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Abstract Background The objective of this research is to statistically assess the risk of cardiovascular mortality (CVM) between patients with small bowel adenocarcinoma (SBA) and the general population. Additionally, it aims to identify CVM-associated risk factors among individuals with SBA. Methods Data obtained between 2000 and 2017 on SBA patients from the Surveillance, Epidemiology, and End Results (SEER) database were examined. Standardized mortality ratios (SMRs) and absolute excess risks (AERs) were obtained to compare CVM between patients and the general US population. To evaluate the cumulative mortality (CM) rate for all causes of death (COD), cumulative hazard curves were constructed. Two multivariate competing risk models were established to determine the independent predictors for CVM. Results In the cohort of 5,175 SBA patients observed for 15,068.24 person-years, a total of 205 deaths were attributed to cardiovascular disease (CVD). The overall SMR of CVM was 1.41 (95% confidence interval (CI): 1.23–1.62, P

Abstract Bergenia purpurascens is an important medicinal, edible and ornamental plant. The lack of omics information hinders the study of its metabolic pathways and related genes. In order to investigate candidate genes and pathways involved in secondary metabolism in B. purpurascens, roots, stems and leaves of B. purpurascens were subjected to metabolomic and transcriptomic analyses in this study. A total of 351 differentially accumulated secondary metabolites were identified. We identified 120 candidate genes involved in phenylpropanoid and flavonoid biosynthesis pathway, from which 29 key candidate genes were obtained by WGCNA. Five UDP-Glycosyltransferases and four O-methyltransferases were suggested to be the candidate enzymes involved in synthetic pathway from gallic acid to bergenin by correlation analysis between transcriptional and metabolic levels and phylogenetic analysis. This study provides data resources and new insights for further studies on the biosynthesis of major active components in B. purpurascens.

Abstract Background China has the third largest number of TB cases in the world, and the average annual floating population in China is more than 200 million, the increasing floating population across regions has a tremendous potential for spreading infectious diseases, however, the role of increasing massive floating population in tuberculosis transmission is yet unclear in China. Methods 29,667 tuberculosis flow data were derived from the new smear-positive pulmonary tuberculosis cases in China. Spatial variation of TB transmission was measured by geodetector q-statistic and spatial interaction model was used to model the tuberculosis flow and the regional socioeconomic factors. Results Tuberculosis transmission flow presented spatial heterogeneity. The Pearl River Delta in southern China and the Yangtze River Delta along China’s east coast presented as the largest destination and concentration areas of tuberculosis inflows. Socioeconomic factors were determinants of tuberculosis flow. Some impact factors showed different spatial associations with tuberculosis transmission flow. A 10% increase in per capita GDP was associated with 10.2% in 2010 or 2.1% in 2012 decrease in tuberculosis outflows from the provinces of origin, and 1.2% in 2010 or 0.5% increase in tuberculosis inflows to the destinations and 18.9% increase in intraprovincial flow in 2012. Per capita net income of rural households and per capita disposable income of urban households were positively associated with tuberculosis flows. A 10% increase in per capita net income corresponded to 14.0% in 2010 or 3.6% in 2012 increase in outflows from the origin, 44.2% in 2010 or 12.8% increase in inflows to the destinations and 47.9% increase in intraprovincial flows in 2012. Tuberculosis incidence had positive impacts on tuberculosis flows. A 10% increase in the number of tuberculosis cases corresponded to 2.2% in 2010 or 1.1% in 2012 increase in tuberculosis inflows to the destinations, 5.2% in 2010 or 2.0% in 2012 increase in outflows from the origins, 11.5% in 2010 or 2.2% in 2012 increase in intraprovincial flows. Conclusions Tuberculosis flows had clear spatial stratified heterogeneity and spatial autocorrelation, regional socio-economic characteristics had diverse and statistically significant effects on tuberculosis flows in the origin and destination, and income factor played an important role among the determinants.

Remote sensing image data especially hyperspectral imagery (HSI) data have been widely applied in various research fields. However, HSI often suffers from significant noise contamination, such as stripe noise and Gaussian noise. These noises adversely affect the utilization of remote sensing data, prompting the development of numerous noise removal algorithms for HSI. Specifically, addressing stripe noise involves employing different strategies, including the employment of total-variation-based (TV-based) and low-rank-based algorithms. Yet, evaluating the effectiveness and applicability of these algorithms can be challenging due to variations in testing conditions provided by their respective authors during the proposal phase. Consequently, our aim was to offer a comprehensive and impartial evaluation of these stripe noise removal algorithms for HSI. Within the TV-based and low-rank-based algorithm categories, we had chosen 10 distinct algorithms on which third-party testing and evaluation would be conducted. We considered various noise scenarios, resulting in a total of 48 noise configurations. Our evaluation encompassed multiple dimensions, including the quality of noise removal, computational speed, and parameter stability, thereby delivering a comprehensive assessment of the performance of different stripe noise removal algorithms. In addition, we conducted an analysis to identify the underlying causes of varying denoising results across different algorithms. This analysis offered valuable insights and recommendations for the future development of denoising algorithms.

