THE EFFECT OF INTELLECTUAL CAPITAL ON KNOWLEDGE MANAGEMENT: STUDY ON AGRICULTURE ORGANIZATION EXPERTS IN KURDISTAN PROVINCE

This study aimed at exploring the effect of intellectual capital (IC) on knowledge management (KM) among Agriculture Organization experts of Kurdistan Province. Statistical population of this study consisted of all Agriculture organization experts in the Kurdistan province of Iran (N=326). Using Cochran’s sampling formula, 63 farmers were selected as a sample. Respondents were selected by using Stratified random sampling method. For increasing reliability of the findings, 125 questionnaires distributed among experts, ultimately 101 questionnaires completed and analyzed in SPSS software. The instrument of the study was a questionnaire which its validity was confirmed by a panel of experts and its reliability was established by calculating Chronbach’s Alpha Coefficient (α>0.7). Data analysis was performed by SPSSwin18 software. The Results of this study showed that level of IC and KN was moderate among Agriculture organization expert. Moreover, Results of correlation analysis showed that there is a significant positive relationship between indicators of the IC (human, structural and relational) and KM. Finally, the results of stepwise multiple regression analysis showed that the indicators of IC (human, structural and relational), they can to explain 4.6% of the variance in the dependent variable

Effects of low-dose contraceptive pills on the risk factors of cardiovascular diseases among 15-35-year-old women: A retrospective cohort

Background: Cardiovascular diseases could be preventable; as a result, understanding the risk factors was regarded as the major priority for healthcare providers. Objective: The main objective of this research was to achieve a deeper insight into the effect of long-term use of low-dose oral contraceptive pills (OCP) on the risk factors of cardiovascular diseases. Materials and Methods: This research was a retrospective cohort conducted (historical and prospectively) conducted on 100 women with normal menstrual cycles aged 15 to 35 yr, who were referred to the healthcare centers in Yazd, Iran. The participants were categorized into two groups: The OCP group was consuming the pills for 3, 4-23, and 24-36 months, and the non-OCP group. Participants were followed up for a minimum of 3 months and a maximum of six months. Results: The highest level of low-density lipoprotein (LDL), homocysteine, cholesterol, triglyceride levels, and systolic blood pressure was observed in the OCP group in the duration of 24 to 36 months. The Tukey’s test demonstrated that there were comprehensible differences in the LDL (p = 0.01), cholesterol (p = 0.01), triglyceride (p < 0.001), and homocysteine levels (p < 0.001), also systolic blood pressure (p = 0.04). Conclusion: It was realized that the long-term consumption of low-dose OCP can augment the incidence of some risk factors (systolic blood pressure, homocysteine levels, cholesterol, LDL-c, and triglyceride) and lead to developing cardiovascular diseases amongst the healthy women. Key words: Birth control pills, Homocysteine, Nitric oxide, Dyslipidemias, Coronary artery diseases

A Selective Fluorescent Optode for Lead(II) Based on the Dansylamidopropyl Pendant Arm Derivative of 1,4-dioxa-7,13-dithia-10-azacyclopentadecane ([15]aneNS2O2)

In this study, a novel highly sensitive and selective fluorescent optode membrane aimed at the determination of Pb(II) ion is proposed by incorporating N-(3-(1,4-dioxa-7,13-dithia-10-azacyclopentadecan-10-yl)propyl)-5-(dimethylamino)naphthalene-1-sulfonamide (L) as fluoroionophore in polyvinyl chloride (PVC) containing 2-nitrophenyl octylether (NPOE) as a plasticizer. In addition to high stability and reproducibility, the proposed optosensor showed a unique selectivity toward Pb(II) ion, with a wide linear range of molar concentrations (1.0 × 10−9–1.0 × 10−3 M) and a low detection limit of 7.5 × 10−10 M in solution at pH 5.0. The formation constants of the Pb(II) complexes with the fluoroionophore were evaluated by fitting the fluorescence data with a nonlinear least-squares curve-fitting program, and further information about the structures of the complexes were evaluated based on hybrid-DFT calculations. The optosensor exhibited a fast response time of less than three min, being easily regenerated by exposure to a solution of dithiothreitol. The sensor was applied to the determination of Pb(II) in real samples (canned tuna fish), and it provided satisfactory results comparable to those obtained via atomic absorption spectrometry (AAS)

