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Abstract A High-Fat Diet (HFD) leads to disruption of mitochondrial biogenesis and dynamics. Exercise training, especially High-Intensity Interval Training (HIIT) increases mitochondrial biogenesis and dynamics. The present study aimed to investigate the effect of a period of HIIT with and without HFD consumption on the expression of peroxisome proliferator-activated receptor gamma coactivator 1-alpha (Pgc1-α), Mitofusins-2 (Mfn2), Optic atrophy-1 (Opa1), Dynamin-related protein-1 (Drp1) and mitochondrial Fission protein-1 (Fis1) genes as indicators of mitochondrial biogenesis and dynamics function in the soleus muscle of male Wistar rats. Twenty-four healthy male Wistar rats were randomly divided into four groups: (1) Control, (2) Control + HIIT, (3) HFD, and (4) HFD + HIIT. The HIIT training protocol lasted for 10 weeks with a frequency of 3 sessions per week. The Real-Time Quantitative Reverse Transcription PCR method was used to investigate the gene expression. One-way ANOVA and Fisher’s post-hoc analyses were used to examine group differences. HFD consumption caused an increase in weight (P

Abstract Background Effective epidemic preparedness is critical for minimizing the health and societal impacts of viral respiratory infections. This study details the development of a data-driven early warning system (EWS) designed to improve outbreak detection and response utilizing the data integration and visualization capabilities of Microsoft Power BI. Methods This research utilized a structured three-phase approach to design a respiratory infections (RIs) management dashboard. Phase 1, focused on identifying critical variables through literature reviews and expert interviews. In Phase 2, Microsoft Power BI was employed for dashboard development, integrating data from diverse sources. Phase 3 involved usability testing with health professionals who evaluated navigation, data accuracy, decision-support features, providing feedback to enhance visualization clarity and filtering capabilities. Results Key data categories include individual-level variables, such as age, symptoms, and vaccination records, alongside population-level metrics like infection rates and regional vaccination coverage enabling functionalities such as identifying high-risk individuals, tracking infection dynamics, and optimizing resource allocation. The dashboard, developed using Power BI visualizes epidemiological trends, intervention outcomes, and resource utilization. A relational database schema ensures efficient data retrieval, facilitating comprehensive analysis. Conclusion The prototype EWS represents a scalable and integrative framework aimed at enhancing public health applications, particularly in the context of respiratory infections. By incorporating data from diverse health sectors, the system offers decision-makers access to critical epidemiological indicators, supporting early outbreak detection and improved epidemic management. Its potential to unify health institutions underscores its value in fostering a more cohesive and effective approach to epidemic preparedness. Nevertheless, while the system demonstrates significant promise, further evaluation in real-world settings is essential to determine its practical impact on public health outcomes and its ability to mitigate health crises.

Abstract Nowadays, topological parity-time (PT) and anti- parity-time (APT) symmetry systems have attracted substantial attention due to their noticeable features and specific applications. The emergence of exceptional points in these systems plays a direct role in their overall responses and causes them to exhibit an entirely real spectrum. Here, we propose and analyze a new approach based on the broken PT in the vicinity of a third-order exceptional point and APT symmetry that allows us to experimentally achieve a stable single-mode laser. A feasible third-order exceptional point can be synthesized by coupling three microcavities to each other. The behaviors of these lasers are evaluated in different situations according to introducing the gain and loss perturbation to the system. Our proposed microlasers and their distinct properties based on photonic exceptional points may find use in a wide variety of applications such as ultrahigh precision sensing, spectroscopy, and optical on-chip filters and lasers.

Abstract Intelligent reflecting surfaces (IRS) are valuable tools for enhancing the intelligence of the propagation environment. They have the ability to direct EM Waves to a specific user through beamforming. A significant number of passive elements are integrated into metasurfaces, allowing for their incorporation onto various surfaces such as walls and buildings. In certain situations, metasurfaces may need to be installed on surfaces that are not flat, such as surfaces with curves or surfaces with two sides. Line of sight and non line of sight rays are radiated toward IRS and both components must be considered in channel modeling. In this work, a unit cell with three polarization modes, consisting of absorption, reflection, and a 1-bit phase shift, is designed and investigated. The unit cell in the nonplanar metasurface is composed of two vertical surfaces. A mathematical model is used to analyze two vertically-faced metasurfaces. The results include S parameter values and full structure radiation pattern in simulation and measurement. It is demonstrated that both absorption reflection mode and phase shift mode are achieved within a specific frequency band. The simulations demonstrate that an appropriate absorption level, reaching − 10 dB, is achieved in absorption mode. In reflection mode, a 180-degree phase shift is achieved within the same frequency band. Reports on the radiation pattern of two vertically faced structures indicate that there is no quantized beam when there is a one-bit phase shift. Channel modeling and signal to noise ratio of the designed metasurface in wireless network is represented in comparison with planar metasurface with the same cell number.

