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[Objective] The summer rainfall intensity in the desert steppe is strong and concentrated, and the harm of hydraulic erosion is serious. It is of great significance for soil and water conservation in this area to clarify the process of runoff and sediment yield, as well as the law of nutrient transport. [Methods] The experiment is based on natural rainfall observation data and artificial rainfall simulation methods, studying the runoff and sediment production processes, nutrient transport patterns in the desert steppe area, and investigating the impact of vegetation on runoff and sediment production through different vegetation treatments. [Results] (1) Different vegetation treatments had different effects on soil and water conservation. Among the three different treatments, the soil and water conservation effect of natural grassland the best, and the runoff reduction rate and sediment reduction rate were 11.37% and 49.67%, respectively. (2) The process of runoff and sediment production would change the material composition of surface soil, make the surface soil coarse-grained, and also affect soil nutrients. After rainfall, the sand content increased by 5.97%~15.71%, and the soil available N, P and organic matter decreased by 40.84%, 27.08%, 33.49%, respectively. (3) The runoff and sediment yield increased with the increase of slope and rainfall intensity, and the power function can better fit the relationship between rainfall duration and runoff and sediment yield. With the increase of rainfall intensity, the peak runoff yield increased by 6.70 L on average when the slope was 5°~25°. When the rainfall intensity is 0.6~2.0 mm/L, the inflection point of the sediment yield increase rate will appear between the slope of 15°~20°. [Conclusion] The research results can provide a theoretical reference for the comprehensive prevention and control of soil and water loss in desert steppe areas, which is helpful in improving the ecological environment of desert steppe regions and carrying out soil and water conservation efforts in this area.

The temperature prediction of geothermal reservoirs at different depths is to determine the key parameters such as thermal energy storage, heat output capacity, and the sustainable utilization period of geothermal reservoirs. Taking the geothermal wells in the Qiabuqia area of Gonghe Basin as an example, this study proposes a temperature prediction model for heat reservoirs under different constraints based on particle swarm optimization (PSO) and long short-term memory network (LSTM). The prediction effect of this model is verified by comparing with those of the BP model and LSTM model. The results show that the RMSE value, MAPE value and MAD value in the prediction results of the model are the smallest compared with those in BP and LSTM models, and the minimum RMSE value is only 1.192. The determination coefficient of the model is 0.929, showing a good prediction effect. This indicates that this model could realize the prediction of reservoir temperature in geothermal system, which provides references for the efficient and long-term development of geothermal system.

Objective: To assess the correlation between atmospheric pollutants, meteorological factors, and emergency department visits for respiratory diseases in Haikou City. Methods: Daily data on atmospheric pollutants, meteorological factors, and emergency department visits for respiratory diseases in Haikou City from 2018 to 2021 were collected. The Spearman rank correlation test was used to analyze the correlation, and a distributed lag non-linear model was employed to analyze the health effects and lag impacts of environmental factors. Subgroup analyses were conducted based on sex and age. Results: According to the criteria of International Classification of Diseases (ICD-10: J00-J99), a total of 221 913 cases were included, accounting for 21.3% of the total emergency department visits in Haikou City. For every 1 °C increase in temperature, the risk of emergency department visits increased by 1.029% (95% CI 1.016%-1.042%). Relative humidity greater than 80% reduced the risk of visits, while higher atmospheric pressure (>1 010 hpa) also decreased the likelihood of daily emergency department visits. Higher concentrations of PM25 (30-50 μg/m3), PM10 (>60 μg/m3), and O3 (75-125 μg/m3) were associated with increased visits. Higher temperatures (>25 °C) have a greater impact on females and children aged 0-14 years, while males are more sensitive to low atmospheric pressure. Individuals aged 65 and above exhibited increased sensitivity to O3 concentration, and the effects of PM2.5, PM10, and O3 are more pronounced in individuals over 14 years old. Conclusions: Short-term exposure to high temperatures, particulate matter pollutants (PM25 and PM10), and ozone (O3) is associated with increased emergency department visits for respiratory diseases.

Abstract [Objective] The study aims to elucidate the regulatory mechanism of the double petal trait in rose. We cloned an AG homologous gene RcAGL61, which was previously screened and related to flower development, and examined its function. [Methods] qRT-PCR was used to analyze the expression of RcAGL61 in flower buds of the double-petaled lines and single-petaled lines in Rosa chinensis ‘Zhaiye Tengben Yuejihua’ × R. chinensis‘Old Blush’ population. RcAGL61 was cloned from the double-petaled lines and single-petal lines, and bioinformatics analysis, subcellular localization, and VIGS experiments were carried out. [Results] (1) The expression of RcAGL61 was higher in the five developmental stages of the singlepetaled line than the double-petaled line, and the expression was higher in S4-S5 stages than in S1-S3 stages in the single-petaled line. (2) The coding sequence of RcAGL61 was the same in the double-petaled line and single-petaled line, with a length of 495 bp, which had a similarity of 30.75% with RcAG. RcAGL61 encoded 164 amino acids, which contained a conserved MADS-box, belonging to the MADS-box family. (3) RcAGL61 was localized in the nucleus. (4) When silenced by VIGS technique in R. chinensis ‘Old Blush’, the petalized stamens and petal numbers were increased, while the stamen numbers were decreased. The number of sepals and pistils had no significant change. [Conclusion] RcAGL61 is involved in regulating the transition between stamens and petal primordiums, and affects the number of petals in R. chinensis.

Fresh-cut Chinese water chestnuts (CWCs) are susceptible to yellowing and browning during storage due to mechanical damage and the loss of protective outer skin, adversely affecting their marketability and shelf life. Methyl jasmonate (MeJA) is currently extensively used for food preservation, but it has not been used in Chinese water chestnuts. This study investigated the effect of MeJA treatment on the quality of fresh-cut CWCs. Fresh-cut CWCs immersed in 20 μM MeJA solution for 10 min and stored at 10°C for 5 d effectively delayed the yellowing process, reduced the respiration rate, and minimized the weight and soluble solids loss during storage. In addition, MeJA treatment induced the activities of superoxide dismutase (SOD) and catalase (CAT), which improved the antioxidant capacity of fresh-cut CWCs and inhibited the generation of reactive oxygen species (ROS). Meanwhile, MeJA treatment inhibited the activities of phenylalanine aminotransferase (PAL), polyphenol oxidase (PPO) and peroxidase (POD). The results of quantitative real-time PCR (qRT-PCR) showed that MeJA down-regulated the expression of CwCHS1, CwCHS2, CwCHS3 and CwCHI2 in freshly cut CWCs and inhibited the accumulation of flavonoids, thus delaying the surface discoloration of freshly cut CWCs.

Background: Late-Life Depression (LLD) is a prevalent mental health disorder that is often accompanied by cognitive impairments. The objective of this study is to investigate the influence of coexisting Generalized Anxiety Disorder (GAD) on both subjective and objective cognitive abilities in untreated LLD individuals. Methods: A total of 77 participants aged 60 years and above were recruited for this study, comprising 31 individuals with Major Depressive Disorder (LLD group), 46 with MDD and coexisting Generalized Anxiety Disorder (LLDA group), and 54 healthy controls (HC). Prior to the study, all patients had abstained from psychotropic medication for a minimum of two weeks. Comprehensive neuropsychological assessments were administered to all participants. Results: The LLDA group exhibited substantial disparities in memory, attention, processing speed,executive function,overall cognitive functioning, and subjective cognitive functioning when compared to the HC group. The LLD group displayed deficits in memory, SCWT-W in attention, SCWT-C in processing speed,overall cognitive functioning, and subjective cognitive functioning in comparison to the healthy controls. Although the LLD group achieved lower average scores in executive function, TMTA in processing speed, and DSST in attention than the HC group, no significant distinctions were identified between these groups in these domains. Linear regression analysis unveiled that anxiety symptoms had a significant impact on subjective cognitive deficits among MDD patients, but exhibited a milder influence on objective cognitive performance. After adjusting for the severity of depression, anxiety symptoms were found to affect TMTA in processing speed and subjective cognitive functioning in LLD patients. Conclusion: Late-Life Depression (LLD) exhibits pervasive cognitive impairments, particularly in individuals with generalized anxiety disorder, presenting a crucial target for future therapeutic interventions. Among elderly individuals with depression, anxiety symptoms significantly impact subjective cognitive functioning, suggesting its potential utility in distinguishing between depression-associated cognitive decline and pre-dementia conditions.

