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Background/Aims: Low educational attainment is a well-established risk factor for nonalcoholic fatty liver disease (NAFLD) in developed areas. However, the association between educational attainment and the risk of NAFLD is less clear in China. Methods: A cross-sectional study including over 200,000 Chinese adults across mainland China was conducted. Information on education level and lifestyle factors were obtained through standard questionnaires, while NAFLD and advanced fibrosis were diagnosed using validated formulas. Outcomes included the risk of NAFLD in the general population and high probability of fibrosis among patients with NAFLD. Logistic regression analysis was employed to estimate the risk of NAFLD and fibrosis across education levels. A causal mediation model was used to explore the potential mediators. Results: Comparing with those receiving primary school education, the multi-adjusted odds ratios (95% confidence intervals) for NAFLD were 1.28 (1.16 to 1.41) for men and 0.94 (0.89 to 0.99) for women with college education after accounting for body mass index. When considering waist circumference, the odds ratios (95% CIs) were 0.94 (0.86 to 1.04) for men and 0.88 (0.80 to 0.97) for women, respectively. The proportions mediated by general and central obesity were 51.00% and 68.04% for men, while for women the proportions were 48.58% and 32.58%, respectively. Furthermore, NAFLD patients with lower educational attainment showed an incremental increased risk of advanced fibrosis in both genders. Conclusion : s: In China, a low education level was associated with a higher risk of prevalent NAFLD in women, as well as high probability of fibrosis in both genders.

Background/Aims: Necrotizing pancreatitis (NP) presents a more severe clinical trajectory and increased mortality compared to edematous pancreatitis. Prompt identification of NP is vital for patient prognosis. A risk prediction model for NP among Chinese patients has been developed and validated to aid in early detection. Methods: A retrospective analysis was performed on 218 patients with acute pancreatitis (AP) to examine the association of various clinical variables with NP. The least absolute shrinkage and selection operator (LASSO) regression was utilized to refine variables and select predictors. Subsequently, a multivariate logistic regression was employed to construct a predictive nomogram. The model's accuracy was validated using bootstrap resampling (n=500) and its calibration assessed via a calibration curve. The model's clinical utility was evaluated through decision curve analysis. Results: Of the 28 potential predictors analyzed in 218 AP patients, the incidence of NP was 25.2%. LASSO regression identified 14 variables, with procalcitonin, triglyceride, white blood cell count at 48 hours post-admission, calcium at 48 hours post-admission, and hematocrit at 48 hours post-admission emerging as independent risk factors for NP. The resulting nomogram accurately predicted NP risk with an area under the curve of 0.822, sensitivity of 82.8%, and specificity of 76.4%. The bootstrap-validated area under the curve remained at 0.822 (95% confidence interval, 0.737 to 0.892). This model exhibited excellent calibration and demonstrated greater predictive efficacy and clinical utility for NP than APACHE II, Ranson, and BISAP. Conclusions: We have developed a prediction nomogram of NP that is of great value in guiding clinical decision.

Abstract BackgroundCardiovascular-kidney-metabolic (CKM) health is affected by social determinants of health, especially education. CKM syndrome has not been evaluated in Chinese population, and the association of education with CKM syndrome in different sexes and its intertwined relation with lifestyles have not been explored. ObjectiveWe aimed to explore the association between educational attainment and the prevalence of CKM syndrome stages in middle-aged and older Chinese men and women as well as the potential role of health behavior based on Life’s Essential 8 construct. MethodsThis study used data from the nationwide, community-based REACTION (Risk Evaluation of Cancers in Chinese diabetic individuals: a longitudinal study). A total of 132,085 participants with complete information to determine CKM syndrome stage and education level were included. Educational attainment was assessed by the self-reported highest educational level achieved by the participants and recategorized as low (elementary school or no formal education) or high (middle school, high school, technical school/college, or above). CKM syndrome was ascertained and classified into 5 stages according to the American Heart Association presidential advisory released in 2023. ResultsAmong 132,085 participants (mean age 56.95, SD 9.19 years; n=86,675, 65.62% women) included, most had moderate-risk CKM syndrome (stages 1 and 2), and a lower proportion were at higher risk of CKM (stages 3 and 4). Along the CKM continuum, low education was associated with 34% increased odds of moderate-risk CKM syndrome for women (odds ratio 1.36, 95% CI 1.23-1.49) with a significant sex disparity, but was positively correlated with high-risk CKM for both sexes. The association between low education and high-risk CKM was more evident in women with poor health behavior but not in men, which was also interactive with and partly mediated by behavior. ConclusionsLow education was associated with adverse CKM health for both sexes but was especially detrimental to women. Such sex-specific educational disparity was closely correlated with health behavior but could not be completely attenuated by behavior modification. These findings highlight the disadvantage faced by women in CKM health ascribed to low education, underscoring the need for public health support to address this inequality.

Abstract In order to fulfill the complex cognitive behaviors in neuromorphic systems with reduced peripheral circuits, the reliable electronic synapses mimicked by single device that achieves diverse long‐term and short‐term plasticity are essential. Phase change random access memory (PCRAM) is of great potential for artificial synapses, which faces, however, difficulty to realize short‐term plasticity due to the long‐lasting resistance drift. This work reports the ruthenium‐doped Ge2Sb2Te5 (RuGST) based PCRAM, demonstrating a series of synaptic behaviors of short‐term potentiation, pair‐pulse facilitation, long‐term depression, and short‐term plasticity in the same single device. The optimized RuGST electronic synapse with the high transformation temperature of hexagonal phase >380°C, the outstanding endurance >108 cycles, the low resistance drift factor of 0.092, as well as the extremely high linearity with correlation coefficients of 0.999 and 0.976 in parts of potentiation and depression. Further investigations also go insight to mechanisms of Ru doping according to thorough microstructure characterization, revealing that Ru dopant is able to enter GST lattices thus changing and stabilizing atomic arrangement of GST. This leads to the short‐term plasticity realized by RuGST PCRAM. Eventually, the proposed RuGST electronic synapses performs a high accuracy of ~94.1% in a task of image recognition of CIFAR‐100 database using ResNet 101. This work promotes the development of PCRAM platforms for large‐scale neuromorphic systems.

BackgroundThe triglyceride glucose (TyG) index has been associated with an increased risk in breast cancer. However, this association remains unclear among the Chinese population. This study aimed to investigate whether the TyG index is associated with the risk of prevalent breast cancer in Chinese women.MethodsThis cross-sectional study included 142,184 women from the REACTION (Risk Evaluation of Cancers in Chinese Diabetic Individuals: A Longitudinal) Study, which recruited adults aged 40 years or older from 25 centers across mainland China between 2011 and 2012. The TyG index was calculated according to the formula: Ln (fasting triglycerides [mg/dL] × fasting glucose [mg/dL]/2). Multivariable-adjusted logistic regression models were used to evaluate odds ratios (ORs) and 95% confidence intervals (CIs) regarding the associations between the TyG index and breast cancer.ResultsMultivariable-adjusted logistic regression analysis showed that compared with the lowest quartile of the TyG index, the highest quartile of the TyG index was significantly associated with an increased risk of prevalent breast cancer, with an OR (95% CI) of 1.61 (1.19–2.17). In the stratified analysis, the association of each 1 SD increase in the TyG index with risk of prevalent breast cancer was more dominant in individuals with menarche at age 13–17, those who were postmenopausal, those with a history of breastfeeding, and those who had two to four children, with the ORs (95% CIs) of 1.35 (1.09–1.68), 1.27 (1.05–1.54), 1.26 (1.05–1.52), and 1.32 (1.08–1.62), respectively. Moreover, among those without discernible insulin resistance (homeostatic model assessment-insulin resistance [HOMA-IR] ≥2.5), hyperglycemia and dyslipidemia, each 1 SD increase in the TyG index was associated with a 1.36-fold increase in breast cancer risk, with an OR (95% CI) of 2.36 (1.44–3.87).ConclusionThe TyG index is significantly associated with the prevalent breast cancer risk among middle-aged and elderly Chinese women.

