This study focuses on the investigation of intelligent form-finding and vibration analysis of a triangular polyhedral tensegrity that is enclosed within a sphere and subjected to external loads. The nonlinear dynamic equations of the system are derived using the Lagrangian approach and the finite element method. The proposed form-finding approach, which is based on a basic genetic Algorithm, can determine regular or irregular tensegrity shapes without dimensional constraints. Stable tensegrity structures are generated from random configurations and based on defined constraints (nodes located on the sphere, parallelism, and area of upper and lower surfaces), and shape finding is performed using the fitness function of the genetic Algorithm and multi-objective optimization goals. The genetic Algorithm's efficacy in determining the shape of structures with unpredictable configurations is evaluated in two distinct scenarios: one involving a known connection matrix and the other involving fixed or random member positions (struts and cables). The shapes obtained from the Algorithm suggested in this study are validated using the force density approach, and their vibration characteristics are examined. The findings of the comparative study demonstrate the efficacy of the proposed methodology in determining the vibrational behavior of tensegrity structures through the utilization of intelligent shape seeking techniques.

Increasing population and food demand, disproportionate cultivation and annual production of various agricultural products with market needs and low productivity of the agricultural sector and the loss of water and soil resources have made it necessary to determine and implement the country's optimal cropping pattern. In this study, due to the limitations and problems of classical methods in order to reduce processing time and improve the quality of solutions, the Multi-Objective Chaotic Particle Swarm Optimization was used to determine the optimal cultivation pattern of Sistan plain in optimal conditions and deficit irrigation. The results of the Multi-Objective Chaotic Particle Swarm Optimization for the dominant cultures in the region showed that the current cropping pattern of the region is not optimal and with the implementation of the proposed model, the profit per unit area under cultivation will increase. The results of application of deficit irrigation during different growing periods of wheat, barley, alfalfa, sorghum, watermelon and grapes showed that applying deficit irrigation in this plain is not a good strategy and therefore only a full irrigation strategy is recommended. The results of sensitivity analysis of the model showed that at low prices, farmers reaction is less and at higher prices more reaction to price changes and with increasing prices, the program efficiency is lower.

One of the basic topics in hydrological and river engineering studies is flood routing.Flood flooding is common in multi-tributary rivers and rivers without intermediate basin statistics. Therefore, to achieve the determination of slopes and cross-sections in all sections of the river, the Muskingum hydrological model is a useful method that helps to save information on the depth and flow of the flood at any time by saving time and money. To specify. In this study, the nonlinear parameters of the new Muskingum model are optimized based on the fly Algorithm (MA). In this non-linear model of Muskingum, which has eight parameters, the recovery coefficient γ is used, which has more or less values ​​than the number of peaks discharged in the output hydrograph.To evaluate the performance of Muskingum's new nonlinear model with the new MA Algorithm, the Wilson and Weisman-Lewis case study has been used by many previous researchers for validation.The results of the MA Algorithm for Wilson and Weissman-Lewis rivers show the minimization of the residual squares (SSQ) as the objective function, which is 3.21 for the Wilson River and 68722 for the Weissman River. The results of this study showed that the proposed model has high accuracy in estimating the output discharge values.

Many of the theorems that were developed by researchers in the 1960s and 1970s in combinations and graph theory as mathematical theorems, are still used today in designing Algorithms and solving new problems. The purpose of this article is to show that useful things happened in the past that we should not forget and use them with a creative eye. Bollobás Lemma \cite{bollobas}, which was proposed in the 1970s, is a well-known problem in combinatorics. In this problem, we have a family of sets $A_1, A_2,\ldots,A_m$ each with size a and another family of sets $B_1, B_2,\ldots,B_m$ each with size b. The goal is to find the maximum size m, the number of sets so that for each index i we have $A_i \cap B_i = \emptyset $ and also $A_i \cap B_j \neq \emptyset$ where $(i \neq j).$ The Bollobás lemma expresses the upper bound for the maximum number of these sets as $m\leq \binom{a+b}{b}$. In this paper, after stating the versions of the lemma and the existing proof for this lemma, we present another probability-based proof for the Bollobás Lemma, and then with a different look at this combinatorial problem, we investigate the interesting applications of this lemma in graph theory problems and parameterized Algorithms.

