Search

The rise of the Internet of things has catalyzed extensive research in the realm of flexible wearable sensors. In comparison with conventional sensor power supply methods that are reliant on external sources, self-powered sensors offer notable advantages in wearable comfort, device structure, and functional expansion. The energy-harvesting modes dominated by piezoelectric nanogenerators (PENGs), triboelectric nanogenerators (TENGs), and pyroelectric nanogenerators (PyENGs) create more possibilities for flexible self-powered sensors. This paper meticulously examines the progress in flexible self-powered devices harnessing TENG, PENG, and PyENG technologies and highlights the evolution of these sensors concerning the material selection, pioneering manufacturing techniques, and device architecture. It also focuses on the research progress of sensors with composite power generation modes. By amalgamating pivotal discoveries and emerging trends, this review not only furnishes a comprehensive portrayal of the present landscape but also accentuates avenues for future research and the application of flexible self-powered sensor technology.

Abstract The current research on ST elevation myocardial infarction (STEMI) patients has been mostly limited to Door-to-Balloon (D-to-B) time. This study aimed to compare the effects of different hospital admission modes to on the time metrics of patients undergoing primary percutaneous coronary intervention (PPCI). It also examined the effects of these modes on in-hospital mortality and other influencing factors. The goal was to prompt healthcare facilities at all levels, including chest hospitals, the Centers for Disease Control and Prevention (CDC), and communities to take measures to enhance the treatment outcomes for patients with STEMI. A total of 1053 cases of STEMI patients admitted to Tianjin Chest Hospital from December 2016 to December 2023 and successfully underwent PPCI were selected for this study. They were divided into three groups based on the admission modes: the ambulances group (363 cases), the self-presentation group (305 cases), and the transferred group (385 cases). Multivariate logistic regression was used to explore the impact of different modes of hospital admission on the standard-reaching rate of key treatment time metrics. The results showed that the S-to-FMC time of transferred patients (OR = 0.434, 95% CI 0.316–0.596, P

Jilin Province is a crucial region of interest for agricultural and forestry development in China. The deterioration of its ecological environment could have a severe impact on agricultural production and ecological conservation. A systematic assessment of ecological environment quality in Jilin Province is essential for its sustainable development. In this study, we utilized Landsat data from 1990 to 2020 (every 5 years) to construct the Remote Sensing Ecological Index (RSEI) for Jilin Province. We applied the Sen’s slope estimator and the Mann-Kendall trend test to examine the spatiotemporal changes in ecological environment quality over a 30-year period. Additionally, we employed the Geo-detector to explore the socioeconomic and natural factors influencing ecological environment quality. The results revealed: 1) From 1990 to 2020, the average RSEI index in Jilin Province ranged from 0.586 to 0.699, indicating overall good ecological environment quality. Spatially, ecological environment quality gradually declined from east to west. 2) The RSEI in Jilin Province exhibited an initial increase, followed by a decrease, and then another increase trend. This improvement can be attributed to the implementation of government policies, which reversed the expansion of saline-alkali land. Ecological environment quality significantly improved in the western region of Jilin Province over the 30-year period. 3) Socioeconomic and natural factors both influence ecological environment quality in Jilin Province. Among these factors, vegetation coverage has the most significant impact on the ecological environment quality in the study area, with natural factors exerting a more significant influence than socioeconomic factors. Our research can provide relevant data support for policy-making in Jilin Province.

BackgroundHeterologous booster vaccines are more effective than homologous booster vaccines in combating the coronavirus disease 2019 (COVID-19) outbreak. However, our understanding of homologous and heterologous booster vaccines for COVID-19 remains limited.MethodsWe recruited 34 healthy participants from two cohorts who were primed with two-dose inactivated COVID-19 vaccine before, vaccinated with COVID-19 inactivated vaccine and adenovirus-vectored vaccine (intramuscular and aerosol inhalation of Ad5-nCoV) as a third booster dose. We assessed the immune responses of participants before and 14 days after vaccination, including levels of neutralizing antibodies, IgG, and cytokines, and quantified the transcriptional profile of peripheral blood mononuclear cells (PBMCs).ResultsThe Ad5-nCoV group showed a significantly higher neutralizing antibody geometric mean titer (GMT) compared to the ICV group after 14 days of heterologous boosting. The intramuscular Ad5-nCoV group had a GMT of 191.8 (95% CI 129.0, 285.1) compared to 38.1 (95% CI 23.1, 62.8) in the ICV1 group (p

Abstract Background The paucity of reliable biomarkers for predicting immunotherapy efficacy in patients with advanced hepatocellular carcinoma (HCC) has emerged as a burgeoning concern with the expanding use of immunotherapy. This study endeavors to delve into the potential peripheral biomarkers capable of prognosticating efficacy in HCC patients who are poised to receive anti-PD-1 monotherapy within the phase III clinical trial, KEYNOTE394. Additionally, we sought to elucidate the underlying molecular mechanisms for resistance to immune checkpoint blockade (ICB) and propose innovative combination immunotherapy strategies for future clinical application. Methods Patient blood samples were collected for single-cell RNA sequencing to evaluate the immune cell signature before receiving ICB therapy. Subsequently, in vitro assays and in vivo murine model experiments were conducted to validate the mechanism that S100A9+CD14+ monocytes play a role in ICB resistance. Results Our study demonstrates a notable enrichment of S100A9+CD14+ monocytes in the peripheral blood of patients exhibiting suboptimal responses to anti-PD-1 therapy. Moreover, we identified the Mono_S100A9 signature as a predictive biomarker, indicative of reduced efficacy in immunotherapy and decreased survival benefits across various tumor types. Mechanistically, S100A9 activates PD-L1 transcription by directly binding to the CD274 (PD-L1) gene promoter, thereby suppressing T-cell proliferation and cytotoxicity via the PD-1/PD-L1 axis, consequently diminishing the therapeutic effectiveness of subsequent anti-PD-1 treatments. Furthermore, our in vivo studies revealed that inhibiting S100A9 can synergistically enhance the efficacy of anti-PD-1 drugs in the eradication of hepatocellular carcinoma. Conclusions Our study underscores the significance of S100A9+CD14+ monocytes in predicting inadequate response to ICB treatment and provides insights into the monocyte cell-intrinsic mechanisms of resistance to ICB therapy. We also propose a combined therapeutic approach to enhance ICB efficacy by targeting S100A9.

