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This paper aims to determine the optimum arrangement of a reverse osmosis system in two methods of plug and concentrate recycling.

To compare the optimum conditions of these two methods, a seawater reverse osmosis system was considered to produce fresh water at a rate of 4,000 m3/d for Mahyarkala city, located in north of Iran, for a period of 20 years. Using genetic algorithms and two-objective optimization method, the reverse osmosis system was designed.

The results showed that exergy efficiency in optimum condition for concentrate recycling and plug methods was 82.6 and 92.4 per cent, respectively. The optimizations results showed that concentrate recycling method, despite a 36 per cent reduction in the initial cost and a 2 per cent increase in maintenance expenses, provides 6 per cent higher recovery and 19.7 per cent less permeate concentration than two-stage plug method.

Optimization parameters include feed water pressure, the rate of water return from the brine for concentrate recycling system, type of SW membrane, feedwater flow rate and numbers of elements in each pressure vessel (PV). These parameters were also compared to each other in terms of recovery (R) and freshwater unit production cost. In addition, the exergy of all elements was analyzed by selecting the optimal mode of each system.

Apitourism is a form of tourism that deals with the culture and traditions of rural communities and can be considered one of the most sustainable methods of development and tourism. Accordingly, this study aims to identify the key factors and plausible scenarios of Iranian apitourism in the future.

This study is applied research. For this purpose, first, by examining the theoretical foundations and interviewing experts, the key factors affecting the future of Iranian apitourism were identified. Then, using a binomial test, these factors were screened. Both critical uncertainty and DEMATEL techniques were used to select the final drivers.

Two drivers of “apitourism information system and promotional activities” and “organizing ecological infrastructure” were selected for scenario planning using critical uncertainty and DEMATEL techniques. According to these two drivers, four golden beehive, expectancy, anonymous bee and black beehive scenarios were developed. Each scenario represents a situation for apitourism in the future. According to the criteria of trend compliance, fact-based plausibility and compliance with current data, the “Black Beehive” scenario was selected as the most likely scenario. The “Golden Beehive” scenario shows the best case in terms of apitourism information system and implementation of promotional activities and organizing and providing ecological infrastructure. The “Black Beehive” scenario, on the other hand, describes an isolated and vulnerable system.

Developing plausible Iranian apitourism scenarios helps key stakeholders and actors develop flexible plans for various situations.

The purpose of this paper is to design a hierarchical routing protocol. Wireless sensor network (WSN) consists of a set of miniature sensor nodes powered by a low-capacity energy battery. This limitation requires that energy is used in an efficient way and kept as long as possible to allow the WSN to accomplish its mission. Thus, energy conservation is a very important problem facing researchers in this context. Because sending and receiving messages is the activity that consumes the most energy in a WSN, so when designing routing protocols, this problem is targeted specifically. The aim of this paper is to propose a solution to this problem by designing a hierarchical routing protocol.

The authors started by designing a protocol called efficient energy-aware distributed clustering (EEADC). Simulation result showed EEADC might generate clusters with very small or very large size. To solve this problem, the authors designed a new algorithm called fixed efficient energy-aware distributed clustering (FEEADC). They concluded from the simulation result that cluster-heads (CHs) far away from the base station die faster than the ones closer to it. To remedy this problem, they propose multi-hop fixed efficient energy-aware distributed clustering (M-FEEADC). It is based on a new fixed clustering mechanism, which aims to create a balanced distribution of CHs. It uses data aggregation and sleep/wakeup techniques.

The simulation results show a significant improvement in terms of energy consumption and network lifetime over the well-known low-energy adaptive clustering hierarchy and threshold-sensitive energy-efficient protocols.

The authors propose M-FEEADC. It is based on a new fixed clustering mechanism, which aims to create a balanced distribution of CHs. It uses data aggregation and sleep/wakeup techniques.

This study aims to analyze the definition and contextual variations of homo islamicus in literature across disciplines, including beyond Islamic economics, and to explore their implications for Islamic economic agents.

Using a machine learning-based text analysis approach, 61 articles will be examined to classify definitions and identify contextual clusters for homo islamicus.