In this article, we present the first demonstration of the FengYun-3E (FY3E) Global Navigation Satellite System Occultation Sounder II-Reflectometry (GNOS-R) payload's capacity to detect near-surface soil freeze/thaw (F/T) states. This study offers an initial analysis of the F/T retrieval algorithm applied to data collected from the Arctic Circle, underscoring the GNOS-R's potential to deliver long-term near-surface soil F/T products. Data for the period extending from the launch day of GNOS-R (Day of Year (DOY) 179, 2021) to DOY 270 in 2022 were analyzed using the surface reflectivity (SR) ratio factor to discriminate F/T variations. Comparisons were made with soil moisture active passive (SMAP) F/T products, serving as an auxiliary analysis. We found a strong consistency between SR ratio factor and SMAP F/T values, with the accuracy of the F/T retrieval algorithm exceeding 60%. These findings corroborate the efficacy of the GNOS-R payload aboard FY3E in monitoring F/T patterns at higher latitudes, specifically, the Arctic Circle. The outcomes of this study will be beneficial for future F/T detection efforts using spaceborne Global Navigation Satellite System-Reflectometry payloads.

The Microwave Radiation Imager (MWRI) onboard the FengYun satellite plays a crucial role in global change monitoring and numerical weather prediction. Estimating and correcting geolocation errors are important to retrieving accurate geophysical variables. However, the instantaneous field of view (IFOV) inter-channel deviation, which is mainly caused by the structure mounting error and measurement error of feedhorns, is less studied. In this present study, we constructed a general theoretical model to automatically estimate the IFOV inter-channel deviations suitable for conical-scanning instruments. The model can automatically detect the along-track and across-track vectors that pass through the land–sea boundary points and are perpendicular to the actual coastlines. Regarding the midpoints of the vectors as the brightness temperature (Tb) inflection points, the IFOV inter-channel deviation is the pixel offset or distance of the maximum gradients of the Tb near the inflection points for each channel relative to the 89-GHz V-pol channel. We tested the model’s operational performance using the FY-3G/MWRI-Rainfall Mission (MWRI-RM) observations. Considering that parameter uploading adjusted the IFOV inter-channel deviations, the model’s validity was verified by comparing the adjustments calculated by the model with the theoretical changes caused by parameter uploading. The result shows that the differences between them for all window channels are less than 100 m, indicating the model’s effectiveness in evaluating the IFOV inter-channel deviation for the MWRI-RM. Furthermore, the estimated on-orbit IFOV inter-channel deviations for the MWRI-RM show that all channel deviations are less than 1 km, meeting the instrument’s design requirement of 2 km. We believe this study will provide a foundation for IFOV inter-channel registration of passive microwave payloads and spatial matching of multiple payloads.

Fusion of thermal infrared (TIR) and passive microwave (PMW) observations are important techniques for estimating all-weather land surface temperature (LST) of relatively higher resolutions. For such fusion techniques under cloudy weather, PMW observations are especially useful in correcting the cloud-shadowing bias of the real cloudy LST against a theoretically clear-sky one in the daytime. However, PMW observations have very limited transit times in a day, and cannot be fused with asynchronous TIR data as LST can vary significantly during the daytime. To overcome this flaw, we developed a model for simulating the variation of cloud-shadowing bias based on cloud total amount (CTA) information observed by geostationary satellites. As constant coefficients of the model were found to have dependence on space and time, they were dynamically fitted for each pixel in each month using cloud-shadowing bias calculated by TIR and synchronous PMW data in the early-afternoon (1:30 P.M.). The model was then used to provide middle-morning (10:30 A.M.) cloud-shadowing bias estimates, based on which, all-weather LST at 1 km were produced at that specific moment. Validation results show that reconstructed cloudy LST in the middle-morning, with no synchronous PMW observations, has its overall RMSE values against ground measurements and real remote sensing data under cloud between 2.4 and 4.0 K. This accuracy result is generally comparable to that obtained through fusing information from synchronous PMW data in the early-afternoon moment. Therefore, it is prospective to be further applied for generating high-resolution all-weather LST with much shorter re-visit cycles than the satellite PMW data.

Abstract Background The association between weight change during early adulthood and cardiometabolic diseases remains uncertain in Chinese population. Whether the association varies with comprehensive cardiovascular health (CVH) in midlife assessed by “Life’s Essential 8” has not been characterized. We aim to examine the associations of early adulthood weight change and midlife “Life’s Essential 8” CVH status with cardiometabolic outcomes in a Chinese cohort. Methods The study participants were from the China Cardiometabolic Disease and Cancer Cohort (4 C) Study. This analysis included 72,610 middle-aged and older participants followed for a median of 3.6 years. At baseline, the participants recalled body weight at age 20 and 40 years, and we calculated change in weight and BMI between 20 and 40 years of age. Health behaviors information in “Life’s Essential 8” was collected by questionnaire, and health factors were measured in the study center. During follow-up, we ascertained incident cardiovascular events based on medical records, and diagnosed incident diabetes according to the American Diabetes Association 2010 criteria. Results 72,610 study participants were included with a mean age of 56.0 ± 8.8 years and 29% of them were males. Weight gain of more than 10 kg between 20 and 40 years of age was associated with 22% increased risk of incident cardiovascular events (HR: 1.22; 95%CI: 1.04–1.43) and 38% increased risk of diabetes (HR: 1.38; 95%CI: 1.25–1.53) compared to stable weight. Besides, the association of weight gain more than 10 kg in early adulthood with cardiometabolic risk was even stronger in those with low CVH score in midlife (HR: 2.44; 95%CI: 2.01–2.97 for incident cardiovascular events; HR: 2.20; 95%CI: 1.90–2.55 for incident diabetes) or with few ideal cardiovascular health metrics in midlife. Conclusions Our study indicated that weight gain in early adulthood was associated with significantly increased risk of cardiometabolic diseases. And the association could be stronger in those with poor CVH profiles in midlife. These findings confirmed the significance of weight management during early adulthood and suggested that individuals who experienced substantial weight gain in early life should be encouraged to maintain good CVH status in Chinese population.

Based on introducing the technical characteristics of FY-3G, which is China's first precipitation measurement satellite and successfully launched at 09∶36 BT on April 16 in 2023, this paper focuses on the precipitation detection capabilities and application prospect in rainstorm monitoring of FY-3G. The results show that, with an orbit at 407 km and an inclination angle of 50°, and equipped with a dual-frequency Ka/Ku band precipitation measurement radar, microwave, and optical imaging instruments, the FY-3G satellite can detect the three-dimensional structure of disastrous weather systems such as typhoon, heavy rainfall, and other strong convection events in most of China. At the design level, FY-3G has precipitation detection capabilities comparable to the current US Second Generation Global Precipitation Measurement Program (GPM) Core Satellite (GPMCO), but better payload types, quantities, and channel settings compared with the GPMCO satellite. After the service operation, the FY-3G satellite, together with other polar-orbiting meteorological satellites such as FY-3 AM, PM, and EM, as well as high-orbit geostationary satellites, will form the Fengyun precipitation detection constellation system, which will improve the overall precipitation detection capability of the Fengyun Satellite constellation and provide stronger basic support for meteorological disaster prevention and mitigation.

Abstract Surface soil moisture (SSM) is an important variable in drought monitoring, floods predicting, weather forecasting, etc. and plays a critical role in water and heat exchanges between land and atmosphere. SSM products from L-band observations, such as the Soil Moisture Active Passive (SMAP) Mission, have proven to be optimal global estimations. Although X-band has a lower sensitivity to soil moisture than that of L-band, Chinese FengYun-3 series satellites (FY-3A/B/C/D) have provided sustainable and daily multiple SSM products from X-band since 2008. This research developed a new global SSM product (NNsm-FY) from FY-3B MWRI from 2010 to 2019, transferred high accuracy of SMAP L-band to FY-3B X-band. The NNsm-FY shows good agreement with in-situ observations and SMAP product and has a higher accuracy than that of official FY-3B product. With this new dataset, Chinese FY-3 satellites may play a larger role and provide opportunities of sustainable and longer-term soil moisture data record for hydrological study.

