The limits of ethnic capital: impacts of social desirability on Korean views of co-ethnic immigration

A substantial body of research has found that social desirability motivates respondents to overstate support for immigration when asked directly, but when provided an unobtrusive means of expressing preferences, support declines. In this paper, we ask whether South Koreans follow this pattern, especially with regards to co-ethnic migrants from North Korea and China. We use list experiments to determine whether observed levels of support for general immigration and co-ethnic migration are biased by social desirability. We find that generally respondents overstate their support for co-ethnics from North Korea by a significant amount when asked directly, but not for the other groups, although college-educated respondents overstate their support for general immigration. Social desirability bias with respect to co-ethnics from North Korea is particularly evident in older respondents and males. These findings challenge the notion that native-born citizens prefer co-ethnic immigrants.Asian Studie

한국인의 통일방식에 대한 숨겨진 선호: 선택형 컨조인트 분석(Choice-based Conjoint Analysis) 결과를 중심으로

본고는 통일의식 연구에서 그동안 활용되지않았던 컨조인트 분석(conjoint analysis)을통해 한국 국민의 통일방식을 더 세부적이고정밀하게 측정하는 데 목적을 둔다. 통일의식을 측정하는 기존 연구 방법론은 직접 단답형다항 선택식 문항으로 통일의 필요성, 시기, 통일관, 통일한반도의 정치체제 등 최종 체제에 관한 질문으로 측정해왔다. 그런데 각 변수 내 선택지에 대한 선호 혹은 비선호의 강도를 측정할 수 없었기에 어느 조건이 더 중요하게 여겨지는지 알 수 없었다. 따라서 기존 조사 결과를 활용한 복합적 정책 설계는 한계가존재한다. 본 연구는 컨조인트 분석이라는 실험적 조사설계를 활용하여 통일 후의 정치체제, 북한 지도부 정리, 노동당 당원 정리, 남한기업의 북한 경제참여, 북한 지역 군대 주둔문제 등 여러 차원의 속성수준으로 설문지를구성하여 실제 선호도를 도출하고자 한다. 연구 결과는 연합제보다 단일민주 정부에 대한선호, 노동당 당원에 대한 민감한 직위의 배제와 지도부의 기소 등 여러 차원에서 강한 선호가 나타났다. 본 연구는 한국 국민의 통일방안에 대한 구체적인 선호를 보여줌으로써, 통일이 갑작스럽게 이루어질 경우, 통일에 대한 정책설계를 위한 유익한 자료를 제공할 것으로 기대된다.Asian Studie

Epigenetic predictors of all-cause mortality are associated with objective measures of neighborhood disadvantage in an urban population

BACKGROUND: Neighborhood characteristics are robust predictors of overall health and mortality risk for residents. Though there has been some investigation of the role that molecular indicators may play in mediating neighborhood exposures, there has been little effort to incorporate newly developed epigenetic biomarkers into our understanding of neighborhood characteristics and health outcomes. METHODS: Using 157 participants of the Detroit Neighborhood Health Study with detailed assessments of neighborhood characteristics and genome-wide DNA methylation profiling via the Illumina 450K methylation array, we assessed the relationship between objective neighborhood characteristics and a validated DNA methylation-based epigenetic mortality risk score (eMRS). Associations were adjusted for age, race, sex, ever smoking, ever alcohol usage, education, years spent in neighborhood, and employment. A secondary model additionally adjusted for personal neighborhood perception. We summarized 19 neighborhood quality indicators assessed for participants into 9 principal components which explained over 90% of the variance in the data and served as metrics of objective neighborhood quality exposures. RESULTS: Of the nine principal components utilized for this study, one was strongly associated with the eMRS (β = 0.15; 95% confidence interval = 0.06-0.24; P = 0.002). This principal component (PC7) was most strongly driven by the presence of abandoned cars, poor streets, and non-art graffiti. Models including both PC7 and individual indicators of neighborhood perception indicated that only PC7 and not neighborhood perception impacted the eMRS. When stratified on neighborhood indicators of greenspace, we observed a potentially protective effect of large mature trees as this feature substantially attenuated the observed association. CONCLUSION: Objective measures of neighborhood disadvantage are significantly associated with an epigenetic predictor of mortality risk, presenting a potential novel avenue by which neighborhood-level exposures may impact health. Associations were independent of an individual's perception of their neighborhood and attenuated by neighborhood greenspace features. More work should be done to determine molecular risk factors associated with neighborhoods, and potentially protective neighborhood features against adverse molecular effects

