46 research outputs found

    Association between vitamin D and cardiovascular disease: Findings from a national study

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    ABSTRACT Introduction Many studies have investigated the association between vitamin D and cardiovascular disease (CVD), but literature has shown various results. The aim of this study was to investigate the role of vitamin D in CVD. Methods Data source The data were obtained from the 2015-2018 National Health and Nutrition Examination Survey database and included adults aged 20 years and older with a history of CVD. Descriptive statistics for participants’ demographics, vitamin D levels, CVD status, and risk factors were reported. Chi-square tests and t-tests were performed to examine differences in participant characteristics among those who had CVD and did not have CVD. Regression models were used to explore the association between vitamin D levels and CVD. Results A total of 9,825 participants took part in this study with an average age of 50.28 years. Majority were female (52.1%) and Non-Hispanic White (34%). Most had normal vitamin D levels (64.8%) and had never been told that they had CVD (89.5%). Individuals with vitamin D deficiency or insufficiency had a higher likelihood of having CVD than those with normal vitamin D levels. Conclusions Both vitamin D deficiency and insufficiency were associated with an increased risk of CVD. Healthcare professionals may consider recommending the intake of vitamin D supplements to improve and prevent cardiovascular health in adults. Keywords: Vitamin D, cardiovascular disease, healthcare, supplements Word count: 24

    Malmquist Productivity Index by Extended VIKOR Method Using Interval Numbers

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    The VIKOR method was developed for multicriteria optimization of complex systems. It determines the compromise ranking list and the compromise solution obtained with the given weights. This method focuses on ranking and selecting from a set of alternatives in the presence of conflicting criteria. Here, the VIKOR method is used for two times t and t+1. In order to calculate the progress or regression via Malmquist productivity index, the positive and negative ideals at times t and t+1 are calculated first. Then we introduce the multi-criteria ranking index based on the particular measure of “closeness” to the ideal solution and calculate the separation of each alternative from the ideal solution at times t and t+1. Then we use the Malmquist productivity index to calculate the progress or regression of all alternatives. In this paper, productivity of alternatives available in decision matrix with interval numbers and their improvement or deterioration is researched. To achieve this practical goal, use of extended VIKOR is made to calculate Malmquist productivity index for multicriteria decision-making (MCDM) problem with interval numbers, and by applying Malmquist productivity index, productivity rate of growth for alternatives is calculated. Finally, a numerical example illustrates and clarifies the main results developed in this paper

    Association between Fluoride Exposure and Blood pressure

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    Objectives: This study investigated whether fluoride was associated with an increased prevalence of high blood pressure (BP) among adolescents in the United States. Methods: The study sample consisted of 2015–2016 National Health and Nutrition Examination Survey participants aged 13–17 years. Independent-samples t-tests, Chi-square tests, and regression models were used to analyze the data. Results: A total of 814 participants met the study criteria. The findings showed that the proportion of patients with high levels of water or plasma fluoride in the high BP group was higher than that in the normal BP group. However, after adjusting for sociodemographic covariates, neither water nor plasma fluoride levels were significantly associated with a high BP. Conclusions: This study did not find an association between either water or plasma fluoride levels and high BP. Further study is needed to exclude a dose dependent effect at higher levels of fluoride

    Auto parts supply chain risk assessment and rating models using fuzzy cognitive map and Interpretive Structural Modeling