Segmentation is crucial in geographic object-based image analysis for accurate land use and land cover mapping. However, obtaining outstanding segmentation results in all scenarios proves challenging with a single algorithm. This study investigates seven segmentation algorithms: mean shift (MF), O Sistema de Processamento de informações georreferenciadas (the geographic information and image processing system) (SPRING), Estimation of scale parameter 2 (ESP2) (three global-scale algorithms), image object detection approach (IODA), SA, edge-guided image object detection approach (EIODA) (three local-scale optimization algorithms), and segment anything model (SAM) (deep learning). In the custom dataset and semantic segmentation datasets, we apply visual interpretation, unsupervised, and supervised evaluation methods with 15 test images, using a total of 17 evaluation indices to assess the segmentation results. Based on the evaluation results, the effectiveness and adaptability of the algorithms in scene segmentation are comprehensively analyzed. The results report that global-scale segmentation approaches encounter difficulties in distinguishing meaningful objects in complicated scenarios. Both MF and SPRING methods are prone to over-segmentation. In many cases, ESP2 tends to generate homogeneous segments (low weighted variance), whereas EIODA tends to produce heterogeneous adjacent segments (low Moran's I). ED3 and segmentation evaluation index demonstrate that scale parameter (SA) and IODA can to some extent identify geo-objects, with SA being more effective and performing exceptionally well in building extraction. The EIODA performs well in areas with clear boundaries, like aquaculture ponds and water-land transitions. SAM accurately detects objects of various sizes, displaying rich semantic content and high consistency with reference polygons. The average intersection over union reaches 71.10% and F measure attains 0.77 under normal conditions.

A new forward model (FM) was developed to characterize the influence of precipitation on L-band passive ocean surface measurements. The FM, which relates rain-induced brightness temperature (TB) variations to the rain rate and wind speed (WS), was established through a machine learning approach (referred to as the ML-FM). The soil moisture active passive (SMAP) data matched with integrated multisatellite retrievals for global precipitation measurement (IMERG) rain rate data and cross-calibrated multiplatform (CCMP) wind data were binned as a function of the rain rate, WS, and wind direction. The ML-FM was validated by comparing the simulated top-of-atmosphere (TOA) TB values with SMAP measurements. The results showed favorable agreement between the ML-FM outputs and SMAP data, with a root mean square error (RMSE) smaller than 0.55 K for both the horizontal and vertical polarizations. The validation results for ensuring more reasonable rainfall intensity distributions showed that the ML-FM returned stable results with a slightly reduced RMSE of ∼0.75 K for both the horizontal and vertical polarizations. Based on the ML-FM, we found that sea surface emission exhibited significant dependence on the rain rate for both polarizations. In addition, the ML-FM demonstrated signal saturation when the rain rate exceeded 45 mm/h, while precipitation slightly affected the directional characteristics of sea surface emission. These effects accounted for ∼0.3 K at a rain rate of 50 mm/h. Overall, our analyses demonstrated that the proposed ML-FM achieved superior performance in retrieving the TOA TB for both the vertical and horizontal polarizations with a higher accuracy than existing models.

Abstract Bergenia purpurascens is an important medicinal, edible and ornamental plant. It generally grows in high-altitude areas with complex climates. There have been no reports about how B. purpurascens survives under cold stress. Here, the B. purpurascens under low temperature were subjected to transcriptomics analysis to explore the candidate genes and pathways that involved in the cold tolerance of B. purpurascens. Compared with the control treatment, we found 9,600 up-regulated differentially expressed genes (DEGs) and 7,055 down-regulated DEGs. A significant number of DEGs were involved in the Ca2+ signaling pathway, mitogen-activated protein kinase (MAPK) cascade, plant hormone signaling pathway, and lipid metabolism. A total of 400 transcription factors were found to respond to cold stress, most of which belonged to the MYB and AP2/ERF families. Five novel genes were found to be potential candidate genes involved in the cold tolerance of B. purpurascens. The study provide insights into further investigation of the molecular mechanism of how B. purpurascens survives under cold stress.

SPL transcription factors are widely involved in plant growth and development, stress response and so on. At present, there is no study on the STM (SPL with transmembrane motif) transcription factor in Dendrobium officinale. In order to explore the role of STM in the growth, development and stress response of D. officinale, four STM transcription factors were identified at the whole genome of D. officinale, and bioinformatics analysis of DoSTM gene family members were carried out. The expression of DoSTM in different tissue parts and different stress treatments were studied by reverse transcription PCR. The results were as follows: (1)DoSTM1-4 were hydrophilic proteins with SBP conserved domains and some hormone response sites. (2)Four DoSTM were expressed in root, stem and leaf, and the relative expression of DoSTM2 was the lowest in leaf; there was no significant differences in the relative expression level of DoSTM1/3/4. (3)The relative expression level of DoSTM1-4 changed significantly under low temperature, high temperature and drought stress, and the expression of DoSTM1/3/4 decreased most significantly. Therefore, it is speculated that DoSTM is related to hormone response, temperature change response and drought resistance in plants. These conclusions provide the reference for the further research on STM transcription factor of D. officinale.

AbstractThe surrounding rock control has been a difficult problem for fractured rock mass in hard rock mines. This article describes a case study of the failure mechanisms and the support design technology for fractured rock mass drifts in Xinli Gold Mine. Based on field investigation, the geology characteristics, failure types, influencing factors, support types, and their failure types were analyzed. The rock mass classification, rock mass physical and mechanical parameters were obtained by using Q, RMR, and GSI systems. The zoning of surrounding rock, stability analysis and zoning support schemes design were carried out based on rock mass classification results. The pretension is designed by China underground mine experiences and verified by numerical simulation. RS2 was used to compare the plastic zone under pre- and post-support conditions. The plastic zone is significantly reduced after support is installed, which indicates that the designed support schemes can effectively control the failure of surrounding rock. In view of difficulties in the excavation and support of fractured rock mass, the short excavation and short support technology was proposed to ensure the success excavation of the drift in fractured rock mass. The field application shows that the short excavation and support technology are effective.

