Mechanism,prevention,and control of mining-induced dynamic disasters in underground metal mines in China:Challenges and solutions

Metal mineral resources play an indispensable role in the development of the national economy.Dynamic disasters in underground metal mines seriously threaten mining safety,which are major scientific and technological problems to be solved urgently.In this article,the occurrence status and grand challenges of some typical dynamic disasters involving roof falling,spalling,collapse,large deformation,rockburst,surface subsidence,and water inrush in metal mines in China are systematically presented,the characteristics of mining-induced dynamic disasters are analyzed,the examples of dynamic disasters occurring in some metal mines in China are summarized,the occurrence mechanism,monitoring and early warning methods,and prevention and control techniques of these disasters are highlighted,and some new opinions,suggestions,and solutions are proposed simultaneously.Moreover,some shortcomings in current disaster research are pointed out,and the direction of efforts to improve the prevention and control level of dynamic disasters in China’s metal mines in the future is prospected.The integration of forward-looking key innovative theories and technologies in the abovementioned aspects will greatly enhance the cognitive level of disaster prevention and mitigation in China’s metal mining industry and achieve a significant shift from passive disaster relief to active disaster prevention.

Practice of Infection Prevention and Control Strategies in Risk Departments during the COVID-19 Epidemic

Objective: To explore the practice and application of infection prevention and control strategies in risk departments during the COVID-19 epidemic, and to formulate the infection prevention and control measures to provide advice and guidance in risk departments. Methods: According to the latest plan of diagnosis and treatment, prevention and control issued by the National Health Commission, expert advice and consensus, combined with the actual situation in our hospital, a series of infection prevention and control measures of COVID-19 in risk department was formulated. Results: During the epidemic period, the prevention and control measures of nine risk departments including emergency operation, anesthesiology, endoscopy center, blood purification center, otolaryngology, stomatology, medical imaging department, medical cosmetology department and pulmonary function room were established from six aspects, including pre-examination and screening, medical technology control, personnel management, personal protection, environmental disinfection, medical waste disposal, etc. Conclusion: During the epidemic period, the infection prevention and control strategy of risk departments is one of the key links to control the spread of the epidemic, and risk departments must pay attention to and strictly implement various infection prevention and control measures.

Prevention and Control Strategies of Nosocomial Infection and Effectiveness Evaluation in a Tertiary Teaching Hospital during the Epidemic of COVID-19

Objective: To evaluate the role of prevention and control strategies for nosocomial infection in a tertiary teaching hospital during the sudden outbreak of Corona Virus Disease 2019 (COVID-19). Methods: The hospital initiated an emergency plan involving multi-departmental defense and control. It adopted a series of nosocomial infection prevention and control measures, including strengthening pre-examination and triage, optimizing the consultation process, improving the hospital’s architectural composition, implementing graded risk management, enhancing personal protection, and implementing staff training and supervision. Descriptive research was used to evaluate the short-term effects of these in-hospital prevention and control strategies. The analysis compared changes in related evaluation indicators between January 24, 2020 and February 12, 2020 (Chinese Lunar New Year’s Eve 2020 to lunar January 19) and the corresponding lunar period of the previous year. Results: Compared to the same period last year, the outpatient fever rate increased by 1.85-fold (P P Conclusion: The nosocomial infection prevention and control strategies implemented during this specific period improved the detection and control abilities for the COVID-19 source of infection and enhanced the compliance with measures. This likely contributed significantly to avoiding the occurrence of nosocomial infection.

Infection control and prevention in burn victims:The role of nurses

Burn injury is a major public health concern,with an estimated 180,000 deaths each year associated with burn-related infections.The majority of these occur in low-and middle-income countries,and almost two-thirds occur in the World Health Organization African and South-East Asia Regions.There is a risk of an escalation of burn injury site infections if nurses who are directly involved in burn care do not develop a mechanism to mitigate this risk in the coming years.Hence,this study aims at explaining what burn injuries are and how nurses can prevent the occurrence of infection among burn victims.This review analyzed published studies using keywords such as burn injury,infection in burn patients,and nurses’involvement in infection prevention and control(IPC)on search engines such as PubMed,Science Direct,and Google Scholar.The literature was retrieved and reviewed for eligibility to capture just the variables indicated in this seminar objective;the date range chosen in the literature search was from 2015 to 2023.The study found that many patients die from burn injuries as a result of exposure to infection and most nurses are not adequately informed about infection control.The study also found that nurses’responsibilities include proper hand hygiene,wound care,the use of personal protective equipment,antibiotic medication,cleaning the patient’s surroundings,and preventing patient cross-contamination.Burn injuries pose a significant risk to patients,necessitating infection control and prevention.Therefore,nurses in burn units should be informed on IPC practices and also educate patients,families,and coworkers on their importance.

