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The development of pesticides has significantly advanced global agricultural production, but the ensuing problem of pesticide residues poses a severe threat to human health. So, there is an urgent need to establish a rapid, accurate, sensitive, cost-effective and on-site method for large-scale detection of pesticide residues. Electrochemical paper-based analytical devices (ePADs) represents a highly sensitive and portable microanalysis system, which uses paper as a substrate and relies on a capillary force to drive the fluid for the separation and detection of samples. The diversity of pesticides and agricultural products and the complexity of matrices impose high requirements on the sample preparation procedure. This article summarizes the preparation process of ePADs from the aspects of paper selection, the establishment of hydrophilic and hydrophobic channels, the integration of separation zones, and electrode printing. Subsequently, this paper establishes the relationship between pesticide detection and chip preparation based on the mechanism of electrochemical detection of pesticides. Finally, it discusses the advantages, challenges and future prospects of ePADs with a view to providing theoretical reference for enhanced application of ePADs in the field of pesticide residue detection.

Partial discharge at the oil-paper interface is one of the main reasons for the failure of oil-paper insulation in oil-immersed transformers. In this article, based on the numerical model of multi-branching streamer discharge, a multi-branching streamer discharge model in oil-paper insulation system is constructed by further considering the charge transport characteristics of oil-paper interface. The surface discharge characteristics under the influence of the dielectric constant ratio between natural ester insulating oil and insulating paper, and the spacing between needle electrode and paperboard are studied by finite element method, respectively. The results show that the distance between the needle electrode and the paperboard, and the dielectric constant ratio of insulating oil and insulating paper both significantly affect the streamer branching. The smaller the clearance between the needle electrode and paper-board is, the more serious the inhibition of streamer branches at the oil-paper interface is, which resulting in the streamers near the oil-paper interface are more significant effect on the propagation of the z-axis streamer. When the dielectric constant of the insulating oil is larger than that of the paperboard, the development and branching of the streamer in the oil will be more significant. On the contrary, the streamer is more likely to develop along the surface of the paperboard and accumulate charge at the oil-paper interface.

Oil-immersed power transformer is an important part of power grid, and its reliable operation plays a vital role in pomler system security. Aiming at the problem that the insulation state of transformer cannot be assessed quantitatively after long-term operation, the accelerated aging and damp tests of oil-paper insulation model are carried out in this paper. The influence of aging and damp of oil-paper insulation on its recovery voltage curves is explored. The particle swarm optimization (PSO) is used to improve the parameter prediction method of extreme learning machine (ELM), which realizes the quantitative assessment of aging and moisture of oil-paper insulation based on the characteristic parameters of the recovery voltage curve. By comparing the physical and chemical performance analysis of oil-paper insulation models, it is shown that the prediction accuracy of PSO-ELM method is much higher than that of traditional ELM method. The absolute error range for predicting the moisture content of oil-paper insulation the degree of polymerization (DP) of pressboard is less than ±0.4% or ±30, respectively.

Ultra high frequency (UHF) partial discharge (PD) detection is a common method for transformer oil-paper insulation defect location. However, the accuracy of PD positioning in practical application is easily affected by noise and sensor layout. In order to ensure the effectiveness of PD positioning detection of transformer oil-paper insulation defect, an UHF PD positioning detection platform for oil-paper insulation defects is established. Based on the conventional K-means method, a modified clustering demarcation PD anti-interference positioning method is proposed, which effectively reduces the positioning error. Aiming at the problem of sample clustering demarcation aliasing, when the optimal correction coefficient L is 1.1, the UHF PD positioning error can be reduced to less than 0.1 m, which verifies the effectiveness of the proposed method. Finally, the variation law of positioning error of different sensor layout is analyzed, and the optimal layout scheme of UHF sensor for transformer oil-paper insulation defect detection is proposed, which can provide reference for the layout and positioning of transformer on-line monitoring sensor.

High prevalence and low control rate of hypertension have brought a significant disease burden globally. In order to improve the level of hypertension prevention and treatment, remote healthcare and digital medicine have been rapidly developed and widely used worldwide. Currently, there are no relevant regulations in China for these technologies. In 2023, the Italian Society of Arterial Hypertension issued a position statement to guide the development, validation, and clinical use of remote medicine and digital healthcare. This article will interpret this position paper, focusing on the forms of application of telemedicine and digital healthcare in managing hypertension and its related cardiovascular diseases, key research evidence, existing advantages, as well as current opportunities and challenges. The aim is to guide general practitioners in China on how to utilize these technologies in managing hypertension and related cardiovascular conditions.

A flexible wipe paper for rapid nondestructive detection of ferbam residues on the surface of fruits and vegetables by surface-enhanced Raman scattering (SERS) was prepared using filter paper as the substate by a simple soaking method. The synthesis and storage conditions were optimized to ensure that the SERS method has excellent performance. The results showed that concentration factor of silver nanoparticles (AgNPs), soaking time in AgNP solution and drying method greatly affected the performance of the SERS wipe paper. The performance under the condition of soaking for 8 h in a 5-fold concentrate of AgNP solution was significantly better than that under other conditions. The SERS wipe paper prepared by vacuum drying had better performance that those prepared by other drying methods. After 9 days of storage at −20 ℃, the optimized substrate retained approximately 50% of the original peak value. Besides, it exhibited good sensitivity, uniformity, and repeatability. The limit of detection (LOD) for ferbam on a glass plate was 4.07 × 10-6 mg/mL, and the LOD for ferbam on the surface of spinach and nectarine were 0.043 and 0.062 mg/kg, respectively. This study provides an excellent basis for the development and utilization of SERS wipe paper.

BackgroundIn recent years, the rising number of e-cigarette users among adolescents and the surging cases of lung injury related to e-cigarette use have attracted the attention of researchers in various fields.ObjectiveTo identify the research hotspots and trends of e-cigarette or vaping product use associated lung injury (EVALI) worldwide from 2013 to 2022 by bibliometric and visual analysis. MethodsWeb of Science Core Collection was selected to obtain literature related to EVALI from 2013 to 2022 across the world, statistics were calculated by country/region, institution, author, journal, cited literature, keyword, etc. CiteSpace 6.2.R1 was used for visual analysis to draw diagrams of publication trend, author cooperation network, co-citation clustering time distribution, and keyword cluster. ResultsA total of 888 EVALI-related papers published between 2013 and 2022 were retrieved. The number of publications was gradually increased, with a significant increase in 2020 and a decrease from 2021, but the number of citations was increased year by year. The most active country was the United States (631 articles). European and American countries cooperated closely and the centrality was prominent. Among the publishing institutions, the University of California system topped the list with 103 articles. Rahman I (27 articles) published the most articles and had a high degree of centrality; Goniewicz M L was the most cited author; and the network analysis diagram showed relatively weak collaboration between authors. The American Journal of Respiratory and Critical Care Medicine was the journal with the highest number of publications (94 articles). The top 5 cited articles were all cited more than 300 times. The leading high-frequency keywords of EVALI-related studies were nicotine (149 times), exposure (118 times), and oxidative stress (80 times). The cluster of key nodes in the co-citation network and the clustering time distribution diagram indicated youth e-cigarette addiction received widespread attention from society. From the top 25 keywords with the strongest bursts, the focus of research on the pathogenesis of EVALI gradually shifted from the oxidative stress damage associated with e-cigarette vapor to the oxidative effect of flavoring chemicals in the process of lung injury. The current research interests in this field were mainly the mechanisms of various chemicals in e-cigarettes and the heating elements that led to damage to the lungs. ConclusionEVALI is receiving continuous attention from researchers in government, medical institutions, and other organizations. A variety of e-cigarette ingredients such as flavoring chemicals may lead to varying degrees of cytotoxicity, inflammation, and lung damage. However, the pathophysiology of EVALI remains unclear. In the future, more Chinese scholars should be encouraged to participate in this field.

The insulation performance of transformer bushings is a crucial aspect that directly affects the safe operation of equipment. To diagnose the insulation status of transformer bushings and mitigate the impact of small-sample imbalanced data on diagnostic results, a particle swarm optimization combined with back propagation neural network (PSO-BPNN) and adaptive synthetic sampling (ADASYN) method are employed to fault diagnosis of transformer bushing. Initially, historical fault data of transformer bushings are gathered, and a sample set of dissolved gases in transformer oil with distinct fault categories is established. The ADASYN algorithm is used to synthesize the minority class samples in the original data, which allowed for obtaining balanced fault data. The balanced dissolved gases in oil served as the model input, and the fault status is used as the label output to diagnose the transformer bushings using the PSO-BPNN model. To diagnose the bushings under the original sample set, the back propagation neural network (BPNN), genetic combined with back propagation neural network (G-BPNN), cuckoo search combined with back propagation neural network (CS-BPNN), and PSO-BPNN models are used. The results reveal that the PSO-BPNN model based on ADASYN balanced data exhibited the highest accuracy among the various models for fault diagnosing the insulation status of transformer bushings. This approach effectively mitigate the impact of small sample imbalanced data on diagnostic results, and provide an effective method for assessing the insulation performance of transformer bushings.

