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Abstract Rotala rotundifolia is an amphibious aquatic plant that can live in submerged and emergent forms. It is superior in nitrogen and phosphorus removal and has been used as a traditional medicine in China for over a hundred years. In this study, the bioactive constituents from different tissues of submerged and emergent R. rotundifolia at different growth periods were investigated. The response surface method was used to optimize the flavonoids extraction condition. The amount of flavonoids and triterpenoids from different tissues of R. rotundifolia were much higher than tannins and alkaloids. The highest total flavonoids amount from the leaves of submerged R. rotundifolia was 270.92 ± 13.34 mg/g at day 30 (phyllomorphosis finished), 1.8 times that of the emergent form (150.45 ± 15.11 mg/g). The highest triterpenoids content from the submerged and emergent forms was 242.20 ± 11.51 and 163.09 ± 14.87 mg/g at days 90 and 150 (flowering stage), respectively. The optimal flavonoid extraction conditions were: extraction time 50 min, ultrasonic power 333 W, ethanol concentration 79.3%, and a solid–liquid ratio of 1:60. The LC-MS/MS analysis showed that the extracts from submerged and emergent R. rotundifolia contained 26 and 22 flavonoids, respectively. This study provides phytochemical evidence for the further utilization of R. rotundifolia.

Abstract Surrounding rock pressure prediction for fully mechanized coal face (FMCF) roof management and control is of great significance. The key challenge is to effectively combine various factors to evolve the surrounding rock pressure trend with high temporal-spatial correlation and heterogeneity. The hydraulic support load is an important indicator that reflects the change in the surrounding rock pressure. Inspired by the research on 'support-surrounding rock’ and the massive data collected by sensors, this paper proposes a data-driven prediction framework for surrounding rock pressure in FMCFs. The framework includes the multidimensional working condition matrix (MWCM) building module, the hydraulic support group temporal-spatial feature fusion (HTSFF) network, and the adaptive deployment strategy (ADS). The MWCM generating methods of hydraulic support in combination with the mining process and the data quality and quantity requirements of the conventional supervised learning method are weakened by the treatment of missing data adapting to the working conditions. The HTSFF network focuses on capturing the spatial correlation of the surrounding rock pressure along the mining direction and the temporal periodicity along the advancing direction of the FMCF and fully considers the dependencies between them. ADS aims to solve the problem of missing data in model deployment and reduce the interference of abnormal data in the model prediction process by adaptively generating MWCM. The rationality and practicability of various designs of the proposed framework were verified on our dataset. Quantitative experiments show that the average error of the surrounding rock pressure prediction is 1.2406 MPa, and the accuracy, precision, and recall rate of periodic pressure prediction are all above 95%. This method can effectively assist FMCF roof management and control. Although the method is effective, it may require further fine-tuning of the model to adapt to different geological conditions and varying sensor quality, ensuring broader applicability.

Abstract Background Non-hypervascular hypointense nodules (NHHNs) can transform into hypervascular hepatocellular carcinoma (HCC) during the long-term follow-up. However, the risk factors for NHHN hypervascular transformation in chronic hepatitis B virus (HBV)-infected populations are unknown. This study assessed the predictive value of gadoxetic acid-enhanced magnetic resonance imaging (MRI) for HCC development in patients with chronic HBV infection. Methods A total of 86 patients with HBV infection who underwent gadoxetic acid-enhanced MRI at the First Affiliated Hospital of Sun Yat-sen University between January 2011 and July 2019 and were followed up for 2 years were retrospectively reviewed. Imaging features, including cirrhosis, steatosis, and NHHNs, were collected. Radiomics features were extracted from the entire liver. The HCC development predictive models were built based on each patient’s clinical data, MRI features, and radiomic features. We then collected the qualitative and quantitative features of each NHHN and investigated the risk factors of hypervascular transformation. Results Thirteen patients developed HCC within two years. The risk factors for HCC development in patients with chronic HBV infection included older age, cirrhosis, and NHHNs. The MRI, radiomics, and integrated models developed all had an area under the curve (AUC) above 0.8. The potential risk factors for hypervascular transformation of NHHNs were the diameter of the NHHN (OR = 1.69, 95% CI:1.23, 2.32, P = 0.001) and the signal intensity (SI) ratio of the NHHN to the liver in the hepatobiliary phase (HBP SI ratio*10, OR = 0.36, 95% CI:0.11, 0.85, P = 0.044). The AUC of the hypervascular transformation model was 0.846 (95% CI:0.719, 0.972). Conclusion In chronic HBV infection population, patients with older age, cirrhosis and NHHNs are more likely to develop HCC within two years. Models based on these factors or radiomic features can effectively predict HCC development. The diameter of the NHHNs and the signal intensity ratio of NHHN to the liver in the hepatobiliary phase are potential risk factors for the hypervascular transformation of NHHNs.

Abstract Background Homo- and heteromerization of G protein-coupled receptors (GPCRs) plays an important role in the regulation of receptor functions. Recently, we demonstrated an interaction between the serotonin receptor 7 (5-HT7R), a class A GPCR, and the cell adhesion molecule CD44. However, the functional consequences of this interaction on 5-HT7R-mediated signaling remained enigmatic. Methods Using a quantitative FRET (Förster resonance energy transfer) approach, we determined the affinities for the formation of homo- and heteromeric complexes of 5-HT7R and CD44. The impact of heteromerization on 5-HT7R-mediated cAMP signaling was assessed using a cAMP responsive luciferase assay and a FRET-based cAMP biosensor under basal conditions as well as upon pharmacological modulation of the 5-HT7R and/or CD44 with specific ligands. We also investigated receptor-mediated G protein activation using BRET (bioluminescence resonance energy transfer)-based biosensors in both, homo- and heteromeric conditions. Finally, we analyzed expression profiles for 5-HT7R and CD44 in the brain during development. Results We found that homo- and heteromerization of the 5-HT7R and CD44 occur at similar extent. Functionally, heteromerization increased 5-HT7R-mediated cAMP production under basal conditions. In contrast, agonist-mediated cAMP production was decreased in the presence of CD44. Mechanistically, this might be explained by increased Gαs and decreased GαoB activation by 5-HT7R/CD44 heteromers. Unexpectedly, treatment of the heteromeric complex with the CD44 ligand hyaluronic acid boosted constitutive 5-HT7R-mediated cAMP signaling and receptor-mediated transcription, suggesting the existence of a transactivation mechanism. Conclusions Interaction with the hyaluronan receptor CD44 modulates both the constitutive activity of 5-HT7R as well as its agonist-mediated signaling. Heteromerization also results in the transactivation of 5-HT7R-mediated signaling via CD44 ligand.

Abstract As the main equipment of coal mining production, the anomaly detection of shearer is important to ensure production efficiency and coal mine safety. One key challenge lies in the limited or even absence of labeled monitoring data for the equipment, coupled with the high costs associated with manual annotation. Another challenge stems from the complex structure of the mining machines, making it difficult to reflect the overall operational state through local anomaly detection. Consequently, the application of decoupled local anomaly detection for mining machines in practical production remains challenging. This paper presents an unsupervised learning-based method for detecting anomalies in shearer. The method includes a module for constructing a Multi-scale Correlation Matrix (MSCM) of mining machine operating conditions, as well as the CNN-ConvLSTM Autoencoder (C-CLA) network. The module for constructing an MSCM enhances the representation of interrelationships between various features of the equipment from different perspectives using multiple correlation analysis methods. The C-CLA network integrates convolutional and convolutional recurrent neural networks, with the convolutional structure extracting local spatial features and the ConvLSTM structure further capturing information from different time scales and feature scales, thereby enhancing the model’s perceptual capabilities towards changes in equipment status. Finally, shearer anomaly detection is achieved through the analysis of reconstructed residual matrices. The rationality and practicality of the proposed method have been validated on our dataset, and the model’s generalization capability has been verified through repeated experiments in similar scenarios. However, due to variations in the working environment of different mining faces and differences in equipment models, implementing detection on other mining faces often requires retraining the model with new data. Furthermore, we compared our method with other anomaly detection techniques, and our detection efficiency was superior by approximately 3%. This method effectively detects anomalies in the shearer.