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    One of the major challenges in the automotive industry is facing different risks, especially when introducing new products to meet customer needs. This often leads to difficulties in accurately identifying and adapting to changing methods, designs, new machinery and materials, demand fluctuations, production speed, and more. These factors can result in serious injuries and risks. In order to address these risks, it is crucial to employ effective risk identification methods and prioritize them to exert control over critical risks. Therefore, this paper focuses on identifying the main areas of risks in the automotive industry, specifically within the production line. The identified risks are then categorized and graded. Based on this assessment, a fuzzy cognitive maps approach is developed to analyze 13 risks, which are further divided into three groups: technical, strategic, and operational risks. Furthermore, an interpretive structural modeling approach is used to evaluate the interrelationships among these risks, allowing for a comprehensive understanding of their correlations. Through the network analysis process, the most significant risks are identified. The findings reveal that design errors, low motivation, lack of financial resources, lack of parts, and low productivity are among the top five risks in the ISACO auto parts supply chain. IntroductionThe increasing complexity of industrial systems and the incorporation of new technologies, processes, machinery, and materials have highlighted the importance of considering environmental and safety aspects in risk assessment. Evaluating the impact of failures and their effects is a critical task in industries, particularly in the automotive sector. Among the various risk assessment techniques, failure mode and effects analysis (FMEA) has been widely recognized as a reliable method. Despite the extensive application of FMEA, there are limitations associated with this approach. One of the significant drawbacks is that it considers the SOD factors independently without considering the interdependencies among failures. In reality, production stages are not executed simultaneously, and potential failures do not occur concurrently. Some failures are influenced by previous stage failures and, in turn, affect subsequent stages. On the other hand, interpretive structural modeling (ISM) allows for the comprehensive structuring of a set of interconnected factors in an organized model. By utilizing fundamental concepts of graph theory, ISM describes the intricate pattern of conceptual relationships among variables. In this way, it overcomes the limitations of independent consideration of failures in FMEA. Therefore, this paper employs ISM as an approach to assess the impact of failures. It provides a comprehensive and structured model that captures the interrelationships among various factors. By using this approach, the evaluation of failures becomes more accurate and reliable, considering the interdependencies among different stages and failures.Materials and MethodsThis research is categorized as applied research in terms of its objective and descriptive-qualitative in terms of its method. Field studies were conducted as the data collection tools for this research. The scoring method (utilizing experts) was used for data analysis, and a case study of the ISACO company was employed to test the model. The required data for this research, aimed at presenting a model for identifying production risks in the first stage, were collected through a literature review. Relevant English and Persian books, student theses, related websites, journal articles, conferences, and seminars focusing on the identification of multi-stage production risks were used to gather research literature. Existing documentation from various industries was also utilized in the field of risk assessment and identification. In the initial stage, the main risks of the automotive parts supplier company are identified. In this phase, risks identified in existing scientific research sources were finalized through interviews with experts. The extracted risks are evaluated and ranked based on the failure mode and effects analysis method in the second step. In the third step, the interactions among various risks are examined using the fuzzy cognitive map approach. The results obtained from the second step are utilized in this phase through normalization. In the fourth step, the final ranking of risks is determined based on the static analysis conducted in the third step. In the fifth step, an interpretive structural model is used to determine the interdependence and susceptibility of risks to each other.Discussion and ResultsBased on the research objectives, the risks in the production line domain were first identified using the FMEA (Failure Mode and Effects Analysis) approach. Then, the FCM (Fuzzy Cognitive Mapping) method was employed to design a fuzzy network, and ultimately, the ISM (Interpretive Structural Modeling) approach was used to analyze the penetration and interdependence of risks. The ranking of risks using the FMEA approach is as follows: lack of motivation, parts shortage, low productivity, rework in execution, and weak supervision are ranked from 1 to 5, respectively. After considering the interactions among risks in the dynamic analysis of FCM, the factor of lack of motivation descends from rank 1 to 7. Furthermore, the factors of low productivity and lack of financial resources rank first and second, respectively.ConclusionDecision-making in the field of risk management involves considering various factors that are subject to change over time. The dynamic nature of these factors can influence the effectiveness of risk management decisions, and their impact on the desired outcomes needs to be carefully assessed. Proper risk management requires a comprehensive understanding of potential failures and the ability to predict and mitigate their consequences. Analyzing risks, employing effective mitigation strategies, and conducting thorough evaluations are essential for ensuring the success of a project or business venture. Professional risk management involves identifying and addressing potential vulnerabilities, evaluating their impact on the desired objectives, and devising appropriate strategies to prevent or mitigate their occurrence. The use of risk assessment methodologies, such as Failure Mode and Effects Analysis (FMEA), allows for systematic identification and prediction of potential failures, while incorporating flexibility and adaptability in risk mitigation approaches. These methodologies offer advantages such as scalability, speed, high accuracy in predicting failures, enhanced understanding of complex systems, and facilitation of decision-making processes. By employing fuzzy cognitive mapping (FCM) in FMEA, the prioritization and prediction of potential risks can be effectively performed. This approach provides a more flexible and comprehensive understanding of risks, enabling easier decision-making and utilization of valuable feedback from domain experts. Following the identification of primary risk areas, the risks associated with production lines were classified, and a fuzzy cognitive mapping approach was developed based on this classification. Thirteen identified risks were then analyzed using interpretive structural modeling (ISM) to assess the interrelationships among the risks and provide further insights for decision-making