Technical Points of Green Prevention and Control Technology of Major Diseases and Pests in Lixian Rhubarb(Rheum palmatum L.)

Based on different types of diseases,pests and weeds in the whole growth period of rhubarb(sowing period-harvesting period),the corresponding green prevention and control technology is proposed,aiming to further reduce the application amount of pesticides and fertilizers in the production of medicinal sources of Lixian rhubarb during the"14 th Five-Year Plan"period.The results will provide a theoretical basis for increasing the promotion and application of agricultural prevention and control(including disease-resistant varieties,ecological regulation),physical prevention and control,biological prevention and control measures,thus ensuring effective protection of the ecological environment,green,healthy and sustainable development of traditional Chinese medicine agriculture in Longnan,and source quality of authentic medicinal materials.

Major Diseases and Pests of Blueberry in Guizhou Province and Progress in Their Prevention and Control

As the blueberry industry continues to evolve,the effective control of its diseases and pests has become an essential component of local agricultural development.This paper provides a comprehensive overview of the principal types of blueberry diseases and pests in Guizhou Province,along with the corresponding control measures,in order to serve as a valuable reference for blueberry growers.

Comprehensive Prevention and Control Technology of Vegetable Diseases and Pests in Shandong Province

An in-depth research and practice has been conducted on vegetable diseases and pests in Shandong Province,and the principles of comprehensive and ecological control of diseases and pests are put forward,including agricultural control measures such as crop rotation,field cleaning,fertilizer and water management,physical control measures such as catching and killing,trapping,blocking,photoelectric energy treatment,biological control measures such as the use of natural enemies,pathogenic microorganisms,other beneficial organisms and metabolites,and scientific and rational chemical control measures.Comprehensive prevention and control not only controls vegetable diseases and pests effectively,but also protects the ecological environment.

Establishment and Application of Prevention and Control Techniques of New Sugarcane White Leaf Disease

Aiming at the basic and key technical problems in prevention and control of sugarcane white leaf disease(SCWL),this study systematically overcame key technical bottleneck of prevention and control of new SCWL after 10 years of collaborative research,and achieved several innovative achievements.SCWL phytoplasmas newly recorded in China and the new subgroup of SCWL phytoplasmas(16SrXI-D)were discovered for the first time in Yunnan,and the whole genome analysis of the epidemic subgroup was completed.The main transmission source of SCWL pathogens has been identified as infected seed canes,and Tettigoniella viridis and Clovia conifer were newly discovered as vectors for virus transmission.The disease resistance of 25 main varieties was identified,and 10 control varieties were selected.The prevention and control strategy of"emphasizing early warning,strictly carrying out quarantine,blocking the vectors and controlling residual plants"was put forward,and a comprehensive prevention technique was established through integration of various techniques,and standardized technical regulations were formulated for demonstration application.The promotion and application of these achievements have realized scientific prevention and control of SCWL,effectively curbed the spread of SCWL,and ensured the safety of sugarcane producing areas in China,achieving great economic,social and ecological benefits and providing technical support for high-quality development,loss reduction and efficiency improvement of China's sugar industry.

The Research on the Paths of Popular Science Education about Myopia Prevention and Control among College Students in the Context of Shifting the Focus Forward

Currently, the number of myopic people in China has reached as high as 600 million, and it shows a trend of “early onset, high incidence, and a high degree of severity”. The issue of myopia among children and adolescents has attracted widespread attention from all sectors of society. Comprehensive myopia prevention and control efforts have been launched nationwide. Popular science education, vision screening, and improving visual environments are effective measures for preventing myopia. However, among the target audience for comprehensive myopia prevention and control, the preschool children group has been neglected, and the work of myopia prevention and control for this group has been significantly weakened and marginalized. Due to insufficient awareness of prevention and control, the hyperopia reserve in the preschool children group is being continuously depleted, leading to the early onset of myopia. In light of this situation, the focus of myopia prevention and control needs to shift forward, and it is worth exploring and pondering how college students with a background in optometry can develop entertaining and engaging popular science education materials and methods.

Internal Control Management and Risk Prevention Measures of State-Owned Enterprises

As an important pillar of national economic development,state-owned enterprises,their operational efficiency,and risk management ability are directly related to the stability and security of the national economy.As an important part of enterprise management,internal control management plays an irreplaceable role.Especially in the current domestic and international economic situation is complex and changeable,market competition is increasingly fierce environment,to strengthen the internal control management of state-owned enterprises and risk prevention measures is particularly important.This paper starts with the importance of internal control management and risk prevention for state-owned enterprises,and analyzes the problems and strategies in the internal control management and risk prevention of state-owned enterprises,in order to build a more comprehensive and efficient risk management system for state-owned enterprises to adapt to the ever-changing market environment and realize sustainable development.