Abstract Background Root systems are key contributors to plant health, resilience, and, ultimately, yield of agricultural crops. To optimize plant performance, phenotyping trials are conducted to breed plants with diverse root traits. However, traditional analysis methods are often labour-intensive and invasive to the root system, therefore limiting high-throughput phenotyping. Spectral electrical impedance tomography (sEIT) could help as a non-invasive and cost-efficient alternative to optical root analysis, potentially providing 2D or 3D spatio-temporal information on root development and activity. Although impedance measurements have been shown to be sensitive to root biomass, nutrient status, and diurnal activity, only few attempts have been made to employ tomographic algorithms to recover spatially resolved information on root systems. In this study, we aim to establish relationships between tomographic electrical polarization signatures and root traits of different fine root systems (maize, pinto bean, black bean, and soy bean) under hydroponic conditions. Results Our results show that, with the use of an optimized data acquisition scheme, sEIT is capable of providing spatially resolved information on root biomass and root surface area for all investigated root systems. We found strong correlations between the total polarization strength and the root biomass ( $$R^2 = 0.82$$ R 2 = 0.82 ) and root surface area ( $$R^2 = 0.8$$ R 2 = 0.8 ). Our findings suggest that the captured polarization signature is dominated by cell-scale polarization processes. Additionally, we demonstrate that the resolution characteristics of the measurement scheme can have a significant impact on the tomographic reconstruction of root traits. Conclusion Our findings showcase that sEIT is a promising tool for the tomographic reconstruction of root traits in high-throughput root phenotyping trials and should be evaluated as a substitute for traditional, often time-consuming, root characterization methods.

The indoor thermal history of residents in the hot summer and cold winter climate zone in China have undergone a significant change in recent years, which also changes their seasonal thermal adaptations and this has formed feed-back effects to the increasing usage of air conditioning units in this area. To study the seasonal variations of thermal adaptation, the thermal comfort experiments were conducted on two groups of participants. Each groups included 20 participants who had indoor history mainly with natural ventilation (NV group) and air-conditioning (AC group), respectively. The results demonstrated that the thermal sensation vote (TSV) in warm environments did not differ between AC and NV subjects in summer. However, the TSV of AC subjects were much lower than that of NV subjects in the same standard effective temperature and skin temperature in a cold environment in winter. Overall, the participants who spent most of their time in AC space in winter showed a low level of thermal adaptation with a narrower acceptable skin temperature range of 32.6 – 33.5 °C. Thus, this study presents the basic information regarding the seasonal effects on human thermal adaptation due to different long-term indoor thermal histories.

Urban green spaces (UGS) contribute to residents’ health by promoting physical activity. However, there are significant spatial and socioeconomic disparities in UGS accessibility, leading to unequal access to UGS benefits among residents. Current assessments of UGS accessibility often overlook the role of UGS in promoting physical activity. Additionally, the consideration of UGS components typically focuses on their quantity rather than diversity. In light of this, our study proposes an evaluation method for the Physical Activity Diversity Index (PADI) of UGS and revises the supply scale parameter in the Gaussian two-step floating catchment area (Ga2SFCA) model based on this index. Taking Harbin, China as an example, we measure UGS accessibility and explore its association with residents’ income levels using the bivariate Moran’s I and multiple linear regression models. Our findings indicate that a higher PADI can partially compensate for insufficient UGS area, thereby increasing accessibility in certain areas and alleviating the relative disadvantage of low-income groups in accessing UGS. Considering PADI can more accurately identify underserved areas, providing more precise guidance for urban planning. This study highlights the importance of considering the diversity of UGS components in accessibility assessments and offers feasible solutions to mitigate spatial and socioeconomic disparities in UGS accessibility.

The MILD combustion is a combustion mode that occurs in a moderate or extremely low oxygen environment, combining the advantages of high combustion heat utilization and very low NOx emissions, and is considered by the international combustion field to be one of the cleaner combustion technologies with great potential for application. Since the relevant research began around 1990, the technology for achieving a MILD combustion of gas fuels has been relatively mature, while the research on the MILD combustion mechanism and implementation conditions of solid fuels such as coal powder and biomass is still relatively lacking. Based on the high momentum oxidizer jet, internal recirculation is achieved, eliminating the need for external high-temperature preheating to establish MILD combustion, greatly expanding the application range of MILD combustion. This paper provides an overview of the basic characteristics of MILD powder fuel combustion from the aspects of particle dispersion, heating, ignition, combustion, and pollutants. Due to the uneven dispersion and reaction of particles, the MILD combustion process of carbon-based solid fuels such as coal powder is more complex than that of gas fuels. High speed jet MILD combustion not only increases ignition delay but also expands ignition and reaction zones, requiring systematic research on the characteristics and mechanisms of each combustion stage. This paper introduces the research achievements in the theoretical design and equipment development of solid fuel MILD combustion. It is recommended to improve the existing coal-fired boiler burner, adjust the process parameters to match the MILD combustion mode, increase the residence time of coke particles to improve combustion efficiency, improve combustion stability, and suppress various pollutant emissions, including fine particulate matter, through high-precision numerical simulation. Based on the overall approach of interconnected energy systems, the coupling research between MILD combustion and various new combustion technologies should be promoted, especially strengthening the research on the co-combustion characteristics of coal powder, biomass and hydrogen, ammonia and other combustible gases, and assisting in energy transformation. Exploring the characteristics of turbulent two-phase flow, turbulent interphase heat transfer, and turbulent chemical coupling in the powder MILD combustion is crucial for deepening the understanding of powder MILD combustion. It involves multivariate analysis and high-precision simulation, which will be the focus and difficulty of future research.

Under the carbon peaking and carbon neutrality strategy, biomass has attracted much attention due to its characteristics of regeneration, low pollution and zero carbon emissions. The imperfects of biomass, such as the loose structure and low energy density, can be effectively solved by briquetting, and the resulted fuel pellets can be used as a substitute for fossil fuels, which is of great significance for the construction of new energy system. In the paper, the influencing factors of the hot briquetting process of biomass were summarized, and the evolution behavior and binding mechanism of biomass particles during the hot briquetting process were analyzed and discussed. Biomass briquetting process mainly includes cold briquetting and hot briquetting. Compared with cold briquetting process of biomass, hot briquetting with lower energy consumption can produce the biomass fuel pellets with higher quality. The moisture content (4%−15%) of the raw biomass has greater influence, the briquetting temperature (70−150 ℃) has relatively smaller effect on the density of the fuel pellets, and the briquetting pressure (60−130 MPa) and the particle size ( < 2.5 mm) of the raw material show the different impact on the density of the fuel pellets from different biomass. During the hot process, cellulose mainly plays the role of supporting skeleton, hemicellulose and lignin play the role of binder. In the microcosmic process of hot briquetting process, the inertia movement and subsequent viscoelastic-plastic deformation of the biomass particles occur and the mechanical interlock is formed between the particles. The brittle particles are broken and the natural viscous components are released, and thus, the bridge linkage between the particles is formed under the integrated effects of moisture, temperature and pressure. Mechanical interlocking and bridging reduce the distance between biomass molecules and promote the generation of intermolecular forces. Based on the above-mentioned mechanism of the hot briquetting of biomass, the quality of the resulted fuel pellets can be improved by biomass component adjustment, biomass blending or hydrothermal pretreatment. In the future, the molecular dynamics simulation method will be used to investigate the biomass briquetting process to obtain the molecular bonding mechanism of biomass components, which is conducive to further exploring the hot briquetting mechanism of biomass, and provide important guiding significance for the preparation of fuel pellets and molding materials from biomass.

Abstract Background Increasing evidence proves that RBP7 plays a significant role in breast cancer (BC). The present study was aimed to investigate the mechanism of RBP7. Methods Western Blotting and qRT-PCR were performed for evaluating the expression levels. CCK8, colony forming, xenograft mouse model, wound healing and transwell assays were conducted to examine cell ability of proliferation, invasion and migration. Nile red staining and Oil red O staining were used for testing the lipid. Results RBP7 was related to overall survival (OS) in patients with HR + BC. RBP7 protein was significantly decreased in HR + BC tissues and cells. RBP7 suppressed HR + BC cell proliferation in vitro and in vivo, and inhibited migration and invasion. RBP7 reduced fatty acid in HR + BC cells by inhibiting the AKT/SREBP1 pathway. Conclusions RBP7 may function as a tumor suppressor in HR + BC by inhibiting the AKT/SREBP1 pathway and reducing fatty acid.