Abstract Accurately retrieving precipitable water vapor (PWV) over wide‐area land surface remains challenging. Unlike passive infrared remote sensing, passive microwave (PMW) remote sensing provides almost all‐weather PWV retrievals. This study develops a PMW‐based land PWV retrieval algorithm using automated Machine learning (ML) (AutoML). Data from the Advanced Microwave Scanning Radiometer 2 serve as the main predictor variables and high‐quality Global Positioning System (GPS) PWV data as the target variable. Unprecedentedly large GPS training samples (over 50 million) from more than 12,000 stations worldwide are used to train the AutoML model. New predictors with clear physical mechanisms enable PWV retrieval over almost any land surface type, including snow cover and near open water. Validation shows good agreement between PWV retrievals and ground observations, with a root mean square error of 3.1 mm. This encouraging outcome highlights the potential of the algorithm for application with other PMW radiometers with similar wavelengths.

The effect of the thickness of the amorphous silicon (a-Si) intermediate layer on the thermal transport of the Si/diamond heterointerface is investigated by using molecular dynamics simulations. It is found that the TBC of the Si/diamond heterostructure with a 0.5-nm-thick a-Si intermediate layer increases by more than 38 % in comparison with that of the Si/diamond without the a-Si intermediate layer. Meanwhile, the thermal boundary conductance (TBC) of Si/diamond decreases with the increasing thickness of an introduced a-Si intermediate layer. Furthermore, by examining the phonon vibrational spectrum, we found that introducing the a-Si intermediate layer at the interface between Si and diamond alleviates the phonon mismatch between Si and diamond, which increases the available heat transport channels and therefore leads to an increase in TBC. Finally, we observed that the TBC increases with the temperature of the Si/diamond heterostructure due to the enhancement of the inelastic scattering of phonons. These results indicate that the thermal transport of the Si/diamond heterointerface can be effectively regulated by controlling the thickness of the a-Si intermediate layer, which also provides further insight into thermal management design in Si/diamond-based electronic devices.

Abstract Background Evidence regarding the impact of education on diabetes risk is scarce in developing countries. We aimed to explore the association between education and diabetes within a large population in China and to identify the possible mediators between them. Methods Information on educational level and lifestyle factors was collected through questionnaires. Diabetes was diagnosed from self‐report and biochemical measurements. A structural equation model was constructed to quantify the mediation effect of each mediator. Results Compared with their least educated counterparts, men with college education had a higher risk of diabetes (odds ratio [OR] 1.19; 95% confidence interval [CI], 1.12–1.27), while college‐educated women were less likely to have diabetes (OR 0.77; 95% CI, 0.73–0.82). Obesity was the strongest mediator in both genders (proportion of mediation: 11.6% in men and 23.9% in women), and its association with education was positive in men (β[SE] 0.0387 [0.0037]) and negative in women (β[SE] −0.0824 [0.0030]). Taken together, all behavioral factors explained 12.4% of the excess risk of diabetes in men and 33.3% in women. Conclusions In a general Chinese population, the association between education level and diabetes was positive in men but negative in women. Obesity was the major mediator underlying the education disparities of diabetes risk, with a stronger mediation effect among women.

AimsWe aimed to explore the metabolic features of lean nonalcoholic fatty liver disease (Lean-NAFLD) and its association with the risk of incident type 2 diabetes in young and middle-aged people.MethodsWe conducted a retrospective cohort study of 3001 participants who were enrolled in a health check-up program from January 2018 to December 2020 in the Health Management Center of Karamay People’s Hospital. The age, sex, height, weight, body mass index (BMI), blood pressure, waist circumference (WC), fasting plasma glucose (FPG), lipid profiles, serum uric acid and alanine aminotransferase (ALT) of the subjects were collected. The cutoff point of BMI for lean nonalcoholic fatty liver disease is 0.05) and 4.20 (95% CI 1.44-12.22, p

Abstract In recent years, nonalcoholic fatty liver disease (NAFLD) has become the most important chronic liver disease worldwide. The prevalence of NAFLD in China has also increased year by year. This study aimed to detect NAFLD early by developing a nomogram model in Chinese individuals. A total of 8861 subjects who underwent physical examination in Karamay and were 18 to 62 years old were enrolled. Clinical information, laboratory results and ultrasound findings were retrieved. The participants were randomly assigned to the development set (n = 6203) and the validation set (n = 2658). Significant variables independently associated with NAFLD were identified by least absolute shrinkage and selection operator (LASSO) regression and the multiple logistic regression model. Six variables were selected to construct the nomogram: age, sex, waist circumference (WC), body mass index (BMI), alanine aminotransferase (ALT), triglycerides and glucose index (TyG). The area under the receiver operating characteristic curve (AUROC) of the development set and validation set was 0.886 and 0.894, respectively. The calibration curves showed excellent accuracy of the nomogram model. This physical examination and laboratory test-based nomogram can predict the risk of NAFLD intuitively and individually.

Aiming at the problems of insufficient samples of gear fault signals collected in practical engineering，insufficient training，low fault recognition rate and easy pattern collapse of generative adversarial networks when using common deep learning network for pattern recognition under noise interference. An intelligent diagnosis method of gear faults based on MGAN （Mixture Generative Adversarial Nets） and CNN （Convolutional Neural Networks） is proposed. The real gear signals are transformed into time-frequency signals by time-frequency transformation technology after morphological filtering，and new samples are synthesized by MGAN to obtain a balanced data set，which overcomes the problem of insufficient samples. At the same time，the influence law of main parameters of MGAN on the quality of synthesized samples is analyzed. The balanced data set is used to train CNN for fault diagnosis，which effectively improves the fault diagnosis rate. Through the comparative test and bench test，the effectiveness and advantages of this method in accurately identifying faults and overcoming the collapse of neural network mode under the condition of insufficient samples are verified，which provides a new research idea for typical fault extraction and intelligent identification of gearboxes.

The reliable knowledge of seasonal snow volume and its trend is very important to understand Earth’s climate system. Thus, a long-time snow water equivalent (SWE) dataset is necessary. This work presents a daily SWE product of 1980–2020 with a linear unmixing method through passive microwave data including SMMR, SSM/I and SSMIS over China after cross-calibration and bias-correction. The unbiased root-mean-square error of snow depth is about 5–7 cm, corresponding to 10–15 mm for SWE, when compared with stations measurements and field snow course data. The spatial patterns and trends of SWE over China present significant regional differences. The overall slope trend presented an insignificant decreasing pattern during 1980–2020 over China; however, there is an obvious fluctuation, i.e. a significant decrease trend during the period 1980–1990, an upward trend from 2005 to 2009, a significant downward trend from 2009 to 2018. The increase of SWE occurred in the Northeast Plain, with an increase trend of 0.2 mm per year. Whereas in the Hengduan Mountains, it presented a downward trend of SWE, up to −0.3 mm per year. In the North Xinjiang, SWE has an increasing trend in the Junggar Basin, while it shows a decreasing trend in the Tianshan and Altai Mountains.

Abstract Background Whether smoking modifies the associations of diabetes and risk factor management with subsequent risk of cardiovascular disease (CVD), and whether the smoking related CVD risk differs among people with and without diabetes are unclear. This study aimed to examine the associations and interactions of smoking, diabetes, and risk factor management in relation to incident CVD. Methods This nationwide, population-based, prospective cohort study of 20 communities from various geographic regions recruited adults aged 40 years or older during 2011–2012. The follow-up survey was conducted between 2014 and 2016. This study included 126,181 participants who were free from CVD at baseline. Results Study participants included 19,397 current smokers (15.4%), 6,049 former smokers (4.8%), and 100,735 never smokers (79.8%). Mean (SD) age ranged from 55.8 (8.6) years to 60.7 (9.1) years. Compared with never smokers, heavy smokers exhibited a greater risk of CVD events among participants with diabetes (multivariable-adjusted hazard ratio [HR], 1.45; 95% CI, 1.17–1.78) than among participants without diabetes (HR, 1.20; 95% CI, 1.01–1.42; P for interaction = 0.006). Compared with participants without diabetes, participants with diabetes who were never smokers and had 5 or more controlled risk factors showed no significantly excess CVD risk (HR, 0.93; 95% CI, 0.71–1.22), but the cardiovascular benefits from risk factor management were counteracted among participants with diabetes who were current smokers (HR, 1.28; 95% CI, 0.77–2.14) or former smokers (HR, 1.22; 95% CI, 0.66–2.28). Conclusions Smoking and diabetes interacted with each other in relation to increased risk of CVD events, and the beneficial effect of risk factor management on CVD risk among participants with diabetes was attenuated by current or former smoking.