Due to the influence of underground coal dust and easy obstruction, the laser point cloud data of hydraulic supports is prone to be incomplete. The existing point cloud segmentation algorithms are difficult to obtain fine-grained point cloud features, unable to obtain complete structural information of the point cloud. The algorithms are prone to introducing semantically dissimilar points in the neighborhood, resulting in low precision of laser point cloud segmentation for hydraulic supports. In order to solve the above problems, a laser point cloud segmentation algorithm for hydraulic supports based on neighborhood feature encoding and optimization is proposed. The method introduces a local neighborhood feature aggregation module consisting of neighborhood feature encoding module, neighborhood feature optimization module, and hybrid pooling module. The neighborhood feature encoding module adds polar coordinate encoding and centroid offset to represent the spatial structure of local point clouds on the basis of traditional 3D coordinate encoding, improving the feature extraction capability for incomplete point clouds. The neighborhood feature optimization module optimizes the feature expression in the neighborhood space by judging the feature distance and discarding redundant features, thereby more effectively learning the local fine-grained features of the point cloud and enhancing the local contextual information of the point cloud. The hybrid pooling module combines attention pooling and max pooling to obtain single point features with rich information by aggregating salient and important features within the neighborhood, reducing information loss. A neighborhood expansion module consisting of two sets of local neighborhood feature aggregation modules and residual connections is constructed to capture long-range dependencies between features, expand the local receptive field of individual points, and aggregate more effective features. The experimental results show that the algorithm has an mean intersection over union of 93.26% and an average accuracy of 96.42% on the laser point cloud segmentation dataset of hydraulic supports. It can effectively distinguish different geometric structures of hydraulic supports and achieve accurate segmentation of various components of hydraulic supports.

Objective: The feasibility of the conduction system pacing (CSP) upgrade as an alternative modality to the traditional biventricular pacing (BiVP) upgrade in patients with pacemaker-induced cardiomyopathy (PICM) remains uncertain. This study sought to compare two modalities of CSP (His bundle pacing (HBP) and left bundle branch pacing (LBBP)) with BiVP and no upgrades in patients with pacing-induced cardiomyopathy.Methods: This retrospective analysis comprised consecutive patients who underwent either BiVP or CSP upgrade for PICM at the cardiac department from 2017 to 2021. Patients with a follow-up period exceeding 12 months were considered for the final analysis.Results: The final group of patients who underwent upgrades included 48 individuals: 11 with BiVP upgrades, 24 with HBP upgrades, and 13 with LBBP upgrades. Compared to the baseline data, there were significant improvements in cardiac performance at the last follow-up. After the upgrade, the QRS duration (127.81 ± 31.89 vs 177.08 ± 34.35 ms, p < 0.001), NYHA class (2.28 ± 0.70 vs 3.04 ± 0.54, p < 0.05), left ventricular end-diastolic diameter (LVEDD) (54.08 ± 4.80 vs 57.50 ± 4.85 mm, p < 0.05), and left ventricular ejection fraction (LVEF) (44.46% ± 6.39% vs 33.15% ± 5.25%, p < 0.001) were improved. There was a noticeable improvement in LVEF in the CSP group (32.15% ± 3.22% vs 44.95% ± 3.99% (p < 0.001)) and the BiVP group (33.90% ± 3.09% vs 40.83% ± 2.99% (p < 0.001)). The changes in QRS duration were more evident in CSP than in BiVP (56.65 ± 11.71 vs 34.67 ± 13.32, p < 0.001). Similarly, the changes in LVEF (12.8 ± 3.66 vs 6.93 ± 3.04, p < 0.001) and LVEDD (5.80 ± 1.71 vs 3.16 ± 1.35, p < 0.001) were greater in CSP than in BiVP. The changes in LVEDD (p = 0.549) and LVEF (p = 0.570) were similar in the LBBP and HBP groups. The threshold in LBBP was also lower than that in HBP (1.01 ± 0.43 vs 1.33 ± 0.32 V, p = 0.019).Conclusion: The improvement of clinical outcomes in CSP was more significant than in BiVP. CSP may be an alternative therapy to CRT for patients with PICM. LBBP would be a better choice than HBP due to its lower thresholds.

Water sorption and its hysteresis are widespread phenomena that are important for food processing and food quality. In the present study, water sorption and desorption isotherms of wheat flour were measured at three temperatures using a dynamic vapor sorption (DVS) instrument, and modeled according to the Vrentas-Vrentas (VV) theory. Results showed that the degree of water sorption hysteresis decreased with an increase in temperature. In addition, overlapping between desorption and sorption isotherms was observed at high water activity. Based on this, an approach was proposed to determine the critical water content at which glass transition occurs. For both water sorption and desorption, the Flory-Huggins interaction parameter χ varied with the volume fraction of water, and a modified Fermi function was proposed using the Peleg model to describe this relationship. When desorption isotherms were modeled based on the sorption parameter χ, the VV model parameter k was expressed as a function of the volume fraction of water using a Fermi-type function.

Goal: Auscultation for neonates is a simple and non-invasive method of diagnosing cardiovascular and respiratory disease. However, obtaining high-quality chest sounds containing only heart or lung sounds is non-trivial. Hence, this study introduces a new deep-learning model named NeoSSNet and evaluates its performance in neonatal chest sound separation with previous methods. Methods: We propose a masked-based architecture similar to Conv-TasNet. The encoder and decoder consist of 1D convolution and 1D transposed convolution, while the mask generator consists of a convolution and transformer architecture. The input chest sounds were first encoded as a sequence of tokens using 1D convolution. The tokens were then passed to the mask generator to generate two masks, one for heart sounds and one for lung sounds. Each mask is then applied to the input token sequence. Lastly, the tokens are converted back to waveforms using 1D transposed convolution. Results: Our proposed model showed superior results compared to the previous methods based on objective distortion measures, ranging from a 2.01 dB improvement to a 5.06 dB improvement. The proposed model is also significantly faster than the previous methods, with at least a 17-time improvement. Conclusions: The proposed model could be a suitable preprocessing step for any health monitoring system where only the heart sound or lung sound is desired.

Objective To explore the research hotspots and trends in the field of quality of life of oral cancer patients, so as to provide a guiding basis for quality of life studies on oral cancer patients in China. Methods Using the literature related to the quality of life of oral cancer patients published in Web of Science from 2000 to 2022 as the data source. The CiteSpace software was used for visual analysis. Results A total of 860 relevant articles were included after removing the duplicates by Citespace, and the number of annual publications basically showed an upward trend. The main body of the researches was concentrated in universities and research institutes in the United States and the United Kingdom, and the institutions and countries have formed a certain scale of cooperative groups. Research hotspots are the factors influencing the quality of life of oral cancer patients, assessment tools for quality of life, interventions and management of influencing factors. Conclusion It is recommended that researchers learn from the advanced theories and models of foreign countries to further develop a quality of life assessment scale more suitable for oral cancer patients in China. In the future, the main focus should be on personalized treatment plans, rehabilitation training methods and management, supportive care needs, and body imagery changes so as to better improve the quality of life of oral cancer patients. (目的 使用文献计量法探讨国际口腔癌患者生活质量研究的热点及趋势, 为我国口腔癌患者生活质量研究提供指导依据。方法 以2000年—2022年Web of Science收录的口腔癌患者生活质量相关文献为数据来源, 运用CiteSpace软件进行可视化分析。结果 经CiteSpace去重后共纳入860篇相关文献, 年度发文量基本呈上升趋势; 研究主体集中在美国和英国的高校及研究所, 各机构和国家形成了一定规模的合作团体; 研究热点为口腔癌患者生活质量的影响因素、生活质量的评估工具、影响因素的干预和管理。结论 建议研究者学习借鉴国外先进理论及模式, 进一步研制更适合我国口腔癌患者的生活质量评估量表。未来应重点关注个性化治疗方案、康复训练方法及管理、支持性照护需求、身体意象改变, 以更好地提高口腔癌患者生活质量。)

Currently, human health due to corona virus disease 2019 (COVID-19) pandemic has been seriously threatened. The coronavirus severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike (S) protein plays a crucial role in virus transmission and several S-based therapeutic approaches have been approved for the treatment of COVID-19. However, the efficacy is compromised by the SARS-CoV-2 evolvement and mutation. Here we report the SARS-CoV-2 S protein receptor-binding domain (RBD) inhibitor licorice-saponin A3 (A3) could widely inhibit RBD of SARS-CoV-2 variants, including Beta, Delta, and Omicron BA.1, XBB and BQ1.1. Furthermore, A3 could potently inhibit SARS-CoV-2 Omicron virus in Vero E6 cells, with EC50 of 1.016 μM. The mechanism was related to binding with Y453 of RBD determined by hydrogen-deuterium exchange mass spectrometry (HDX-MS) analysis combined with quantum mechanics/molecular mechanics (QM/MM) simulations. Interestingly, phosphoproteomics analysis and multi fluorescent immunohistochemistry (mIHC) respectively indicated that A3 also inhibits host inflammation by directly modulating the JNK and p38 mitogen-activated protein kinase (MAPK) pathways and rebalancing the corresponding immune dysregulation. This work supports A3 as a promising broad-spectrum small molecule drug candidate for COVID-19.

