Integrating depression and acute coronary syndrome care in low resource hospitals in China: the I-CARE randomised clinical trial.

Background: Acute coronary syndrome (ACS) often co-occurs with depression, which adversely affects prognosis and increases medical costs, but effective treatment models are lacking, particularly in low-resource settings. This study aims to determine the effectiveness of an ACS and depression integrative care (IC) model compared to usual care (UC) in improving depression symptoms and other health outcomes among patients discharged for ACS in Chinese rural hospitals. Methods: A multicentre, randomised controlled trial was conducted in sixteen rural county hospitals in China, from October 2014 to March 2017, to recruit consecutively all ACS patients aged 21 years and older after the disease stablised and before discharge. Patients were randomly assigned in a 1:1 ratio to receive either the IC or UC, stratified by hospital and depression severity. Patients allocated to IC received an ACS secondary prevention program and depression care including case screening, group counselling, and individual problem-solving therapy. Patients allocated to UC received usual care. The primary outcome was change in Patient Health Questionnaire-9 (PHQ-9) from baseline to 6 and 12 months. Main secondary outcomes included major adverse events (MAEs) composed of all-cause death, non-fatal myocardial infarction and stroke, and all-cause re-hospitalisation. Participants were followed up till March 2018. All data were collected in person by trained assessors blinded to treatment group and MAEs were adjudicated centrally. This trial is registered with ClinicalTrials.gov, NCT02195193. Findings: Among 4041 eligible patients (IC: 2051; UC: 1990), the mean age was 61 ± 10 years and 63% were men. The mean PHQ-9 score lowered at both 6 and 12 months in both groups but was not lower in IC compared to UC at 6 months (mean difference (MD): -0.04, 95% confidence interval (CI): -0.20, 0.11) or 12 months (MD: -0.06, 95% CI: -0.21, 0.09). There were no treatment group differences for MAEs or other secondary outcomes except for secondary prevention medications at 12 months (45.2% in IC vs 40.8% in UC; relative risk: 1.21, 95% CI: 1.05-1.40). Pre-specified subgroup analyses showed that IC, compared to UC, may be more effective in lowering PHQ-9 scores in women, older patients, and patients with low social support, but less effective in moderately and severely depressed patients (all p for interaction <0.05). Interpretation: The study found that the cardiology nurse-led ACS- and depression-integrated care, compared to usual care, did not improve depression symptoms in all patients discharged with ACS. Greater benefits in certain subgroups warrants further studies. Funding: R01MH100332 National Institute of Mental Health.

Evaluation of best management practices for mitigating harmful algal blooms risk in an agricultural lake basin using a watershed model integrated with Bayesian Network approach.

Lake eutrophication caused by nitrogen and phosphorus has led to frequent harmful algal blooms (HABs), especially under the unknown challenges of climate change, which have seriously damaged human life and property. In this study, a coupled SWAT-Bayesian Network (SWAT-BN) model framework was constructed to elucidate the mechanisms between non-point source nitrogen pollution in agricultural lake watersheds and algal activities. A typical agricultural shallow lake basin, the Taihu Basin (TB), China, was chosen in this study, aiming to investigate the effectiveness of best management practices (BMPs) in controlling HABs risks in TB. By modeling total nitrogen concentration of Taihu Lake from 2007 to 2022 with four BMPs (filter strips, grassed waterway, fertilizer application reduction and no-till agriculture), the results indicated that fertilizer application reduction proved to be the most effective BMP with 0.130 of Harmful Algal Blooms Probability Reduction (HABs-PR) when reducing 40% of fertilizer, followed by filter strips with 0.01 of HABs-PR when 4815ha of filter strips were conducted, while grassed waterway and no-till agriculture showed no significant effect on preventing HABs. Furthermore, the combined practice between 40% fertilizer application reduction and 4815ha filter strips construction showed synergistic effects with HABs-PR increasing to 0.171. Precipitation and temperature data were distorted to model scenarios of extreme events. As a result, the combined approach outperformed any single BMP in terms of robustness under extreme climates. This research provides a watershed-level perspective on HABs risks mitigation and highlights the strategies to address HABs under the influence of climate change.