Under the action of alternating load，the gear is easy to generate fatigue crack fault in the tooth root，and the crack propagation will not only affect the transmission accuracy，but even cause serious safety accident and economic loss. Therefore，it is urgent to study the evolution law of tooth root crack propagation. For this，by using complex function method，the Westergaard stress function is constructed to analyze the complex stress field at the crack tip，and the critical condition of crack growth is determined according to the maximum circumferential tensile stress intensity factor theory. Considering the complexity of crack tip discontinuity and singularity in the process of crack propagation，the extended finite element method is modified and the finite element model of tooth root crack propagation is established to solve these problems. Study on the root crack nucleation point location and the crack propagation path of the relationship between the outside diameter of the web，the web hole and the corresponding location of the nucleation point in the gear matrix structure，the crack propagation law of different influencing factors is obtained and the accuracy and effectiveness of the modified finite element method is verified. The results greatly enrich the research on the evolutionary mechanism of tooth root fatigue crack propagation.

Land surface microwave emissivity is crucial to the accurate retrieval of surface and atmospheric parameters and the assimilation of microwave data into numerical models over land. The microwave radiation imager (MWRI) sensors aboard on Chinese FengYun-3 (FY-3) series satellites provide valuable measurements for the derivation of global microwave physical parameters. In this study, an approximated microwave radiation transfer equation was used to estimate land surface emissivity from MWRI by using brightness temperature observations along with corresponding land and atmospheric properties obtained from ERA-Interim reanalysis data. Surface microwave emissivity at the 10.65, 18.7, 23.8, 36.5, and 89 GHz vertical and horizontal polarizations was derived. Then, the global spatial distribution and spectrum characteristics of emissivity over different land cover types were investigated. The seasonal variations of emissivity for different surface properties were presented. Furthermore, the error source was also discussed in our emissivity derivation. The results showed that the estimated emissivity was able to capture the major large-scale features and contains a wealth of information regarding soil moisture and vegetation density. The emissivity increased with the increase in frequency. The smaller surface roughness and increased scattering effect may result in low emissivity. Desert regions showed high emissivity microwave polarization difference index (MPDI) values, which suggested the high contrast between vertical and horizontal microwave signals in this region. The emissivity of the deciduous needleleaf forest in summer was almost the greatest among different land cover types. There was a sharp decrease in the emissivity at 89 GHz in the winter, possibly due to the influence of deciduous leaves and snowfall. The land surface temperature, the radio-frequency interference, and the high-frequency channel under cloudy conditions may be the main error sources in this retrieval. This work showed the potential capabilities of providing continuous and comprehensive global surface microwave emissivity from FY-3 series satellites for a better understanding of its spatiotemporal variability and underlying processes.

BackgroundsWhether longitudinal changes in metabolic status influence the effect of kidney stones on cardiovascular disease (CVD) remains unclarified. We investigated the modification effect of status changes in metabolic syndrome (MetS) in the association of kidney stones with risk of incident CVD events.MethodsWe performed a prospective association and interaction study in a nationwide cohort including 129,172 participants aged ≥ 40 years without CVDs at baseline and followed up for an average of 3.8 years. Kidney stones information was collected by using a questionnaire and validated by medical records. The repeated biochemical measurements were performed to ascertain the metabolic status at both baseline and follow-up.Results4,017 incident total CVDs, 1,413 coronary heart diseases (CHDs) and 2,682 strokes were documented and ascertained during follow-up. Kidney stones presence was significantly associated with 44%, 70% and 31% higher risk of CVDs, CHDs and stroke, respectively. The stratified analysis showed significant associations were found in the incident and sustained MetS patients, while no significant associations were found in the non-MetS at both baseline and follow-up subjects or the MetS remission ones, especially in women. For the change status of each single component of the MetS, though the trends were not always the same, the associations with CVD were consistently significant in those with sustained metabolic disorders, except for the sustained high blood glucose group, while the associations were consistently significant in those with incident metabolic disorders except for the incident blood pressure group. We also found a significant association of kidney stone and CVD or CHD risk in the remain normal glucose or triglycerides groups; while the associations were consistently significant in those with incident metabolic disorders except for the incident blood pressure group. We also found a significant association of kidney stone and CVD or CHD risk in the remain normal glucose or triglycerides groups.ConclusionsA history of kidney stones in women with newly developed MetS or long-standing MetS associated with increased risk of CVD. The mechanisms link kidney stones and CVD risk in the metabolic and non-metabolic pathways were warranted for further studies.

AimTo determine the effect of decade-based body weight gain from 20 to 50 years of age on later life diabetes risk.Methods35,611 non-diabetic participants aged ≥ 50 years from a well-defined nationwide cohort were followed up for average of 3.6 years, with cardiovascular diseases and cancers at baseline were excluded. Body weight at 20, 30, 40, and 50 years was reported. The overall 30 years and each 10-year weight gain were calculated from the early and middle life. Cox regression models were used to estimate risks of incident diabetes.ResultsAfter 127,745.26 person-years of follow-up, 2,789 incident diabetes were identified (incidence rate, 2.18%) in 25,289 women (mean weight gain 20-50 years, 7.60 kg) and 10,322 men (7.93 kg). Each 10-kg weight gain over the 30 years was significantly associated with a 39.7% increased risk of incident diabetes (95% confidence interval [CI], 1.33-1.47); weight gain from 20-30 years showed a more prominent effect on the risk of developing diabetes before 60 years than that of after 60 years (Hazard ratio, HR = 1.084, 95% CI [1.049-1.121], P

In this study, the feasibility indicators of the injection of coke breeze for blast furnaces (BFs) were tested. Experiments were conducted on the combustion behavior of coke breeze at different particle sizes, and the effects of ratio of coke breeze in pulverized coal on the combustion performance of blends were studied. On the basis of the above experiments, industrial tests involving injecting coke breeze after milling were carried out in 3# BF of Shougang Jingtang. The results show that most of the coke breeze particle sizes were distributed above 1 mm. The grindability and combustion performance are poor, so the material needs to be ground before mixing with pulverized coal. The best combustibility can be obtained by using a particle size of less than 8.74 μm of coke breeze in the injection. With the increase in the coke breeze ratio, the combustion performance of blended coal worsened; the negative effects of coke breeze can be improved by increasing the proportion of bituminous coal. According to the results of industrial tests, 8% coke breeze in blends had no negative effect on the smelting state, and the output of the BF increased slightly. Industrial tests proved that coke breeze can partly replace anthracite for BF injecting, which reduced the cost of hot metal while realizing the high value-added resource utilization of coke breeze.

Soil moisture (SM) and land surface temperature (LST) are entangled, and the retrieval of one of them requires a priori specification of the other one. Due to insufficient observational information, retrieval of LST and SM from passive microwave remote sensing data is often ill-posed, and the retrieval accuracy needs to be improved. In this study, a novel fully-coupled paradigm is developed to robustly retrieve SM and LST from passive microwave data, which integrates deep learning, physical methods, and statistical methods. The key condition of the general paradigm proposed by us is that the output parameters of deep learning can be uniquely determined by the input parameters theoretically through a certain mathematical equation. Firstly, the physical method is deduced based on the energy radiation balance equation. The nine unknowns require the brightness temperatures of nine channels to construct nine equations, and the solutions of the physical method equations are obtained by model simulation. Based on the derivation of the physical method, the solution of the statistical method is constructed using multi-source data. Secondly, the solutions of physical and statistical methods constitute the training and test data of deep learning, which is used to obtain the solution curve of physical and statistical methods. The retrieval accuracy of LST and SM is greatly improved by smartly utilizing the mutual prior knowledge of SM and LST and cross iterative optimization calculations. Finally, validation indicates that the mean absolute error of the retrieved SM and LST data are 0.027 m3/m3 and 1.38 K, respectively, at an incidence angle of 0–65°. A model-data-knowledge-driven and deep learning method can overcome the shortcomings of traditional methods and provide a paradigm for retrieval of other geophysical variables. The proposed paradigm not only has physical meaning, but also makes deep learning physically interpretable, which is a milestone in the retrieval of geophysical remote sensing parameters based on artificial intelligence technology.