In this study, we aimed to compare survival outcomes after receiving radiofrequency ablation (RFA) and hepatic resection (HR) for solitary hepatocellular carcinoma (HCC) with stratification by tumor size and age. A retrospective cohort was obtained from the Surveillance, Epidemiology, and End Results (SEER) database from 2004 to 2015. Patients were grouped by tumor size (0-2, 2-5, and > 5 cm) and age (>65 and ≤65). Overall survival (OS) and disease-specific survival (DSS) were assessed. For patients >65 with tumors measuring 0-2 and 2-5 cm, the HR group had better OS and DSS compared with the RFA group. For patients >65 with tumors > 5 cm, OS and DSS did not differ significantly between the RFA and HR groups (p = 0.262 and p = 0.129, respectively). For patients ≤65, the HR group had better OS and DSS compared with the RFA group regardless of tumor size. For patients with resectable solitary HCC, regardless of age, HR is the better choice not only for tumors ≤ 2 cm, but also for tumors 2-5 cm. For resectable solitary HCC with tumors ＞5 cm, HR is the better choice for patients ≤65 but for patients >65, the issue of treatment choice needs to be further studied.

Modeling sea foam emissivity is important for microwave remote sensing of the ocean. Based on the matrix-operator method, we propose a vector radiative transfer model (RTM) for the simulation of wave propagation in the foam layer and the sea foam emissivity is then calculated. The RTM simulates the emissivity of a vertically structured foam layer with various water properties. We assess the model simulations under different conditions. It is found that the foam thickness and the void fraction profile could be critical parameters in modeling foam emissivity. The sea foam emissivity could range from 0.2 to 0.3 in our simulations with varying foam thicknesses and void fraction profiles. Then, comparisons were made to experimental data for validation, and our model achieved a good consistency with the different experimental measurements of three previous studies. And it was also found that the modeled emissivity fits the experimental data well using an exponential profile with a small profile shape-control parameter.

Polar-orbiting ocean color satellites can monitor daily to interannual variations in water transparency (or Secchi disk depth, SDD) from regional to global oceans. However, diurnal variations in SDD of coastal oceans remain poorly understood. Based on the bio-optical SDD algorithm, we retrieved the SDD products of hourly observations using the Geostationary Ocean Color Imager (GOCI) from 2011 to 2020 in the eastern China seas. The determination coefficient (R2) between the SDD product and the in situ dataset is 0.93, with a root mean squared error (RMSE) of 0.86 m. Based on the pixel-level tempo-spatial analysis, superpixel image segmentation retrieved by a simple linear iterative clustering algorithm (SLIC) was applied to classify the SDD product. The reconstruction SDD superpixel products not only match the spatial distribution well but can also more clearly express the spatial gradient. The percentage of the diurnal change in transparency was high in the nearshore (∼10 %), medium in transitional waters (∼5%), and low in offshore waters (∼3%). Finally, we found a significant negative correlation between SDD and wind speed (R2 = 0.65) and a significantly positive correlation between diurnal change range (DCR) and wind speed (R2 = 0.62). In contrast, sea surface temperature (SST) was positively correlated with SDD (R2 = 0.72) but significantly negatively correlated with DCR (R2 = 0.80). These results provide a basis for studying diurnal SDD changes in highly dynamic waters.

The failure of surrounding rock in deep hard rock roadway is closely related to mining disturbance. In this study, the 13# stope ramp of −767 m level (at a buried depth of 1,197 m) at Hongtoushan copper mine was taken as the engineering background, a comprehensive analysis method of numerical analysis and borehole detection was put forward, and the evolution law of fracture depth of the ramp surrounding rock under the mining influence was obtained. The results show that the maximum tangential stress and fracture depth of the ramp surrounding rock on both sidewalls increase slowly at the initial mining stage. When the ore body above the ramp is mined, the maximum tangential stress and fracture depth of the ramp surrounding rock on both sidewalls increase rapidly, and the two parameters are positively correlated. Based on this, the ratio of the maximum tangential stress of the surrounding rock to the uniaxial compressive strength of intact rock (σθmax/σc) and the equivalent radius (a) of the roadway were used as parameters, and an equation for the fracture depth of the roadway surrounding rock was proposed. Through the case analysis, the results show that the proposed equation of fracture depth of the roadway surrounding rock has good prediction accuracy. This study enriches the research on the stability and failure mechanism of the roadway surrounding rock under the mining disturbance, and provides new basis for the support design of mining roadways.

Abstract Background Previous studies have indicated that the risk of infectious disease spread is greatest in locations where a population has massive and convenient access to the epicenter of an outbreak. However, the spatiotemporal variations and risk determinants of COVID-19 in typical labor export regions of China remain unclear. Understanding the geographical distribution of the disease and the socio-economic factors affecting its transmission is critical for disease prevention and control. Methods A total of 2152 COVID-19 cases were reported from January 21 to February 24, 2020 across the 34 cities in Henan and Anhui. A Bayesian spatiotemporal hierarchy model was used to detect the spatiotemporal variations of the risk posed by COVID-19, and the GeoDetector q statistic was used to evaluate the determinant power of the potential influence factors. Results The risk posed by COVID-19 showed geographical spatiotemporal heterogeneity. Temporally, there was an outbreak period and control period. Spatially, there were high-risk regions and low-risk regions. The high-risk regions were mainly in the southwest areas adjacent to Hubei and cities that served as economic and traffic hubs, while the low-risk regions were mainly in western Henan and eastern Anhui, far away from the epicenter. The accessibility, local economic conditions, and medical infrastructure of Wuhan in Hubei province all played an important role in the spatiotemporal heterogeneity of COVID-19 transmission. The results indicated that the q statistics of the per capita GDP and the proportion of primary industry GDP were 0.47 and 0.47, respectively. The q statistic of the population flow from Wuhan was 0.33. In particular, the results showed that the q statistics for the interaction effects between population density and urbanization, population flow from Wuhan, per capita GDP, and the number of doctors were all greater than 0.8. Conclusions COVID-19 showed significant spatiotemporal heterogeneity in the labor export regions of China. The high-risk regions were mainly located in areas adjacent to the epicenter as well as in big cities that served as traffic hubs. Population access to the epicenter, as well as local economic and medical conditions, played an important role in the interactive effects of the disease transmission.