Strong-aroma natural spices are characterized by their strong aroma, possessing aromatic and irritating properties, with the main components being aromatic compounds. Typical representatives include star anise, cinnamon, fennel, and cloves. The aforementioned strong-aroma natural spices are widely used both domestically and internationally, especially in soy sauce stewed meat products and fermented meat products. Nonetheless, current research on the aroma-imparting and flavor-presenting mechanisms of natural spices remains insufficiently in-depth and systematic. This paper bases on a review of relevant domestic and international research in recent years, systematically summarizes the flavor analysis methods, flavor characteristics, and key flavor components of typical strong-aroma natural spices. It concurrently discusses their impact on the flavor formation of meat products: spice flavor components can influence the flavor of soy sauce stewed meat products by directly migrating into the food or by improving the flavor of fermented meat products through inhibiting fat oxidation and anti-bacterial effects. Building on this, the paper further elucidates the aroma-imparting and flavor-presenting mechanisms of strong-aroma natural spices, encompassing direct migration of flavor components into food for aroma enhancement, aroma-generating reactions between spice components and food matrices, inhibition of flavor precursor oxidation processes, and suppression of spoilage bacteria growth to ameliorate undesirable flavor formation. The summary of the flavor characteristics and aroma-imparting mechanisms of strong-aroma natural spices facilitates researchers in delving into the mechanisms by which these spices regulates food flavor formation and provides a reference for food enterprises, particularly meat product manufacturers, in further rational development and utilization of natural spices.

The dry matter content in buffalo milk is relatively high, and its comprehensive nutritional value, which is higher than that of ordinary milk, is considered a good source of various bioactive components. Therefore, buffalo milk and its related products are receiving increasing attention from consumers. In this paper, the contents of protein, fat, carbohydrate and other nutrients in buffalo milk and their physical and chemical properties are introduced according to the cutting-edge research results on buffalo milk nutrients and their products. Meanwhile, the preparation and related research of buffalo milk dairy products, such as cheese, cream, yogurt and ice cream are summarized. Finally, this paper provides some insights on the possibility of developing functional food based on bioactive substances in buffalo milk and reference for enterprises to develop buffalo-milk-related products.

Objective: To conduct a bibliometric analysis of the literature in the field of amino acid radiation protection over the past decade using CiteSpace software, exploring the formation, development, hotspots, and trends in this domain. Methods: The data source is the core collection of the Web of Science database, which include 413 papers on radiation damage of amino acids after deduplication and screening. CiteSpace software is used to visualize these papers, and the keywords and their clusters in this field are summarized from multiple dimensions and perspectives. Results: According to these papers, this field is dynamic and continuously growing, attracting interest from many scholars. Regarding country/institution distribution, China, the United States, and India have higher publication volumes, while the UK and India have more vital centrality in their publications. Keyword analysis reveals that the research hotspots in this field include ultraviolet radiation, oxidative stress, mycotoxin amino acids, and antioxidant activity. In contrast, emerging keywords such as DNA damage, photoprotection, and porphyrin-334 show research potential. Cluster analysis find that ultraviolet radiation protection, mycotoxin amino acids, glutamate, and adjuvant radiotherapy are the main research directions in this field. According to ionizing and non-ionizing radiation classification, the representative papers of the past decade sorted out the amino acids and their derivatives related to radiation protection. Conclusion: The visualization of the current situation, hotspots, and trends in the field of amino acid radiation protection provides valuable guidance and prospects for the development of amino acid food and the research of radiation protection in the future. Since the nuclear leakage accidents caused widespread concern, the demand for natural and harmless radiation protection products has surged, especially the development potential of amino acid radiation protection food. However, the current research on the structure-activity or mechanism of amino acid radiation protection needs to be more in-depth. It is still necessary to strengthen multi-agency cooperation and multi-center communication and focus on research hotspot keywords to help the development of amino acid radiation protection foods. In the context of the continuous spread of nuclear sewage, food technology is used as a shield to safeguard people's health.

Diffusion tensor imaging is an essential technique to study tissue brain microstructure and the distribution of white matter fiber tracts. However, affected by the diffusion-weighted signal attenuation and long echo time, diffusion tensor images suffer from serious low signal-to-noise ratio problem. Therefore, efficient denoising techniques are crucial for enhancing image quality. This paper starts with the principle of diffusion tensor imaging and the types of noise. Then it discusses the classical diffusion tensor image denoising algorithms, including algorithms based on traditional image processing and deep learning. Special emphasis is given to the status and shortcomings of diffusion tensor image denoising research. The denoising evaluation criteria and commonly used public datasets are also introduced, followed by experiments and quantitative analysis on the diffusion tensor image denoising methods mentioned in this paper. Finally, it concludes with a summary and an outlook for the field’s future research directions.

In recent years, deep learning-based object detection algorithms have been a hot topic in computer vision research, with the YOLO (you only look once) algorithm standing out as an excellent object detection algorithm. The evolution of its network architecture has played a crucial role in improving detection speed and accuracy. This paper conducts a comprehensive horizontal analysis of the overall frameworks of YOLOv1 to YOLOv9, comparing the network architecture (backbone network, neck layers and head layers) and loss functions. The strengths and limitations of different improvement methods are thoroughly discussed, with a specific evaluation of the impact of these improvements on model accuracy. This paper also delves into discussions on dataset selection and construction methods, the rationale behind choosing different evaluation metrics, and their applicability and limitations in various application scenarios. It further explores specific improvement methods for YOLO algorithm in five application domains (industrial, transportation, remote sensing, agriculture, biology), and discusses the balance among detection speed, accuracy, and complexity in these application domains. Finally, this paper analyzes the current development status of YOLO in various fields, summarizes existing issues in YOLO algorithm research through specific examples, and in conjunction with the trends in application domains, provides an outlook on the future of the YOLO algorithm. It also offers detailed explanations for four future research directions of YOLO (multi-task learning, edge computing, multimodal integration, virtual and augmented reality technology).

The main purpose of unbiased cross-domain object detection is to utilize the knowledge of the source domain to the maximum extent through knowledge distillation, and reduce the cross-domain gap of the model through domain adaptation. However, the pseudo labels generated by the mean teacher method commonly used for unbiased cross-domain object detection are not reliable, resulting in significant domain bias issues between teacher and student models. Therefore, inspired by the invariance of phase information in Fourier transform, this paper proposes the Fourier augmentation unbiased mean teacher (FAUMT) model based on the mean teacher. This paper utilizes the invariance of Fourier phase information to design an amplitude mixing data augmentation (AMDA) module, which can effectively mix phase information between the source and target domains to achieve data augmentation. And data augmentation will generate additional noise, thus this paper designs two consistency losses to ensure the consistency of predictions before and after data augmentation. In addition, to balance the cross-domain bias between the source and target domains during model training, this paper also designs a multi-layer adversarial learning (MAL) module, with the aim of domain alignment of pixel level features at different levels. On three benchmark datasets Cilpart1K, Watercolor2K and Comic2K, the mAP of proposed method achieves 47.5%, 58.9% and 46.1%, respectively, outperforming other algorithms.

The application of large language models in process specifications is an effective approach to addressing the issue of inaccurate process knowledge queries. At present, the domain model construction methods through domain knowledge graph embedding or fine-tuning with instruction data are not effective. The difficulty lies in the fact that the process knowledge in the process specifications involves relationships between multiple process elements, which is highly complex. The data are sparse because the standards are only used through citation. The high complexity of process knowledge and sparse data limit the model’s ability to learn process domain concepts, the relationships between concepts and attributes, the relationships between concepts, the relationships between multiple concepts, and reference-based knowledge. To address this difficulty, this paper proposes a large language model knowledge injection method for process specification texts. According to the characteristics of process specification data, this paper designs knowledge injection data including auxiliary sentence identification task, concept-chapter generation task, chapter continuation task and chapter-summary generation task. The model is fine-tuned through supervised learning by combining question-answer pair data to inject domain concepts, attributes, relationships between multiple concepts, and reference knowledge into the model. Experimental results show that the model trained with knowledge injection data and question-answer pair data improves ACC (accuracy) by 7.3 percentage points, ROUGE-L by 7.4 percentage points, and BLEU-4 by 6.2 percentage points compared with the model trained only with question-answer pair data, indicating the effectiveness of the proposed knowledge injection method.

