A New Optimization Algorithm Based on Search and Rescue Operations

[EN] In this paper, a new optimization algorithm called the search and rescue optimization algorithm (SAR) is proposed for solving single-objective continuous optimization problems. SAR is inspired by the explorations carried out by humans during search and rescue operations. The performance of SAR was evaluated on fifty-five optimization functions including a set of classic benchmark functions and a set of modern CEC 2013 benchmark functions from the literature. The obtained results were compared with twelve optimization algorithms including well-known optimization algorithms, recent variants of GA, DE, CMA-ES, and PSO, and recent metaheuristic algorithms. The Wilcoxon signed-rank test was used for some of the comparisons, and the convergence behavior of SAR was investigated. The statistical results indicated SAR is highly competitive with the compared algorithms. Also, in order to evaluate the application of SAR on real-world optimization problems, it was applied to three engineering design problems, and the results revealed that SAR is able to find more accurate solutions with fewer function evaluations in comparison with the other existing algorithms. Thus, the proposed algorithm can be considered an efficient optimization method for real-world optimization problems.This study was partially supported by the Spanish Research Project (nos. TIN2016-80856-R and TIN2015-65515-C4-1-R).Shabani, A.; Asgarian, B.; Gharebaghi, SA.; Salido Gregorio, MA.; Giret Boggino, AS. (2019). A New Optimization Algorithm Based on Search and Rescue Operations. Mathematical Problems in Engineering. 2019:1-23. https://doi.org/10.1155/2019/2482543S1232019Bianchi, L., Dorigo, M., Gambardella, L. M., & Gutjahr, W. J. (2008). A survey on metaheuristics for stochastic combinatorial optimization. Natural Computing, 8(2), 239-287. doi:10.1007/s11047-008-9098-4Holland, J. H. 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COVID-19 coinfection with Mucormycosis

Objectives: We will try to present cases of coinfection with COVID‑19 and mucormycosis in Kashan to increase the awareness of health‑care providers and reduce the number of forgotten and neglected cases.Methods: This is a descriptive cross‑sectional study that patients infected with COVID‑19 become vulnerable to a variety of opportunistic diseases. There are several studies of COVID‑19 and mucormycosis, but an effort has been made to provide a collection of cases in Kashan (the center of Iran) to reduce morbidity and mortality by increasing the awareness of health‑care providers.Results: A total of 31 patients with mucormycosis following COVID‑19 including 18 males and 13 females were included in the study. All reverse transcriptase‑polymerase chain reaction patients were positive for severe acute respiratory syndrome‑coronavirus‑2. Twenty had a history of diabetes, eight had a history of hypertension, and three had no record of any underlying disease. The maxillary sinuses were the most common site of involvement. The maximum length of hospital stay was 52 dayss.Conclusion: Patients with COVID‑19 vulnerable to comorbidities, any facial involvement, or severe glucocorticoid and antibiotic treatment should be closely examined and monitored at the first encounter and during hospitalization for any signs of mucormycosis and start standard care and antifungal treatment as soon as possible

Correlation Between Health Literacy and Self-efficacy of the Elderly

Background Health literacy is the capacity of a person to obtain, process, and understand basic health information for appropriate health decision making. Self-efficacy is the assurance that is felt about a particular activity which maintains and promotes effective health behaviors. Objective The purpose of this study is to evaluate the relationship between health literacy and self-efficacy in the elderly people. Methods This descriptive-correlational study with cross-sectional design was conducted on 144 elderly living in Ramsar city in 2018 who were selected using a random cluster sampling method. Data collection tools were a demographic form, Self Rated Abilities for Health Practices Scale, and Health Literacy for Iranian Adults completed by the researcher after obtaining informed consent from the participants. Data were analyzed in SPSS v.16 software using correlation test, independent t-test, chi-square test, and Fisher’s exact test. Findings Most of participants were female (59%), married (86.8%), housekeeper (52.8%) and high school dropouts (35.4%), and moderate financial status (61.8%) with a mean age of 68.75±2.12 years. Pearson correlation test results showed a significant relationship between health literacy and self-efficacy of the elderly (P=0.0001). Conclusion Considering the role of health literacy in increasing the self-efficacy of the elderly, healthcare system policymakers need to pay attention to the issue of health literacy in health system planning

Search and rescue optimization algorithm: A new optimization method for solving constrained engineering optimization problems

[EN] A new optimization method namely the Search and Rescue optimization algorithm (SAR) is presented here to solve constrained engineering optimization problems. This metaheuristic algorithm imitates the explorations behavior of humans during search and rescue operations. The e-constrained method is utilized as a constraint-handling technique. Besides, a restart strategy is proposed to avoid local infeasible minima in some complex constrained optimization problems. SAR is applied to solve 18 benchmark constraint functions presented in CEC 2010, 13 benchmark constraint functions, and 7 constrained engineering design problems reported in the specialized literature. The performance of SAR is compared with some state-of-the-art optimization algorithms. According to the statistical comparison results, the performance of SAR is better or highly competitive against the compared algorithms on most of the studied problems.Shabani, A.; Asgarian, B.; Salido, MA.; Asil Gharebaghi, S. (2020). Search and rescue optimization algorithm: A new optimization method for solving constrained engineering optimization problems. Expert Systems with Applications. 161:1-15. https://doi.org/10.1016/j.eswa.2020.11369811516

The Tehran longitudinal family-based cardiometabolic cohort study sheds new light on dyslipidemia transmission patterns

Abstract Dyslipidemia, as a metabolic risk factor, with the strongest and most heritable independent cause of cardiovascular diseases worldwide. We investigated the familial transmission patterns of dyslipidemia through a longitudinal family-based cohort, the Tehran Cardiometabolic Genetic Study (TCGS) in Iran. We enrolled 18,729 individuals (45% were males) aged > 18 years (mean: 38.15 (15.82)) and observed them over five 3-year follow-up periods. We evaluated the serum concentrations of total cholesterol, triglyceride, high-density lipoprotein cholesterol, and low-density lipoprotein cholesterol with the first measurement among longitudinal measures and the average measurements (AM) of the five periods. Heritability analysis was conducted using a mixed-effect framework with likelihood-based and Bayesian approaches. The periodic prevalence and heritability of dyslipidemia were estimated to be 65.7 and 42%, respectively. The likelihood of an individual having at least one dyslipidemic parent reveals an OR = 6.94 (CI 5.28–9.30) compared to those who do not have dyslipidemic parents. The most considerable intraclass correlation of family members was for the same-sex siblings, with ICC ~ 25.5%. For serum concentrations, heritability ranged from 33.64 to 60.95%. Taken together, these findings demonstrate that familial transmission of dyslipidemia in the Tehran population is strong, especially within the same-gender siblings. According to previous reports, the heritability of dyslipidemia in this population is considerably higher than the global average