In order to solve the potential safety hazards caused by the fluctuation of photovoltaic (PV) power generation, it is necessary to predict it in advance and take countermeasures as soon as possible. Based on the three models of vanilla Transformer, Informer, and Autoformer, this paper considers three prediction scenarios: zero-cost prediction, low-cost prediction, and high-cost prediction, and realizes the power prediction under two prediction horizons of 4 h and 24 h for a matrix of a centralized PV power station in Hubei Province, China. The results of some configurations meet the industry-recommended metric requirements, and the overall performance of the vanilla Transformer is better than Informer and Autoformer. After comparing the three models and different prediction intervals, and considering the practical industrial demand, this paper gives recommended configurations for both 4 h and 24 h predictions. The practical rolling prediction performance of the recommended configurations demonstrates the applicability and flexibility of the proposed methods.

Purpose: The product recommendation type is attracting attention from both the retail and academic communities. However, there is no consensus on the effectiveness of set recommendation versus separate recommendation. This research investigates the interaction effect of product recommendation type and consumer’s focal goal importance on initial product purchase intention and cross-buying intention. Design/methodology/approach: Four studies were used to examine the hypotheses, including three experimental studies with general participants and a field study with student participants. Findings/results: An empirical analysis confirms an interaction relationship between product recommendation style and focal goal importance on enhancing purchase. When focal goal importance is high, set recommendation has a more positive effect on purchase intention. When focal goal importance is low, the separate recommendation has a more positive effect on purchase intention. Practical implications: Research findings provide guidance for sellers on which product recommendation type to use with different customers. Sellers should be flexible in determining different product recommendation types through different consumers’ focal goals. Originality/value: Findings reveal the congruency effect between product recommendation type and consumer’s focal goal importance, which indicates an interaction effect on initial product purchase intention and cross-buying intention. In addition, this research expands the application of regulatory focus theory and analyses the underlying mechanism by exploring the role of perceived incompleteness and cognitive load.

Abstract Rock salt is considered a suitable medium for the permanent disposal of heat‐generating radioactive waste due to its isolation properties. However, excavation damage and heating induce complex and heterogeneous thermal‐hydrological‐mechanical (THM) processes across different zones. Quantifying this heterogeneity is crucial for accurate long‐term performance assessment models, but traditional methods lack the necessary resolution. This study employs 4D electrical resistivity tomography (ERT) monitoring during controlled heating experiments in a salt formation to unravel the spatiotemporal dynamics of THM processes. Advanced time‐lapse inversion and clustering analysis quantify subsurface properties and map the heterogeneity of THM dynamics. The ERT results can estimate subsurface properties and delineate the damaged and intact zones, enabling appropriate parameterization and representation of processes for long‐term modeling. This approach may be used in further improving the predictive models and ensuring the safe long‐term disposal of radioactive waste in rock salt.

IntroductionMolecular subgroups influence the vascular architecture within medulloblastomas, particularly the wingless (WNT) subgroup, which contributes to its propensity for primary tumor hemorrhage. Whether this mechanism affects intraoperative blood loss remains unknown. This study aimed to assess the association between WNT medulloblastoma and the predisposition for blood loss.MethodsThis was a retrospective observational study using data from a neuro-oncology center comprising molecular data on patients treated between December 31, 2014, and April 30, 2023. Differences between WNT and other subgroups in the risk of primary outcome-intraoperative blood loss were assessed using multivariable-adjusted linear regression.ResultsOf the 148 patients included in the analysis, 18 patients (12.2%) had WNT, 42 (28.4%) had sonic hedgehog (SHH) TP53-wildtype, 7 (4.7%) had SHH TP53-mutant, and 81 (54.7%) were non-WNT/ non-SHH. The WNT subgroup more frequently underwent primary intratumoral hemorrhage (22% vs. 3.8%; p = 0.011). The median intraoperative blood loss was 400.00 (interquartile range [IQR] 250, 500) mL for WNT and 300.00 [200, 400] mL for the other subgroups (p = 0.136), with an adjusted β of 135.264 (95% confidence intervals [CI], 11.701–258.827; p = 0.032). Similar results were observed in both midline and noninfiltrative margin medulloblastoma.DiscussionWNT medulloblastoma is typically associated with primary intratumoral hemorrhage and intraoperative blood loss. The validity of determining the surgical approach based on predicted molecular subtypes from imaging data is questionable. However, attempting to engage in risk communication with patients in a molecular-specific way is worthwhile to validate.

Objective: This study explores the structural relationships between sustainable development and competitive advantage in tourism enterprises, along with the mediating role of dynamic capability, especially following the impact of COVID-19. Design/Method/Approach: An online questionnaire survey was conducted to collect 430 valid primary data sets from middle and senior managers in Henan tourism enterprises. Covariance-based structural equation modeling was utilized to test the direct effect, while the bootstrap method was used for testing mediating effects. Findings: The results reveal that sustainable development has a significant impact on the competitive advantage of tourism enterprises from three sustainability dimensions: economic, environmental and social. Meanwhile, dynamic capabilities represented by adaptive, absorptive and innovative capacities play a mediating role between them. Conclusions/Recommendation: The reshaping of the tourism industry by COVID-19 requires practitioners to take dynamic capability seriously in an uncertain environment. The higher demand for sustainability from tourists after the pandemic also suggests that improvements are a viable way for tourism enterprises to restore and cultivate competitive advantage. Originality/ Value: This study focuses on public health emergencies which are scarce in tourism crisis research (Duan et al., 2021). In addition, it is designed to help managers identify elements that can be used as internal drivers (Wang, 2021) showing how firms can incorporate sustainable development into strategic management, as this is still lacking (Zhang et al., 2020) in practice.

Abstract Grasslands are one of the most common land‐cover types, providing important ecosystem services globally, yet few studies have examined grassland critical‐zone functioning throughout hillslopes. This study characterised a coastal grassland over a small hillslope at Point Reyes National Seashore, California, using multidisciplinary techniques, combining remotely‐sensed, geophysical, plant, and soil measurements. Clustering techniques delineated the study area into four landscape zones, up‐, mid‐, and down‐slope, and a bordering riparian ecotone, which had distinct environmental properties that varied spatially across the site, with depth, and time. Soil moisture increased with depth and down slope towards a bordering riparian zone, and co‐varied with soil CO2 flux rates both spatially and temporally. This highlighted three distinct controls of soil moisture on soil respiration: CO2 fluxes were inhibited by high moisture content in the down‐slope during the wet winter months, and converged across landscape positions in the dry summer months, while also displaying post‐rain pulses. The normalised difference vegetation index (NDVI) ranged from 0.32 (September)–0.80 (April) and correlated positively with soil moisture and aboveground biomass, moving down slope. Yet, NDVI, aboveground biomass, and soil moisture were not correlated to soil organic carbon (SOC) content (0.4%–4.5%), which was highest in the mid‐slope. The SOC content may instead be linked to shifts in dominant grassland species and their rhizosphere properties with landscape position. This multidisciplinary characterisation highlighted significant heterogeneity in grassland properties with landscape position, and demonstrated an approach that could be used to characterise other critical‐zone environments on hillslopes.

BackgroundHealthy aging is crucial to the quality of life of older adults, of which mental health is an essential part. Physical exercise strongly affects their mental health and can alleviate psychological problems to a certain extent. Nevertheless, the correlation between physical exercise and the mental health of older adults individuals, as well as the underlying mechanism by which physical exercise impacts mental health, remains rather ambiguous.MethodsWe utilized multiple linear regression models to investigate the relationship between physical activity and mental health in 3,240 persons aged 60 and up. The propensity score matching (PSM) method was used to assess the robustness of the regression results. In addition, sequential recursive models were employed to investigate the mediating role of social competence in the link between physical activity and mental health.Results and discussionWe discovered a strong favorable association between physical exercise and mental health, which was mediated by social competence. Furthermore, the effect of physical exercise on mental health differed across older persons from various socioeconomic backgrounds.ConclusionOlder adults should strengthen their understanding of the role of physical exercise. Sports organizations that serve older adults by providing resources and services to help them maintain physical fitness and by hosting sports activities and competitions according to their needs should be established.

