod, biological yield, grain yield, productivity degree and plant height respectively. The high genetic advance and heritability were observed for the number of the two-seed pod and biological yield. The phenotypic correlation revealed that rainwater productivity, biological yield and plant height had the greatest, positive and significant association with seed yield. By performing path analysis based on stepwise regression, rainwater productivity had the most direct effect on seed yield, while the number of secondary stems per plant through rainwater productivity had the most indirect and negative effect on seed yield. That means with increasing number of the secondary stem, rainwater productivity is decreased which results in reduced grain yield. As a result, it was concluded that rainwater productivity and biological yield can be good SELECTION criteria for improving seed yield per plant in Lens culinaris.

BACKGROUND AND OBJECTIVES: Choosing a location for mariculture is very important because it affects water quality, while problems that affect cultivation and the environment can be avoided by choosing the right location. The objective of this study is to develop a methodological strategy for integrating and analyzing spatial data, which will facilitate the identification of optimal locations for mariculture. In this context, the ecosystem approach to mariculture is analyzed with an emphasis on evaluating water quality CONDITIONs and determining primary productivity values.METHODS: Water quality parameter data was analyzed using principal component analysis, values, and distribution of primary productivity using the kriging interpolation method using geographic information system. Spatial analysis employing Geographic Information System applications is used to evaluate the appropriateness of locations for mariculture.FINDINGS: The distribution pattern of primary productivity is strongly influenced by the distribution of phytoplankton and the highest concentration values are located in coastal waters and small islands. The analysis identified three primary components that account for 79.64 percent of the results. The most influential factors include suspended particulate matters, nitrate, temperature, salinity, ammonia, current, and water transparency. According to the study results, the principal component values indicate that the most affected regions by pollutant pressure are agricultural lands that drain into rivers and watersheds, along with coastal residential neighborhoods.CONCLUSION: The status of water quality is the main limiting factor in determining the location of mariculture, therefore it is necessary to relocate existing mariculture, improve agricultural cultivation techniques, and/or regulate the use of pesticides that not carried out during the rainy season. These findings may assist the appropriate authorities in the SELECTION and oversight of mariculture sites. The innovative aspect of this study lies in its focus on adaptive management of sustainable marine cultivation, designed to align with regional CONDITIONs and promote ecological health alongside the socio-economic prosperity of local communities.

Purpose: Managers are one of the important elements of an organization, for this reason, in order to draw the future of the organization, it is necessary for the planners to specify the CONDITIONs of their SELECTION and appointment. Therefore, the current research has been done with the aim of identifying and analyzing the components of selecting future principals.Method: In this research, comparative and benchmarking method is used as a prospective approach. This approach is based on the belief that today's advanced organizations/countries can be considered as a model for the future of another organization/countries in their respective subjects. For this, first, the fields of comparison and benchmarking were determined using Brody's four-step comparison method; then the countries of Canada, Finland, Australia, South Africa, and Japan were selected according to the qualitative balance value in the international advanced TEAMS test, human development index, life quality index(health, instruction, and welfare), education quality index, and other scientific-scholarly indexes; finally, by extracting the criteria for the SELECTION and appointment of principals through content analysis and comparison with Iran, the proposed framework for Iran has been presented.Findings: A total of 61 components for the SELECTION of secondary school principals were identified from among the studies conducted in the selected countries in this article. By extracting the commonalities and differences of each of the components among the countries, it was found that the highest index of manager SELECTION and appointment belongs to Japan and the lowest one is related to Finland.Conclusion: There are similarities between the components of SELECTION of principals of secondary schools in Iran and selected countries. In Iran, special attention should be paid to important components such as adherence to religious principles, appropriate personality traits, creativity and innovation, motivation to develop capabilities, professional growth, power of supervision and accountability, social image, leader skills, and purposefulness and foresight.

