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Pedestrians account for 26% of all traffic fatalities worldwide. According to in-depth collision databases, around 3500 variables can affect the outcome of a collision, making it crucial to establish the relationship between each variable and the outcome. To date, there is no method defined to assess these variables' relevance other than a statistical correlation, which can sometimes lead to reasonable conclusions, but only under specific circumstances. This article addresses this issue by first conducting a literature review to determine all relevant variables, followed by developing a variable selection criterion to select crucial variables, and then conducting a meta-analysis to quantify these relationships. Epidemiological studies published between 1990 and 2022 were examined, including 93 papers from 19 different nations that considered 904,655 pedestrian collisions. Of the 204 variables that were extracted from these studies, 152 were examined using the variable selection criterion, and 68 were found to be significant. Of these, 20 were included in the meta-analysis, which combined odds ratios to aggregate the effect of a variable across various studies, thus removing study-specific conclusions. This study makes a compelling argument that using statistical correlation by itself is insufficient to determine a variable's significance. The proposed method is an objective way to distinguish the variables for stakeholders and identify their relevance. This study offers a definitive list of the 15 characteristics that must be present in any pedestrian-to-vehicle collision databases, as well as a list of 53 variables that require additional investigation, allowing for appropriate actions for safer roads.

Abstract Background: Nowadays, cytokines such as Leptin and adiponectin are introduced as prognostic factors which, according to some studies, are also associated with body mass index. This study aimed to determine serum leptin level and its relationship with prognostic factors in breast cancer patients. Methods: This case–control study was conducted in the oncology department of Tohid Hospital, Sanandaj, Iran, between 2019 and 2020. Hundred new cases of breast cancer patients with histological evidence were enrolled in this study. Additionally, 100 age- and BMI-matched healthy individuals were recruited as the control group. The serum leptin level was measured using the ELISA method. Results: Serum leptin levels were significantly higher in breast cancer patients compared to the control group (21.68 ± 9.16 vs 11.89 ± 4.45; p < 0.001). There was no significant relationship between plasma leptin levels with ER, PR, and HER2 expressions (p > 0.05). Also, no significant associations were noted between leptin levels and grading and disease staging (p > 0.05). Conclusion: The study found that leptin is higher in breast cancer patients than in healthy individuals, however, it did not prove that leptin is a predictive or prognostic factor.

This paper presents a novel mathematical framework for assessing and predicting the resilience of critical coastal infrastructures against wave overtopping hazards and extreme climatic events. A probabilistic sensitivity analysis model is developed to evaluate the relative influence of hydrodynamic, geomorphological, and structural factors contributing to wave overtopping dynamics. Additionally, a stochastic Gaussian process (GP) model is introduced to predict the mean overtopping discharge from coastal defences. Both the sensitivity analysis and the predictive models are validated using a large homogeneous dataset comprising 163 laboratory and field-scale tests. Statistical evaluations demonstrate the superior performance of the GPs in identifying key parameters driving wave overtopping and predicting mean discharge rates, outperforming existing regression-based formulae. The proposed model offers a robust predictive tool for assessing the performance of critical coastal protection infrastructures under various climate scenarios. [ABSTRACT FROM AUTHOR]

Occupant comfort is a key consideration in automobile dynamics, with vibrations potentially causing long-term physical discomfort, especially for drivers. This study investigates the impact of adding TiO2 and CuO nanoparticles to fuel on engine-induced vibrations. Experiments were conducted at various nanoparticle concentrations (0, 50, 100, and 150 ppm) and engine speeds (1000, 2000, and 3000 rpm). Key performance metrics, including kinematic viscosity, density, heating value, thermal conductivity, and brake power (BP), were analyzed. The results indicated that increasing nanoparticle concentration led to a rise in BP. The highest reduction in root mean square (RMS) vibration accelerations occurred at 3000 rpm and 150 ppm, with vibration reductions of 30.33% for CuO and 28.61% for TiO2. Additionally, 8–10% of engine vibrations were transmitted to the steering wheel. The use of 150 ppm CuO nanoparticles resulted in reduced vibration transmission to the steering wheel at all tested speeds. These findings suggest that nanoparticle-enhanced fuels can significantly reduce engine vibrations, potentially improving driver comfort and reducing wear on vehicle components. [ABSTRACT FROM AUTHOR]