Study region: The Loess Plateau, China Study focus: The trade-off between carbon uptake and water loss, characterized by ecosystem water use efficiency (WUE), deeply influences ecosystem sustainability. In this study, WUE was estimated based on GPP from the Moderate Resolution Imaging Spectroradiometer (MODIS) product and ET simulated by the Priestley Taylor Jet Propulsion Laboratory (PT-JPL) model. The emerging hot spot analysis (EHSA) was used to comprehensively examine the spatio-temporal heterogeneity of WUE. Additionally, the Geodetector model was employed to identify the main drivers of WUE and quantify the interactive effects of drivers on WUE, focusing on different vegetation types. New hydrological insights for the region: Results indicated obvious spatial heterogeneity of WUE under different vegetation and hydro-climatic conditions. Significant increases in WUE occurred in sub-humid cropland and grassland areas that have experienced large-scale ecological restoration and agricultural intensification. By contrast, slight decreases in WUE were observed in semi-arid grassland areas, some of which were accompanied by intensifying cold spots. It was noteworthy that WUE in some hot spots with excessive vegetation coverage also showed a slight downward trend. Further, the WUE pattern in cropland/forests/grassland was dominated by the interaction of vegetation coverage (characterized by the Normalized Difference Vegetation Index, NDVI) and precipitation/air temperature/vapor pressure deficit, with NDVI playing a leading role and hydro-climatic drivers playing a supporting role.

The role of the gut microbiota in the occurrence and progression of primary biliary cholangitis (PBC) is not fully understood. First, the fecal microbiota of patients with PBC (n = 4) (PBC-FMT) or healthy individuals (n = 3) (HC-FMT) was transplanted into pseudo germ-free mice or 2OA-BSA–induced PBC models. The functions, histology and transcriptome of the liver, and microbiota and metabolome of the feces were analyzed. Second, the liver transcriptomes of PBC patients (n = 7) and normal individuals (n = 7) were analyzed. Third, the liver transcriptomes of patients with other liver diseases were collected from online databases and compared with our human and mouse data. Our results showed that PBC-FMT increased the serum ALP concentration, total bile acid content, liver injury and number of disease-related pathways enriched with upregulated liver genes in pseudo germ-free mice and increased the serum glycylproline dipeptidyl aminopeptidase level and liver damage in a 2OA-BSA–induced PBC model. The gut microbiota and metabolome differed between PBC-FMT and HC-FMT mice and reflected those of their donors. PBC-FMT tended to upregulate hepatic immune and signal transduction pathways but downregulate metabolic pathways, as in some PBC patients. The hematopoietic cell lineage, Toll-like receptor, and PPAR signaling pathway were not affected in patients with alcoholic hepatitis, HBV, HCV, HCV cirrhosis, or NASH, indicating their potential roles in the gut microbiota affecting PBC. In conclusion, the altered gut microbiota of PBC patients plays an important role in the occurrence and progression of PBC. The improvement of the gut microbiota is worthy of in-depth research and promotion as a critical aspect of PBC prevention and treatment.

Abstract Diabetes has long been considered a risk factor in implant therapy and impaired wound healing in soft and hard oral tissues. Magnesium has been proved to promote bone healing under normal conditions. Here, we elucidate the mechanism by which Mg2+ promotes angiogenesis and osseointegration in diabetic status. We generated a diabetic mice model and demonstrated the alveolar bone healing was compromised, with significantly decreased angiogenesis. We then developed Mg-coating implants with hydrothermal synthesis. These implants successfully improved the vascularization and osseointegration in diabetic status. Mechanically, Mg2+ promoted the degradation of Kelch-like ECH-associated protein 1 (Keap1) and the nucleation of nuclear factor erythroid 2-related factor 2 (Nrf2) by up-regulating the expression of sestrin 2 (SESN2) in endothelial cells, thus reducing the elevated levels of oxidative stress in mitochondria and relieving endothelial cell dysfunction under hyperglycemia. Altogether, our data suggested that Mg2+ promoted angiogenesis and osseointegration in diabetic mice by regulating endothelial mitochondrial metabolism.

Abstract Covering array generation (CAG) is the key research problem in combinatorial testing and is an NP‐complete problem. With the increasing complexity of software under test and the need for higher interaction covering strength t, the techniques for constructing high‐strength covering arrays are expected. This paper presents a hybrid heuristic memetic algorithm named QSSMA for high‐strength CAG problem. The sub‐optimal solution acceptance rate is introduced to generate multiple test cases after each iteration to improve the efficiency of constructing high‐covering strength test suites. The QSSMA method could successfully build high‐strength test suites for some instances where t up to 15 within one day cutoff time and report five new best test suite size records. Extensive experiments demonstrate that QSSMA is a competitive method compared to state‐of‐the‐art methods.