Research on the prediction model of energy separation effect of vortex tube based on trajectory deflection characteristics and its numerical solution method.

In this paper, in order to establish the energy separation mechanism of the vortex tube, the hydrodynamic behavior of the compressible fluid in the asymmetric cavity space is investigated, and a numerical model of the trajectory deflection behavior is deduced and established; in order to form the optimal design method of the structural parameters of the vortex tube, the force situation of the fluid microelements entering different regions of the vortex chamber of the vortex tube is analyzed, and the trajectory deflection equations are corrected by combining with the expansion behavior of the fluid and the characterizing equations of vortex strength, transportability, and vortex initiation characteristics are given. The characterization equations of vortex strength, transportability and vortex initiation characteristics are given, and the numerical simulation of their influence parameters is carried out; in order to realize the prediction of the vortex tube performance of a given structure, the multifactor Pearson thermodynamic map is used to correlate and analyze the experimental data of vortex tubes reported publicly in the past years, and the polynomial regression equations are designed and established for the prediction of the vortex tube's energy separation effect and the confidence level and the degree of coincidence of the prediction results are examined. The confidence level and degree of agreement of the prediction results were examined. It is found that: the trajectory deflection motion of the compressible fluid in the asymmetric cavity space is the result of the combined effect of structural air pressure bias and the expansion behavior of the incident fluid; in order to improve the vortex strength in the vortex tube, the vortex initiation chamber space should be as small as possible; the increase of the diameters of the hot-end pipe and the cold-end pipe is conducive to the enhancement of vortex strength, but at the same time, it weakens the vortex transport in the heat pipe; the vortex initiation chamber size has a negative correlation with the hot-end temperature rise, and the inlet fluid pressure has a The negative correlation between the size of the vortex chamber and the temperature rise at the hot end, the positive correlation between the increase of inlet fluid pressure and the resulting temperature rise, and the strong correlation between the inlet fluid pressure and the friction coefficient on the effect of energy separation; the predictive equations for the effect of energy separation obtained by the fitting are in good agreement with the real situation.

Effects of Temperature on Novel Molecular Perovskite Energetic Material (C6H14N2)[NH4(ClO4)3]: A Molecular Dynamics Simulation.

Molecular dynamics (MD) simulations were performed on the energetic molecular perovskite (C6H14N2)[NH4(ClO4)3], with excellent detonation properties, thermal stability, and high specific impulse, which is a potential replacement for AP as the next generation propellants. The cohesive energy density, binding energy, pair correlation function, maximum bond length (Lmax) of the N-H trigger bond, and mechanical properties of the (C6H14N2)[NH4(ClO4)3] were reported. The calculated cohesive energy density and binding energy decrease with increasing temperature, indicating a gradual decrease in the thermal stability with temperature. In addition, H···O hydrogen bonding interactions have been found based on the results of pairwise correlation functions. The maximum length (Lmax) of the N-H trigger bond was calculated and used as a criterion to theoretically judge the impact sensitivity. The maximum bond length of the N-H trigger bond grows gradually with temperature; however, it does very slightly yet gradually above 373 K. This suggests that an increase in temperature leads to a higher impact sensitivity and lower thermal stability. However, this effect becomes less pronounced when the temperature surpasses 373 K. Moreover, the calculated mechanical data indicate that as the temperature rises, the material's stiffness, hardness, yield strength, and fracture strength all decrease. The material's ductility shows an upward trend with increasing temperature, reaching its peak at 373 K and subsequently declining as the temperature continues to rise.

Study on the spatial distribution of urban carbon emissions at the micro level based on multisource data.