Urban Traffic Control Meets Decision Recommendation System:A Survey and Perspective

Urban traffic control is a multifaceted and demanding task that necessitates extensive decision-making to ensure the safety and efficiency of urban transportation systems.Traditional approaches require traffic signal professionals to manually intervene on traffic control devices at the intersection level,utilizing their knowledge and expertise.However,this process is cumbersome,labor-intensive,and cannot be applied on a large network scale.Recent studies have begun to explore the applicability of recommendation system for urban traffic control,which offer increased control efficiency and scalability.Such a decision recommendation system is complex,with various interdependent components,but a systematic literature review has not yet been conducted.In this work,we present an up-to-date survey that elucidates all the detailed components of a recommendation system for urban traffic control,demonstrates the utility and efficacy of such a system in the real world using data and knowledgedriven approaches,and discusses the current challenges and potential future directions of this field.

Traffic Control Based on Integrated Kalman Filtering and Adaptive Quantized Q-Learning Framework for Internet of Vehicles

Intelligent traffic control requires accurate estimation of the road states and incorporation of adaptive or dynamically adjusted intelligent algorithms for making the decision.In this article,these issues are handled by proposing a novel framework for traffic control using vehicular communications and Internet of Things data.The framework integrates Kalman filtering and Q-learning.Unlike smoothing Kalman filtering,our data fusion Kalman filter incorporates a process-aware model which makes it superior in terms of the prediction error.Unlike traditional Q-learning,our Q-learning algorithm enables adaptive state quantization by changing the threshold of separating low traffic from high traffic on the road according to the maximum number of vehicles in the junction roads.For evaluation,the model has been simulated on a single intersection consisting of four roads:east,west,north,and south.A comparison of the developed adaptive quantized Q-learning(AQQL)framework with state-of-the-art and greedy approaches shows the superiority of AQQL with an improvement percentage in terms of the released number of vehicles of AQQL is 5%over the greedy approach and 340%over the state-of-the-art approach.Hence,AQQL provides an effective traffic control that can be applied in today’s intelligent traffic system.

Identification of Early Warning Signals of Infectious Diseases in Hospitals by Integrating Clinical Treatment and Disease Prevention

The global incidence of infectious diseases has increased in recent years,posing a significant threat to human health.Hospitals typically serve as frontline institutions for detecting infectious diseases.However,accurately identifying warning signals of infectious diseases in a timely manner,especially emerging infectious diseases,can be challenging.Consequently,there is a pressing need to integrate treatment and disease prevention data to conduct comprehensive analyses aimed at preventing and controlling infectious diseases within hospitals.This paper examines the role of medical data in the early identification of infectious diseases,explores early warning technologies for infectious disease recognition,and assesses monitoring and early warning mechanisms for infectious diseases.We propose that hospitals adopt novel multidimensional early warning technologies to mine and analyze medical data from various systems,in compliance with national strategies to integrate clinical treatment and disease prevention.Furthermore,hospitals should establish institution-specific,clinical-based early warning models for infectious diseases to actively monitor early signals and enhance preparedness for infectious disease prevention and control.

Audio-Text Multimodal Speech Recognition via Dual-Tower Architecture for Mandarin Air Traffic Control Communications

In air traffic control communications (ATCC), misunderstandings between pilots and controllers could result in fatal aviation accidents. Fortunately, advanced automatic speech recognition technology has emerged as a promising means of preventing miscommunications and enhancing aviation safety. However, most existing speech recognition methods merely incorporate external language models on the decoder side, leading to insufficient semantic alignment between speech and text modalities during the encoding phase. Furthermore, it is challenging to model acoustic context dependencies over long distances due to the longer speech sequences than text, especially for the extended ATCC data. To address these issues, we propose a speech-text multimodal dual-tower architecture for speech recognition. It employs cross-modal interactions to achieve close semantic alignment during the encoding stage and strengthen its capabilities in modeling auditory long-distance context dependencies. In addition, a two-stage training strategy is elaborately devised to derive semantics-aware acoustic representations effectively. The first stage focuses on pre-training the speech-text multimodal encoding module to enhance inter-modal semantic alignment and aural long-distance context dependencies. The second stage fine-tunes the entire network to bridge the input modality variation gap between the training and inference phases and boost generalization performance. Extensive experiments demonstrate the effectiveness of the proposed speech-text multimodal speech recognition method on the ATCC and AISHELL-1 datasets. It reduces the character error rate to 6.54% and 8.73%, respectively, and exhibits substantial performance gains of 28.76% and 23.82% compared with the best baseline model. The case studies indicate that the obtained semantics-aware acoustic representations aid in accurately recognizing terms with similar pronunciations but distinctive semantics. The research provides a novel modeling paradigm for semantics-aware speech recognition in air traffic control communications, which could contribute to the advancement of intelligent and efficient aviation safety management.