Background: Protein-based pneumococcal vaccines (PBPVs) may offer expanded protection against Streptococcus pneumoniae and tackle the antimicrobial resistance crisis in pneumococcal infections. This study examined the safety and immunogenicity in healthy adults vaccinated with three doses of a protein-based pneumococcal vaccine containing pneumococcal surface protein A (PspA) (PRX1, P3296 and P5668) and in combination with a recombinant detoxified pneumolysin protein (PlyLD). Methods: This phase Ia randomized, double blind, placebo-controlled clinical study enrolled healthy adults aged 18–49 years. The participants were randomized into experimental (low-dose, medium-dose, high-dose) and placebo groups in a ratio of 3:1. Three doses of investigational vaccine were given to the participants with an interval of two months. Safety endpoints included the occurrence of total adverse reactions, solicited local and systemic adverse reactions, unsolicited adverse reactions, serious adverse events (SAEs), and several laboratory parameters. Immunogenicity endpoints included geometric mean titers (GMT) of anti-PspA (PRX1, P3296 and P5668) and anti-PlyLD antibodies level as determined by ELISA, seropositivity rates of PspA and PlyLD antibodies (>4-fold increase) and neutralization activity of anti-Ply antibody in serum. Results: A total of 118 participants completed the study of three doses. The candidate PBPV was safe and well-tolerated in all experimental groups. No vaccine-related SAEs were observed in this study. Most solicited adverse reactions were mild and transient. The most frequently reported solicited adverse reactions in the medium- and high-dose groups was pain at the injection site, while in the low-dose group it was elevated blood pressure. The immunogenicity data showed a sharp increase in the GMT level of anti-PspA-RX1, anti-PspA-3296, anti-PspA-5668, and anti-PlyLD antibodies in serum. The results also showed that the elicited antibodies were dosage-dependent. The high-dose group showed a higher immune response against PspA-RX1, PspA-3296, PspA-5668, and PlyLD antigens. However, repeat vaccination did not increase the level of anti-PspA antibodies but the level of anti-PlyLD antibody. High seropositivity rates were also observed for anti-PspA-RX1, anti-PspA-3296, anti-PspA-5668, and anti-PlyLD antibodies. In addition, a significant difference in the GMT levels of anti-Ply antibody between the high-, medium-, and low-dose groups post each vaccination were indicated by neutralization activity tests. Conclusions: The PBPV showed a safe and immunogenic profile in this clinical trial. Taking into consideration both safety and immunogenicity data, we propose a single dose of 50 µg (medium dose) of PBPV as the optimum approach in providing expanded protection against Streptococcus pneumoniae.

Jilin Province is located in the northeast of China, and has fragile ecosystems, and a vulnerable environment. Large-scale, long time series, high-precision land-use/cover change (LU/CC) data are important for spatial planning and environmental protection in areas with high surface heterogeneity. In this paper, based on the high temporal and spatial fusion data of Landsat and MODIS and the Google Earth Engine (GEE), long time series LU/CC mapping and spatio-temporal analysis for the period 2000–2023 were realized using the random forest remote sensing image classification method, which integrates remote sensing indices. The prediction results using the OL-STARFM method were very close to the real images and better contained the spatial image information, allowing its application to the subsequent classification. The average overall accuracy and kappa coefficient of the random forest classification products obtained using the fused remote sensing index were 95.11% and 0.9394, respectively. During the study period, the area of cultivated land and unused land decreased as a whole. The area of grassland, forest, and water fluctuated, while building land increased to 13,442.27 km2 in 2023. In terms of land transfer, cultivated land was the most important source of transfers, and the total area share decreased from 42.98% to 38.39%. Cultivated land was mainly transferred to grassland, forest land, and building land, with transfer areas of 7682.48 km2, 8374.11 km2, and 7244.52 km2, respectively. Grassland was the largest source of land transfer into cultivated land, and the land transfer among other feature types was relatively small, at less than 3300 km2. This study provides data support for the scientific management of land resources in Jilin Province, and the resulting LU/CC dataset is of great significance for regional sustainable development.

This study aimed to evaluate the immunogenicity non-inferiority and safety of the quadrivalent inactivated split-virion influenza vaccine in participants ≥ 3 years old. A total of 3,328 participants were enrolled. Participants 3–8 years old were administered one or two doses of the investigational vaccine or one dose of the control vaccine, whereas the other participants were administered only one dose of the investigational or control vaccine. The immunogenicity and occurrence of adverse events (AEs) after 30 days of full-course vaccination and serious adverse events (SAEs) within 6 months after full-course vaccination were assessed. The sero-conversion rates (SCRs) of anti-H1N1, H3N2, B(Y), and B(V) antibodies in the test group were 74.64%, 87.40%, 82.66%, and 78.89%, respectively, and their geometric mean titers were 1:250.13, 1:394.54, 1:200.84, and 1:94.91, respectively, which were non-inferior to those in the control group. The SCRs and sero-protection rates in the two-dose group of participants 3–8 years old were greater than those in the one-dose group. The incidences of total AEs and adverse reactions in the test group were 31.6% and 21.7%, respectively, which were close to those in the control group. In the two-dose group, the incidence of adverse reactions was considerably lower in the second dose (5.5%) than in the first dose (14.7%). Most AEs were grade 1 in severity, and no SAEs were recorded. The investigational vaccine had immunogenicity non-inferior to the control vaccine, and two doses were more effective than one dose in participants 3–8 years old, with a good overall safety. Trial registration: CTR20200715.

Soil salinization is one of the most critical threats to land degradation in arid and semiarid regions. This study is based on machine learning using Landsat 8 operational land imager (OLI) imagery to estimate soil salinity in Da'an City. A total of 19 spectral indexes, including 15 salinity indexes, 3 vegetation indexes, and a brightness index, were calculated using the blue, green, red, and near-infrared bands of Landsat 8 OLI images. Four machine learning regression algorithms, namely Cubist, support vector regression, random forest regression, and extreme gradient boosting regression, were used on the basis of the 19 aforementioned indexes to estimate soil salinity. Results demonstrated that the Cubist model has the highest prediction accuracy (RMSE = 0.31 mS/cm). Thus, the spatial distribution of soil salinity based on the Cubist model best meets the expectations of the authors. Moreover, the canopy salinity index correlated the most with the measured electrical conductivity, demonstrating a correlation coefficient of −0.44. After using the random forest method for variable screening, the Cubist model based on nine spectral indexes still achieved satisfactory prediction accuracy with the RMSE of 0.34 mS/cm. Thus, the Cubist method is recommended for soil salinity monitoring in arid and semiarid areas.

