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The genus Latrodectus contains the most medically important spiders around the world. This study describes the first case of Latrodectus cinctus Blackwall, 1865 bite and clinical treatment from Iran. Also, it is the first collection report from the southeast of the country that can enhance prior knowledge on the geographical distribution of this species. We describe a 42-year-old female patient with neurological pain caused by the spider bite. Also, a summary of the entomological survey and morphological identification of the collected species from the patient’s house is presented.

Cornelia de Lange syndrome (CdLS) is a spectrum disorder due to variants in genes of the cohesin protein complex. The following abstracts are from the Cornelia de Lange Syndrome Scientific and Educational Symposium held virtually in October 2020. Aspects of behavior, including autistic features, impulsivity, adaptive skills, executive function, and anxiety are described. Applied behavioral analysis is a promising approach for autism, and an N-acetylcysteine trial is proposed. Children below 6 years with CdLS have an increased number of and further travel to medical providers, with insurance type comprising a significant barrier. Speech, language, and feeding abilities fall significantly below expectations for age in CdLS. Augmentative alternative communication can yield potential barriers as well as interesting benefits. Developmentally, studies in animal models further elucidate the mechanisms and roles of cohesin: link with mediator transcriptional complex; facilitation of enhancer-promoter communication; regulation of gene expression; allocation of cells to germ layers; and repair of spontaneous DNA damage in placental cells. Genome and RNA sequencing can help identify the molecular cause in the 20% of individuals with suspected CdLS and negative testing. The phenotypes in individuals with variants in the SMC1A gene are distinct, and that with intractable seizures has been further evaluated. AMA CME credits provided by GBMC, Baltimore, MD. All studies approved by an ethics committee.

In the present work, we used treated domestic wastewater with different pHs in self-compacting concrete (SCC) to find the effect of treated wastewater with different pH on the workability, mechanical, and durability properties of SCC. Eight different SCC mixtures were designed, including two control samples using tap water with a water-to-cement ratio (W/C) of 0.5 with 400 kg/m 3 of cement and W/C of 0.36 with 440 kg/m 3 of cement. Six SCC samples with the same characteristic as control samples except using treated domestic treated wastewater with different pHs. The results indicate that the workability of the SCC sample using the treated domestic wastewater in acidic pH was higher than the alkalinity state. Using treated domestic wastewater instead of tap water in SCC samples decreased compressive, flexural strength, and fracture toughness by less than10%. Also, carbonation,30-minute water adsorption, and capillary water adsorption of SCC samples increased when treated domestic wastewater was used. The compressive strength of SCC samples made with treated domestic wastewater in an acidic state is less than about 5% in an alkaline state. The energy dispersive spectroscopy and the scanning electron microscope images confirmed that using treated wastewater instead of tap water, in SCC samples, reduced compressive strength because the Ca/Si ratio increased when treated domestic wastewater was used. The SCC samples with treated domestic wastewater in the alkaline state have a lower Ca/Si ratio. The higher compressive strength belongs to concrete samples that used treated domestic wastewater in analkaline environment with a lower Ca/Si ratio.

Background Chitosan is one of dietary fiber that has received great attention in improving obesity-related markers, but little is known on its effects on adolescents. Objectives To analyze the effects of chitosan supplementation on obesity-related cardiometabolic markers and appetite-related hormones in adolescents with overweight or obesity. Methods and analysis A randomized clinical trial was performed on 64 adolescents with overweight and obesity, who were randomly allocated to receive chitosan supplementation (n = 32) or placebo as control (n = 32) for 12 weeks. Anthropometric measures, lipid and glycemic profiles, and appetite-related hormones were examined. Results Sixty-one participants completed study (chitosan = 31, placebo = 30). Chitosan supplementation significantly improved anthropometric indicators of obesity (body weight: − 3.58 ± 2.17 kg, waist circumference: − 5.00 ± 3.11 cm, and body mass index: − 1.61 ± 0.99 kg/m2 and − 0.28 ± 0.19 Z-score), lipid (triglycerides: − 5.67 ± 9.24, total cholesterol: − 14.12 ± 13.34, LDL-C: − 7.18 ± 10.16, and HDL-C: 1.83 ± 4.64 mg/dL) and glycemic markers (insulin: − 5.51 ± 7.52 μIU/mL, fasting blood glucose: − 5.77 ± 6.93 mg/dL, and homeostasis model assessment of insulin resistance: − 0.24 ± 0.44), and appetite-related hormones (adiponectin: 1.69 ± 2.13 ng/dL, leptin − 19.40 ± 16.89, and neuropeptide Y: − 41.96 ± 79.34 ng/dL). When compared with the placebo group, chitosan supplementation had greater improvement in body weight, body mass index (kg/m2 and Z-score), waist circumference, as well as insulin, adiponectin, and leptin levels. Differences were significant according to P-value Conclusion Chitosan supplementation can improve cardiometabolic parameters (anthropometric indicators of obesity and lipid and glycemic markers) and appetite-related hormones (adiponectin, leptin, and NPY) in adolescents with overweight or obesity.