Hong Kong International Airport (HKIA) is an important sea airdrome in China. The aim of this study is to evaluate the impacts of this reclamation on the water quality of the Northwestern Bay of Hong Kong (NWBHK). In all, 117 Landsat 5 TM and 44 Landsat 8 OLI images were preprocessed and matched with the marine water data of 18 in situ monitoring points, acquiring 458 and 119 sets of data, respectively. This study adopted BPNN Machine Learning methods to establish the retrieval algorithm. Based on the images, the construction of HKIA was divided into three stages: (1) the construction of the first and second runways from 1992 to 1995; (2) the construction of the Hong Kong Port from 2013 to 2016; and (3) the construction of the third runway from 2017 to 2020. The concentrations of suspended particulate matter, orthophosphate phosphorus, and dissolved inorganic nitrogen from 1986 to 2022 were retrieved. In this paper, it was found that (1) the construction activities led to an increase in SPM, PO4P, and DIN concentrations in adjacent water bodies; (2) the impact of the Tuen Mun River on the NWBHK increased, while the impact of the Tung Chung River on the NWBHK decreased; and (3) the interception impact of HKIA on the transportation of the Pearl River water became stronger.

The ocean front has a non-negligible role in global ocean–atmosphere interactions, marine fishery production, and the marine military. Hence, obtaining the positions of the ocean front is crucial in oceanic research. At present, the positioning method of recognizing an ocean front has achieved a breakthrough in the mean dice similarity coefficient (mDSC) of above 90%, but it is difficult to use to achieve rapid extraction in emergency scenarios, including marine fisheries and search and rescue. To reduce the its dependence on machines and apply it to more requirements, according to the characteristics of an ocean front, a multi-scale model SQNet (Simple and Quick Net) dedicated to ocean front position recognition is designed, and its perception domain is expanded while obtaining current scale data. In experiments along the coast of China and the waters of the Gulf of Mexico, it was not difficult to find that SQNet exceedingly reduced running time while ensuring high-precision results (mDSC of higher than 90%). Then, after conducting intra-model self-comparison, it was determined that expanding the perceptual domain and changing the weight ratio of the loss function could improve the accuracy and operational efficiency of the model, which could be better applied in ocean front recognition.

Abstract Multidrug resistance (MDR) based on ATP-dependent efflux transporters (p-glycoprotein (p-gp)) remains a major obstacle in successful chemotherapy treatment. Herein, we have investigated the potential of PD-L1 mAb-conjugated nanoliposome to serve as a targeted delivery platform for the co-delivery of paclitaxel (PTX) and p-gp specific transport inhibitor (TQD, tariquidar) in drug-resistant gastric cancers. Two drugs, PTX and TQD, were co-loaded in a single vehicle in a precise ratio to enhance the prospect of combination chemotherapeutic effect. Cellular uptake study indicated that PD-PTLP had higher internalization efficiency in PD-L1 receptor overexpressing SGC7901/ADR cells than non-targeted PTLP. Highest synergy was observed at a weight fraction of 1/0.5 (PTX/TQD) and the combination of PTX and TQD resulted in obvious synergistic effect compared to that of individual drugs alone. Our in vitro results showed that TQD was effective in reversing the multidrug resistance in SGC7901/ADR cells. The IC50 value of PD-PTLP was 0.76 μg/ml compared to 6.58 μg/ml and 7.64 μg/ml for PTX and TQD, respectively. PD-TPLP triggered significantly higher levels of reactive oxygen species (ROS) and cell apoptosis compared to that of free PTX or TQD. Furthermore, the in vivo antitumor study showed that the combination chemotherapy of PD-PTLP displayed a significant inhibition of tumor burden of drug-resistant xenograft tumors with significantly higher terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL)-positive cells. Furthermore, free PTX resulted in significant increase in the levels of AST and ALT while PD-PTLP insignificantly different compared to that of control indicating the safety index. Overall, we believe that combination of anticancer drug with a p-gp inhibitor could provide a potential direction toward the treatment of drug-resistant gastric tumors.

Energy-absorbing rockbolt is now recognized as an important support element in deep mines around the world. A novel kind of energy-absorbing bolt called J-bolt was developed, which consists of anchoring (damping) module, deformation module, blending module and thread segment. The static pulling loading model and dynamic impact constitutive model of J-bolt were established. The experiment results show: (1) the static pulling load is greater than 190 kN; (2) under multiple dynamic impact loading condition, the peak load of J-bolt exceeds 250 kN each time. Under the given initial dynamic impact loading condition, with the increasing of damping ratio, the oscillation amplitude of J-bolt attenuates quickly along the bolt axial impact direction. The greater the damping effect of J-bolt, the more quickly releasing of the dynamic impact energy. The absorbed energy of J-bolt exceeds 19.3 kJ under each dynamic impact, the accumulated energy absorbing capacity reaches 46.5 kJ. Due to the objective existence of joints in rock mass, the bolted rock mass can generate dilatation and tensile failure in the joints surface of rock mass under dynamic impact condition, but the energy-absorbing support system will keep surfaces of tunnels (stopes) stable, which can effectively absorb the kinetic energy induced by dynamic hazards.