A method for detecting mebendazole and its metabolites in cattle and sheep products was established by EMR-Lipid-ultra-performance liquid chromatography-tandem mass spectrometry. The samples were first extracted by oscillation with 0.2% ammoniated acetonitrile solution, then freeze centrifugation, purified by Captiva EMR-Lipid column and directly analyzed by LC-MS/MS. The 3 kinds of mebendazole drugs were separated by SB-C18 column (2.1 mm×100 mm, 1.8 μm) and gradiently eluted with acetonitrile and 0.1% formic acid water solution as mobile phase. The detection of mebendazole drugs was performed by tandem mass spectrometry in electrospray ionization under multiple reactions monitoring (MRM) mode. Matrix matching standard working curve and internal standard method were used for quantification. The calibration curves for target compounds were linear over the range of 0.2~50 ng/mL with correlation coefficients larger than 0.999. The detection limits (S/N>3) of 3 kinds of mebendazole drugs were 0.3 μg/kg. The recoveries of the 3 kinds of mebendazole drugs at three added levels were between 80.5% and 108.0%．The relative standard deviations were 1.1%~5.8%. The method overcame the current shortcomings of cumbersome preprocessing and long detection cycle, and it was simple in operation and accurate in results. The method was applicable to the rapid detection of mebendazole and its metabolites residues in cattle and sheep products.

Considering the percentage of dissatisfied due to local thermal sensation (PDLTSV), a vertical air temperature difference (ΔTd) threshold of about 3 °C was recommended in standards. However, some novel air distribution methods might create large positive (which means the head warmer than the feet, vice versa) or negative ΔTd, with no suitable proved criteria to be used. In this study, sixteen subjects were seated in a climatic box placed in a climate chamber to evaluate thermal sensation and percentage of dissatisfied with negative and positive ΔTd in different whole-body thermal conditions. Air temperatures were controlled independently at the upper and lower body parts, with 13 different air temperature sets combined with 22 °C, 25 °C, 28 °C, and 31 °C (i.e. -9 °C ≤ ΔTd ≤ 9 °C). Results showed that subjects were more thermally sensitive at the upper body and with positive ΔTd than at the lower body or with negative ΔTd. The 80% acceptable ΔTd range is about -8 to 7 °C in overall neutral (TSV = 0), -7 °C to 6 °C in slightly cool (TSV = -0.5) conditions, which is wider than -3 to 3 °C in slightly warm conditions (TSV = +0.5). By considering the factors of both TSV and ΔTd, a new overall percentage of dissatisfied index (OPDP) was proposed. Case studies show that the new OPDP index is more precise and suitable for the evaluations of different air distributions to predict overall percentage of dissatisfied in thermal environments with vertical air temperature difference.

Background/Objectives: Excessive reactive oxygen species (ROS) can lead to oxidative stress, which has become an urgent problem requiring effective solutions. Due to the drawbacks of chemically synthesized antioxidants, there is a growing interest in natural antioxidants, particularly antioxidant peptides. Methods: By reviewing recent literature on antioxidant peptides, particularly those extracted from various parts of fish, summarize which fish by-products are more conducive to the extraction of antioxidant peptides and elaborate on their characteristics. Results: This article summarizes recent advancements in extracting antioxidant peptides from fish processing by-products, Briefly introduced the purification and identification process of antioxidant peptides, specifically focusing on the extraction of antioxidant peptides from various fish by-products. Additionally, this article comprehensively reviews the relationship between amino acid residues that compose antioxidant peptides and their potential mechanisms of action. It explores the impact of amino acid types, molecular weight, and structure–activity relationships on antioxidant efficacy. Conclusions: Different amino acid residues can contribute to the antioxidant activity of peptides by scavenging free radicals, chelating metal ions, and modulating enzyme activities. The smaller the molecular weight of the antioxidant peptide, the stronger its antioxidant activity. Additionally, the antioxidant activity of peptides is influenced by specific amino acids located at the C-terminus and N-terminus positions. Simultaneously, this review provides a more systematic analysis and a broader perspective based on existing research, concluded that fish viscera are more favorable for the extraction of antioxidant peptides, providing new insights for the practical application of fish by-products. This could increase the utilization of fish viscera and reduce the environmental pollution caused by their waste, offering valuable references for the study and application of antioxidant peptides from fish by-products.

The alteration of landscape spatial patterns (LSPs) and ecosystem services (ESs) in watersheds can have detrimental effects on the local environment and community. However, a comprehensive understanding of the current state of LSPs and ESs in watersheds around Winter Olympic venues in China is limited. Here, we assessed current LSPs and ESs and developed optimization strategies for the Xigou watershed around Winter Olympic venues in the northern agro-pastoral ecotone of China. The results indicated that the main land use type was grassland in the Xigou watershed, and landscape types were relatively homogenous. All three ESs (water yield, sediment retention, and carbon storage) generally improved from 2004 to 2020. For ESs, there was the lowest total volume of water yield in 2004 (637.44 × 104 m3). But sediment retention (10.54 × 106 t, 18.13 × 106 t, 13.28 × 106 t, and 16.85 × 106 t) had an upward, then downward, then upward trend before and after ERP. Carbon storage grew steadily. Correlation analysis suggested that the three ESs were closely related to the landscape spatial indices of average patch area (AREA_MN), contagion index (CONTAG), and Shannon’s evenness index (SHEI). AREA_MN, CONTAG, and SHEI in the eastern part of the study area promoted sediment retention and carbon storage, while in the southwestern part of the study area, they inhibited water yield and sediment retention. The results suggest that improving sediment retention by optimizing land use and cover change (LUCC) and LSPs is the main approach to further enhance ESs in the study area. Our study suggests that the inclusion of multiple landscape pattern indices can provide a more comprehensive representation of regional ecosystem service.

Passion fruit is a valued tropical fruit crop that faces environment-related growth strains. TCP genes are important for both growth modulation and stress prevention in plants. Herein, we systematically analyzed the TCP gene family in passion fruit, recognizing 30 members. Genes exhibiting closer phylogenetic relationships exhibited similar protein and gene structures. Gene members of the TCP family showed developmental-stage- or tissue-specific expression profiles during the passion fruit life cycle. Transcriptome data also demonstrated that many PeTCPs showed induced expression in response to hormonal treatments and cold, heat, and salt stress. Based on transcriptomics data, eight candidate genes were chosen for preferential gene expression confirmation under cold stress conditions. The qRT-PCR assays suggested PeTCP15/16/17/19/23 upregulation, while PeTCP1/11/25 downregulation after cold stress. Additionally, TCP19/20/29/30 exhibited in silico binding with cold-stress-related miRNA319s. GFP subcellular localization assays exhibited PeTCP19/1 were localized at the nucleus. This study will aid in the establishment of novel germplasm, as well as the further investigation of the roles of PeTCPs and their cold stress resistance characteristics.

In the context of Integrated Energy System (IES), accurate short-term power demand forecasting is crucial for ensuring system reliability, optimizing operational efficiency through resource allocation, and supporting effective real-time decision-making in energy management. However, achieving high forecasting accuracy faces significant challenges due to the inherent complexity and stochastic nature of IES’s short-term load profiles, resulting from diverse consumption patterns among end-users and the intricate coupling within the network of interconnected energy sources. To address this issue, a dedicated Short-Term Power Load Forecasting (STPLF) framework for IES is proposed, which relies on a newly developed hybrid deep learning architecture. The framework seamlessly combines Long Short-Term Memory (LSTM) with Temporal Convolutional Network (TCN), enhanced by an attention mechanism module. By merging these methodologies, the network leverages the parallel processing prowess of TCN alongside LSTM’s ability to retain long-range temporal information, thus enabling it to dynamically concentrate on relevant sections of time series data. This synergy leads to improved prediction accuracy and broader applicability. Furthermore, the integration of residual connections within the network structure serves to deepen its learning capabilities and enhance overall performance. Ultimately, results from a real case study of a user-level IES demonstrate that the Mean Absolute Percentage Error (MAPE) of the proposed framework on the test set is 2.35%. This error rate is lower than the averages of traditional methods (3.43%) and uncombined single submodules (2.80%).