The prediction of protein-protein interactions (PPIs) is essential to understand the cellular processes from a medical perspective. Among the various machine learning techniques, kernel-based Support Vector Machine (SVM) has been commonly employed to discriminate between interacting and non-interacting protein pairs. The main drawback of employing the kernel-based SVM to datasets with many features, such as the primary sequence-based protein-protein dataset, is the significant increase in computational time of training stage. This increase in computational time is mainly due to the presence of the kernel in solving the quadratic optimisation problem (QOP) involved in nonlinear SVM. In order to fix this issue, we propose a novel and efficient computational algorithm by approximating the kernel-based SVM using a low-rank truncated Mercer series as well as desired. As a result, the QOP for the approximated kernel-based SVM will be very tractable in the sense that there is a significant reduction in computational time of training and validating stages. We illustrate the novelty of the proposed method by predicting the PPIs of “S. Cerevisiae” where the protein features extracted using the multiscale local descriptor (MLD), and then we compare the predictive performance of the proposed low-rank approximation with the existing methods. Finally, the new method results in significant reduction in computational time for predicting PPIs with almost as accuracy as kernel-based SVM.

Background: The effects of anesthetics on memory have not yet been completely clear, and there have been some discrepancies on this issue in the literature. This study aimed to compare the effect of two sedatives, Propofol and Midazolam, on the incidence of cognitive dysfunction in elderly patients undergoing spinal anesthesia. Methods: This double-blind clinical trial was conducted on 136 elderly patients‏ who underwent spinal anesthesia in Besat Hospital, Hamadan, Iran, during 2020-21. The patients were randomly assigned into two groups of Propofol (0.2 mg/kg) and Midazolam (0.02 mg/kg). The Wechsler Memory Scale-III (WMS-III) were utilized to assess the cognitive dysfunction and memory coefficient in the two groups. Results: There was no significant difference between the two groups in terms of short and long-term memory, as well as cognitive dysfunction before and after spinal anesthesia (P>0.05). The time of onset of sedation (Z=-11.11; P0.05). The comparison of the two groups in terms of memory coefficient after operation showed no significant differences between them in this regard (Z=-0.63; P=0.52). Conclusion: Midazolam and Propofol showed no differences regarding the effects on the postoperative memory coefficient or cognitive dysfunction.

Abstract Background Sleep disorders, which are among the foremost important medical care issues, are prevalent in pregnancy. The present study is a meta-analysis of the prevalence of insomnia in the third trimester of pregnancy. This study aims to systematically review the overall prevalence of insomnia in the third trimester of pregnancy through conducting a meta-analysis. Method The literature used in this meta-analysis for the topic discussed above were obtained through searching several databases, including SID, MagIran, IranDoc, Scopus, Embase, Web of Science (WoS), PubMed Science Direct and Google Scholar databases without time limitation until December 2020. Articles developed based on cross-sectional studies were included in the study. The heterogeneity of studies was investigated using the I2 index. Also, the possible effects of heterogeneity in the studied studies are investigated using meta-regression analysis. Result In 10 articles and 8798 participants aged between11–40, the overall prevalence of insomnia in the third trimester of pregnancy based on meta-analysis was 42.4% (95% CI: 32.9–52.5%). It was reported that as the sample size increases, the prevalence of insomnia in the third trimester of pregnancy increases. Conversely, as the year of research increases, the prevalence of insomnia in the third trimester of pregnancy decreases. Both of these differences were statistically significant (P