Introduction: Myocardial infarction (MI), the most prevalent ischemic heart disease, constitutes a primary cause of global cardiovascular disease with incidence and mortality. The pathogenesis of MI is exceedingly intricate, with PANoptosis playing a pivotal role in its pathological process. Xian Ling Gu Bao capsule (XLGB) contains various active components, including flavonoids, terpenes, and phenylpropanoids, and exhibits a wide range of pharmacological activities. However, it remains unclear whether XLGB can protect the myocardium from damage after MI. This study aimed to investigate the impact of XLGB on isoprenaline (ISO)-induced MI in mice and its potential mechanisms.Methods: This study assessed the protective effects of XLGB against ISO-induced MI through techniques such as echocardiography, HE staining, Masson staining, and enzyme-linked immunosorbent assay (ELISA). Furthermore, the potential mechanisms of XLGB's protective effects on MI were explored using bioinformatics, molecular docking, and molecular dynamics simulations. These mechanisms were further validated through immunofluorescence staining and Western blotting.Results: The results demonstrated that various doses of XLGB exhibited a significant reduction in myocardial injury induced by myocardial infarction. Intriguingly, higher dosages of XLGB displayed superior therapeutic efficacy compared to the positive control metoprolol. This protective effect is primarily achieved through the inhibition of oxidative stress and the inflammatory processes. Furthermore, we have elucidated that XLGB protected the myocardium from MI-induced damage by suppressing PANoptosis, with a critical role played by the NLRP3/Caspase3/RIP1 signaling pathway. Of particular note, the primary compounds of XLGB were found to directly interact with NLRP3/Caspase3/RIP1, a discovery further validated through molecular docking and molecular dynamics simulations. This suggests that NLRP3/Caspase3/RIP1 may be a therapeutic target for XLGB-induced myocardial protection.Conclusion: In summary, our findings reveal a novel property of XLGB: reverses myocardial damage following MI by inhibiting the NLRP3/Caspase3/RIP1-mediated PANoptosis pathway.

In this paper, an adaptive bearing rigid formation control strategy for a class of nonlinear system with unknown dead-zone inputs and external disturbance is proposed. Firstly, the I-Type fuzzy system is used to approximate the unknown nonlinear dynamics of the formation model, and the approximation errors and unknown external disturbance are eliminated by the parameter adaptive estimation. Furthermore, the adaptive dynamic estimation algorithm is utilized to estimate and compensate the unknown dead-zone parameters, effectively suppressing the impact of dead-zone on formation system performance. Finally, the stability of the formation system is proved based on LaSalle’s invariance principle, and the effectiveness of the algorithm is verified by simulation results.

Large-scale application of new energies is a major approach to achieving carbon peaking and carbon neutralization. Conducting research on the safety risk prevention and control strategy of new energy application helps in the establishment of a monitoring, risk prevention, and guarantee system for new energy application and promotes the high-quality development of related industries. Currently, new energy application in China involves various types of emerging infrastructures and faces challenges such as complex causes of safety accidents, incomplete understanding of safety risks, inadequate safety prevention and control technology systems, and lagging construction of a safety regulatory system. This study analyzes the current status and safety situation of new energy application in China and delves into the safety risk prevention and control issues faced by new energy application infrastructures such as charging/swapping stations, energy storage stations, hydrogen fuelling stations, and integrated energy stations. It also summarizes the current situation and experiences abroad regarding safety risk prevention and control. To establish a comprehensive system for preventing and controlling safety accidents before, during, and after they occur, and to enhance the safety risk management and regulatory capabilities of all stakeholders, this study constructs a strategic framework for safety risk prevention and control for new energy application. It clarifies the key tasks in terms of management and technology development and proposes medium- to long-term engineering and technological support projects. Furthermore, we propose development suggestions in terms of top-level design, governance standards, regulatory platforms, technological research and development, talent cultivation, and ecological co-construction, thus to promote the safety research and application of new energies.

This paper aims to convert a feeder of a bulk supply point (BSP) into a microgrid with rooftop solar PV plants sited in senior high schools along that MV grid in Ghana. The study used a solar PV Python optimization and forward–backwards algorithms to arrive at its results. The results show that rooftop PV plants sited in the study area can produce electricity to meet the feeder’s peak demand (8.2 MW) and have an extra 11.3 MW fed back to the grid. Cases 1, 2, 3 and 4 saw increases of 1.16%, 1.74%, 2.26% and 2.32%, respectively, higher than the nominal voltage of 34.5 kV. The base case total loss was 1.1 MW, and case 1 was 0.3 MW.

In this study, “Honghu White Lotus”, “Red Lotus (HH)”, “Hunan Cunshan Lotus (CS)”, “Wuyi Xuanlian”, “Space Lotus 36”, “Fujian Jianning White Lotus (JB)”, “Jiangsu Yangzhou Lotus (JY)”, and “Suzhou Dongshan Lotus” were selected as experimental subjects. The lotus seed flesh and lotus plumule of each cultivar were selected for nutritional quality and functional active substance analyses. Comparing different cultivars of lotus seeds, the protein and crude fat contents of JY flesh were the highest at 65.59 mg/g and 13%, respectively. The VC content of JB flesh and lotus plumule is the highest at 41.56 mg/g and 204.29 mg/g, respectively. JB flesh has the lowest soluble sugar content, at 17.87 mg/g, while HB’s lotus plumule and flesh have the highest content, at 33.67 mg/g and 29.62 mg/g, respectively. There was no significant difference in the crude fat content of the flesh and lotus plumule among the eight cultivars. TK flesh and lotus plumule have the highest amylose content, at 23.67 mg/g and 76.81 mg/g, respectively. Among them, the total starch content of JB (476.17 mg/g) was relatively high, whereas its amylose content was only 26.09 mg/g. Lower amylose content makes it less prone to aging. The total phenolic and flavonoid contents of the JY lotus plumule were the highest, at 18.64 and 21.04 mg/g, respectively. The alkaloid content of CS, HH, and JY was relatively high at 20.01, 19.29, and 18.68 mg/g, respectively. These can provide a consultation for the estimation and processing of the nutritional quality of different lotus seeds.

This study investigated the impact of variety and harvest time on the visual appearance, nutritional quality, and functional active substances of six lotus root cultivars: “Xinsanwu”, “Wuzhi No. 2”, “Baiyuzhan”, “Huaqilian”, “Elian No. 6”, and “Elian No. 5”. Samples were collected monthly from December 2023 to April 2024. A nutrient analysis revealed a decrease in the water content with a delayed harvest. The total soluble solids and soluble sugar content peaked towards the end and middle-to-late harvest periods, respectively. Starch levels initially increased before declining, while the soluble protein exhibited a triphasic trend with an initial rise, a dip, and a final increase. The vitamin C (Vc) content varied across cultivars. Functional active substances displayed dynamic changes. The total phenolics initially decreased, then increased, before ultimately declining again. The total flavonoid content varied by both cultivar and harvest time. The phenolic acid and flavonoid content mirrored the trends observed for total phenolics and total flavonoids. Gastrodin was the most abundant non-flavonoid compound across all varieties. “Wuzhi No. 2” and “Baiyuzhan” displayed higher levels of functional active substances and starch, while the Elian series and “Xinsanwu” cultivar exhibited a greater content of Vc, soluble sugar, and soluble protein. Specific harvest periods yielded optimal results: “Wuzhi No. 2” (H1 and H5), “Huaqilian” (H2), and “Baiyuzhan” (H3 and H4) demonstrated a high nutrient and functional active substance content. Overall, the lotus roots harvested in period H4 achieved the highest score. Overall, this study provides the foothold for the rapid identification of superior lotus root cultivars and the valorization of lotus root by-products via advanced processing methods. Additionally, it offers valuable insights for market participants and consumers to select optimal varieties and harvest times based on their specific needs.

