University of Gonabad

ABSTRACT Reliability assessment of complex engineering systems is crucial for ensuring safety, performance, and cost‐effectiveness. Traditional reliability models frequently treat failure rates as static and analyze component failure rates in isolation. When dependencies are acknowledged, they are typically considered in a linear manner. This approach, however, fails to adequately capture the dynamic and nonlinear interactions that characterize real‐world systems. This paper proposes a novel reliability modeling framework that integrates dynamic failure rates and nonlinear dependencies to enhance predictive accuracy in reliability analysis. The model considers time‐varying operational and environmental factors that influence failure behavior, along with nonlinear interdependencies among system components, which can amplify risks in unpredictable ways. The proposed framework improves reliability estimation under evolving conditions. To illustrate the implications of the proposed model assumptions, the model is applied on two numerical examples and to demonstrate the impact of the model assumptions, the reliability is compared with the case where these assumptions are not considered. The findings of this research contribute to the advancement of reliability engineering by providing a more comprehensive approach to modeling failures in dynamic, interconnected systems.

Enhancing learning results in the field of language education requires a vital responsibility of cultivating motivation and self-efficacy among learners of English as a Foreign Language (EFL). Key determinants that may impact these psychological characteristics include reflective thinking, academic mindfulness, and teacher support. This study examines the traces of reflective thinking, academic mindfulness, and teacher support on Motivation and Educational Self-efficacy in a sample of 318 EFL learners in AI-enhanced EFL learning. By using Structural Equation Modeling (SEM) and Confirmatory Factor Analysis (CFA) with Lisrel, the study demonstrates that reflective thinking and academic mindfulness are crucial elements in improving learners’ motivation and self-efficacy. Moreover, the supporting function of teachers is recognized as crucial in fostering a favorable learning atmosphere. The results emphasize the interdependence of these components, indicating that the combination of reflective practices and mindfulness techniques, along with strong teacher support, may greatly enhance educational results in AI-enhanced learning environments. This study augments the comprehension of motivational dynamics and provides practical insights for instructors seeking to improve the experiences of EFL learners.

<h3>Introduction</h3> Flow Re-Direction Endoluminal Device X (FRED^TM-X, MicroVention, Inc., Terumo Corporation, USA), introduces a dual-layer structure and antithrombotic surface technology, designed to address the limitations of earlier devices in reducing material thrombogenicity and promoting better vessel endothelialization for brain aneurysm. <h3>Aim of study</h3> We present the first systematic review and meta-analysis summarizing available literature to reach a consensus regarding the safety and effectiveness of FRED^TM-X. <h3>Method</h3> A literature search was performed for studies that evaluated FRED-X in managing intracranial aneurysms. Proportions were pooled employing the inverse variance method, and binary outcomes were analyzed using odds ratio (OR) and 95% confidence interval (CI). The primary outcome of the measure was an aneurysm occlusion at the final follow-up. <h3>Results</h3> Eight studies involving 709 patients and 728 aneurysms were included. Most aneurysms were unruptured (87.3%, 95%CI=77.3% – 95%) and located in anterior circulation (85.1%, 95%CI= 73.9% – 93.8%), primarily in internal carotid artery (67.5%). Procedural data showed mean procedure time of 68.2 (SD=38.1) minutes and a fluoroscopy time of 23.5 (SD=11.7) minutes. Mean aneurysm size was 6.4 mm (SD = 5.1). In-stent stenosis occurred in 1.2% of cases. Adequate occlusion was achieved in 81.6% (95%CI=76.9% – 85.9%) of patients at last follow-up. Symptomatic complications occurred in 5.1% (95%CI=2.2% – 8.8%) of patients, and mortality rate was 0.07% (95%CI=0.0% – 0.72%). <h3>Conclusion</h3> FRED-X flow diverter is safe and effective in treating intracranial aneurysms. It has low complication rates, minimal in-stent stenosis, and efficient procedural metrics. Long-term studies must confirm its durability and potential for broader applications. <h3>Conflict of Interest</h3> No

