Prioritizing pre-hospital and hospital emergency staff’s training needs regarding traffic accidents: Comparing the viewpoints of experts and target group

Background and Aims: It is essential to recognize the current situation and training needs for staff in the field of traffic accident prevention in order to organize suitable training programs. This study was conducted to assess the educational needs of pre-hospital and hospital personnel with respect to traffic accidents in 2015.Materials and methods: This combined study was conducted in three phases-collection of qualitative data, design and validation of the needs assessment questionnaire, and a cross-sectional study. In the first stage, the assessment questionnaire was prepared using semi-structured interviews. The content validityof the questionnaire was then conducted by an expert panel. Finally, educational needs of the target group were assessed in a cross-sectional study using the questionnaire. All stages of this research were conducted ethically. Results: Results showed that the most important educational needs of pre-hospital centers were CPR training, opening up airways, checking the status of victim awareness, and ABC training courses. The three priorities of hospital emergency centers included ways to deal with special cases (such as amputation), advanced burn life support, and advanced trauma life support (ATLS) with the same degree of importance and self-care as in a road accident course.Conclusion: The identified priorities point out that it is necessary to formulate and implement educational programs to enhance the skills of pre-hospital and hospital staff

The Optimization of Energy Supply Systems by Sequential Streamflow Routing Method and Invasive Weed Optimization Algorithm; Case Study: Karun II Hydroelectric Power Plant

Among the major sources of energy supply systems, hydroelectric power plants are more common. Energy supply during peak hours and less environmental issues are some of the most important advantages of hydroelectric power plants. In this study, designing parameters to supply maximum amount of energy was determined by using the simulation-optimization perspective and combination of IWO-WEAP models. Subsequently, the developed model has been applied for designing the Karun II hydroelectric power plant. The sequential streamflow routing method has been developed for obtaining energy in WEAP water resources management software. In addition the optimization algorithm has been applied to optimize the invasive weeds. To verify the performance of this method, obtained results for the firm energy were compared to those of the total energy. Using this method, for 1398 GWY (Giga watt per your) firm energy, the minimum and normal levels of operation were 668 and 672 m.a.s.l (meters above sea level), respectively, and the installation capacity calculated around 498 MW as optimal value

The Role of Perceived Risk in the Adoption of Internet of Things Technology in Sports

The Internet of Things (IoT) is one technology that can revolutionize traditional methods and transform sports infrastructure. To promote the adoption of IoT effectively, it's vital for sports manager to understand the factors that positively and negatively affect it. The aim of this study was to investigate how perceived risk impacts people's willingness to use IoT technology in sports. This quantitative study used a survey method and applied a descriptive approach. The statistical population included Iranian athletes, and 394 individuals completed questionnaires using a non-probability sampling method. Data analysis was performed using Smart PLS3 software. Results showed that perceived risk has a direct and negative impact on perceived ease of use, willingness to use, and perceived usefulness. However, its effect on attitude towards use was insignificant. The study also confirmed the positive impact of perceived ease of use on perceived usefulness and attitude towards use. Perceived usefulness had a greater effect on the latter variable. Additionally, perceived usefulness had a significant positive impact on willingness to use IoT technology in sports, as did attitude towards use. Attitude towards use also had a significant positive impact on willingness to use IoT technology in sports. The study recommends implementing strategies to enhance and improve perceived usefulness, ease of use, and attitude towards use while reducing perceived risk to increase acceptance and willingness to use IoT technology in sports

Effect of Different Oil Regimes on the Hedging of Oil Transactions by Participating in Gold Market: RS-DCC Approach

Oil prices and other oil-products prices are connected to each other and their price volatilities are parallel. Firms which are using crude oil in their products are facing a risk of price volatility which has different reactions in each era and is known under different oil regimes. For example lubricant industry is completely connected to the oil price. With this philosophy when the economy faced volatility the market players faced loss and so to overcome this issue they began to hedge themselves with another commodity. This hedging process in different regimes has different rates. So there is a need to introduce a new model. From the work of Hamiltonian (1989) oil price has its own volatility and regimes so to this attitude there is an effort to calculate an efficient hedging ratio with regime switching dynamic constant correlation. In this article, monthly data of oil and gold prices for about 10 years from 2010 till 2020 is used and the model is programed with MATLAB. The result showed that the efficient hedge ratio for the first regime (first major change in price of two markets) is 66 percent and the second (second major change in price of two markets) one is 26 percent

DIDA: Distributed Indexing Dispatched Alignment

One essential application in bioinformatics that is affected by the high-throughput sequencing data deluge is the sequence alignment problem, where nucleotide or amino acid sequences are queried against targets to find regions of close similarity. When queries are too many and/or targets are too large, the alignment process becomes computationally challenging. This is usually addressed by preprocessing techniques, where the queries and/or targets are indexed for easy access while searching for matches. When the target is static, such as in an established reference genome, the cost of indexing is amortized by reusing the generated index. However, when the targets are non-static, such as contigs in the intermediate steps of a de novo assembly process, a new index must be computed for each run. To address such scalability problems, we present DIDA, a novel framework that distributes the indexing and alignment tasks into smaller subtasks over a cluster of compute nodes. It provides a workflow beyond the common practice of embarrassingly parallel implementations. DIDA is a cost-effective, scalable and modular framework for the sequence alignment problem in terms of memory usage and runtime. It can be employed in large-scale alignments to draft genomes and intermediate stages of de novo assembly runs. The DIDA source code, sample files and user manual are available through http://www.bcgsc.ca/platform/bioinfo/software/dida. The software is released under the British Columbia Cancer Agency License (BCCA), and is free for academic use

