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Purpose: Sustainability is one of the global challenges, individuals and businesses need to change their behavior and consumption patterns to move towards sustainable development. This is not possible without planning for education and related knowledge transfer. On the other hand, disruptive technologies such as virtual reality (VR) have revolutionized the field of education. The purpose of this study is to evaluate the effect of holding traditional training courses and VR-based training courses on sustainable behavior. Design/Methodology/Approach: It is a quasi-experimental study, in which pretest-posttest design and control group are used. The statistical population includes students of one of the Iranian universities. A total of 105 students were randomly divided into two experimental groups and one control group (35 students in each group). Experimental group 1 underwent a training course using VR and Experimental group 2 received a traditional training course. At first, a pre-test was performed and after completing the eight-session period (two 1-h sessions per week), the post-test was conducted again for the groups. Findings: The results of analysis of variance test show that there was a significant difference between the mean scores of sustainable behaviors in the post-test phase in the two experimental groups and the control group. Using Tukey's test, it was found that the scores of sustainable behavior were different among three groups in pairs. That is, holding a training course as well as using VR has been effective on sustainable behavior. Environmental policymakers and planners can use technologies such as VR to teach environmental issues to create a culture of sustainability and sustainable development, in addition to training and educational courses. Originality/Value: Contribution of this study shows that the use of VR can be effective in learning sustainable behavior. Also, holding training courses is a way to change the consumption pattern and behavior of people to maintain the environment and sustainability.

Purpose: The cation exchange capacity (CEC) is a pivotal soil attribute that influences soil chemistry, fertility, and productivity. Nevertheless, the conventional techniques employed for CEC measurements present challenges in terms of complexity, cost, and laboriousness. Hence, there is a demand for expedited, cost-effective, streamlined alternative methodologies that can yield accurate outcomes. The objective of this study was to employ and compare various techniques, including Pedotransfer Functions (PTFs) based on fundamental soil properties, support vector regression (SVR), sequential orthogonalized partial least squares (SOPLS) as a multiblock data analysis method, and Spectrotransfer Function (SPTF) utilizing visible-near infrared (VNIR) and mid infrared (MIR) diagnostic wavelengths to estimate the CEC of calcareous soils with diverse land uses in the semi-arid region of Fars province, Iran. Materials and methods: A total of 130 samples were gathered from the soils of the study region, CEC was measured using sodium acetate, and the spectral reflectance in the VNIR and transmission in the MIR regions were measured, and prediction models were created using linear support vector regression (L-SVR), radial basis function support vector regression (RBF-SVR), partial least squares regression (PLSR), and multiblock data analysis algorithms, after different spectral preprocessing methods. Results and discussion: The results generally indicated that spectroscopy models performed better than PTFs in predicting CEC with the multiblock SOPLS showing the best results (R2 = 0.92, RMSE = 1.67 cmol(+) kg−1, and RPIQ = 4.34). The performance of the models followed the order: SOPLS > SPTF > L-SVR > RBF-SVR. Conclusion: Our findings indicate that spectroscopy coupled with SOPLS analysis can be a robust, viable, fast, cheap, and efficient alternative assessment method with acceptable accuracy for estimating soil CEC in calcareous soils, instead of the difficult, costly, and cumbersome conventional measurement approaches or other estimation methods. [ABSTRACT FROM AUTHOR]

Background. Hospitals, patients, researchers, and healthcare organizations are producing enormous amounts of data in both the healthcare and drug detection sectors. With continued development of cheap data storage and availability of smart devices in the world, the influence of big data (BD) will continue to grow. This influence has also carried over to healthcare. The volumes of data available in the fields of pharmacology, toxicology, and pharmaceutics are constantly increasing. Therefore, the present study aimed to identify the applications of big data technology in the field of pharmaceutics. Methods. Using the mixed methods approach, this study was conducted in two phases in winter 2023. In the first phase, the applications of big data technology were identified by library search and assessed by content analysis. In the second phase, applications were ranked by a panel of experts, including 17 experts who worked in the Iranian pharmaceutical industry. The stepwise weight assessment ratio analysis (SWARA) method was used for ranking the application of big data in pharmaceutics. Results. The present study examined the importance of big data applications in pharmaceutics. The results showed that drug discovery (0.263) and clinical study analysis (0.224) had the highest importance, followed by drug efficacy and performance (0.197), drug safety (0.170) and drug personalization (0.146). Conclusion. The present study detailed a substantial attempt to review the existing literature regarding the implementation of big data and to rank big data applications in the pharmaceutical industry. Big data can help researchers to better discover and develop drugs and understand the effects of drugs and other chemicals on the human body. As a result, it can help improve the safety and efficacy of drugs and other chemicals. Also, big data can help to improve the accuracy of predictions regarding the effects of drugs and chemicals, which can improve safety in drug development and help to avoid potential adverse drug interactions. The applications considered in this study are ultimately necessary for humanity, and big data may significantly impact the betterment of these domains. Big data has a revolutionary potential, providing new ways to understand and predict the effects of drugs. BD will possibly play an important role in pharmaceutics in future, critically helping to drug discovery and improve drug safety and efficacy. [ABSTRACT FROM AUTHOR]

