Little is known with regard to the occurrence of potentially toxic chemicals in textiles and clothes. In this study, 77 textiles and infant clothing pieces were analyzed for the determination of ...bisphenols including bisphenol A (BPA) and bisphenol S (BPS), benzophenones, bisphenol A diglycidyl ethers (BADGEs), and novolac glycidyl ethers (NOGEs). BPA and BPS occurred in 82% and 53% of the textile samples, respectively, and at mean concentrations of 366 and 15 ng/g, respectively. Benzophenone-3 (BP3) occurred in 70% of the samples at a mean concentration of 11.3 ng/g. Among 11 BADGEs and NOGEs analyzed, BFDGE was the predominant compound, with a mean concentration of 13.6 ng/g. Concentrations of target chemicals were assessed by fabric type, color, and uses. Socks contained the highest concentrations of BPA (mean: 1810 ng/g) with concentrations as high as 13 300 ng/g in a 97% polyester fabric marketed for infants. Calculated dermal exposure dose to BPA by infants via textiles was as high as 7280 pg/kg BW/d. This is the first study to report the occurrence of, and exposure to, BPA, BPS, BADGEs, and NOGEs in textiles and clothing.
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IJS, KILJ, NUK, PNG, UL, UM
Micro-expression recognition (MER) is a growing field of research which is currently in its early stage of development. Unlike conventional macro-expressions, micro-expressions occur at a very short ...duration and are elicited in a spontaneous manner from emotional stimuli. While existing methods for solving MER are largely non-deep-learning-based methods, deep convolutional neural network (CNN) has shown to work very well on such as face recognition, facial expression recognition, and action recognition. In this article, we propose applying the 3D flow-based CNNs model for video-based micro-expression recognition, which extracts deeply learned features that are able to characterize fine motion flow arising from minute facial movements. Results from comprehensive experiments on three benchmark datasets—SMIC, CASME/CASME II, showed a marked improvement over state-of-the-art methods, hence proving the effectiveness of our fairly easy CNN model as the deep learning benchmark for facial MER.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OBVAL, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
About this supplement This article has been published as part of BMC Bioinformatics Volume 20 Supplement 22, 2019: Decipher computational analytics in digital health and precision medicine. The full ...contents of the supplement are available online at https://bmcbioinformatics.biomedcentral.com/articles/supplements/volume-20-supplement-22 . Funding This study and publication costs were supported in part by the National Natural Science Foundation of China under Grant No. 61572367 and 61573017.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
•Develop a stepwise scheme for mapping rapeseed with multi-source data and GEE.•Estimate annual peak flowering dates of rapeseed to facilitate extent mapping.•Interpret the geographical ...differentiation of flowering phenology in rapeseed.•Reveal the spatio-temporal cropping pattern of rapeseed fields.•First multiyear field-level rapeseed maps at 10-m resolution for the YREB.
Knowledge on the distribution of rapeseed enables accurate yield forecasting and supports agricultural planning to assist global security in edible oil supply. Large-scale remotely sensed maps of rapeseed nevertheless are non-existent in China because of landscape fragmentation, cloudy weather conditions, and phenological variations. Existing rapeseed mapping methods based on spectral, phenological, and machine learning algorithms are challenging to accurately and seamlessly extract the planting distribution of rapeseed over a large spatial region. In view of this, the annual extent of rapeseed in the Yangtze River Economic Belt (YREB) of China from 2017 to 2021 was mapped. Multisource data including Sentinel-1/2, Google Earth very-high-resolution (GE-VHR) images, and Global Land Data Assimilation System (GLDAS) data were used to develop a systematic methodology. First, the ground reference dataset was collected from fieldwork and all available GE-VHR images to construct a rapeseed point collection (RPC). Second, RPC, Sentinel-1, and GLDAS data were used to estimate the annual rapeseed peak-flowering date maps (RPDMs) based on a random forest regression model. Third, a hybrid mapping strategy was implemented on Google Earth Engine leveraging the dense Sentinel-1/2 data to generate the annual seamless 10 m rapeseed extent maps (REMs). Accuracy assessment illustrates the reliability of the RPDM with an R2 of 0.86 (RMSE = 5.32 days). Comparisons with other rapeseed mapping methods and comprehensive validation attest to the high precision of the REMs, with an average F1 score of 0.93. Moreover, the rapeseed cultivation area decreased over the five study years. Rapeseed fields in the YREB are highly fragmented, averaging 18 per ha, but trend analysis suggests a potential for crop intensification. This study provides an essential reference and information service for rapeseed production and agricultural resource survey in China.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Remote sensing based vegetation index provides a practical method for the monitoring of vegetation dynamics at regional and global scales. Here, using a long-term remotely sensed normalized ...difference vegetation index (NDVI) dataset, we quantified the vegetation changes in the Loess Plateau (LP) over the last three decades (1982–2015), which includes the period before the Chinese“Grain for Green Program”(GGP) was launched (1982–1999), and the period after the GGP (1999–2015). The correlations between the NDVI and four climate related variables, i.e., precipitation, temperature, root-soil moisture (RSM), and a drought proxy-standardized evapotranspiration deficit index (SEDI), were also examined. The results indicated that, (i) the GGP strongly changed the vegetation in the LP. The growing-season mean NDVI (GSM-NDVI) and the annual mean NDVI (AM-NDVI) decreased slightly before the GGP launched in 1999, with slopes of −3.38×10−3 and−8.00×10−4year−1, respectively. However, they showed slight and significant (p<0.05) increases after the GGP, with slopes of 4.75×10−3 and 2.32×10−3year−1, respectively. (ii) Climate change (i.e., warming and drying) resulted in adverse effects on vegetation in the LP during the period before the GGP. However, the observed changes (i.e., wetting and reduced drought) exerted positive effects on the vegetation during the period after the GGP. (iii) Inter-annual variations of spatially averaged NDVI over the LP were primarily determined by RSM rather than any other climate related variables. In the southeastern LP, the inter-annual variation of GSM-NDVI was mainly determined by precipitation and SEDI, while the inter-annual variation of AM-NDVI was mainly caused by SEDI and RSM. Inter-annual variations of both GSM-NDVI and AM-NDVI were mainly determined by SEDI and RSM in the northwestern LP, and by temperature in the southwestern LP.
