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This study was conducted to investigate the impact of indoor environmental quality (IEQ) and internal design on the performance of students in university dormitories in Tehran and North Cyprus.

Using a survey questionnaire, 298 students living in student dormitories in Tehran and North Cyprus were surveyed for data collection.

Research has shown that the academic performance and well-being of students are heavily impacted by factors related to IEQ and internal design. The study conducted in Tehran and North Cyprus has identified the most effective components of IEQ and internal design for student dormitories. The study suggests that proper ventilation, furniture design, temperature control and lighting design are key factors that significantly affect IEQ and internal design. Control and lighting design are key factors that significantly affect IEQ and internal design.

Originality: The study utilizes a comparative study designed to analyze the differences and similarities between the two locations.

The purpose of this paper is to compare the stability of the three nanocarriers created by DNA origami method with different positions and numbers of crossovers

Nanocarriers are attractive components among a variety of nanostructures created by DNA origami and can have numerous applications in mechanical and medical engineering. For this reason, the current study compares three nanotubes with different positions and numbers of crossovers created by DNA origami method that can be utilized as nanocarriers. To investigate the structures, the DNA nanocarriers are studied at the human body temperature 310 K. Molecular dynamics simulations are used for this study. For a quantitative analysis of DNA nanocarriers, the areas of three hexagons at three different sites in each of the nanotubes are investigated. The results indicate that the number and position of crossovers are among the significant factors in the structure stability of nanocarriers. The analyses also revealed that although adding crossovers in locations with fewer crossovers increase structural stability, the position of crossovers can have different effects on the stability. DNA origami-based nanocarriers can be implemented in drug delivery, allow the nanocargoes to pass various surfaces and act as filters for passing cargoes of different dimensions and chemical structures.

The results indicate that the number and position of crossovers are among the significant factors in the structure stability of nanocarriers

In this paper, the stability of DNA origami nanocarriers with different positions and numbers of crossovers was investigated.

The purpose of this paper is to present the factors affecting purchase intention of foreign food products in the Iranian context.

The present study is a survey research and has a quantitative approach. According to Morgan’s table, 384 people were selected as sample size. Based on an in-depth review of previous literature, a comprehensive set of sub-factors related to customer’s purchase intention was extracted to design questionnaire. Then, exploratory factor analysis and confirmatory factor analysis were applied to identify and confirm the factors affecting purchase intention of foreign food products in Iran.

The obtained results illustrate 13 factors as follows: “corporate social responsibility,” “customer knowledge and awareness,” “perceived risk,” “retailer’s commercial image,” “customer’s personality characteristics,” “social identity,” “product features,” “attitude,” “country-of-origin,” “perceived value,” “subjective norm,” “loyalty” and “perceived behavioral control.”

As the present research was carried out in the Iranian context, the generalization of the findings is limited and caution should be taken in this regard.

The identified factors could contribute to international food companies and retailers to understand customers’ expectations and to gain more market share in Iran.

The originality of this paper lies in identifying a comprehensive set of the factors affecting purchase intention of foreign food products and developing the theoretical literature in the field of the present research.

Understanding the factors that influence individuals’ adherence to social distancing is critical to effective policymaking in respiratory pandemics such as COVID-19. This study aims to explore the role of social factors in relation to social distancing measures.

Stratified convenience sampling was used in this survey research, involving 450 adults residing in both rural and urban areas of Aligodarz County, Lorestan, Iran.

The findings showed that approximately 14% of participants did not adhere to any of the assessed social distancing behaviors, while only around 30% adhered to all four assessed behaviors. On average, participants reported having 5.13 (SD = 3.60) close physical contact within the 24 h prior to completing the questionnaire. Bridging social capital and gender emerged as the most frequently observed predictors across the assessed social distancing measures. Additionally, age, employment status and residential setting were identified as influential factors for some of the evaluated measures.

This study contributes to the field by highlighting that the likelihood of non-adherence to social distancing measures tends to increase among male participants, those aged above 60, employed individuals, urban residents and those with a higher level of bridging social capital.