Pediatric sleep-related breathing disorders: advances in imaging and computational modeling

We understand now that sleep of sufficient length and quality is required for good health. This is particularly true for infants and children, who have the added physiologic task of growth and development, as compared to their adult counterparts. Sleep-related breathing disorders (SRBDs) are common in childhood and if unrecognized and not treated can result in significant morbidity. For example, children with obstructive sleep apnea (OSA) can exhibit behavioral, mood, and learning difficulties. If left untreated, alterations in the function of the autonomic nervous system and a chronic inflammatory state result, contributing to the risk of heart disease, stroke, glucose intolerance, and hypertension in adulthood

Measurements of Scintillation Efficiency and Pulse-Shape for Low Energy Recoils in Liquid Xenon

Results of observations of low energy nuclear and electron recoil events in liquid xenon scintillator detectors are given. The relative scintillation efficiency for nuclear recoils is 0.22 +/- 0.01 in the recoil energy range 40 keV - 70 keV. Under the assumption of a single dominant decay component to the scintillation pulse-shape the log-normal mean parameter T0 of the maximum likelihood estimator of the decay time constant for 6 keV < Eee < 30 keV nuclear recoil events is equal to 21.0 ns +/- 0.5 ns. It is observed that for electron recoils T0 rises slowly with energy, having a value ~ 30 ns at Eee ~ 15 keV. Electron and nuclear recoil pulse-shapes are found to be well fitted by single exponential functions although some evidence is found for a double exponential form for the nuclear recoil pulse-shape.Comment: 11 pages, including 5 encapsulated postscript figure

Associations between long-term fine particulate matter exposure and hospital procedures in heart failure patients

Background Ambient fine particulate matter (PM2.5) contributes to global morbidity and mortality. One way to understand the health effects of PM2.5 is by examining its impact on performed hospital procedures, particularly among those with existing chronic disease. However, such studies are rare. Here, we investigated the associations between annual average PM2.5 and hospital procedures among individuals with heart failure. Methods Using electronic health records from the University of North Carolina Healthcare System, we created a retrospective cohort of 15,979 heart failure patients who had at least one of 53 common (frequency > 10%) procedures. We used daily modeled PM2.5 at 1x1 km resolution to estimate the annual average PM2.5 at the time of heart failure diagnosis. We used quasi- Poisson models to estimate associations between PM2.5 and the number of performed hospital procedures over the follow-up period (12/31/2016 or date of death) while adjusting for age at heart failure diagnosis, race, sex, year of visit, and socioeconomic status. Results A 1 μg/m3 increase in annual average PM2.5 was associated with increased glycosylated hemoglobin tests (10.8%; 95% confidence interval = 6.56%, 15.1%), prothrombin time tests (15.8%; 95% confidence interval = 9.07%, 22.9%), and stress tests (6.84%; 95% confidence interval = 3.65%, 10.1%). Results were stable under multiple sensitivity analyses. Conclusions These results suggest that long-term PM2.5 exposure is associated with an increased need for diagnostic testing on heart failure patients. Overall, these associations give a unique lens into patient morbidity and potential drivers of healthcare costs linked to PM2.5 exposure

Multidimensional endotyping in patients with severe asthma reveals inflammatory heterogeneity in matrix metalloproteinases and chitinase 3–like protein 1

