Lorentz invariance of entanglement classes in multipartite systems

We analyze multipartite entanglement in systems of spin-1/2 particles from a relativistic perspective. General conditions which have to be met for any classification of multipartite entanglement to be Lorentz invariant are derived, which contributes to a physical understanding of entanglement classification. We show that quantum information in a relativistic setting requires the partition of the Hilbert space into particles to be taken seriously. Furthermore, we study exemplary cases and show how the spin and momentum entanglement transforms relativistically in a multipartite setting.Comment: v2: 5 pages, 4 figures, minor changes to main body, journal references update

Thermo-visual feature fusion for object tracking using multiple spatiogram trackers

In this paper, we propose a framework that can efficiently combine features for robust tracking based on fusing the outputs of multiple spatiogram trackers. This is achieved without the exponential increase in storage and processing that other multimodal tracking approaches suffer from. The framework allows the features to be split arbitrarily between the trackers, as well as providing the flexibility to add, remove or dynamically weight features. We derive a mean-shift type algorithm for the framework that allows efficient object tracking with very low computational overhead. We especially target the fusion of thermal infrared and visible spectrum features as the most useful features for automated surveillance applications. Results are shown on multimodal video sequences clearly illustrating the benefits of combining multiple features using our framework

Within- and Between-Child Variation in Repeated Urinary Pesticide Metabolite Measurements over a 1-Year Period

Background: Children are exposed to pesticides from many sources and routes, including dietary and incidental ingestion, dermal absorption, and inhalation. Linking health outcomes to these exposures using urinary metabolites requires understanding temporal variability within subjects to avoid exposure misclassification. Objectives: We characterized the within- and between-child variability of urinary organophosphorus and pyrethroid metabolites in 23 participants of the Children’s Pesticide Exposure Study–Washington over 1 year and examined the ability of one to four spot urine samples to categorize mean exposures. Methods: Each child provided urine samples twice daily over 7- to 16-day sessions in four seasons in 2003 and 2004. Samples were analyzed for five pyrethroid and five organophosphorus (OP) metabolites. After adjusting for specific gravity, we used a customized maximum likelihood estimation linear mixed-effects model that accounted for values below the limit of detection to calculate intraclass correlation coefficients (ICC) and conducted surrogate category analyses. Results: Within-child variability was 2–11 times greater than between-child variability. When restricted to samples collected during a single season, ICCs were higher in the fall, winter, and spring than in summer for OPs, and higher in summer and winter for pyrethroids, indicating an increase in between-person variability relative to within-person variability during these seasons. Surrogate category analyses demonstrated that a single spot urine sample did not categorize metabolite concentrations well, and that four or more samples would be needed to categorize children into quartiles consistently. Conclusions: Urinary biomarkers of these short half-life pesticides exhibited substantial within-person variability in children observed over four seasons. Researchers investigating pesticides and health outcomes in children may need repeated biomarker measurements to derive accurate estimates of exposure and relative risks. Citation: Attfield KR, Hughes MD, Spengler JD, Lu C. 2014. Within- and between-child variation in repeated urinary pesticide metabolite measurements over a 1-year period. Environ Health Perspect 122:201–206; http://dx.doi.org/10.1289/ehp.130673

Measure of genuine multipartite entanglement with computable lower bounds

We introduce an intuitive measure of genuine multipartite entanglement which is based on the well-known concurrence. We show how lower bounds on this measure can be derived that also meet important characteristics of an entanglement measure. These lower bounds are experimentally implementable in a feasible way enabling quantification of multipartite entanglement in a broad variety of cases.Comment: 5 pages, 2 figure

Chemical Characterization and Source Apportionment of Household Fine Particulate Matter in Rural, Peri-urban, and Urban West Africa

Household air pollution in sub-Saharan Africa and other developing regions is an important cause of disease burden. Little is known about the chemical composition and sources of household air pollution in sub-Saharan Africa, and how they differ between rural and urban homes. We analyzed the chemical composition and sources of fine particles (PM2.5) in household cooking areas of multiple neighborhoods in Accra, Ghana, and in peri-urban (Banjul) and rural (Basse) areas in The Gambia. In Accra, biomass burning accounted for 39–62% of total PM2.5 mass in the cooking area in different neighborhoods; the absolute contributions were 10–45 μg/m3. Road dust and vehicle emissions comprised 12–33% of PM2.5 mass. Solid waste burning was also a significant contributor to household PM2.5 in a low-income neighborhood but not for those living in better-off areas. In Banjul and Basse, biomass burning was the single dominant source of cooking-area PM2.5, accounting for 74–87% of its total mass; the relative and absolute contributions of biomass smoke to PM2.5 mass were larger in households that used firewood than in those using charcoal, reaching as high as 463 μg/m3 in Basse homes that used firewood for cooking. Our findings demonstrate the need for policies that enhance access to cleaner fuels in both rural and urban areas, and for controlling traffic emissions in cities in sub-Saharan Africa

Social stressors and air pollution across New York City communities: a spatial approach for assessing correlations among multiple exposures