Studying land use transition and restructuring has value for promoting sustainable regional development, especially in China’s vast rural areas, which are undergoing rapid changes. Current research tends to focus on the macro level, and analyses of driving forces are mostly based on the correlation analysis of influencing factors. However, in the case of villages and towns, which are at the micro level, it is important to know who promotes land use transition and how to promote it under the influence of the macro environment. This study, therefore, focused on the endogenous driving force behind land use transition and its characteristics at the micro level of villages and towns. On the basis of our theoretical framework, an empirical study was carried out on the transformation and restructuring of ecology–production–living (EPL) spaces in the town of Zhulin in Central China over the past 30 years. We found the following: (1) The overall distribution of EPL spaces in Zhulin shifted from mixed distribution to relatively concentrated distribution, and the spatial transfer of EPL spaces showed fluctuations in the expansion and contraction of different types of spaces. (2) Land use transition was more active in spatial interface areas than in noninterface areas, where the interconversion of ecological space and agricultural production space was concentrated at the terrain interface. In addition, transformation processes related to living space and non-agricultural production space were concentrated at the urban–rural interface. (3) Macro-level social and economic changes were the root cause of land use transformation, and the autonomous spatial governance capability of villagers’ self-organization institutions was key to regulating land use transformation. The spatial interface was a sensitive area for land use transformation in a natural state. An endogenous driving mode of active response to land use transformation based on rural autonomous spatial governance capability and spatial interface sensitivity is proposed. How to improve the rural governance capacity of key local actors in different regions and at different levels is an aspect worthy of further consideration.

The data quality of the remote sensing reflectance (Rrs) from the two ocean color satellites HaiYang-1C (HY-1C) and HaiYang-1D (HY-1D) and the consistency with other satellites are critical for the products. The Layer Removal Scheme for Atmospheric Correction (LRSAC) has been applied to process the data of the Chinese Ocean Color and Temperature Scanner (COCTS) on HY-1C/1D. The accuracy of the Rrs products was evaluated by the in situ dataset from the Marine Optical BuoY (MOBY) with a mean relative error (MRE) of −1.56% and a mean absolute relative error (MAE) of 17.31% for HY-1C. The MRE and MAE of HY-1D are 1.05% and 15.68%, respectively. The comparisons of the global daily Rrs imagery with the Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra show an MRE of 10.94% and an MAE of 21.38%. The comparisons between HY-1D and Aqua exhibit similar results, with an MRE of 13.31% and an MAE of 21.46%. The percentages of valid pixels of the global daily images of HY-1C and HY-1D are 32.3% and 32.6%, much higher than that of Terra (11.9%) and Aqua (11.9%). The gaps in the 8-day composite images have been significantly reduced, with 83.9% of valid pixels for HY-1C and 85.4% for HY-1D, which are also much higher than that of Terra (52.9%) and Aqua (50.9%). The gaps due to the contamination of sun glint have been almost removed from the 3-day composite imagery, with valid pixels of 63.5% for HY-1C and 65.6% for HY-1D, which are higher than that of the 8-day imagery of Terra and Aqua. The patterns of HY-1C imagery exhibit a similarity with those of HY-1D, but they are different on a pixel scale, mainly due to the changes in the ocean dynamic features within 3 h. The evaluations of the COCTS indicate that the imagery of HY-1C/1D can be used as a kind of standard product.

For the mosaicking of multiple remote sensing images, obtaining the optimal stitching line in the overlapping region is a key step in creating a seamless mosaic image. However, for very large remote sensing images, the computation of finding seamlines involves a huge amount of image pixels. To handle this issue, we propose a stepwise strategy to obtain pixel-level optimal stitching lines for large remote sensing images via an upscaling–downscaling image sampling procedure. First, the resolution of the image is reduced and the graph cut algorithm is applied to find an energy-optimal seamline in the reduced image. Then, a stripe along the preliminary seamline is identified from the overlap area to remove the other inefficient nodes. Finally, the graph cut algorithm is applied nested within the identified stripe to seek the pixel-level optimal seamline of the original image. Compared to the existing algorithms, the proposed method produces fewer spectral differences between stitching lines and less-crossed features in the experiments. For a wide range of remote sensing images involving large data, the new method uses less than 10 percent of the time needed by the SLIC+ graph cut method.

Geotechnical issues due to inappropriate support designs of underground drift will affect mining developments and production. The aim of this study was to provide a systematic support design method for deep hard-rock drifts in China. Field investigations and laboratory studies were carried out on the engineering geological properties of the rock masses along drifts in the Sanshandao Gold Mine. Potential wedge analysis and safety factors were determined using Unwedge software. The rock mass properties and support requirements were analyzed accordingly using different rock mass classification systems; then, an updated combined support system including rock bolts, wire mesh, and shotcrete was proposed. Numerical methods were used to quantify the plastic zone and principal stress of the drift, the plastic zone was reduced, and the rock stress state was improved after installing the support systems. Field monitoring data also confirmed that the updated support system prevented excessive rock mass deformation in drift. This study provides a reliable method for deep hard-rock drift support at Sanshandao Gold Mine and will also be helpful for the optimization of subsequent support.

The bottom depth of coastal benthic habitats plays a vital role in the coastal ecological environment and navigation. In optically shallow waters (OSWs), seafloor reflectance has an impact on the remotely sensed data, and thus, water depth can be retrieved from the remote sensing reflectance (Rrsλ) values provided by satellite imagery. Empirical methods for depth estimation are mainly limited by field measurements coverage. In addition, owing to the diverse range of water bio-optical properties in coastal regions, the high-precision models that could be applied to all OSWs are insufficient. In this study, we developed a novel bottom-depth retrieval method based on Hydrolight simulated datasets, in which Rrsλ were generated from radiative transfer theory instead of actual satellite data. Additionally, this method takes into consideration the variable conditions of water depth, chlorophyll concentrations, and bottom reflectance. The bottom depth can be derived from Rrsλ using a data-driven machine learning method based on the random forest (RF) model. The determination coefficient (R2) was greater than 0.98, and the root mean squared error (RMSE) was less than 0.4 m for the training and validation datasets. This model shows promise for use in different coastal regions while also broadening the applications that utilize satellite data. Specifically, we derived the bottom depth in three areas in the South China Sea, i.e., the coastal regions of Wenchang city, Xincun Bay, and Huaguang Reef, based on Sentinel-2 imagery. The derived depths were validated by the bathymetric data acquired by spaceborne photon-counting lidar ICESat-2, which was able to penetrate clean shallow waters for sufficient bottom detection. The predicted bottom depth showed good agreement with the true depth, and large-scale mapping compensated for the limitations resulting from along-track ICESat-2 data. Under a variety of circumstances, this general-purpose depth retrieval model can be effectively applied to high spatial resolution imagery (such as that from Sentinel-2) for bottom depth mapping in optically shallow waters.