Abstract Background Pulmonary mucinous adenocarcinoma is a special type of lung cancer. Its imaging manifestations are diverse, which brings challenges to clinical diagnosis. However, its formation mechanism is unclear. Objective The objective of this study is to analyse the relevant mechanisms of the formation of pulmonary mucinous adenocarcinoma by observing its different imaging and pathological manifestations. Data and methods Retrospective analysis was conducted on imaging manifestations and pathological data of 103 patients with pulmonary mucinous adenocarcinoma confirmed intraoperatively or pathologically. Results Forty‐three patients had pulmonary mucinous adenocarcinoma with a solitary nodule/mass, 41 patients with localized pneumonia and 19 patients with diffuse pneumonia. Their CT manifestations included ‘falling snowflake sign’, ground‐glass opacity close to the heart, vacuous signs/honeycombing and withered tree branches. Under the microscope, all the three types of pulmonary mucinous adenocarcinoma had visibly formed mucus lakes but were made of tumour cells with totally different shapes, which included the goblet‐like shape (tall column‐like shape) and quasi‐circular shape. Tall column‐shaped tumour cells were negative or weakly positive for thyroid transcription factor‐1 (TTF‐1) and strongly positive for ALK mutation, whereas quasi‐circular tumour cells were positive for TTF‐1 and less positive for ALK mutation. Conclusion The different imaging manifestations of mucinous adenocarcinoma are possibly due to the different amounts or viscosity of mucus produced, and the mechanisms of its formation may include (1) tumour cells in different shapes have different abilities to produce mucus; (2) tumours in different stages produce different amounts or viscosity of mucus; and (3) the TTF‐1 and ALK genes affect the production of mucus.

Cardiovascular diseases (CVDs) are one of the leading causes of death worldwide. Despite significant advances in current drug therapies, issues such as poor drug targeting and severe side effects persist. In recent years, nanomedicine has been extensively applied in the research and treatment of CVDs. Among these, biomembrane-modified biomimetic nanodrug delivery systems (BNDSs) have emerged as a research focus due to their unique biocompatibility and efficient drug delivery capabilities. By modifying with biological membranes, BNDSs can effectively reduce recognition and clearance by the immune system, enhance biocompatibility and circulation time in vivo, and improve drug targeting. This review first provides an overview of the classification and pathological mechanisms of CVDs, then systematically summarizes the research progress of BNDSs in the treatment of CVDs, discussing their design principles, functional characteristics, and clinical application potential. Finally, it highlights the issues and challenges faced in the clinical translation of BNDSs.

The velocity obstacles (VO) method is widely employed in real-time obstacle avoidance research for UAVs due to its succinct mathematical foundation and rapid, dynamic planning abilities. Traditionally, VO assumes a circle protection domain with a fixed radius, leading to issues such as excessive conservatism of obstacle avoidance areas, longer detour paths, and unnecessary avoidance angles. To overcome these challenges, this paper firstly reviews the fundamentals and pre-existing defects of the VO methodology. Next, we explore a scenario involving UAVs in head-on conflicts and introduce an elliptic velocity obstacle method tailored to the UAV’s current flight state. This method connects the protection domain size directly to the UAV’s flight state, transitioning from the conventional circle domain to a more efficient elliptic domain. Additionally, to manage the computational demands of Minkowski sums and velocity obstacle cones, an approximation algorithm for discretizing elliptic boundary points is introduced. A strategy to mitigate unilateral velocity oscillation had is developed. Comparative validation simulations in MATLAB R2022a confirm that, based on the experimental results for the first 10 s, the apex angle of the velocity obstacle cone for the elliptical domain is, on average, reduced by 0.1733 radians compared to the circular domain per unit simulation time interval, saving an airspace area of 13,292 square meters and reducing the detour distance by 14.92 m throughout the obstacle avoidance process, facilitating navigation in crowded situations and improving airspace utilization.

In 2021, the price of most of the domestic coal skyrocketed, affecting the stable supply of electric power supply in some regions, while the price of Xinjiang Zhundong coal remains stable at a low level. Thus, the study of safe and stable large-scale combustion of Zhundong coal in boilers is more and more important for the energy supplyHowever, fouling and slagging often occur on the heating surfaces of the boiler due to the characteristics of Zhundong coal and the high temperature of the flue gas. The effects of the operating parameters, including the primary air velocity, operating oxygen content, air staging and coal fineness on the combustion temperature and NOx emission were investigated on a four-corner tangentially fired boiler of 660 MW capacity, which burned 95% Zhundong coal to get the relevant control criterion. Based on the research, the improvement of control function for contamination of heating surfaces was implemented under steady and dynamic working conditions. Finally, the influence of the improvement on the contamination of the heating surfaces was proved by the method of the contamination monitoring of heated surfaces. The results show that, at 660 MW load condition, the operating oxygen content had the most obvious influence on the flue gas temperature at the outlet of the furnace. The flue gas temperature decreased 99 °C when it increased from 2.0% to 3.5%. The reduction of the operating oxygen content and the local mean stoichiometric ratio of the main combustion zone could lead to a significant reduction of NOx emission and the change of the coal fineness had no obvious effect on NOx emission. After the improved control function was implemented, the rate of flue gas temperature decreased from 6.18 to 4.26 °C min−1 during the load increase process, the maximum temperature decreased from 1104 to 1023 °C under 660 MW. The heat absorption ratio of the platen superheater, low-temperature superheater and low-temperature reheater increased by 0.6%, 1.6% and 0.9%, respectively, indicating that the fouling and slagging was significantly reduced. At 330 MW load condition, increasing the coal fineness R90 to around 4.9% of the uppermost mill could effectively reduce the flue gas temperature near the bottom of the high-temperature reheater, reduce the deposition of combustible matter and fly ash, and inhibit the formation of fouling and slagging.

Developing a cleaner and more efficient combustion technology of pulverized coal is an important way to deal with the increasingly serious environmental pollution. Moderate or intense low-oxygen dilution (MILD) combustion of pulverized coal is regarded as a new combustion technology with great potential due to its advantages of reducing NOx emission and improving the uniformity of heat flux in the furnace. More importantly, the pulverized coal MILD technology combined with the oxy-fuel combustion technology will be an important path to reduce carbon emission in the process of coal utilization in the future. The history, characteristics and current research status of the MILD combustion of pulverized coal worldwide are summarized, and the key issues and research challenges of the MILD combustion technology of pulverized coal with a low preheating temperature are put forward. The MILD combustion technology of pulverized coal originates from that of gaseous fuels, which strengthen the entrainment of high-temperature flue gas and then dilute the reactants to make the flame become blurred or even invisible. Under the MILD conditions, the peak temperature in the combustion region is reduced and the uniformity of temperature distribution is improved, therefore significantly inhibiting the generation of thermal NOx and fuel NOx. The MILD combustion of pulverized coal can be realized by preheating air to high temperatures or increasing the jet velocity greatly, and the second way is more economical and feasible. However, the mechanisms and characteristics of the MILD combustion of pulverized coal under the condition of strong shear and turbulent mixing, when the jet velocity is as high as around 100 m/s, still need to be further investigated. Under the strong shear and entrainment of high-speed jets, the dispersion of coal particles, which is directly related to the achievement of the MILD combustion mode, is quite different from that in the conventional coal combustion. In addition, a strong turbulent mixing will affect the heating, devolatilization and char combustion of pulverized coal, therefore changing the ignition delay, the flame structure and the generation of pollutants. Based on the in-depth understanding of the above key issues and combined with the research on the MILD combustion of gaseous fuels, a systematic and accurate criterion for the MILD combustion of pulverized coal can be further developed, so as to better guide the application of the MILD combustion technology of pulverized coal.

The Soil serves as the foundational pillar that sustains life on our planet, providing vital resources such as food and raw materials. However, the pursuit of technological advancements aimed at ex- tracting more from natural reserves, coupled with the necessity of supporting growing populations, has compromised the intricate natural systems that maintain life on Earth. Over the past decades, erosion and pollution have led to the degradation of one-third of the world’s arable land. Regret- tably, modern agricultural practices, characterised by extensive tilling and the heavy use of chemical fertilisers, have resulted in the erosion of topsoil, leaving it vulnerable and diminishing both food security and the soil’s capacity for carbon sequestration (Maximillian et al., 2019). In 2014, the UN Food and Agriculture Organisation (FAO) reported that the world’s remaining topsoil has been rapidly deteriorating and is expected to be completely degraded in the next 60 years. Without intervention, this leaves a mere six decades of viable harvests remaining.