Background Using discrete choice experiment (DCE) to study the employment preference of health personnel to choose jobs can provide scientific and efficient basis for the formulation of policies related to the attraction and retention of health personnel in rural and remote areas. Objective To review, summarize and generalize the researches on the application of DCE to the field of human resources for health, so as to provide reference for future research. Methods Web of Science, PubMed, CNKI, Wanfang and VIP were systematically searched for literature related to DCE application to the field of health human resources from February to April in 2022. The data of included studies such as study objectives, data analysis models, the choice item settings and results were extracted. Results A total of 44 papers published from 2000 to 2020 were finally included. The study objects were mainly health workers in service and students; six studies were labeled and others were unlabeled in the included papers; the number of working attributes ranged from 4 to 8; the number of levels of working attributes was predominantly 2 to 4 (88.6%, 39/44). The teamwork of general practitioners and workload were used as working attributes in the studies in high-income countries; the most frequently selected working attribute in studies from low-and middle-income countries was housing (21 times), followed by essential equipment such as facilities and medications (19 times), and learning/training opportunities (16 times). Income (salary) was incorporated into the working attributes across the literature. Furthermore, we formulated a framework of working attributes containing four aspects: social aspects, including the hospital volume, social support/respect, identification (establishment or becoming a permanent employee) ; working aspects, including working location, working conditions, workload, working (management) atmosphere, teamwork, mentoring by supervisors (for primary health workers) ; career development aspects, including years of promotion, training (continuing education) opportunities, academic and research opportunities; life aspects, including income, housing, traffic, and children's education. Mixed Logit Model was the frequently used analytical model (19 times), followed by Conditional Logit Model (9 times), Generalized Multinomial Logit Model (3 times) . Conclusion The heterogeneity of research findings in this field is large, making it difficult to draw uniform conclusions. Moreover, the application of DCE in the field of human resources for health still needs to be promoted globally. Relevant studies are very limited and the evidence obtained needs to be confirmed by further research.

Background Cardiovascular disease (CVD) is a major cause of human mortality worldwide, characterized by its insidious onset, intricate and variable course, and poor prognosis. Early identification and active intervention of potentially critically ill patients is essential to improve their prognosis. Objective To conduct a scoping review of the research on early warning assessment tools for cardiovascular disease risk at home and abroad, summarize and analyze their assessment content and application, ultimately providing reference for the selection of appropriate early warning tools for cardiovascular disease patients in China. Methods CNKI, Wanfang Data, VIP, CBM, PubMed, Web of Science, Cochrane Library, Embase, CINAHL, and Scopus were systematically searched from inception to May 2023. Two investigators independently screened literature and extracted data, analyzed in terms of assessment content, study subjects, validation method, reliability and validity, and predictive efficacy. Results A total of 16 papers were included, comprising 7 papers on the development and validation of assessment tools and 9 papers on the localized application of these tools, involving 20 early warning assessment tools for cardiovascular disease risk. The results of the analysis showed that each assessment tool contained 3 to 17 assessment items, with the most frequently mentioned items of age, systolic blood pressure, respiratory rate, oxygen saturation, heart rate, comorbidities, level of consciousness, and gender. The results of the reliability and validity tests for 2 papers indicated robust reliability and validity, while all other studies lacked reliability and validity evaluations. Ten papers reported the area under the curve (AUC), with values ranging from 0.550 to 0.926 9. Conclusion Diverse early warning assessment tools for cardiovascular disease risk are available, however, their overall quality remains to be improved and there is a lack of specific assessment tools. In the future, it is imperative to conduct further validations of the reliability and validity of the existing tools, and develop localized early warning assessment tools specialized for cardiovascular diseases considering the unique characteristics of the disease, which exhibit robust reliability and validity.

Background Traditional Chinese medicine (TCM) is effective in the treatment of sepsis-induced acute lung injury (ALI) /acute respiratory distress syndrome (ARDS). However, the lack of standard and uniform outcome indicators in the design of most published clinical trials makes it difficult to combine and compare the results of similar studies, causing the impossibility of generating high-quality evidence to guide clinical decision-making. Objective To analyze the use of outcome indicators in randomized controlled trials on TCM for sepsis-induced ALI/ARDS from 2017 to 2022. Methods CNKI, Wanfang Data, SinoMed, PubMed, Embase, Web of Science and Cochrane Library were searched for RCTs on sepsis-induced ALI/ARDS, with the intervention group treated with TCM combined with other drugs or conventional treatment, and no restrictions in the control group. The ROB.2 tool of the Cochrane Review Group was used to assess the quality of literature and the classification of outcome indicators was summarized. Results 39 papers were included after screening, including 1 (2.56%) with low risk of bias, 3 (7.69%) with high risk of bias and 35 (89.74%) with concerns of bias. The outcome indicators in 5 RCTs were reported with a quality score of ≥5, indicating the complete reporting of outcome indicators. A total of 106 outcome indicators were reported and used for 443 times, including physicochemical testing outcome (55 types, 51.89%), TCM syndrome/sign outcome (2 types, 1.89%), symptom and syndrome outcome (13 types, 12.26%), long-term prognosis outcome (19 types, 17.92%), quality of life outcome (7 types, 6.60%), safety event outcome (8 types, 7.55%) and economic evaluation outcome (2 types, 1.89%). There were four outcome indicators with utilization rate>50%, including oxygenation index (82.05%), Acute Physiology and Chronic Health Evaluation Scoring System (58.97%), mechanical ventilation duration (51.28%) and interleukin-6 (51.28%). The composite outcome indicators of effective rate or TCM syndrome efficacy were used in 21 papers, involving a total of 12 times of effective rate, TCM syndrome score of 8 times and TCM symptom efficacy of 6 times. The total 106 outcome indicators were summarized and categorized sequentially including overall evaluation indicators (36 types, 33.96%), common indicators (36 types, 33.96%) and different focus indicators (34 types, 32.08%) . Conclusion At present, the selection of outcome indicators in RCTs on TCM for sepsis-induced ALI/ARDS is still nonstandard, mainly manifests in unclear differentiation between primary and secondary outcome indicators, trivialization of endpoint indicators, lack of follow-up data and characteristic indicators of TCM. A core outcome set of TCM outcome indicators for septic induced ALI/ARDS should be constructed to promote the high-quality development of TCM in the future.

Background With the aging and life expectancy increasing in China, sleep disorders in the elderly (≥80 years old) have received widespread attention. As one of the common problems, sleep disorders seriously affect the quality of life and physical and mental health among the elderly, and can also aggravate or induce multiple diseases. Objective To conduct a scoping review of studies on sleep disorders in community dwelling older adults over 80 years and provide guidance for the early diagnosis and treatment of sleep disorders in community dwelling older adults in China. Methods PubMed, Embase, CINAHL, Web of Science, Cochrane Library, OpenGrey, SinoMed, CNKI, Wanfang Data, and VIP databases were searched for literature on sleep disorders in community dwelling older adults from inception to March 15, 2023. Literature was independently screened by 2 investigators and basic characteristics of the literature were extracted (authors, time of publication, country, type of study, sample size, assessment tool or modality, prevalence, findings) . Results A total of 10 486 papers were searched, and 21 papers were finally included, of which 14 were in English and 7 were in Chinese, 16 were cross-sectional studies, 2 were quasi-experiment studies and 3 were longitudinal studies. The results of the analysis indicated that sleep disorders were more prevalent with serious adverse effects in the community dwelling older adults aged over 80 years (the prevalence rate ranged from 10.0% to 60.3%), which were assessed by nine tools or modalities, including three structured scales with the more commonly used scale being Pittsburgh Sleep Quality Index (PSQI). The influencing factors of sleep disorders were divided into three categories of social demographic factors, physical health and disease-related factors, psychological and behavioral characteristic factors. Interventions such as music therapy, therapy combined with interaction mode groups were found to be effective in improving sleep disorders. However, few prevention and intervention studies were conducted. Conclusion The high prevalence of sleep disorders among older people in the community is high with serious effects, there is insufficient knowledge about sleep disorders among community dwelling older adults and fewer types of assessment tools lacking specificity in China. The influencing factors of sleep disorders among older people are complex and diverse, with a lack of research on prevention and intervention.

