Estimating daily nitrogen dioxide level: Exploring traffic effects

Data used to assess acute health effects from air pollution typically have good temporal but poor spatial resolution or the opposite. A modified longitudinal model was developed that sought to improve resolution in both domains by bringing together data from three sources to estimate daily levels of nitrogen dioxide ($\mathrm {NO}_2$) at a geographic location. Monthly $\mathrm {NO}_2$ measurements at 316 sites were made available by the Study of Traffic, Air quality and Respiratory health (STAR). Four US Environmental Protection Agency monitoring stations have hourly measurements of $\mathrm {NO}_2$. Finally, the Connecticut Department of Transportation provides data on traffic density on major roadways, a primary contributor to $\mathrm {NO}_2$ pollution. Inclusion of a traffic variable improved performance of the model, and it provides a method for estimating exposure at points that do not have direct measurements of the outcome. This approach can be used to estimate daily variation in levels of $\mathrm {NO}_2$ over a region.Comment: Published in at http://dx.doi.org/10.1214/13-AOAS642 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Clinical application of Kirschner wires combined with 5-Ethibond fixation for patella fractures

BackgroundPatella fractures that require surgery are conventionally treated using Kirschner wires (K-wires) and stainless steel wires. In recent years, the nonabsorbable polyester has been reported to have excellent outcomes clinically. Therefore, the goal of our study was to evaluate the effects of Kirschner wires combined with 5-Ethibond on treating patellar fractures.MethodsFrom July 2018 to January 2022, 22 patella fracture patients were treated with Kirschner wires combined with 5-Ethibond. Radiographs of the knees were used to evaluate fracture healing and hardware complications. The clinical results were evaluated through the functional score, knee joint range of motion (ROM), and Bostman patella fracture functional score.ResultsThe average age of patients was 57.4 ± 11.9 (range 33–74) years. The mean follow-up time was 15.2 ± 7.6 (range 4–36) months. The mean operation time was 56.8 ± 8.7 (range 45–80) min. The entire patients had bony union at an average of 10.5 ± 1.9 (range 8–14) weeks. At the final follow-up, the mean range of postoperative ROM was 123.4° ± 14.6° (range 95°–140°), and the functional score was 28.7 ± 1.2 (range 26–30) points. No patient exhibited internal fixation failure, and no symptomatic implants or skin complications were recorded.ConclusionsThe fixation approach using K-wires combined with 5-Ethibond has a lower complication rate and delivers superior clinical results. This research reveals that such technology is a safe and prospective substitute for conventional metal fixation approaches

Optimization strategy of community planning for environmental health and public health in smart city under multi-objectives

As population density increases, environmental hygiene and public health become increasingly severe. As the space where residents stay for the longest time and have the most profound impact on their physical and mental health, the quality of the environment in urban communities largely determines the degree to which residents engage in physical activity, bear the risk of pollution exposure, and obtain healthy food. Therefore, in order to ensure the physical and mental health of residents, this study proposes community planning guided by environmental hygiene and public health, and establishes an environmental health assessment system for this purpose. This system evaluates the community environment from four aspects: land use, service facilities, site convenience, and environmental quality. Established the diversity, density, road network connectivity and facilities accessibility nine criteria, as well as the land function of mix, plot ratio, food environment, network ring α and connected β index, pavement risk level, green configuration and neighborhood material environment disorder degree of 27 indicators of community built environmental evaluation index system. The data is collected through field survey, questionnaire distribution, resident interview and data mapping, and the established evaluation index system is used to evaluate the construction environment of the community. The experimental research data included population data, CAD plan, land use data, street data, POI point data, building data and bus station data, etc. 273 questionnaires were distributed, 264 were recovered, 8 invalid questionnaires were removed, and 256 valid questionnaires were obtained. These experiments confirm that land use, service facilities, site convenience, and environmental quality have a significant impact on the built environment of communities, with impact weights of 0.513, 0.227, 0.135, and 0.125, respectively. The above weights are calculated based on the index judgment matrix and the eigenvectors. The scores of land use, service facilities, site convenience, and environmental quality for the study subjects were 3.44, 1.46, 0.94, and 0.51, respectively, among them, the land use score is less than 3.85, the 1 service facility score is less than 1.71, the site convenience score is less than 1.01, and the environmental quality score is less than 0.94; indicating that the community has serious problems such as single land use types, pollution exposure, and difficulty in obtaining healthy food. Therefore, community planning and transformation based on land use, service facilities, venue convenience, and environmental quality can effectively improve the physical and mental health of residents. In the specific community transformation plan, artificial intelligence and data-driven methods can be used to optimize the land use plan, service facility configuration, site convenience transformation and environmental quality improvement, so as to formulate the optimal community transformation plan and improve the comfort and happiness of community residents. In the future, on the basis of the existing research, the selection of community types will be further enriched and the research cases will be expanded. And through the in-depth practical study of the case, the constructed evaluation index system is optimized and improved to make it more scientific. At the same time, as urban renewal and design have entered the era of stock planning, based on the more perfect evaluation index system, more specific and detailed system discussion of the built communities with public health problems, in order to provide more detailed services for the construction of a better and healthy living environment in the future

