Calibration method of the right-angle error of a hollow corner-cube retroreflector based on an independent autocollimator.

Hollow corner-cube retroreflectors (HCCRs) are an essential reflection component of next-generation lunar laser-ranging technology. The verticality among the three reflectors, known as the right-angle error, is a critical parameter that affects the emission performance, and thus, should be correctly measured and calibrated. However, conventional methods measure the three right-angle errors separately, which can induce error superposition during the measurement process. A one-time measurement method was developed for the three right-angle errors of the HCCR using a single autocollimator (AC). The method establishes a mathematical relationship between the right-angle error of the HCCR and the angle offset of the reflected beam, and it considers the observation coordinates of the AC simultaneously to perform the coordinate transformation of the relationship parameters. The corresponding measurement equation was derived to extract the three-plane right-angle error of the HCCR using the measured readings of a single AC. In addition, a HCCR was designed to freely adjust the angle of the two reflective surfaces and used to simulate the different states of the three right-angle errors in practice. The measurement results show that the root-mean-square error of the proposed method in all right-angle error states is smaller than 16 ' ' .

Effects of ambient particulate exposure on blood lipid levels in hypertension inpatients.

Background: With modernization development, multiple studies of atmospheric particulate matter exposure conducted in China have confirmed adverse cardiovascular health effects. However, there are few studies on the effect of particulate matter on blood lipid levels in patients with cardiovascular disease, especially in southern China. The purpose of this study was to investigate the association between short- and long-term exposure to ambient particulate matter and the levels of blood lipid markers in hypertension inpatients in Ganzhou, China. Methods: Data on admission lipid index testing for hypertension inpatients which were divided into those with and without arteriosclerosis disease were extracted from the hospital's big data center from January 1, 2016 to December 31, 2020, and air pollution and meteorology data were acquired from the China urban air quality real time release platform from January 1, 2015 to December 31, 2020 and climatic data center from January 1, 2016 to December 31, 2020, with data integrated according to patient admission dates. A semi-parametric generalized additive model (GAM) was established to calculate the association between ambient particulate matter and blood lipid markers in hypertension inpatients with different exposure time in 1 year. Results: Long-term exposure to particulate matter was associated with increased Lp(a) in three kinds of people, and with increased TC and decreased HDL-C in total hypertension and hypertension with arteriosclerosis. But particulate matter was associated with increased HDL-C for hypertension inpatients without arteriosclerosis, at the time of exposure in the present study. It is speculated that hypertension inpatients without arteriosclerosis has better statement than hypertension inpatients with arteriosclerosis on human lipid metabolism. Conclusion: Long-term exposure to ambient particulate matter is associated with adverse lipid profile changes in hypertension inpatients, especially those with arteriosclerosis. Ambient particulate matter may increase the risk of arteriosclerotic events in hypertensive patients.

Rutting prediction and analysis of influence factors based on multivariate transfer entropy and graph neural networks.

The Rutting prediction model is an essential element of efficient pavement management systems. Accuracy of commonly used predictive model necessitates knowledge of the input parameters that was incorporated and local calibration of the model coefficients. In this paper, a novel rutting prediction model based on multivariate transfer entropy and graph neural networks is proposed for incorporating a limited number of observable inputs, which can accommodate with sufficient prediction performance and generalization to a variety of complex pavement design structure data. The multivariate transfer entropy based graph representation is able to find the significant causality between variables and rutting. The influence factor analysis results confirm the high influence of temperature and vehicle axle load. Several experiments are set up on the Research Institute of Highway Ministry of Transport track (RIOHTrack) dataset for the comparison between the proposed model and the state-of-art prediction models. The result demonstrates that the proposed model is more accurate and robust compared to existing methods on the rutting prediction task.

Long-Term Performance Evolution of RIOHTrack Pavement Surface Layer Based on DMA Method.

Asphalt mixture is a typical viscoelastic material, and its road performance will change with the action of environment and load during actual service. This study conducted experimental research on the surface course asphalt mixture of three categories and six typical structures of RIOHTrack based on the Dynamic Mechanical Analysis method. Moreover, this study explored the performance evolution law of asphalt mixture under the coupling action of load and environment in the process of loading from 0 million to 54 million standard axle times. Results demonstrated that the phase transition characteristic temperature of the surface course materials of the three types of typical structures showed a trend of first increasing and then decreasing with the accumulation of load and environmental effects, indicating the presence of two stages of the dual coupling effect of environmental aging and load rolling on the asphalt mixture during service. In addition, the results suggested that the phase transition characteristic temperature, modulus, and phase angle of the surface layer materials have obvious material differences and structure dependencies.

Ambient air pollutants relate to hospital admissions for chronic obstructive pulmonary disease in Ganzhou, China.

