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Adequate knowledge about the effects of climate change on the environment is an important factor in taking conscious action to reduce its effects. The future behavior of students is influenced by their education about environmental and climate change issues. Students located in forested (Kalibar) and non-forested (Tabriz) regions were selected to participate in this study because of the importance of environmental knowledge in promoting better management of natural resources and combating climate change effects. Measuring students' attitudes toward education and climate change can allow decision-makers to plan an appropriate program of instruction and determine the effectiveness of the curriculum.

Purpose: The article explores how best agricultural extension and advisory services (AEAS) can contribute to communicative interventions in preventing the COVID-19 outbreak in rural and farming communities. Methodology: An action research was conducted in Iran, as one of the top countries experiencing the COVID-19 outbreak. Findings: A strategic communicative intervention campaign for preventing the COVID-19 outbreak was designed at national level through diagnosing the situation, planning, organising expert teams, producing appropriate information, and disseminating through social networks, mass media and interpersonal communications. Extension staff, many relevant institutions, most key rural informants, local leaders, facilitators, farmers and nomads received and exchanged this information. Practical Implications: These communicative interventions can not only help health care service systems control the outbreak, but help rural communities increase their knowledge about the virus and health measures to participate in preventing further spreading of the virus, while continue their agricultural activities. Theoretical Implications: Preventing and managing health-related crises require effective measures, including communicative intervention campaigns. The article shows how agricultural extension systems can contribute to crisis and emergency risk communication and can support health care efforts and enhance the competencies of rural communities during human health-related crises. Originality/Value: The novel coronavirus (COVID-19) which has transmitted to all parts of the world, including rural areas, can threaten food security and rural communities' livelihoods. The study generates important insights about the process of extension interventions for enhancing these communities' knowledge and skills to prevent and manage the virus transmission.

Objective: The present study aimed to assess the impact of the aqueous-ethanolic extract of Zataria multiflora (ZM), carvacrol (Car), and their co-administration with a PPAR activator, pioglitazone (Pio), on oxidative stress and inflammation induced by paraquat (PQ) inhalation at a systemic level. Materials and Methods: The rats in the control group were exposed to saline and those of other groups to PQ (54 mg/m³) aerosols for 8 times on alternate days. Nine PQ groups were treated with saline, Car (20 and 80 mg/kg/day), ZM (200 and 800 mg/kg/day), Pio (5 mg/kg/day), dexamethasone (Dexa, 0.03 mg/kg/day), and low-dose ZM or Car + Pio for 16 days during the period of PQ exposure (n=6). Results: Differential and total WBC counts, and malondialdehyde (MDA), interleukin (IL)-10, and tumor necrosis factor (TNF)-α levels were enhanced but catalase (CAT), thiol, and superoxide dismutase (SOD) levels were reduced in the blood in the PQ group (p<0.01 to p<0.001). All measured variables improved in groups treated with both doses of ZM, Car, Pio, ZM + Pio, Car+Pio, and Dexa vs the PQ group (p<0.05 to p<0.001). Most variables were more improved in combined treatment groups in comparison with three agents alone. The combination of ZM or Car, and Pio showed an impact on PQ inhalation-induced systemic changes. Conclusion: The synergistic effect between Pio with ZM or Car indicates that these substances work together to enhance their individual effects. [ABSTRACT FROM AUTHOR]

Lack of an appropriate linkage between extension and research, is one of the problems of the agricultural extension system. After the implementation of the agricultural extension new system, "senior extension researchers" and "supportive researchers" were defined in order to play a more organized role in the agricultural knowledge network. Accordingly, the purpose of this research was to analyze the challenges and strategies to improve the performance of supportive researchers in the agricultural knowledge network of Iran. The statistical population of the study consisted of research network (N= 1876), out of whom 348 people determined as sample using Daniel's sampling formula and simple sampling technique. Data were collected through a questionnaire; validity of questionnaire was approved by a panel of experts and construct validity (AVE Index). In order to measure the reliability of the questionnaire, Cronbach's alpha and composite reliability (CR) were calculated. The collected data were analyzed by SPSS22 and Smart PLS3 software. Results of prioritizing challenges facing supportive researchers indicated that "infrastructural-supportive" dimension was in the highest, and "functional" dimension was in the lowest ranks. Also, results of prioritizing performance improvement strategies for supportive researchers showed that "infrastructural-supportive" dimension was in the highest, and "policy making-planning" dimension was in the lowest ranks. In addition, the results of confirmatory factor analysis confirmed that challenges and performance improvement strategies models had four dimensions (i.e. functional, infrastructural-supportive, structural and policy making-planning). At last, some recommendations were presented due to the research results in order to improve the performance of supportive researchers. [ABSTRACT FROM AUTHOR]

