Neighborhood Cohesion, Neighborhood Disorder, and Cardiometabolic Risk

Perceptions of neighborhood disorder (trash, vandalism) and cohesion (neighbors trust one another) are related to residents’ health. Affective and behavioral factors have been identified, but often in studies using geographically select samples. We use a nationally representative sample (n = 9032) of United States older adults from the Health and Retirement Study to examine cardiometabolic risk in relation to perceptions of neighborhood cohesion and disorder. Lower cohesion is significantly related to greater cardiometabolic risk in 2006/2008 and predicts greater risk four years later (2010/2012). The longitudinal relation is partially accounted for by anxiety and physical activity

Neighborhood Socioeconomic Status and Health: A Longitudinal Analysis

Higher income neighborhoods are associated with better health, a relation observed in many cross-sectional studies. However, prior research focused on the prevalence of health conditions, and examining the incidence of new health conditions may provide stronger support for a potential causal role of neighborhoods on health. We used the 2004 and 2014 waves of the Midlife in the United States Study (n = 1726; ages 34–83) to examine health condition incidence as a function of neighborhood income. Among participants who had lived in the same neighborhood across the time period, we hypothesized that higher neighborhood income would be associated with a lower incidence of health conditions ten years later. Health included 18 chronic conditions related to mental (anxiety, depression) and physical (cardiovascular, immune) health. Multinomial logistic regression analyses adjusting for individual income and sociodemographics indicated that the odds of developing two or more new health conditions (no new health conditions as referent), was significantly lower (OR = 0.92, CI: 0.86, 0.99) for every $10,000 increment in neighborhood income. Associations did not vary by age or neighborhood tenure. Results add to a literature documenting that higher neighborhood income is associated with better health

CASTNet: Community-Attentive Spatio-Temporal Networks for Opioid Overdose Forecasting

Opioid overdose is a growing public health crisis in the United States. This crisis, recognized as "opioid epidemic," has widespread societal consequences including the degradation of health, and the increase in crime rates and family problems. To improve the overdose surveillance and to identify the areas in need of prevention effort, in this work, we focus on forecasting opioid overdose using real-time crime dynamics. Previous work identified various types of links between opioid use and criminal activities, such as financial motives and common causes. Motivated by these observations, we propose a novel spatio-temporal predictive model for opioid overdose forecasting by leveraging the spatio-temporal patterns of crime incidents. Our proposed model incorporates multi-head attentional networks to learn different representation subspaces of features. Such deep learning architecture, called "community-attentive" networks, allows the prediction of a given location to be optimized by a mixture of groups (i.e., communities) of regions. In addition, our proposed model allows for interpreting what features, from what communities, have more contributions to predicting local incidents as well as how these communities are captured through forecasting. Our results on two real-world overdose datasets indicate that our model achieves superior forecasting performance and provides meaningful interpretations in terms of spatio-temporal relationships between the dynamics of crime and that of opioid overdose.Comment: Accepted as conference paper at ECML-PKDD 201

Neighborhood Features and Physiological Risk: An Examination of Allostatic Load

Poor neighborhoods may represent a situation of chronic stress, and may therefore be associated with health-related correlates of stress. We examined whether lower neighborhood income would relate to higher allostatic load, or physiological well-being, through psychological, affective, and behavioral pathways. Using data from the Biomarker Project of the Midlife in the United States (MIDUS) study and the 2000 Census, we demonstrated that people living in lower income neighborhoods have higher allostatic load net of individual income. Moreover, findings indicate that this relation is partially accounted for by anxious arousal symptoms, fast food consumption, smoking, and exercise habits

Elevation dependency of mountain snow depth

Elevation strongly affects quantity and distribution patterns of precipitation and snow. Positive elevation gradients were identified by many studies, usually based on data from sparse precipitation stations or snow depth measurements. We present a systematic evaluation of the elevation snow depth relationship. We analyse areal snow depth data obtained by remote sensing for seven mountain sites near to the time of the maximum seasonal snow accumulation. Snow depths were averaged to 100 m elevation bands and then related to their respective elevation level. The assessment was performed at three scales: (i) the complete data sets (10 km scale), (ii) sub-catchments (km scale) and (iii) slope transects (100 m scale). We show that most elevation-snow depth curves at all scales are characterised through a single shape. Mean snow depths increase with elevation up to a certain level where they have a distinct peak followed by a decrease at the highest elevations. We explain this typical shape with a generally positive elevation gradient of snow fall that is modified by the interaction of snow cover and topography. These processes are preferential deposition of precipitation and redistribution of snow by wind, sloughing and avalanching. Furthermore, we show that the elevation level of the peak of mean snow depth correlates with the dominant elevation level of rocks (if present)