One of the most significant uncertain parameters in microgrid planning is wind speed. Wind speed has a complex dynamic behavior and developing models with high accuracy for this parameter can help decrease microgrid costs and can help improve reliability. Previous methods for wind speed modeling have been mostly statistical methods (e.g., the auto-regressive integrated moving average (ARIMA), the multivariate distribution functions, Copula function). Afore-mentioned methods are suitable for modeling stationary data. However, since the wind speed data are not stationary, the measure correlate predict (MCP) method, capable of modeling the non-stationary data, is used in this paper to generate the wind speed scenarios. Based on radial basis function (RBF) artificial neural network, this work has proposed a novel hybrid computational model to improve MCP method’s performance. The results indicate that the Hybrid-MCP method is more accurate than the conventional statistical methods, which are used to generate the wind speed scenarios (24 h).

Background The distribution of population-level real-time reverse transcription-polymerase chain reaction (RT-PCR) cycle threshold (Ct) values as a proxy of viral load may be a useful indicator for predicting COVID-19 dynamics. Objective The aim of this study was to determine the relationship between the daily trend of average Ct values and COVID-19 dynamics, calculated as the daily number of hospitalized patients with COVID-19, daily number of new positive tests, daily number of COVID-19 deaths, and number of hospitalized patients with COVID-19 by age. We further sought to determine the lag between these data series. Methods The samples included in this study were collected from March 21, 2021, to December 1, 2021. Daily Ct values of all patients who were referred to the Molecular Diagnostic Laboratory of Iran University of Medical Sciences in Tehran, Iran, for RT-PCR tests were recorded. The daily number of positive tests and the number of hospitalized patients by age group were extracted from the COVID-19 patient information registration system in Tehran province, Iran. An autoregressive integrated moving average (ARIMA) model was constructed for the time series of variables. Cross-correlation analysis was then performed to determine the best lag and correlations between the average daily Ct value and other COVID-19 dynamics–related variables. Finally, the best-selected lag of Ct identified through cross-correlation was incorporated as a covariate into the autoregressive integrated moving average with exogenous variables (ARIMAX) model to calculate the coefficients. Results Daily average Ct values showed a significant negative correlation (23-day time delay) with the daily number of newly hospitalized patients (P=.02), 30-day time delay with the daily number of new positive tests (P=.02), and daily number of COVID-19 deaths (P=.02). The daily average Ct value with a 30-day delay could impact the daily number of positive tests for COVID-19 (β=–16.87, P Conclusions It is important for surveillance of COVID-19 to find a good indicator that can predict epidemic surges in the community. Our results suggest that the average daily Ct value with a 30-day delay can predict increases in the number of positive confirmed COVID-19 cases, which may be a useful indicator for the health system.

Despite global efforts, HIV/AIDS is still one of the major public health problems in the entire world. In this context, assessing the burden of this disease in different parts of the world is of great importance. In this study, we aimed to investigate the trends of HIV/AIDS incidence and mortality in Iran in the period 1990- 2017.The HIV/AIDS burden data including age-standardized incidence rate (ASIR) and mortality rate (ASMR) was extracted from the Global Burden of Diseases 2017 study for total Iranian population and by gender from 1990 to 2017. The trend analyses was performed using joinpoint regression modeling approach. The obtained results showed that in year 2017 the HIV/AIDS ASIR and ASMR were, respectively, more than 12 and 10 times of these rates in year 1990. Also, the estimated average annual percent change (AAPC) was 9.8% and 8.7%, respectively for ASIR and ASMR. In this period of time, women have experienced sharper slope of ASIR and ASMR trends compared to Iranian men. The increasing trend of HIV/AIDS burden is a serious alarm for the Iranian health policy makers. To achieve the UNAIDS goals, there is an urgent need for an efficient national action plan which breaks the HIV/AIDS taboo in the society, promote access to HIV testing and prevention facilities especially among the key populations and provides care and treatments for all infected people.

Background: Life expectancy is one the key indicators for investigating the overall health status of a population. Thus, analyzing the trend of this demographic summary measure is of great importance for planning health and social services in different societies. In this study, we aimed to model the long-term trend of life expectancy at birth in Iran and also compare the pattern of life expectancy in Iran with the whole population across Asia over the past six decades.Methods: The annual life expectancy at birth data sets were extracted for Iran and total Asia between 1960 and 2020 from the database provided by the Our World in Data website. The trend analysis was performed using the joinpoint regression model. Results: During the study period, Iranians and Asians have, respectively, experienced about 32 and 28.6 year increase in life expectancy. In addition, the obtained results from the joinpoint analysis showed that, despite the noticeable decline in life expectancy during the Iran-Iraq war, the average annual percent change of life expectancy in Iranian people was about 0.1 higher than total Asian population (0.9% vs. 0.8%).Conclusions: Despite protracted wars, poverty and social inequality in some parts of Asia, life expectancy has drastically increased in this continent during the last decades. However, life expectancy in Iranians and Asians is still much lower than those who live in wealthier parts of the world. To elevate life expectancy to a higher level, the policy makers in Asian countries should put more efforts into improving the standards of living and access to health facilities in their societies.