Global warming is currently an area of concern. Human activities are the leading cause of urban greenhouse gas intensification. Inversing the spatial distribution of carbon emissions at microscopic scales such as communities or controlling detailed planning plots can capture the critical emission areas of carbon emissions, thus providing scientific guidance for intracity low-carbon development planning. Using the Sino-Singapore Tianjin Eco-city as an example, this paper uses night-light images and statistical yearbooks to perform linear fitting within the Beijing-Tianjin-Hebei city-county region and then uses fine-scale data such as points of interest, road networks, and mobile signaling data to construct spatial characteristic indicators of carbon emissions distribution and assign weights to each indicator through the analytic hierarchy process. As a result, the spatial distribution of carbon emissions based on detailed control planning plots is calculated. The results show that among the selected indicators, the population distribution significantly influences carbon emissions, with a weight of 0.384. The spatial distribution of carbon emissions is relatively distinctive. The primary carbon emissions are from the Sino-Singapore Cooperation Zone due to its rapid urban construction and development. In contrast, carbon emissions from other areas are sparse, as there is mostly unused land under construction.

Interaction, Insensitivity and Thermal Conductivity of CL-20/TNT-Based Polymer-Bonded Explosives through Molecular Dynamics Simulation.

Binders mixed with explosives to form polymer-bonded explosives (PBXs) can reduce the sensitivity of the base explosive by improving interfacial interactions. The interface formed between the binder and matrix explosive also affects the thermal conductivity. Low thermal conductivity may result in localized heat concentration inside the PBXs, causing the detonation of the explosive. To investigate the binder-explosive interfacial interactions and thermal conductivity, PBXs with polyurethane as the binder and 2,4,6,8,10,12-hexanitro-2,4,6,8,10,12-hexaazaisowurtzitane/2,4,6-trinitrotoluene (CL-20/TNT) co-crystal as the matrix explosive were investigated through molecular dynamics (MD) simulations and reverse non-equilibrium molecular dynamics (rNEMD) simulation. The analysis of the pair correlation function revealed that there are hydrogen bonding interactions between Estane5703 and CL-20/TNT. The length of the trigger bonds was adopted as a theoretical criterion of sensitivity, and the effect of polymer binders on the sensibility of PBXs was correlated by analyzing the interfacial trigger bonds and internal trigger bonds of PBXs for the first time. The results indicated that the decrease in sensitivity of CL-20/TNT mainly comes from the CL-20/TNT contact with Estane5703. Therefore, the sensitivity of CL-20/TNT-based PBXs can be further reduced by increasing the contact area between CL-20/TNT and Estane5703. The thermal conductivity of PBXs composed of Estane5703 and CL-20/TNT (0 0 1), (0 1 0) and (1 0 0) crystal planes, respectively, were calculated through rNEMD simulations, and the results showed that only the addition of Estane5703 to the (1 0 0) crystal plane can improve the thermal conductivity of PBX100.

Impacts of Climate Change on Rice Grain: A Literature Review on What Is Happening, and How Should We Proceed?

More than half of the people on Earth get their calories, proteins, and minerals from rice grains. Staple increases in the quantity and quality of rice grains are key to ending hunger and malnutrition. Rice production, however, is vulnerable to climate change, and the climate on Earth is becoming more fluctuating with the atmospheric change induced by human activities. As a result, the impacts of climate change on rice grain (ICCRG) have sparked widespread concern. In order to reveal the development and the trend in the study on the ICCRG, a bibliometric analysis was conducted. The results showed that both the model simulations and the field experiment-based observations, as reflected by APSIM (the Agricultural Production Systems sIMulator) and free-air carbon dioxide (CO2) enrichment, are of concern to researchers worldwide, especially in China, India, the United States, and Japan. Different types of warming include short-term, nighttime, soil and water, and canopy, and their interactions with other climate factors, such as CO2, or agronomic factors, such as nitrogen level, are also of concern to researchers. Spatiotemporal variations in changing weather and regional adaptations from developed and developing countries are challenging the evaluation of ICCRG from an economic perspective. In order to improve the efficacy of breeding adaptable cultivars and developing agronomic management, interdisciplinary studies integrating molecular biology, plant physiology, agronomy, food chemistry, ecology, and socioeconomics are needed.

Atmospheric elemental carbon pollution and its regional health disparities in China.