Purpose: The blockchain technology is based on distributed ledger. Many stakeholders, such as developers, entrepreneurs and technology lovers, consider the blockchain as an economic and business re-creation that is faced with numerous challenges in its application. Blockchain technology is the backbone of many digital currencies, i.e. Bitcoin and Ethereum. Although presently digital currencies are recognized as payment and exchange instruments in many countries, the economic sanctions imposed on some countries have restricted the possibility of the trading. So, this study seeks to evaluate the adoption of blockchain for digital currency use in Iran in the shadow of economic sanctions. Design/methodology/approach: The developed value-based technology adoption model and smart PLS software have been used in this research. The statistical population of the study was people active in the Iranian stock market; the purpose for this selection was their familiarity with financial and digital currency issues. Findings: The results show that the terms of sanctions, usage and facilitating conditions are directly related to users' perceived value of digital currency and its use; As a result, in a sanctioned country like Iran, the use of digital currencies is being accepted as a way of rolling out economic sanctions and thus making commercial payments. Originality/value: As well as the fact that evaluating the adoption of the blockchain technology in a sanctioned country like Iran is considered as the originality aspect of the research, applying an extended model in the technology adoption is also the research innovation. [ABSTRACT FROM AUTHOR]

The recently emerged Coronavirus (COVID-19) has been identified as a pandemic by the World Health Organization (WHO) and has affected all sections of human society including agriculture, livestock, manufacturing, and industry. In this research, we investigated the impact of COVID-19 on Iran's livestock and meat market by using an equilibrium displacement model. The prevalence of the Coronavirus has had the greatest economic effects on rising exchange rates and has reduced exports in Iran. The results also show that the factors of the Coronavirus (exchange rate and exports) have the highest effect on Iran's meat market. The rising exchange rates and reduced exports lead to higher prices and lower quantities in the meat market, which increase the suppliers' welfare at the retail and farm levels. These results show the negative effect of the outbreak of Coronavirus. Corona outbreak increases price at the farm and retail level, therefore, farm and retail quantities fall. Since the impact of an increase in the price is much greater than the effect of reducing production, producer surplus increases. A policy conclusion of this research is that the current situation in Iran is difficult for the poultry and livestock industry because of the need for foreign currency and the abuse of market power in the distribution system. Farmer cooperatives can overcome these problems because their objectives are to serve farmers and their goals align with farmers goals. [ABSTRACT FROM AUTHOR]

Background and Objectives: The Internet of Things (IoT) refers to billions of physical devices around the world that are now connected to the internet, all collecting and sharing data. The IoT has been widely applied to interconnect available medical resources and provide reliable, effective and smart healthcare service to the people. The social acceptance of IoT applications and services strongly deepens on the trustworthiness of information and the protection of private data. The marked expansion of the IoT specific technologies has presented daunting ethical challenges. Therefore, the present study aimed to identify the ethical issues of IoT in medical sciences in Iran. Methods: The current study was conducted in two phases using the mixed-method approach in winter 2020. In the first phase, the ethical issues of the IoT were identified by library search and assessed by the content analysis. In the second phase, ethical issues were ranked by a panel of experts, including 15 IT experts who worked in medical universities in Iran. The Stepwise Weight Assessment Ratio Analysis (SWARA) method was used for ranking the ethical issues of IoT. Results: The obtained results revealed the importance of informed consent (0.259), privacy (0.227), information security (0.195), trust (0.171), and physical safety (0.148) in ethical issues of IoT. Conclusion: As evidenced by the obtained results, informed consent and privacy were the most important ethical issues in IoT. Moreover, IoT devices that target or profile peoples' information without their knowledge or consent could be interpreted as infringing upon their privacy. The users of these devices should be able to intentionally manage the transformative effects of the technologies that influence and shape their development. Moreover, the health sector policymakers should be aware of the ethical commitment to using IoT technology. [ABSTRACT FROM AUTHOR]