The rapid growth in the number of scholarly documents on the Web and in other digital platforms makes it challenging for researchers to find research publications most relevant to their information needs. This challenge has been mitigated to a greater extent by the major scholarly retrieval systems, such as Google Scholar, Semantic Scholar, PubMed, CiteSeerX, and others. The reason for the success of these retrieval solutions lies in the advances in ranking approaches. However, the existing studies advocate for the fact that we are still far from the method’s effectiveness ceiling, leaving ample room for further improvement to meet the scholarly needs of users. The existing methods adopt different approaches; some use classical Information Retrieval (IR), others use semantics-aware methods, including Knowledge Graph (KG) to support scholarly search. However, we hypothesize that combining the best of both worlds can further improve search relevance. In this context, this work incorporates inverted index from the classical IR with BM25 as the weighting scheme, combined with Citation Networks Analysis (CNA) for the baseline search results, which are then re-ranked by passing the selected entities from the top-k initial search results as the search query to the KG. This way, not only the textual content but also the structural semantics of the research publications are well exploited in the retrieval processes. The goal is to exploit IR and KG-based retrieval techniques to gain insights into the behavior of both textual and structured information in the strategic ranking of scholarly articles. The proposed solution has been evaluated using the ACL Anthology Network (AAN) dataset. The results show that the proposed technique can comparatively improve the retrieval performance in terms of Normalized Discounted Cumulative Gain (nDCG) and precision rates.

BackgroundWe aimed to evaluate the association between depression and major cardiovascular events and test whether the relationship between depression and cardiovascular events is influenced by lifestyle or metabolic risk factors.MethodsThe China Cardiometabolic Disease and Cancer Cohort (4C) Study was a nationwide, multicenter, prospective cohort study. About 92,869 participants without cardiovascular disease or cancer at baseline were included. Depression status was evaluated by the Patient Health Questionnaire-9 (PHQ-9). Lifestyle information was collected by the questionnaire, and metabolic risk factors including waist circumference, blood pressure, lipid profiles, and plasma glucose were measured. Major cardiovascular events including cardiovascular death, myocardial infarction, stroke, and hospitalized or treated heart failure events were validated based on medical records.ResultsDuring an average of 3.8 years of follow-up, we detected 2,076 cardiovascular events and showed that participants with depressive symptoms had an increased risk for cardiovascular events after adjustments [hazard ratio (HR): 1.29; 95% confidence index (CI): 1.08–1.53]. Stratified on metabolic risk status, the relationship between depression and cardiovascular events tended to be stronger according to the increasing numbers of metabolic risk factors, with HR (95% CI) of 0.98 (0.72–1.35) in the category with 0–2 metabolic risk factors, 1.36 (0.996–1.87) and 1.47 (1.13–1.92) for those with 3, and 4–5 metabolic risk factors, respectively, indicating an interaction effect (P = 0.039).ConclusionDepression was independently associated with an increased risk of major cardiovascular events. The effect was particularly prominent among populations at higher metabolic risk.

Summary: Background: The updated definition of hypertension by the American College of Cardiology (ACC) and the American Heart Association (AHA) is an important paradigm shift and has lead to extensive discussion. We aimed to examine the association between the updated blood pressure (BP) categories and the risk of cardiovascular diseases (CVDs) with potential modifications from other cardiovascular health metrics (CVHMs). Methods: This prospective study included 91,204 participants ≥40 years recruited from 20 community sites across mainland China. Participants were followed up during 2010-2016 for CVD events including nonfatal myocardial infarction, stroke, heart failure, and cardiovascular death. BP categories were defined according to the 2017 ACC/AHA guideline and CVHMs included smoking, physical activity, diet, body-mass index, total cholesterol, and fasting glucose. Findings: Overall, 1,985 major CVD events occurred during a mean follow-up of 3.7 years. Having more ideal CVHMs significantly reduced the risk of CVD events in both stage 1 and stage 2 hypertension. Compared with participants without hypertension, participants having ≥4 ideal CVHMs were no longer associated with an increased CVD risk in stage 1 hypertension (HR=1·04; 95% CI=0·83-1·31), but less so in stage 2 hypertension (HR=1·90, 95% CI=1·70-2·13). Such pattern of association was more evident in participants aged

Coke oven gas (COG) dome injection in COREX melter gasifier is recognized as one of effective method to reduce the amount of solid fuel used for gasification. In this work, a static model was developed to study the characteristics when COG is injected from dome. The critical bosh gas and critical fuel rate in COREX melter gasifier under different melting rate and coke rate were discussed. The amount of COG injection from dome under the critical fuel rates was studied. The results shows that when the heat of bosh gas reaching the critical value, the decrement of fuel rate decreases with the increase of melting rate and increases with the increase of coke rate. Under the critical fuel rate, the total volume of COG increases with the increase of melting rate and coke rate. After the COG injection, the amount and reduction capacity of the generator gas can meet the needs of reduction in shaft furnace. The findings of this work can be used as a theoretical basis to guide plant operations for COG injection.

Hepatocellular carcinoma (HCC) is the main subtype of primary liver cancer with high malignancy and poor prognosis. Metabolic reprogramming is a hallmark of cancer and has great importance on the tumor microenvironment (TME). As an abundant metabolite, lactate plays a crucial role in cancer progression and the immunosuppressive TME. Nonetheless, the potential roles of lactate in HCC remain unclear. In this study, we downloaded transcriptomic data of HCC patients with corresponding clinical information from the TCGA and ICGC portals. The TCGA-HCC dataset used as the training cohort, while the ICGC-LIRI-JP dataset was served as an external validation cohort. Cox regression analysis and the LASSO regression model were combined to construct the lactate metabolism-related gene signature (LMRGS). Then, we assessed the clinical significance of LMRGS in HCC. Besides, enriched molecular functions, tumor mutation burden (TMB), infiltrating immune cells, and immune checkpoint were comprehensively analyzed in different LMRGS subgroups. In total, 66 differentially expressed lactate metabolism-related genes (LMRGs) were screened. The functions of LMRGs were mainly enriched in mitochondrial activity and metabolic processes. The LMRGS comprised of six key LMRGs (FKTN, PDSS1, PET117, PUS1, RARS1, and RNASEH1) had significant clinical value for independently predicting the prognosis of HCC patients. The overall survival and median survival of patients in the LMRGS-high group were significantly shorter than in the LMRGS-low group. In addition, there were differences in TMB between the two LMRGS subgroups. The probability of genetic mutations was higher in the LMRGS-high group. Most importantly, the LMRGS reflected the TME characteristics. In the LMRGS-high group, the immune microenvironment presented a suppressed state, accompanied by more inhibitory immune cell infiltration, including follicular helper T cells and regulatory T cells. Additionally, the expression of inhibitory checkpoint molecules was much higher in the LMRGS-high group. Our study suggested that the LMRGS was a robust biomarker to predict the clinical outcomes and evaluate the TME of patients with HCC.