Background Cardiovascular diseases (CVDs) are the number one cause of global mortality representing about one third of all deaths across the world. The objective of the present study was to model the global trend in disability-adjusted life years (DALY) and its components due to CVD over the past three decades. We also aimed to evaluate the longitudinal relationship between CVD DALY and Human Development Index (HDI) in this period of time. Methods The age-standardized rates of years lost due to disability (YLD), years of life lost (YLL) and DALY were extracted for cardiovascular diseases from the Global Burden of Disease (GBD) Study 2019 in years 1990 to 2019. Additionally, the United Nations Development Programme (UNDP) database was used to retrieve HDI values for all world countries at the same period time. The trend analysis was performed using the joinpoint regression model. Results The obtained revealed a significant downward trend for DALY and its components with the average annual percent change of − 1.0, − 0.3 and − 1.1 per 100,000 population, respectively for DALY, YLD and YLL. We also found that countries with high/very high levels of HDI have remarkably experienced steeper declining slope of trend than those in lower levels of HDI over the study period. Conclusions Although the observed decreasing trend of CVD burden is a hopeful message for all world countries, the considerable gap in slope of trend between richer and poorer parts of the world is a serious alarm for health policy makers. Regarding this, there is an urgent need to put more efforts on implementing preventive programs, improving the level of patients’ care and providing efficient treatment, especially in regions with lower levels of HDI.

PurposeAlthough the business model field of study has been a focus of attention for both researchers and practitioners within the past two decades, it still suffers from concern about its identity. Accordingly, this paper aims to clarify the intellectual structure of business model through identifying the research clusters and their sub-clusters, the prominent relations and the dominant research trends.Design/methodology/approachThis paper uses some common text mining methods including co-word analysis, burst analysis, timeline analysis and topic modeling to analyze and mine the title, abstract and keywords of 14,081 research documents related to the domain of business model.FindingsThe results revealed that the business model field of study consists of three main research areas including electronic business model, business model innovation and sustainable business model, each of which has some sub-areas and has been more evident in some particular industries. Additionally, from the time perspective, research issues in the domain of sustainable development are considered as the hot and emerging topics in this field. In addition, the results confirmed that information technology has been one of the most important drivers, influencing the appearance of different study topics in the various periods.Originality/valueThe contribution of this study is to quantitatively uncover the dominant knowledge structure and prominent research trends in the business model field of study, considering a broad range of scholarly publications and using some promising and reliable text mining techniques.

In this paper, we propose regularized block diagonalization (RBD) precoding using artificial noise (AN) for physical layer security in downlink multi-user MIMO wireless networks. We derive secrecy sum rate and asymptotic secrecy sum rate for the proposed scheme. The optimum power allocation for legitimate users and the AN signal are derived in closed form for optimal asymptotic secrecy sum rate. Our analysis shows that to achieve best performance, it is more efficient to degrade the performance of the eavesdropper than improving legitimate users’ rates. We also study the impact of error in channel estimation on the system and derive closed-form SINR and secrecy sum-rate expressions for this case. Simulations show that the secrecy sum rate of RBD precoding outperforms the secrecy sum rate of regularized channel inversion by 0.5 bits/s/Hz. We also show that in the presence of channel estimation error, our approximate closed forms for secrecy sum rate are very closed to the actual secrecy sum rate over a wide range of SNR and channel estimation error values.

We derive the asymptotic ergodic secrecy sum rate (ESSR) of block diagonalization precoding for physical-layer security in downlink multi-user wireless networks that use artificial noise. First, we derive the ESSR of the system. Then, we derive the power allocation and the asymptotic ESSR as the number of antennas increases. After, we derive an approximate expression for the optimum ratio of the number of transmit antennas to the number of receive antennas ( $\Psi $ ). We then introduce the user dropping factor (UDF) as a means to derive the optimum number of users in the system under different scenarios and then derive the asymptotic optimum UDF, which gives the optimum number of scheduled users. We also study the effect of imperfect channel state information and derive a closed-form ESSR. Simulation results show that these precoders outperform channel inversion (CI) and regularized CI schemes in terms of the ESSR at all SNRs. We also show that as the number of receive antennas of each user increases, the asymptotic ESSR gap also increases.

Background Cardiovascular diseases (CVDs) are one of the global leading causes of concern due to the rising prevalence and consequence of mortality and disability with a heavy economic burden. The objective of the current study was to analyze the trend in CVD incidence, mortality, and mortality-to-incidence ratio (MIR) across the world over 28 years. Methods The age-standardized CVD mortality and incidence rates were retrieved from the Global Burden of Disease (GBD) Study 2017 for both genders and different world super regions with available data every year during the period 1990–2017. Additionally, the Human Development Index was sourced from the United Nations Development Programme (UNDP) database for all countries at the same time interval. The marginal modeling approach was implemented to evaluate the mean trend of CVD incidence, mortality, and MIR for 195 countries and separately for developing and developed countries and also clarify the relationship between the indices and Human Development Index (HDI) from 1990 to 2017. Results The obtained estimates identified that the global mean trend of CVD incidence had an ascending trend until 1996 followed by a descending trend after this year. Nearly all of the countries experienced a significant declining mortality trend from 1990 to 2017. Likewise, the global mean MIR rate had a significant trivial decrement trend with a gentle slope of 0.004 over the time interval. As such, the reduction in incidence and mortality rates for developed countries was significantly faster than developing counterparts in the period 1990–2017 (p Conclusions Generally, the findings of this study revealed that there was an overall downward trend in CVD incidence and mortality rates, while the survival rate of CVD patients was rather stable. These results send a satisfactory message that global effort for controlling the CVD burden was quite successful. Nonetheless, there is an urgent need for more efforts to improve the survival rate of patients and lower the burden of this disease in some areas with an increasing trend of either incidence or mortality.