Spirocerca lupi (family: Spirocercidae; order: Spirurida) are parasitic nematodes found in the esophagus of cats and dogs, as well as in other carnivore animals throughout the tropical, subtropical, and temperate countries of Asia and the Americas. These animals become infested by eating an intermediate host or a transport host. In adult felines, this parasite often resides in the mucosa of the esophagus, where it forms granulomatous nodules. In this work, a wild immature female Pallas's cat (Otocolobus manul) that was younger than 1 year old was killed by a herding dog (heeler) in Mashhad, Iran. After necropsy, parasite samples were gathered from the stomach and after clarification by lactophenol, the nematodes were recognized as Spirocerca lupi. Microscopic diagnoses in the stomach include granulomatous nodules, mucosal gland destruction, necrosis, and inflammatory cell infiltration. This report characterizes the first documented case of spirocercosis in a Pallas's cat in the world. [ABSTRACT FROM AUTHOR]

Spirocerca lupi is an international nematode of Canine and wild carnivores. The generic clinical symptoms are regurgitation, vomiting, and pursiness. The parasite usually procreates nodular masses in the esophagus and pectoral aorta. On July 2014, a four-month male sandy fox was found accidentally killed on the road in Bafgh City, Southeast of Yazd, Yazd Province, Iran during necropsy, referring to esophagus, parasites were collected from esophagus and transmissive up to 70% of alcohol. Parasites were recognized as S. lupi. After clarification of lactophenol and staining, the nematodes were recognized as S. lupi according to key guidelines of Taylor. Besides, the tissue samples were isolated from esophagus wall - the appendix site of nematode for histopathological investigation - so they were transmissive up to 10% of buffered formalin and stained with haematoxylin and eosin. Microscopic diagnoses in esophagus were included epithelial destruction, wall thickening, inflammatory cells infiltration, necrosis and vascular thrombosis. With the author's knowledge, this is the first report and histopathological investigation of S. lupi in sandy fox. [ABSTRACT FROM AUTHOR]

Background: A standardized method to measure and quantify women's birth experiences is required to study satisfaction of childbirth care. Therefore, this study aimed to translate and culturally adapt the Childbirth Experience Questionnaire (CEQ) for use in Iran. Materials and Methods: This was a cross-sectional study including 203 women who attended 2 hospitals and 2 health centers and met the inclusion criteria in Ahvaz city, between February 2013 and June 2014. After forward and backward translation of the Swedish CEQ into Persian language, content validity was assessed by an expert panel. Scale reliability (internal consistency and test-retest reliability) was assessed with respect to the psychometric properties of the scale. Results: Minor cultural differences were identified and resolved during the translation process. One item was excluded. The intraclass correlation coefficient ranging from 0.63 to 0.90 was satisfactory. Conclusions: The Persian version of the CEQ appears to be valid and reliable; hence, it can be an effective tool in designing childbirth experience interventions and also childbirth care and education interventions for the promotion of positive childbirth experience in Iranian women. [ABSTRACT FROM AUTHOR]

The discussion of factors affecting the acceptance of new technologies in developing countries is very important. The lack of modern technology uses in developing countries, especially in the agricultural (livestock farming) sector, leads to negative effects on the quality and quantity of products and the country loses its ability to compete in the international arena. The main purpose of this study is to investigate the factors affecting on Augmented Reality (AR) technology acceptance in the agricultural (livestock) sector of Iran. In this study, using Meta method, effective factor codes were extracted from AR. The SWARA method was used to weigh the factors affecting the dependent variable based on the opinion of experts. The dependent variable is a qualitative variable that is classified into five levels based on the opinion of experts. We used the multinomial logit model due to the dependent variable is a qualitative variable and has more than two categories. The results showed that, the variables of public participation, and education have a significant effect to accept augmented reality technology at all levels among farmers. The policy recommendations of this research are that councils can play an important role in raising the level of public participation and conveying the demands of the people to the government. To do this, they must receive the necessary training in order to attract public participation. This is possible through training workshops to increase the level of farmers' awareness. • Investigating the impact factors on AR technology acceptance in agriculture sector. • Public participation has a significant effect on the willingness to adopt AR. • Costs and the number of family labor do not have a significant effect to accept AR. [ABSTRACT FROM AUTHOR]