Vendor management inventory, as one of the inventory management methods, reduces the cost of inventory in the chain, quick response to customers, increased service level, customer satisfaction, and improves collaboration between the members of supply chain. In this study, a single-product bi-level supply chain model with one manufacturer and several retailers under a vendor management inventory system to select retailers under competitive CONDITIONs is investigated. In this study, the retailer SELECTION problem formulated as a Stackelberg game model with consideration of manufacturing as a leader and retailers as followers to help the manufacturer and optimally select his retailers to form a VMI system. The manufacturer delivers the products to the selected retailer at the same time. Also, demand for the product in the retailers market is the decreasing function of price. Due to the prevailing policy and the agreement between the manufacturer and the retailer, the manufacturer is also responsible for managing the retailer's inventory. Therefore, the manufacturer will bear all the costs of maintaining the inventory, whether with himself or the retailer. In return, to accept the responsibility of inventory management by the manufacturer, the retailer pays the manufacturer a fee per unit as inventory costs. The objective of the model is to maximize manufacturing profits at the first level and maximize profits of any retailer at the second level. Model decisions are finding the optimal quantities of wholesale price decisions, product's replenishment cycle time, backorder, retailer SELECTION, and determining whether or not to set up a production line for the manufacturer and retail price quantities for the retailer. In order to validate the proposed model, sensitivity analysis was performed on some parameters. As demonstrated by our numerical studies, the optimal retailer SELECTION can increase the manufacturer's profit by 91% and the selected retailer's profits significantly compared to the non-SELECTION strategy.

Introduction: The main objective of this research is to perform a site SELECTION and planning with respect to environmental and spatial characteristics. This is to gain the primary social and physical needs of survivors of the accident (the earthquake) and promoting the health CONDITION of crisis. This is for multipurpose use of these places even in ordinary or emergency situations....

Suppliers play an important role in reducing costs and increasing product quality. Accordingly, assessment and SELECTION of suppliers based on desired criteria, has become one of the fundamental headquarters of decision-making in supply chain management. Since now the suppliers have a significant impact on the success or failure of a company, purchases that previously was considered as a mere tactical tool, now is known as a strategic task. So, considering the importance of the subject, the aim of this study is providing a fuzzy approach in order to select multi-product and multi-purpose supplier and determine the economic order quantity in supply chain. Objectives considered in the above model include minimizing the total cost (including the purchase cost, cost of returned goods, control and order costs), maximizing quality (including the product’ s quality and services provided by suppliers, and maximizing the amount of products received from suppliers on-time. To resolve the above issue, the Lp-Metric and Zimmermann fuzzy approach-due to dealing with uncertainty and getting more flexibility of decision-making-are applied. The results represent the best suppliers to purchase the products from and also optimized allocation to each of them.

The aim of this study was a strain-improvement program for Trichoderma reesei PTCC 5142 by using a combination of UV light and NTG (N-methyl-N'-nitro-N-nitrosoguanidine) for enhanced cellulase production. Following mutagenesis after several rounds, mutant A6: 2 was selected from a total of 6500 colonies. Results obtained after 4 days were: Enzyme activity 1.26 U/ml and 0.82 U/ml for exoglucanase and endoglucanase, respectively. The comparative results showed increased production exoglucanase and endoglucanase by mutant A6: 2 than Trichoderma reesei PTCC 5142 to amount 130% for exoglucanase and 156% for endoglucanase.

Multi-label classification aims at assigning more than one label to each instance. Many real-world multi-label classification tasks are high dimensional, leading to reduced performance of traditional classifiers. Feature SELECTION is a common approach to tackle this issue by choosing prominent features. Multi-label feature SELECTION is an NP-hard approach, and so far, some swarm intelligence-based strategies and have been proposed to find a near optimal solution within a reasonable time. In this paper, a hybrid intelligence algorithm based on the binary algorithm of particle swarm optimization and a novel local search strategy has been proposed to select a set of prominent features. To this aim, features are divided into two categories based on the extension rate and the relationship between the output and the local search strategy to increase the convergence speed. The first group features have more similarity to class and less similarity to other features, and the second is redundant and less relevant features. Accordingly, a local operator is added to the particle swarm optimization algorithm to reduce redundant features and keep relevant ones among each solution. The aim of this operator leads to enhance the convergence speed of the proposed algorithm compared to other algorithms presented in this field. Evaluation of the proposed solution and the proposed statistical test shows that the proposed approach improves different classification criteria of multi-label classification and outperforms other methods in most cases. Also in cases where achieving higher accuracy is more important than time, it is more appropriate to use this method.