Background: Recent toxicological and epidemiological evidence suggests that chronic psychosocial stress may modify pollution effects on health. Thus, there is increasing interest in refined methods for assessing and incorporating non-chemical exposures, including social stressors, into environmental health research, towards identifying whether and how psychosocial stress interacts with chemical exposures to influence health and health disparities. We present a flexible, GIS-based approach for examining spatial patterns within and among a range of social stressors, and their spatial relationships with air pollution, across New York City, towards understanding their combined effects on health. Methods: We identified a wide suite of administrative indicators of community-level social stressors (2008–2010), and applied simultaneous autoregressive models and factor analysis to characterize spatial correlations among social stressors, and between social stressors and air pollutants, using New York City Community Air Survey (NYCCAS) data (2008-2009). Finally, we provide an exploratory ecologic analysis evaluating possible modification of the relationship between nitrogen dioxide (NO2) and childhood asthma Emergency Department (ED) visit rates by social stressors, to demonstrate how the methods used to assess stressor exposure (and/or consequent psychosocial stress) may alter model results. Results: Administrative indicators of a range of social stressors (e.g., high crime rate, residential crowding rate) were not consistently correlated (rho = - 0.44 to 0.89), nor were they consistently correlated with indicators of socioeconomic position (rho = - 0.54 to 0.89). Factor analysis using 26 stressor indicators suggested geographically distinct patterns of social stressors, characterized by three factors: violent crime and physical disorder, crowding and poor access to resources, and noise disruption and property crimes. In an exploratory ecologic analysis, these factors were differentially associated with area-average NO2 and childhood asthma ED visits. For example, only the ‘violent crime and disorder’ factor was significantly associated with asthma ED visits, and only the ‘crowding and resource access’ factor modified the association between area-level NO2 and asthma ED visits. Conclusions: This spatial approach enabled quantification of complex spatial patterning and confounding between chemical and non-chemical exposures, and can inform study design for epidemiological studies of separate and combined effects of multiple urban exposures. Electronic supplementary material The online version of this article (doi:10.1186/1476-069X-13-91) contains supplementary material, which is available to authorized users

Nitrogen dioxide concentrations in neighborhoods adjacent to a commercial airport: a land use regression modeling study

BACKGROUND: There is growing concern in communities surrounding airports regarding the contribution of various emission sources (such as aircraft and ground support equipment) to nearby ambient concentrations. We used extensive monitoring of nitrogen dioxide (NO(2)) in neighborhoods surrounding T.F. Green Airport in Warwick, RI, and land-use regression (LUR) modeling techniques to determine the impact of proximity to the airport and local traffic on these concentrations. METHODS: Palmes diffusion tube samplers were deployed along the airport's fence line and within surrounding neighborhoods for one to two weeks. In total, 644 measurements were collected over three sampling campaigns (October 2007, March 2008 and June 2008) and each sampling location was geocoded. GIS-based variables were created as proxies for local traffic and airport activity. A forward stepwise regression methodology was employed to create general linear models (GLMs) of NO(2 )variability near the airport. The effect of local meteorology on associations with GIS-based variables was also explored. RESULTS: Higher concentrations of NO(2 )were seen near the airport terminal, entrance roads to the terminal, and near major roads, with qualitatively consistent spatial patterns between seasons. In our final multivariate model (R(2 )= 0.32), the local influences of highways and arterial/collector roads were statistically significant, as were local traffic density and distance to the airport terminal (all p < 0.001). Local meteorology did not significantly affect associations with principal GIS variables, and the regression model structure was robust to various model-building approaches. CONCLUSION: Our study has shown that there are clear local variations in NO(2 )in the neighborhoods that surround an urban airport, which are spatially consistent across seasons. LUR modeling demonstrated a strong influence of local traffic, except the smallest roads that predominate in residential areas, as well as proximity to the airport terminal

Reducing patients’ exposures to asthma and allergy triggers in their homes: an evaluation of effectiveness of grades of forced air ventilation filters

Objective: Many interventions to reduce allergen levels in the home are recommended to asthma and allergy patients. One that is readily available and can be highly effective is the use of high performing filters in forced air ventilation systems. Methods: We conducted a modeling analysis of the effectiveness of filter-based interventions in the home to reduce airborne asthma and allergy triggers. This work used “each pass removal efficiency” applied to health-relevant size fractions of particles to assess filter performance. We assessed effectiveness for key allergy and asthma triggers based on applicable particle sizes for cat allergen, indoor and outdoor sources of particles 70% for cat dander particles, fine particulate matter (PM2.5) and respiratory virus can lower concentrations of those asthma triggers and allergens in indoor air of the home by >50%. Very high removal efficiency filters, such as those rated a 16 on the nationally recognized Minimum Efficiency Removal Value (MERV) rating system, tend to be only marginally more effective than MERV12 or 13 rated filters. Conclusions: The results of this analysis indicate that use of a MERV12 or higher performing air filter in home ventilation systems can effectively reduce indoor levels of these common asthma and allergy triggers. These reductions in airborne allergens in turn may help reduce allergy and asthma symptoms, especially if employed in conjunction with other environmental management measures recommended for allergy and asthma patients

Heisenberg's Uncertainty Relation and Bell Inequalities in High Energy Physics

An effective formalism is developed to handle decaying two-state systems. Herewith, observables of such systems can be described by a single operator in the Heisenberg picture. This allows for using the usual framework in quantum information theory and, hence, to enlighten the quantum feature of such systems compared to non-decaying systems. We apply it to systems in high energy physics, i.e. to oscillating meson-antimeson systems. In particular, we discuss the entropic Heisenberg uncertainty relation for observables measured at different times at accelerator facilities including the effect of CP violation, i.e. the imbalance of matter and antimatter. An operator-form of Bell inequalities for systems in high energy physics is presented, i.e. a Bell-witness operator, which allows for simple analysis of unstable systems.Comment: 17 page