Highly calcareous soils are abundant in Iran. The calcium carbonate equivalent (CCE) of these soils reach up to 650 g kg -1 . Although phosphorus (P) fertilizer is being widely used in these soils, little information, if any, is available about P status in such soils. The objectives of this study were to 1) determine inorganic P forms in 18 surface soils of southern Iran, 2) study P readsorption during different stages of fractionation schemes, 3) assess the ability of NaOH to extract aluminum (Al)‐P, and 4) evaluate the relationships between P availability indices and inorganic P forms. Eighteen soil samples with a wide range of physicochemical properties were selected for this study. Inorganic P forms was determined by sequential extraction with NaHCO 3 , NH 4 OAc, NH 4 F, NaOH, citrate dithionite (CD), and H 2 SO 4 , which are referred to as Ca 2 ‐P, Ca 8 ‐P, Al‐P, Fe‐P, occluded P (O‐P), and Ca 10 ‐P. Phosphorus readsorption in different stages was determined by 1 M MgCl 2 . Furthermore, a fractionation scheme without an NH 4 F step was used to evaluate the ability of NaOH to extract Al‐P. NaHCO 3 (Olsen‐P) and MgCl 2 ‐extractable P (Exch‐P) were regarded as P-availability indices. The abundance of different P forms was in the order Ca 2 ‐P [ABSTRACT FROM AUTHOR]

Desorption of copper (Cu) is an important factor in determining Cu availability in calcareous soils. Kinetics of native and added Cu desorption by DTPA (diethylene-tnaminepentaacetic-acid) from 15 highly calcareous soils of southern Iran were studied in a laboratory experiment. Our results showed that two constant-rate, Elovich, simple Elovich, and parabolic-diffusion equations were the best-fitted equations among eight kinetic models used. The copper desorption pattern based on the parabolic-diffusion equation revealed that the rate of native Cu desorption was higher in the first 2 h followed by a slower release rate, which suggests that two different mechanisms are involved. The trend may describe why the DTPA soil test has been considerably successful in predicting Cu availability in calcareous soils. Stepwise multiple regression equations indicated that CCE (calcium carbonate equivalent), CEC (cation exchange capacity), and clay content are the most important soil characteristics that predict the rate constants of the kinetic models. Mean extractant recovery percentage (ERP) of the soils was only 20%, which indicated that after 20 days, DTPA extracted only one-fifth of added Cu. Regression equations indicated that as soil OM (organic matter) content increased, the value of ERP decreased. From results reported herein it seems that CCE, CEC, and clay are the most important factors controlling Cu release from highly calcareous soils of southern Iran. However, the initial soil Cu desorption rate is probably controlled by CEC. [ABSTRACT FROM AUTHOR]

Documented plant responses to copper (Cu) are rare and consequently Cu soil tests have not received much individual effort. However, soil extraction techniques to measure the status of available Cu for plants are important in the diagnosis of deficiency or toxicity. In the present study, DTPA-CaCl2, EDTA-NH4OAc, EDTA-(NH4)2CO3, DTPA-NH4HCO3, and EDTA were evaluated for their relative efficiency to extract Cu from 26 soil series with a wide range of chemical properties. Wheat (Triticum aestivum L.) was used as a test crop. The results showed that Cu extractability decreased in the order: EDTA-(NH4)2CO3, DTPA-NH4HCO3, EDTA, EDTA-NH4OAc, and DTPA-CaCl2. Significant positive correlations were found between extractable Cu among the five extractions. Stepwise multiple regression equations showed that organic matter (OM) and clay content followed by cation exchange capacity (CEC) and calcium carbonate equivalent (CCE) were the most influential soil characteristics affecting extractable Cu. Mean top dry weight, Cu concentration and Cu uptake were significantly higher in Cu-treated plants than those in untreated plants. Significant correlations were found between Cu extracted with DTPA-CaCl2 and EDTA-(NH4)2CO3 and Cu uptake by wheat. However, the two extractants were not adequately efficient to predict Cu uptake with each accounting for only about 30% of the variation. Among soil properties tested, clay, pH, OM, and CCE correlated negatively and CEC positively with wheat top dry weight, whereas, pH, CEC, and CCE related positively and clay, and OM negatively with Cu uptake. In conclusion, it appears that none of the five test procedures in view of their relatively low coefficient of determinations with plant response proved to be a promising extractant for the determination of available Cu in the soils tested. [ABSTRACT FROM AUTHOR]