Purpose: The flourishing of political parties and currents is one of the signs of the degree of development in societies. In contemporary Iran and since the formation of the constitutional movement, political currents have gone through many ups and downs and it can be said that political currents in Iran after the Islamic Revolution have not yet reached the stage of institutionalization and stability. A characteristic feature of political currents in Iran is the divergence and division among political currents in recent decades, and this can be one of the reasons for the instability and cross-sectional and seasonal activity of political parties in Iran. Therefore, the necessity of leading research seeks to answer the question of how factors and divergence among political currents in Iran after the victory of the Islamic Revolution can be analyzed? And what are the scenarios for the advancement of political currents in Iran?Method: To answer this question, the method of causal-layer analysis, which is one of the qualitative methods in futures research, has been used.Findings: The research findings indicate that this divergence is due to a wide range of reasons from the level of causal systems (from the institutionalization of power to the formation of parties as elitist initiatives), worldview and discourse (from charismatic political authority to culture). Subsidiary-follower politics to myth-metaphor (Iranian individualism to belief in a strong state-weak society) can be analyzed.Conclusions: Three scenarios for the future of Iranian political currents can be considered: integration of currents as the security valve of the political system, the collapse of political currents in the traditional form, integration and consolidation in new social movements (virtualized parties).

Recognition and understanding the genetic control of traits, combining ability and genetic structure are directly related to the success of breeding programs. For this purpose, a 7 × 7 one-way diallel design was conducted in a randomized complete block design with three replications. The measured traits were included plant height, height to the first capsule, number of days to 50% and 90% of flowering, number of capsules per plant, number of seeds per capsule, number of days to physiological ripening, number of branches, leaves number and length, 1000-seeds weight, capsule weight, length and width, chlorophyll a, b and total chlorophyll, biological andeconomic yields, harvest index, oil and protein percentage. analysis of variance showed that there was a significant difference between genotypes and diallel analysis showed that the additive variance of all traits and dominant variance of all traits except height to the first fruit-bearing capsule were significant. The oltan cultivar was the best and Ardestan genotype was the worst genotype in terms of general combining ability. Sabzevar×TS-3 and Sirjan×Fars were the best hybrids in most traits. The general heritability was between 0.90 to 0.96 for biologic yield and number of branches, respectively and narrow heritability was between 0.36 to 0.91 for the number of branches and harvest index, respectively. The analysis of variance by Hayman method confirmed the results of Griffing analysis.

METRIC (Mapping Evapotranspiration at High Resolution with Internalized Calibration) is known as an appropriate surface energy balance model for the estimation of the spatial distribution of evapotranspiration (ET) in semi-arid regions. Based on lysimeter measurements, METRIC has shown ET estimates of 10% on a sub-field scale on a daily basis. There is a need to identify how the model is sensitive to the input parameters. Therefore, the most influential parameters in the Algorithm can be identified and the model can be further improved. Sensitivity analysis at three levels of vegetation cover shows that METRIC is highly sensitive to dT, surface temperature, net radiation, sensible heat flux, surface albedo, soil heat flux, and air temperature. It is also moderately sensitive to friction velocity, aerodynamic resistance to heat transfer, surface emissivity and less sensitive to leaf area index, soil adjusted vegetation index, wind speed (except wind speed at low level of vegetation cover), and roughness length for momentum (except Zom<0.1). A two-factor analysis of the Algorithm’s primary inputs showed that the pair albedo-surface temperature is the most and the normalized vegetation index-soil adjusted vegetation index or normalized vegetation index-leaf area index is the least effective pair in this model. In order to improve the accuracy of METRIC, this study suggests upgrading the equations for the above-mentioned effective variables.