Abstract Background Stress, anxiety, and depression are some of the most important research and practice challenges for psychologists, psychiatrists, and behavioral scientists. Due to the importance of issue and the lack of general statistics on these disorders among the Hospital staff treating the COVID-19 patients, this study aims to systematically review and determine the prevalence of stress, anxiety and depression within front-line healthcare workers caring for COVID-19 patients. Methods In this research work, the systematic review, meta-analysis and meta-regression approaches are used to approximate the prevalence of stress, anxiety and depression within front-line healthcare workers caring for COVID-19 patients. The keywords of prevalence, anxiety, stress, depression, psychopathy, mental illness, mental disorder, doctor, physician, nurse, hospital staff, 2019-nCoV, COVID-19, SARS-CoV-2 and Coronaviruses were used for searching the SID, MagIran, IranMedex, IranDoc, ScienceDirect, Embase, Scopus, PubMed, Web of Science (ISI) and Google Scholar databases. The search process was conducted in December 2019 to June 2020. In order to amalgamate and analyze the reported results within the collected studies, the random effects model is used. The heterogeneity of the studies is assessed using the I 2 index. Lastly, the data analysis is performed within the Comprehensive Meta-Analysis software. Results Of the 29 studies with a total sample size of 22,380, 21 papers have reported the prevalence of depression, 23 have reported the prevalence of anxiety, and 9 studies have reported the prevalence of stress. The prevalence of depression is 24.3% (18% CI 18.2–31.6%), the prevalence of anxiety is 25.8% (95% CI 20.5–31.9%), and the prevalence of stress is 45% (95% CI 24.3–67.5%) among the hospitals’ Hospital staff caring for the COVID-19 patients. According to the results of meta-regression analysis, with increasing the sample size, the prevalence of depression and anxiety decreased, and this was statistically significant (P

Abstract Background Cardiovascular disease is the cause of more than 50% of mortalities globally, and this rate has grown by 8.6% since the 60 s. One of the risk factors associated with cardiovascular disease and its resulting mortality rate is the metabolic syndrome. Different studies have reported inconsistent rates for the metabolic syndrome. However, no comprehensive study has been conducted to combine the results of existing studies. Thus, the present study was performed with the aim of determining the prevalence of metabolic syndrome among cardiovascular patients in Iran through a systematic review and meta-analysis. Method : In this review study, the Scientific Information Database, Google Scholar, Science Direct, Scopus, PubMed, and Web of Science (ISI), databases were searched from January 2005 and until May 2020, to identify and extract related articles. To conduct the analysis, a random effects model was used, and the heterogeneity of the studies was examined using the I2 index. Data analysis was performed within Comprehensive Meta-Analysis (version 2) software. Results The prevalence of metabolic syndrome in cardiovascular patients in Iran in the 27 papers examined with a sample size of 44,735 patients was 34.2% (95% CI: 26.8–42.6%). A sensitivity analysis was performed to ensure the stability of the results, these results show that by omitting the prevalence from each study, the overall prevalence (34.2%) does not change significantly. the highest prevalence of metabolic syndrome in studies conducted in the period between 2015 and 2020, and this was reported as 55.3 (95% CI: 47.9–62.3) and the highest prevalence of metabolic syndrome in studies conducted in the methods of diagnosis IDF, and the rate was reported as 48 (95% CI: 36.5–59.8). based on meta-regression as the year of research increased, the prevalence of metabolic syndrome in cardiovascular patients in Iran also increased. However, with the increase in sample size, this prevalence decreased (p