The vibration comfort evaluation is a control standard other than strength and deflection, but the general comfort evaluation method only considers the response of the mid-span position and does not consider the difference in the vibration response of different positions at the same time. It is crucial to study how pedestrians actually feel when they walk on footbridges. The computer vision-based vibration comfort evaluation method is a novel method with advantages, such as noncontact and long-distance. In this study, a computer vision-based method was used to evaluate the global vibration comfort of footbridges under human-induced excitation. The improved Lucas–Kanade optical flow method is used for multitarget displacement identification of footbridges. Additionally, the YOLOv5 algorithm for pedestrian detection is used to obtain the position information of pedestrians on the footbridges. Then, according to the pedestrian position information, the structural responses of different pedestrian positions corresponding to time periods are extracted from the displacement responses of each point, and they are combined to obtain the structural global displacement. The global acceleration can be obtained by calculating the global displacement. The rms value can be calculated based on the global acceleration and compared with the standard for comfort evaluation. The global comfort evaluation method is validated by pedestrian walking experiments with different frequencies on a laboratory footbridge. The experimental results show that the computer vision-based global comfort evaluation method for footbridges is feasible and is a more specific and real-time comfort evaluation method.

With the gradual depletion of shallow resources, deep mining has become an inevitable trend and has become an important part of the world mining industry. The high stress concentration caused by redistribution of original stress field will lead to stress-driven failure of surrounding rock; conventional methods, such as point-location stress measurement, analytical analysis, numerical simulation, and physical modeling, are not able to completely reflect the distribution and evolution characteristics of the mining-induced stress field in real time and at mine scale, so it is difficult to fully understand, control, and prevent mining-induced injuries and fatalities. In the past decades, microseismic monitoring technology, velocity tomography, numerical simulation, and laboratory test technology have been successfully applied to better understand mining-induced stress and rock mass failures. The combination of these methods has led to innovative ways to investigate the mining-induced stress field, surrounding rock failure, and hazard prevention. This review focuses on the mining-induced stress and velocity tomography based on microseismic monitoring data. Research progress in analysis and measurement methods of mining-induced stress, rock mechanics for mining, and velocity tomography practices are presented.

Atmospheric correction is a fundamental process of ocean color remote sensing to remove the atmospheric effect from the top-of-atmosphere. Generally, Near Infrared (NIR) based algorithms perform well for clear waters, while Ultraviolet (UV) based algorithms can obtain good results for turbid waters. However, the latter tends to produce noisy patterns for clear waters. An ideal and practical solution to deal with such a dilemma is to apply NIR- and UV-based algorithms for clear and turbid waters, respectively. We propose a novel atmospheric correction method that integrates the advantages of UV- and NIR-based atmospheric correction (AC) algorithms for coastal ocean color remote sensing. The new approach is called UV-NIR combined AC algorithm. The performance of the new algorithm is evaluated based on match-ups between GOCI images and the AERONET-OC dataset. The results show that the values of retrieved Rrs (Remote Sensing Reflectance) at visible bands agreed well with the in-situ observations. Compared with the SeaDAS (SeaWiFS Data Analysis System) standard NIR algorithm, the new AC algorithm can achieve better precision and provide more available data.

Validation of remote-sensing reflectance (Rrs) products is necessary for the quantitative application of ocean color satellite data. While validation of Rrs products has been performed in low to moderate turbidity waters, their performance in highly turbid water remains poorly known. Here, we used in situ Rrs data from Hangzhou Bay (HZB), one of the world’s most turbid estuaries, to evaluate agency-distributed Rrs products for multiple ocean color sensors, including the Geostationary Ocean Color Imager (GOCI), Chinese Ocean Color and Temperature Scanner aboard HaiYang-1C (COCTS/HY1C), Ocean and Land Color Instrument aboard Sentinel-3A and Sentinel-3B, respectively (OLCI/S3A and OLCI/S3B), Second-Generation Global Imager aboard Global Change Observation Mission-Climate (SGLI/GCOM-C), and Visible Infrared Imaging Radiometer Suite aboard the Suomi National Polar-orbiting Partnership satellite (VIIRS/SNPP). Results showed that GOCI and SGLI/GCOM-C had almost no effective Rrs products in the HZB. Among the others four sensors (COCTS/HY1C, OLCI/S3A, OLCI/S3B, and VIIRS/SNPP), VIIRS/SNPP obtained the largest correlation coefficient (R) with a value of 0.7, while OLCI/S3A obtained the best mean percentage differences (PD) with a value of −13.30%. The average absolute percentage difference (APD) values of the four remote sensors are close, all around 45%. In situ Rrs data from the AERONET-OC ARIAKE site were also used to evaluate the satellite-derived Rrs products in moderately turbid coastal water for comparison. Compared with the validation results at HZB, the performances of Rrs from GOCI, OLCI/S3A, OLCI/S3B, and VIIRS/SNPP were much better at the ARIAKE site with the smallest R (0.77) and largest APD (35.38%) for GOCI, and the worst PD for these four sensors was only −13.15%, indicating that the satellite-retrieved Rrs exhibited better performance. In contrast, Rrs from COCTS/HY1C and SGLI/GCOM-C at ARIAKE site was still significantly underestimated, and the R values of the two satellites were not greater than 0.7, and the APD values were greater than 50%. Therefore, the performance of satellite Rrs products degrades significantly in highly turbid waters and needs to be improved for further retrieval of ocean color components.