Background: Musculoskeletal disorder (MSD) is one of the important problems concerning the staffs' health and productivity in the workplace. Nutritional status and consumption of some foods are also among the determining factors of MSD. So, this study aimed to evaluate the correlation of diet and consumed food groups with MSD. Methods: This cross-sectional study was conducted on 100 office workers. The participants' anthropometric parameters and their dietary information were collected using a semi-quantitative food frequency questionnaire. The findings were categorized into nine levels. The total scores were calculated for all the items per food group and per person. Nordic musculoskeletal questionnaire was also administered to evaluate the MSD symptoms in nine parts of body. Results: The score of consumed food groups was compared between individuals “with pain” and “without pain” in nine parts of the body. The scores of fruit intake in individuals “with pain” and “without pain” were 2.94 ± 1.27 vs. 3.29 ± 1.16 and 2.81 ± 1.10 vs. 3.49 ± 1.38 in terms of neck and wrists, respectively. The difference between the two groups were significant (P < 0.05). Furthermore, the participants with pain in the neck consumed significantly lower amounts of cereals and nuts (P = 0.03, 0.04). In the case of the shoulder pain, consuming legumes and nuts in the “without pain” group was higher than the group of participants who had pain (P = 0.01, P = 0.03). Fat intake was higher in the patients who had pain in their hips (P = 0.02). Conclusion: Less pain was reported in the musculoskeletal system by higher consumption of fruits, nuts, and legumes. It seems that plant-based dietary pattern is more effective in musculoskeletal health.

Background: Tuberculosis (TB) is still a serious health problem with a remarkable global burden. In this study, we aimed to assess the trend of TB mortality in Asian and North African countries in the period 1990-2017 and provide a new classification according to TB mortality trend. Methods: TB mortality rates from 1990 to 2017 were extracted from the Global Burden of Disease website for 55 Asian and North African countries. Trend analysis of TB mortality rates for males, females, and the total population was performed using the marginal modeling approach. Moreover, the latent growth mixture modeling (LGMM) framework was applied to classify these 55 countries based on their trend of TB mortality rate. Results: In the period between 1990 and 2017, South Asia and High Income Asia-Pacific regions had the highest and lowest death rates due to TB, respectively. The marginal modeling results showed that the Asian and North African countries had experienced a downward trend with an intercept of 28.79 (95%CI: 19.64, 37.94) and a slope (mean annual reduction) of -0.67 (95%CI: -0.91, -0.43) per 100,000 the study period. Finally, the LGMM analysis classified these 55 countries into four distinct classes. Conclusion: In general, our findings revealed that although the countries in Asia and North Africa super region experienced a descending TB mortality trend in the past decades, the slope of this reduction is quite small. Also, our new classification may be better suited for combating TB through future healthcare planning in lieu of the commonly used geographic classifications.

Background: Female breast cancer is known as one of the top five cancers in terms of mortality. Regarding contradictory reports about the mortality trend of this cancer and its association with the socio-economic status of the world countries, we aimed at assessing the global trend of female breast cancer mortality rate and investigate the relationship between its mortality rate and development status. Methods: The breast cancer Age Standardized Mortality Rate (ASMR) per 100,000 and Human Development Index (HDI) for 179 world countries were extracted, respectively from the Global Burden of Disease (GBD) 2017 study and the United Nations Development Programme (UNDP) database, for the period 1990 to 2017. The marginal modeling methodology was employed to analyze the global trend of ASMR and examine the relationship between ASMR and HDI. Results: The results showed a slightly constant curve for the global trend of breast cancer ASMR from 1990 to 2017 (around 17 per 100,000). Moreover, it was indicated that the ASMR is strongly related to development status. While countries with higher levels of HDI have experienced a declining trend of breast cancer mortality rate, countries with lower HDI levels experienced an ascending trend at this period. Conclusions: In general, the findings showed that mortality due to breast cancer is still a major health problem in total world countries. Hence, more efforts should be made to screen the patients in the early stages of the disease and promote the level of care, especially in countries with lower levels of economic development.