Geochemical data are expressed in closed numerical systems due to their non-normality and the presence of outliers. The specificity of such data makes it challenging to analyze them using standard statistical techniques. The U-modeling of log-transformed data represents a novel approach to geochemical anomaly separation. This method models the geochemical open or log-transformed data by the U-spatial statistics algorithm and has been used for the first time in this paper. In this research, Additive and Centered Logarithmic Transformations (ALR and CLR) were applied to data from the Doostbiglou region in Ardabil province, Iran, known for its copper-gold and molybdenum mineralization. After transforming the data into an open numerical system, the correlation between elements was calculated for both systems to compare the results. The output data were modeled using the U-spatial statistics method, and anomaly maps were subsequently generated. Validation and comparison of the results, considering field data obtained from the local and regional exploration, revealed that both models produced similar results in separating anomalous areas and showed a high degree of agreement with field data. However, the U-modeling of the ALR data more closely aligns with field observations and provides a more precise representation of the mineralization trend. Therefore, these new models are recommended for evaluating the spatial distribution of elements and determining the threshold value.

A review of studies has revealed that the concept of traffic literacy in Iran has not been investigated so far, and there is no valid and reliable tool to measure traffic literacy. In addition, there is a relationship between health literacy in one hand, and managing diseases and accidents, the number of traffic injuries and prevention of road traffic injuries in other hand. Also, considering the relationship between health literacy and the management of diseases and accidents, the rate of traffic injuries, and its role in preventing road traffic injuries, and considering the potential impact of health literacy in promoting safer practices for pedestrians and for having a healthier and safer society, it seems necessary to design a tool to measure traffic literacy in the country.

Selection of an embolic agent for middle meningeal artery embolization (MMAE) in a chronic subdural hematoma (cSDH) is a subject of debate and is limited to observational data. We report the first meta-analysis that exclusively assessed randomized controlled trials (RCTs) to address this gap. A systematic review and meta-analysis was conducted, incorporating all available RCTs that compared MMAE plus standard of care (SOC) versus SOC alone for cSDH usingeither Onyx, n-BCA, and Squid as embolic agent for embolization. Primary outcomes were the rate of hematoma recurrence/progression and the need for reoperation. Secondary outcomes included serious adverse events (SAE), all-cause mortality, functional independence (defined as a Modified Rankin Scale (mRS) score of 0-2), and the rate of successful embolization. To assess heterogeneity, a fixed-effect or random-effects model was applied, depending on statistical significance (I²>50%, P < 0.1). Four RCTs, with 894 patients in the MMAE plus SOC group and 914 patients in the SOC alone group, were identified and met our standard for analysis. Results revealed significant superiority of n-BCA compared to Onyx and Squid in lower all-cause mortality at last follow-up. There was no significant difference in using Onyx, Squid, and n-BCA in recurrence at the last follow-up (P = 0.36), reoperation at the last follow-up (P = 0.55), and successful embolization (P = 0.52), and 90-day functional independence (P = 0.076) between trials. Additionally, further analysis on safety outcomes showed no significant difference between embolic agents in SAE at last follow-up (P = 0.78), embolization-related complications (P = 0.087), new onset ischemic stroke (P = 0.98), and deep venous thrombosis (P = 0.94). This meta-analysis of RCTs suggests that while n-BCA is associated with lower all-cause mortality compared to Onyx and Squid in MMAE for cSDH, all three embolic agents demonstrate comparable efficacy and safety.

ABSTRACT Heavy metals (HMs) emitted into the atmosphere from various sources pose numerous health risks, including cancer, respiratory and skin disorders, and neurological effects. This research aimed to conduct comprehensive quantitative and semi-quantitative risk assessments concerning HMs exposure among employees within the Iron and Steel industry. The study included a group of 149 workers exposed to HMs. Air sampling and analysis were conducted according to the NIOSH 7300 method. The semi-quantitative risk assessment followed the delineations provided by the Singapore Health Department, while the quantitative assessment adhered to the methodology outlined by the Office of Environmental Health Hazard Assessment. The study outcomes delineated those levels of exposure to heavy metals across all operational units were lower than the air exposure limits recommended by the ACGIH. According to the semi-quantitative risk assessment, a majority of workers were categorized within the negligible-risk level. Furthermore, mean carcinogenic risk values attributed to Cr surpassed the acceptable threshold of 1 × 10−4. The research findings also indicate the presence of non-carcinogenic risks associated with Mn and Cr exposure among the workforce. Thus, it is imperative to institute strategies aimed at mitigating workers’ exposure to HMs, including the implementation of engineering controls and the establishment of regular monitoring protocols.