The cellular source for APOBEC3G's incorporation into HIV-1

<p>Abstract</p> <p>Background</p> <p>Human APOBEC3G (hA3G) has been identified as a cellular inhibitor of HIV-1 infectivity. Viral incorporation of hA3G is an essential step for its antiviral activity. Although the mechanism underlying hA3G virion encapsidation has been investigated extensively, the cellular source of viral hA3G remains unclear.</p> <p>Results</p> <p>Previous studies have shown that hA3G forms low-molecular-mass (LMM) and high-molecular-mass (HMM) complexes. Our work herein provides evidence that the majority of newly-synthesized hA3G interacts with membrane lipid raft domains to form Lipid raft-associated hA3G (RA hA3G), which serve as the precursor of the mature HMM hA3G complex, while a minority of newly-synthesized hA3G remains in the cytoplasm as a soluble LMM form. The distribution of hA3G among the soluble LMM form, the RA LMM form and the mature forms of HMM is regulated by a mechanism involving the N-terminal part of the linker region and the C-terminus of hA3G. Mutagenesis studies reveal a direct correlation between the ability of hA3G to form the RA LMM complex and its viral incorporation.</p> <p>Conclusions</p> <p>Together these data suggest that the Lipid raft-associated LMM A3G complex functions as the cellular source of viral hA3G.</p

Evolutionary analysis of mitochondrially encoded proteins of toad-headed lizards, Phrynocephalus, along an altitudinal gradient.

BACKGROUND: Animals living at high altitude must adapt to environments with hypoxia and low temperatures, but relatively little is known about underlying genetic changes. Toad-headed lizards of the genus Phrynocephalus cover a broad altitudinal gradient of over 4000 m and are useful models for studies of such adaptive responses. In one of the first studies to have considered selection on mitochondrial protein-coding regions in an ectothermic group distributed over such a wide range of environments, we analysed nineteen complete mitochondrial genomes from all Chinese Phrynocephalus (including eight genomes sequenced for the first time). Initial analyses used site and branch-site model (program: PAML) approaches to examine nonsynonymous: synonymous substitution rates across the mtDNA tree. RESULTS: Ten positively selected sites were discovered, nine of which corresponded to subunits ND2, ND3, ND4, ND5, and ND6 within the respiratory chain enzyme mitochondrial Complex I (NADH Coenzyme Q oxidoreductase). Four of these sites showed evidence of general long-term selection across the group while the remainder showed evidence of episodic selection across different branches of the tree. Some of these branches corresponded to increases in altitude and/or latitude. Analyses of physicochemical changes in protein structures revealed that residue changes at sites that were under selection corresponded to major functional differences. Analyses of coevolution point to coevolution of selected sites within the ND4 subunit, with key sites associated with proton translocation across the mitochondrial membrane. CONCLUSIONS: Our results identify mitochondrial Complex I as a target for environment-mediated selection in this group of lizards, a complex that frequently appears to be under selection in other organisms. This makes these lizards good candidates for more detailed future studies of molecular evolution

A Bayesian Spatio–Temporal Model for Estimating Daily Nitrogen Dioxide Levels

A Bayesian spatio-temporal model for estimating daily nitrogen dioxide (NO2) levels is described. The model uses two datasets with different temporal resolutions. The dataset from the Study of Traffic, Air quality and Respiratory health in children (STAR) contains NO2 measurements at a relatively large number of sites (most of which are in the state of Connecticut) but for one month in each season over a year. The dataset from the U.S. Environmental Protection Agency (EPA) contains measurements on an hourly level but only at a limited number of sites (four sites in Connecticut). The modal first establishes relationship between STAR observations and EPA observations on the monthly level (the duration-level of the STAR study). The relationship is then assumed to hold at the daily level and thus daily NO 2 levels at the STAR study sites can be estimated from the average daily NO2 levels at the EPA sites. The model can also provide predictions of daily NO2 levels at random sites. The model performed well (R 2 > 0.7) and two important implications follow. First, daily pollution information as estimated by the model makes it possible to study the relationship between pollution and pollution-related symptoms such as childhood asthma severity in a more meaningful way. Second, the model offers significant cost reduction on future studies of pollution levels: the readily available pollutant information at EPA monitoring sites and the observations at some sites can be used to make predictions over a long period and at random sites. The model is implemented under the Bayes framework with a Gibbs sampler