The global health crisis caused by the COVID-19 pandemic has led to a surge in demand and use of personal protective equipment (PPE) such as masks, putting great pressure on social production and the environment. It is urgent to find an efficient and non-destructive disinfection method for the safe reuse of PPE. This study proposes a PPE disinfection method that uses erythrosine, a U.S. Food and Drug Administration-approved food dye, as photosensitizer to produce singlet oxygen for virus inactivation, and indicates the completion of disinfection by its photobleaching color change. After spraying 100 μL of 10 μM erythrosine on the surface of the mask for 3 times and light exposure for 25 min, the titer of coronavirus decreased by more than 99.999%, and the color of erythrosine on the mask surface disappeared. In addition, the structure of the mask was intact and the filtration efficiency was maintained at > 95% after 10 cycles of erythrosine treatment. Therefore, this disinfection method can provide at least 10 cycles of reuse with the advantages of high safety and convenient, and the completion of disinfection can be indicated by its photobleaching, which is suitable for hospitals and daily life to reduce the consumption of PPE.

Study region: The Han River Basin, China Study focus: As the water source of the Middle Route Project of the South to North Water Transfer Project, water security in the Han River Basin deeply impacts national water resource allocation. This study constructed a Multi-Dimensional Flood Risk Assessment (MDFRA) framework combining a comprehensive index system, an integrated weight method, and a clustering algorithm to assess flood risk in the Han River Basin. We first constructed a comprehensive index system including eight hazard indexes, four exposure indexes, and eight vulnerability indexes in demographic, economic, ecological, and infrastructural categories to assess flood risk. The index weights were determined by the integrated weight method, which integrated the Shapley value and the Analytic Hierarchy Process method (SAHP). Finally, the possibilistic fuzzy C-means algorithm was employed to identify flood risk levels. New hydrological insights for the region: The MDFRA framework presents flood risk in the Han River Basin realistically and comprehensively, revealing flood risk composition and providing more detailed risk information. Results show that high-risk regions accounted for 34.51% of the basin area and were mainly concentrated in the mid-lower reaches, while middle-risk (19.13%) and middle-high-risk (23.35%) regions were mainly distributed in the upstream. 4.52%, 5.12%, and 13.37% of the basin area were assigned as very-low, low, and middle-low risk regions respectively, and were mainly adjacent to the Danjiangkou reservoir. Flood-prone natural conditions and dense population and assets were the causes of high flood risk, while reservoir regulation and storage capacity had significantly alleviated flood risk.

We present a straightforward and cost-effective method for the fabrication of flexible photodetectors, utilizing tetragonal phase VO2 (A) nanorod (NR) networks. The devices exhibit exceptional photosensitivity, reproducibility, and stability in ambient conditions. With a 2.0 V bias voltage, the device demonstrates a photocurrent switching gain of 1982% and 282% under irradiation with light at wavelengths of 532 nm and 980 nm, respectively. The devices show a fast photoelectric response with rise times of 1.8 s and 1.9 s and decay times of 1.2 s and 1.7 s for light at wavelengths of 532 nm and 980 nm, respectively. In addition, the device demonstrates exceptional flexibility across large-angle bending and maintains excellent mechanical stability, even after undergoing numerous extreme bending cycles. We discuss the electron transport process within the nanorod networks, and propose a mechanism for the modulation of the barrier height induced by light. These characteristics reveal that the fabricated devices hold the potential to serve as a high-performance flexible photodetector.

The functionalization of biosensor interfaces constitutes a crucial aspect of biosensing systems, as it directly governs key characteristics, including sensitivity, selectivity, accuracy, and rapidity. Among the diverse range of functionalization strategies available for biosensor interfaces, the click reaction has emerged as an exceptionally straightforward and stable approach for modifying electrodes and sensing films. Notably, the electro-click reaction enables the reagent-free functionalization of the biosensing interface, offering significant advantages, such as high speed, selectivity, and minimal pollution. Consequently, this strategy has garnered substantial attention and is widely regarded as a promising avenue for enhancing biosensor interface functionalization. Within this comprehensive review, we commence by presenting the latest advancements in functionalized biosensor interfaces, organizing the regulatory strategies into distinct categories based on the mediators employed, ranging from nanomaterials to biomolecules. Subsequently, we provide a comprehensive summary with an emphasis on recently developed electro-click strategies for functionalizing electrochemical and optical biosensor interfaces, covering both principles and applications. It is our anticipation that gaining a profound understanding of the principles and applications underlying electro-click strategies for biosensor interface functionalization will facilitate the design of highly selective and sensitive biosensor systems for diverse domains, such as clinical, pharmaceutical, environmental, and food analyses.

Deep learning, neural networks and other data-driven processing techniques are increasingly used in the analysis of LiDAR point cloud data in forest environments due to the benefits offered in accuracy and adaptability to new environments. One of the downsides of these techniques in practical applications is the requirement for manually annotated data necessary for training neural networks, which can be time consuming and costly to attain. We develop an approach to training neural networks for forest tree stem segmentation from point clouds that uses synthetic data from a custom tree simulator, which can generate large quantities of training examples without manual human effort. Our tree simulator captures the geometric characteristics of tree stems and foliage, from which automatically-labelled synthetic point clouds can be generated for training a semantic segmentation algorithm based on the PointNet++ architecture. Using evaluations on real aerial and terrestrial LiDAR point clouds from a range of different forest sites, we demonstrate our synthetic data-trained models can out-perform, or provide comparable performance with models trained on real data from other sites or when available real training data is limited (increases in IoU from 1–7%). Our simulation code is open-source and made available to the research community.