Previous studies have reported that atmospheric elemental carbon (EC) may pose potentially elevated toxicity when compared to total ambient fine particulate matter (PM2.5). However, most research on EC has been conducted in the US and Europe, whereas China experiences significantly higher EC pollution levels. Investigating the health impact of EC exposure in China presents considerable challenges due to the absence of a monitoring network to document long-term EC levels. Despite extensive studies on total PM2.5 in China over the past decade and a significant decrease in its concentration, changes in EC levels and the associated mortality burden remain largely unknown. In our study, we employed a combination of satellite remote sensing, available ground observations, machine learning techniques, and atmospheric big data to predict ground EC concentrations across China for the period 2005-2018, achieving a spatial resolution of 10 km. Our findings reveal that the national average annual mean EC concentration has remained relatively stable since 2005, even as total PM2.5 levels have substantially decreased. Furthermore, we calculated the all-cause non-accidental deaths attributed to long-term EC exposure in China using baseline mortality data and pooled mortality risk from a cohort study. This analysis unveiled significant regional disparities in the mortality burden resulting from long-term EC exposure in China. These variations can be attributed to varying levels of effectiveness in EC regulations across different regions. Specifically, our study highlights that these regulations have been effective in mitigating EC-related health risks in first-tier cities. However, in regions characterized by a high concentration of coal-power plants and industrial facilities, additional efforts are necessary to control emissions. This observation underscores the importance of tailoring environmental policies and interventions to address the specific challenges posed by varying emission sources and regional contexts.

Application of multi-angle spaceborne observations in characterizing the long-term particulate organic carbon pollution in China.

Ambient PM2.5 pollution is recognized as a leading environmental risk factor, causing significant mortality and morbidity in China. However, the specific contributions of individual PM2.5 constituents remain unclear, primarily due to the lack of a comprehensive ground monitoring network for constituents. This issue is particularly critical for carbonaceous species such as organic carbon (OC) and elemental carbon (EC), which are known for their significant health impacts, and understanding the OC/EC ratio is crucial for identifying pollution sources. To address this, we developed a Super Learner model integrating Multi-angle Imaging SpectroRadiometer (MISR) retrievals to predict daily OC concentrations across China from 2003 to 2019 at a 10-km spatial resolution. Our model demonstrates robust predictive accuracy, as evidenced by a random cross-validation R2 of 0.84 and an RMSE of 4.9 µg/m3, at the daily level. Although MISR is a polar-orbiting instrument, its fractional aerosol data make a significant contribution to the OC exposure model. We then use the model to explore the spatiotemporal distributions of OC and further calculate the EC/OC ratio in China. We compared regional pollution discrepancies and source contributions of carbonaceous pollution over three selected regions: Beijing-Tianjin-Hebei, Fenwei Plain, and Yunnan Province. Our model observes that OC levels are elevated in Northern China due to industrial operations and central heating during the heating season, while in Yunnan, OC pollution is mainly contributed by local forest fires during fire seasons. Additionally, we found that OC pollution in China is likely influenced by climate phenomena such as the El Niño-Southern Oscillation. Considering that climate change is increasing the severity of OC concentrations with more frequent fire events, and its influence on OC formation and dispersion, we suggest emphasizing the role of climate change in future OC pollution control policies. We believe this study will contribute to future epidemiological studies on OC, aiding in refining public health guidelines and enhancing air quality management in China.

First-principles study on the mechanical and electronic properties of energetic molecular perovskites AM(ClO4)3 (A = C6H14N2 2+, C4H12N2 2+, C6H14N2O2+; M = Na+, K+).

