17 research outputs found

    Hub Covering Location Problem Considering Queuing and Capacity Constraints

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    In this paper, a hub covering location problem is considered. Hubs, which are the most congested part of a network, are modeled as M/M/C queuing system and located in placeswhere the entrance flows are more than a predetermined value.A fuzzy constraint is considered in order to limit the transportation time between all origin-destination pairs in the network.On modeling, a nonlinear mathematical program is presented.Then, the nonlinear constraints are convertedto linear ones.Due to the computational complexity of the problem,genetic algorithm (GA),particle swarm optimization (PSO)based heuristics, and improved hybrid PSO are developedto solve the problem. Since the performance of the given heuristics is affected by the corresponding parameters of each, Taguchi method is appliedin order to tune the parameters. Finally,the efficiency ofthe proposed heuristicsis studied while designing a number of test problems with different sizes.The computational results indicated the greater efficiency of the heuristic GA compared to the other methods for solving the proble

    Power System Dynamic Stability Enhancement Using a New PID Type PSS 1

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    Abstract: Power System Stabilizers (PSS) are used to generate supplementary damping control signals for the excitation system in order to damp the Low Frequency Oscillations (LFO) of the electric power system. The PSS is usually designed based on classical control approaches but this Conventional PSS (CPSS) has some problems. To overcome the drawbacks of CPSS, numerous techniques have been proposed in literatures. In this paper a PID type PSS (PID-PSS) is considered for damping electric power system oscillations. The parameters of this PID type PSS (PID-PSS) are tuned based on Hybrid Genetic Algorithm optimization method. The proposed PID-PSS is evaluated against the conventional power system stabilizer (CPSS) at a single machine infinite bus power system considering system parametric uncertainties. The simulation results clearly indicate the effectiveness and validity of the proposed method

    Circulating nesfatin-1 levels in women with polycystic ovary syndrome: A systematic review and meta-analysis

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    Background: Polycystic ovary syndrome (PCOS) is a prevalent endocrine disorder in females. Nesfatin-1 is a neuropeptide synthesized in the hypothalamus and other peripheral organs, and there are conflicting opinions about its correlation with PCOS. Objective: This study aims to investigate the correlation between nesfatin-1 and PCOS and evaluates the effectiveness of nesfatin-1 as a biomarker for the detection of PCOS in women. Materials and Methods: A systematic review and meta-analysis were conducted to identify pertinent articles from databases such as PubMed, Web of Science, Cochrane, EMBASE, Scopus, and Google Scholar. The standardized mean difference (SMD) and 95% confidence interval (CI) were calculated using a random effects model to compare group outcomes. Additionally, meta-regression and subgroup analysis were performed to elucidate sources of heterogeneity. Results: The meta-analysis involved 12 studies with 1222 participants, and the findings revealed a significant relationship between PCOS and nesfatin-1 levels. The pooled (SMD = 0.54; 95% CI: 0.00-1.07; p = 0.04) indicated a significant difference between the evaluated groups. Moreover, a subgroup analysis showed that there was a substantial difference in nesfatin-1 levels among women with PCOS and higher homeostatic model assessment for insulin resistance ratio (SMD = 1.46; 95% CI: 0.92-2.00; p < 0.001). Conclusion: Our meta-analysis indicates an association between high nesfatin-1 levels and PCOS. This suggests a potential role of nesfatin-1 in the development of PCOS and proposes it as a potential diagnostic biomarker for the disease. However, further research is necessary to validate these findings. Key words: Polycystic ovary syndrome, Insulin resistance, Body mass index, Meta-analysis

    Optimal PID power system stabilizer tuning based on particle swarm optimization

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    Abstract Power system stabilizers (PSS) are used to generate supplementary damping control signals for the excitation system in order to damp the low frequency oscillations (LFO) of the electric power system. The PSS is usually designed based on classical control approaches but this conventional PSS (CPSS) has some problems. To overcome the drawbacks of CPSS, numerous techniques have been proposed in literatures. In this paper a PID type PSS is considered for damping electric power system oscillations. The parameters of this PID type PSS are tuned based on particle swarm optimization method. The proposed PSS (PSO-PSS) is evaluated against the conventional power system stabilizer (CPSS) at a single machine infinite bus power system considering system parametric uncertainties. The simulation results clearly indicate the effectiveness and validity of the proposed method

    Global incidence, prevalence, years lived with disability (YLDs), disability-adjusted life-years (DALYs), and healthy life expectancy (HALE) for 371 diseases and injuries in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