OBJECTIVE: To evaluate the relationship between ambient air pollutants and chronic obstructive pulmonary disease in relatively low-polluted areas in China. METHODS: Atmospheric pollutants levels and meteorological data were obtained from January 2016 to December 2020. The medical database including daily hospital admissions for chronic obstructive pulmonary disease (ICD10: J44) was derived from the First Affiliated Hospital of Gannan Medical University. The generalized additive model was used to analyze the percentage change with 95% confidence interval in daily hospital admissions for chronic obstructive pulmonary disease associated with a 10 µg/m3 increase in atmospheric pollutants levels. RESULTS: In total, occurred 4,980 chronic obstructive pulmonary disease hospital admissions (not including emergency department visits) during 2016-2020. The mean concentrations of daily PM2.5, PM10, SO2, NO2, O3, and CO were 37.5 µg/m3, 60.1 µg/m3, 18.7 µg/m3, 23.5 µg/m3, 70.0 µg/m3, and 1.2 mg/m3 in Ganzhou. Each 10 µg/m3 increment of PM2.5, PM10, NO2, and O3 were significantly associated with 2.8% (95%CI: 1.0-4.7), 1.3% (95%CI: 0.3-2.4), 2.8% (95%CI: 0.4-5.4), and 1.5% (95%CI: 0.2-2.7) elevation in daily chronic obstructive pulmonary disease hospital admissions. The estimates of delayed effects of PM2.5, PM10, NO2, and O3 were observed at lag6, lag6, lag8, lag1, respectively. The health effects of particulate pollutants (PM2.5 and PM10) may be independent of other pollutants. The adverse effects of air pollutants were more evident in the warm season (May-Oct) than in the cold season (Nov-Apr). CONCLUSION: Our study demonstrated that elevated concentrations of atmospheric pollutant (PM2.5, PM10, NO2, and O3), especially particulate pollutants, can be associated with increased daily count of hospital admissions for chronic obstructive pulmonary disease , which may promote further understanding of the potential hazards of relatively low levels of air pollution on chronic obstructive pulmonary disease and other respiratory disorders.

Association Between Sulfur Dioxide and Daily Inpatient Visits With Respiratory Diseases in Ganzhou, China: A Time Series Study Based on Hospital Data.

Background: Sulfur dioxide (SO2) has been reported to be related to the mortality of respiratory diseases, but the relationship between SO2 and hospital inpatient visits with respiratory diseases and the potential impact of different seasons on this relationship is still unclear. Methods: The daily average concentrations of air pollutants, including SO2 and meteorological data in Ganzhou, China, from 2017 to 2019 were collected. The data on daily hospitalization for respiratory diseases from the biggest hospital in the city were extracted. The generalized additive models (GAM) and the distributed lag non-linear model (DLNM) were employed to evaluate the association between ambient SO2 and daily inpatient visits for respiratory diseases. Stratified analyses by gender, age, and season were performed to find their potential effects on this association. Results: There is a positive exposure-response relationship between SO2 concentration and relative risk of respiratory inpatient visits. Every 10 µg/m3 increase in SO2 was related to a 3.2% (95% CI: 0.6-6.7%) exaltation in daily respiratory inpatient visits at lag3. In addition, SO2 had a stronger association with respiratory inpatient visits in women, older adults (≥65 years), and warmer season (May-Oct) subgroups. The relationship between SO2 and inpatient visits for respiratory diseases was robust after adjusting for other air pollutants, including PM10, NO2, O3, and CO. Conclusion: This time-series study showed that there is a positive association between short-term SO2 exposure and daily respiratory inpatient visits. These results are important for local administrators to formulate environmental public health policies.

Ambient air pollutants relate to hospital admissions for chronic obstructive pulmonary disease in Ganzhou, China

ABSTRACT OBJECTIVE To evaluate the relationship between ambient air pollutants and chronic obstructive pulmonary disease in relatively low-polluted areas in China. METHODS Atmospheric pollutants levels and meteorological data were obtained from January 2016 to December 2020. The medical database including daily hospital admissions for chronic obstructive pulmonary disease (ICD10: J44) was derived from the First Affiliated Hospital of Gannan Medical University. The generalized additive model was used to analyze the percentage change with 95% confidence interval in daily hospital admissions for chronic obstructive pulmonary disease associated with a 10 µg/m3 increase in atmospheric pollutants levels. RESULTS In total, occurred 4,980 chronic obstructive pulmonary disease hospital admissions (not including emergency department visits) during 2016-2020. The mean concentrations of daily PM2.5, PM10, SO2, NO2, O3, and CO were 37.5 μg/m3, 60.1 μg/m3, 18.7 μg/m3, 23.5 μg/m3, 70.0 μg/m3, and 1.2 mg/m3 in Ganzhou. Each 10 µg/m3 increment of PM2.5, PM10, NO2, and O3 were significantly associated with 2.8% (95%CI: 1.0-4.7), 1.3% (95%CI: 0.3-2.4), 2.8% (95%CI: 0.4-5.4), and 1.5% (95%CI: 0.2-2.7) elevation in daily chronic obstructive pulmonary disease hospital admissions. The estimates of delayed effects of PM2.5, PM10, NO2, and O3 were observed at lag6, lag6, lag8, lag1, respectively. The health effects of particulate pollutants (PM2.5 and PM10) may be independent of other pollutants. The adverse effects of air pollutants were more evident in the warm season (May-Oct) than in the cold season (Nov-Apr). CONCLUSION Our study demonstrated that elevated concentrations of atmospheric pollutant (PM2.5, PM10, NO2, and O3), especially particulate pollutants, can be associated with increased daily count of hospital admissions for chronic obstructive pulmonary disease , which may promote further understanding of the potential hazards of relatively low levels of air pollution on chronic obstructive pulmonary disease and other respiratory disorders.