Rural-spatial restructuring involves the spatial mapping of the current rural development process. The transformation of land-use morphologies, directly or indirectly, affects the practice of rural restructuring. Analyzing this process in terms of the dominant morphology and recessive morphology is helpful for better grasping the overall picture of rural-spatial restructuring. Accordingly, this paper took Zhulin Town in Central China as a case study area. We propose a method for studying rural-spatial restructuring based on changes in the dominant and recessive morphologies of land use. This process was realized by analyzing the distribution and functional suitability of ecological-production-living (EPL) spaces based on land-use types, data on land-use changes obtained over a 30-year observation period, and in-depth research. We found that examining rural-spatial restructuring by matching the distribution of EPL spaces with their functional suitability can help to avoid the misjudgment of the restructuring mode caused by the consideration of the distribution and structural changes in quantity, facilitating greater understanding of the process of rural-spatial restructuring. Although the distribution and quantitative structure of Zhulin’s EPL spaces have changed to differing degrees, ecological- and agricultural-production spaces still predominate, and their functional suitability has gradually increased. The spatial distribution and functional suitability of Zhulin are generally well matched, with 62.5% of the matched types being high-quality growth, and the positive effect of Zhulin’s spatial restructuring over the past 30 years has been significant. We found that combining changes in EPL spatial area and quantity as well as changes in functional suitability is helpful in better understanding the impact of the national macro-policy shift regarding rural development. Sustaining the positive spatial restructuring of rural space requires the timely adjustment of local actors in accordance with the needs of macroeconomic and social development, and a good rural-governance model is essential.

Knowledge of the vertical distribution of absorbing aerosols is crucial for radiative forcing assessment, and its quasi real-time prediction is one of the keys for the atmospheric correction of satellite remote sensing. In this study, we investigated the seasonal and interannual changes of the vertical distribution of global absorbing aerosols based on satellite measurement from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) and proposed a neural network (NN) model to predict the vertical distribution of global absorbing aerosols. Gaussian fitting was proposed to derive the maximum fitted particle number concentration (MFNC), altitude corresponding to MFNC (MFA), and standard deviation (MFASD) for vertical distribution of dust and smoke aerosols. Results showed that higher MFA values of dust and smoke aerosols mainly occurred over deserts and tropical savannas, respectively. For dust aerosol, the MFA is mainly observed at 0.5 to 6 km above deserts, and low MFNC values occur in boreal spring and winter while high values in summer and autumn. The MFA of smoke is systematically lower than that of dust, ranging from 0.5 to 3.5 km over tropical rainforest and grassland. Moreover, we found that the MFA of global dust and smoke had decreased by 2.7 m yr−1 (statistical significance p = 0.02) and 1.7 m yr−1 (p = 0.02) over 2007–2016, respectively. The MFNC of global dust has increased by 0.63 cm−3 yr−1 (p = 0.05), whereas that of smoke has decreased by 0.12 cm−3 yr−1 (p = 0.05). In addition, the determination coefficient (R2) of the established prediction models for vertical distributions of absorbing aerosols were larger than 0.76 with root mean square error (RMSE) less than 1.42 cm−3, which should be helpful for the radiative forcing evaluation and atmospheric correction of satellite remote sensing.

Extensive research revealed tremendous details about how plants sense pathogen effectors during effector-triggered immunity (ETI). However, less is known about downstream signaling events. In this report, we demonstrate that prolonged activation of MPK3 and MPK6, two Arabidopsis pathogen-responsive mitogen-activated protein kinases (MPKs), is essential to ETI mediated by both coiled coil-nucleotide binding site-leucine rich repeats (CNLs) and toll/interleukin-1 receptor nucleotide binding site-leucine rich repeats (TNLs) types of R proteins. MPK3/MPK6 activation rapidly alters the expression of photosynthesis-related genes and inhibits photosynthesis, which promotes the accumulation of superoxide ([Formula: see text]) and hydrogen peroxide (H2O2), two major reactive oxygen species (ROS), in chloroplasts under light. In the chemical-genetically rescued mpk3 mpk6 double mutants, ETI-induced photosynthetic inhibition and chloroplastic ROS accumulation are compromised, which correlates with delayed hypersensitive response (HR) cell death and compromised resistance. Furthermore, protection of chloroplasts by expressing a plastid-targeted cyanobacterial flavodoxin (pFLD) delays photosynthetic inhibition and compromises ETI. Collectively, this study highlights a critical role of MPK3/MPK6 in manipulating plant photosynthetic activities to promote ROS accumulation in chloroplasts and HR cell death, which contributes to the robustness of ETI. Furthermore, the dual functionality of MPK3/MPK6 cascade in promoting defense and inhibiting photosynthesis potentially allow it to orchestrate the trade-off between plant growth and defense in plant immunity.

Continued sea-level rise and coastal development have led to considerable concerns on coastline changes along inhabited islands. Analysis of long-term coastline changes of islands is however limited due to unavailable data and the cost of field work. In this study, high-resolution images taken from 1970–2011 at an interval of about 10 years and topographic maps were collected to determine coastline changes and their drivers in the Zhoushan Islands, China. Results show that nearly all inhabited islands appeared to have noteworthy seaward expansion during the past four decades. Coastline change rates varied among islands, and the annual change rate of Zhoushan Island (the main island) reached 12.83 ± 0.17 m/year during the same period. Since 2003, the study area has been dominated by artificial coast. The proportion of harbor/port and urban/industrial coast has significantly increased, while rocky coasts and shelter-farm coasts have shrunk greatly. Preliminary analysis of drivers for these coastline changes across the Zhoushan Islands highlights the roles of human policies during different periods as well as location, which were the dominant factors controlling the great spatial and temporal complexity of coastline changes of the major islands. Sediment supply from the Yangtze River decreased after the completion of the Three Gorges Dam in 2003; however, the Zhoushan coast rapidly accreted seaward during the last decade and the artificial siltation, coastal engineering, and harbor dredging materials could be responsible for the observed coastline changes. Pressured by rapid development of the port industry, the Zhoushan coast may face unprecedented challenges in coastal use in the near future. This research provides the basic background information for future studies on coastal protection and management.