Density functional theory (DFT) simulations were conducted to study the crystal structures, and mechanical and electronic properties of a series of new energetic molecular perovskites, including (C6H14N2)[Na(ClO4)3], (C6H14N2)[K(ClO4)3], (C4H12N2)[Na(ClO4)3] and (C6H14N2O)[K(ClO4)3], abbreviated as DAP-1, DAP-2, PAP-1, and DAP-O2, respectively. By calculating the elastic constants, moduli (Young's modulus E, bulk modulus B, and shear modulus G), Poisson ratio ν and Pugh's ratio B/G, we found that the four energetic molecular perovskites not only possessed good mechanical stability but excellent mechanical flexibility and ductility. In addition, DFT calculations were used to investigate the electronic properties of all of the perovskite compounds. The band gaps of DAP-1 and DAP-2 were comparable, and the band gap of PAP-1 was the smallest and that of DAP-O2 was the largest. A comprehensive analysis of the density of states and the M-O bonding characteristics provided a good explanation for the band gap characteristics. Besides, we found that the modulus properties of these molecular perovskite energetic compounds are also tightly bound to the strength of M-O bonding.

Assessment of long-term particulate nitrate air pollution and its health risk in China.

Air pollution is a major environmental and public health challenge in China and the Chinese government has implemented a series of strict air quality policies. However, particulate nitrate (NO3 -) concentration remains high or even increases at monitoring sites despite the total PM2.5 concentration has decreased. Unfortunately, it has been difficult to estimate NO3 - concentration across China due to the lack of a PM2.5 speciation monitoring network. Here, we use a machine learning model incorporating ground measurements and satellite data to characterize the spatiotemporal patterns of NO3 -, thereby understanding the disease burden associated with long-term NO3 - exposure in China. Our results show that existing air pollution control policies are effective, but increased NO3 - of traffic emissions offset reduced NO3 - of industrial emissions. In 2018, the national mean mortality burden attributable to NO3 - was as high as 0.68 million, indicating that targeted regulations are needed to control NO3 - pollution in China.

Spectral-Spatial Attention Transformer with Dense Connection for Hyperspectral Image Classification.

In recent years, deep learning has been widely used in hyperspectral image (HSI) classification and has shown good capabilities. Particularly, the use of convolutional neural network (CNN) in HSI classification has achieved attractive performance. However, HSI contains a lot of redundant information, and the CNN-based model is limited by the receptive field of CNN and cannot balance the performance and depth of the model. Furthermore, considering that HSI can be regarded as sequence data, CNN-based models cannot mine sequence features well. In this paper, we propose a model named SSA-Transformer to address the above problems and extract spectral-spatial features of HSI more efficiently. The SSA-Transformer model combines a modified CNN-based spectral-spatial attention mechanism and a self-attention-based transformer with dense connection. The SSA-Transformer model can combine the local and global features of HSI to improve the performance of the model. A series of experiments showed that the SSA-Transformer achieved competitive classification accuracy compared with other CNN-based classification methods using three HSI datasets: University of Pavia (PU), Salinas (SA), and Kennedy Space Center (KSC).

Anisotropic Impact Sensitivity of Metal-Free Molecular Perovskite High-Energetic Material (C6H14N2)(NH2NH3)(ClO4)3 by First-Principles Study.

Density functional theory simulations were carried out to investigate energetic molecular perovskite (C6H14N2)(NH2NH3)(ClO4)3 which was a new type energetic material promising for future application. The electronic properties, surface energy, and hydrogen bonding of (100), (010), (011), (101), (111) surfaces were studied, and the anisotropic impact sensitivity of these surfaces were reported. By comparing the values of the band gaps for different surface structures, we found that the (100) surface has the lowest sensitivity, while the (101) surface was considered to be much more sensitive than the others. The results for the total density of states further validated the previous conclusion obtained from the band gap. Additionally, the calculated surface energy indicated that surface energy was positively correlated with impact sensitivity. Hydrogen bond content of the surface structures showed distinct variability according to the two-dimensional fingerprint plots. In particular, the hydrogen bond content of (100) surface was higher than that of other surfaces, indicating that the impact sensitivity of (100) surface is the lowest.

Ion Transport in the EMITFSI/PVDF System at Different Temperatures: A Molecular Dynamics Simulation.