Osteoporosis is increasingly affecting the young female adults of the Iranian population. The role of nutrition and physical activity on bone mineral content (BMC) and bone mineral density (BMD) in young female students has not been fully examined. This study aims to assess the dietary intake of several nutrients, such as calcium, phosphorus and protein; serum concentrations of vitamin D; and physical activity and their relationship with BMC and BMD in young female students.

Three-day dietary intakes of 67 female students were measured via duplicate portion sampling (DPS) method. Calcium and phosphorus content of the food samples were determined using atomic absorption spectrophotometer. Protein intake was determined by Kjeldahl method. Serum 25(OH) D concentrations were measured using enzyme-linked immunosorbent assay. Lumbar spine and femoral neck BMD were measured using dual-energy X-ray absorptiometry (DEXA).

The mean ±SD dietary intake of protein, calcium and phosphorus was 58.8 ± 16.9 g/day, 388 ± 135 mg/day and 1884 ± 682 mg/day, respectively. Significant positive correlation was found between serum vitamin 25(OH) D concentrations and BMC of lumbar spine (r = 0.28, p = 0.016) and BMD of femoral neck (r = 0.29, p = 0.016). Moreover, the authors observed a significant positive correlation between physical activity and femoral neck BMC (r = 0.26, p = 0.03) and BMD (r = 0.28, p = 0.02). This study found no significant associations between dietary intakes of protein, calcium and phosphorus and bone density measurements.

In this study, the authors measured the dietary intake of protein, calcium and phosphorus using DPS method. This study highlights the role of physical activity and serum vitamin 25(OH) D concentrations in female students’ bone health.

The accounting system plays an important role in the company’s organizational structure. The purpose of this paper is to demonstrate that the integration of management accounting practices is subject to coordination between external and internal factors and accounting management practices.

Therefore, the authors move to the contingency model to determine the most significant external “unexpected factors” that explain the introduction of management practices for the management of the various stages of development. The exploratory study examines a sample of Pakistani companies from various sectors.

This study reveals that the main factors of uncertainty that affect the organizational structure, environmental uncertainty, advanced production technology, just-in-time method strategy, integrated management of quality and structure findings reveal that MAP affected all process and changes all system in simple to complex system in Pakistani’s industries.

This study is to acquisition the impact of external factors on management accounting practices, to find the impact of internal factors on management accounting practices, to establish the management accounting practices undertaken by the companies in Pakistan.

The study contributes to the literature by enhancing our understanding for the impact of external and internal factors on management accounting practices in Pakistan.

The purpose of this paper, because of the complexity of demand time series and the need to construct a more accurate hybrid model that can model all relationships in data, is to propose a parallel-series hybridization of seasonal neural networks and statistical models for demand time series forecasting.

The main idea of proposed model is centered around combining parallel and series hybrid methodologies to use the benefit of unique advantages of both hybrid strategies as well as intelligent and classic seasonal time series models simultaneously for achieving results that are more accurate for the first time. In the proposed model, in contrast of traditional parallel and series hybrid strategies, it can be generally shown that the performance of the proposed model will not be worse than components.

Empirical results of forecasting two well-known seasonal time series data sets, including the total production value of the Taiwan machinery industry and the sales volume of soft drinks, indicate that the proposed model can effectively improve the forecasting accuracy achieved by either of their components used in isolation. In addition, the proposed model can achieve more accurate results than parallel and series hybrid model with same components. Therefore, the proposed model can be used as an appropriate alternative model for seasonal time series forecasting, especially when higher forecasting accuracy is needed.

To the best of the authors’ knowledge, the proposed model, for first time and in contrast of traditional parallel and series hybrid strategies, is developed.

This study aims to activated carbon prepared from pistachio waste by using phosphoric acid as chemical activator agent. Activated carbon adsorbents were prepared from pistachio waste by using phosphoric acid as chemical activator agent.