The fine modeling of the lunar gravity field is a fundamental task for establishing lunar altitude references, conducting research on lunar interior structure, and other scientific endeavors. The lunar gravity field model constructed solely based on spacecraft orbit data has limited spatial resolution, making it challenging to meet the demands of fine gravity field research. The acquisition of high-resolution terrain models presents new opportunities for the study of precise lunar gravity fields. This paper reviews the current status and advancements in fine lunar gravity field modeling, including research efforts and evaluation methods for global lunar gravity field models, principles and technologies for fine gravity field modeling, as well as related research outcomes. On this basis, this paper systematically summarizes the key theoretical issues and technical challenges in the theory of lunar gravity field modeling based on high-resolution terrain models. These include data updating, error correction in high-frequency gravity field modeling, calculation efficiency, and the series divergence problem in spherical harmonic analysis. In addition, future research directions are discussed. This work will provide references for gravity field research on the Moon and other terrestrial planets.

The situation of coal as the stabilizer guarantee the energy safety in China cannot be changed in the short term, and it will continue to face the problems of coal resource protection and the low utilization rate of coal-based solid waste. Through innovative mining methods, improving the recovery rate of coal resources and the large-scale disposal of coal-based solid waste, a new path is being paved for the green and sustainable development of the coal industry. Based on the in-depth research on the development status of coal mining technology, a new roadway excavation method of “excavation-backfill-retention” is proposed. This paper systematically discusses the scientific problems and key technologies of the “excavation-backfill-retention” construction method from three aspects: rapid excavation, continuous and efficient backfilling and safe construction of large-section roadways. The research results show that ① aiming at the engineering problems such as the fast excavation of large section roadway and the stability control of surrounding rock of heading face, three scientific problems are summarized: the matching mechanism between coal and rock characteristics and cutting parameters of roadway boring machine, the spatial transfer mechanism of overburden load and the deformation mechanism of surrounding rock, the interaction relationship between anchor/cable roof and support mechanism. The technology system has been built, which is based on the real-time sensing of the geological environment in the excavation area, the intelligent cooperative operation of the multi-process of falling, loading and transporting coal, the aging control of surrounding rock of the drilling anchor support together with excavation, the anti-leakage and ventilation optimization of the large section roadway. ② The scientific problems of continuous and efficient backfilling are summarized from the two aspects of timely construction of large section roadway bearing system and its bearing performance regulation, including the co-bearing mechanism of background coal anchor/cable, the hydration consolidation mechanism of multi-component solid waste base backfill materials, and the space-time evolution law of physical and mechanical characteristics of backfill are clarified. A continuous and efficient backfill key technology system with the core of safe and efficient backfill space construction, backfill material performance control and backfill material flow-consolidation perception has been established. The breakthrough of relevant theories and technologies can provide a theoretical basis for raw material selection and ratio design of backfill materials, additive development/selection and working performance control, excavation rate and backfill step optimization design, consolidation monitoring of backfill body, etc. ③ Based on the key problems of roadway safety and surrounding rock easy to break, sheet and damage in the whole life cycle, the paper elaborates three scientific problems: the spatial and temporal distribution characteristics of stress field of roadway surrounding rock, the evolution mechanism of roadway deformation and damage, the engineering quality monitoring and stability regulation theory of roadway surrounding rock. The key technology system is formed with the intelligent stability warning of the rock surrounding the roadway and the deformation control of the rock surrounding the roadway as the core. It is of great significance to conduct the scientific research and technical demonstration of the “excavation-backfill-retention” construction method in coal mines, and to realize the synergy of large-scale solid waste disposal, efficient coal pillar section recovery and rapid roadway excavation, which can promote the green and low-carbon transformation and development of the coal industry.

In order to systematically understand the various types of water hazards and standardize the management of water prevention and control work in coal mines, the National Mine Safety Administration in June 2022 extended the “three zones” management methodology for old goaf water prevention and control to more types of water hazards, such as roof water, floor water, and structural water. However, in the process of dividing the “three zones” of water prevention and control in coal mines, it is revealed that the water damage causing factors and water damage management situation are not closely linked with the division standard, and that technically different divisions are not made for different coal seams and mining areas, and there are inconsistencies in the scope of the division area, and the standardization and timeliness of the division results. Accordingly, combined with the purpose of water hazard prevention and control “three zones” division, compared the similarities and differences between the new and old “three zones” division work, this paper clarifies the degree of hydrogeological conditions survey, water hazard analysis, water hazard management as elements of the division principles, and determines the technical path of the division of the “three zones”. Combining the characteristics of five common types of water hazards in coal mines, the paper puts forward the division method of different types of water hazards, that is: surface water hazard should be divided according to the distribution and development characteristics of surface water bodies in the mining area and the degree of influence of atmospheric precipitation, landslides and other geological disasters in mining. The roof water hazard should be divided according to whether there is a strong water-rich aquifer, a medium water-rich but hydrostatic reservoir-rich aquifer, a loose aquifer. The floor water hazard should be divided according to the relationship between the thickness of the floor water barrier and the depth of the floor mine pressure damage zone in the coal seam pressure mining area, as well as the size of the floor water inrush coefficient. The old goaf water hazard should be divided according to the distribution range and amount of water in the mine and the surrounding mines. The structural water hazards should be divided according to the water-richness, water content, and water source conduction of geological structures and bad geological bodies such as faults, trap columns and caves in the mining area. The key points and difficulties of the division work include the clear division of time and space scope, the comprehensive analysis of division standards, the clear management responsibilities for the “three zones”, and the dynamic transformation of division results. On this basis, typical coal mines with various types of water hazards and complex hydrogeological conditions are selected as case studies. Following the principle of division, according to the division standard, the mineable zone, the slow mining zone and no-mining zone are divided by the method of separating coal seams and mining areas, and detailed explanations are given. The significance of carrying out the division of the “three zones” for water hazard prevention and control is clarified, which can enhance the comprehensive detection level, strengthen the prediction ability, and identify the direction of water hazard management in order to guide and standardize the division of the “three zones” for water prevention and control in the coal mines of China.

With the promotion of the “carbon peaking and carbon neutrality” goals, the social’s concern and demand for the treatment of coal gasification slag is becoming more and more urgent. Based on previous research, this paper introduces the main sources and discharge methods of coal gasification slag, and compares the properties and characteristics of coarse and fine slag in terms of morphology, particle size composition, mineral phase, chemical composition, etc, which providing a theoretical basis for the realization of its “reduction, resourcefulness and harmlessness” utilization. According to the obvious differences in properties between coarse slag and fine slag in entrained-flow gasification, this paper explores the different resource treatment methods both of them, and analyzes the limitations of the current utilization methods. Coarse slag has excellent hydration activity and volcanic ash activity, and is widely used in mine backfilling, roadbed filling, cement and concrete aggregate, ceramic materials, wall materials and other low-value utilization fields, but there are problems such as the risk of heavy metal leaching and low economic benefits. Fine slag contains rich carbon residue, and gravity separation and flotation are mainly used for combustible recovery and ash separation. However, the high fine-grained content reduces the precision of gravity separation, and the complex carbon-ash combination morphology increases the difficulty of flotation recovery. At the same time, the pore structure of fine slag is developed, with a specific surface area as high as 258.29 m2/g and certain adsorption capacity. Fine slag has great application potential in fields such as soil improvement, catalyst carrier, chemical raw materials, ceramic materials, adsorption materials, etc. But the complex high-value treatment process and high cost make industrial applications more difficult. In order to address these problems, it is necessary to explore the way of combing large-scale elimination with high-value utilization based on the physical and chemical properties of coal gasification slag, and realize the classified and graded resource utilization of coal gasification slag. It is necessary to explore the treatment method of on-site solution of coal gasification slag, combined with field production practice, which benefits to reduce the transportation cost. As well as the induction of physical and chemical properties to improve the treatment in the process of its generation.

Metal hydride hydrogen storage is a hydrogen storage method based on the principle of chemical absorption. Featuring high volumetric hydrogen storage density and high safety, its potential applications in the field of hydrogen storage on ships have attracted significant attention. Against this background, there is a series of issues to be studied, such as material properties, reactor performance, thermal management systems, cost, etc. This paper categorizes metal hydride hydrogen storage technology, summarizes its working principle and research progress on its material properties, and introduces its applications on ships. Next, combined with the application environment and demands of hydrogen ships, the paper analyzes the technological and economic feasibility of the application of metal hydride hydrogen storage technology on ships. To meet the requirements of hydrogen ships for hydrogen storage capacity and release rate, research on marine metal hydride hydrogen storage systems is introduced, including hydrogen storage system performance research, hydrogen storage reactor structure, reactor structure optimization and design ideas for thermal management systems coupled with marine fuel cell and hydrogen storage systems. Finally, the research direction of marine metal hydride hydrogen storage systems is predicted and summarized.