Objective: This study aimed to explore the best irradiation method and irradiation dose to treat Choerospondias axillaris pastilles. Methods: C. axillaris pastilles were irradiated with 0～10 kGy gradient dose of 60Co-γ ray and electron beam respectively, the changes of the indexes including microbial load, protein, fat, total sugar, L(+)-ascorbic acid, organic acids, pH value, sensory quality, and the shelf life quality stored in 0～360 days at room temperature were studied. Results: 60Co-γ ray and electron beam irradiation both had bactericidal effects on C. axillaris pastilles, all microbial limit indexes including aerobic bacterial count, coliform bacteria, mold, and the pathogenic bacteria limit indexes including salmonella and staphylococcus aureus were not detected in the samples with the irradiation dose of 4 kGy. The contents of protein, fat, total sugar, organic acids (mainly citric acid), pH, and sensory quality in C. axillaris pastilles were not significantly affected by 60Co-γ ray and electron beam irradiation of less than 10 kGy. However, the content of L(+)-ascorbic acid was significantly decreased compared with the control group after irradiation (P＜0.05), it was negatively correlated with irradiation dose, and 60Co-γ ray irradiation had a greater impact than that of electron beam irradiation. The C. axillaris pastilles batch products were irradiated with 60Co-γ ray and electron beam of 4～10 kGy, the products were stored for 0～360 days at room temperature, and the microbial limit indexes including aerobic bacterial count, coliform bacteria, mold in the products were less than 10 CFU/g. There were no significant changes in the smell, taste, and tissue state of C. axillaris pastilles, but with the extension of storage time, its color deepened due to browning, but it was still acceptable within 270 days of storage. Conclusion: 60Co-γ ray and electron beam irradiation both are effective methods for sterilization and storage of C. axillaris pastilles, and the recommended irradiation dose is 4～10 kGy.

Spatial-temporal modeling is crucial for action recognition in videos within the field of artificial intelligence. However, robustly extracting motion information remains a primary challenge due to temporal deformations of appearances and variations in motion frequencies between different actions. In order to address these issues, we propose an innovative and effective method called the Motion Sensitive Network (MSN), incorporating the theories of artificial neural networks and key concepts of autonomous system control and decision-making. Specifically, we employ an approach known as Spatial-Temporal Pyramid Motion Extraction (STP-ME) module, adjusting convolution kernel sizes and time intervals synchronously to gather motion information at different temporal scales, aligning with the learning and prediction characteristics of artificial neural networks. Additionally, we introduce a new module called Variable Scale Motion Excitation (DS-ME), utilizing a differential model to capture motion information in resonance with the flexibility of autonomous system control. Particularly, we employ a multi-scale deformable convolutional network to alter the motion scale of the target object before computing temporal differences across consecutive frames, providing theoretical support for the flexibility of autonomous systems. Temporal modeling is a crucial step in understanding environmental changes and actions within autonomous systems, and MSN, by integrating the advantages of Artificial Neural Networks (ANN) in this task, provides an effective framework for the future utilization of artificial neural networks in autonomous systems. We evaluate our proposed method on three challenging action recognition datasets (Kinetics-400, Something-Something V1, and Something-Something V2). The results indicate an improvement in accuracy ranging from 1.1% to 2.2% on the test set. When compared with state-of-the-art (SOTA) methods, the proposed approach achieves a maximum performance of 89.90%. In ablation experiments, the performance gain of this module also shows an increase ranging from 2% to 5.3%. The introduced Motion Sensitive Network (MSN) demonstrates significant potential in various challenging scenarios, providing an initial exploration into integrating artificial neural networks into the domain of autonomous systems.

The field of wireless communication is currently being pushed to new boundaries with the emergence of 6G technology. This advanced technology requires substantially increased data rates and processing speeds while simultaneously requiring energy-efficient solutions for real-world practicality. In this work, we apply a neuroscience-inspired machine learning model called echo state network (ESN) to the critical task of symbol detection in massive MIMO-OFDM systems, a key technology for 6G networks. Our work encompasses the design of a hardware-accelerated reservoir neuron architecture to speed up the ESN-based symbol detector. The design is then validated through a proof of concept on the Xilinx Virtex-7 FPGA board in real-world scenarios. The experiment results show the great performance and scalability of our symbol detector design across a range of MIMO configurations, compared with traditional MIMO symbol detection methods like linear minimum mean square error. Our findings also confirm the performance and feasibility of our entire system, reflected in low bit error rates, low resource utilization, and high throughput.

Fine particulate matter (PM2.5) concentration, a crucial indicator reflecting changes in air quality, has frequently been used in previous studies. However, the effects of large-scale ecological restoration (ER) projects on PM2.5 concentrations are often overlooked. Therefore, we used net primary productivity (NPP) as an indicator of ER engineering benefits, used ensemble empirical modal decomposition (EEMD) to reveal the trend of linear and nonlinear relationships of PM2.5 driven by different types and amounts of ER projects, and utilized the Extreme Gradient Boosting (XGBoost) and Shapley's Additive Interpretation (SHAP) values to quantify the impact of each factor on long-term PM2.5 concentrations. The results suggest that: (1) The nonlinear trend better describes the trend of PM2.5 change, with a shift from increasing to decreasing in areas covering 74.15% of China's area, especially in the four major ER zones; (2) PM2.5 concentration exhibits regional effects, L-L and H-H aggregation areas account for a larger proportion of the area, and are distributed in the areas with low and high PM2.5 concentrations, respectively. (3) The year 1990 marks a turning point for 36.8% of the regions. Across four ER regions emerge: a dramatic increase in PM2.5 concentration before ER implementation, followed by a slowing growth trend in the initial stages of the project, and ultimately a gradual decrease. (4) While the contribution of ER to the decrease of PM2.5 concentration is lower than the contribution of the growth caused by human activities and climate change, plant and newly plant areas are the main regions in which the ER project suppresses its growth. These findings highlight the influence of ER projects on PM2.5 concentration in addition to climate and human activities and provide a theoretical basis and scientific and technological support for quantifying the suppression of air pollution by ER projects.

For the current artwork, 3D printing design simulation technology has the disadvantage of low clarity and poor effect, which cannot effectively describe the designer's work. To this end, this paper investigates the artistic aesthetic and cultural value orientation of 3D printing. First, the 3D digitization work of the oil painting was carried out by using the multi-baseline photogrammetry method in photogrammetry technology. Then the non-measurement digital camera was checked for internal orientation elements, the control panel was photographed, and the internal orientation elements of the camera were measured using the spatial backward rendezvous solution method. Next, the digital image acquisition of the oil painting is carried out, and finally, the photos are sequentially introduced into the Lens photo multi-baseline photogrammetry system to generate the color point cloud model of the oil painting after performing the steps of homonymous point selection null-three matching and beam leveling. In order to enhance the visualization effect, the color point cloud model was used to generate a digital model of the TIN irregular triangular network to realize the 3D digitization of oil painting art. The results of the study show that the thickness of each layer obtained by UV inkjet printing of five types of inks: yellow, green, blue, black, and white is about 11.19 μm, 12.71 μm, 7.91 μm, 9.47 μm, and 13.12 μm, respectively. 3D printing technology for positive impact on art design needs to be recognized and respected, and the better development of related technologies can make the advantages and advancement of the technology itself more fully embodied.

To reduce the damage of mechanical parts during machining, a tool wear prediction method based on the SVM-Clara model is proposed. By analyzing the support vector machine (SVM) and Clara algorithm, using regular prediction data or unobservable data, the average dissimilarity of all objects is concentrated, and the characteristics of the overall data are accurately represented. Randomly select data samples from the overall data samples according to a certain proportion, and standardize them to improve the clustering quality. Find the best objective function to minimize the damage function and make the predicted value closer to the actual value. Through experiments, it is proved that the method in this paper can accurately predict the tool wear condition, the mean square error value is 0.03, the prediction method is better, and the production efficiency is ensured.