Alpine Musk Deer (Moschus chrysogaster) Adjusts to a Human-Dominated Semi-Arid Mountain Ecosystem

Comprehension of whether human and livestock presence affects wildlife activity is a prerequisite for the planning and management of humans and livestock in protected areas. Xinglong Mountain Nature Reserve (XMNNR) in northwest China, as a green island in a semi-arid mountain ecosystem, is one of the scattered and isolated areas for Alpine musk deer (AMD), an endangered species. AMD cohabits their latent habitat area with foraging livestock and humans. Hence, habitat management within and outside the distribution areas is crucial for the effective conservation of AMD. We applied camera traps to a dataset of 2 years (September 2018&ndash;August 2020) to explore seasonal activity patterns and habitat use and assess the impacts of AMD habits in XMNNR. We investigated AMD responses to livestock grazing and human activities and provided effective strategies for AMD conservation. We applied MaxENT modeling to predict the distribution size under current conditions. The activity patterns of the AMD vary among seasons. The optimum habitat average distance to cultivated land ranges of AMD (150~3300 m during grass period/100~3200 m during withered grass period), distances to the residential area ranges (500~5700 m during the grass period/1000~5300 m during the withered grass period), elevation ranges (2350~3400 m during the grass period/2360~3170 m during the withered grass period), aspect ranges (0~50&deg; and 270~360&deg;), normalized vegetation index ranges (0.64~0.72 during the grass period/0.14~0.60 during the withered grass period), and land cover types (forest, shrub, and grassland). Results present that the predicted distributions of AMD were not confined to the areas reported but also covered other potential areas. The results provide evidence of strong spatial-temporal avoidance of AMD in livestock, but gradually adjusting to human activities. These camera trap datasets may open new opportunities for species conservation in much wider tracts, such as human-dominated landscapes, and may offer guidance and mitigate impacts from livestock, as well as increase artificial forest planting and strengthen the investigation of the potential population resources of AMD

A real-time throughput model based particle filter program generator on GPU : a real-time analysis

State estimation plays an important role in cyber-physical systems. An accurate state of the physical plant is required by the controller to compute optimal control signals that are sent to the actuators to move the physical system towards the target state. However, in most cases, states cannot be obtained from sensors directly. And for complicated physical systems, whose dynamics are high-dimensional non-linear models, particle filters are required for state estimation due to their superior quality compared to linear estimators such as Kalman filters. A major drawback of particle filters is the computational cost they incur since a large number of particles is required to produce accurate estimation results. Fortunately, the computation of particle filters can be parallelized so that it can be accelerated by graphics processing units (GPUs). One of the hindrances of utilizing GPUs as the computing engine in cyber-physical systems is the lack of real-time performance information. Due to concurrency and synchronization between different processors, real-time performance analysis for parallel architectures is challenging. This dissertation focuses on the real-time analysis of state estimators using particle filters implemented on GPUs. The goal is to compute an accurate prediction of the execution time of the state estimator according to static information of the implementation, which includes both the source code of the state estimator and the hardware specifications. To achieve its goal, this dissertation presents an analytical performance model, which takes as input the source code of the state estimator, the number of particles, and the specifications of the hardware. The analytical performance model outputs a prediction of the execution time of the state estimator. The analytical performance model is tested by a synthetic benchmark and three real-world applications. The benchmark contains synthetic GPU programs with different arithmetic intensities and parallelism. The real-world applications, Vacuum Arc Remelting, Early Kick Detection, and Monte Carlo Localization, apply particle filters to perform state estimation. This dissertation demonstrates the application of the analytical performance model in a particle filter program generator system.Computer Science

Comprehensive Detection Technology for Urban Subway

The urban subway comprehensive detection system is a complex system, which is the collection of advanced sensor technology, computer technology, network technology, data analysis, image analysis and processing technology, artificial intelligence technology and so on. The bow net, orbit and threshold detection of basic project and detection principle for subway are expounded in this paper. And the composition and development of subway comprehensive detection system is proposed