The cotton stalk is a typical biomass waste. Its problems such as the loose structure, low calorific value and low energy density can be effectively solved by hydrothermal treatment and hot pressing forming. In this study, the Xinjiang cotton stalk was taken as the research object, and the molded particles were prepared after completing the 180−280 ℃ hydrothermal treatment experiment using a high-pressure reactor. The diffraction of the main chemical components (cellulose, hemicellulose and lignin) in the cotton stalk was analyzed by means of Fourier infrared analyzer and X-ray diffractometer. The influence of the three-component diffraction behavior of biomass on the physical properties of the molding particles was explored. The influence of the evolution of the main chemical components (cellulose, hemicellulose, lignin) in the cotton stalk on the physical properties of its pellets and the key components were investigated. The results show that with the increase of hydrothermal temperature, the compress strength and apparent density of cotton stalk pellets increased first and then decreased, and reached the highest value at 230 ℃ (The compress strength was 9.3 MPa, the apparent density was 1 478.46 kg/m3). In the hydrothermal treatment process, the hemicellulose was completely decomposed before 200 ℃, the amorphous cellulose and crystalline cellulose were completely decomposed before 230 ℃ and 280 ℃, respectively, while the lignin still existed at 280 ℃. Finally, based on the variation trend of the physical properties of the pellets, it was found that the crystalline cellulose played a skeleton supporting role in the cotton stalk pellets, which was an important component to provide mechanical strength and also an important source of apparent density. Lignin, as a binder in the pellets, could strengthen the degree of bonding between surrounding particles during the densification process.

Abstract Background Lung cancer has always been the malignant tumor with the highest incidence rate. Smoking is the most important risk factor for lung cancer. Although potential positive effects of smoking cessation interventions on the high-risk population of lung cancer have been observed, evidence of its definitive effect remains uncertain. This study aimed to summarize the evidence related to the effects and safety of smoking cessation interventions for the high-risk population of lung cancer. Methods A systematic literature search was conducted through the following seven databases: PubMed, Embase, Web of Science, CENTRAL, CINAHL, PsycINFO, and Science Direct. Screening and assessment for risk of bias were conducted by two independent reviewers. Meta-analysis was performed for the 7-day-point prevalence of smoking abstinence and continuous smoking abstinence using RevMan 5.3 software. Results Meta-analysis results show that in the 7-day-point prevalence of smoking abstinence (by patient-reported outcome): individualized intervention was significantly higher than that of the standard care [RR = 1.46, 95%CI = (1.04,2.06), P

Summary: ERBB receptor tyrosine kinases are involved in development and diseases like cancer, cardiovascular, neurodevelopmental, and mental disorders. Although existing drugs target ERBB receptors, the next generation of drugs requires enhanced selectivity and understanding of physiological pathway responses to improve efficiency and reduce side effects. To address this, we developed a multilevel barcoded reporter profiling assay, termed ‘ERBBprofiler’, in living cells to monitor the activity of all ERBB targets and key physiological pathways simultaneously. This assay helps differentiate on-target therapeutic effects from off-target and off-pathway side effects of ERBB antagonists. To challenge the assay, eight established ERBB antagonists were profiled. Known effects were confirmed, and previously uncharacterized properties were discovered, such as pyrotinib’s preference for ERBB4 over EGFR. Additionally, two lead compounds selectively targeting ERBB4 were profiled, showing promise for clinical trials. Taken together, this multiparametric profiling approach can guide early-stage drug development and lead to improved future therapeutic interventions.

Objective The study aimed to explore the association between the site of interictal epileptic discharges (IEDs) on postoperative electroencephalogram (EEG) and seizure recurrence after antiepileptic drug (AED) withdrawal. The study hypothesizes that the concordance of IED sites with surgical sites indicates incomplete resection of epileptic focus, while non-concordance of IED sites with surgical sites indicates postoperative changes or cortical stimulation. The former has a higher risk of seizure recurrence.Methods We retrospectively analyzed the postoperative EEG pattern of 182 consecutive children who underwent resection surgery. To identify the risk factors for seizure recurrence, we compared the attributes of seizure recurred and seizure-free groups by univariate and multivariate analyses. AED tapering was standardized, involving a 25% reduction in the dose of a single type of AED every 2 weeks, independent of the presurgical AED load.Results We attempted AED withdrawal in 116 (63.7%) children. Twenty-eight (24.1%) children experienced seizure recurrence during or after AED withdrawal. A greater number of AEDs used at the time of surgery (p=0.005), incomplete resection (p=0.001), and presence of IED on postoperative EEG (p=0.011) are predictors of seizure recurrence. The completeness of resection and seizure recurrence after AED withdrawal were related to the presence of IED on the EEG, but not to the concordance of IED with surgical sites.Conclusion For children with abnormal EEG, the decision to discontinue AED should be made more cautiously, regardless of the relative location of the discharge site and the surgical site.

Abstract Hydrogeophysical methods have been increasingly used to study subsurface soil–water dynamics, yet their application beyond the soil compartment or the quantitative link to soil hydraulic properties remains limited. To examine how these methods can inform model‐based evapotranspiration (ET) calculation under varying soil water conditions, we conducted a pilot‐scale field study at an experimental maize plot with manipulated irrigation treatments. Our goal was to develop a workflow for (1) acquiring and inverting field electrical resistivity tomography (ERT) data, (2) correlating ERT to soil hydraulic properties, (3) spatially characterizing soil water stress that feeds into ET modeling (the FAO‐56 model), and (4) evaluating the performance of ERT‐based ET computation. Our results showed that ERT was able to capture decimeter‐scale soil water content (SWC) dynamics from root water uptake and irrigation manipulation and the contrast of soil water stress between deficiently and fully irrigated maize. We also demonstrated the flexibility of using ERT to spatially integrate soil water stress in the soil volume of interest, which could be adjusted based on different crops and plot layouts. The integration of the ERT datasets into ET modeling provided insights into the spatial heterogeneity of the subsurface that has been challenging for point‐based sensing, which can further our understanding of the hydraulic dynamics in the soil‐plant‐atmosphere continuum.

In this study, we develop a machine-learning (ML)-enabled strategy for selecting hillslope-scale ecohydrological monitoring sites within snow-dominated mountainous watersheds, with a particular focus on snow-soil–plant interactions. Data layers rely on spatial data layers from both remote sensing and hydrological model simulations. Specifically, a Landsat-based foresummer drought sensitivity index is used to define the dependency of the annual peak plant productivity on the Palmer drought severity index in the early growing season. Hydrological simulations provide the spatiotemporal dynamics of near-surface soil moisture and snow depth. In this framework, a regression analysis identifies the key hydrological variables relevant to the spatial heterogeneity of drought sensitivity. We then apply unsupervised clustering to these key variables, using the Gaussian mixture model, to group hillslopes into several zones that have divergent relationships regarding soil moisture, snow dynamics, and drought sensitivity. Using the datasets collected in the East River Watershed (Crested Butte, Colorado, United States), results show that drought sensitivity is significantly correlated with model-derived soil moisture and snow-free timing over space and time. The relationship is, however, non-linear, such that the correlation decreases above a threshold elevation and in a heavy snow year due to large snowpacks, lateral flow, and soil storage limitations. Clustering is then able to define the zones that have high or low sensitivity to drought, as well as the mid-elevation regions where sensitivity is associated with the topographic aspect and net potential radiation. In addition, the algorithm identifies the most representative hillslopes with road/trail access within each zone for installing monitoring sites. Our method also aims to significantly increase the use of ML and model-simulation results to guide critical zone and watershed monitoring activities.