ObjectiveThis paper analyzes and models the core logic of a strike chain in terms of time sensitivity, reconfiguration and coverage, thereby providing model and method support for improving the dynamic management ability of naval combat resources under confrontation conditions. MethodsFirst, the typical combat platforms and elements related to the cross-domain cooperative combat of naval battlefields, such as escort ships, UAVs and unmanned boats, are abstracted into four types of resource nodes, namely detection, processing, decision-making and strike. Next, taking the shortest delay as the goal and considering constraints such as wide battlespace, low transmission rate between nodes and limited communication distance, the dynamic integration optimization mathematical model of the strike chain is established. A typical air defense scenario is then designed to demonstrate the shortest delay analysis of the strike chain and the destruction reconstruction analysis under the absence or attack of nodes, and quantitatively describe the changes of the shortest delay and sector coverage index of the reorganized strike chain under countermeasure conditions. Finally, based on a typical combat example of a Ukrainian unmanned cluster attack on the Black Sea Fleet, the ability of the fleet to resist the attack is analyzed on basis of the strike chain model. ResultsThe simulation results show that the model can be used to generate multiple strike chains with the shortest delays, and the responsibility division of each strike chain can be optimized, forming a multi-target killing network at sea. The destruction reconstruction of the strike chain often needs to pay such costs as increased delay and decreased sector coverage. The model can also be used to test anti-saturation attack ability under different formations.ConclusionsThis paper studies and validates the feasibility of analyzing the naval warfare system based on the strike chain model, and can provide theoretical model support for the subsequent design of future naval joint combat systems oriented to the killing network.

The application of offshore wind power gangways ensures the normal operation of offshore wind turbines and provides reliable support for optimizing the boarding process, improving the operation and maintenance efficiency, and reducing the cost of wind power projects. This paper provides an overview of the development history and technological progress of gangways, and analyzes the main equipment in this field and its performance at home and abroad, as well as discussing the key technologies of offshore wind turbine gangways in such aspects as motion sensing and data analysis, compensation control and execution, structural design and reliability, and composite material application. It is pointed out that the parallel platform is the mainstream offshore gangway actuator; wave compensation is the core of equipment performance and the source of competitiveness; and advanced wave compensation technology depends on the development of sensor technology, artificial intelligence technology and other multidisciplinary development. This paper makes a comprehensive analysis for researchers and practitioners in the field of offshore wind power gangways, providing valuable references for subsequent technology exploration.

China has successfully launched six lunar probes so far. From Chang’E-1 to Chang’E-4, they completed the circling, landing and roving exploration, of which Chang’E-4 was the first landing on the far side of the Moon in human history. Chang’ E-5 was launched in December 2020, bringing back 1731 g of lunar soil samples. Through the detailed analysis of the samples, the scientists understand the history of late lunar volcanism, specifically extending lunar volcanism by about 800 million to 1 billion years, and proposed possible mechanisms. In addition, there are many new understandings of space weathering such as meteorite impacts and solar wind radiation on the Moon. China’s first Mars exploration mission Tianwen-1 was successfully launched in July 2021. Through the study of scientific data, a number of important scientific achievements have been made in the topography, water environment and shallow surface structure of Mars. This paper introduces the main scientific achievements of Chang’E-4, Chang’E-5 and Tianwen-1 in the past two years, excluding technical and engineering contents. Due to the large number of articles involved, this paper only introduces part of the results.

Since the launch in June 2017, Insight-HXMT has been in service smoothly in orbit and particularly productive in 2023 and 2024. Among a total number of 238 papers published so far based on Insight-HXMT data, 63 were published in 2023, and 32 in the early 2024 (till 2024 April), accounting for 40% of the total. These studies cover a variety of scientific subjects including the basic properties of black holes and neutron stars, the outburst of accreting black hole and neutron star X-ray binaries, thermal nuclear burst probes, isolated pulsars, quasi periodical oscillations, cyclotron resonant scattering features, fast radio bursts and gamma-ray bursts, etc. This paper introduces the overall progress with focus on some potential breakthroughs.

Real-time sensing of hot spot temperature in three-core cable joints is of significant importance for studying operation safety of cables， temperature rise， and dynamic load carrying capacity assessment. Therefore， focusing on 10 kV three-core cable joints and considering the variations in structures， materials， and on-site process for different types of joints， the paper constructs a simulation model for cable joint temperature fields and analyzes the temperature field distribution rules of the joints. Moreover， the paper establishes a unified inverse model for axial temperature of conductor based on axial heat flow. By employing single factor variation and orthogonal combination methods， the paper analyzes the impact of material parameter variations on the fitting degree and sensitivity of the axial inverse model for joint conductors. Simulation results demonstrate that the sensitivity coefficient and fitting goodness of the inverse model for axial temperature vary slightly， indicating good robustness for different structural， material， and on-site process variations.

Electrical wiring diagrams， which represent the positions of electrical equipment and describe their wiring and cabling methods， need to be converted into XML for smart grid system scheduling and management. This conversion process is known as vectorization. To address the inefficiencies and time-consuming nature of manual vectorization， this paper proposes a solution for vectorizing electrical wiring diagrams. First， the paper introduces an attention mechanism-enhanced YOLOv3 method for precise recognition and localization of graphic elements in electrical wiring diagrams. Next， it proposes a text region detection algorithm based on multi-scale feature extraction to locate electrical text annotation areas on the diagrams， and uses a CRNN model to recognize their content. Finally， the paper presents a vectorization strategy based on template matching， which analyzes the relationships between electrical elements on the diagrams at the graphic element group level. This method has been practically deployed and can efficiently and accurately complete the vectorization of electrical wiring diagrams， meeting the application needs of power systems.

In response to challenges such as the subtle early fault indications and the fluctuating harmonic content in power systems affecting diagnostic accuracy， this paper presents a novel method for analyzing and diagnosing inter-turn short circuit faults in dry-type air-core reactors， taking into consideration the influence of harmonic voltages. Addressing three distinct operating conditions such as normal reactor operation， early-stage arc-type inter-turn short circuits， and mid-to-late-stage metal fusion-type inter-turn short circuits， the paper analyzes the operational characteristics of both series and parallel reactors under fault conditions to identify specific early fault indicators for inter-turn short circuits in each configuration. Additionally， the paper establishes a simulation model for inter-turn short circuit faults in reactors that accounts for harmonic voltage effects and analyzes the variation in electrical characteristics of series and parallel reactors under various operating conditions. Subsequently， it proposes a diagnostic method based on the current harmonic ratio for series reactor faults and another method based on the active power ratio for parallel reactor faults. To validate the effectiveness of the proposed method， the paper constructs an experimental test platform for inter-turn faults in series and parallel reactors and conducts experiments to confirm its correctness and efficacy.

Bipolar disorder （BD） is a complex mental illness characterized by mood fluctuations， excitability and impaired functioning. Anxiety in BD patients frequently leads to increased clinical symptoms， worse social functioning， and a higher risk of suicide. Current research on BD with anxiety symptom primarily examined clinical characteristics， prevalence and treatment， with limited focus and inconsistent findings on its neuro-biogenetic mechanisms. The findings in this area were also inconsistent. Magnetic resonance imaging （MRI）， known for its non-invasive nature and high resolution， is extensively utilized in investigating disease mechanisms. Consequently， this paper gave a comprehensive review on the progress in brain imaging on BD patients with anxiety symptom， seeking to discern stable changes in brain structure and function， thereby enrich our understanding of the neurobiological etiology of this condition and offer valuable insights for clinical diagnosis and treatment strategies making. This paper covered 14 original studies and synthesized their findings on brain structure and function. Conclusively， the changes of brain functional activities in BD patients with anxiety symptom mainly involve the prefrontal lobe， posterior cingulate cortex， temporal lobe and angular gyrus， while the changes of brain structure mainly involve the left hippocampus and middle frontal gyrus， but the consistency of the research results needs to be enhanced. The research in this field is not sufficient, and more homogeneous clinical samples and larger longitudinal studies are needed to verify and supplement the above results. ［Funded by National Natural Science Foundation of China （number， 82071524）］