Using wind energy for hydrogen production in Iran can be important for reasons such as abundant wind resources in Iran, reducing dependence on fossil fuels, ensuring clean energy supply, the potential for hydrogen exports, technology development and job creation. Therefore, this study signifies the first exploration into the potential for generating electricity and producing hydrogen in ten wind-rich cities in Iran. HOMER V.2.81 software was used for simulations, and the wind data used are averaged over a 25-year period. The results show that in Iran, the price range for wind power is $0.515-$0.620 per kWh in the top 10 stations. Bandar Abbas, Parsabad, and Khalkhal had the best economic and environmental performance, respectively. The highest percentage of renewable electricity production is 71% in Bandar Abbas. Finally, the amount of hydrogen produced based on four common electrolyzer types in Iran was investigated. The total annual hydrogen production per ton for SOE, MCE, AE, and PEME electrolysis method at the examined stations is 131.29, 93.43, 40.99, and 30.69, respectively. According to the results, the highest hydrogen production with a value of 16.87 tons per year is related to the Bandar Abbas station and the SOE electrolysis method. The lowest hydrogen production, with a value of 2.36 tons per year, is related to Alvand station and the PEME electrolysis method.

Abstract Background Worldwide, tuberculosis (TB) is among the most common causes of death. To our knowledge, there has been no study showing the prevalence of EPTB in Khuzestan province. Therefore, the objective of this research was to investigate the prevalence of EPTB in patients with or without pulmonary TB in different cities of Khuzestan province from 2002 to 2023. Additionally, the correlation between patient’s gender, and age groups with the disease was also investigated. Methods In this retrospective study, the existing records in Tuberculosis Regional Reference Laboratory of Khuzestan province related to patients were used. The research was carried out by investigating the archive information in 19 years (from 1st January 2002 to December 30, 2023). All confirmed cases of EPTB and simultaneous EPTB and PTB, based on laboratory results and medical examination were included in the study. Patients with incomplete information and military TB were excluded from the study. Information collected from patients includes age, gender, involved organ, place of residence, and year of disease. Results A total of 12,900 EPTB-related medical records were extracted from Tuberculosis Regional Reference Laboratories in southwest Iran, Ahvaz. After excluding records, 12,836 clinically diagnosed or laboratory-confirmed tuberculosis patients were included in this study, including 5991 patients with simultaneous PTB and EPTB, and 6845 patients with EPTB only. The mean age of male EPTB patients was 37.5 years (SD ± 14.6), while the mean age of male patients with simultaneous PTB and EPTB was 45.8 years (SD ± 15.3). The mean age of female patients with EPTB only, and with simultaneous PTB and EPTB was 31.2 years (SD ± 12.6), and 31.5 years respectively. Discussion tuberculosis is a systemic disease with different clinical manifestations. This study described different epidemiologic patterns of concurrent EPTB. The proportion of different types of EPTB was simultaneously determined for a group of hospitalized patients and shown to be different with gender and age. This study will likely increase clinicians’ awareness of the disease and help them better address diagnostic challenges and improve treatment outcomes for patients with EPTB.