Based on the LISEREL model and the characteristics of ordered categorical variables, this paper establishes a structural equation model with ordered categorical variables to study the cultivation effect of e-commerce management talents under F2C mode. The measurement model and structural model are constructed using the content and cultivation effect of e-commerce management talent training and e-commerce sales performance, and the degrees of freedom of exogenous observation variables, endogenous observation variables and parameters in the model are estimated. Path analysis was utilized to determine the degree of influence of the F2C talent cultivation model on e-commerce management talent competency and management performance, as well as the effect size. The results show that all the dimensions of e-commerce talent competence under F2C talent cultivation mode are between 3.5 and 4.5, and the relationship between F2C talent cultivation mode on e-commerce talent sales performance is significant at the level of P-value 0.001, and the path coefficients of talent cultivation and sales performance are between 0.1-0.3, and that the F2C cultivation mode is beneficial for the enhancement of e-commerce managerial talent competence.

Co–Cr–Fe–Ni–Ta eutectic multi-principal element alloys (MPEAs) demonstrate great potential to replace structural alloys in engineering applications. However, the cost of these alloys is high due to the usage of a number of precious metals. To decrease the cost, the present work developed a set of novel Fe55Cr15Ni30−xTax (x = 0, 5, 8, 10 and 15 at.%) eutectic MPEAs and the effect of Ta on microstructure and compressive mechanical properties were investigated for the first time. As the Ta content increases, the microstructure changes from a single-phase FCC solid solution (x = 0) to hypoeutectic microstructure (x = 6), then to eutectic microstructure (x = 8), and eventually to hypereutectic microstructure (x = 10 and 15). The yield strength and the hardness increase at the expense of ductility reduction with increasing Ta content. The strengthening mechanism of this alloy system is mainly second-phase strengthening caused by Laves phase and grain boundary strengthening produced by eutectic interface, supplemented by solid solution strengthening. The Fe55Cr15Ni22Ta8 and Fe55Cr15Ni20Ta10 alloys present the excellent comprehensive mechanical properties. The yield strength, fracture strength and fracture strain of the former are 838 MPa, 1994 MPa and 45.1%, respectively. The yield strength, fracture strength and fracture strain of the latter are 1029 MPa, 1956 MPa and 43.0%, respectively. The phase formation of Fe55Cr15Ni30−xTax alloys can be predicted by Md criterion. When Md ≥ 0.89, the alloys consist of FCC phase and Laves phase. Otherwise, the alloys consist of FCC single phase.

The environment of a port city can shape the technological behavior of port-vicinity enterprise and then can influence their innovation performance. Conversely, the technological change of port-vicinity enterprise can determine the transformation and upgrade toward diversification of the port city. The limitation of the current research is that it could not be refined to port enterprises from the regional or industrial level and could not fit the dynamic trajectory of technological change of port-vicinity enterprises. Benefiting from the "evolutionary turn" of economic geography in recent years, the target of evolutionary economic geography, which fuses temporal and spatial factors, is to understand the historical process of economic evolution; hence, evolutionary economic geography is the appropriate platform to analyze this topic. This study integrates the main perspectives of evolutionary economic geography, including generalized Darwinism, complexity theory, and path dependence, to explain the behavior characteristics of port-vicinity enterprises such as technology search and selection, path locking, and so on. An evolutionary analysis framework was constructed for the technological change mechanism of port-vicinity enterprises and demonstrated the applicability and value space of evolutionary economic geography on this theme. The findings conclude the following: 1)Observed from the perspective of generalized Darwinism, the heterogenous port-vicinity enterprises have different technology selection mechanisms in market competition, and the technological change is similar to the biological population evolution. The entry and exit of enterprises and technology reset of existing enterprises contribute jointly to the spatiotemporal evolution of port-vicinity enterprises' technology. 2)Under the premise of bounded rationality, the technological change of port-vicinity enterprise was conducted by local search, the preferable innovation performance could be achieved on the certain position between cognitive proximity and distance. For complex technology networks and different technology paths, port-vicinity enterprises need to adapt and make constant trade-offs to promote the diversified technological path of the port city. With the gradual progress of the port life cycle, the type of distribution and technical level of port-vicinity enterprises will change greatly, leading to the unbalanced development of port cities. (3) The path dependence of port-vicinity enterprises' technological change is a series of temporary equilibrium. The evolution of the technological path of such enterprises can be divided into four stages and face three obstacles (functional, cognitive, and institutional locking). The embeddedness of technological change of port-vicinity enterprises leads to spatial dependence. The windows of locational opportunity of emerging industries will be mainly grasped by port cities with greater inclusiveness and diversity. Past port activities may have strengthened the dependence on heavy chemical industry, locking port cities in the low technology path; therefore, the formation of a new technological path needs the combined action of internal and external forces.

C-Glycosides are important natural products with various bioactivities. In plant biosynthetic pathways, the C-glycosylation step is usually catalyzed by C-glycosyltransferases (CGTs), and most of them prefer to accept uridine 5′-diphosphate glucose (UDP-Glc) as sugar donor. No CGTs favoring UDP-rhamnose (UDP-Rha) as sugar donor has been reported, thus far. Herein, we report the first selective C-rhamnosyltransferase VtCGTc from the medicinal plant Viola tricolor. VtCGTc could efficiently catalyze C-rhamnosylation of 2-hydroxynaringenin 3-C-glucoside, and exhibited high selectivity towards UDP-Rha. Mechanisms for the sugar donor selectivity of VtCGTc were investigated by molecular dynamics (MD) simulations and molecular mechanics with generalized Born and surface area solvation (MM/GBSA) binding free energy calculations. Val144 played a vital role in recognizing UDP-Rha, and the V144T mutant could efficiently utilize UDP-Glc. This work provides a new and efficient approach to prepare flavonoid C-rhamnosides such as violanthin and iso-violanthin.

Radiotherapy is widely used in the management of advanced colorectal cancer (CRC). However, the clinical efficacy is limited by the safe irradiated dose. Sensitizing tumor cells to radiotherapy via interrupting DNA repair is a promising approach to conquering the limitation. The BRCA1–BARD1 complex has been demonstrated to play a critical role in homologous recombination (HR) DSB repair, and its functions may be affected by HERC2 or BAP1. Accumulated evidence illustrates that the ubiquitination–deubiquitination balance is involved in these processes; however, the precise mechanism for the cross-talk among these proteins in HR repair following radiation hasn't been defined. Through activity-based profiling, we identified PT33 as an active entity for HR repair suppression. Subsequently, we revealed that BAP1 serves as a novel molecular target of PT33 via a CRISPR-based deubiquitinase screen. Mechanistically, pharmacological covalent inhibition of BAP1 with PT33 recruits HERC2 to compete with BARD1 for BRCA1 interaction, interrupting HR repair. Consequently, PT33 treatment can substantially enhance the sensitivity of CRC cells to radiotherapy in vitro and in vivo. Overall, these findings provide a mechanistic basis for PT33-induced HR suppression and may guide an effective strategy to improve therapeutic gain.

Chondrocyte senescence is an important mechanism underlying osteoarthritis in the senile population and is characterized by reduced expressions of the extracellular matrix proteins. The involvement of glycolysis and the tricarboxylic acid cycle in the development of osteoarthritis is inclusive. The present study aims to investigate the role of the glycolytic enzyme M2 isoform of pyruvate kinase (PKM2) in chondrocytes in senescence and inflammation. Primary chondrocytes are isolated from the knee joints of neonatal mice. Small interfering RNAs (siRNAs) against PKM2 are transfected using lipofectamine. RNA sequencing is conducted in primary chondrocytes with the PKM2 gene deleted. Cell apoptosis, autophagy, reactive oxygen species measurement, and senescent conditions are examined. The glycolytic rate in cells is measured by Seahorse examination. Interleukin 1-β (IL-1β) increases the protein expressions of matrix metallopeptidases (MMP)13 and PKM2 and reduces the protein expression of collagen type II (COL2A1) in primary chondrocytes. Silencing of PKM2 alters the protein expressions of MMP13, PKM2, and COL2A1 in the same pattern in quiescent and stimulated chondrocytes. RNA sequencing analysis reveals that PKM2 silencing reduces senescent biomarker p16INK4a expression. Compared with low-passage chondrocytes, high-passage chondrocytes exhibit increased expression of p16 INK4a and reduced expression of COL2A1. Silencing of PKM2 reduces SA-β-Gal signals and increases COL2A1 expression in high-passage chondrocytes. Seahorse assay reveals that PKM2 deletion favors the tricarboxylic acid cycle in mitochondria in low- but not in high-passage chondrocytes. In summary, the glycolytic enzyme PMK2 modulates chondrocyte senescence but does not participate in the regulation of inflammation.