128-pixel arrays of 4H-SiC UV APD with dual-frequency PECVD SiNx passivation.

In this paper, high-performance 1×128 linear arrays of 4H-SiC ultraviolet (UV) avalanche photodiode (APD) with dual-frequency plasma enhanced chemical vapor deposition (PECVD) passivation are demonstrated for the first time. The results show that SiNx dielectric deposited by dual-frequency PECVD can effectively reduce the leakage current at high bias voltages. Due to the improved 4H-SiC epi-layer material and SiNx passivation, the fabricated 22 mm-long 1×128 4H-SiC APD linear arrays exhibit an excellent performance with a high pixel yield of 100% and a small breakdown voltage variation of 0.2 V, which is the best result ever reported. At room temperature, the pixels have a gain of over 105 and a maximum quantum efficiency of 53.5% @ 285 nm. Besides the high uniformity of breakdown voltage for 128 pixels, the dark currents at 95% of breakdown voltage are all below 1 nA.

Experimental Study on the Phase Transition Characteristics of Asphalt Mixture for Stress Absorbing Membrane Interlayer.

Asphalt mixtures used in stress absorbing membrane interlayers (SAMIs) play a significant role in improving the performance of asphalt pavement. To investigate the rheological properties and phase transition characteristics of asphalt mixtures used in SAMI with temperature changes, twenty-seven candidate mixtures with different binders, gradation types and binder contents were selected in this research. During the study, dynamic mechanical analysis method was employed to evaluate their temperature-dependent properties and a series of wide-range temperature sweep tests were conducted under a sinusoidal loading. Some critical points and key indexes from the testing curves such as glass transition temperature (Tg) can be obtained. Test results show that phase transition characteristics can better reflect the rheological properties of asphalt mixtures at different temperatures. Crumb rubber modified asphalt mixtures (AR) provide a better performance at both high and low temperatures. Additionally, the range of AR asphalt mixtures' effective functioning temperature ΔT is wider, and the slope K value is greater than the others, which indicates that AR asphalt mixtures are less sensitive to temperature changes. Additionally, gradation type and asphalt content also influence the properties: finer gradation and more asphalt content have a good effect on the low-temperature performance of the asphalt mixtures; while mixtures with a coarser gradation and less asphalt content perform better at high temperature and they are less sensitive to temperature changes. Finally, AR asphalt mixture is more suitable to be applied in the SAMI due to its phase transition characteristics from this method.

Optimization Strategy of 4H-SiC Separated Absorption Charge and Multiplication Avalanche Photodiode Structure for High Ultraviolet Detection Efficiency.

In this work, parametric investigations on structural optimization are systematically made for 4H-SiC-based separated absorption charge and multiplication (SACM) avalanche ultraviolet photodiode (UV APD). According to our results, the breakdown voltage can be strongly affected by the thickness for the multiplication layer and the doping concentration for the charge control layer. The thickness for the n-type ohmic contact layer, the absorption layer, and the charge control layer can remarkably affect the light penetration depth, which correspondingly influences the number of photo-generated electron-hole pairs, and therefore the aforementioned layer thickness has a strong impact on the responsivity for SACM APD. For enhancing the responsivity of the APD, we require a reduced energy band barrier height at the interface of the optical absorption layer and the charge control layer, so that the promoted carrier transport into the multiplication layer can be favored. In addition, we investigate positive beveled mesas with smaller angles so as to reduce the electric field at the mesa edge. Thus, the dark current is correspondingly suppressed.

A unified drain current model for nanoscale double-gate and surrounding-gate MOSFETs incorporating velocity saturation.

A unified drain current model for undoped or lightly doped symmetric double-gate and surrounding-gate MOSFETs incorporating velocity saturation effect is proposed in this paper. The unified charge-based core model for undoped or lightly doped double-gate and surrounding-gate MOSFETs is presented first based on the previously published separate models. Caughey-Thomas engineering mobility model with its exponent factor n = 2 is then integrated self-consistently into the unified drain current model development of the two device structures. Extensive two dimensional and three dimensional device simulations are performed to validate the proposed model. Good agreements of the output and transfer characteristics between the unified model and the numerical simulations are obtained for both the double-gate and surrounding-gate MOSFETs. Symmetry property of the proposed unified current model is obtained with the exponent factor n = 2 in Cauhey-Thomas Model.