    Cryptanalysis and Security Enhancement on the Generation of Mu-Varadharajan Electronic Voting Protocol

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    Mu and Varadharajan proposed an electronic voting scheme and claimed that their scheme authenticates the voters, protects the anonymity of them, and detects the identity of double voters. Due to some weaknesses in Mu-Varadharajan scheme, several modified schemes have been proposed by Lin et al., Hwang et al., Rodriguez-Henriquez et al. and Asaar et al.; however this paper shows that these schemes suffer from some weaknesses in fulfilling the pointed properties. For this purpose, we get Hwang et al. scheme as a case study and apply our new attacks on it. Also we consider the applicability of the attacks on other pointed schemes. In addition, we present a new scheme and show that the scheme resists against the proposed attacks without loosing efficiency

    Rapid and simultaneous genotypic detection of Rifampin-Isoniazid and Ethambutol resistant Mycobacterium tuberculosis by use of MAS-PCR

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    AbstractAims and objectivesThis study aims to identify common mutations leading to Isoniazid (INH), Rifampin (RMP) and Etambutol (EMB) resistance using Multiplex Allele-Specific Polymerase Chain Reaction (MAS-PCR).MethodIn a cross-sectional study during 2012–2013, 257 patients with smear-positive pulmonary tuberculosis residing in five frontier west and north-west provinces of Iran were evaluated in respect of common point mutations leading to resistance to tree first-line drugs.ResultsThe overall frequency of mutations was 37 out of which 8 mutations were related to katG 315, 26 mutations pertained to rpoB 516, 526 and 531 and 3 mutations related to emb B. The rpoB single, double and triple mutations were found in 45.3%, 42.3% and 15.4% of rpoB, respectively. Frequency of patients with mutation to katG and at least one rpoB codon was 7cases (2.7%) at the same time. In this study 60.0% of INH-resistant and 83.3% of RMP-resistant isolates were detected by MAS-PCR technique. Mutation odds were higher in females and in patients with a history of anti-TB drug use.ConclusionThe MAS-PCR is a relatively rapid, sustainable, efficient and accurate technique for detection of drug resistance in tuberculosis. This highlights also the role of mutation at inhA, ahp and oxy R genes in the creation of IHN resistance which may be the causative factor in the remainder of cases

    A National Study Exploring the Association Between Fluoride Levels and Dental Fluorosis

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    Importance: While the effects of fluoride on health have been widely researched, fewer high-quality studies examine the association of fluoride levels in water and dental fluorosis. Objective: To investigate the association between fluoride exposure from drinking water and dental fluorosis. Design, setting, and participants: This cross-sectional study used the 2013-2014 and 2015-2016 National Health and Nutrition Examination Survey (NHANES) data (January 1, 2013, through December 31, 2016). NHANES uses a complex sampling technique to develop nationally representative sample estimates of the US population that consists of interviews and physical assessments. Children and adolescents aged 6 to 15 years were included because NHANES contains their data for all 3 forms of fluoride measures: plasma fluoride levels, water levels of fluoride, and dietary fluoride supplementation. Data were analyzed from January 1 to April 30, 2023. Exposures: Water and plasma fluoride levels were measured by laboratory personnel. Dietary fluoride supplement data were self-reported. Main outcomes and measures: The Dean's Fluorosis Index was used to evaluate fluorosis status for each tooth. The dental fluorosis severity value was based on the second most affected tooth. Independent variables included plasma and water fluoride concentrations and dietary fluoride supplementation. An independent samples t test was used to compare fluoride exposures between groups, and Pearson correlation assessed the association between plasma and water fluoride levels. To assess whether fluoride exposures were associated with dental fluorosis, logistic regression analyses were conducted. Results: There were 1543 participants in the 2013-2014 NHANES cycle (weighted proportion male, 51.9%; mean [SD] age, 11.0 [2.7] years) and 1452 in the 2015-2016 cycle (weighted proportion male, 52.6%; mean [SD] age, 11.1 [2.8] years). A weighted 87.3% exhibited some degree of fluorosis in the 2013-2014 cycle and 68.2% in the 2015-2016 cycle. Higher fluoride levels in water and plasma were significantly associated with higher odds of dental fluorosis (adjusted odds ratios, 2.378 [95% CI, 2.372-2.383] in the 2013-2014 cycle and 1.568 [95% CI, 1.564-1.571] in the 2015-2016 cycle). Conclusions and relevance: The findings of this cross-sectional study suggest that exposure to higher concentrations of fluoride in water and having higher plasma levels of fluoride were associated with a greater risk of dental fluorosis. Further research can help policy makers develop policies that balance substantial caries prevention with the risk of dental fluorosis.</p