BackgroundThe COVID-19 pandemic, caused by the SARS-CoV-2 virus, has necessitated reliable and authoritative information for public guidance. The World Health Organization (WHO) has been a primary source of such information, disseminating it through a question and answer format on its official website. Concurrently, ChatGPT 3.5 and 4.0, a deep learning-based natural language generation system, has shown potential in generating diverse text types based on user input. ObjectiveThis study evaluates the accuracy of COVID-19 information generated by ChatGPT 3.5 and 4.0, assessing its potential as a supplementary public information source during the pandemic. MethodsWe extracted 487 COVID-19–related questions from the WHO’s official website and used ChatGPT 3.5 and 4.0 to generate corresponding answers. These generated answers were then compared against the official WHO responses for evaluation. Two clinical experts scored the generated answers on a scale of 0-5 across 4 dimensions—accuracy, comprehensiveness, relevance, and clarity—with higher scores indicating better performance in each dimension. The WHO responses served as the reference for this assessment. Additionally, we used the BERT (Bidirectional Encoder Representations from Transformers) model to generate similarity scores (0-1) between the generated and official answers, providing a dual validation mechanism. ResultsThe mean (SD) scores for ChatGPT 3.5–generated answers were 3.47 (0.725) for accuracy, 3.89 (0.719) for comprehensiveness, 4.09 (0.787) for relevance, and 3.49 (0.809) for clarity. For ChatGPT 4.0, the mean (SD) scores were 4.15 (0.780), 4.47 (0.641), 4.56 (0.600), and 4.09 (0.698), respectively. All differences were statistically significant (P

Abstract Background While some lung adenocarcinoma (LUAD) patients benefit long-term from treatment with immune checkpoint inhibitors, the sad reality is that a considerable proportion of patients do not. The classification of the LUAD tumor microenvironment (TME) can be used to conceptually comprehend primary resistance mechanisms. In addition, the most recent research demonstrates that the release of damage-associated molecular pattern (DAMP) in TME by immunogenic cell death (ICD) may contribute to the adaptive immune response. Currently, however, there is no such comprehensive research on this topic in LUAD patients. Therefore, we set out to investigate how to reverse the poor infiltration characteristics of immune cells and boost antitumor immunity by identifying DAMP model. Methods In this study, ICD-related DAMP genes were selected to investigate their effects on the prognosis of LUAD. To create a risk signature using the TCGA-LUAD cohort, the univariate COX regression and the least absolute shrinkage and selection operator regression were carried out, and the results were verified in a GEO dataset. Subsequently, the multivariate COX regression was applied to establish a prognostic nomogram. And the ESTIMATE and ssGSEA algorithms were utilized to analyze immune activity and the TIDE algorithm was for responsiveness to immunotherapy. Moreover, clinical tissue samples were used to verify the differential expression of 9 DAMP genes in the signature. Results We identified two distinct DAMP molecular subtypes, and there are remarkable differences in survival probability between the two subtypes, and patients with higher levels of DAMP-related genes are “hot tumors” with increased immune activity. In addition, 9 DAMP genes were selected as prognostic signature genes, and clinical outcomes and immunotherapy response were better for participants in the low-risk group. Importantly, according to the area under the curve (AUC) value in evaluating the efficacy of immunotherapy, this signature is superior to existing predictors, such as PD-L1 and TIDE. Conclusions Our study suggests ICD plays an important part in modeling the TME of LUAD patients. And this signature could be utilized as a reliable predictor to estimate clinical outcomes and predict immunotherapy efficacy among LUAD patients.

Abstract To support multi-source data stream generated from Internet of Things devices, edge computing emerges as a promising computing pattern with low latency and high bandwidth compared to cloud computing. To enhance the performance of edge computing within limited communication and computation resources, we study a cloud-edge-end computing architecture, where one cloud server and multiple computational access points can collaboratively process the compute-intensive data streams that come from multiple sources. Moreover, a multi-source environment is considered, in which the wireless channel and the characteristic of the data stream are time-varying. To adapt to the dynamic network environment, we first formulate the optimization problem as a markov decision process and then decompose it into a data stream offloading ratio assignment sub-problem and a resource allocation sub-problem. Meanwhile, in order to reduce the action space, we further design a novel approach that combines the proximal policy optimization (PPO) scheme with convex optimization, where the PPO is used for the data stream offloading assignment, while the convex optimization is employed for the resource allocation. The simulated outcomes in this work can help the development of the application of the multi-source data stream.

Urban green spaces (UGSs) play a significant role in promoting public health by facilitating outdoor activities, but issues of spatial and socioeconomic inequality within UGSs have drawn increasing attention. However, current methods for assessing UGS inequality still face challenges such as data acquisition difficulties and low identification accuracy. Taking Harbin as a case study, this research employs various advanced technologies, including Python data scraping, drone imagery collection, and Amap API, to gather a diverse range of data on UGSs, including photos, high-resolution images, and AOI boundaries. Firstly, elements related to physical activity within UGSs are integrated into a supply adjustment index (SAI), based on which UGSs are classified into three categories. Then, a supply–demand improved two-step floating catchment area (SD2SFCA) method is employed to more accurately measure the accessibility of these three types of UGSs. Finally, using multiple linear regression analysis and Mann–Whitney U tests, socioeconomic inequalities in UGS accessibility are explored. The results indicate that (1) significant differentiation exists in the types of UGS services available in various urban areas, with a severe lack of small-scale, low-supply UGSs; (2) accessibility of all types of UGSs is significantly positively associated with housing prices, with higher-priced areas demonstrating notably higher accessibility compared to lower-priced ones; (3) children may be at a disadvantage in accessing UGSs with medium-supply levels. Future planning efforts need to enhance attention to vulnerable groups. This study underscores the importance of considering different types of UGSs in inequality assessments and proposes a method that could serve as a valuable tool for accurately assessing UGS inequality.

In China, 65 types of venomous snakes exist, with the Chinese Cobra Naja atra being prominent and a major cause of snakebites in humans. Furthermore, N. atra is a protected animal in some areas, as it has been listed as vulnerable by the International Union for Conservation of Nature. Recently, due to the medical value of snake venoms, venomics has experienced growing research interest. In particular, genomic resources are crucial for understanding the molecular mechanisms of venom production. Here, we report a highly continuous genome assembly of N. atra, based on a snake sample from Huangshan, Anhui, China. The size of this genome is 1.67 Gb, while its repeat content constitutes 37.8% of the genome. A total of 26,432 functional genes were annotated. This data provides an essential resource for studying venom production in N. atra. It may also provide guidance for the protection of this species.

An effective approach to reducing building energy is determining the proper insulation location of the exterior walls. Two conflicting conclusions were found in previous research that focused on the optimal insulation location of exterior walls in buildings with intermittently operated convective air systems (CASs). Why conflicting conclusions are produced and which factors influence them have not yet been answered. Thus, this paper analyzes the generation of the transmission load through the exterior walls with outside and inside insulation, and accordingly evaluates the parameters that might affect the energy-saving advantage of two insulation locations. An analytic model is utilized to calculate the heat transfer through the exterior walls. Results show that the heat stored in exterior walls’ inner layer during CAS off-periods is the key to determining the relative energy-saving of two insulation locations. Furthermore, the relative energy-saving increases with thermal capacity of exterior envelopes and air change rate but decreases with the increase in thermal capacity of interior envelopes and setpoint temperature. Based on these, a predictive model is devised to determine the proper insulation location of exterior wall. A critical daily sol-air temperature range beyond which the relative energy-saving advantage transitions is found using the model.

The digital economy is an important driving force for the high-quality development of the manufacturing industry. This paper uses 2013–2019 manufacturing panel data to empirically test the impact of digital economic growth on China's manufacturing export competitiveness. The results show that, first, the degree of integration of manufacturing and digital economy in the eastern region is higher than that in the central and western regions. Second, the development of the digital economy has indeed had a significant positive impact on the export competitiveness of China's manufacturing industry. Third, the digital economy has different impacts on the export competitiveness of manufacturing industries in different industries and regions. Based on the findings, some suggestions are made to further enhance the export competitiveness of China's manufacturing industry, such as paying attention to the development of digital infrastructure, optimizing the mode of integration of the manufacturing sector and the digital economy, and enhancing international collaboration in digital technology innovation.