BackgroundDisease heterogeneity in patients with severe asthma and its relationship to inflammatory mechanisms remain poorly understood.ObjectiveWe aimed to identify and replicate clinicopathologic endotypes based on analysis of blood and sputum parameters in asthmatic patients.MethodsOne hundred ninety-four asthmatic patients and 21 control subjects recruited from 2 separate centers underwent detailed clinical assessment, sputum induction, and phlebotomy. One hundred three clinical, physiologic, and inflammatory parameters were analyzed by using topological data analysis and Bayesian network analysis.ResultsSevere asthma was associated with anxiety and depression, obesity, sinonasal symptoms, decreased quality of life, and inflammatory changes, including increased sputum chitinase 3–like protein 1 (YKL-40) and matrix metalloproteinase (MMP) 1, 3, 8, and 12 levels. Topological data analysis identified 6 clinicopathobiologic clusters replicated in both geographic cohorts: young, mild paucigranulocytic; older, sinonasal disease; obese, high MMP levels; steroid resistant TH2 mediated, eosinophilic; mixed granulocytic with severe obstruction; and neutrophilic, low periostin levels, severe obstruction. Sputum IL-5 levels were increased in patients with severe particularly eosinophilic forms, whereas IL-13 was suppressed and IL-17 levels did not differ between clusters. Bayesian network analysis separated clinical features from intricately connected inflammatory pathways. YKL-40 levels strongly correlated with neutrophilic asthma and levels of myeloperoxidase, IL-8, IL-6, and IL-6 soluble receptor. MMP1, MMP3, MMP8, and MMP12 levels were associated with severe asthma and were correlated positively with sputum IL-5 levels but negatively with IL-13 levels.ConclusionIn 2 distinct cohorts we have identified and replicated 6 clinicopathobiologic clusters based on blood and induced sputum measures. Our data underline a disconnect between clinical features and underlying inflammation, suggest IL-5 production is relatively steroid insensitive, and highlight the expression of YKL-40 in patients with neutrophilic inflammation and the expression of MMPs in patients with severe asthma

Neighborhood environment, social cohesion, and epigenetic aging

Living in adverse neighborhood environments has been linked to risk of aging-related diseases and mortality; however, the biological mechanisms explaining this observation remain poorly understood. DNA methylation (DNAm), a proposed mechanism and biomarker of biological aging responsive to environmental stressors, offers promising insight into potential molecular pathways. We examined associations between three neighborhood social environment measures (poverty, quality, and social cohesion) and three epigenetic clocks (Horvath, Hannum, and PhenoAge) using data from the Detroit Neighborhood Health Study (n=158). Using linear regression models, we evaluated associations in the total sample and stratified by sex and social cohesion. Neighborhood quality was associated with accelerated DNAm aging for Horvath age acceleration (β = 1.8; 95% CI: 0.4, 3.1), Hannum age acceleration (β = 1.7; 95% CI: 0.4, 3.0), and PhenoAge acceleration (0 = 2.1; 95% CI: 0.4, 3.8). In models stratified on social cohesion, associations of neighborhood poverty and quality with accelerated DNAm aging remained elevated for residents living in neighborhoods with lower social cohesion, but were null for those living in neighborhoods with higher social cohesion. Our study suggests that living in adverse neighborhood environments can speed up epigenetic aging, while positive neighborhood attributes may buffer effects

Filtering and Tracking with Trinion-Valued Adaptive Algorithms

A new model for three-dimensional processes based on the trinion algebra is introduced for the first time. Compared with the pure quaternion model, the trinion model is more compact and computationally more efficient, while having similar or comparable performance in terms of adaptive linear filtering. Moreover, the trinion model can effectively represent the general relationship of state evolution in Kalman filtering, where the pure quaternion model fails. Simulations on real-world wind recordings and synthetic data sets are provided to demonstrate the potentials of this new modeling method