Reinforcing Data Integrity in Renewable Hybrid AC-DC Microgrids from Social-Economic Perspectives

The microgrid (MG) is a complicated cyber-physical system that operates based on interactions between physical processes and computational components, which make it vulnerable to varied cyber-attacks. In this paper, the impact of data integrity attack (DIA) has been considered, as one of the most dangerous cyber threats to MGs, on the steady-state operation of hybrid MGs (HMGs). Additionally, a novel method based on sequential hypothesis testing (SHT) approach, is proposed to detect DIA on the renewable energy sources’ metering infrastructure and improve the data security within the HMGs. The proposed method generates a binary sample, which is used to compute a test statistic that is further used against two thresholds to decide among three alternatives. The performance of the suggested method is examined using an IEEE standard test system. The results illustrated the acceptable performance of the proposed methodology in detection of DIAs. Also, to evaluate the effect of DIA on the operation of the HMGs, DIAs with different severities are launched on the measured power generation of renewable energy resources (RESs) like wind turbine (WT). The results of this part showed that a successful DIA on renewable units can severely affect the operation of electric grids and cause serious damages.© 2022 Copyright held by the owner/author(s), published by Association for Computing Machinery (ACM). This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in ACM Transactions on Sensor Networks, http://dx.doi.org/10.1145/3512891. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]=vertaisarvioitu|en=peerReviewed

Scientometrics and Analysis of the Research Trends in the Fourth Industrial Revolution Field and Quality 0.4

Purpose: This research aims to investigate the changes that have taken place in the Fourth Industrial Revolution, particularly in the field of quality 4.0, at a global level and within organizations. The researchers seek to explore the impact of intelligent technologies on society and products, as well as how advanced and developing countries have moved towards digitalization. Various specific topics related to Industry 4.0 and Quality 4.0 have received special attention in this study. Additionally, the research aims to examine the collaboration between countries in different areas and how researchers and industry professionals in developed countries have utilized intelligent technologies to enhance their capabilities.Method: Scientometrics and data analysis methods were employed in this research to achieve the research objectives and answer the research questions. Data, including articles, books, dissertations, conference papers, and more, were extracted from the Web of Science database, specifically focusing on the years 2012 to 2020, in the fields of industry 4.0, intelligent technologies, quality 4.0, and related concepts. A total of 4,926 studies were included. The Space software was used for data analysis, where nodes represent author names, journals, countries, keywords, etc., and the links indicate citations or correlations between nodes. The desired outputs were presented in the form of figures and tables.Findings: Although countries like Germany and the United States were among the first to pursue digitalization and the use of intelligent technologies in their production systems and all sectors of their countries, many developing countries, such as India, have increasingly embraced these technologies. It is expected that these countries will achieve significant technological advancements in the near future. Furthermore, recent studies have shown that researchers have focused more on the use of intelligent technologies to reduce environmental pollution by minimizing the use of natural resources. This demonstrates the global attention given to environmental issues. The findings also indicate a trend towards intelligent production and the necessity of automated quality control using robots. Such advancements should be widely implemented within organizations, leading to smart quality or quality 4.0.Conclusion: Based on the results of this research, it is evident that the Fourth Industrial Revolution has brought significant changes to technologies in general, transforming production and service processes through technologies such as cyber-physical systems, 3D printing, blockchain, and big data. In recent years, many organizations in both developing and developed countries have sought to implement quality 4.0 concepts in various areas such as leadership, culture, and strategy development, utilizing intelligent technologies for smart quality control within their organizations. Therefore, future research in the fields of industry 4.0 and quality 4.0 may consider topics such as digital leadership, digital culture, digital organizational structure, and more

Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks for 195 countries and territories, 1990–2017 : a systematic analysis for the Global Burden of Disease Study 2017