Abstract Background Physical activity and exercise are among the most important, simplest, and cheapest approaches to anxiety treatment, especially for the elderly. Their positive effects on improvement of mental disorders in the elderly have attracted a considerable level of attention. Therefore, the present study was conducted to determine the effect of sport on reducing anxiety in the elderly using meta-analysis. Methods In this study, national and international databases of SID, MagIran, IranMedex, IranDoc, Cochrane, Embase, ScienceDirect, Scopus, PubMed, and Web of Science were searched to find studies published electronically from 1999 to 2019. Heterogeneity between the collected studies was determined using the Cochran's test (Q) and I2. Due to presence of heterogeneity, the random effects model was used to estimate the standardized mean difference of sport test scores obtained from the measurement of anxiety reduction among the elderly, between the intervention group before and after the test. Results In this meta-analysis and systematic review, 19 papers finally met the inclusion criteria. The overall sample size of all collected studies for the meta-analysis was 841 s. Mean anxiety score before and after intervention were 38.7 ± 5.6 33.7 ± 3.4 respectively, denoting a decrease in anxiety score after intervention. Conclusion Results of this study indicates that Sport significantly reduces Anxiety in the Elderly. Therefore, a regular exercise program can be considered as a part of the elderly care program.

Abstract Background The Dupuytren disease is a benign fibroproliferative disorder that leads to the formation of the collagen knots and fibres in the palmar fascia. The previous studies reveal different levels of Dupuytren’s prevalence worldwide; hence, this study uses meta-analysis to approximate the prevalence of Dupuytren globally. Methods In this study, systematic review and meta-analysis have been conducted on the previous studies focused on the prevalence of the Dupuytren disease. The search keywords were Prevalence, Prevalent, Epidemiology, Dupuytren Contracture, Dupuytren and Incidence. Subsequently, SID, MagIran, ScienceDirect, Embase, Scopus, PubMed and Web of Science databases and Google Scholar search engine were searched without a lower time limit and until June 2020. In order to analyse reliable studies, the stochastic effects model was used and the I 2 index was applied to test the heterogeneity of the selected studies. Data analysis was performed within the Comprehensive Meta-Analysis Software version 2.0. Results By evaluating 85 studies (10 in Asia, 56 in Europe, 2 in Africa and 17 studies in America) with a total sample size of 6628506 individuals, the prevalence of Dupuytren disease in the world is found as 8.2% (95% CI 5.7–11.7%). The highest prevalence rate is reported in Africa with 17.2% (95% CI 13–22.3%). According to the subgroup analysis, in terms of underlying diseases, the highest prevalence was obtained in patients with type 1 diabetes with 34.1% (95% CI 25–44.6%). The results of meta-regression revealed a decreasing trend in the prevalence of Dupuytren disease by increasing the sample size and the research year (P < 0.05). Conclusion The results of this study show that the prevalence of Dupuytren disease is particularly higher in alcoholic patients with diabetes. Therefore, the officials of the World Health Organization should design measures for the prevention and treatment of this disease.

This study presents a novel approach for real-time flood control by optimizing operation of a reservoir during the flood. However, the fundamental operational challenge of using this method is to determine optimized decisions of the reservoir management before the occurrence of flood, and optimal use of the pre-release to reduce the flood damages. In addition to this optimization challenge, since the timely forecasts are derived by employing the probabilistic methods, they would always associate with uncertainty. As a result, quantifying and considering these uncertainties in the flood control would result in reducing the risk of flood damage that can be evaluated by minimizing the expected value of the damage. Timely and continuous forecasting of inflow and reservoir operation management will be implemented before the occurrence of flood until it ends. In order to address the above challenges, a novel simulation-optimization methodology, by taking into account uncertainty, is developed; and illustrated on a case study of Dez reservoir, as a highly important reservoir system in south-west of Iran, to optimize the performance of this reservoir, during the floods. Accordingly, a new water resource management has been proposed and tested. The results derived from the proposed method, indicate a significant reduction in the peak release from the reservoir and the improved operation of the Dez reservoir in controlling the flood at real-time, which will reduce damages in the downstream area.