Abstract The Mongolian Plateau (MP) is in the interior of Northeast Asia, far from the sea, and is extremely vulnerable to climate change and the deleterious effects of human activity. The United Nations Sustainable Development Goals (SDGs) explicitly set land degradation neutrality (LDN) as one of the sub‐goals of the seventeen main tasks. However, achieving this goal in Mongolia, a country with a fragile and sensitive ecological environment and a lack of high‐precision land cover and land degradation monitoring data, is challenging. In this study, we established rules for remote sensing‐based land cover classification and reference threshold ranges based on an object‐oriented remote sensing interpretation method. Then, we obtained the refined land cover data of Mongolia from 1990, 2000, 2010 and 2020 with 30‐m resolution. The land cover classification of Mongolia comprises 11 categories: forest, meadow steppe, real steppe, desert steppe, barren, sand, desert, ice, water, cropland and built area. The overall classification accuracies, corresponding to the aforementioned data year, were 82.26%, 82.77%, 92.34% and 81.84%, respectively. We found that the land cover showed an apparent law of zonal gradual change. Among them, barren land, real steppe, desert steppe and forest were consistently the four major land cover types. Since the last 30 years, barren land areas present an overall decreasing trend, showing a trend of shrinking to the south. Overall, real steppe presents a wavelike decreasing trend, and desert steppe shows a fluctuating increasing trend. The forest area is relatively stable with no notable changes in spatial distribution. The dataset of this study fills the gaps in high‐resolution land cover data for Mongolia, and it can provide fundamental scientific data to support sustainable development in the MP.

Dissolved oxygen (DO) is crucial for fish farming, and when fish experience hypoxic stress, negative effects such as the disruption of normal physiological activities, a decline in aerobic swimming ability, and feeding restriction will occur. In this study, healthy Epinephelus coioides individuals were subjected to hypoxic (DO = 0.6 ± 0.1 mg/L) and reoxygenation treatments (DO = 6.0 ± 0.1 mg/L), with a normoxic group (DO = 6.0 ± 0.1 mg/L) set as the control. Transcriptome sequencing (RNA-seq) was performed on the brains of E. coioides in hypoxia-sensitive (EBW), hypoxia-tolerant (EBS), and normoxic control (CB) groups. In total, 1174 differentially expressed genes (DEGs) were screened from the three groups. KEGG analysis revealed several pathways, including the HIF-1 signaling pathway, and immune-related pathways such as MAPK signaling, microRNAs (miRNAs), and oxidative phosphorylation pathways enriched in the EBS group, and cAMP signaling pathway enriched in the EBW group. Moreover, a variety of significant hypoxia-responsive DEGs involved in energy metabolism and immune reactions were identified in the EBS and EBW groups. qRTPCR analysis showed that the key DEGs HIF-1α, LDH-A, PPARα, PNP, RAB13, DDIT4, TNF-1, and ALDOA were significantly upregulated in the brain tissues of E. coioides under acute hypoxic stress and that their expression returned to normoxic levels after reoxygenation, indicating that they provided energy to the organism and regulated severe damage and lesions appearing in the brains of E. coioides during hypoxic stress to prolong the survival time of the organism. Altogether, these results suggest that hypoxia disrupts the expression patterns of multiple genes in E. coioides and that these genes may participate in resistance and adaptation to hypoxia in the organisms by regulating apoptosis, proliferation, differentiation, and energy metabolism.

Salt solution pool boiling is of great significance in thermal engineering equipment, such as boilers and heat exchangers. Few researchers have been able to draw on systematic research into the impacts of salt concentration on boiling heat transfer coefficients. This experimental work is aimed to understand the role of dissolved salts on pool boiling performance, which is affected by surface wettability and bubble dynamics. Pool boiling experiment was conducted within a broad range of salt concentration. The results show two different tendencies for the two heating surfaces. The heat transfer coefficient is enhanced in the pin–fin heating surface while deteriorated in the bare heating surface as the salt concentration increased. It is indicated that salt solution promotes bubble diameter and nucleate density for ∼13% and 9%, respectively, by strengthening the hydrophobicity of the pin–fin heating surface. Hence, the boiling heat transfer is strengthened.

Lobular capillary hemangioma (LCH), previously known as pyogenic granuloma, is a benign vascular lesion commonly found within the oral and nasal cavities. However, it is rarely encountered within the trachea, especially in pediatric patients, where it manifests as hemoptysis, cough, and wheeze, and is frequently misdiagnosed as bronchitis or asthma. There is limited literature on the presentation, behavior, and management of tracheal LCH. Herein, we describe a rare case of tracheal LCH in an 11-year-old boy with a history of hemoptysis, which was successfully managed with arterial embolization followed by electrocautery loop snaring via flexible bronchoscopy. No complications occurred during and after the procedure. A review of the relevant literature is also provided. Our case is unique, given the therapeutic strategy utilized for pediatric tracheal LCH, and reminds physicians to be aware of tracheal LCH in the differential diagnosis for hemoptysis.

Based on snow coverage remote sensing data NOAA, the simulation ability of the snow coverage rate from the core experiments of the 5th Coupled Model Intercomparison Project (CMIP5) over the Upper Yarkant River Basin was evaluated. The ensemble mean of the eight models was used to project future changes in the snow coverage rate over the basin under the three different representative concentration pathways (RCP2.6, RCP4.5 and RCP8.5). The results show that the snow coverage rate of the eight models can basically simulate a sharp drop of the spatial distribution from the west to the northeast; all the eight models have the capacity to simulate the snow coverage rate of the Yarkant River Basin analyzed from the correlation analysis (R), the ratio of spatial standard deviation (SDR) and the S index. The simulation capacity of the eight models in spring, autumn and winter is stronger than the one in summer, and the ensemble mean of the eight models simulates the best. Under the scenarios of RCP2.6 and RCP4.5, changes in the snow coverage rate show negative differences in most areas over the basin, only the local part shows positive differences. Under the scenario of RCP8.5, changes in the snow coverage rate in all seasons present negative differences in the whole basin, and the decreasing trends are more obvious. Under the same emission scenario, the negative differences in winter are weaker than those of other seasons, and the most significant negative difference appears in spring and autumn. The projection scenarios indicate a clearly decreasing trend under the different emission scenarios. Under the scenario of RCP2.6, the decreasing trend is not obvious as it fails the 90% confidence level test. Under the scenarios of RCP4.5 and RCP8.5, the decreasing trend of the snow coverage rate is significant, passing the 99% confidence level test. HIGHLIGHTS The Yarkant River basin, where glacier and perennial snow are widely distributed, is sensitive to climate change.; The variation of the snow cover under the climate change is not clear.; The paper first focused on the changes of the future snow cover rate under the climate change, in order to provide beneficial guidance for flood control and drought relief in the downstream of the alpine basin.;

In this paper, a combination of non-targeted metabolomics and multi-element analysis was used to investigate the impact of five different cultivars on the sensory quality of QTMJ tea and identify candidate markers for varietal authenticity assessment. With chemometric analysis, a total of 54 differential metabolites were screened, with the abundances significantly varied in the tea cultivars. By contrast, the QTMJ tea from the Yaoshan Xiulv (XL) monovariety presents a much better sensory quality as result of the relatively more abundant anthocyanin glycosides and the lower levels of 2′-o-methyladenosine, denudatine, kynurenic acid and L-pipecolic acid. In addition, multi-elemental analysis found 14 significantly differential elements among the cultivars (VIP > 1 and p < 0.05). The differences and correlations of metabolites and elemental signatures of QTMJ tea between five cultivars were discussed using a Pearson correlation analysis. Element characteristics can be used as the best discriminant index for different cultivars of QTMJT, with a predictive accuracy of 100%.

Abstract On the surface and grain boundary of perovskite films there are large quantities defects, which leads to photogenerated carrier nonradiative recombination and degrades the performance of the perovskite solar cells (PSCs). Surface passivation can suppress the detrimental effects of defect and improve the performance of PSCs. Here, an organic molecule, 4‐chloro‐1,8‐naphthalic anhydride (ALS), is adopted to passivate the defects on the surface and grain boundary of (FAPbI3)0.95(MAPbBr3)0.05 perovskite films. The oxygen of carbonyl group in the ALS provides lone pair electron to the undercoordinated Pb2+ and passivated this defect. The ALS passivated perovskite films have lower trap state density and longer carrier lifetime. As a result, the photoelectric conversion efficiency (PCE) of the PSCs was improved from 21.52% to 23.72%. Furthermore, the ALS passivated PSC show good stability, and it could maintain 88% of its initial efficiency after 1200 h storage in ambient atmosphere without encapsulation.