Two-Fermion Production in Electron-Positron Collisions

This report summarizes the results of the two-fermion working group of the LEP2-MC workshop, held at CERN from 1999 to 2000. Recent developments in the theoretical calculations of the two fermion production process in the electron-positron collision at LEP2 center of the mass energies are reported. The Bhabha process and the production of muon, tau, neutrino and quark pairs is covered. On the basis of comparison of various calculations, theoretical uncertainties are estimated and compared with those needed for the final LEP2 data analysis. The subjects for the further studies are identified.Comment: 2-fermion working group report of the LEP2 Monte Carlo Workshop 1999/2000, 113 pages, 24 figures, 35 table

Giant persistent photoconductivity in monolayer MoS2 field-effect transistors

Monolayer transition metal dichalcogenides (TMD) have numerous potential applications in ultrathin electronics and photonics. The exposure of TMD-based devices to light generates photo-carriers resulting in an enhanced conductivity, which can be effectively used, e.g., in photodetectors. If the photo-enhanced conductivity persists after removal of the irradiation, the effect is known as persistent photoconductivity (PPC). Here we show that ultraviolet light (λ = 365 nm) exposure induces an extremely long-living giant PPC (GPPC) in monolayer MoS2 (ML-MoS2) field-effect transistors (FET) with a time constant of ~30 days. Furthermore, this effect leads to a large enhancement of the conductivity up to a factor of 107. In contrast to previous studies in which the origin of the PPC was attributed to extrinsic reasons such as trapped charges in the substrate or adsorbates, we show that the GPPC arises mainly from the intrinsic properties of ML-MoS2 such as lattice defects that induce a large number of localized states in the forbidden gap. This finding is supported by a detailed experimental and theoretical study of the electric transport in TMD based FETs as well as by characterization of ML-MoS2 with scanning tunneling spectroscopy, high-resolution transmission electron microscopy, and photoluminescence measurements. The obtained results provide a basis for the defect-based engineering of the electronic and optical properties of TMDs for device applications

Four-Fermion Production in Electron-Positron Collisions

This report summarises the results of the four-fermion working group of the LEP2-MC workshop, held at CERN from 1999 to 2000. Recent developments in the calculation of four-fermion processes in electron-positron collisions at LEP-2 centre-of-mass energies are presented, concentrating on predictions for four main reactions: W-pair production, visible photons in four-fermion events, single-W production and Z-pair production. Based on a comparison of results derived within different approaches, theoretical uncertainties on these predictions are established.Comment: 150 pages, 73 figures, 45 table

The influence of anesthetics, neurotransmitters and antibiotics on the relaxation processes in lipid membranes

In the proximity of melting transitions of artificial and biological membranes fluctuations in enthalpy, area, volume and concentration are enhanced. This results in domain formation, changes of the elastic constants, changes in permeability and slowing down of relaxation processes. In this study we used pressure perturbation calorimetry to investigate the relaxation time scale after a jump into the melting transition regime of artificial lipid membranes. This time corresponds to the characteristic rate of domain growth. The studies were performed on single-component large unilamellar and multilamellar vesicle systems with and without the addition of small molecules such as general anesthetics, neurotransmitters and antibiotics. These drugs interact with membranes and affect melting points and profiles. In all systems we found that heat capacity and relaxation times are related to each other in a simple manner. The maximum relaxation time depends on the cooperativity of the heat capacity profile and decreases with a broadening of the transition. For this reason the influence of a drug on the time scale of domain formation processes can be understood on the basis of their influence on the heat capacity profile. This allows estimations of the time scale of domain formation processes in biological membranes.Comment: 12 pages, 6 figure