We used all-atom molecular dynamics simulations to study the ion transport in the 1-ethyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide/poly(vinylidene fluoride) (EMITFSI/PVDF) system with 40.05 wt % EMITFSI at different temperatures. The glass-transition temperature (T g = 204 K) of this system shows a good agreement with the experimental value (200 K). With the increase of temperature, the peaks of the pair correlation function show an increasing trend. Interestingly, the coordination numbers of ion pairs and the degree of independent ion motion are mainly affected by the binding energy between ion pairs as the temperature increases. In addition, the ion transport properties with increasing temperature can be studied by the ion-pair relaxation times, ion-pair lifetimes, and diffusion coefficients. The simulation results illustrate that the ion transport is intensified. Especially, the cations can always diffuse faster than the anions. The power law shows that mobilities of anions and cations are seen to exhibit a "superionic" behavior. With the increase of temperature, transference numbers of anions decrease first and then increase and transference numbers of cations show the opposite changes; ionic conductivity increases gradually; and viscosity decreases gradually, indicating that the diffusion resistance of ions decreases. In general, after adding PVDF into the EMITFSI system, the glass-transition temperature and viscosity increase, the ionic conductivity and degree of independent ion motion decrease, and diffusion coefficients of cations decrease faster than those of the anions.

Satellite-Based Long-Term Spatiotemporal Patterns of Surface Ozone Concentrations in China: 2005-2019.

BACKGROUND: Although short-term ozone (O3) exposure has been associated with a series of adverse health outcomes, research on the health effects of chronic O3 exposure is still limited, especially in developing countries because of the lack of long-term exposure estimates. OBJECTIVES: The present study aimed to estimate the spatiotemporal distribution of monthly mean daily maximum 8-h average O3 concentrations in China from 2005 to 2019 at a 0.05° spatial resolution. METHODS: We developed a machine learning model with a satellite-derived boundary-layer O3 column, O3 precursors, meteorological conditions, land-use information, and proxies of anthropogenic emissions as predictors. RESULTS: The random, spatial, and temporal cross-validation R2 of our model were 0.87, 0.86, and 0.76, respectively. Model-predicted spatial distribution of ground-level O3 concentrations showed significant differences across seasons. The highest summer peak of O3 occurred in the North China Plain, whereas southern regions were the most polluted in winter. Most large urban centers showed elevated O3 levels, but their surrounding suburban areas may have even higher O3 concentrations owing to nitrogen oxides titration. The annual trend of O3 concentrations fluctuated over 2005-2013, but a significant nationwide increase was observed afterward. DISCUSSION: The present model had enhanced performance in predicting ground-level O3 concentrations in China. This national data set of O3 concentrations would facilitate epidemiological studies to investigate the long-term health effect of O3 in China. Our results also highlight the importance of controlling O3 in China's next round of the Air Pollution Prevention and Control Action Plan. https://doi.org/10.1289/EHP9406.

Development and Assessment of a High-Resolution Biogenic Emission Inventory from Urban Green Spaces in China.

Biogenic volatile organic compound (BVOC) emissions have long been known to play vital roles in modulating the formation of ozone and secondary organic aerosols (SOAs). While early studies have evaluated their impact globally or regionally, the BVOC emissions emitted from urban green spaces (denoted as U-BVOC emissions) have been largely ignored primarily due to the failure of low-resolution land cover in resolving such processes, but also because their important contribution to urban BVOCs was previously unrecognized. In this study, by utilizing a recently released high-resolution land cover dataset, we develop the first set of emission inventories of U-BVOCs in China at spatial resolutions as high as 1 km. This new dataset resolved densely distributed U-BVOCs in urban core areas. The U-BVOC emissions in megacities could account for a large fraction of total BVOC emissions, and the good agreement of the interannual variations between the U-BVOC emissions and ozone concentrations over certain regions stresses their potentially crucial role in influencing ozone variations. The newly constructed U-BVOC emission inventory is expected to provide an improved dataset to enable the research community to re-examine the modulation of BVOCs on the formation of ozone, SOA, and atmospheric chemistry in urban environments.

Spatiotemporal evolution analysis of NO2 column density before and after COVID-19 pandemic in Henan province based on SI-APSTE model.