Objective: To evaluate the relationship between preoperative magnetic resonance imaging (MRI) examination and the success rate and prognosis of breast-conserving surgery in ductal carcinoma in situ (DCIS) patients. Methods: Patients with DCIS received surgery between January 2009 and January 2017 in the breast cancer medical record database of Shanghai Jiao Tong University were retrospectively analyzed. Patients who received preoperative MRI was defined as MRI group, who did not receive preoperative MRI was defined as non-MRI group. Results: A total of 210 DCIS patients were included, of which 167 cases in the MRI group and 43 cases in the non-MRI group, respectively. Initial negative resection margin rates were similar between MRI and non-MRI groups undergoing breast-conserving surgery (91.0% vs. 97.7%, P=0.142). There was also no significant difference in the success rate of breast-conserving surgery between MRI and non MRI groups (95.2% vs. 100.0%, P=0.143). In terms of prognosis, there was no significant difference in 10-year loco-regional recurrence rate (4.8% vs. 2.3%, P=0.426) and breast cancer related mortality (0.9% vs. 0.5%, P=0.668) between MRI and non-MRI groups. Conclusions: Preoperative breast MRI examination in patients with DCIS had no effect on the rate of negative resection margin, success rate of breast preservation and the prognosis of the patients.

The increasing prominence of climate change, geopolitical crises, and global economic slowdown highlights the challenges and structural deficiencies of traditional cross-border agro-food supply chains. As a result, there has been a growing consensus on the need to leverage digital technology to rebuild and innovate a safe, stable, and sustainable global food system. This study assessed the knowledge progress and development trends in the sustainable development of cross-border agro-food supply chains enabled by digital technology. A total of 352 authoritative papers from the core Web of Science database were selected for analysis. The Citespace tool was utilized to visually examine research elements. The findings reveal that research outcomes in this territory experienced a significant period of rapid growth, particularly after 2020. Sustainability and IEEE Access are the journals with the highest and second-highest number of publications. China and the France National Institute are the countries and research institutions with the largest number of publications in this field. The research hotspots are mainly the application of digital technologies, food safety, and supply chain system model innovation. In the past ten years, the research in this territory has gone through three stages: precise timeliness orientation, intelligent strategic decision-making orientation, and model predictability orientation. We further construct the ‘antecedent–practice–performance’ conceptual framework of the sustainability of the digital technology-enabled cross-border agro-food supply chain. Finally, this paper presents the potential research directions in this territory, focusing on four aspects: research method, research mechanism, research topic, and research frontier.

Fission product yields are fundamental nuclear data for nuclear energy applications and nuclear physics research. In this work, HPGe γ spectrometric technique is applied to absolutely measure the mass distributions from 0.57, 1.0 MeV and 1.5 MeV neutron induced fission of 235U, and more than 30 mass chain yields are obtained for each energy. The fission rate of uranium sample is monitored by a double fission chamber and its neutron spectrum is simulated via MCNP program. Comparing with the existing data of other lab, our results are in good agreement within the experimental uncertainties. The output data obtained in this work clarifies the difference of up to 16% in the original data and improves the data accuracy from 5%-7% of the original international data to 3%-5%.

Bone marrow mesenchymal stem cell (BMSC)-derived exosomes are a promising therapeutic agent for human disease, but their effects on neural stem cells (NSCs) subject to spinal cord ischaemia-reperfusion injury (SCIRI) remain unknown. Here, we examine the impact of miR-199a-5p-enriched exosomes derived from BMSCs on NSC proliferation. We establish a rat model of aortic cross-clamping to induce SCIRI in vivo and a primary NSC model of oxygen-glucose deprivation/reoxygenation (OGD/R) to simulate SCIRI in vitro. CCK8, EdU, and BrdU assays are performed to evaluate the proliferation of NSCs. Hematoxylin and eosin (H&E) staining is used to determine the number of surviving neurons. The Basso, Beattie, and Bresnahan (BBB) scale and inclined plane test (IPT) are used to evaluate hind limb motor function. DiO-labelled exosomes are efficiently internalized by NSCs and increase ectopic amounts of miR-199a-5p, which promotes the proliferation of NSCs. In contrast, exosomes derived from miR-199a-5p-depleted BMSCs exert fewer beneficial effects. MiR-199a-5p targets and negatively regulates glycogen synthase kinase 3β (GSK-3β) and increases nuclear β-catenin and cyclin D1 levels. miR-199a-5p inhibition reduces the total number of EdU-positive NSCs after OGD/R, but the GSK-3β inhibitor CHIR-99021 reverses this effect. In vivo, intrathecal injection of BMSC-derived exosomes increases the proliferation of endogenous spinal cord NSCs after SCIRI. In addition, more proliferating NSCs are found in rats intrathecally injected with exosomes overexpressing miR-199a-5p. In summary, miR-199a-5p in BMSC-derived exosomes promotes NSC proliferation via GSK-3β/β-catenin signaling.

Emerging 3D photonic circuits would greatly benefit from the ability to integrate skimming waveguides with low loss and controllable inscription depth into photonic circuits. These waveguides allow for the interaction of guiding light directly with external modulation signals and enable programmable photonic circuits. Here, we report the fabrication of a novel photonic-lattice-like skimming waveguide (PLLSW) using femtosecond laser writing. Our method enables fine control of cross-sectional symmetry and writing depth of waveguides, achieving a minimum depth of 1 μm and a low insertion loss of 1 dB. Based on the PLLSW, we demonstrate on-chip light modulation by designing an evanescent-field-type saturable absorber through the coupling of a carbon nanotube film with the PLLSW, which exhibits saturation intensity from 20 to 200 MW/cm2 through the balanced twin-detector measurement. The strong nonlinear optical response of the PLLSW-based saturable absorber is further exploited to drive a Q-switched pulse laser at 1550 nm based on a fiber laser cavity. Our work demonstrates an effective method to integrate nonlinear optical materials into a glass chip for all-optical switching based on 3D waveguides, which holds great potential for the construction of large-scale programmable photonic circuits in the future.

Abstract Background Sepsis-related AKI is related to short-term mortality and poor long-term prognoses, such as chronic renal insufficiency, late development of end-stage renal disease, and long-term mortality. In this study, we aimed to investigate the association of hyperuricemia with acute kidney injury (AKI) in patients with sepsis. Methods The retrospective cohort study included 634 adult sepsis patients hospitalized in the intensive care unit (ICU) of the First Affiliated Hospital of Guangxi Medical University from March 2014 to June 2020 and the ICU of the Second Affiliated Hospital of Guangxi Medical University from January 2017 to June 2020. Based on the first serum uric acid level within 24 h of admission to the ICU, patients were divided into groups with or without hyperuricemia, and the incidence of AKI within seven days of ICU admission was compared between the two groups. The univariate analysis analyzed the effect of hyperuricemia on sepsis-related AKI, and the multivariable logistic regression model analysis was used. Results Among the 634 patients with sepsis, 163 (25.7%) developed hyperuricemia, and 324 (51.5%) developed AKI. The incidence of AKI in the groups with and without hyperuricemia was 76.7% and 42.3%, respectively, with statistically significant differences (2 = 57.469, P