    Exploring accuracy of statistical characterization of gravel beds using Kinect device in the laboratory scale

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    Mountainous river beds-generally consist of gravel particles that the precise description of such bed is not only important hydraulically, but also it has great environmental significance. The accurate estimation of bed roughness gives us valuable information to make reliable hydraulic models of flow in river with rigorous bed form. This study discuses about the accuracy of the Kinect device in determining the digital elevation model (DEM) of the gravel-bed. In this regard, the DEMs of the two beds include-hemispheres and two beds with artificial gravel beds have been -used and their statistical characteristics have been analyzed. The results show that while the error in the area among the particles is quite high, themethod can accurately conduct these in general. The comparison of the bed elevation histograms shows that although the artificial gravel beds histograms have higher accuracy compared to the histograms of the beds with hemispheres form, the gravel bed with distance elevations histogram shows the best fit among the four explored beds. Furthermore, exploring the statistical characteristics of these four beds shows that the Kinect device is able to obtain reasonable error rate in statistical parameters except the skewness quantity which has the highest rate of relative error. The variogram analysis of artificial gravel beds emphasis that the Kinect and scanner variograms reasonably close to each other and the longitudinal and transversal particles length scales are exactlythe same. According to the results of this investigation, application ofthe Kinect device in statistical analysis of the gravel beds can be suggested

    Factors Associated with Periodontitis in Younger Individuals: A Scoping Review

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    Periodontitis is a disease that affects many young adults, and if left untreated, it can have lasting and permanent effects on an individual’s oral health. The purpose of this scoping review was to review the recent literature to identify factors that place young individuals at risk of stage II or III periodontitis. Using the PRISMA guidelines for scoping reviews, three databases were systematically searched for peer-reviewed human studies published in English that investigated risk factors associated with stage II and/or III periodontitis in individuals less than 40 years of age. This review excluded abstracts, literature reviews, including narrative, scoping, and systematic reviews and meta-analyses, conference proceedings, letters to the editor, and editorials. The authors then extracted data from the relevant studies using a predefined form to summarize the aims, design, results, risk factors examined, and the type and severity of periodontitis. Among a total of 2676 articles screened, only three articles met the review’s inclusion criteria. Of these articles, one was a longitudinal case-control study and two were cross-sectional studies. Identified risk factors associated with stage II or III periodontitis included self-reported bleeding when brushing, low bone mineral density, being overweight, and smoking in young adults. Of note, only three studies met the inclusion criteria, suggesting a gap in the research literature

    Double Voter Perceptible Blind Signature Based Electronic Voting Protocol

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    Mu et al. have proposed an electronic voting protocol and claimed that it protects anonymity of voters, detects double voting and authenticates eligible voters. It has been shown that it does not protect voter\u27s privacy and prevent double voting. After that, several schemes have been presented to fulfill these properties. However, many of them suffer from the same weaknesses. In this paper, getting Asadpour et al. scheme as one of the latest one and showing its weaknesses, we propose a new voting scheme which is immune to the weaknesses of previous schemes without loosing efficiency. The scheme, is based on a special structure, which directly use the identity of voter, hides it in that structure and reveals it after double voting. We also, show that the security of this scheme depends on hardness of RSA cryptosystem, Discrete Logarithm problem and Representation problem
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