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•The Grain for Green Program (GGP) greatly changed vegetation in the Loess Plateau.•Climate changes exerted adverse effects on vegetation in the LP before the GGP.•Wetting and reduced drought positively affected vegetation in the LP after the GGP.•The inter-annual variation of NDVI was primarily determined by soil moisture.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Dislocation transmission across grain boundary (GB) and activation of dislocation source in adjacent grains are considered common features of dislocation-GB interactions in regulating mechanical ...properties and behaviors of metallic materials and structures. However, it is currently unclear which of dislocation transmission and dislocation source activation plays the dominant role in regulating dislocation-GB interaction. To study the competition between dislocation transmission and dislocation source activation, a theoretical framework is established based on a dislocation pile-up model. It is found that both dislocation transmission and dislocation source activation exhibit strong dependence on the GB misorientation angle. The critical transmission stress derived based on an energy method also depends on the grain size in a scaling form similar to the Hall-Petch relation. The outgoing slip systems during dislocation transmission are successfully predicted and agree with experimental observations. Regarding the dislocation source activation, the critical activation stress is investigated by examining the local stress fields generated by single and multiple slip dislocation pile-ups. It is found that compared with single slip dislocation pile-up, the result of multiple slip dislocation pile-ups displays lower critical activation stresses and exhibits feature of sensitivity to loading direction, interpreting the reported results of dislocation source activation in polycrystals. Further comparison between dislocation transmission and dislocation source activation for ⟨100⟩ tilt GBs indicates that the dislocation transmission prevails at low angle GB, while dislocation source activation is prone to occur at high angle GB. Our theoretical studies quantify the dislocation-GB interaction induced by dislocation pile-ups, shed light on the competition between dislocation transmission and dislocation source activation, and might provide essential guidance for high-performance metallic material design.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Despite there is growing evidence focusing on health inequalities in China, socioeconomic inequalities in cognitive impairment among older adults have received little attention. This study aims to ...measure socioeconomic inequalities in cognitive impairment among Chinese older adults, and determine the contributing social factors to the inequalities.
A cross-sectional analysis was performed using data from the 2018 Chinese Longitudinal Healthy Longevity Survey (CLHLS). A total of 10,556 older adults aged 65 and over were included in the study. The prevalence of cognitive impairment was measured by using the Chinese version of the Mini-Mental State Examination. The socioeconomic inequalities in cognitive impairment were illustrated and quantified by the concentration curve and normalized concentration index. Multivariate logistic regression was conducted to identify the associated factors of cognitive impairment. And decomposition analysis was further applied to decompose the contribution of each determinant to the observed inequalities in cognitive impairment.
The study indicated that the prevalence of cognitive impairment among Chinese older adults was 18.95%. The overall concentration index for cognitive impairment was - 0.046, which suggested a higher concentration of cognitive impairment among socioeconomically disadvantaged older adults. The results showed the prevalence of cognitive impairment was associated with sex, age, marital status, education level, occupation, economic status, emotional support, financial support, living arrangement, and participation in informal activities. Decomposition results further revealed the contributions of the determinants to the inequalities in cognitive impairment. Specifically, age (131.61%), marital status (85.68%), emotional support (84.85%), education level (39.73%), occupation (21.24%), sex (17.25%), financial support (- 4.19%), economic status (1.02%), living arrangement (0.88%), and informal activities (0.30%) have varying degrees of contributions to the inequality in cognitive impairment.
This study sheds light on the pro-rich inequality in cognitive impairment among older adults in China. It suggests that policymakers should pay more attention to older adults who are female, old-old, widowed, illiterate, economically disadvantaged, with no social support, and less socially involved. Also, more targeted interventions should be undertaken to improve the socioeconomic conditions of these vulnerable individuals and strengthen their ability to cope with the risk of cognitive impairment.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
► This definition of extreme precipitation events has been first time applied in China. ► The relationships between extreme rainfall and climatic variability index are investigated. ► The ...relationships between extreme rainfall and annual rainfall/number of rainfall days are explored.