Air pollution is the result of comprehensive evolution of a dynamic and complex system composed of emission sources, topography, meteorology and other environmental factors. The establishment of spatiotemporal evolution model is of great significance for the study of air pollution mechanism, trend prediction, identification of pollution sources and pollution control. In this paper, the air pollution system is described based on cellular automata and restricted agents, and a Swarm Intelligence based Air Pollution SpatioTemporal Evolution (SI-APSTE) model is constructed. Then the spatiotemporal evolution analysis method of air pollution is studied. Taking Henan Province before and after COVID-19 pandemic as an example, the NO2 products of TROPOMI and OMI were analysed based on SI-APSTE model. The tropospheric NO2 Vertical Column Densities (VCDs) distribution characteristics of spatiotemporal variation of Henan province before COVID-19 pandemic were studied. Then the tropospheric NO2 VCDs of TROPOMI was used to study the pandemic period, month-on-month and year-on-year in 18 urban areas of Henan Province. The results show that SI-APSTE model can effectively analyse the spatiotemporal evolution of air pollution by using environmental big data and swarm intelligence, and also can establish a theoretical basis for pollution source identification and trend prediction.

Molecular Dynamics Simulations for Effects of Fluoropolymer Binder Content in CL-20/TNT Based Polymer-Bonded Explosives.

In order to better understand the role of binder content, molecular dynamics (MD) simulations were performed to study the interfacial interactions, sensitivity and mechanical properties of 2,4,6,8,10,12-hexanitro-2,4,6,8,10,12-hexaazaisowurtzitane/2,4,6-trinitrotoluene (CL-20/TNT) based polymer-bonded explosives (PBXs) with fluorine rubber F2311. The binding energy between CL-20/TNT co-crystal (1 0 0) surface and F2311, pair correlation function, the maximum bond length of the N-NO2 trigger bond, and the mechanical properties of the PBXs were reported. From the calculated binding energy, it was found that binding energy increases with increasing F2311 content. Additionally, according to the results of pair correlation function, it turns out that H-O hydrogen bonds and H-F hydrogen bonds exist between F2311 molecules and the molecules in CL-20/TNT. The length of trigger bond in CL-20/TNT were adopted as theoretical criterion of sensitivity. The maximum bond length of the N-NO2 trigger bond decreased very significantly when the F2311 content increased from 0 to 9.2%. This indicated increasing F2311 content can reduce sensitivity and improve thermal stability. However, the maximum bond length of the N-NO2 trigger bond remained essentially unchanged when the F2311 content was further increased. Additionally, the calculated mechanical data indicated that with the increase in F2311 content, the rigidity of CL-20/TNT based PBXs was decrease, the toughness was improved.

Random forest model based fine scale spatiotemporal O3 trends in the Beijing-Tianjin-Hebei region in China, 2010 to 2017.

Ambient ozone (O3) concentrations have shown an upward trend in China and its health hazards have also been recognized in recent years. High-resolution exposure data based on statistical models are needed. Our study aimed to build high-performance random forest (RF) models based on training data from 2013 to 2017 in the Beijing-Tianjin-Hebei (BTH) region in China at a 0.01 ° × 0.01 ° resolution, and estimated daily maximum 8h average O3 (O3-8hmax) concentration, daily average O3 (O3-mean) concentration, and daily maximum 1h O3 (O3-1hmax) concentration from 2010 to 2017. Model features included meteorological variables, chemical transport model output variables, geographic variables, and population data. The test-R2 of sample-based O3-8hmax, O3-mean and O3-1hmax models were all greater than 0.80, while the R2 of site-based and date-based model were 0.68-0.87. From 2010 to 2017, O3-8hmax, O3-mean, and O3-1hmax concentrations in the BTH region increased by 4.18 µg/m3, 0.11 µg/m3, and 4.71 µg/m3, especially in more developed regions. Due to the influence of weather conditions, which showed high contribution to the model, the long-term spatial distribution of O3 concentrations indicated a similar pattern as altitude, where high concentration levels were distributed in regions with higher altitude.