Background: The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 comparative risk assessment (CRA) is a comprehensive approach to risk factor quantification that offers a useful tool for synthesising evidence on risks and risk outcome associations. With each annual GBD study, we update the GBD CRA to incorporate improved methods, new risks and risk outcome pairs, and new data on risk exposure levels and risk outcome associations. Methods: We used the CRA framework developed for previous iterations of GBD to estimate levels and trends in exposure, attributable deaths, and attributable disability-adjusted life-years (DALYs), by age group, sex, year, and location for 84 behavioural, environmental and occupational, and metabolic risks or groups of risks from 1990 to 2017. This study included 476 risk outcome pairs that met the GBD study criteria for convincing or probable evidence of causation. We extracted relative risk and exposure estimates from 46 749 randomised controlled trials, cohort studies, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. Using the counterfactual scenario of theoretical minimum risk exposure level (TMREL), we estimated the portion of deaths and DALYs that could be attributed to a given risk. We explored the relationship between development and risk exposure by modelling the relationship between the Socio-demographic Index (SDI) and risk-weighted exposure prevalence and estimated expected levels of exposure and risk-attributable burden by SDI. Finally, we explored temporal changes in risk-attributable DALYs by decomposing those changes into six main component drivers of change as follows: (1) population growth; (2) changes in population age structures; (3) changes in exposure to environmental and occupational risks; (4) changes in exposure to behavioural risks; (5) changes in exposure to metabolic risks; and (6) changes due to all other factors, approximated as the risk-deleted death and DALY rates, where the risk-deleted rate is the rate that would be observed had we reduced the exposure levels to the TMREL for all risk factors included in GBD 2017. Findings: In 2017,34.1 million (95% uncertainty interval [UI] 33.3-35.0) deaths and 121 billion (144-1.28) DALYs were attributable to GBD risk factors. Globally, 61.0% (59.6-62.4) of deaths and 48.3% (46.3-50.2) of DALYs were attributed to the GBD 2017 risk factors. When ranked by risk-attributable DALYs, high systolic blood pressure (SBP) was the leading risk factor, accounting for 10.4 million (9.39-11.5) deaths and 218 million (198-237) DALYs, followed by smoking (7.10 million [6.83-7.37] deaths and 182 million [173-193] DALYs), high fasting plasma glucose (6.53 million [5.23-8.23] deaths and 171 million [144-201] DALYs), high body-mass index (BMI; 4.72 million [2.99-6.70] deaths and 148 million [98.6-202] DALYs), and short gestation for birthweight (1.43 million [1.36-1.51] deaths and 139 million [131-147] DALYs). In total, risk-attributable DALYs declined by 4.9% (3.3-6.5) between 2007 and 2017. In the absence of demographic changes (ie, population growth and ageing), changes in risk exposure and risk-deleted DALYs would have led to a 23.5% decline in DALYs during that period. Conversely, in the absence of changes in risk exposure and risk-deleted DALYs, demographic changes would have led to an 18.6% increase in DALYs during that period. The ratios of observed risk exposure levels to exposure levels expected based on SDI (O/E ratios) increased globally for unsafe drinking water and household air pollution between 1990 and 2017. This result suggests that development is occurring more rapidly than are changes in the underlying risk structure in a population. Conversely, nearly universal declines in O/E ratios for smoking and alcohol use indicate that, for a given SDI, exposure to these risks is declining. In 2017, the leading Level 4 risk factor for age-standardised DALY rates was high SBP in four super-regions: central Europe, eastern Europe, and central Asia; north Africa and Middle East; south Asia; and southeast Asia, east Asia, and Oceania. The leading risk factor in the high-income super-region was smoking, in Latin America and Caribbean was high BMI, and in sub-Saharan Africa was unsafe sex. O/E ratios for unsafe sex in sub-Saharan Africa were notably high, and those for alcohol use in north Africa and the Middle East were notably low. Interpretation: By quantifying levels and trends in exposures to risk factors and the resulting disease burden, this assessment offers insight into where past policy and programme efforts might have been successful and highlights current priorities for public health action. Decreases in behavioural, environmental, and occupational risks have largely offset the effects of population growth and ageing, in relation to trends in absolute burden. Conversely, the combination of increasing metabolic risks and population ageing will probably continue to drive the increasing trends in non-communicable diseases at the global level, which presents both a public health challenge and opportunity. We see considerable spatiotemporal heterogeneity in levels of risk exposure and risk-attributable burden. Although levels of development underlie some of this heterogeneity, O/E ratios show risks for which countries are overperforming or underperforming relative to their level of development. As such, these ratios provide a benchmarking tool to help to focus local decision making. Our findings reinforce the importance of both risk exposure monitoring and epidemiological research to assess causal connections between risks and health outcomes, and they highlight the usefulness of the GBD study in synthesising data to draw comprehensive and robust conclusions that help to inform good policy and strategic health planning

Nationwide Prevalence of Diabetes and Prediabetes and Associated Risk Factors Among Iranian Adults: Analysis of Data from PERSIAN Cohort Study