The Es4 source rock is the primary source of hydrocarbon in deep reservoirs in the Baxian Sag, Jizhong Depression of Bohai Bay Basin, China, and its quantitative description is useful for understanding hydrocarbon generation and accumulation in the deep basin. The Es4 source rock contains organofacies C, D/E and F, with organofacies C having a thin thickness of less than 40 m and organofacies D/E having a thickness of 50 m and 250 m. The drilled Es4 source rock has a maximum RO of 1.27%, indicating that it is in the late oil window. The kinetic parameters for three organofacies source rock have been obtained from the simulation of gold tube pyrolysis. The result showed that organofacies C, D/E and F source rock entered into the mature level in sequence, but that at 150 °C, the organofacies C will be transformed to around 90% of their original state. For organofacies D/E and F, the hydrocarbon generation potential is still high, with condensate and wet gas dominating.

Biopolymer silk fibroin (SF) is a great candidate for drug carriers characterized by its tunable biodegradability, and excellent biocompatibility properties. Recently, we have constructed SF-based nano-enabled drug delivery carriers, in which doxorubicin (Dox) and atovaquone (Ato) were encapsulated with Arg-Gly-Asp-SF-Polylactic Acid (RSA) to form micellar-like nanoparticles (RSA-Dox-Ato NPs). The RGD peptide was decorated on micellar-like nanoparticles, promoting tumor accumulation of the drug. Meanwhile, Ato, as a mitochondrial complex III inhibitor inhibiting mitochondrial respiration, would reverse the hypoxia microenvironment and enhance chemotherapy in the tumor. In vitro, the biopolymer alone showed extremely low cytotoxicity to 4T1 cell lines, while the RSA-Dox-Ato demonstrated a higher inhibition rate than other groups. Most significantly, the ROS levels in cells were obviously improved after being treated with RSA-Dox-Ato, indicating that the hypoxic microenvironment was alleviated. Eventually, SF-based targeted drug carrier provides biocompatibility to reverse hypoxia microenvironment in vivo for enhancing chemotherapy, strikingly suppressing tumor development, and thereby suggesting a promising candidate for drug delivery system.

Despite the fact that gross primary productivity (GPP) and water use efficiency (WUE) have been widely used as indicators to evaluate the water-carbon cycle, uncertainties exist in the patterns of GPP and WUE responses to climate variability along different aridity gradients. In this study, the aridity index was used to divide China into four arid-humid zones. The spatiotemporal variability of multiple vegetation types GPP and WUE in response to climate change under different arid-humid zones were investigated based on remote sensing data. The results indicated that the increasing trend of WUE in the four arid-humid zones of China was less pronounced than GPP from 2001 to 2021. The GPP value decreased gradually from the humid to the arid zone, and the WUE value in the arid zone was slightly higher than in the semi-arid zone. The GPP of all vegetation types in China showed a tendency to increase, while shrubland and wetland WUE tended to decrease. The major vegetation types (e.g., forest, cropland and grassland) in each aridity gradient contributed to the changes in local GPP and WUE. However, in individual arid-humid zones, wetland and shrubland also exhibited high GPP and WUE values that were not inferior to forest and cropland. Temperature and precipitation were the main climatic factors responsible for the increase in vegetation GPP in different aridity gradients, with a higher positive correlation for temperature than precipitation. WUE showed a distinct positive and negative correlation with the thermal factors (temperature and net radiation) and the moisture factors (precipitation and relative humidity); this pattern was more pronounced in the humid and semi-humid zones. Net radiation and precipitation may be the main climatic factors causing a slight upward trend in WUE across the arid-humid zones, while the decrease in shrubland and wetland WUE may be related to relative humidity and precipitation.

Accurate measurement of the geometric parameters of trees is a vital part of forest inventory in forestry management. Aerial and terrestrial Light Detection and Ranging (LiDAR) sensors are currently used in forest inventory as an effective and efficient means of forest data collection. Many recent approaches to processing and interpreting this data make use of supervised machine learning algorithms such as Deep Neural Networks (DNNs) due to their advantages in accuracy, robustness and the ability to adapt to new data and environments. In this paper, we develop new approaches to deep-learning-based forest point cloud analysis that address key issues in real applications in forests. Firstly, we develop a point cloud segmentation framework that identifies tree stem points in individual trees and is designed to improve performance when labelled training data are limited. To improve point cloud representation learning, we propose a handcrafted point cloud feature for semantic segmentation which plays a complementary role with DNNs in semantics extraction. Our handcrafted feature can be integrated with DNNs to improve segmentation performance. Additionally, we combine this feature with a semi-supervised and cross-dataset training process to effectively leverage unlabelled point cloud data during training. Secondly, we develop a supervised machine learning framework based on Recurrent Neural Networks (RNNs) that directly estimates the geometric parameters of individual tree stems (via a stacked cylinder model) from point clouds in a data-driven process, without the need for a separate procedure for model-fitting on points. The use of a one-stage deep learning algorithm for this task makes the process easily adaptable to new environments and datasets. To evaluate our methods for both the segmentation and parameter estimation tasks, we use four real-world datasets of different tree species collected using aerial and terrestrial LiDAR. For the segmentation task, we extensively evaluate our method on the three different settings of supervised, semi-supervised, and cross-dataset learning, and the experimental results indicate that both our handcrafted point cloud feature and our semi-supervised and cross-dataset learning framework can significantly improve tree segmentation performance under all three settings. For the tree parameter estimation task, our DNN-based method performs comparably to well-established traditional methods and opens up new avenues for DNN-based tree parameter estimation.

The concrete shear walls of masonry structures with RC frames on the first story are low-rise shear walls with a height–width ratio of less than 1. The strength, stiffness, and ductility of these low-rise shear walls are not matched, resulting in poor seismic performance. Based on the idea of the passive control theory and multi-seismic defensive lines, the scheme of a masonry structure with RC frames on the first story with a concrete-filled steel tubular (CFST) dampers is proposed in this paper. To explore the seismic mitigation effect of CFST dampers applied to a masonry structure with RC frames on the first story, the seismic performance under low-reversed cyclic loading of the frame with the CFST dampers is first compared with that of the energy-dissipated low-rise concrete shear wall proposed by previous researchers and the ordinary low-rise concrete shear wall. Furthermore, the response of the masonry structure model with RC frames on the first story with CFST dampers and two other comparative structural models under earthquake action are discussed. The results show that a masonry structure with RC frames on the first story with CFST dampers has a fuller hysteretic loop, lighter pinching, better energy dissipation ability, and better seismic performance. Compared with the other two structures, the energy dissipation capacity of the masonry structure with RC frames on the first story with CFST dampers is significantly improved, by 1.25~1.5 times. The amplification effect of the deformation angle allows the CFST dampers to play a significant role in energy dissipation, whereas the main structure still undergoes a small deformation. The CFST dampers can dissipate more seismic energy to protect the main structure from damage and improve the seismic performance of masonry structures with RC frames on the first story.