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    Background: Detailed, comprehensive, and timely reporting on population health by underlying causes of disability and premature death is crucial to understanding and responding to complex patterns of disease and injury burden over time and across age groups, sexes, and locations. The availability of disease burden estimates can promote evidence-based interventions that enable public health researchers, policy makers, and other professionals to implement strategies that can mitigate diseases. It can also facilitate more rigorous monitoring of progress towards national and international health targets, such as the Sustainable Development Goals. For three decades, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) has filled that need. A global network of collaborators contributed to the production of GBD 2021 by providing, reviewing, and analysing all available data. GBD estimates are updated routinely with additional data and refined analytical methods. GBD 2021 presents, for the first time, estimates of health loss due to the COVID-19 pandemic. Methods: The GBD 2021 disease and injury burden analysis estimated years lived with disability (YLDs), years of life lost (YLLs), disability-adjusted life-years (DALYs), and healthy life expectancy (HALE) for 371 diseases and injuries using 100 983 data sources. Data were extracted from vital registration systems, verbal autopsies, censuses, household surveys, disease-specific registries, health service contact data, and other sources. YLDs were calculated by multiplying cause-age-sex-location-year-specific prevalence of sequelae by their respective disability weights, for each disease and injury. YLLs were calculated by multiplying cause-age-sex-location-year-specific deaths by the standard life expectancy at the age that death occurred. DALYs were calculated by summing YLDs and YLLs. HALE estimates were produced using YLDs per capita and age-specific mortality rates by location, age, sex, year, and cause. 95% uncertainty intervals (UIs) were generated for all final estimates as the 2·5th and 97·5th percentiles values of 500 draws. Uncertainty was propagated at each step of the estimation process. Counts and age-standardised rates were calculated globally, for seven super-regions, 21 regions, 204 countries and territories (including 21 countries with subnational locations), and 811 subnational locations, from 1990 to 2021. Here we report data for 2010 to 2021 to highlight trends in disease burden over the past decade and through the first 2 years of the COVID-19 pandemic. Findings: Global DALYs increased from 2·63 billion (95% UI 2·44–2·85) in 2010 to 2·88 billion (2·64–3·15) in 2021 for all causes combined. Much of this increase in the number of DALYs was due to population growth and ageing, as indicated by a decrease in global age-standardised all-cause DALY rates of 14·2% (95% UI 10·7–17·3) between 2010 and 2019. Notably, however, this decrease in rates reversed during the first 2 years of the COVID-19 pandemic, with increases in global age-standardised all-cause DALY rates since 2019 of 4·1% (1·8–6·3) in 2020 and 7·2% (4·7–10·0) in 2021. In 2021, COVID-19 was the leading cause of DALYs globally (212·0 million [198·0–234·5] DALYs), followed by ischaemic heart disease (188·3 million [176·7–198·3]), neonatal disorders (186·3 million [162·3–214·9]), and stroke (160·4 million [148·0–171·7]). However, notable health gains were seen among other leading communicable, maternal, neonatal, and nutritional (CMNN) diseases. Globally between 2010 and 2021, the age-standardised DALY rates for HIV/AIDS decreased by 47·8% (43·3–51·7) and for diarrhoeal diseases decreased by 47·0% (39·9–52·9). Non-communicable diseases contributed 1·73 billion (95% UI 1·54–1·94) DALYs in 2021, with a decrease in age-standardised DALY rates since 2010 of 6·4% (95% UI 3·5–9·5). Between 2010 and 2021, among the 25 leading Level 3 causes, age-standardised DALY rates increased most substantially for anxiety disorders (16·7% [14·0–19·8]), depressive disorders (16·4% [11·9–21·3]), and diabetes (14·0% [10·0–17·4]). Age-standardised DALY rates due to injuries decreased globally by 24·0% (20·7–27·2) between 2010 and 2021, although improvements were not uniform across locations, ages, and sexes. Globally, HALE at birth improved slightly, from 61·3 years (58·6–63·6) in 2010 to 62·2 years (59·4–64·7) in 2021. However, despite this overall increase, HALE decreased by 2·2% (1·6–2·9) between 2019 and 2021. Interpretation: Putting the COVID-19 pandemic in the context of a mutually exclusive and collectively exhaustive list of causes of health loss is crucial to understanding its impact and ensuring that health funding and policy address needs at both local and global levels through cost-effective and evidence-based interventions. A global epidemiological transition remains underway. Our findings suggest that prioritising non-communicable disease prevention and treatment policies, as well as strengthening health systems, continues to be crucially important. The progress on reducing the burden of CMNN diseases must not stall; although global trends are improving, the burden of CMNN diseases remains unacceptably high. Evidence-based interventions will help save the lives of young children and mothers and improve the overall health and economic conditions of societies across the world. Governments and multilateral organisations should prioritise pandemic preparedness planning alongside efforts to reduce the burden of diseases and injuries that will strain resources in the coming decades. Funding: Bill & Melinda Gates Foundation

