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The purpose of the present survey is to identify and measure generic core competencies essential for Iranian library and information science (LIS) students.

The study population included all undergraduate LIS students in Iran, and the sample included all undergraduate LIS students in the three universities of Tehran, Shahid Chamran and Ferdowsi of Mashhad. The study was performed during the second semester (February to May) of the 2010-2011 academic year. After a thorough review of the literature, a pattern for generic core competencies was formulated and, accordingly, a researcher-designed questionnaire was developed and distributed. The final data analysis was carried out using 207 completed questionnaires, and the data were analysed using the SPSS19 software.

Except for English and management, the major participants’ scores mean for the 12 identified generic core competencies were higher than the total mean.

Besides presenting a new theoretical pattern for measuring core generic competencies, especially for students in the LIS field, the study is expected to help higher education planners to channel their efforts into strengthening the examined competencies.

This study aims to identify the key activities after sales and the intended criteria by the customers, considering their expected services after the product purchase process.

This study is a qualitative approach, and the co-creation logic and the Delphi technique were used in two rounds to design and validate the proposed model. To achieve this study’s aims, extensive literature, interviews, interaction and exploratory meetings were reviewed with manufacturers and consumers, and then the dimensions of the proposed model were regulated, corrected and validated in the two-round Delphi technique. The final model is presented after establishing the model in the test pilots and getting feedback from industry experts. To present a conceptual model, the enabler’s logic and the underlying results in the European Foundation for Quality Management (EFQM) Excellence Model were used.

The findings of this study include the identification of dimensions for the after-sales services model and the designing of a conceptual model in both sections of enablers and results. The enabler section of the proposed model includes seven dimensions, three main sectors and four support sections.

This model can be used to design, deploy or improve after-sales services system in manufacturing companies.

For the first time in an innovative procedure, the approach of value co-creation was used to design one of the organizational systems (after-sale services system). On the other hand, the conceptual pattern was proposed inspired by the EFQM Excellence Model, to create the necessary proportionality between the enabler and results sections.

This paper proposes a novel deep learning based method towards the identification of a pistachio tree cultivar from its image.

The investigated scope of this study includes Iranian commercial pistachios (Jumbo, Long, Round and Super long) trees. Effective use of high-resolution images with standard deep models is addressed in this study. A novel image patches extraction method is also used to boost the number of samples and dataset augmentation. In the proposed method, handcrafted ORB features are used to detect and extract patches which may contain identifiable information. An innovative algorithm is proposed for searching and extracting these patches. After extracting patches from initial images, a Convolutional Neural Network, named EfficientNet-B1, was fine-tuned on it. In the testing phase, several patches were extracted from the prompted image using the ORB-based method, and the results of their prediction were consolidated. In this method, patch prediction scores were in descending order, sorted by the highest score in a list, and finally, the average of a few list tops was calculated and the final decision was made.

Examining the proposed method on the test images led to an achievement of a recognition rate of 97.2% accuracy. Investigation of decision-making in the test dataset could reveal that this method outperformed human experts.

Cultivar identification using deep learning methods, due to their high recognition speed, lack of specialist requirement, and independence from human decision-making error is considered as a breakthrough in horticultural science. Variety cultivars of pistachio trees possess variant characteristics or traits, accordingly recognising cultivars is crucial to reduce the costs, prevent damages and harvest the optimal yields.

Today, coronavirus disease-19 (COVID-19) treatment is an evolving process, and synbiotic administration has been suggested as a new therapeutic strategy. This study aims to investigate the effect of synbiotic supplementation in COVID-19 patients.

In this placebo-controlled trial, 80 patients were randomized to receive oral synbiotic capsule (containing fructooligosaccharide and seven bacterial strains; Lactobacillus (L) casei, L. rhamnosus, Streptococcus thermophilus, Bifidobacterium breve, L. acidophilus, Bifidobacterium longum, L. bulgaricus, each one 109 colony-forming units) or placebo for two months. Inflammatory markers (Interleukin-6 [IL-6], C-reactive protein [CRP], erythrocyte sedimentation rate [ESR]) and white blood cell (WBC) count were evaluated at two timepoints (baseline, two months later). The measured variables were adjusted for confounders and analyzed by SPSS v21.0.

All 80 enrolled patients completed the study. The study adherence was good (approximately 70%). The mean changes for IL-6 were not significant (Δ = −0.6 ± 10.4 pg/mL vs Δ = +11.2 ± 50.3 pg/mL, p > 0.05). There were no significant improvements for CRP, ESR and WBC.

Administration of synbiotics for two months did not improve inflammatory markers in COVID-19 patients.

Teachers can be regarded as key figures in climate change education (CCE). Therefore, the purpose of this study is assessment of Iranian lower secondary teachers? level of knowledge, attitudes and practices toward CCE in a less-touched-upon context.