Background Curcumin is a biologically active phytochemical ingredient found in turmeric. It has several pharmacologic effects that might benefit patients with polycystic ovary syndrome (PCOS). Objective We hypothesized curcumin to be effective in improving blood sugar levels, insulin resistance and hyperandrogenism in individuals with PCOS. Methods In a randomized double-blind placebo-controlled trial, individuals with PCOS were treated with curcumin (500 mg three times daily) or placebo for 12 weeks. Primary outcome measures were fasting plasma glucose (FPG), fasting insulin (FI), sex hormone levels, and hirsutism (Ferriman-Gallwey [mFG] score). Secondary outcomes included anthropometric measurements. Results Of 72 randomized individuals, 67 completed the trial. The two groups were comparable at baseline. At the end of the study, FPG and Dehydroepiandrosterone levels had decreased significantly in the intervention group compared to control (difference of change (post-pre) between intervention and placebo groups: -4.11 mg/dL; 95% CI: -8.35, -0.35 mg/dL; p = 0.033 and -26.53 microg/dL; 95% CI: -47.99, -4.34 µg/dL; p = 0.035, respectively). We also observed a statistically non-significant increase (p = 0.082) in Estradiol levels in the intervention group compared to control. No serious adverse events were reported throughout the trial. Conclusions Curcumin might be a safe and useful supplement to ameliorate PCOS-associated hyperandrogenemia and hyperglycemia. However, longer trials investigating different dosages in longer durations are needed to underpin these findings.

We study the secrecy sum-rate (SSR) of a multi-user system in the presence of artificial noise (AN) and determine conditions under which it is necessary to add AN assuming eavesdropper (Eve) cannot remove the interference. We first derive a closed-form expression for the asymptotic SSR of the system and determine the optimum power allocation. The closed form expressions for the SSR and optimum power allocation closely match our simulation results. We also show that as the number of receive antennas at Eve increases, we need to allocate more power to AN in order to degrade reception at Eve.

The monitoring of severely ill patients is a crucial procedure for every intensive care unit (ICU). By applying different data exploration methods on monitoring data, some perspective can be gained. In the present research, such monitoring data were explored in the electronic ICU (eICU) Collaborative Research Database—an ICU database collected from more than 200 hospitals and over 139,000 ICU patients across the United States. The eICU database, with its enormous quantity of remote monitoring data, could be a great resource for extracting insightful information that can help to identify potential areas of improvement in the quality of patient treatment. Important information such as patients’ vital signs, care plan documentation, stage of illness, diagnosis, and treatment is available in the database. In the present study, we explore the distribution of the data, including demographics, conditions, and diseases, and identify important patterns and relationships between features of the data. Through an exploratory analysis of the data, including the relationships between gender, ethnicity, diseases, and quality of care and mortality rates, remarkable insights were obtained. To the best of our knowledge, this is the first comprehensive exploratory analysis of the eICU database. A deep understanding of the ICU data provides the foundation for further predictive and prescriptive analyses of the data with the ultimate goal of improving ICU treatment procedures for future patients.

Background: Many people facing life difficulties are unable to sort out these problems. Objectives: A study was designed to determine students’ life skills at the Iran University of Medical Sciences (IUMS). Methods: This cross-sectional study was conducted at IUMS in 2016 - 17 with a sample of 342 students. A questionnaire was used with multi-choice questions from poor to high skills. Latent class models were applied for data analysis using Mplus. Bayesian information criterion (BIC) and Bootstrap likelihood ratio tests were used to determine the number of classes. Results: A two-class model had the best fit since the BIC had the lowest amount. Almost 76% and 24% of the cases entered the high and moderate skill classes of the model, respectively. The level of education (LOE) was the only significant variable (P = 0.004) for classifying the students. Conclusions: The model could predict the probability of high life skilled students. Also, LOE had a high impact on the probability of high life skills.

Background: Pregnancy outcomes are affected by many different factors. One of the influential factors on pregnancy outcomes is the male partner as an important person to mother’s wellbeing....

Background The recent progress and achievements in the advanced, accurate, and rigorously evaluated algorithms has revolutionized different aspects of the predictive microbiology including bacterial growth. Objectives In this study, attempts were made to develop a more accurate hybrid algorithm for predicting the bacterial growth curve which can also be applicable in predictive microbiology studies. Materials and methods Sigmoid functions, including Logistic and Gompertz, as well as least square support vector machine (LSSVM) based algorithms were employed to model the bacterial growth of the two important strains comprising Listeria monocytogenes and Escherichia coli. Even though cross-validation is generally used for tuning the parameters in LSSVM, in this study, parameters tuning (i.e.,'c' and 'σ') of the LSSVM were optimized using non-dominated sorting genetic algorithm-II (NSGA-II), named as NSGA-II-LSSVM. Then, the results of each approach were compared with the mean absolute error (MAE) as well as the mean absolute percentage error (MAPE). Results Applying LSSVM, it was resulted in a precise bacterial growth modeling compared to the sigmoid functions. Moreover, our results have indicated that NSGA-II-LSSVM was more accurate in terms of prediction than LSSVM method. Conclusion Application of the NSGA-II-LSSVM hybrid algorithm to predict precise values of 'c' and 'σ' parameters in the bacterial growth modeling resulted in a better growth prediction. In fact, the power of NSGA-II for estimating optimal coefficients led to a better disclosure of the predictive potential of the LSSVM.