    Concept, Components and Promotion of Global Citizenship

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    The term "citizenship" refers to an identity between a person and a city, state or nation. When combined with the term "global", it typically defines a person who places their identity with a "global community" above their identity as a citizen of a particular nation or place. The idea is that one’s identity transcends geography or political borders and that responsibilities or rights are or can be derived from membership in a broader class: "humanity". The message of Global citizenship is that the core social, political, economic and environmental realities of the world today should be addressed at all levels - by individuals, civil society organizations, communities and nation states - through a global lens. The lack of a global democratic government that is accountable and responsible against citizens in the face of global challenges, demonstrate the ineffectiveness and lack of effectiveness of the world existing structures. Therefore, to supplement the existing structures, global citizenship is performative and citizen-oriented. Citizens through information and communication networks participate in solving global issues, including environmental problems, human rights, peace and global poverty. This type of citizenship is promoted thorough information technology, environmental, multicultural and human rights education

    Analysis of Administrative Justice Act from the Perspective of Specific Administrative Fair Trial Standards (with Regard to European Human Rights Court)

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    Administrative hearing is one of the important new areas of proceedings. Fair administrative justice standards are divided into two categories: comprehensive general standards of fair trial and specific fair trial standards which govern the three stages of the administrative hearing (including institution of case, hearing and decision making). In this article, Administrative Justice Act (enacted of 1992 by Islamic Council (Majlis)) as legislative action is analyzed in terms of specific fair trial principles and criteria that govern the three stages of Administrative Procedure to be clarified that, to what extent these standards are met in the legislative process related to principle 173. Therefore, this article seeks to answer the questions that follow: what principles and rules as administrative fair trial standards are governing over the three stages of administrative hearing? To what extent the principles of administrative justice system are guaranteed and respected

    A highly accurate model for prediction of thermal conductivity of carbon-based nano-enhanced PCMs using an artificial neural network

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    Nano-PCMs, which contain nanostructured materials, can enhance the low thermal conductivity of phase change materials (PCMs). It is crucial to predict the precise thermal conductivity of nano-PCM to assess the heat transfer during phase change procedures such as melting and solidification. In this study, artificial neural network (ANN) and response surface method (RSM) were used to develop a model for predicting the thermal conductivity of carbon-based nano-enhanced phase change materials (NEPCMs) using 482 experimental samples collected from various datasets. The carbon-based nano-particles were SWCNTs, MWCNTs, graphite, graphene, and (CNFs). Six input parameters were considered with varying temperature, mass fractions, sizes, thermal conductivities of PCMs and nano-particles, and the phase of PCM. The ANN was designed using a multi-layered feed-forward structure and Levenberg–Marquardt back-propagation algorithm with one hidden layer consisting of eight neurons. The transfer function was varied to achieve optimal performance. It was revealed that the predictive capacity of the ANN model is greater than that of the RSM model based on their corresponding the coefficient of determination (R2) and root mean square error (RMSE) values. The developed ANN achieved a R2 value of 0.99, while the RSM method model achieved an R2 value of 0.79

    The Effect of Health Expenditure on Labor Productivity in Iran in 2005 -2013

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    Introduction: Increase human capital and quality of human resources by increase health level one of the important factors for economic growth, that in constant level of inputs increase productivity. Method: This study uses panel data of 30 provinces over 2005 -2013 that obtained from regional data of statistical center of Iran, estimate Mankiw, Romer and Weil model by generalized method of moments and panel data. Data analysis was performed using Spss22 and Eviews8 software. Result: The results show that public health expenditures have a more effect on the labor productivity than private health expenditures, so that for 100 rials the increase in private and public health expenditures, respectively, was significantly more than 0.75 rials and 27.4 Rial increases. Conclusion: by considering that the private health expenditure has treatment aspect and public expenditure has sanitary aspect, and because the heath expenditure has high cost for some of household, government must reduce the cost of health so that increase the labor productivity
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