The present study used a cross-sectional survey design, which used a specially designed questionnaire administered in ten high schools (five boys’ and five girls’ lower secondary schools). A sample of 108 lower secondary school teachers was selected through a multistage stratified random sampling technique. The gender structure of the sample was 48.1 per cent male and 51.9 per cent female subjects. To determine the status of teachers’ knowledge, attitudes and practices, the obtained quantitative data were classified into three categories on a scale of 100 per cent: good status (more than 75 per cent), moderate status (50-75 per cent) and weak status (less than 50 per cent).

The findings revealed that the involved teachers were equipped with an appropriate knowledge, i.e. 22.2 per cent good and 52.8 per cent moderate levels of knowledge. Furthermore, the subjects’ level of attitude was moderate (44.5 per cent); however, their level of practice was weak (52.8 per cent). In terms of gender, male subjects’ knowledge and attitude levels were higher than those of female subjects. However, female subjects reported higher levels of practice in comparison with male subjects. Overall, the results of this study highlighted the necessity of improving lower secondary teachers’ CCE in general and of the level of their attitudes and practices in particular.

The present study sheds more light on the change management and environmental education within the Iranian context. The results of this study accentuate the necessity of presenting more CCE programs for teachers. Furthermore, curriculum planners can take advantage of the obtained results to carry out curriculum reforms.

The purpose of this paper is standardize and provide a multidimensional measure for assessing human resources competencies (HRCs) scale.

The data collected in this study were 2018 from the 234 people selected from 603 managers and experts in human resources of selected firms existing in the Yazd Industrial Town randomly. Based on the model of HRCs designed by Ulrich et al. (2008), a questionnaire was developed to assess HRCs. Internal consistency and split-half methods were used to obtain the reliability of the instrument. Content validity and construct validity of the instrument were also assessed through exploratory factor analysis (EFA) and confirmatory factor analysis (CFA).

This paper elucidates a key scale for assessing HRCs including three dimensions: knowledge business, functional expertise and managing change. Also, results revealed that two items were then dropped from the questionnaire as they were unreliable, and a final 31 items were extracted to form the scale for assessing HRCs. The coefficients for Cronbach’s α and split-half were 0.963 and 0.947, respectively. In EFA, Kaiser-Meyer-Olkin test yielded optimal 0.962, and Bartlett’s test was statistically significant. Additionally, three factors with eigenvalues higher than 1 explained 63% of the total variance. Hence, CFA confirmed the results from EFA too. Moreover, the model proved to enjoy a good fit.

The scale is useful for both researchers and practitioners. Also, the scale provides researchers with a sought-after conceptualization of HRCs.

Consequently, considering that the validity and reliability indices of HRCs were estimated to be desirable, the authors believe that the developed questionnaire can be used as an appropriate scale for measuring HRCs in future research.

Nowadays, designing environmentally compatible buildings with acceptable performance in terms of cost, materials, and energy efficiency is considered crucial for developing sustainable cities. This research aims to identify and rank the most influential factors in the application of Building Information Modeling (BIM) systems in the smartification of green and sustainable buildings.

The present research is applied and descriptive. In this study, we identified the most influential factors in the application of Building Information Modeling (BIM) systems through library studies and expert opinions. Data were collected using a questionnaire, and a combination of the one-sample t-test method with a 95% confidence level and the fuzzy VIKOR method was employed for analysis.

The results show that the most influential factors in the application of Building Information Modeling (BIM) systems in the Smartification of green and sustainable buildings, in order, are: “Energy saving and consumption reduction,” “Increased productivity and efficiency,” “Life-cycle assessment (LCA),” “Eco-friendly design,” “Integration with IoT and other technologies.”

In this study, while addressing the intersection of BIM technology, green building principles, and smart building objectives to optimize the performance of buildings during their life cycle, the most influential factors in the use of this system were ranked based on the criteria of “impact level,” “importance level,” and “availability of necessary tools” for implementation in Kerman. Moreover, solutions for more effectively utilizing this system in the smartification of green and intelligent buildings were proposed.

This paper aims to propose a new nonlinear function estimation fuzzy system as a novel statistical approach to estimate nanofluids’ thermal conductivity.

A fuzzy system having a product inference engine, a singleton fuzzifier, a center average defuzzifier and Gaussian membership functions is proposed for this purpose.

Results indicate that the proposed fuzzy system can predict the thermal conductivity of Al₂O₃/paraffin nanofluid with appropriate precision and generalization and it also outperforms the classic interpolation methods.

A new nonlinear function estimation fuzzy system was introduced as a novel statistical approach to estimate nanofluids’ thermal conductivity for the first time.