Scenario generation is of great significance to scenario-based stochastic programming. The higher the accuracy of the scenarios, the closer the solutions of the problem are to real optimal values. One uncertain variable which is significant in planning microgrids and wind farms is wind speed. Complex dynamic behavior, being non-stationary, and the different type of tail dependence of wind speed data complicate its modeling. Tail dependence is an important feature in modeling accuracy and conventional wind speed scenario generation methods such as autoregressive integrated moving average (ARIMA) and multivariate distribution functions are not capable of modeling tail dependence. The current study uses copula functions with the ability to model tail dependence for the generation of wind speed scenarios. First, the structure of the dependence of wind speed data has been investigated using correlation matrix and tail dependence coefficients. Then, according to the dependence structure of the data, the appropriate copula function has been selected. The results show that the scenarios made by the student-T copula function are more accurate than conventional methods such as ARIMA and the normal multivariate distribution function.

The accurate modeling of uncertainties is one important issue in planning of microgrids. The more accurate modeling of the uncertainties results in answers of the stochastic optimization methods which are close to the actual optimal values. This paper utilized a scenario-based stochastic optimization method, considering photovoltaic (PV) and wind turbine power output and load as the uncertain variables in determining the capacity of distributed generation resources in an autonomous microgrid. Costs were considered as the objective function while the grid reliability was the constraint. To generate the scenarios of variables with uncertainty in microgrid, the dynamics of variables was first characterized by the Recurrence Plot nonlinear analysis, followed by the study of their seasonal behaviors. Based on this analysis, a method for classifying data was presented according to their seasonal behavior and the appropriate method to generate the scenarios for each of the uncertain variables was determined. The results showed that generating the scenarios based on the analysis of the uncertain variables results to an increase in the optimization accuracy.

Temporal distribution of earthquakes with M w > 6 in the Dasht-e-Bayaz region, eastern Iran has been investigated using time-dependent models. Based on these types of models, it is assumed that the times between consecutive large earthquakes follow a certain statistical distribution. For this purpose, four time-dependent inter-event distributions including the Weibull, Gamma, Lognormal, and the Brownian Passage Time (BPT) are used in this study and the associated parameters are estimated using the method of maximum likelihood estimation. The suitable distribution is selected based on logarithm likelihood function and Bayesian Information Criterion. The probability of the occurrence of the next large earthquake during a specified interval of time was calculated for each model. Then, the concept of conditional probability has been applied to forecast the next major (M w > 6) earthquake in the site of our interest. The emphasis is on statistical methods which attempt to quantify the probability of an earthquake occurring within a specified time, space, and magnitude windows. According to obtained results, the probability of occurrence of an earthquake with M w > 6 in the near future is significantly high.

Background We aimed to establish the prevalence of parental consanguinity among patients with primary immunodeficiency diseases (PID) and compare the prevalence with the general population. Method We searched PubMed, EMBASE, and Scopus for studies mentioning parental consanguinity prevalence in patients with PID and calculated the prevalence odds ratio (POR) of parental consanguinity in each study, compared to a matched healthy population. Results We identified 21 eligible studies with a total population of 18091 accounting for sample overlap. The POR among studies on a sample of mixed patients with PID ranged from 0.6 to 21.9 with the pooled POR of 3.0 (p < 0.001; I2 = 89%, 95% CI: 2.5–3.7). Conclusion PIDs with an autosomal recessive pattern of inheritance had significant odds of parental consanguinity compared to the healthy population, a phenomenon not observed in other inheritance patterns. Determining the extent of the impact that consanguinity imposes upon the progeny paves the way for convincing healthcare policymakers in highly consanguineous communities to act more diligently in informing the masses about the consequences of practicing inbreeding.

Landslide forecasting can lead to prevent great human injuries and financial losses in the world. For this purpose, monitoring of slope displacement is necessary. In this paper, a sensor network that monitors the actual displacement of soil layers to predict landslides is described. The proposed landslide monitoring system determines the movement of soil layers by using the changes in the sensor network The processor of the system is a trained computational model. At first, by using a calibration device, the data of the sensor network are collected and then the obtained data have been used to train the computational model. According to the dependence analysis results, an artificial neural network have been selected to computational model. Finally the results show that the landslide monitoring system can measure the displacement of soil layers accurately.

Objective: National surveys revealed a high prevalence of psychiatric disorders in Iran. Province-level estimates are needed to manage the resources and focus on preventive efforts more efficiently. The objective of this study was to provide province-level estimates of psychiatric disorders. Method: In this study, Iranian Mental Health Survey (IranMHS) data (n = 7886) was used to produce province-level prevalence estimates of any psychiatric disorders among 15-64 year old males and females. Psychiatric disorders were diagnosed based on structured diagnostic interview of the Persian version of Composite International Diagnostic Interview (CIDI, version, 2.1). The Hierarchical Bayesian (HB) random effect model was used to calculate the estimates. The mental health status of half of the participants was also measured using a 28-item general health questionnaire (GHQ). Results: A wide variation in the prevalence of psychiatric disorders was found among 31 provinces of Iran. The direct estimates ranged from 3.6% to 62.6%, while the HB estimates ranged from 12.6% to 36.5%. The provincial prevalence among men ranged from 11.9% to 34.5%, while it ranged from 18.4% to 38.8% among women. The Pearson correlation coefficient between HB estimates and GHQ scores was 0.73. Conclusion: The Bayesian small area estimation provides estimation with improved precision at local levels. Detecting high-priority communities with small-area approach could lead to a better distribution of limited facilities and more effective mental health interventions.

