As social networks grow, they become more and more complex and analyzing them becomes complicated. One way to reduce this complexity is to divide the network into subnets, which are also called communities. Dividing social networks into desirable communities can help the analysts and experts to understand the behavior and function of the networks. Community detection in networks is a challenging topic in network science and various methods have been proposed for that. Modularity maximization is one of the state-of-the-art methods suggested for community detection. Modularity maximization is an NP-hard problem meaning that no polynomial-time algorithm exists that could solve the problem optimally unless P=NP. One group of approaches that could solve such problems is the approximate algorithms. Identifying the influential nodes has many important applications in social networks. This technique could also be used in community detection. To maximize the modularity, in this paper, we propose approximate algorithms based on identifying the influential nodes and their Influence domain. We used the concept of scale-free networks to prove the approximate factor. Experiments on real-world networks show that the proposed algorithm can compete with the state-of-the-art methods of community detection algorithms.

Introduction: The ethical dimensions of agriculture need to be explored, distinguishing between ethics in agriculture and ethics of agriculture. Ethics in agriculture is traditionally based on abstract moral theory, formulated through logical reasoning, but often found inadequate to address the complex ethical challenges within agriculture due to its abstract nature and lack of practical visibility. Conversely, ethics of agriculture is approached within a context-specific Framework derived from the research topic with the aim of providing more tailored solutions. Materials and Methods: A comprehensive review of the relevant literature is conducted, using a descriptive-analytical approach to provide a conceptual Framework for understanding agricultural ethics. Conclusion: The article highlights the critical need for a comprehensive ethical Framework to address the multifaceted ethical challenges in the agricultural sector. The importance of analyzing and resolving ethical dilemmas at all stages of agriculture is underscored in order to align practices with human ideals and to ensure ethical decision-making by stakeholders involved in agriculture.

With the advent of the next generation of wireless communication networks, the requirements for high-rate and timely information delivery, especially in real-time applications, have increased dramatically. In particular, Millimeter wave (mmWave) communications can provide a high data rate, and reconfigurable intelligent surfaces ((RIS)s) can reduce the blockage sensitivity of mmWave links. Also, to quantify the data freshness, the age of information (AoI) metric is introduced in the recent literature, defined as the time elapsed since the last successfully received status update was generated. This paper aims to optimize the average AoI in a multi-user (RIS)-assisted millimeter wave network. For this purpose, the proposed problem was formulated as a Markov decision process (MDP) that aims to obtain the optimal control policy that minimizes the sum of the average AoI of all users. Under the unknown system statistics assumption, we propose a model-free deep reinforcement learning algorithm to schedule the users’ transmission, adjust the transmit power, and configure the (RIS) to reflect the signals.  The performance of the proposed method is evaluated in terms of convergence characte(RIS)tics and the impact of changes in network parameters.

Reverse redistribution pattern is defined as decreased activity in the myocardium in the rest phase of the myocardial perfusion scan in compa(RIS)on with the stress images. There are many studies concerning the etiology and clinical significant of this phenomenon in nuclear medicine literature. The dominant idea about etiology of Reverse redistribution is early wash out of the radiotracer from the myocardium. There is rather unanimous agreement among researchers about viability of the areas of Reverse redistribution and the majority of the studies point to existence of viable tissue in these regions. However from prognostic point of view, this issue is much more controversial. In this review, we tried to summarize the current literature and reach a guideline for practical significance of Reverse redistribution in every day work of nuclear medicine specialists.

Background: Cumulative evidence shows that dysregulation of the hypothalamic-pituitary-adrenal (HPA) axis is involved in the depressive disorders and natural or synthetic glucocorticoids have a direct effect on HPA activity.Objectives: Considering the reports that show zinc deficiency is one of the causes of depressive-like behavior, the current study aimed to examine the effects of systemic injection of zinc chloride (ZnCl2) and/or dexamethasone sodium-phosphate (DEX) on depression in adult male rats.Materials and Methods: Different groups received ZnCl2 (2.5, 5, 10, and 20 mg/kg) and DEX (0.5, 1, 5, 10, and 30 mg/kg) and then depression was assessed in the forced swimming test (FST).Results: Results showed that DEX 1 significantly increased, while DEX 30 and groups treated with zinc 10 mg/kg and zinc 20 mg/kg decreased total immobility time as compared to that of saline group. Also there was a significant decrease of total immobility time when zinc administered to rats already received DEX 1, compared with that of control group.Conclusions: The current study findings suggest that zinc has antidepressant effects dose dependently, while administration of DEX induced dual effects on depression; therefore, a low dose of DEX showed an increased level of depressive-like behavior while higher doses had antidepressant effects. Also, results showed that zinc administration could ameliorate depressive-like behavior induced via dexamethasone in FST.

One of the main activities of humanitarian logistics is to provide relief items for survivors in case of a disaster. To facilitate the procurement operation, this paper proposes a bidding Framework for supplier selection and optimal allocation of relief items. The proposed auction process is divided into the announcement construction, bid construction and bid evaluation phases. In the announcement phase, the bidder (purchaser or relief organization) invites certain suppliers to the auction. Next, the construction phase is formulated as a bi-objective fuzzy model from the perspective of suppliers. This phase provides the bidder with several suggestions, each of which containing the amount, price, and lead time of the delivery of relief items. Then, in the evaluation phase, the bidder determines the winners and optimally assigns orders by a multi-objective fuzzy model. Each of the fuzzy mathematical models in the paper is formulated under the uncertainty of parameters and is then solved by a two-stage fuzzy approach. Finally, to illustrate the validity and applicability of the proposed model, a numerical example is provided and its result is analyzed.

This paper investigates the physical layer security of a wireless network assisted by a Reconfigurable Intelligent Surface ((RIS)) in the presence of full-duplex active eavesdropping. In this scenario, the (RIS) cooperates with the Base Station (BS) to transfer information to the intended user while an active attacker attempts to intercept the information through a wiretap channel. In addition, the attacker sends jamming signals to obstruct with the legitimate user’s signal reception and increase the eavesdropping rate. Our objective is to maximize the secrecy rate by jointly optimizing the active and passive beamformers at the BS and (RIS), respectively. To solve the resulting non-convex optimization problem, we propose a solution that decomposes it into two disjoint beamforming design sub-problems solved iteratively using Alternating Optimization (AO) techniques. Numerical analysis is conducted to evaluate the effects of varying the number of active attacking antennas and elements of the (RIS) on the secrecy performance of the considered systems under the presence of jamming signals sent by the attacker. The results demonstrate the importance of considering the impact of jamming signals on physical layer security in (RIS)-aided wireless networks. Overall, our work contributes to the growing body of literature on (RIS)-aided wireless networks and highlights the need to address the effects of jamming and active eavesdropping signals in such systems.

One of the features of new theories of development is that it considers dynamism at the regional level, innovation, production and transfer of knowledge as a key factor in regional development. Accordingly, innovation at the regional level is mainly done through collective learning and synergy between different actors who work inside and outside the organization. The central goal of this article is to identify the factors affecting the regional innovation system. In order to investigate the impact of different variables on the rate of regional innovation, the panel model related to the variables of one hundred and fifty countries during the years 2017-2013 has been used. Then, according to the hypotheses and diagnostic tests using panel data and the fixed effects pattern method, the relationship between innovation and the factors affecting it is examined. The results confirm that the variables of R&D expenditures, industry and university participation in R&D, access to the latest technology and finally higher education and patent programs have a positive and significant effect on countries' innovation.