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Students’ academic achievement is a multifaceted phenomenon. While depression can suppress academic performance, academic satisfaction can promote it. This study aims to investigate the relationship between depression and academic satisfaction among students studying at Shahroud University of Medical Sciences.

This cross-sectional study was carried out on 312 undergraduate students of Shahroud University of Medical Sciences. Data collection tools included demographic data form, University Student Depression Inventory and academic satisfaction scale. Data were collected by a simple random sampling method and self-reporting by the participants. Data were analyzed using descriptive and inferential statistics (multivariate multiple regression analysis and multivariate linear regression).

The participants’ mean depression and academic satisfaction scores were 71.92 ± 22.94 and 53.70 ± 9.69, respectively. In addition, the depression score was significantly and inversely correlated with students' academic satisfaction (r = −0.122, p-value = 0.031). Moreover, there was a significant correlation between students’ depression with marital status, level of the semester, interest in the field of study and study topic.

This study emphasizes improving education, spiritual and social support and strengthens strategies to deal with depression and medical science students’ related factors.

Students of medical sciences are exposed to depression during their college years, which is related to their academic satisfaction.

Many opinion-mining systems and tools have been developed to provide users with the attitudes of people toward entities and their attributes or the overall polarities of documents. In addition, side effects are one of the critical measures used to evaluate a patient’s opinion for a particular drug. However, side effect recognition is a challenging task, since side effects coincide with disease symptoms lexically and syntactically. The purpose of this paper is to extract drug side effects from drug reviews as an integral implicit-opinion words.

This paper proposes a detection algorithm to a medical-opinion-mining system using rule-based and support vector machines (SVM) algorithms. A corpus from 225 drug reviews was manually annotated by a medical expert for training and testing.

The results show that SVM significantly outperforms a rule-based algorithm. However, the results of both algorithms are encouraging and a good foundation for future research. Obviating the limitations and exploiting combined approaches would improve the results.

An automatic extraction for adverse drug effects information from online text can help regulatory authorities in rapid information screening and extraction instead of manual inspection and contributes to the acceleration of medical decision support and safety alert generation.

The results of this study can help database curators in compiling adverse drug effects databases and researchers to digest the huge amount of textual online information which is growing rapidly.

Health is one of the most basic human rights. This study aims to examine the pattern of unmet health services needs and barriers to use health services among people with disabilities.

This cross-sectional study was conducted among people with disabilities in Sanandaj, the capital of a less economically developed province in western Iran in 2020. In total, 548 samples were selected using random sampling, and data were collected using a questionnaire. Chi-square test and Fisher's exact test were used to examine the relationship between independent variables including demographic variables and dependent variables. Statistical tests were performed using STATA software package.

About 64% and 23% of participants needed outpatient and inpatient services, respectively. The gap between the perceived need and using health services for outpatient and inpatient services was reported to be 55% and 30%, respectively. The main reasons for not seeking the required health care were “insufficient coverage of costs by insurance” and “lack of physical access.” Having supplementary insurance and better economic status were significantly correlated with using outpatient care and having supplementary insurance and type of disability had a significant relationship with using inpatient care.

There was a big gap between the perceived need, seeking for and receiving health services in people with disabilities. Designing and implementing appropriate interventions to reduce barriers on the way of transforming, the need for health services into demand in the population of people with disabilities should be on the agenda of policymakers and relevant managers in the country.

Silicone softeners are widely used in the textile industry to improve the performance of textile products. The thermal characteristics and flammability of polyester fabrics can be influenced by these compounds, which need to be considered, as important issues of human safety. The purpose of this paper is to investigate the changes induced on the polyester fibre by silicone softener treatment using a pad/dry/cure method.

The fibres were first treated with nano‐ and microemulsion silicone softeners. The influence of the silicone emulsion type on thermal properties and flammability of the resultant samples were investigated by various analytical techniques, namely, the differential scanning calorimetry (DSC), thermal gravimetric analysis (TGA), dynamical mechanical thermal analysis (DMTA) and horizontal flammability test (HFT).

Results showed that the silicone softeners increase the thermal degradation and flammability of the polyethylene terephthalate (PET) substrate.

The paper's study of thermal and flammability of the silicone‐treated sample is novel and can be used to optimize the properties of silicone polymers during production and consumption.

The purpose of this paper is to propose the sustainable housing (SH) model for the housing of Region-one of Mashhad city in Iran.

Building the SH particularly increases mitigation measures as well as creates healthier environments for inhabitants by decreasing harmful environmental and physical effects. This research in terms of the target is applied research that has been done with the descriptive-analytical method. The research population is residents who live in the Region-one of Mashhad, with a statistical sample of 384 people. The responses were collected from the questionnaire, and structural equation modeling (SEM) was employed to illustrate the research SH model in AMOS software.

The findings indicate that the suitability of the housing model with meeting needs together with the quality of the health situation in housing has the most influences, and in contrast, the number of residential units with building permits besides the amount of home green space has the least influences on the sustainability of housing in the region.

The results can offer valuable insights for helping the sustainability of housing in the studied area and similar cases, which may vary in a different context.

The new aspect of the study is to provide the SH model by SEM, which has not been investigated in almost all previous research. This paper makes a contribution to the understanding of the physical and environmental components that affect the sustainability of housing in Region-one of Mashhad city in Iran according to respond to the needs of both lifestyles: pilgrims-tourists and residents. The results can also contribute to housing stabilizing in other developing countries, especially the pilgrimage and tourism countries.