Smart Farming is the application of modern technologies, tools and gadgets for increasing the agricultural crops quality and quantity. The Internet of Things (IoT) technology has had a prominent role in the establishment of smart farming. However, the application of this technology could be hard and, in some cases, challenging for the Middle Eastern users. Therefore, the research purpose is to identify the influential factors in the adoption and then application of IoT in smart farming by farmers with a contextualized approach in Iran, a typical Middle Eastern country. Thus, the Unified Theory of Acceptance and Use of Technology (UTAUT) has contextually been used as the theoretical model of the research. The results accentuated and proved the positive impacts of performance expectancy (H1), effort expectancy (H2), social influence (H3), individual factors (H4), and facilitating conditions (H5), on the intention to use IoT technology. Ultimately, the results were indicating the significant impact of behavioral intention on the actual usage of IoT technology (H6). One of the implications of the research is for the IT policymakers in the agricultural sector in the Middle East, where water and cultivable land are two valuable but scarce economic resources. Hence, smart farming could not be promoted unless the farmers had fulfilled its prerequisite factors proposed by the research results for using the IoT technology. • The results proved the positive impacts of Performance expectancy, Effort expectancy, Social influence, facilitating conditions, on the intention to use IoT technology. • In elder farmers and as the age increased, acceptance of change in the work style (using IoT) will hardly happen. • The individuals with higher income are rarely risk takers and they accept the installation cost of modern smart technologies reluctantly. [ABSTRACT FROM AUTHOR]

Abstract: The impact of a single nucleotide polymorphism (SNP) in the CD24 gene on the risk and progression of multiple sclerosis (MS) was investigated in the Iranian population. Our data revealed that the susceptibility and the progression of MS in individuals with the CD24V/V genotype were greater than in those with the CD24A/V and CD24A/A genotypes. [Copyright &y& Elsevier]

The fate of antibiotics and their effects on plant growth may be changed by the application of fertilizers. The present study was carried out to investigate the effect of sulfadiazine (SDZ), rice husk compost (RHC), rice husk biochar (RHB), and mycorrhiza (MR) on the growth attributes of Iranian Echium amoenum Fisch & C.A. Mey. A greenhouse experiment as a completely randomized design with six treatments of bio/organic-fertilizers (no bio-fertilizer (NF), RHB, RHC, MR, RHB+MR, and RHC+MR) and three levels of SDZ application (0, 100, and 200 mg kg -1 ) was performed for 7months with three replicates. Shoot and root SDZ concentrations were determined using high-pressure liquid chromatography-diode array detection (HPLC-DAD) instrumentation. The results revealed that the application of RHC, RHB, and MR had a significant impact on the reduction of the toxicity effects of SDZ on plant properties. The lowest values of growth parameters belonged to the 200 mg kg -1 of SDZ with no bio-fertilizers, while the highest growth parameters were observed in the treatments of RHB+MR, and RHC+MR with no SDZ application. Also, chlorophyll pigments content was affected by used treatments and the lowest rates of chlorophyll a (4.24), chlorophyll b (2.99), and carotenoids (2.88) were related to the 200 mg kg -1 of SDZ with no biofertilizers application. The co-application of bio-fertilizers and SDZ (at both levels of 100 and 200 mg kg -1 ) decreased SDZ uptake by both shoot and root in comparison with the control. The same results were obtained with macro (NPK) and micro (Fe, Zn, Cu, and Mn) nutrients uptake by the shoot in which the lowest values of nutrients uptake were observed in treatment of 200 mg kg -1 of SDZ with no bio-fertilizers. Furthermore, in the case of the effect of the used treatments on root colonization, the results showed that the lowest value (7.26%) belonged to the 200 mg kg -1 application of SDZ with no bio-fertilizers. Generally, this study demonstrated that bio-fertilizers could be considered as an effective strategy in controlling the negative effects of antibiotics on the growth properties and nutrients status of the plants grown in such contaminated soils., (Copyright © 2020 Elsevier Inc. All rights reserved.)