Background Stroke is one of the major public health problems affecting human health in current. Longitudinal check up data has accumulated a large amount of health information. However, the utilization rate of the longitudinal check up data is low and important information has not been fully extracted due to many problems such as missing data and small sample size, which brings difficulties to the effective prevention and control of common chronic diseases. Objective To explore the risk factors of stroke in check-up population based on Bayesian multivariate joint model, so as to provide a new approach for the analysis of risk factors for chronic diseases. Methods In this study, the data were collected from the Center for Health and Medicine, Xijing Hospital, Air Force Military Medical University from 2008 to 2015. Follow-up status: the follow up was conducted with the first occurrence of stroke as the outcome event and stopped at the occurrence of outcome event or ended when the collection of medical examination information was completed by 2015 if the outcome event did not occur. The interval between physical examinations was 1 year. The participants were divided into the stroke group and the non-stroke group according to whether stroke occurred during follow-up. Longitudinal variables observed in this study included total cholesterol (TC) , triglyceride (TG) , low density lipoprotein cholesterol (LDL-C) , high density lipoprotein cholesterol (HDL-C) , body mass index (BMI) and systolic blood pressure (SBP) . Multivariate Cox regression model was used to analyze the influence of baseline conditions on stroke outcome events. Bayesian multivariate joint model was used for analyzing the effect of longitudinal trajectory of TC, TG, LDL-C, HDL-C, BMI and SBP on the incidence of stroke during follow-up. Results A total of 234 subjects with 1 581 longitudinal follow-up records were included in this study, with the mean follow-up time of (7.4±1.2) years, of which 70 cases (29.9%) developed stroke during the follow-up. The results of multivariate Cox proportional hazards model showed that there was no effect of baseline values including TC, TG, LDL-C, HDL-C, BMI and SBP on the incidence of stroke (P>0.05) . The results of Bayesian multivariate joint model showed that the risk of stroke was 1.863 times higher for per longitudinal increase of 1 mmol/L TG level 〔95%CI (1.018, 3.294) , P=0.042〕 and 1.347 times higher for per longitudinal increase of 1 mmol/L LDL-C level〔95%CI (1.045, 1.863) , P=0.046〕. Conclusion The longitudinal increase of TG and LDL-C levels over time is a risk factor for stroke in check-up population. Bayesian multivariate joint model can be used to explore the risk factors of chronic diseases in check-up population.

During the coal caving process in the fully mechanized caving face, due to the impact of coal dust and dust water mist on the workers' line of sight, there are problems of over-caving and under-caving in manually controlled coal caving. In order to solve this problem, the tail beam of the hydraulic support is regarded as an intelligent agent, and the coal caving process is abstracted as a Markov optimal decision. A deep Q-network (DQN) is used to make decisions on the action of the coal drawing port. However, there is an overestimation problem in the DQN algorithm. A fuzzy deep Q-network (FDQN) algorithm is proposed and applied to intelligent decision-making of coal caving. The fuzzy control system is constructed by using the fuzzy features of the coal seam status in the coal caving process. The coal quantity and the coal gangue ratio in the coal seam state are taken as the inputs of the fuzzy control system. The output action of the fuzzy control system is replaced with the action of the DQN algorithm using the max operation to select the output Q value of the target network. It improves the online learning rate of the agent and increases the reward value of coal caving action. The coal caving model for the fully mechanized caving face is constructed. The three-dimensional numerical simulation of the coal caving process based on DQN, double depth Q-network (DDQN), and FDQN algorithms is conducted respectively. The results show that the FDQN algorithm has the fastest convergence speed, which is 31.6% faster than the DQN algorithm. It increases the online learning rate of the intelligent agent. The coal caving effect based on the FDQN algorithm is the best from three aspects: the straightness of the coal gangue boundary, the remaining coal above the tail beam, and the amount of gangue in the released body. The extraction rate based on the FDQN algorithm is the highest and the gangue content is the lowest. Compared with the DQN algorithm and DDQN algorithm, the extraction rate of the FDQN algorithm has increased by 2.8% and 0.7% respectively, and the gangue content has decreased by 2.1% and 13.2% respectively. The FDQN-based intelligent decision-making method for coal caving can adjust the action of the hydraulic support tail beam based on the coal seam occurrence status. It effectively solves the problems of over-caving and under-caving during the coal caving process.

As a novel antioxidant, a growing body of studies has documented the diverse biological effects of molecular hydrogen (H2) in a wide range of organisms, spanning animals, plants, and microorganisms. Although several possible mechanisms have been proposed, they cannot fully explain the extensive biological effects of H2. Mitochondria, known for ATP production, also play crucial roles in diverse cellular functions, including Ca2+ signaling, regulation of reactive oxygen species (ROS) generation, apoptosis, proliferation, and lipid transport, while their dysfunction is implicated in a broad spectrum of diseases, including cardiovascular disorders, neurodegenerative conditions, metabolic disorders, and cancer. This review aims to 1) summarize the experimental evidence on the impact of H2 on mitochondrial function; 2) provide an overview of the mitochondrial pathways underlying the biological effects of H2, and 3) discuss H2 metabolism in eukaryotic organisms and its relationship with mitochondria. Moreover, based on previous findings, this review proposes that H2 may regulate mitochondrial quality control through diverse pathways in response to varying degrees of mitochondrial damage. By combining the existing research evidence with an evolutionary perspective, this review emphasizes the potential hydrogenase activity in mitochondria of higher plants and animals. Finally, this review also addresses potential issues in the current mechanistic study and offers insights into future research directions, aiming to provide a reference for future studies on the mechanisms underlying the action of H2.

Standardization is the universal language of the world, and standardization of traditional Chinese medicine (TCM) is essential for its communication in China and globally. However, the principles and methods of TCM acupuncture standardization have been unclear and inadequate in the early stages. Based on an investigative approach to understanding the current status, identifying problems, and finding solutions, our team has established basic principles of TCM acupuncture that embody Chinese wisdom, evaluated the international strategic environment systematically, proposed the principle of “importance of harmony and exercise of impartiality”, and established basic working principles. A series of methods for TCM acupuncture standard development and evaluation have been constructed, including general standards for the revision of TCM acupuncture standards, the first TCM acupuncture clinical research management specification, a shared full chain technology platform, a data center, and an evaluation research base for TCM acupuncture clinical research. Evaluation criteria for ancient literature and expert experience, a recommendation method for the “three main and three auxiliaries” TCM guideline for prevention were established, and quantifiable assessment methods of TCM standard applicability were proposed. These findings provide methodological guidance for TCM acupuncture standardization.

Background: 1,2,3,4,6-Penta-O-galloyl-β-D-glucose (β-PGG) is a polyphenol ellagic compound with a variety of pharmacological effects and has an inhibitory effect on lots of cancers. Objective: To explore the antitumor effects and mechanism of 1,2,3,4,6-Penta-O-galloyl-β-D-glucose on human hepatocellular carcinoma HepG2 cells. Design: A network pharmacology method was first used to predict the possible inhibition of hepatocellular carcinoma growth by 1,2,3,4,6-Penta-O-galloyl-β-D-glucose (β-PGG) through the p53 signaling pathway. Next, the Cell Counting Kit (CCK-8) assay was performed to evaluate changes in the survival rate of human hepatocellular carcinoma HepG2 cells treated with different concentrations of the drug; flow cytometry was used to detect changes in cell cycle, apoptosis, mitochondrial membrane potential (MMP) and intracellular Ca2+ concentration; real-time fluorescence quantification and immunoblotting showed that the expression of P53 genes and proteins associated with the p53 signaling pathway was significantly increased by β-PGG treatment. Reasult: It was found that β-PGG significantly inhibited survival of HepG2 cells, promoted apoptosis, decreased MMP and intracellular Ca2+ concentration, upregulated P53 gene and protein expression, increased CASP3 expression, and induced apoptosis in HepG2 cells. Conclusion: This study has shown that network pharmacology can accurately predict the target of β-PGG’s anti-hepatocellular carcinoma action. Moreover, it was evident that β-PGG can induce apoptosis in HepG2 cells by activating the p53 signaling pathway to achieve its anti-hepatocellular carcinoma effect in vitro.