Passive microwave (PMW) sensors are popularly applied to Earth observations. However, the satellite PMW radiometer data sometimes have non-negligible errors in geolocation. Coastline inflection methods (CIMs) are widely used to improve geolocation errors of PMW images. However, they commonly require accuracy satellite flight parameters, which are difficult to obtain by users. In this study, a simplified coastline inflection method (SCIM) is proposed to correct the geolocation errors without demanding for the satellite flight parameters. SCIM is applied to improve geolocation errors of FengYun-3D (FY-3D) Microwave Radiation Imager (MWRI) brightness temperature images from 2018 and 2019. It reduces the geolocation errors of MWRI images to 0.15 pixels in the along-track and cross-track direction. This means reductions of 75% and 86% of the geolocation errors, respectively. The mean brightness temperature differences between the ascending and descending MWRI images are reduced by 34%, demonstrating the improved geolocation accuracy of SCIM. The corrected images are also used to estimate Arctic sea ice concentration (SIC). By comparing with SICs retrieved from the un-corrected images, the root mean square error (RMSE) and mean absolute error (MAE) of the SICs from the corrected images are reduced from 13.7% to 10.2% and 8.9% to 6.9%, respectively. The mean correlation coefficient (R) increases from 0.91 to 0.95. All these results indicate that SCIM can reduce geolocation errors of satellite-based PMW images significantly. As SCIM is very simple and easy to be applied, it could be a useful method for users of PMW images.

Abstract Background Portal vein system thrombosis (PVST) is potentially fatal for patients if the diagnosis is not timely or the treatment is not proper. There hasn’t been any available technique to detect clinic risk factors to predict PVST after splenectomy in cirrhotic patients. The aim of this study is to detect the clinic risk factors of PVST for splenectomy and cardia devascularization patients for liver cirrhosis and portal hypertension, and build an efficient predictive model to PVST via the detected risk factors, by introducing the machine learning method. We collected 92 clinic indexes of splenectomy plus cardia devascularization patients for cirrhosis and portal hypertension, and proposed a novel algorithm named as RFA-PVST (Risk Factor Analysis for PVST) to detect clinic risk indexes of PVST, then built a SVM (support vector machine) predictive model via the detected risk factors. The accuracy, sensitivity, specificity, precision, F-measure, FPR (false positive rate), FNR (false negative rate), FDR (false discovery rate), AUC (area under ROC curve) and MCC (Matthews correlation coefficient) were adopted to value the predictive power of the detected risk factors. The proposed RFA-PVST algorithm was compared to mRMR, SVM-RFE, Relief, S-weight and LLEScore. The statistic test was done to verify the significance of our RFA-PVST. Results Anticoagulant therapy and antiplatelet aggregation therapy are the top-2 risk clinic factors to PVST, followed by D-D (D dimer), CHOL (Cholesterol) and Ca (calcium). The SVM (support vector machine) model built on the clinic indexes including anticoagulant therapy, antiplatelet aggregation therapy, RBC (Red blood cell), D-D, CHOL, Ca, TT (thrombin time) and Weight factors has got pretty good predictive capability to PVST. It has got the highest PVST predictive accuracy of 0.89, and the best sensitivity, specificity, precision, F-measure, FNR, FPR, FDR and MCC of 1, 0.75, 0.85, 0.92, 0, 0.25, 0.15 and 0.8 respectively, and the comparable good AUC value of 0.84. The statistic test results demonstrate that there is a strong significant difference between our RFA-PVST and the compared algorithms, including mRMR, SVM-RFE, Relief, S-weight and LLEScore, that is to say, the risk indicators detected by our RFA-PVST are statistically significant. Conclusions The proposed novel RFA-PVST algorithm can detect the clinic risk factors of PVST effectively and easily. Its most contribution is that it can display all the clinic factors in a 2-dimensional space with independence and discernibility as y-axis and x-axis, respectively. Those clinic indexes in top-right corner of the 2-dimensional space are detected automatically as risk indicators. The predictive SVM model is powerful with the detected clinic risk factors of PVST. Our study can help medical doctors to make proper treatments or early diagnoses to PVST patients. This study brings the new idea to the study of clinic treatment for other diseases as well.

Summary: Background: National investigations on age-specific modifiable risk factor profiles for cardiovascular disease (CVD) and mortality are scarce in China, the country that is experiencing a huge cardiometabolic burden exacerbated by population ageing. Methods: This is a nationwide prospective cohort study of 193,846 adults in the China Cardiometabolic Disease and Cancer Cohort Study, 2011-2016. Among 139,925 participants free from CVD at baseline, we examined hazard ratios and population-attributable risk percentages (PAR%s) for CVD and all-cause mortality attributable to 12 modifiable socioeconomic, psychosocial, lifestyle, and metabolic risk factors by four age groups (40-

A static model of blast furnace operation of natural gas (NG) injection was developed. The effect of NG injection on the raceway adiabatic flame temperature, the amount and composition of bosh gas, the direct reduction degree and fuel ratio were studied. The results showed that under no thermal compensation, the heat loss of the whole blast furnace increases, which means the heat surplus of the whole furnace is sufficient. However, the heat in the high-temperature zone of the blast furnace is insufficient, showing the characteristics of “cold at bottom and hot at the top”. Based on the comparison of heat loss in the high-temperature zone after NG injection with the reference condition, if the heat loss is consistent with the reference case, the suitable NG injection volumes are 17.3, 34.6, 52 and 69.3 m3/t when the coal ratio is reduced by 20, 40, 60 and 80 kg/t, respectively. With the increase of the suitable NG injection volumes, the adiabatic flame temperature gradually decreases, the amount of bosh gas slightly increases, and the overall fuel ratio reduces gradually. The effect of other thermal compensation operations, such as increasing blast temperature and addition of oxygen on the NG injection, were also investigated. The findings of this work can be used as a theoretical basis to guide plant operations for NG injection in blast furnaces.

Summary: Background: National investigations of age-specific modifiable risk profiles for diabetes are crucial to promote personalised strategies for the prevention and control of diabetes, particularly in countries such as China, which is experiencing both a diabetes epidemic and a rapidly ageing population. We aimed to examine the associations of 12 potentially modifiable socioeconomic, lifestyle, and metabolic risk factors with diabetes in a nationwide prospective cohort of Chinese adults across four age groups. Methods: We analysed data from the China Cardiometabolic Disease and Cancer Cohort Study, a nationwide, population-based, cohort study done between Jan 1, 2011, and Dec 31, 2016. Among 93 781 participants without diabetes at baseline and with complete information available about risk factors and diabetes incidence, we examined the hazard ratios (HRs) and population-attributable risk percentages (PAR%s) of incident diabetes associated with 12 potentially modifiable risk factors: two socioeconomic risk factors (less education and intermediate or low grade occupation), five lifestyle risk factors (unhealthy diet, physical inactivity, current alcohol consumption, current smoking, and unhealthy sleep), and five metabolic risk factors (general or central obesity, insulin resistance, prediabetes, hypertension, and dyslipidaemia) across four age groups (40 to

ObjectivesNationwide studies focusing on the impact of early-onset type 2 diabetes and obesity on the development of cardiovascular diseases (CVD) are limited in China. We aimed to investigate the association between age at diagnosis of type 2 diabetes and the risk of CVD, and to further examine the modifying effect of obesity on this association among Chinese adults.MethodsThis study included 23,961 participants with previously diagnosed diabetes from a large nationwide population-based cohort study across mainland China. With an interviewer-assisted questionnaire, we collected detailed information on CVDs. Logistic regression analysis was used to evaluate the risk of CVDs associated with age at diagnosis of diabetes.ResultsCompared with patients with late-onset diabetes (≥60 years), those with earlier-onset diabetes had increased risks for CVD, with adjusted ORs (95% CIs) of 1.72 (1.36-2.17), 1.52 (1.31-1.75) and 1.33 (1.19-1.48) for patients diagnosed aged

Spalling and pitting are prone to be produced on the tooth surfaces in the meshing process, which seriously affects the stability and reliability of gear meshing. The time-varying meshing stiffness model and six-degree-of-freedom model of gear meshing are established, the Matlab wavelet toolbox is used to generate an adaptive wavelet which is similar to the original signal. The time frequency characteristic change rule of vibration signal is illustrated. Agreement between the results of the dynamic model and the experimental results validates the effectiveness of the generated adaptive wavelet method which is used to analyze the spalling defect. The results provide theoretical basis and practical support for the gear defect size identification in black-box condition.