Brent Crude Oil Price Forecasting by Combining Grey Theory and Econometrics Techniques

The characteristics of crude oil and the factors affecting the price of this energy carrier have made its price forecast always considered by researchers, oil market participants, governments, and policymakers. Because the price of crude oil is affected by many factors, ongoing studies should be done to make more accurate and reliable estimates over time. In this paper, a combination of GM (1,1) and ARIMA models and a hybrid model (GM-ARIMA) for crude oil price forecasting is proposed. The Brent crude oil price data for seasonal (2015Q1-2021Q2), monthly(2020m3-2020m12), and weekly(w12-2020: w16-2021) periods were used to examine this method. The results show that based on the evaluation criteria of mean absolute error percentage (MAPE) and square mean square error (RMSE), the evaluation criteria of MAPE and RMSE in the combined GM-ARIMA model are always lower than the GM and ARIMA models alone. Therefore, the GM-ARIMA hybrid model will be able to predict more accurately than the GM and ARIMA models. Therefore, for more accurate prediction, the GM-ARIMA hybrid model can be used instead of single models

Two-Step Estimation of the Impact of Contextual Variables on Technical Efficiency of Hospitals: The Case Study of Public Hospitals in Iran

Background: Measuring the efficiency and productivity of hospitals is a key tool to cost contamination and management that is very important for any healthcare system for having an efficient system. Objective: The purpose of this study is to examine the effects of contextual factors on hospital efficiency in Iranian public hospitals. Methods: This was a quantitative and descriptive-analytical study conducted in two steps. First, we measured the efficiency score of teaching and non-teaching hospitals by using the Data Envelopment Analysis (DEA) method. Second, the relationship between efficiency score and contextual factors was analyzed. We used median statistics (first and third quarters) to describe the concentration and distribution of each variable in teaching and non-teaching hospitals, then the Wilcoxon test was used to compare them. The Spearman test was used to evaluate the correlation between the efficiency of hospitals and contextual variables (province area, province population, population density, and the number of beds per hospital). Results: On average, the efficiency score in non-teaching hospitals in 31 provinces was 0.67 and for teaching hospitals was 0.54. Results showed that there is no significant relationship between the efficiency score and the number of hospitals in the provinces (p = 0.1 and 0.15, respectively). The relationship between the number of hospitals and the population of the province was significant and positive. Also, there was a positive relationship between the number of beds and the area of the province in both types of teaching and non-teaching hospitals. Conclusion: Multilateral factors influence the efficiency of hospitals and to address hospital inefficiency multi-intervention packages focusing on the hospital and its context should be developed. It is necessary to pay attention to contextual factors and organizational architecture to improve efficiency

Mapping 123 million neonatal, infant and child deaths between 2000 and 2017

Since 2000, many countries have achieved considerable success in improving child survival, but localized progress remains unclear. To inform efforts towards United Nations Sustainable Development Goal 3.2—to end preventable child deaths by 2030—we need consistently estimated data at the subnational level regarding child mortality rates and trends. Here we quantified, for the period 2000–2017, the subnational variation in mortality rates and number of deaths of neonates, infants and children under 5 years of age within 99 low- and middle-income countries using a geostatistical survival model. We estimated that 32% of children under 5 in these countries lived in districts that had attained rates of 25 or fewer child deaths per 1,000 live births by 2017, and that 58% of child deaths between 2000 and 2017 in these countries could have been averted in the absence of geographical inequality. This study enables the identification of high-mortality clusters, patterns of progress and geographical inequalities to inform appropriate investments and implementations that will help to improve the health of all populations

Global injury morbidity and mortality from 1990 to 2017 : results from the Global Burden of Disease Study 2017

Correction:Background Past research in population health trends has shown that injuries form a substantial burden of population health loss. Regular updates to injury burden assessments are critical. We report Global Burden of Disease (GBD) 2017 Study estimates on morbidity and mortality for all injuries. Methods We reviewed results for injuries from the GBD 2017 study. GBD 2017 measured injury-specific mortality and years of life lost (YLLs) using the Cause of Death Ensemble model. To measure non-fatal injuries, GBD 2017 modelled injury-specific incidence and converted this to prevalence and years lived with disability (YLDs). YLLs and YLDs were summed to calculate disability-adjusted life years (DALYs). Findings In 1990, there were 4 260 493 (4 085 700 to 4 396 138) injury deaths, which increased to 4 484 722 (4 332 010 to 4 585 554) deaths in 2017, while age-standardised mortality decreased from 1079 (1073 to 1086) to 738 (730 to 745) per 100 000. In 1990, there were 354 064 302 (95% uncertainty interval: 338 174 876 to 371 610 802) new cases of injury globally, which increased to 520 710 288 (493 430 247 to 547 988 635) new cases in 2017. During this time, age-standardised incidence decreased non-significantly from 6824 (6534 to 7147) to 6763 (6412 to 7118) per 100 000. Between 1990 and 2017, age-standardised DALYs decreased from 4947 (4655 to 5233) per 100 000 to 3267 (3058 to 3505). Interpretation Injuries are an important cause of health loss globally, though mortality has declined between 1990 and 2017. Future research in injury burden should focus on prevention in high-burden populations, improving data collection and ensuring access to medical care.Peer reviewe