The accurate detection of key equipment and personnel in the fully mechanized working face is an important link to realize the information perception of intelligent coal mining. The traditional target detection algorithm realizes the target detection by extracting the features manually. But it is easily affected by the environment and it is not universal. The target detection algorithm based on the convolutional neural network can extract deep information adaptively. But the detection precision is not high, the network parameters are too many, and the calculation is too large in complex environment. In order to the above problems, an improved YOLOv4 model is proposed and applied to the target detection of the fully mechanized working face. In order to accurately detect targets in the complex environment of a fully mechanized working face, a residual self-attention module is integrated into the CSPDarkNet53 network. The capability of acquiring global information is enhanced while parameter sharing and efficient local information aggregation are ensured. The capability of expressing the features of key targets in an image is improved, and the target detection precision is further improved. In order to meet the requirement of high efficiency of target detection in the fully mechanized working face, depthwise-separable convolution is introduced to replace traditional convolution. The model parameter quantity and calculation quantity are reduced. It is beneficial to the industrial deployment of the model. And it improves target detection speed. The experimental results show that compared with YOLOv3, CenterNet and YOLOv4 models, the average precision of the improved YOLOv4 model is the highest, up to 92.59%. It has better balance in parameter quantity, calculation quantity and detection precision. It can accurately detect the target in the complex environment such as coal dust interference, uneven lighting and motion blur.

Objective To identify ulcerative colitis (UC) and Crohn's disease (CD) with aid of deep learning technology for endoscopists. Methods From January 2018 to November 2020, the endoscopic images of 1 576 subjects (including 34 300 CD, UC and normal images) were collected from the Department of Gastroenterology of Army Medical Center of PLA and Sir Run Run Shaw Hospital.The training set and test set were randomly divided according to the ratio of 9:1 to train and test the neural network.A novel spatial and bilinear deep network (SABA-ResNet) was constructed on the basis of ResNet50.The spatial attention mechanism was introduced, and the receptive field was expanded by dilated convolution to leverage contextual information, which was combined with the local induction of standard convolution to adaptively focus the lesion region.Bilinear attention was applied to improve the feature representation ability of the network, and the second-order information was used to weight the channel information of the feature map, so as to improve the classification performance of the model. Results The overall accuracy of SABA-ResNet for the recognition of CD, UC and normal tissues on the test set was 92.67%(95%CI: 91.91~93.37), the AUC value was 0.978(95%CI: 0.972~0.983), 0.977(95%CI: 0.971~0.982) and 0.999(95%CI: 0.998~1.000), the sensitivity was 88.40%, 89.07% and 98.89%, the specificity was 95.49%, 94.88% and 98.93%, and the F1 value was 88.80%, 89.01% and 98.60%, respectively.The ablation experiment and the class activation map suggested that spatial attention and bilinear attention could help the model capture more features of the lesion region. Conclusion Our constructed network combines spatial attention and bilinear attention, achieves excellent performance in the recognition of CD, UC and normal tissue, and effectively assist endoscopists in the diagnosis of UC and CD.

Acute lung injury is featured as diffuse pulmonary edema and persistent hypoxemia caused by lung or systemic injury. It is believed that these pathological changes are associated with damage to the alveolar epithelium and vascular endothelium, recruitment of inflammatory cells, and inflammatory factor storms. In recent years, the metabolic reprogramming of lung parenchymal cells and immune cells, particularly alterations in glycolysis, has been found to occur in acute lung injury. Inhibition of glycolysis can reduce the severity of acute lung injury. Thus, this review focuses on the interconnection between acute lung injury and glycolysis and the mechanisms of interaction, which may bring hope for the treatment of acute lung injury.

This paper proposes a feasible anti-disturbance constrained control algorithm for a class of typical permanent magnet synchronous motor (PMSM) driven-based single-joint flexible manipulator systems with input saturation and angular velocity constraint. Firstly, by actuating with a surface-mounted PMSM, and setting the d-axis current as zero, the single-joint flexible manipulator is converted into a normal state space model. Secondly, compared with classical harmonic or linear disturbance, the exogenous disturbance model with configurable parameters and the associated disturbance observer (DO) are continuously introduced to dynamically estimate those unknown irregular disturbance. Moreover, by combining the convex hull representation of the saturating input with the suggested adaptive law, an efficient adaptive active anti-disturbance controller is designed to ensure the stability of closed-loop manipulator systems. By using convex optimization technique, not only the dynamic tracking for the rotation position but also the angular velocity constraint can be guaranteed simultaneously. Finally, simulation results for three different kinds of disturbances are showed to demonstrate the superiority of the proposed method.

In order to study the dynamic characteristics of the interest rate term structure of zero-yield bonds in China's bond market, and why China's interest rate term shows such changing characteristics 96-month interest rate structure data at the end of December. Among them, the term structure of interest rates in the securities market is from 1 year to 20 years, and the term structure of interest rates in the interbank market is from one year to 30 years. Analyze the data to find out the basic characteristics of the dynamic change of the term structure of China's interest rate, and find the entire term structure of China's bond market from the perspective of trends. This feature is evident in short-term interest rates in the interbank market, influenced by central bank financial policies. In terms of statistical characteristics, as the yield to maturity of Chinese bonds increases on average, that is, the inclination of the term structure of interest rates increases. The volatility of yield to maturity of short-term bonds is significantly higher than that of long-term bonds, and the volatility of yield to maturity in the securities market is lower than that of the interbank market, mainly because short-term bonds and the interbank market are easily affected by the central bank’s financial policies. Experiments show that the level of inflation rate (PPI growth rate) is an important factor that determines the level of the term structure of interest rates. Inflation rate and interest rate levels are important determinants of skew and curvature factors.

In order to accurately detect, predict and maintain the wear condition of drop forged rivetless chain for conveyors, the methods of wear prediction and active maintenance are developed based on gray model and visual decision support. The wear data are acquired by wear detection device based on machine vision. The obtained data are cleaned by defining and analyzing key parameters of wear condition. A wear prediction model is built based on the gray model. A decision-making support model is constructed that can obtain the optimal plan of maintenance by comprehensively evaluating the wear condition with the forecast data, historical data, and operating condition data. The wear condition can be presented in a three-dimensional and dynamic manner to quickly and accurately locate the wear chain by a visual simulation method. The experiment results show that the wear life prediction model has high fitting accuracy, low false alarm rates, and low missed detection rates of wear early-warning, which can satisfy the requirements of wear life prediction. Through the proposed wear prediction model and visual decision support method, the maintenance efficiency is significantly improved, and the risk of forced shutdown of the production line is reduced.

Introduction: Triterpenoids and saponins have a broad range of pharmacological activities. Unlike most legumes which contain mainly oleanane-type scaffold, Astragalus membranaceus contains not only oleanane-type but also cycloartane-type saponins, for which the biosynthetic pathways are unknown. Objectives: This work aims to study the function and catalytic mechanism of oxidosqualene cyclases (OSCs), one of the most important enzymes in triterpenoid biosynthesis, in A. membranaceus. Methods: Two OSC genes, AmOSC2 and AmOSC3, were cloned from A. membranaceus. Their functions were studied by heterologous expression in tobacco and yeast, together with in vivo transient expression and virus-induced gene silencing. Site-directed mutagenesis and molecular docking were used to explain the catalytic mechanism for the conserved motif. Results: AmOSC2 is a β-amyrin synthase which showed higher expression levels in underground parts. It is associated with the production of β-amyrin and soyasaponins (oleanane-type) in vivo. AmOSC3 is a cycloartenol synthase expressed in both aerial and underground parts. It is related to the synthesis of astragalosides (cycloartane-type) in the roots, and to the synthesis of cycloartenol as a plant sterol precursor. From AmOSC2/3, conserved triad motifs VFM/VFN were discovered for β-amyrin/cycloartenol synthases, respectively. The motif is a critical determinant of yield as proved by 10 variants from different OSCs, where the variant containing the conserved motif increased the yield by up to 12.8-fold. Molecular docking and mutagenesis revealed that Val, Phe and Met residues acted together to stabilize the substrate, and the cation-π interactions from Phe played the major role. Conclusion: The study provides insights into the biogenic origin of oleanane-type and cycloartane-type triterpenoids in Astragalus membranaceus. The conserved motif offers new opportunities for OSC engineering.

In present work, Fields Activated Sintering Technology (FAST), has been applied to successfully sinter the high-entropy alloy (HEA) samples. Based on the analysis of the microstructure, relative density and microhardness of the sintered HEA samples, the influence of sintering temperature and pulsed magnetic field treatment (PMT) has been investigated. In terms of performance, HEA samples fabricated using PMT-powder sintering exhibit superior properties compared to UT-powders. Regarding elemental distribution, pre-treating the powders with a pulsed magnetic field can enhance the uniformity of the alloyed powder components. Furthermore, elevated sintering temperatures have been observed to substantially accelerate the densification process, thereby improving the relative density of the sintered samples.