With the development of arid and semi-arid regions in China, the hazards posed by collapsible sands to engineering construction have become increasingly significant. In order to investigate the collapsibility regularity and its influencing factors of sand soils, this paper focuses on the wind-blown sands at the southern edge of the Maowusu Desert. Initially, by controlling the single factor laboratory compression tests, the collapsibility regularity of wind-blown sand under different working conditions was investigated. Subsequently, using PFC3D (three-dimensional particle flow software) for numerical simulation of the laboratory compression tests on wind-blown sands, the paper explores the effects of different porosities and particle compositions on the collapsibility of sandy soils. The research results indicate that the collapsibility coefficient of sandy soils shows a trend of first increasing and then decreasing with pressure, reaching its maximum value at 150 kPa. With the increase in dry density or moisture content, the collapsibility coefficient of sand decreases. Compared to moisture content, dry density has a greater impact on the collapsibility of sandy soils. There is a positive correlation between the collapsibility coefficient of wind-blown sand and its porosity. The initial porosity of the collapsibility of the wind-blown sand on the southern edge of the Maowusu Desert is 0.425. When the ratio of particle content between 0.075～0.25 mm and 0.25～0.5 mm is 0.35∶0.65, the collapsibility of sandy soils is maximized. The research results comprehensively describe the entire process of laboratory compression tests on sand from macro to micro levels, revealing the collapsibility regularity and its influencing factors on wind-blown sand from multiple scales. This can provide a reference for engineering construction in the Maowusu Desert and provide certain ideas and basis for the research on particle flow numerical simulation of sand.

Convolutional neural network (CNN) models are widely used in landslide susceptibility assessment due to their powerful feature extraction capabilities, and traditional CNN is no longer able to meet the requirements. Therefore, this paper proposes a multi-scale convolutional neural networks (MSCNN) model that can take into account deep and shallow features. By increasing the depth of the model and expanding the receptive field of samples, the MSCNN can tap deeper and more stable features to improve the reliability of landslide susceptibility assessment in complex scenarios. In this study, Shenzhen City is selected as the research area, and 12 landslide conditioning factors of landslides in Shenzhen City were selected based on systematic and representative principles. A multi-scale convolutional neural network landslide susceptibility assessment model is constructed and compared with methods such as multilayer perceptron (MLP), support vector machine (SVM), and random forest (RF). The results show that the AUC value (0.99) of the MSCNN model constructed in this paper is higher than that of MLP (0.97), SVM (0.91), and RF (0.85), which proves that the proposed MSCNN model has excellent prediction ability. The area of extremely high susceptibility in Shenzhen City is approximately 105.3 km², accounting for 4.98% of the total area of the study area, mainly distributed in Longgang District with steep slopes, sparse vegetation cover, and frequent human engineering activities. Slope, surface roughness, and surface relief are identified as the main conditioning factors affecting landslides in Shenzhen City. The landslide susceptibility mapping implemented in this paper reflects the current distribution of landslide disasters in Shenzhen City, providing data support and key technical support for future landslide disaster prevention and control in Shenzhen City.

This paper presents a preliminary investigation of the instability and landslide of a road subgrade slope that occurred on May 1, 2024 along Mei–Da Expressway. The investigation method is on the basis of past investigation results and findings about instability and landslide of road subgrade slopes in Hong Kong. The Mei–Da Expressway subgrade was constructed by cutting and filling on mountainous slopes. The landslide occurred at a fill slope along a gully. The fill soil was excavated from local soil of completely decomposed granite (CDG). The paper tests the particle size distribution and liquid and plastic limits of the three CDG soil samples that were excavated from adjacent natural slopes. It then examines the stability of the fill slope with a simplified geological slope model. It further investigates the catchments before and after the road construction. It then presents a possible mechanism for the slope instability and landslide. The field observations by others can confirm this mechanism. The cutting and filling of the hillside slopes significantly changed the runoff paths of the three natural catchments above the road. The road can intercept the runoff along the three gullies and direct all the runoff into the fill slope. The large volume of rainfall water can erode and liquefy the fills, which can cause the instability and landslide of the road subgrade slope. There is an urgent need to further investigate this mode of road subgrade instability and landslide since it is not uncommon.

肺叶楔形切除术后围手术期并发急性缺血性卒中的发生率虽然不高，但严重者可导致终身残疾甚至死亡，影响患者预后，其发病机制目前仍不明确。本文报道了2例肺癌手术后并发急性缺血性卒中经介入取栓治疗的病例，病例1行胸腔镜下左肺上叶楔形切除术后当天，左侧大脑中动脉急性栓塞导致左侧大脑半球大面积梗死，经介入取栓治疗血管再通[脑梗死溶栓分级（TICI 3级）后，患者预后良好（NIHSS评分4分）。病例2行胸腔镜下右下肺楔形切除术后当天，基底动脉闭塞导致小脑大面积梗死，经介入取栓治疗后血管再通良好（TICI 3级），但患者术后脑水肿严重，最终放弃治疗。本文通过总结诊疗经验并回顾相关文献，分析肺叶楔形切除术后并发急性缺血性卒中的可能机制，以供临床参考。 Abstract: The incidence of acute ischemic stroke during the perioperative period after wedge resection of pulmonary lobes is not high, but it may lead to life-long disability and even death in severe cases, thus affecting the prognosis of patients. At present, the pathogenesis is still unclear. This paper reported two cases of interventional thrombectomy in patients with acute ischemic stroke after lung cancer surgery. Patient 1 underwent wedge resection of the upper lobe of the left lung under thoracoscope. On the same day, acute embolism of the left middle cerebral artery caused extensive infarction in the left cerebral hemisphere. After interventional thrombectomy and recanalization (TICI grade 3), the patient had a good prognosis (NIHSS score of 4). Patient 2 underwent the right inferior pulmonary wedge resection under thoracoscope. On the same day, basilar artery occlusion caused extensive cerebellar infarction. After interventional thrombectomy, the blood vessels reopened well (TICI grade 3), but the patient had severe postoperative brain edema and ultimately gave up treatment. This paper summarized the experience, reviewed relevant literature and analyzed the high-risk factors for acute ischemic stroke after wedge resection of pulmonary lobes, to provide a reference for clinical practice.

Based on an elaboration of the resource potential and annual production of tight sandstone gas and shale gas in the United States and China, this paper reviews the researches on the distribution of tight sandstone gas and shale gas reservoirs, and analyzes the distribution characteristics and genetic types of tight sandstone gas reservoirs. In the United States, the proportion of tight sandstone gas in the total gas production declined from 20%–35% in 2008 to about 8% in 2023, and the shale gas production was 8 310×108 m3 in 2023, about 80% of the total gas production, in contrast to the range of 5%–17% during 2000–2008. In China, the proportion of tight sandstone gas in the total gas production increased from 16% in 2010 to 28% or higher in 2023. China began to produce shale gas in 2012, with the production reaching 250×108 m3 in 2023, about 11% of the total gas production of the country. The distribution of shale gas reservoirs is continuous. According to the fault presence, fault displacement and gas layer thickness, the continuous shale gas reservoirs can be divided into two types: continuity and intermittency. Most previous studies believed that both tight sandstone gas reservoirs and shale gas reservoirs are continuous, but this paper holds that the distribution of tight sandstone gas reservoirs is not continuous. According to the trap types, tight sandstone gas reservoirs can be divided into lithologic, anticlinal, and synclinal reservoirs. The tight sandstone gas is coal-derived in typical basins in China and Egypt, but oil-type gas in typical basins in the United States and Oman.

In recent years, great breakthroughs have been made in the exploration and development of natural gas in deep coal-rock reservoirs in Junggar, Ordos and other basins in China. In view of the inconsistency between the industrial and academic circles on this new type of unconventional natural gas, this paper defines the concept of “coal-rock gas” on the basis of previous studies, and systematically analyzes its characteristics of occurrence state, transport and storage form, differential accumulation, and development law. Coal-rock gas, geologically unlike coalbed methane in the traditional sense, occurs in both free and adsorbed states, with free state in abundance. It is generated and stored in the same set of rocks through short distance migration, occasionally with the accumulation from other sources. Moreover, coal rock develops cleat fractures, and the free gas accumulates differentially. The coal-rock gas reservoirs deeper than 2000 m are high in pressure, temperature, gas content, gas saturation, and free-gas content. In terms of development, similar to shale gas and tight gas, coal-rock gas can be exploited by natural formation energy after the reservoirs connectivity is improved artificially, that is, the adsorbed gas is desorbed due to pressure drop after the high-potential free gas is recovered, so that the free gas and adsorbed gas are produced in succession for a long term without water drainage for pressure drop. According to buried depth, coal rank, pressure coefficient, reserves scale, reserves abundance and gas well production, the classification criteria and reserves/resources estimation method of coal-rock gas are presented. It is preliminarily estimated that the coal-rock gas in place deeper than 2 000 m in China exceeds 30×1012 m3, indicating an important strategic resource for the country. The Ordos, Sichuan, Junggar and Bohai Bay basins are favorable areas for large-scale enrichment of coal-rock gas. The paper summarizes the technical and management challenges and points out the research directions, laying a foundation for the management, exploration, and development of coal-rock gas in China.