Snow depth estimation with passive microwave (PM) remote sensing is challenged by spatial variations in the Earth’s surface, e.g., snow metamorphism, land cover types, and topography. Thus, traditional static snow depth retrieval algorithms cannot capture snow thickness well. In this study, we present a new operational retrieval algorithm, hereafter referred to as the pixel-based method (0.25° × 0.25° grid-level), to provide more accurate and nearly real-time snow depth estimates. First, the reference snow depth was retrieved using a previously proposed model in which a microwave snow emission model was coupled with a machine learning (ML) approach. In this process, an effective grain size (effGS) value was optimized by utilizing the snow microwave emission model, and then the nonlinear relationship between snow depth and multiple predictive variables, e.g., effGS, longitude, elevation, and brightness temperature (Tb) gradients, was established with the ML technique to retrieve reference snow depth data. To select a robust and well-performing ML approach, we compared the performance of widely used support vector regression (SVR), artificial neural network (ANN) and random forest (RF) algorithms over China. The results show that the three ML models performed similarly in snow depth estimation, which was attributed to the inclusion of effGS in the training samples. In this study, the RF model was used to retrieve the snow depth reference dataset due to its slightly stronger robustness according to our comparison of results. Second, the pixel-based algorithm was built based on the retrieved reference snow depth dataset and satellite Tb observations (18.7 GHz and 36.5 GHz) from Advanced Microwave Scanning Radiometer 2 (AMSR2) during the 2012–2020 period. For the pixel-based algorithm, the fitting coefficients were achieved dynamically pixel by pixel, making it superior to the traditional static methods. Third, the built pixel-based algorithm was verified using ground-based observations and was compared to the AMSR2, GlobSnow-v3.0, and ERA5-land products during the 2012–2020 period. The pixel-based algorithm exhibited an overall unbiased root mean square error (unRMSE) and R2 of 5.8 cm and 0.65, respectively, outperforming GlobSnow-v3.0, with unRMSE and R2 values of 9.2 cm and 0.22, AMSR2, with unRMSE and R2 values of 18.5 cm and 0.13, and ERA5-land, with unRMSE and R2 values of 10.5 cm and 0.33, respectively. However, the pixel-based algorithm estimates were still challenged by the complex terrain, e.g., the unRMSE was up to 17.4 cm near the Tien Shan Mountains. The proposed pixel-based algorithm in this study is a simple and operational method that can retrieve accurate snow depths based solely on spaceborne PM data in comparatively flat areas.

Three Microwave Radiation Imagers (MWRI) were carried onboard the FengYun-3B/C/D satellites and have collected more than 10 years of data since 2010. To create a robust climate quality of data, MWRI level one data were reprocessed with new calibration. This study evaluates the performance of retrieving global soil moisture from recalibrated MWRI data (RCD) and quantifies the difference of retrieved soil moisture between operational calibration data (OCD) and RCD. Soil Moisture Operational Products System (SMOPS) products from NOAA on four days of different seasons were collocated with MWRI brightness temperatures, and then the collocated data were used for training an algorithm through machine learning. The retrieved soil moisture products using OCD and RCD were evaluated against the independent SMOPS products, in situ networks and SMAP soil moisture product. It is shown that the algorithm from the random forest is suitable for FY-3D recalibrated MWRI data, with a coefficient of determination (R2) of 0.7223, a mean bias of −0.0062 and an unbiased root mean square difference (ubRMSD) of 0.0476 m3 m−3 compared with SMOPS products over the period from 12 July 2018 to 31 December 2019. The difference of retrieved soil moisture using OCD and RCD is spatially heterogeneous. Both temporal and spatial coverage and accuracy of the existing FY-3D operational soil moisture products are significantly improved.

Abstract Silicon-rich silicon oxide (SRSO) film was prepared through the deposition of SiOx film by radio-frequency reactive magnetron sputtering from a Si target and the subsequent rapid thermal annealing treatment of SiOx film, and planar-type field emission cathodes based on SRSO film were fabricated. The surface morphologies and electron emission properties of the SRSO films deposited under different O2/Ar flow ratios were investigated. The experimental results show that a relatively high O2/Ar flow ratio during the deposition of SiOx film can lead to the formation of cluster structure in the SRSO film prepared, and the electron emission efficiency of SRSO film rises with the increase of electric field applied. An SRSO-film cathode fabricated under an O2/Ar flow ratio of 1:1 with a chamber pressure of 0.21 Pa has an emission current density of 65.61 μA/cm2 and a corresponding emission efficiency of 0.53% at a bias voltage of 18 V, and it exhibits relatively stable emission and fine emission uniformity.

Background Previous studies reported that early‐life exposure to undernutrition is associated with the risk of diabetes mellitus and metabolic syndrome in adulthood, but the association with risk of cardiovascular disease (CVD) later in life remains unclear. The current study aimed to investigate whether exposure to Chinese famine in early life is associated with risk of CVD. Methods and Results We used data from REACTION (Risk Evaluation of Cancers in Chinese Diabetic Individuals: A Longitudinal Study), which recruited a total of 259 657 community‐dwelling adults aged 40 years or older from 25 centers across mainland China between 2011 and 2012. Compared with the nonexposed participants, those who had been exposed to famine in early life had a significantly increased risk of total CVD, myocardial infarction, stroke, and coronary heart disease. In the multivariable‐adjusted logistic regression model, the odds ratios (95% CI) for total CVD, myocardial infarction, stroke, and coronary heart disease in fetal famine exposure were 1.35 (1.20–1.52), 1.59 (1.08–2.35), 1.40 (1.11–1.78), and 1.44 (1.26–1.65), respectively; those odds ratios in childhood famine exposure were 1.59 (1.40–1.81), 2.20 (1.52–3.20), 1.82 (1.45–2.28), and 1.80 (1.56–2.09), respectively; and those in adolescent famine exposure were 1.52 (1.27–1.81), 2.07 (1.28–3.35), 1.92 (1.42–2.58), and 1.83 (1.50–2.24), respectively. The main finding of our study is that, compared with those who lived in the less severely affected famine area, individuals in the severely affected famine area had significantly increased risk of total CVD in all 3 exposed groups. Conclusions Early‐life exposure to undernutrition is associated with significantly increased risk of CVD in later life, especially among those who were in the severely affected famine area.

Ionic liquids (ILs) are used as electrolytes in high-performance lithium-ion batteries, which can effectively improve battery safety and energy storage capacity. All atom molecular dynamics simulation and experiment were combined to investigate the effect of the concentration of lithium salt on the performance of electrolytes of four IL solvents ([Cnmim][TFSI] and [Cnmim][FSI], n = 2, 4). The IL electrolytes exhibit higher density and viscosity; meanwhile, larger lithium ion transfer numbers as the concentration of LiTFSI increases. Furthermore, in order to explore the effect of the concentration of lithium salt on the ionic associations of Li+ and anion of IL, the microstructures of the lithium salt in various IL electrolytes at different concentrations were investigated. The structural analysis indicated that strong bidentate and monodentate coordination was found between Li+ and anion of all IL electrolytes. Both cis and trans isomerism of [FSI]− were observed in [FSI]−-type IL electrolyte systems. Furthermore, the existence of the ion cluster [Li[anion]x](x−1)− in IL electrolytes and the cluster became more closed and compact as the concentration of LiTFSI increases.

A new kind of temperature sensor based on a vacuum diode was proposed and numerically studied in this paper. This device operated under different electron emission mechanisms according to the electron density in the vacuum channel. The temperature determination ability of this device was only empowered when working in the electric-field-assisted thermionic emission regime (barrier-lowering effect). The simulated results indicated that the temperature-sensing range of this device was around 273 K–325 K with a supply current of 1 μA. To obtain a linear dependency of voltage on temperature, we designed a proportional-to-absolute-temperature (PTAT) circuit. The mathematic derivation of the PTAT voltage is presented in this study. The temperature-sensing sensitivity was calculated as 7.6 mV/K according to the measured I-U (current versus voltage) characteristic. The structure and principle of the device presented in this paper might provide an alternative method for the study of temperature sensors.