Introduction: Environmental risk assessment in industrial complexes is of significant importance, as the negative impacts of these complexes pose a serious threat to the environment, human life, and international stability. This study aimed to assess the risk of exposure to chemicals and chemical incidents in industrial settings using a hybrid approach based on fuzzy logic. Material and Methods: In this study, a hybrid approach based on fuzzy logic was employed to identify, assess, and prioritize the relevant risks in the Karun oil and gas exploitation industrial zone in Ahvaz city in 1400. This method allows for more accurate and effective risk assessment by considering uncertainties and ambiguities in the data. The study included the assessment of the likelihood of hazard occurrence, the severity of hazard occurrence, the detection probability, hazard effects, risk priority number, and the necessary control measures and proposed actions. Results and Discussion: The results indicated that employees in the evaluated unit are exposed to various chemicals and chemical incidents during their activities. The risk assessment was conducted for 27 types of chemicals and 16 identified chemical incidents. Among the studied substances, exposure and contact with substances butadiene and ethylene oxide are carcinogenic for employees, and mono ethylene glycol with toxic properties causes effects on the heart and kidneys. Butanol can cause respiratory and eye issues due to negligence, leading to fire risks in the facility. The highest risk, with an RPN of 0.715, is associated with gas inhalation from the evaporation of hydrofluoric acid and nitrogen. In contrast, the lowest risks, with RPNs below 0.1, are related to two liquid leakage scenarios at ambient temperature and pressure. The results of the risk assessment calculation show that none of the substances in the company have a very high risk for the employees, but five substances, naphtha, ammonia gas, acetic acid, chlorine gas, and methanol, have a high risk for the employees. The overall risk assessment results for exposure to chemicals and chemical incidents showed that a significant portion of the industry's activities falls within the high-risk range, highlighting the necessity for increased attention and planning to reduce this risk level to prevent serious incidents. Additionally, the results demonstrated that using a systematic fuzzy analysis method provides significant improvements in risk management and can be utilized as an effective tool in this field. Conclusion: Based on the results, risk assessment using a hybrid approach based on fuzzy logic can aid decision-makers in improving environmental performance and creating safer and more sustainable conditions for the industry. By utilizing information related to hazards and the results of measurements and evaluations of chemical factors within the framework of chemical pollutant exposure risk assessment, various jobs can be ranked in terms of exposure to harmful chemical factors. These results can be used to prioritize resource allocation for implementing control measures and reducing exposure risk to an acceptable level.

Background: Considering the importance of using Non-Invasive Ventilation (NIV) in COVID-19-related hypoxemia, the present study was conducted to determine the effective factors on Continuous Positive Airway Pressure (CPAP) failure rate in COVID-19-related hypoxemia. Materials and Methods: This research was a retrospective cross-sectional study (2021) investigating the records of 200 adult patients with the medical diagnosis of acute respiratory failure (ARF) of COVID-19, admitted to the Intensive Care Unit (ICU) in Shoushtar (southwestern Iran) who underwent CPAP therapy. The Heart rate, Acidosis, Consciousness, Oxygenation, and Respiratory rate (HACOR) scores were measured before the treatment and 1 h after undergoing CPAP treatment. Moreover, patients’ demographic and clinical data were recorded. Data were analyzed using the Mann–Whitney, Chi-square, Wilcoxon, and logistic regression tests. The significance level was set at p ≤ 0.05. Results: The mean standard deviation [SD]) age of patients was 63.96 (16.23) years. Among all 200 patients, 78.50% (n = 157) experienced CPAP failure and the remaining 21.50% (n = 43) underwent successful CPAP therapy. Failure chance was 7.10% higher in patients with higher HACOR scores undergoing 1 h CPAP treatment than others. It was also 14.92% higher among patients with diabetes mellitus (DM) than non-DM patients. Additionally, old age (z = 2591.50, p value = 0.02), obesity (z = 2433.00, p value = 0.024), and elevated Blood Urea Nitrogen (BUN) (z = 2620.00, p value = 0.0) impacted CPAP failure rates among patients. Conclusions: The HACOR score 1 h after CPAP, DM, old age, obesity, and elevated BUN favor increased CPAP failure rates among patients.

