Calculation of the Autocorrelation Function of the Stochastic Single Machine Infinite Bus System

Critical slowing down (CSD) is the phenomenon in which a system recovers more slowly from small perturbations. CSD, as evidenced by increasing signal variance and autocorrelation, has been observed in many dynamical systems approaching a critical transition, and thus can be a useful signal of proximity to transition. In this paper, we derive autocorrelation functions for the state variables of a stochastic single machine infinite bus system (SMIB). The results show that both autocorrelation and variance increase as this system approaches a saddle-node bifurcation. The autocorrelation functions help to explain why CSD can be used as an indicator of proximity to criticality in power systems revealing, for example, how nonlinearity in the SMIB system causes these signs to appear.Comment: Accepted for publication/presentation in Proc. North American Power Symposium, 201

Particulate matter air pollution and national and county life expectancy loss in the USA: a spatiotemporal analysis

Background Exposure to fine particulate matter pollution (PM2.5) is hazardous to health. Our aim was to directly estimate the health and longevity impacts of current PM2.5 concentrations, and the benefits of reductions from 1999 to 2015, nationally and at county level, for the entire contemporary population of the contiguous United States. Methods and findings We used vital registration and population data with information on sex, age, cause of death and county of residence. We used four Bayesian spatio-temporal models, with different adjustments for other determinants of mortality, to directly estimate mortality and life expectancy loss due to current PM2.5 pollution, and the benefits of reductions since 1999, nationally and by county. The covariates included in the adjusted models were per capita income; percentage of population whose family income is below the poverty threshold, who are of Black or African American race, who have graduated from high-school, who live in urban areas, and who are unemployed; cumulative smoking; and mean temperature and relative humidity. In the main model, which adjusted for these covariates and for unobserved county characteristics through the use of county random intercepts, PM2.5 pollution in excess of the lowest observed concentration (2.8 µg/m3) was responsible for an estimated 15,612 deaths (95% credible interval 13,248-17,945) in females and in 14,757 deaths (12,617-16,919) for males. These deaths would lower national life expectancy by an estimated 0.15 years (0.13-0.17) for women and 0.13 years (0.11-0.15) for men. The life expectancy loss due to PM2.5 was largest around Los Angeles and in some southern states, such as Arkansas, Oklahoma or Alabama. At any PM2.5 concentration, life expectancy loss was, on average, larger in counties with lower income than in wealthier counties. Reductions in PM2.5 since 1999 have lowered mortality in all but 14 counties where PM2.5 increased slightly. The main limitation of our study, similar to other observational studies, is that it is not guaranteed for the observed associations to be causal. We did not have annual county-level data on other important determinants of mortality, such as healthcare access and quality and diet, but these factors were adjusted for with use of county random intercepts. Conclusions According to our estimates, recent reductions in particulate matter pollution in the USA have resulted in public health benefits. Nonetheless, we estimate that current concentrations are associated with mortality impacts and loss of life expectancy, with larger impacts in counties with lower income and higher poverty rate

Potential Impact of Time Trend of Life-Style Factors on Cardiovascular Disease Burden in China

Cardiovascular disease (CVD) is a leading cause of death in China. Evaluation of risk factors and their impacts on disease burden is important for future public health initiatives and policy making

Impact of KOH etching on nanostructure fabricated by local anodic oxidation method

In this letter, we investigate the impact of potassium hydroxide (KOH) etching procedure on Silicon nanostructure fabricated by Atomic force microscopy on P-type Silicon-on-insulator. An electrochemical process, as the local anodic oxidation followed by two wet chemical etching steps, KOH etching for silicon removal and hydrofluoric etching for oxide removal, were implemented to fabricate the silicon nanostructures. The effect of the pure KOH concentrations (10% to 30% wt) on the quality of the surface is studied. The influence of etching immersing time in etching of nanostructure and SOI surface are considered as well. Impact of different KOH concentrations mixed with 10% IPA with reaction temperature on etch rate is investigated. The KOH etching process is elaborately optimized by 30%wt. KOH + 10%vol. IPA in appropriate time and temperature. The angle of the walls in etch pit for extracted nanowire reveals some deviation from the standard anisotropic etching

Global variation in diabetes diagnosis and prevalence based on fasting glucose and hemoglobin A1c

Fasting plasma glucose (FPG) and hemoglobin A1c (HbA1c) are both used to diagnose diabetes, but these measurements can identify different people as having diabetes. We used data from 117 population-based studies and quantified, in different world regions, the prevalence of diagnosed diabetes, and whether those who were previously undiagnosed and detected as having diabetes in survey screening, had elevated FPG, HbA1c or both. We developed prediction equations for estimating the probability that a person without previously diagnosed diabetes, and at a specific level of FPG, had elevated HbA1c, and vice versa. The age-standardized proportion of diabetes that was previously undiagnosed and detected in survey screening ranged from 30% in the high-income western region to 66% in south Asia. Among those with screen-detected diabetes with either test, the age-standardized proportion who had elevated levels of both FPG and HbA1c was 29–39% across regions; the remainder had discordant elevation of FPG or HbA1c. In most low- and middle-income regions, isolated elevated HbA1c was more common than isolated elevated FPG. In these regions, the use of FPG alone may delay diabetes diagnosis and underestimate diabetes prevalence. Our prediction equations help allocate finite resources for measuring HbA1c to reduce the global shortfall in diabetes diagnosis and surveillance

Type 3c (pancreatogenic) diabetes mellitus secondary to chronic pancreatitis and pancreatic cancer

Diabetes mellitus is a group of diseases defined by persistent hyperglycaemia. Type 2 diabetes, the most prevalent form, is characterised initially by impaired insulin sensitivity and subsequently by an inadequate compensatory insulin response. Diabetes can also develop as a direct consequence of other diseases, including diseases of the exocrine pancreas. Historically, diabetes due to diseases of the exocrine pancreas was described as pancreatogenic or pancreatogenous diabetes mellitus, but recent literature refers to it as type 3c diabetes. It is important to note that type 3c diabetes is not a single entity; it occurs because of a variety of exocrine pancreatic diseases with varying mechanisms of hyperglycaemia. The most commonly identified causes of type 3c diabetes are chronic pancreatitis, pancreatic ductal adenocarcinoma, haemochromatosis, cystic fibrosis, and previous pancreatic surgery. In this Review, we discuss the epidemiology, pathogenesis, and clinical relevance of type 3c diabetes secondary to chronic pancreatitis and pancreatic ductal adenocarcinoma, and highlight several important knowledge gaps