The linkage between research and extension has always been considered as one of the most important and challenging issues in agricultural innovation systems. After the implementation of the agricultural extension new system, the linkage between these two sectors was considered as an important component. The primary objective of this survey research, conducted between 2021 and 2022, was to analyze the efficacy of linkage mechanisms facilitating the integration of research and extension within Iran's agricultural extension system. The statistical population of the study consisted of extension agents (N= 1113) in Alborz, Fars, Sistan & Baluchestan and Lorestan Provinces, out of whom 291 extension agents determined as sample using Krejcie and Morgan sampling table and proportionate stratified sampling technique. Data were collected through a questionnaire, validity of which was approved by a panel of experts and construct validity (AVE Index). Reliability of the questionnaire was approved by calculating the Cronbach's alpha and composite reliability (CR). The collected data were analyzed by SPSS22 and Smart PLS3 software. Results of prioritizing effective linkage mechanisms between research and extension indicated that "motivation" and "monitoring and evaluation" mechanisms, respectively, with the average of 3.85 and 3.80 were in the highest ranks and "structural-functional" and "participatory" mechanisms, respectively, with the average of 3.66 and 3.67 were in the lowest ranks. In addition, the results of confirmatory factor analysis confirmed that these mechanisms had eight components (i.e. motivation, participation, infrastructure-support, legal-policy, structural-functional, monitoring - evaluation, communication and training-empowerment), that "motivation" and "communication" components had the highest and lowest values of standard coefficient (0.964 and 0.786). Accordingly, it is advisable to enhance the connection between research and extension by focusing on: fostering motivation, fostering participation in the multilevel planning process, leveraging the capacities of the non-governmental sector, implementing training and empowerment initiatives, enacting structural reforms, ensuring provision of necessary facilities and infrastructure, and leveraging information and communication technology. [ABSTRACT FROM AUTHOR]

According to the geographical and agricultural conditions, production of flowers and ornamental plants have a suitable situation in Iran. Alborz province is one of the potential areas in this field. Thus, this study aimed to analyze flower and ornamental plants development strategies in this province. The statistical population of study consisted of growers of flower and ornamental plants in Alborz province (N= 1260), out of which 135 people determined as sample using Cochran sampling formula and simple sampling technique. A questionnaire was the main tool of study. Validity of the questionnaire was approved by a panel of experts and construct validity using AVE Index. In order to measure the reliability of the questionnaire, Cronbach's alpha and composite reliability (CR) were calculated. The data were analyzed by SPSS22 and Smart PLS softwares. The finding revealed that, "facilitation-support" and "production process improvement" strategies were in the highest ranks and "research and technology" and "agricultural education and extension and human resources development" strategies were in the lowest ranks for development of the flower and ornamental plants industry. The results of confirmatory factor analysis showed that, flower and ornamental plants development strategies' measurement model consist of seven main elements: "marketing and sales", "agricultural education and extension and human resources development", "infrastructure and facilities development", "production process improvement", "expert development", "research and technology" and "facilitation-support" was homogeneous and the reliability of the Indicators was approved. [ABSTRACT FROM AUTHOR]

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In this paper, a combination of a multi-layer quantum neural network (QNN) with the particle swarm optimization (PSO) algorithm is used with the aim of controlling a continuous stirred-tank reactor (CSTR) system. The CSTR process is highly non-linear and its dynamics are significantly sensitive to system parameter values. Normally, conventional controllers with fixed coefficients are applied to control this kind of system. In highly non-linear systems, having fixed controller coefficients in different operational conditions may decrease the performance of controllers. In the proposed scheme, by using a multi-layer QNN, an adaptive structure is designed for a PI-D controller. In order to train the QNN, the PSO algorithm is employed. With the aim of improving accuracy and convergence speed of the training process, some modifications have been applied to the movement of each particle towards the optimal point. Furthermore, in order to evaluate the performance of the system, the proposed scheme has been applied in various operational situations in the presence of disturbances and set-point change. The efficiency of the proposed control scheme is compared with PID and a perceptron neural network-based controller, and the simulation results endorse that the proposed scheme shows significantly better performance in different operating conditions. [ABSTRACT FROM AUTHOR]

FeO nanoparticles were synthesized at room temperature using a facile precipitation method. Nanoparticles were prepared in reaction time between 2 and 30 min at solvent of water without using inert atmosphere. Magnetite nanoparticles with average diameters of 10 nm were prepared which could be considered in the range of super-paramagnetism. Zeolite-Y-FeO nanocomposites were also prepared using a so-called 'ship-in-bottle' procedure. Magnetic properties of the nanoparticles and the zeolite-Y nanocomposite were investigated using an alternating gradient force magnetometer. The results indicate that the synthesized iron oxide nanoparticles exhibit superparamagnetic behaviour at room temperature, with a saturation magnetization of 19 emu/g. Effect of various surfactants on the morphology was investigated and results show that nanoparticle saturation magnetizations are higher than that of obtained for blank magnetite. It was observed zeolite nanocomposite has para-magnetic property in comparison to super-paramagnetic FeO. Obtained nanocomposite can be used in various applications such as water purification, gas separation and as catalyst in a lot of reactions. [ABSTRACT FROM AUTHOR]

Graphene nanostructures are attracting a great deal of interest because of newly emerging properties originating from quantum confinement effects. We report on using interferometric lithography to fabricate uniform, chip-scale, semiconducting graphene nanomesh (GNM) with sub-10 nm neck widths (smallest edge-to-edge distance between two nanoholes). This approach is based on fast, low-cost and high-yield lithographic technologies and demonstrates the feasibility of cost-effective development of large-scale semiconducting graphene sheets and devices. The GNM is estimated to have a room temperature energy bandgap of ~30 meV. Raman studies showed that the G band of the GNM experiences a blue shift and broadening compared to pristine graphene, a change which was attributed to quantum confinement and localization effects. A single-layer GNM field effect transistor exhibited promising drive current of ~3.9 μA/μm and ON/OFF current ratios of ~35 at room temperature. The ON/OFF current ratio of the GNM-device displayed distinct temperature dependence with about 24-fold enhancement at 77 K. [ABSTRACT FROM AUTHOR]