Hexagonal honeycombs with meso-metric cell size show excellent load bearing and energy absorption potential, which make them attractive in many applications. However, owing to their bend-dominated structure, honeycombs are susceptible to deformation localization. The purpose of this study is to provide insight about shear band propagation in struts of 3D-printed honeycombs and its relation to the achieved macroscopic mechanical behavior.

Hexagonal honeycombs and unit cell models are 3D-printed by fused deposition modeling (FDM). The samples are exposed to compression loading and digital image correlation technique and finite element analyses are incorporated.

It is found that the strain contours, which are obtained by finite element, are in agreement with experimental measurements made by DIC. In addition, three stages of shear band propagation in struts of 3D-printed honeycombs are illustrated. Then the correlation between shear band propagation stages and the achieved macroscopic mechanical responses is discussed in detail.

For the first time, a hierarchical activation of different modes of shear band propagation in struts of a 3D-printed honeycomb is reported. This information can be of use for designing a new generation of honeycombs with tailor-made localization and energy absorption potential.

This research is about embedding service-based supply chain management (SCM) concepts in the education sector. Due to Canada's competitive education sector, the authors focus on Canadian universities.

The authors develop a framework for evaluating and forecasting university performance using data envelopment analysis (DEA) and artificial neural networks (ANNs) to assist education policymakers. The application of the proposed framework is illustrated based on information from 16 Canadian universities and by investigating their teaching and research performance.

The major findings are (1) applying the service SCM concept to develop a performance evaluation and prediction framework, (2) demonstrating the application of DEA-ANN for computing and predicting the efficiency of service SCM in Canadian universities, and (3) generating insights to enable universities to improve their research and teaching performances considering critical inputs and outputs.

This paper presents a new framework for universities' performance assessment and performance prediction. DEA and ANN are integrated to aid decision-makers in evaluating the performances of universities.

The findings suggest that higher education policymakers should monitor attrition rates at graduate and undergraduate levels and provide financial support to facilitate research and concentrate on Ph.D. programs. Additionally, the sensitivity analysis indicates that selecting inputs and outputs is critical in determining university rankings.

This research proposes a new integrated DEA and ANN framework to assess and forecast future teaching and research efficiencies applying the service supply chain concept. The findings offer policymakers insights such as paying close attention to the attrition rates of undergraduate and postgraduate programs. In addition, prioritizing internal research support and concentrating on Ph.D. programs is recommended.

This study aims to numerically explore the heat transfer characteristics in turbulent two-degree-of-freedom vortex-induced vibrations (VIVs) of three elastically mounted circular cylinders.

The cylinders are at the vertices of an isosceles triangle with a base and height that are the same. The finite volume technique is used to calculate the Reynolds-averaged governing equations, whereas the structural dynamics equations are solved using the explicit integration method. Simulations are performed for three different configurations, constant mass ratio and natural frequency, as well as distinct reduced velocity values.

As a numerical challenge, the super upper branch observed in the experiment is well-captured by the current numerical simulations. According to the computation findings, the vortex-shedding around the cylinders increases flow mixing and turbulence, hence enhancing heat transfer. At most reduced velocities, the Nusselt number of downstream cylinders is greater than that of upstream cylinders due to the impact of wake-induced vibration, and the maximum heat transfer improvement of these cylinders is 21% (at U_r = 16), 23% (at U_r = 5) and 20% (at U_r = 15) in the first, second and third configurations, respectively.

The main novelty of this study is inspecting the thermal behavior and turbulent flow–induced vibration of three circular cylinders in the triangular arrangement.

This study aims to render a pattern for heritage restoration in the context of reusing historic buildings, to assist the authorities with decision-making process on the most appropriate time during the building’s life cycle. Here, the adaptive reuse potential (ARP) model is used to find the most appropriate time for adaptive reuse and calculating the useful life as well as the potentiality of the Amir Nezam House so a viable solution can be put forward.

In this research, a quantitative and qualitative method is adopted to evaluate the useful life and potentiality of the Amir Nezam House of Tabriz to determine the most appropriate time for next intervention.

Results show that the potential (ARP score) of the Amir Nezam House is increasing, the value of which will be greater than 50 percent by the next few years. Evaluations show that the most appropriate time for further intervention is the year 2035.

The significance of this research lies within the objective of proposing a preventive and protective schedule for historic buildings before they reach their life expectancy with an emphasis on environmental, economic, social and functional sustainability as well as environmental impacts. ARP model has been applied to implement this concept in the Amir Nezam House, Tabriz, Iran.

This study aimed at exploring the antecedents of English as a Foreign Language (EFL) teachers' self-efficacy (SE). That is, the main purpose was to deeply delve into the main variables and latent which lead to a high sense of SE among teachers of English as a foreign language.

A phenomenological inquiry was employed to explore the antecedents of language teachers from their eyes. In this study, the phenomenon is SE antecedents. The researchers employed this method to help identify the meaning behind the human experience as it is related to a phenomenon or notable collective occurrence. A semistructured interview checklist was developed, carefully worded, reviewed by five teacher educators known as experts in qualitative research methodology and teacher education and edited based on the experts' feedback

The findings showed that the antecedents of SE can be categorized into personal variables, educational variables and institutional variables. Personal variables include verbal intelligence, language proficiency and some other traits. The institutional variables include support from administration, support from colleagues, support from the community and quality of work life. The educational antecedents include preservice and in-service training courses. Preservice training courses included the following: the courses on general language skills, courses on teaching methods, practicum courses, etc.

This study was undertaken in a specific context and the participants are specific. Almost all studies on SE are quantitative, and this qualitative study explored the antecedents of teachers' SE from their own eyes. Some of the explored studies were not mentioned in any of the related studies.