Pore structure in shale is an important factor influencing the storage capacity of a shale gas reservoir and the effect of shale gas development. Taking the core and outcrop shale samples from the Lower Cambrian Niutitang Formation and Lower Silurian Longmaxi Formation as the object of the research, combined with the scanning electron microscope, high pressure mercury injection, CO2 and N2 gas adsorption experiments, we investigated the porosity, pore types, pore structure, and pore size distribution of the Lower Paleozoic shale gas reservoirs in northern Guizhou, South China. The results indicated that there are developed various genetic types of micro-nano pores in the Lower Paleozoic marine shale in northern Guizhou, which provide the main reservoir spaces for shale gas. The porosity of the Lower Paleozoic shale in northern Guizhou is 1.30%–13.37% in range, and the average is 4.56%. The inter-granular pore, organic matter pore and intra-granular pore are most common. Micropore (

The imbalanced number and the high similarity of samples in expression database can lead to overfitting in facial recognition neural networks. To address this problem, based on edge computing, a facial expression recognition method using deep convolutional neural networks is proposed. In order to overcome the shortcoming that circular consensus adversarial network model can only be mapped one-to-one, we construct a constrained circular consensus generative adversarial network by adding class constraint information. Discriminators and classifiers in this network can share network parameters. In addition, for the problems of unstable training and easy to encounter model collapse in original GAN networks, this paper introduces gradient penalty rule into discriminator's loss function to achieve the normative constraint on gradient changes. Using this network not only generates sample data for a few classes in the training set of expression database, but also performs effective expression classification. Compared with other methods, the improved discriminative classifier network structure can enhance the diversity of samples and get a higher expression recognition rate. Even if other expression feature extraction methods are used, the higher recognition rate can still be obtained after using proposed data augmentation framework.

To reveal the relationship between agricultural water resource consumption and grain production in the Yellow River Basin, the irrigation water productivity (WPI), crop water productivity (WPC), total inflow water productivity (WPT), and eleven influencing factors were selected. The spatial and temporal distribution characteristics and driving factors of water productivity of the main crops in the Yellow River Basin were analyzed with the spatial autocorrelation analysis, grey correlation analysis, sensitivity analysis, and relative contribution rate. The results showed that the minimum mean values of WPI, WPC, and WPT were 0.22, 0.35, and 0.18 kg/m3 in Qinghai, respectively, the maximum mean value of WPI was 2.11 kg/m3 in Henan, and the maximum mean values of WPC and WPT were 0.71 and 0.61 kg/m3 in Shandong, respectively. The changing trends in WPI and WPT in Qinghai and in WPC in Shandong were insignificant, whereas the WPI, WPC, and WPT in other provinces showed a significant increasing trend. Water productivity displayed a certain spatial clustering feature in the Yellow River Basin in different years, such as a high-high (H-H) aggregation in Henan in 2005, and an H-H aggregation in Shanxi in 2015 for WPI. The water productivity had a significant positive correlation with the consumption of chemical fertilizer with a 100% effective component (CFCEC), effective irrigated area (EIA), plastic film used for agriculture (PFUA), and total power of agricultural machinery (AMTP), while it had a significant negative correlation with the persons engaged in rural areas (PERA). There was a large grey correlation degree between the water productivity and the average annual precipitation (AAP), CFCEC, PFUA, consumption of chemical pesticides (CFC), and AMTP in the Yellow River Basin, but their sensitivity was relatively small. The main driving factors were EIA (8.98%), agricultural water (AW, 15.55%), AMTP (12.64%), CFCEC (12.06%), and CPC (9.77%) for WPI; AMTP (16.46%), CFCEC (13.25%), average annual evaporation (AAE, 12.94%), EIA (10.49%), and PERA (10.19%) for WPC; and EIA (14.26%), AMTP (13.38%), AAP (12.30%), CFCEC (10.49%), and PFUA (9.69%) for WPT in the Yellow River Basin. The results can provide support for improving the utilization efficiency of agricultural water resources, optimizing the allocation of water resources, and implementing high-quality agricultural developments in the Yellow River Basin.

Warmer temperatures significantly influence crop yields, which are a critical determinant of food supply and human well-being. In this study, a probabilistic approach based on bivariate copula models was used to investigate the dependence (described by joint distribution) between crop yield and growing season temperature (TGS) in the major producing provinces of China for three staple crops (i.e., rice, wheat, and maize). Based on the outputs of 12 models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) under Shared Socioeconomic Pathway 5–8.5, the probability of yield reduction under 1.5 °C and 2 °C global warming was estimated, which has great implications for agricultural risk management. Results showed that yield response to TGS varied with crop and region, with the most vulnerable being rice in Sichuan, wheat in Sichuan and Gansu, and maize in Shandong, Liaoning, Jilin, Nei Mongol, Shanxi, and Hebei. Among the selected five copulas, Archimedean/elliptical copulas were more suitable to describe the joint distribution between TGS and yield in most rice-/maize-producing provinces. The probability of yield reduction was greater in vulnerable provinces than in non-vulnerable provinces, with maize facing a higher risk of warming-driven yield loss than rice and wheat. Compared to the 1.5 °C global warming, an additional 0.5 °C warming would increase the yield loss risk in vulnerable provinces by 2–17%, 1–16%, and 3–17% for rice, wheat, and maize, respectively. The copula-based model proved to be an effective tool to provide probabilistic estimates of yield reduction due to warming and can be applied to other crops and regions. The results of this study demonstrated the importance of keeping global warming within 1.5 °C to mitigate the yield loss risk and optimize agricultural decision-making in vulnerable regions.