IntroductionSarcoidosis is an inflammatory disease that causes functional and physical limitations in patients, negatively impacting their quality of life. Telehealth can provide a solution to improve healthcare services for these patients, regardless of their social and economic status. This research explores the various telehealth technologies and their applications for patients with sarcoidosis.Material and methodsThis scoping review was conducted in 2024 with a comprehensive search in PubMed, Web of Science, Scopus, and ProQuest databases. Following screening and duplicate removal, relevant data were extracted and analyzed.ResultsOut of 821 studies, only 6 studies met the inclusion criteria. The findings showed that mHealth technologies have good acceptance among patients and healthcare providers in managing sarcoidosis symptoms, such as fatigue, stress, and physical activity levels, and improving quality of life. Also, activity tracker technology, alone or in combination with other remote monitoring tools, increases exercise performance, reduces fatigue, and allows for continuous monitoring of the disease status. Hence, it has the potential to be integrated into long-term care programs for patients with sarcoidosis. In addition, telerehabilitation technology could be an acceptable option for patients, but its effectiveness in improving exercise capacity and quality of life in patients with sarcoidosis requires further investigation.ConclusionmHealth and activity tracker technology showed promising results in improving sarcoidosis management and increasing patients’ motivation and adherence to treatment, but further studies are required to assess the effectiveness of telerehabilitation. Overall, telehealth has significant potential to improve the care of sarcoidosis patients, but further research is needed to evaluate the effectiveness of these technologies.

Abstract Aim: Occupational exposure to electromagnetic fields has attracted attention due to potential health effects. This cross-sectional study investigates the impact of static magnetic fields (SMFs) exposure on the sleep quality of workers in a combined cycle power plant. Methods: A total of 185 workers participated in this study. Magnetic flux density was measured using the calibrated HI-3550 magnetic field personal monitor. The Pittsburgh Sleep Quality Index Questionnaire was employed to assess the sleep quality. Data analysis was conducted using the SPSS version 19 software, employing ANOVA, logistic regression, and Chi-square statistical tests. Results: The participants had an average age of 42.16 ± 5.03 years and an average work experience of 15.29 ± 3.38 years. The average magnetic flux density of the SMF, measured at 22.65 ± 2.23 m. The average sleep quality score was 7.25 out of 21. Among the workers, 46.48% reported poor sleep quality, while 53.52% reported good sleep quality. In addition, workers exposed to higher magnetic field levels were more likely to have poor sleep quality compared to those with lower exposure (P &lt; 0.05). The analysis of various factors affecting sleep quality indicated significant associations with marital status, age, and exposure to magnetic fields. Results show with the increase of each unit of age, the chance of having bad sleep quality increased by 0.32 units (95% confidence interval [CI]: 0.11–0.56). Furthermore, with the increase of each unit of magnetic field exposure, the chance of having bad sleep quality increased by 0.16 units (95% CI: 0.09–0.34). Conclusion: The findings suggest that even exposure to magnetic fields below the permissible limits may contribute to poor sleep quality. As magnetic field exposure increases, the likelihood of experiencing poor sleep quality also rises.

This paper presents a novel, efficient, and computationally lightweight approach for voltage and reactive power control in distribution networks with high penetration of distributed generation (DG) using advanced Fuzzy Logic techniques. Unlike traditional methods that rely on complex and time-consuming calculations, the proposed methodology ensures simplicity while maintaining precision and scalability. The core innovation lies in the dynamic modeling of DG's active and reactive power equations, which are adapted to the unique characteristics of electrical distribution networks, including overhead line conductors. This ensures optimal integration of DG without causing voltage violations or instability at the point of interconnection. To validate the accuracy and practical applicability of the proposed approach, extensive simulations were conducted on the IEEE 34-Node Test Feeder using ETAP software. The study evaluates the impact of capacitive compensation structures and DG integration under various load scenarios across three distinct cases, offering a comprehensive analysis of system performance. Results demonstrate significant improvements in voltage stability, reactive power management, and overall system efficiency. Additionally, the proposed framework provides a robust decision-making tool for optimal DG utilization, addressing the emerging challenges of modern power distribution systems in 2025 and beyond. This work sets a new benchmark for sustainable and intelligent voltage control in future smart grids.