This paper reviews the basic research means for oilfield development and also the researches and tests of enhanced oil recovery (EOR) methods for mature oilfields and continental shale oil development, analyzes the problems of EOR methods, and proposes the relevant research prospects. The basic research means for oilfield development include in-situ acquisition of formation rock/fluid samples and non-destructive testing. The EOR methods for conventional and shale oil development are classified as improved water flooding (e.g. nano-water flooding), chemical flooding (e.g. low-concentration middle-phase micro-emulsion flooding), gas flooding (e.g. micro/nano bubble flooding), thermal recovery (e.g. air injection thermal-aided miscible flooding), and multi-cluster uniform fracturing/water-free fracturing, which are discussed in this paper for their mechanisms, approaches, and key technique researches and field tests. These methods have been studied with remarkable progress, and some achieved ideal results in field tests. Nonetheless, some problems still exist, such as inadequate research on mechanisms, imperfect matching technologies, and incomplete industrial chains. It is proposed to further strengthen the basic researches and expand the field tests, thereby driving the formation, promotion and application of new technologies.

In recent years, with the significant rise in global obesity rate, the demand for sugar substitutes such as artificial sweeteners (AS) has soared, but the safety of AS remains controversial. New research from the World Health Organization (WHO) and the journal Nature suggests that long-term consumption of AS may have negative health effects. Currently, the standards on the use of AS in different countries are different, and the mechanism of the health impact of long-term AS consumption is not clear. Therefore, based on recent research results related to AS, this review paper focuses on the human health effect of AS and the current domestic and foreign standards on AS. It elaborates on the relationship between AS and gut microbes, obesity and diabetes, lipid metabolism, cardiovascular disease and cancer, and summarizes the current Codex Alimentarius Commission (CAC), US, EU, Japanese and Chinese standards on AS. In addition, this paper also discusses the key issue of how to determine standards on AS addition in the food industry in order to provide a reference for future research in this field.

为了促进亚麻籽的开发和利用，基于2013—2023年Web of Science核心合集数据源，采用CiteSpace软件的文献计量分析方法，对亚麻籽相关论文发表数量，主要发文国家、机构和作者，关键词共现，文献共被引进行了可视化分析，基于此归纳出亚麻籽的研究热点，并提出研究趋势。结果表明：2013—2023年，亚麻籽领域的年发表论文数量和被引频次总体均呈现先上升后下降的趋势；中国、印度和加拿大等国家发表论文数量最多；埃及知识库、加拿大农业与农业食品部和中国农业科学院等是主要的研究机构；邓乾春是该领域发表论文数量最多的作者，其次是Boaventura和Reaney；大多数研究集中在亚麻籽油、脂肪酸、亚麻籽油的质量和性能等方面。近年来，亚麻籽活性成分的研究以及功能性食品、药物、生物材料等开发成为新的热点。未来几年可以从亚麻籽在医药与保健品、化工和化妆品等领域中的应用，亚麻籽的安全性研究，亚麻籽产品质量稳定方面的研究，亚麻籽种质资源和种植的研究等进行深入探索。In order to promote the development and use of flaxseed, based on the data source of Web of Science Core Collection during 2013-2023, the bibliometric analysis method of CiteSpace software was used to analyze the number of publications, major issuing countries, institutions and authors, keyword co-occurrence, and literature co-citation of papers related to flaxseed were visualized and analyzed, based on this, the research hotspots of flaxseed were summarized, and the trends were analyzed. The results showed that from 2013 to 2023, the annual number of papers and citation frequency in the field of flaxseed showed an increasing and then decreasing trend overall.China, India, and Canada were the countries with the most published papers. Egyptian Knowledge Bank, Agriculture & Agric Food Canada, and Chinese Academy of Agricultural Sciences were the major research institutions. Deng Qianchun was the author with the most published papers in this field, followed by Boaventura and Reaney. Most of the studies focused on flaxseed oil, fatty acids, quality and properties of flaxseed oil. In recent years, the study of active components of flaxseed and the development of functional foods, drugs and biomaterials have become new hotspots.The research in the next few years can be explored in depth from the application of flaxseed in the fields of medicine, health product, chemical industry, cosmetics and other fields, the safety of flaxseed, the stabilization of the quality of the product of flaxseed, the germplasm resources and cultivation of flaxseed.

【Objective】To improve the linear fit between the reflected spectral center wavelength and external environmental variables in Fiber Bragg Grating (FBG) sensing system, this paper proposes to use particle swarm optimization of Gaussian process regression model to the field of FBG stress sensing.【Methods】For the reflectance spectral characteristics of the FBG, the paper studies the impact of the linear fit in the spectral fitting of FBG sensing system. The particle swarm algorithm is used to search for the optimal hyperparameters in the Gaussian process regression model in order to enhance the predictive performance of the reflectance spectral wavelength of the center. A FBG stress sensing experimental platform was built, and the FBG was laid on the strength beam. Different weights were applied to one end of the equal strength beam to produce axial strain on the FBG, and the reflectance spectral data were collected by the spectrometer and analyzed by linear fitting with the studied model. The results obtained by the unoptimized Gaussian process regression model, the maximum value method, the Gaussian fitting method, and the center of mass method were used as the control group.【Results】The results show that under the conditions of erbium-doped fiber amplifier output power of 10 dBm, transmission fiber distance of 50 m, and the number of sampling points of the spectrometer of 501, the linear fit between the reflected spectral center wavelength and the mass of the weights is better than that of the control group. The linear fit of the studied model can reach up to 0.951 9, which is improved compared with that of the control group. Under the conditions of 501, 251, 167 and 126 spectral sampling points, the studied model can improve the linear fit of the system to 0.990 0, which is a maximum improvement of 0.258 7 compared with the maximum value method.【Conclusion】The analysis results show that the Gaussian process regression model optimized by the particle swarm is able to effectively improve the linear fit of the FBG stress sensing system.

【Objective】The optical communication system working at the traditional telecommunication band is faced with "capacity crunch" with the rapidly development of optical communication technology. The acceptable loss of 0.2 dB/km (@2 μm) from the hollow-core photonic bandgap fibers as well as the high optical amplification gains (30 dB@2 μm) of thulium-doped fiber amplifiers (CTFA type) provides the potential for the 2 μm wavelength band to alleviate the communication "capacity crunch". As a result, the needs of the 2 μm silicon-based photodetectors is also raised due to its mature and convenient manufacture process. The main solutions of the silicon-based photodetectors include the usage of Ⅲ-Ⅴ compounds with tunable band gap, the introduction of low band gap width materials as absorption regions, the use of new absorption mechanism in optical absorbed material at the 2 μm wavelength band and so on. The Ge material has a high Two Photon Absorption (TPA) coefficient (1 225 GW/cm@2 μm). And the Ge-on-Silicon-On-Insulator (SOI) photodetector is an excellent method to realize 2 μm optical signal detection, which is compatible with the standard silicon photonics device manufacturing process that has the advantages of low production difficulty and cost. The purpose of this paper is to verify the feasibility of the Ge-on-SOI photodetector to achieve 2 μm wavelength band photoelectric detection by using the special optical absorption mechanism of TPA.【Methods】In this paper, the photoelectric detection at the 2 μm wavelength band based on the physical absorption mechanism of current generated from high TPA of Ge material is realized. The quantification of the photocurrent generated by Ge material through TPA effect is analyzed and discussed in this paper. In the experimental test, we first apply a high power 2 μm wavelength band input light source magnified by thulium-doped fiber amplifiers to the input port (grating coupler) of the commercial waveguide-type Ge-on-SOI photodetector in the on-chip active silicon photonics device test system. Then we adjust the alignment of the optical fiber with the grating coupler and the input light polarization to reduce the optical transmission loss from the input optical fiber to the Ge absorption region. Finally, the TPA photocurrent of the on-chip photodetector is obtained by a probe.【Results】A net photogenerated current up to 651 nA and an estimated value of responsivity greater than 10 mA/W is obtained experimentally under a 2 μm wavelength optical input power of 21.9 dBm.【Conclusion】The work of this paper verifies the scientific feasibility of 2 μm waveband photodetector through the TPA effect of Ge material, and provides experimentally support for the design of the 2 μm wavelength band Ge-on-SOI photodetector based on TPA.