The myometrium is the outer layer of the uterus. Its contraction and steroidogenic activities are required for embryo implantation. However, the molecular mechanisms underlying its functions remain unknown in pigs. The myometrium includes the inner circular muscle (CM) and the outer longitudinal muscle (LM) layers. In this study, we collected the CM and LM samples from the mesometrial side (named M) of the uterus on days 12 (pre-implantation stage) and 15 (implantation stage) of pregnancy and day 15 of the estrous cycle. The transcriptomic results revealed distinct differences between the uterine CM and LM layers in early pregnancy: the genes expressed in the LM layer were mainly related to contraction pathways, whereas the transcriptional signatures in the CM layer on day 15 of pregnancy were primarily involved in the immune response processes. Subsequent comparisons in the CM layer between pregnant and cyclic gilts show that the transcriptional signatures of the CM layer are implantation-dependent. Next, we investigated the genome-wide profiling of histone H3 lysine 27 acetylation (H3K27ac) and histone H3 lysine 4 trimethylation (H3K4me3) in pig uterine CM and LM layers. The genomic regions that had transcriptional activity and were associated with the expression of genes in the two layers were characterized. Taken together, the regulatory regions identified in the study may contribute to modulating the gene expression in pig uterine CM and LM layers during implantation.

In order to investigate the potential of the Lower Cambrian shale gas in South China, a study on the accumulation condition of shale gas from the Niutitang Formation was conducted. In addition, the favorable accumulation area of shale gas in northern Guizhou was evaluated. The study and evaluation were both analyzed according to the geochemical analysis data of the core and outcrop samples in this paper. The result shows that the Niutitang Formation shale in northern Guizhou is formed in the shallow sea sedimentary environment, which features moderate buried depth (3.0%), type I kerogens, over-mature thermal evolution level (Ro>2.0%), low porosity, abundant micro- and nano-meter pores and fractures, rich brittle mineral (average content >40%), and relatively high gas content (average 1.5 m3/t). The aforementioned feature indicates that the Niutitang Formation in northern Guizhou has good accumulation condition for shale gas. Through the studies above, it is proposed that the southeastern Shiqian—Yuqing—Shibing area is the most favorable area for shale gas accumulation in northern Guizhou. Keywords: Shale gas, Accumulation condition, Favorable area evaluation, Niutitang Formation, Organic-rich shale, Northern Guizhou

Attachment of conceptus to the endometrial luminal epithelium (LE) is a critical event for early placentation in Eutheria. Since the attachment occurs at a particular site within the uterus, a coordinated communication between three spatially distinct compartments (conceptus and endometrial LE from two anatomical regions of the uterus to which conceptus attaches and does not attach) is essential but remains to be fully characterized. Using the laser capture microdissection (LCM) technique, we firstly developed an approach that can allow us to pair the pig conceptus sample with its nearby endometrial epithelium sample without losing the native spatial information. Then, a comprehensive spatio-temporal transcriptomic profile without losing the original conceptus-endometrium coordinates was constructed. The analysis shows that an apparent difference in transcriptional responses to the conceptus exists between the endometrial LE from the two anatomically distinct regions in the uterus. In addition, we identified the communication pathways that link the conceptus and endometrial LE and found that these pathways have important roles in conceptus attachment. Furthermore, a number of genes whose expression is spatially restricted in the two different anatomical regions within the uterus were characterized for the first time and two of them (SULT2A1 and MEP1B) may cooperatively contribute to establish conceptus attachment in pigs. The results from our study have implications in understanding of conceptus/embryo attachment in pigs and other large polytocous species.

Data was acquired from both the drillings and core samples of the Lower Paleozoic Qiongzhusi and Longmaxi Formations' marine shale gas reservoirs in the southern Sichuan Basin by means of numerous specific experimental methods such as organic geochemistry, organic petrology, and pore analyses. Findings helped determine the characteristics of organic matter, total porosity, microscopic pore, and pore structure. The results show that the Lower Paleozoic marine shale in the south of the Sichuan Basin are characterized by high total organic carbon content (most TOC>2.0%), high thermal maturity level (RO = 2.3%–3.8%), and low total porosity (1.16%–6.87%). The total organic carbon content and thermal maturity level of the Qiongzhusi Formation shale are higher than those of the Longmaxi Formation shale, while the total porosity of the Qiongzhusi Formation shale is lower than that of the Longmaxi Formation shale. There exists intergranular pore, dissolved pore, crystal particle pore, particle edge pore, and organic matter pore in the Lower Paleozoic Qiongzhusi Formation and Longmaxi Formation shale. There are more micro-nano pores developed in the Longmaxi Formation shales than those in the Qiongzhusi Formation shales. Intergranular pores, dissolved pores, as well as organic matter pores, are the most abundant, these are primary storage spaces for shale gas. The microscopic pores in the Lower Paleozoic shales are mainly composed of micropores, mesopores, and a small amount of macropores. The micropore and mesopore in the Qiongzhusi Formation shale account for 83.92% of the total pore volume. The micropore and mesopore in the Longmaxi Formation shale accounts for 78.17% of the total pore volume. Thus, the micropores and mesopores are the chief components of microscopic pores in the Lower Paleozoic shale gas reservoirs in the southern Sichuan Basin.