Wireless communications systems are highly vulnerable to jamming. There is a large body of research demonstrating the potential of smart-jamming that targets specific mechanisms in a wireless stack. Many proactive mitigation techniques sacrifice performance for guaranteed robustness. In this work, we develop a proactive mitigation approach for multi-carrier wireless links. The approach is formulated within the framework of game theory. We show that the interaction between a multi-carrier multi-rate system (in particular OFDM) and a power-limited jammer can be formulated as a constrained zero-sum or a bimatrix game. We show that the Nash equilibrium strategies can be derived analytically and numerically and we apply them to the special case of IEEE 802.11 OFDM links.

BACKGROUND: Financial management system acts as a driving force and the first important principle of health sector reform. This study aimed to prepare a framework for new financial management system in Iran health sector. MATERIALS AND METHODS: This qualitative study was conducted by content analysis approach and 15 key informant participants selected through purposive sampling consisted of three minsters of Ministry of Health and Medical Education (MOHME), three vice-chancellors in the Center of Resource Development and Management, Two members of the Health Assembly of the Islamic Consultative, four Medical Sciences university's presidents, and three managers in Budgeting and performance Monitoring Center of MOHME in 2017. Data were collected through semi-structured interviews and they were analyzed using Atlas T6 software. RESULTS: Six main themes were emerged as follow: “legal reform,” “removing barriers to set up accrual accounting,” “cost price calculation,” “operational planning and budgeting,” “human resources' organization, recruitment, and moderation,” and “financial system output utilization (management accounting techniques) as the base for evidence-based policymaking and decision-making practices.” CONCLUSION: Any efforts for improving the current situation and reducing of mentioned limitations could be useful in providing required space for future phases of reforms and calculation of unit cost, operational budgeting, and management of cost and productivity. This can be achieved through an integrated system of recording and producing standard and accrual financial information. Furthermore, changing the accounting process and the financial system that complies with one single encoding in the country is a key issue.

The area southeast of Iran still copes with malaria as an unstable infectious disease and includes the most autochthonous malaria reports in the country. This comprehensive study was carried out for the evaluation of environmental factors, welfare indicators and health facilities on the malaria situation before and at the beginning of a pre-elimination programme in this area. The probable factors affecting the malaria situation, including the water-pipe network, electricity, rainfall, long-lasting integrated nets (LLINs), indoor residual spraying and malaria diagnosis-treatment centres were analysed using SPSS software. The Pearson correlation test showed no significant correlation between some factors such as piped water networks, annual precipitation, number of sprayed villages and autochthonous cases as well as autochthonous foci. But a significant correlation between electricity coverage, number of diagnoses of malaria-treatment centres and autochthonous cases\foci was observed. Also, the number of distributed LLINs didn't have any correlation with the number of total malaria cases, but a significant correlation between LLINs and autochthonous foci was seen. Detailed studies on the correlation of various variables, such as piped water, spraying coverage and number of malaria diagnosis centres, with the malaria situation is limited in Asia and other parts of the world. This study and others like it can help malaria managers and directors in the more accurate allocation of financial resources.

We develop a linearly constrained bimatrix game framework that can be used to model many practical problems in many disciplines, including jamming in packetized wireless networks. In contrast to the widely used zero-sum framework, in bimatrix games it is no longer required that the sum of the players’ utilities be zero or constant, thus, ir can be used to model a much larger class of jamming problems. Additionally, in contrast to the standard bimatrix games, in linearly constrained bimatrix games, the players’ strategies must satisfy some linear constraint/inequality, consequently, not all strategies are feasible and the existence of the Nash equilibrium (NE) is not guaranteed anymore. We provide the necessary and sufficient conditions under which the existence of the Nash equilibrium is guaranteed, and show that under linear constraints, the equilibrium pairs and the Nash equilibrium solution of the constrained game corresponds to the global maximum of a quadratic program. Finally, we use our game theoretic framework to find the optimal transmission and jamming strategies for a typical wireless link under power limited jamming.