Accurate prediction of sea surface emission is the key for sea surface salinity retrieval from satellite microwave radiometer. In order to retrieve salinity from satellite observation, several sea surface microwave emission models have been developed based on theoretical or empirical methods and validated by in-situ measurements in different regions. However, their performances are still unclear in the Chinese coastal waters. In this study, based on two cruises measurements in the East China Sea (ECS), including the brightness temperature measured by a shipborne microwave radiometer and other auxiliary data (sea surface salinity, sea surface temperature and wind speed), the performances of different sea surface emission models are tested. The results showed that the developed models provide fairly good accuracy in predicting brightness temperature; for example, the accuracy of small perturbance/small scale approximation model (SPM/SSA), two-scale model (TSM) and empirical model is in the range from 0.6 K to 3 K. Moreover, the TSM and empirical models are further improved by optimizing the model parameters in the ECS. Finally, the sea surface salinity were retrieved from shipborne measured data based on the improved models, and the results show that the root mean square (rms) differences between retrieved and in-situ sea surface salinity is about 0.4 psu, indicating the significant improvement by the regional model parameters.

In this study, the goal is to estimate the sedimentation on the bottom bed of Lake Taihu using numerical simulation combined with geostationary satellite ocean color data. A two-dimensional (2D) model that couples the dynamics of shallow water and sediment transport is presented. The shallow water equations are solved using a semi-implicit finite difference method with an Alternating Direction Implicit (ADI) method. Suspended sediment transport is simulated by solving the general convection-diffusion equation with resuspension and deposition terms using a second-order explicit central difference method in space and two-step Adams⁻Bashforth method in time. Moreover, the total suspended particulate matter (TSM) is retrieved by the world’s first geostationary satellite ocean color sensor Geostationary Ocean Color Imager (GOCI) using atmospheric correction algorithm for turbid waters using ultraviolet wavelengths (UV-AC) and regional empirical TSM algorithm. The 2D model and GOCI-retrieved TSM are applied to study the sediment transport and sedimentation in Lake Taihu. Validation results show rationale TSM concentration retrieved by GOCI, and the simulated TSM concentrations are consistent with GOCI observations. In addition, simulated sedimentation results reveal the dangerous locations that must be observed and desilted.

Dendrobium officinale Kimu et Migo has increased many researchers' interest for its high medical and horticultural values and the molecular mechanism of its protocorm development remains unclear. In this study, 19 genes from 26 most stably expressed genes in whole transcriptome of protocorms and 5 housekeeping genes were used as candidate reference genes and screened with 4 application softwares (geNorm, NormFinder, BestKeeper and RefFinder). The results showed that a few reference genes could effectively normalize expression level of specific genes in protocorm development and the optimal top 2 reference genes were ASS and APH1L. Meanwhile, validation of GNOM, AP2 and temperature induced gene (TIL) for normalization demonstrates the usefulness of the validated candidate reference genes. The expression profiles of these genes varied under protocorms and temperature stress according to the stablest and unstablest reference genes, which proved the importance of the choice of appropriate reference genes. The first systematic evaluation of stably expressed genes will be very useful in the future analysis of specific genes expression in D. officinale.

The Bering Sea, one of the largest and most productive marginal seas, is a crucial carbon sink for the marine carbonate system. However, restricted by the tough observation conditions, few underway datasets of sea surface partial pressure of carbon dioxide (pCO2) have been obtained, with most of them in the eastern areas. Satellite remote sensing data can provide valuable information covered by a large area synchronously with high temporal resolution for assessments of pCO2 that subsequently allow quantification of air-sea carbon dioxide 2 flux. However, pCO2 in the Bering Sea is controlled by multiple factors and thus it is hard to develop a remote sensing algorithm with empirical regression methods. In this paper pCO2 in the Bering Sea from July to September was derived based on a mechanistic semi-analytical algorithm (MeSAA). It was assumed that the observed pCO2 can be analytically expressed as the sum of individual components controlled by major factors. First, a reference water mass that was minimally influenced by biology and mixing was identified in the central basin, and then thermodynamic and biological effects were parameterized for the entire area. Finally, we estimated pCO2 with satellite temperature and chlorophyll data. Satellite results agreed well with the underway observations. Our study suggested that throughout the Bering Sea the biological effect on pCO2 was more than twice as important as temperature, and contributions of other effects were relatively small. Furthermore, satellite observations demonstrate that the spring phytoplankton bloom had a delayed effect on summer pCO2 but that the influence of this biological event varied regionally; it was more significant on the continental slope, with a later bloom, than that on the shelf with an early bloom. Overall, the MeSAA algorithm was not only able to estimate pCO2 in the Bering Sea for the first time, but also provided a quantitative analysis of the contribution of various processes that influence pCO2.

Purpose. Systematic reviews of case-control and prospective studies showed a positive association between habitual salt intake and gastric cancer. Given new studies published thereafter, we carried out a meta-analysis to assess the association between dietary salt intake and gastric cancer. Methods. Case-control studies and cohort studies published between January 1992 and January 2012 on PubMed and Embase were searched. We quantified associations between salt intake and gastric cancer with meta-analysis. Results. Eleven studies (7 case controls and 4 cohorts) finally were included in the meta-analysis (total population: n=2076498; events: n=12039). The combined odds ratio showed significantly positive association between high salt intake and gastric cancer compared with low salt intake (OR = 2.05, 95% CI [1.60, 2.62]; P