Based on the raw data of the organic-rich shale in the Lower Cambrian Qiongzhusi Formation and Lower Silurian Longmaxi Formation which were collected from the drilling core, we investigated the accumulation conditions of the Lower Paleozoic marine shale gas in the southern Sichuan Basin, China. The results indicate that the Qiongzhusi and the Longmaxi Formations' black shales in this region are mainly deposited in the deep water shelf sedimentary environment. Both the Qiongzhusi and Longmaxi Formations in the southern Sichuan Basin have great organic-rich shale thickness (mainly 50–300 m). The marine shales of the Qiongzhusi and the Longmaxi Formations are characterized by high total organic carbon contents (average TOC>2%), I–II1 kerogen types, highthermal maturity level (equivalent RO>1.9%), abundant rich brittle mineral (average > 50%), micro- and nanometer pore development, as well as high gas content of shale (average > 1.8 m3/t). All these features are favorable for marine shale gas generation and enrichment in the southern Sichuan Basin. Compared to the Barnett shale in North America, in which shale gas has been explored and developed successfully, it is suggested that the Lower Paleozoic in the southern Sichuan Basin would possess good conditions for shale gas accumulation. Therefore, the Qiongzhusi and the Longmaxi Formations are considered as potential targets for marine shale gas exploration, and favorable areas for shale gas enrichment are also purposed. The favorable areas for shale gas enrichment for the Qiongzhusi Formation in the southern Sichuan Basin are the Zhigong-Yibin, Changning-Gongxian, Jianwei-Muchuan, and Weiyuan areas. The favorable areas for shale gas enrichment for the Longmaxi Formation in the southern Sichuan Basin are the Longchang-Rongchang, Yibin-Luzhou-Changning, and Weiyuan areas.

In this study, the RegCM4 regional climate model was employed to investigate the impacts of water consumption in the Haihe Plain on the local climate in the nearby Taihang Mountains. Four simulation tests of twelve years’ duration were conducted with various schemes of water consumption by residents, industries, and agriculture. The results indicate that water exploitation and consumption in the Haihe Plain causes wetting and cooling of the local land surface and rapid increases in the depth of the groundwater table. These wetting and cooling effects increase atmospheric moisture, which is transported to surrounding areas, including the Taihang Mountains to the west. In a simulation where water consumption in the Haihe Plain was doubled, the wetting and cooling effects in the Taihang Mountains were enhanced but at less than double the amount, because a cooler land surface does not enhance atmospheric convective activities. The impacts of water consumption activities in the Haihe Plain were more obvious during the irrigation seasons (primarily spring and summer). In addition, the land surface variables in the Taihang Mountains, e.g., sensible and latent heat fluxes, were less sensitive to the climatic impacts due to the water consumption activities in the Haihe Plain because they were strongly affected by local surface energy balance.

The porosities of the Lower Cambrian shale and Upper Ordovician-Lower Silurian marine shale from the Sichuan Basin were analyzed using He-Hg porosimetry and field-emission scanning electron microscopy, to discuss the relationship of porosity to the organic matter maturity, total organic carbon (TOC) and free gas volume. Overmature (Ro greater than 2%) shale samples with a TOC less than 5% display a positive correlation between TOC and porosity, but samples with a TOC greater than 5% display a limited increase in porosity with increasing TOC. The porosity of shale decreases generally with increasing maturity in the overmature stage. The free gas in porosity is the key factor for successful development of shale gas, and free gas volumes are controlled by porosity and gas saturation. Higher TOC shale has higher porosity and gas saturation. The Lower Silurian Longmaxi Formation shale has a higher TOC, Ro ranging from 2.0% to 2.3%, its porosity and gas saturation are significantly higher than the Lower Cambrian shale. The high free gas volume results in high production in the Lower Silurian Longmaxi Formation shale pay. Key words: marine shale, porosity, free gas, overmature, Sichuan Basin

Our research aimed to look into the clinical traits and genetic mutations in sporadic non-syndromic anodontia and to gain insight into the role of mutations of PAX9, MSX1, AXIN2 and EDA in anodontia phenotypes, especially for the PAX9. Material and Methods The female proband and her family members from the ethnic Han families underwent complete oral examinations and received a retrospective review. Venous blood samples were obtained to screen variants in the PAX9, MSX1, AXIN2, and EDA genes. A case-control study was performed on 50 subjects with sporadic tooth agenesis (cases) and 100 healthy controls, which genotyped a PAX9 gene polymorphism (rs4904210). Results Intra-oral and panoramic radiographs revealed that the female proband had anodontia denoted by the complete absence of teeth in both the primary and secondary dentitions, while all her family members maintained normal dentitions. Detected in the female proband were variants of the PAX9 and AXIN2 including A240P (rs4904210) of the PAX9, c.148C>T (rs2240308), c.1365A>G (rs9915936) and c.1386C>T (rs1133683) of the AXIN2. The same variants were present in her unaffected younger brother. The PAX9 variations were in a different state in her parents. Mutations in the MSX1 and EDA genes were not identified. No significant diferences were found in the allele and genotype frequencies of the PAX9 polymorphism between the controls and the subjects with sporadic tooth agenesis. Conclusions These results suggest that the association of A240P with sporadic tooth agenesis still remains obscure, especially for different populations. The genotype/phenotype correlation in congenital anodontia should be verified.

Quantifying the effects of climate change and human activities on runoff changes is the focus of climate change and hydrological research. This paper presents an integrated method employing the Budyko-based Fu model, hydrological modeling, and climate elasticity approaches to separate the effects of the two driving factors on surface runoff in the Luan River basin, China. The Budyko-based Fu model and the double mass curve method are used to analyze runoff changes during the period 1958~2009. Then two types of hydrological models (the distributed Soil and Water Assessment Tool model and the lumped SIMHYD model) and seven climate elasticity methods (including a nonparametric method and six Budyko-based methods) are applied to estimate the contributions of climate change and human activities to runoff change. The results show that all quantification methods are effective, and the results obtained by the nine methods are generally consistent. During the study period, the effects of climate change on runoff change accounted for 28.3~46.8% while those of human activities contributed with 53.2~71.7%, indicating that both factors have significant effects on the runoff decline in the basin, and that the effects of human activities are relatively stronger than those of climate change.