The spatial and temporal variability of the frequency of extreme precipitation events in China for 1961–2009 was examined using the high quality rainfall dataset provided by the China Meteorology Administration (CMA) for 599 stations. Extreme events were defined by duration and recurrence interval, the event durations chosen were 1, 5, 10 and 30days and the event thresholds were those associated with recurrence intervals of 1, 5 and 10years. The results indicated that temporal variations of extreme precipitation index (EPI) showed interannual and interdecadal variability. Time series of anomalies of the nine regional EPI indices indicated that Northeast China, North China and the Yellow River basin had experienced a decreasing trend of extreme rainfall events during the last 50years, while other six regions, namely the Yangtze River basin, Southeast Coast, South China, the Inner Mongolia, Northwest China and Tibetan Plateau, had experienced an increasing trend of extreme rainfall events. Seasonal results indicated that 95.6% of 1-day, 1-yr recurrence interval extreme rainfall events occurred from April to September in China. The possible attributions of trend and variability of extreme rainfall events at China include, but are not limited to, El Niño – Southern Oscillation (ENSO), the magnitude of East Asian Monsoon, wind circulations, as well as global warming. Obviously these factors are not independent. For example, it has long been recognized that ENSO can exert an important impact on the East Asian monsoon.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
•Annual performances of nine ET products were evaluated in 35 global river basins.•A water balance method corrected for the water storage change at annual time scale is used.•All ET products ...performed better in dry basins than in wet basins.•Most products could not adequately estimate the inter-annual variability and trends of ETwb.
Evapotranspiration (ET) plays a critical role in linking the water and energy cycles but is difficult to estimate at regional and basin scales. In this study, we present a worldwide evaluation of nine ET products (three diagnostic products, three land surface model (LSM) simulations and three reanalysis-based products) against reference ET (ETwb) calculated using the water balance method corrected for the water storage change at an annual time scale over the period 1983–2006 for 35 global river basins. The results indicated that there was no significant intra-category discrepancy in the annual ET estimates for the 35 basins calculated using the different products in 35 basins, but some products performed better than others, such as the Global Land surface Evaporation estimated using the Amsterdam Methodology (GLEAM_E) in the diagnostic products, ET obtained from the Global Land Data Assimilation System version 1 (GLDAS 1) with the Community Land Model scheme (GCLM_E) in LSM simulations, and ET from the National Aeronautics and Space Administration (NASA) Modern Era Retrospective-analysis for Research and Applications reanalysis dataset (MERRA_E) in the reanalysis-based products. Almost all ET products (except MERRA_E) reasonably estimated the annual means (especially in the dry basins) but systematically underestimated the inter-annual variability (except for MERRA_E, GCLM_E and ET simulation from the GLDAS 1 with the MOSAIC scheme – GMOS_E) and could not adequately estimate the trends (e.g. GCLM_E and MERRA_E) of ETwb (especially in the energy-limited wet basins). The uncertainties in nine ET products may be primarily attributed to the discrepancies in the forcing datasets and model structural limitations. The enhancements of global forcing data (meteorological data, solar radiation, soil moisture stress and water storage changes) and model physics (reasonable consideration of the water and energy balance and vegetation processes such as canopy interception loss) will undoubtedly improve the estimation of global ET in the future.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
Recently, the potential role of gut microbiome in metabolic diseases has been revealed, especially in cardiovascular diseases. Hypertension is one of the most prevalent cardiovascular diseases ...worldwide, yet whether gut microbiota dysbiosis participates in the development of hypertension remains largely unknown. To investigate this issue, we carried out comprehensive metagenomic and metabolomic analyses in a cohort of 41 healthy controls, 56 subjects with pre-hypertension, 99 individuals with primary hypertension, and performed fecal microbiota transplantation from patients to germ-free mice.
Compared to the healthy controls, we found dramatically decreased microbial richness and diversity, Prevotella-dominated gut enterotype, distinct metagenomic composition with reduced bacteria associated with healthy status and overgrowth of bacteria such as Prevotella and Klebsiella, and disease-linked microbial function in both pre-hypertensive and hypertensive populations. Unexpectedly, the microbiome characteristic in pre-hypertension group was quite similar to that in hypertension. The metabolism changes of host with pre-hypertension or hypertension were identified to be closely linked to gut microbiome dysbiosis. And a disease classifier based on microbiota and metabolites was constructed to discriminate pre-hypertensive and hypertensive individuals from controls accurately. Furthermore, by fecal transplantation from hypertensive human donors to germ-free mice, elevated blood pressure was observed to be transferrable through microbiota, and the direct influence of gut microbiota on blood pressure of the host was demonstrated.
Overall, our results describe a novel causal role of aberrant gut microbiota in contributing to the pathogenesis of hypertension. And the significance of early intervention for pre-hypertension was emphasized.
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