Abstract Background In all epidemics, healthcare staff are at the centre of risks and damages caused by pathogens. Today, nurses and physicians are faced with unprecedented work pressures in the face of the COVID-19 pandemic, resulting in several psychological disorders such as stress, anxiety and sleep disturbances. The aim of this study is to investigate the prevalence of sleep disturbances in hospital nurses and physicians facing the COVID-19 patients. Method A systematic review and metanalysis was conducted in accordance with the PRISMA criteria. The PubMed, Scopus, Science direct, Web of science, CINHAL, Medline, and Google Scholar databases were searched with no lower time-limt and until 24 June 2020. The heterogeneity of the studies was measured using I2 test and the publication bias was assessed by the Egger’s test at the significance level of 0.05. Results The I2 test was used to evaluate the heterogeneity of the selected studies, based on the results of I2 test, the prevalence of sleep disturbances in nurses and physicians is I2: 97.4% and I2: 97.3% respectively. After following the systematic review processes, 7 cross-sectional studies were selected for meta-analysis. Six studies with the sample size of 3745 nurses were examined in and the prevalence of sleep disturbances was approximated to be 34.8% (95% CI: 24.8-46.4%). The prevalence of sleep disturbances in physicians was also measured in 5 studies with the sample size of 2123 physicians. According to the results, the prevalence of sleep disturbances in physicians caring for the COVID-19 patients was reported to be 41.6% (95% CI: 27.7-57%). Conclusion Healthcare workers, as the front line of the fight against COVID-19, are more vulnerable to the harmful effects of this disease than other groups in society. Increasing workplace stress increases sleep disturbances in the medical staff, especially nurses and physicians. In other words, increased stress due to the exposure to COVID-19 increases the prevalence of sleep disturbances in nurses and physicians. Therefore, it is important for health policymakers to provide solutions and interventions to reduce the workplace stress and pressures on medical staff.

Abstract Background Curcumin is herbal compound that has been shown to have anti-cancer effects in pre-clinical and clinical studies. The anti-cancer effects of curcumin include inhibiting the carcinogenesis, inhibiting angiogenesis, and inhibiting tumour growth. This study aims to determine the Clinical effects of curcumin in different types of cancers using systematic review approach. Methods A systematic review methodology is adopted for undertaking detailed analysis of the effects of curcumin in cancer therapy. The results presented in this paper is an outcome of extracting the findings of the studies selected from the articles published in international databases including SID, MagIran, IranMedex, IranDoc, Google Scholar, ScienceDirect, Scopus, PubMed and Web of Science (ISI). These databases were thoroughly searched, and the relevant publications were selected based on the plausible keywords, in accordance with the study aims, as follows: prevalence, curcumin, clinical features, cancer. Results The results are derived based on several clinical studies on curcumin consumption with chemotherapy drugs, highlighting that curcumin increases the effectiveness of chemotherapy and radiotherapy which results in improving patient’s survival time, and increasing the expression of anti-metastatic proteins along with reducing their side effects. Conclusion The comprehensive systematic review presented in this paper confirms that curcumin reduces the side effects of chemotherapy or radiotherapy, resulting in improving patients’ quality of life. A number of studies reported that, curcumin has increased patient survival time and decreased tumor markers’ level.

Abstract Background RLS is known as one of the most common movement disorders during pregnancy, which is most aggravated in the third trimester of pregnancy and can affect up to one-third of pregnant women. This study intends to determine the total prevalence of RLS in the third trimester of pregnancy through a systematic review. Methods The present study was conducted via meta-analysis method up to 2019. The papers related to the subject of interest were obtained through searching in SID, MagIran, IranDoc, Scopus, Embase, Web of Science (ISI), PubMed, Science Direct, and Google Scholar databases. Heterogeneity of the studies was examined via I2 index, and the data were analyzed in Comprehensive meta-analysis software. Results In investigating 10 papers capturing 2431 subjects within the age range of 25–39 years, the total prevalence of RLS in the third trimester of pregnancy based on meta-analysis was obtained as 22.9% (95% CI: 14.7–33.8%). Further, as the sample size increased, the RLS prevalence diminished, while with increase in years, this prevalence increased, where this difference was statistically significant (P