Microwave land surface emissivity (MLSE) is an important geophysical parameter to determine the microwave radiative transfer over land and has broad applications in satellite remote sensing of atmospheric parameters (e.g., precipitation, cloud properties), land surface parameters (e.g., soil moisture, vegetation properties), and the parameters of interactions between atmosphere and terrestrial ecosystem (e.g., evapotranspiration rate, gross primary production rate). In this study, MLSE in China under both clear and cloudy sky conditions was retrieved using satellite passive microwave measurements from Aqua Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E), combined with visible/infrared observations from Aqua Moderate Resolution Imaging Spectroradiometer (MODIS), and the European Centre for Medium-Range Weather Forecasts (ECMWF) atmosphere reanalysis dataset of ERA-20C. Attenuations from atmospheric oxygen and water vapor, as well as the emissions and scatterings from cloud particles are taken into account using a microwave radiation transfer model to do atmosphere corrections. All cloud parameters needed are derived from MODIS visible and infrared instantaneous measurements. Ancillary surface skin temperature as well as atmospheric temperature-humidity profiles are collected from ECMWF reanalysis data. Quality control and sensitivity analyses were conducted for the input variables of surface skin temperature, air temperature, and atmospheric humidity. The ground-based validations show acceptable biases of primary input parameters (skin temperature, 2 m air temperature, near surface relative humidity, rain flag) for retrieving using. The subsequent sensitivity tests suggest that 10 K bias of skin temperature or observed brightness temperature may result in a 4% (~0.04) or 7% (0.07) retrieving error in MLSE at 23.5 GHz. A nonlinear sensitivity in the same magnitude is found for air temperature perturbation, while the sensitivity is less than 1% for 300 g/m2 error in cloud water path. Results show that our algorithm can successfully retrieve MLSE over 90% of the satellite detected land surface area in a typical cloudy day (cloud fraction of 64%), which is considerably higher than that of the 29% area by the clear-sky only algorithms. The spatial distribution of MLSE in China is highly dependent on the land surface types and topography. The retrieved MLSE is assessed by compared with other existing clear-sky AMSR-E emissivity products and the vegetation optical depth (VOD) product. Overall, high consistencies are shown for the MLSE retrieved in this study with other AMSR-E emissivity products across China though noticeable discrepancies are observed in Tibetan Plateau and Qinling-Taihang Mountains due to different sources of input skin temperature. In addition, the retrieved MLSE exhibits strong positive correlations in spatial patterns with microwave vegetation optical depth reported in the literature.

Vacuum diodes, based on field emission mechanisms, demonstrate a superior performance in high-temperature operations compared to solid-state devices. However, when considering low operating voltage and continuous miniaturization, the cathode is usually made into a tip structure and the gap between cathode and anode is reduced to a nanoscale. This greatly increases the difficulty of preparation and makes it difficult to ensure fabrication consistency. Here, a metal-insulator-semiconductor (MIS) structural nanoscale vacuum diode, based on thermionic emission, was numerically studied. The results indicate that this device can operate at a stable level in a wide range of temperatures, at around 600 degrees Kelvin above 260 K at 0.2 V voltage bias. Moreover, unlike the conventional vacuum diodes working in field emission regime where the emission current is extremely sensitive to the gap-width between the cathode and the anode, the emission current of the proposed diode shows a weak correlation to the gap-width. These features make this diode a promising alternative to vacuum electronics for large-scale production and harsh environmental applications.

Lymphocyte‐specific protein 1 (LSP1) has been reported to regulate cell biology in several human cancers including lymphoma and breast cancer. However, the functions of LSP1 in human hepatocellular carcinoma (HCC) are still unknown. In this study, we found that LSP1 expression was downregulated in HCC tissues and cell lines, and lower LSP1 expression was correlated with poor clinicopathological features including large tumor size, high Edmondson–Steiner grading and advanced tumor–node–metastasis (TNM) stage. Additionally, we demonstrated that patients with high LSP1 expression had significantly better overall survival and disease‐free survival. Moreover, LSP1 was found to be an independent factor for predicting the prognosis of HCC patients. In vitro and in vivo assays showed that overexpressing LSP1 inhibited HCC growth by inducing both apoptosis and growth arrest. Mechanistically, we found that expression of phosphorylated extracellular regulated protein kinases 1 and 2 (ERK1/2) was downregulated after LSP1 overexpression, indicating LSP1 could suppress HCC growth by inhibiting the ERK pathway in HCC cells. Taken together, these results indicate that LSP1 may serve as a prognostic marker and a potential therapeutic target in human HCC.

IGZO thin films can be used as active layers of thin-film transistors and have been widely studied. However, amorphous indium gallium zinc oxide (IGZO) fabricated at room temperature is vulnerable in subsequent manufacturing processes, such as etching and sputtering; this limits IGZO thin film transistors’ (TFTs) use in commercial products. In this paper, we prepared a c-axis crystallized IGZO thin film by Radio Frequency (RF) sputtering at 180 °C, with a 50% O2 ratio and 110 W power. XRD images show that the crystallized film has an obvious diffraction peak near 31°, and the spacing between the crystal surfaces was calculated to be ≈0.29 nm. The HRTEM map confirmed the above results. The stability of IGZO thin films was investigated by etching them with an acid solution. The crystalline IGZO films exhibited better acid corrosion resistance, and their anticorrosion performance was 74% higher than that of amorphous IGZO (a-IGZO) films, indicating the crystalline IGZO film can provide more stable performance in applications.

Surface activated bonding (SAB) based on argon ion beam irradiation was used to directly bond Si and Si wafers at room temperature, and the effects of the surface activation time on the Si-Si bonding were investigated. The experimental results show that the surface activation treatment with a proper duration is beneficial to the reduction of surface roughness of Si wafers and the realization of high bonding strength. The Si-Si wafers bonded after the surface activation of 420 s has an extremely low percentage of area covered by voids (0.08%) and a high bonding strength (9.45 MPa). Meanwhile, the annealing at 500 °C does not lead to a significant change in the percentage of area covered by voids for Si-Si bonding. Besides, the transmission electron microscope characterization indicates that the argon ion beam irradiation of 180 s can result in the formation of an amorphous Si layer with a thickness of approximately 10.6 nm at the Si-Si bonding interface, and the whole cross-section structure of the Si-Si bonding consists of a Si substrate, an amorphous Si layer and a Si substrate.

To improve the electron-induced secondary electron emission (SEE) properties of MgO/Au composite film, the strategy of Al doping in the MgO surface layer is adopted and investigated. For an MgO/Au film, Al doping in its MgO surface layer results in a slight increase of its grain size as well as a reduction of its surface roughness according to microstructure characterizations and also causes the decreases of both the band gap and work function of MgO crystal on the basis of the first-principles calculations, all of which have a close relationship with the improvement of secondary electron yield (SEY) demonstrated by the SEE measurement. An MgO/Au film including an Al-doped MgO surface layer with a doping ratio of 4.4% has an SEY of 4.7 with an increase of 14.6% at a primary electron energy (Ep) of 200 eV and the maximum SEY of 10.4 with an increase of 8.3% at Ep of 1100 eV in comparison with an MgO/Au film including an undoped MgO surface layer.

Oxidative stress has been demonstrated to be involved in the etiology of alcoholic fatty liver disease (AFLD). Previous studies had demonstrated that resveratrol (RES) could reduce oxidative stress by different mechanisms. However, the effect of RES on alcohol-induced fatty liver remains unclear. In the present study, a total of 48 male SD rats were divided into three groups: Control, AFLD, and RES groups. Rats were administered with either nothing or 65% vol/vol alcohol (5 ml/kg/day in the first three days, and then 10 ml/kg/day in the following days) with or without RES supplementation (250 mg/kg/day) for 4 weeks. Blood and liver tissue samples were collected and subjected to biochemical assays, histological examination, Western blot, and mitochondrial radical oxygen species (ROS) assays. In RES group, significant decreases in serum ALT and AST concentrations, fat deposition, triglyceride (TG) content, HIF-1α protein expression as well as mitochondrial ROS production in liver were observed when compared with AFLD group (all p