【Objective】The significance of wireless network equipment troubleshooting can be used to solve the network connection problems, improving user experience, and maintaining network stability and reliability. However, the accuracy of existing methods needs to be further improved.【Methods】To address this problem, this paper quotes the attention mechanism in the Convolutional Neural Networks(CNN)- Gated Recurrent Unit (GRU) network structure and proposes a wireless network equipment fault diagnosis method based on the CNN-GRU-Attention network structure.【Results】Compared with other methods in the simulation experiment, the method in this paper improved the accuracy of the model from 91% to 98%.【Conclusion】Through the research of this article, the quality and efficiency of wireless network equipment operation have been improved. The network capacity, functionality and reliability have also been improved, and people's growing communication needs for wireless networks have been met.

【Objective】The baseline drift of the Fiber Bragg Grating (FBG) spectral signal is usually one of the main problems, caused by the complex external environment. A spectral baseline correction method based on the improved Long Short Term Memory (LSTM) model is proposed in this paper.【Methods】Compared with LSTM model, the improved LSTM model extracts feature information of FBG spectral signal by the Convolutional Neural Network (CNN). The improved LSTM model is composed of CNN, full connection, and LSTM network. In this paper, the improved LSTM model is trained by artificial datasets and measured datasets. The artificial datasets are made up of feature noise, baseline, and FBG spectroscopy. Five methods including wavelet soft threshold method, penalty least square method, Recurrent Neural Network (RNN), LSTM, and the improved LSTM model are used as baseline correction. Identification signal probability and Root Mean Square Error (RMSE) are used to evaluate correction results by the five methods.【Results】The artificial datasets of FBG signal are corrected by the improved LSTM model, and the identification signal probability is increased by 60.8%. The improved LSTM model with training by artificial datasets and measured datasets shows better correction results, compared with training by measured datasets. The mean of the RMSE for FBG spectrum decreases by 10.95%. The standard deviation of RMSE decreases by 4%. The measured datasets of FBG signal are corrected by the improved LSTM model, and the identification signal probability is increased by 50.5%. Compared with wavelet soft threshold method, penalty least square method, RNN and LSTM, the improved LSTM model shows best correction results. The mean values of RMSE and the standard deviation of RMSE are 0.012 2 and 0.002 4, respectively. The RMSE value of the demodulated central wavelength is 0.036 pm. And the baseline correction process takes only 9.68 ms.【Conclusion】The improved LSTM model is an effective method to achieve baseline correction, and has wide range of application prospects in complex external environment.

Selenium-enriched edible fungi are rich in selenium polysaccharides, selenoproteins, selenium polypeptides and other bioactive components. However, the selenium forms and organic selenium transformation rate of selenium-enriched edible fungi are affected by several factors, such as species, selenium biotransformation methods and cultivation techniques. Subsequently, edible fungi show different biological activities and mechanisms of action. Therefore, it is particularly important to study the forms, distribution, absorption and transformation of selenium in edible fungi. The paper reviews the proportion of different forms of selenium in total selenium, the process of absorption and transformation of different selenium forms, the threshold of total selenium, the present selenium-enriched technology and the industrial problems of representative selenium-enriched edible fungi. The immunological activity, antitumor activity and antioxidant activity of different selenium forms in selenium-enriched edible fungi are also discussed in this paper. This review is expected to provide a reference basis for the precise selenium enrichment of edible fungi, to serve as a scientific support for the development of highly active different forms of selenium, and to propose directions for the development of selenium-enriched edible fungi.

Polygonatum sibiricum, a plant homologous to both medicine and food, is of significant importance. Its primary active components include polysaccharides, saponin, flavonoids, polyphenols, and alkaloids. These constituents are known for their roles in enhancing immune function, combating fatigue, providing anti-oxidative benefits, reducing blood sugar, and offering anti-inflammatory effects. Consequently, P. sibiricum presents wide-ranging prospects in health food and pharmaceutical research and development. This paper provides a comprehensive summary of research advancements in the polysaccharides, flavonoids, saponins, and solomonseal rhizome extract of P. sibiricum, particularly in metabolic regulation. It delves into the mechanisms by which the main active substances of P. sibiricum influence glucose and lipid metabolism. Simultaneously, the paper analyzes current patents and the state of industrial development related to P. sibiricum, aiming to provide a reference for future research and development of metabolic regulation functional products based on this plant.

Ultra-wideband through-wall radar, leveraging its ability to penetrate walls, can be used together with Multiple-Input Multiple-Output (MIMO) technology to image hidden targets behind walls. This approach provides rich information for detecting and locating people within buildings. This paper introduces a closed-loop interferometric calibration method based on a multitransmitter multireceiver ultrawideband wall-penetrating radar system in the Frequency Modulated Continuous Wave (FMCW) regime. This method aims to correct scattering issues caused by internal system errors. The presence of walls causes the target imaging position to deviate from the real position. To address this, this paper derives a three-Dimensional (3D) wall compensation algorithm jointing channels and pixel points. Then, a fast refocusing algorithm is proposed based on the geometric properties of the imaging area. The first step involves removing the influence of walls on delay time and determining the presence of the target. Subsequently, in view of the geometric properties of the region, a spherical coordinate grid division adapted to the region shape is selected. Localized refocusing is then performed in the subregion. This avoids the issue of electromagnetic wave attenuation, causing strong targets to mask weak ones in the imaging results. At the same time, the adoption of spherical coordinates for gridding and localized imaging greatly reduces the overall time consumption by the algorithm. Through simulation analysis and experimental verification, the proposed calibration method can effectively compensate for system errors. The fast refocusing algorithm can be used to realize multitarget 3D localization of the human body behind walls, with the localization accuracy of each dimension surpassing 10 cm and computational speeds improving by five times compared with those of existing algorithms. In terms of target detection probability, the proposed algorithm consistently identifies weak targets that other algorithms may overlook.

Non-Line-Of-Sight (NLOS) 3D imaging radar is an emerging technology that utilizes multipath scattering echoes to detect hidden targets. However, this technology faces challenges such as the separation of multipath echoes, reduction of aperture occlusion, and phase errors of reflective surfaces, which hinder the high-precision imaging of hidden targets when using traditional Line-Of-Sight (LOS) radar imaging methods. To address these challenges, this paper proposes a precise imaging method for NLOS hidden targets based on Sparse Iterative Reconstruction (NSIR). In this method, we first establish a multipath signal model for NLOS millimeter-wave 3D imaging radar. By exploiting the characteristics of LOS/NLOS echoes, we extract the multipath echoes from hidden targets using a model-driven approach to realize the separation of LOS/NLOS echo signals. Second, we formulate a total variation multiconstraint optimization problem for reconstructing hidden targets, integrating multipath reflective surface phase errors. Using the split Bregman Total Variation (TV) regularization operator and the phase error estimation criterion based on the minimum mean square error, we jointly solve the multiconstraint optimization problem. This approach facilitates precise imaging and contour reconstruction of NLOS targets. Finally, we construct a planar scanning 3D imaging radar experimental platform and conduct experimental verification of targets such as knives and iron racks in a corner NLOS scenario. Results validate the capability of NLOS millimeter-wave 3D imaging radar in detecting hidden targets and the effectiveness of the method proposed in this paper.

Aiming at the problem of error in deep-sea DOA(Direction of Arrival, DOA) estimation based on plane wave sound field model, this paper establishes the array signal model of deep-sea DOA estimation under multipath channel based on ray theory. The characterization method of deep-sea multipath ray propagation time and adjacent array element ray propagation delay difference are also derived. Compared with the propagation delay difference expression of adjacent array elements in the traditional plane wave model, the propagation delay difference expression of adjacent array elements derived in this paper is more universal. Combined with the decoherence DOA estimation algorithm, the performance of deep-sea DOA estimation is improved, and the effectiveness of the algorithm is verified by simulation. The research shows that the time delay difference between adjacent array elements is not only related to the distance between array elements and the target azimuth, but also related to the depth of the sound source and the horizontal distance from the sound source to each array element. The construction of the steering vector in DOA estimation should consider the influence of these factors. At this time, DOA estimation is a multi-dimensional parameter optimization problem. Fully considering the acoustic propagation characteristics of the ocean sound field can fundamentally solve the error problem of deep-sea DOA estimation.