This study reveals eight classifications of homo islamicus definitions and three distinct contexts. These findings suggest significant divergence between the concept of homo islamicus in Islamic economic tradition and its interpretation by non-Islamic scholars, attributable to underlying values and ideologies rather than methodological differences.

This study focuses solely on textual analysis of articles using the term “homo islamicus” across disciplines, precluding the formulation of epistemological and ontological frameworks. Future research could expand on these aspects.

By presenting diverse perspectives on homo islamicus, this paper facilitates a more comprehensive understanding among scholars of Islamic economics, aiding in the resolution of disagreements within the field.

This study introduces novel classifications of homo islamicus definitions and contextualizes them, providing insights into their implications for Islamic economic agents.

The present study investigated the impact of earnings volatility and environmental uncertainty on accounting comparability in an emerging economy and the moderating role of COVID-19 pandemic for the companies listed on Tehran Stock Exchange (TSE).

The data about 181 companies during 2014–2021 were examined. In this study, accounting comparability was predicted for the firms' accounting systems and the coefficient estimates were calculated. The present study used the coefficient of variation of sales to capture sales volatility as the primary environmental uncertainty measure.

The results showed that both the earnings volatility and environmental uncertainty have a significant negative effect on accounting comparability, and that COVID-19 significantly increases the negative impact of earnings volatility and environmental uncertainty on accounting comparability. The hypothesis testing based on robust, GLS, GMM, GLM, OLS regressions and t+1 test confirmed these results.

The present study aimed to develop knowledge-providing benefits for companies about the accounting comparability and managing more efficient decisions. The present findings help investors to understand and evaluate the performance of firms more accurately especially in earnings volatility and environmental uncertainty conditions and in the wake of a pandemic crisis such as COVID-19.

Many environmental problems are due to the unfavorable environmental intentions and cultural–behavioral weaknesses in the relationship between man and nature. This study aims to adopt an environmental psychological perspective to green intention (GI) and green behavior (GB) of agricultural students; to this end, protection motivation theory (PMT) was used as the core of the theoretical base.

This research method was based on descriptive–correlational and causal–relational analyses. The statistical population included agricultural students of Iranian universities with green university standards (N = 5,582). Out of the total population, 384 students were selected as the study sample. The research instrument was a questionnaire whose validity was confirmed using a panel of experts and the average variance extracted. Also, its reliability was verified by Cronbach’s alpha coefficients (0.61 ≤ α ≤ 0.92), principal component analysis and composite reliability index.

The results of structural equation modeling showed that the obtained model is able to explain 36.3% and 5.56% of GB and GI variance changes, respectively. In addition, the results revealed that GI has the greatest effect on GB (β = 0.362).

It is worth to mention that according to the results, most of the independent variables, besides the direct effects they have on students’ GB, also indirectly affect this variable. This effect was performed through the key variable – GI. In other words, it can be concluded that the GI variable successfully mediates the effects of variables such as response efficacy (RE), self-efficacy (SE) and environmental norms (EN). Therefore, it is suggested that in the behavioral changes interventions in GB of agricultural studies, it should be considered that the presence or absence of GI can affect the actual behavior of individuals. In other words, it is recommended that to accelerate actual behavioral changes, behavioral interventionists should first focus on encouraging people’s GI.

It can be said that the conclusion of this research can provide a basis for the successful encouragement of students to GB. First, GI, as a key element, can mediate the impacts of variables such as RE, SE and EN on students’ GB. Second, PS only directly affects students’ GB. Third, RE has no significant impact on GB, but its effect on GI is significant. Fourth, RC affects students’ GI directly, without mediation. Fifth, SE and EN constructs affect students both directly and indirectly GB of students through GI. Knowing the location of the effect of these variables on each other and the role they have in explaining GI and GB of agricultural students presented some suggestions that can prepare the ground for further development of GB. Hence, managers, students, agricultural educators and other users can use these results to accelerate GB changes.

The conclusion of this research might provide a basis for the successful encouragement of students to GB. In interventions to change GB, it would be essential to pay enough attention to the fact that the presence or absence of GI might affect the actual behavior. It is suggested that behavioral interventionists focus on encouraging people’s GI so as to be able to accelerate the actual behavioral changes.