Background Folate deficiency is shown to be associated with schizophrenia. Folate profile in patients with psychosis due to stimulant use has not been investigated. We aim to determine whether there is an association between serum folate level and the presence of psychosis in patients with methamphetamine (METH) use disorder. Methods Forty patients diagnosed with METH-use disorder were included in this cross-sectional study. Serum folate levels were measured using enzyme immunoassay technique and compared between psychotic and non-psychotic subgroups (N = 25 and 15, respectively). We designed a logistic regression model to measure the extent of any association and also to adjust for potential confounders. Results We detected lower serum folate level in the psychotics [3.4 (IQR = 5.3)] compared to non-psychotic METH users [8.9 (IQR = 2.5)], p = 0.01. The model demonstrated that every 1-unit increase in serum folate decreases the odds of presence of psychosis by 27% (R2 = 53.5%, CI 12–64%, p = 0.006). The observed difference was not associated with the duration of METH use, patient’s age at first METH use, or concurrent use of other substances. Conclusions Our findings suggest that low folate level in psychotic METH users does not correlate with previously established risk factors for meth-induced psychosis such as duration of use, age of onset of using, and poly-drug use. We assume that low folate levels may play a crucial role in the pathophysiology of psychosis.

Road Traffic Accidents (RTA) are a major worldwide public health problem. The aim of this study was to use the growth mixture model for clustering countries on the basis of the mortality rate patterns of RTAs from 2007 to 2013. We obtained the data on RTA death rates from World Health Organization reports and Human Development Index (HDI) of United Nations Development Programme reports for the years 2007, 2010 and 2013. Simple Latent Growth Models (LGM) in 181 countries were applied to estimate overall RTA mortality rate growth trajectories and the latent growth mixture modeling utilized to cluster them. According to non-linear LGM, the overall mortality rate of RTAs showed a decrease from 2007 to 2010 followed by an increase from 2010 to 2013. The HDI covariate had a significant negative and positive effect on intercept and slope of the LGM, respectively. The extracted mixture model appeared to have seven classes with different trends in RTA mortality rates. The worldwide countries were clustered into seven classes. Further studies on each of the seven classes are suggested to provide recommendations for reducing the mortality rate of the RTAs. Additionally, increasing HDI in some countries could have a significant effect on reducing the RTA death rates.

Background: This study aimed to determine effective factors on geographic distribution of the Incidence of Colorectal Cancer (CRC) in Tehran, Iran using Geographically Weighted Poisson Regression Model. Methods: This ecological study was carried out at neighborhood level of Tehran in 2017-2018. Data for CRC incidence was extracted from the population-based cancer registry data of Iran. The socioeconomic variables, risk factors and health costs were extracted from the Urban HEART Study in Tehran. Geographically weighted Poisson regression model was used for determination of the association between these variables with CRC incidence. GWR 4, Stata 14 and ArcGIS 10.3 software systems were used for statistical analysis. Results: The total number of incident CRC cases were 2815 in Tehran from 2008 to 2011, of whom, 2491 cases were successfully geocoded to the neighborhood. The median IRR for local variables were : unemployed people over 15 year old (median IRR: 1.17), women aged 17 years or older with university education (median IRR: 1.17), women head of household (median IRR: 1.06), people without insurance coverage (median IRR: 1.10), households without daily consumption of milk (median IRR: 0.85), smoking households (median IRR: 1.07), household’s health expenditure (median IRR: 1.39), disease diagnosis costs (median IRR: 1.03), medicines costs of households (median IRR: 1.05), cost of the hospital (median IRR: 1.09), cost of medical visits (median IRR: 1.27). Conclusion: The spatial variability was observed for most socioeconomic variables, risk factors and health costs that had effects on CRC incidence in Tehran. Spatial variability is necessary when interpreting the results and utterly helpful for implementation of prevention programs.

Background: Most studies show that picture-naming test is the best task to evaluate the underlined cognitive and language function in the patients with dementia. Naming performance is the most evident linguistic symptom, which starts in the initial phase of the mild cognitive impairment (MCI) and Alzheimer’s disease (AD). Objectives: The current study aimed at determining the picture-naming performance level of Persian-speaking patients with MCI and AD compared with normal peers using naming subtests of Barnes language assessment (BLA). Methods: In total, 90 subjects were selected through self-report; some relevant tests including mini-mental status examination (MMSE) and functional assessment staging (FAST) scale, as well as experts comments were employed; subjects were divided into three groups of MCI, AD, and normal control (NC) (30 cases per group). Picture-naming performance of patients in the MCI and AD groups was assessed and compared with that of the NC group using the naming subtest of the BLA. Results: In the picture-naming test of BLA, the AD group performed worse than the NC and MCI groups (P < 0.001). Moreover, a significant difference was observed between the NC and MCI groups. While the MCI group performed worse than the NC (P < 0.001), it acted better than the AD group (P < 0.001). Conclusions: According to the results of the current study, picture naming test was a useful cognitive-linguistic task, which can accurately differentiate the three study groups, especially MCI from normal subjects, despite its quick and simple application.

In order to solve problems encountered during natural disasters, in addition to NGOs and relief teams, various individuals intend to help the injured. Although the cooperation of people has remarkable advantages, the disparity between the needs of the injured and the people’s donations can cause problems such as trouble for relief teams and wasting the substantial resources. In generic, the influencer selection in the marketing endeavors is mainly aimed to maximize people’s awareness and attention, but this research proposes a method for influencer selection, using Social Network Analysis (SNA) and optimization techniques, by which it is possible to establish an adaptation between the public attention and the type of injured necessities. The proposed method is applied to a real sample network of Facebook friends, to evaluate the efficiency and validity of the formulated method.