Introduction Over the past decades prevalence of diabetes has increased in Iran and other countries. This study aimed to update the prevalence of diabetes and prediabetes in Iran and to determine associated sociodemographic risk factors, as well as diabetes awareness and control. Methods This is a nationally representative cross-sectional survey that included 163,770 Iranian adults aged 35-70 years, from different ethnic backgrounds, between 2014 and 2020. Diabetes was diagnosed at fasting blood sugar of >= 6.99 mmol/L (126 mg/dL), or receiving blood glucose-lowering treatment. Multivariable logistic regression was applied to detect determinants associated with prevalence of diabetes and prediabetes, as well as predictors of diabetes awareness and glycemic control. Results Sex- and age-standardized prevalence of diabetes and prediabetes was 15.0% (95% CI 12.6-17.3) and 25.4% (18.6-32.1), respectively. Among patients with diabetes, 79.6% (76.2-82.9) were aware of their diabetes. Glycemic control was achieved in 41.2% (37.5-44.8) of patients who received treatment. Older age, obesity, high waist to hip ratio (WHR), and specific ethnic background were associated with a significant risk of diabetes and prediabetes. Higher awareness of diabetes was observed in older patients, married individuals, those with high WHR, and individuals with high wealth score. Moreover, glycemic control was significantly better in women, obese individuals, those with high physical activity, educational attainment, and specific ethnic background. Conclusions The prevalence of diabetes and prediabetes is increasing at an alarming rate in Iranian adults. High proportion of uncontrolled patients require particular initiatives to be integrated in the health care system

Global, regional, and national burden of Alzheimer's disease and other dementias, 1990-2016: a systematic analysis for the Global Burden of Disease Study 2016

Background The number of individuals living with dementia is increasing, negatively affecting families, communities, and health-care systems around the world. A successful response to these challenges requires an accurate understanding of the dementia disease burden. We aimed to present the first detailed analysis of the global prevalence, mortality, and overall burden of dementia as captured by the Global Burden of Diseases, Injuries, and Risk Factors (GBD) Study 2016, and highlight the most important messages for clinicians and neurologists. Methods GBD 2016 obtained data on dementia from vital registration systems, published scientific literature and surveys, and data from health-service encounters on deaths, excess mortality, prevalence, and incidence from 195 countries and territories from 1990 to 2016, through systematic review and additional data-seeking efforts. To correct for differences in cause of death coding across time and locations, we modelled mortality due to dementia using prevalence data and estimates of excess mortality derived from countries that were most likely to code deaths to dementia relative to prevalence. Data were analysed by standardised methods to estimate deaths, prevalence, years of life lost (YLLs), years of life lived with disability (YLDs), and disability-adjusted life-years (DALYs; computed as the sum of YLLs and YLDs), and the fractions of these metrics that were attributable to four risk factors that met GBD criteria for assessment (high body-mass index [BMI], high fasting plasma glucose, smoking, and a diet high in sugar-sweetened beverages). Findings In 2016, the global number of individuals who lived with dementia was 43·8 million (95% uncertainty interval [UI] 37·8–51·0), increased from 20.2 million (17·4–23·5) in 1990. This increase of 117% (95% UI 114–121) contrasted with a minor increase in age-standardised prevalence of 1·7% (1·0–2·4), from 701 cases (95% UI 602–815) per 100 000 population in 1990 to 712 cases (614–828) per 100 000 population in 2016. More women than men had dementia in 2016 (27·0 million, 95% UI 23·3–31·4, vs 16.8 million, 14.4–19.6), and dementia was the fifth leading cause of death globally, accounting for 2·4 million (95% UI 2·1–2·8) deaths. Overall, 28·8 million (95% UI 24·5–34·0) DALYs were attributed to dementia; 6·4 million (95% UI 3·4–10·5) of these could be attributed to the modifiable GBD risk factors of high BMI, high fasting plasma glucose, smoking, and a high intake of sugar-sweetened beverages. Interpretation The global number of people living with dementia more than doubled from 1990 to 2016, mainly due to increases in population ageing and growth. Although differences in coding for causes of death and the heterogeneity in case-ascertainment methods constitute major challenges to the estimation of the burden of dementia, future analyses should improve on the methods for the correction of these biases. Until breakthroughs are made in prevention or curative treatment, dementia will constitute an increasing challenge to health-care systems worldwide