Abstract Background Familial dietary intake can be influenced by both genetic and environmental factors; the current study aimed to examine the role of these two factors on dietary intake by investigating the resemblance in energy, nutrient, and food group intake among spouses and siblings in twin and family-based studies. Methods The online literature databases, including PubMed, Scopus, Web of Science, and Cochrane Library were systematically searched up to September 2024. The pooled correlation coefficient (r) of studies was calculated using Fisher’s z and standard error (SE) of z’s of all studies and our final results were reported in six groups including non-twin siblings, monozygotic (MZ) twins, dizygotic (DZ) twins, all-twins, all siblings, and spouse. Results Our findings on 30 observational studies indicate that siblings, especially MZ twins, tend to have similar dietary intake, with high correlations for vegetables (r: 0.59), red meat (r: 0.58), and fruits (r: 0.56). Among DZ twins, the lowest correlations were observed for eggs (r: 0.07), soft drinks (r: 0.14), and daily intake of simple carbohydrates (r: 0.17). DZ twins did not show significant differences in dietary resemblance compared to non-twin siblings. Among spouses, the highest correlations for dietary intake were found for polyunsaturated fats (r: 0.41), saturated fats (r: 0.40), and total fats (r: 0.39), while the lowest correlation was for protein intake (r: 0.24). Conclusions While the greatest similarity in dietary intake was observed among MZ twins, no significant difference in dietary intake similarity was noted between DZ twins and non-twin siblings. Furthermore, spouses exhibited a significant degree of similarity in their dietary consumption. Therefore, dietary intake is shaped by a complex interplay of genetic and environmental factors, warranting further investigation to validate these observations.

Providing sustainable energy to achieve favorable economic development has attracted the attention of many governments in recent years. Renewable energies, especially wind energy, have gained considerable media attention recently due to challenges with the use of fossil fuels, including difficulty in accessing and devastating environmental impacts. Extensive efforts have been made in Asia to benefit wind energy regionally, all of which have made Asia a leader in this field. There are a few simulation results in this area, given the importance and need to compile infrastructural strategies and programs that require a thorough understanding of the current state of wind energy usage and determining its potential in different regions. Therefore, this study reports for the first time on surveys conducted on average of 20-year wind speed data collected from 2892 stations in 49 Asian countries and wind speed and power density maps obtained using Geographic Information System (GIS) software and the Boolean method. Besides assessing the problems and issues of energy consumption in countries with high potential wind energy in Asia, in this paper, we try to explore the benefits and requirements of using wind energy in these countries as well as the possibility of maximally using wind energy. According to the results, east and north of Russia, as well as west and southwest Asia are optimal regions for establishing large-scale wind plants; there is no significant potential for the use of wind energy in other regions, especially in the majority of China, ASEAN countries, and their neighboring countries.

Abstract Smart signal processing approaches using Artificial Intelligence are gaining momentum in NMR applications. In this study, we demonstrate that AI offers new opportunities beyond tasks addressed by traditional techniques. We developed and trained artificial neural networks to solve three problems that until now were deemed “impossible”: quadrature detection using only Echo (or Anti-Echo) modulation from the traditional Echo/Anti-Echo scheme; accessing uncertainty of signal intensity at each point in a spectrum processed by any given method; and defining a reference-free score for quantitative access of NMR spectrum quality. Our findings highlight the potential of AI techniques to revolutionize NMR processing and analysis.

Background: Since the coronavirus spread in Iran, almost all healthcare workers (HCWs) have been fighting this disease. Due to the high workload, high prevalence of the virus, lack of specific treatment, and the uncertainty of the end of this epidemic, they experienced difficult working conditions, which resulted in psychological consequences. This systematic review was conducted to investigate the psychological effects of COVID-19 on health care workers (HCWs). Awareness of their psychological status will help to suggest strategies to improve the situation.Methods: In this systematic review, the published articles up to August 2022 were systematically searched in PubMed, Scopus, and Google Scholar databases. The following search strategy was used for searching related papers in all databases: “COVID- 19” OR “SARS-COV-2” AND “Psychological” OR “Stress” OR “depression” AND “Healthcare workers” AND “Iran”.Results: The studies showed that psychological problems increased in Iranian HCWs during the pandemic. The most prevalent issues were anxiety (40%-97.24%), stress (27.8%- 48.97%), and depression (35.1%-38.71%). They also suffered from insomnia, PSTD, and burnout. Factors such as gender, age groups, history of physical illnesses, and history of psychiatric were associated with these problems.Conclusion: HCWs are exposed to psychological and mental issues. Thus, taking measures that protect them in both physical and psychological dimensions is very important. Implications for nursing management: the findings showed HCWs were more vulnerable to adverse psychological effects such as anxiety, stress, and depression. Policymakers and managers should implement supportive, protective, motivational, encouraging, and training interventions to prevent and reduce these consequences.