The optimum conditions for the highest adsorption performance were determined by central composite design (CCD). The adsorbent was used for the adsorption of dye reactive black 5 (RB5), and the parameters affecting the adsorption were discussed like pH, initial concentration, contact time and adsorbent dosage. The adsorbent synthesized has been characterized by FTIR spectroscopy and scanning electron microscopy. The kinetic models including pseudo-first-order, pseudo-second-order and intraparticle diffusion with Langmuir and Freundlich isotherm models were applied to investigate the kinetic and isotherms parameters.

When the dye concentration is 10 mg/L, RB5 dye removal rates reach 87.5 per cent. Moreover, the adsorption process of RB5 follows the pseudo-second-order kinetics and the Freundlich adsorption isotherm.

This study provided a simple and effective way to prepare activated carbon adsorbents from pistachio wastes. This way was conductive to protect environmental from a huge amount of agricultural waste produced and subsequent application for removal of pollutants from aqueous solutions.

The activated carbon adsorbents are prepared via chemical activation, which is prepared with pistachio wastes. There are two main innovations: one is that the novel adsorbents are prepared successfully by waste and the other is that the optimized conditions are designed by CCD.

Based on the positive features of the shark smell optimization (SSO) algorithm, the purpose of this paper is to propose a method based on this algorithm, dynamic voltage and frequency scaling (DVFS) model and fuzzy logic to minimize the energy consumption of integrated circuits of internet of things (IoT) nodes and maximize the load-balancing among them.

Load balancing is a key problem in any distributed environment such as cloud and IoT. It is useful when a few nodes are overloaded, a few are under-loaded and the remainders are idle without interrupting the functioning. As this problem is known as an NP-hard one and SSO is a powerful meta-hybrid method that inspires shark hunting behavior and their skill to detect and feel the smell of the bait even from far away, in this research, this study have provided a new method to solve this problem using the SSO algorithm. Also, the study have synthesized the fuzzy logic to counterbalance the load distribution. Furthermore, DVFS, as a powerful energy management method, is used to reduce the energy consumption of integrated circuits of IoT nodes such as processor and circuit bus by reducing the frequency.

The outcomes of the simulation have indicated that the proposed method has outperformed the hybrid ant colony optimization – particle swarm optimization and PSO regarding energy consumption. Similarly, it has enhanced the load balance better than the moth flame optimization approach and task execution node assignment algorithm.

There are many aspects and features of IoT load-balancing that are beyond the scope of this paper. Also, given that the environment was considered static, future research can be in a dynamic environment.

The introduced method is useful for improving the performance of IoT-based applications. We can use these systems to jointly and collaboratively check, handle and control the networks in real-time. Also, the platform can be applied to monitor and control various IoT applications in manufacturing environments such as transportation systems, automated work cells, storage systems and logistics.

This study have proposed a novel load balancing technique for decreasing energy consumption using the SSO algorithm and fuzzy logic.

This study aims to examine the relationship between polychronicity, job autonomy, perceived workload, work–family conflict and high work demand on the health-care employee turnover intention during the COVID-19 pandemic.

The authors conducted quantitative research in private hospitals using a self-administered questionnaire, and 264 respondents participated. The authors also used an analysis of moment structures to determine the relationship between independent and moderating variables.

The results show a significant positive relationship between polychronicity, job autonomy, perceived workload, work–family conflict and high work demand, affecting turnover intention. This study also found the moderating effect of high work demand on work–family conflict and turnover intention.

This research was limited to hospitals in Bahrain during the COVID-19 pandemic. Nevertheless, the findings highlight the factors associated with health-care employee turnover intention and only five factors were identified.

This study enhances the theoretical and practical effects of turnover intention. The results provide a competitive benchmark for hospital managers, administrators and governing bodies of employee retention.

It advances economics and management theory by enhancing the understanding of health-care employees’ turnover intention in Bahrain. It serves as a basis for future large-scale studies to test or refine existing theories.

To the best of the authors’ knowledge, this study is the first to adopt extrinsic variables in self-determination theory to measure the turnover intention of health-care employees. However, using resources in a crisis can be applied to any disaster.