Regional Multi-Agent Cooperative Reinforcement Learning for City-Level Traffic Grid Signal Control

This article studies the effective traffic signal control problem of multiple intersections in a city-level traffic system.A novel regional multi-agent cooperative reinforcement learning algorithm called RegionSTLight is proposed to improve the traffic efficiency.Firstly a regional multi-agent Q-learning framework is proposed,which can equivalently decompose the global Q value of the traffic system into the local values of several regions Based on the framework and the idea of human-machine cooperation,a dynamic zoning method is designed to divide the traffic network into several strong-coupled regions according to realtime traffic flow densities.In order to achieve better cooperation inside each region,a lightweight spatio-temporal fusion feature extraction network is designed.The experiments in synthetic real-world and city-level scenarios show that the proposed RegionS TLight converges more quickly,is more stable,and obtains better asymptotic performance compared to state-of-theart models.

Transient Stability Preventive Control of Wind Farm Connected Power System Considering the Uncertainty

To address uncertainty as well as transient stability constraints simultaneously in the preventive control of windfarm systems, a novel three-stage optimization strategy is established in this paper. In the first stage, the probabilisticmulti-objective particle swarm optimization based on the point estimate method is employed to cope with thestochastic factors. The transient security region of the system is accurately ensured by the interior point methodin the second stage. Finally, the verification of the final optimal objectives and satisfied constraints are enforcedin the last stage. Furthermore, the proposed strategy is a general framework that can combine other optimizationalgorithms. The proposed methodology is tested on the modified WSCC 9-bus system and the New England 39-bussystem. The results verify the feasibility of the method.

Cluster DetectionMethod of Endogenous Security Abnormal Attack Behavior in Air Traffic Control Network

In order to enhance the accuracy of Air Traffic Control(ATC)cybersecurity attack detection,in this paper,a new clustering detection method is designed for air traffic control network security attacks.The feature set for ATC cybersecurity attacks is constructed by setting the feature states,adding recursive features,and determining the feature criticality.The expected information gain and entropy of the feature data are computed to determine the information gain of the feature data and reduce the interference of similar feature data.An autoencoder is introduced into the AI(artificial intelligence)algorithm to encode and decode the characteristics of ATC network security attack behavior to reduce the dimensionality of the ATC network security attack behavior data.Based on the above processing,an unsupervised learning algorithm for clustering detection of ATC network security attacks is designed.First,determine the distance between the clustering clusters of ATC network security attack behavior characteristics,calculate the clustering threshold,and construct the initial clustering center.Then,the new average value of all feature objects in each cluster is recalculated as the new cluster center.Second,it traverses all objects in a cluster of ATC network security attack behavior feature data.Finally,the cluster detection of ATC network security attack behavior is completed by the computation of objective functions.The experiment took three groups of experimental attack behavior data sets as the test object,and took the detection rate,false detection rate and recall rate as the test indicators,and selected three similar methods for comparative test.The experimental results show that the detection rate of this method is about 98%,the false positive rate is below 1%,and the recall rate is above 97%.Research shows that this method can improve the detection performance of security attacks in air traffic control network.

Traditional Chinese medicine for acute mountain sickness prevention: A systematic review and meta-analysis of randomized controlled trials

Objective: To evaluate the efficacy of traditional Chinese medicine(TCM) for preventing acute mountain sickness(AMS).Methods: We included randomized controlled trials(RCTs) which evalueded the effect of TCM for preventing AMS, compared with a placebo, no treatment or acetazolamide. The literature was searched in 6major databases. RevMan 5.4 software was used for the meta-analysis. The relative risk for discrete variables and the mean difference for continuous variables with 95% confidence intervals(CIs) were applied to express the effect size. The risk of bias in the included studies was evaluated using the Cochrane risk assessment tool 2.0(RoB 2.0), and the evidence certainty was assessed using the Grading of Recommendations Assessment and the Development and Evaluation(GRADE) approach.Results: Twenty RCTs involving 3015 participants and 16 TCM patent drugs were included. The overall risk of bias in the majority of studies(15/20) was of some concerns. In terms of the AMS incidence,Rhodiola rosea(R. rosea, Hong Jing Tian) and Ginkgo biloba(G. biloba, Yin Xing Ye) were equivalent to the placebo/no treatment [RR(95% CI): 0.66(0.43-1.01), 0.82(0.63-1.06), respectively]. The AMS incidence in the G. biloba group was higher than that in the acetazolamide group [RR(95% CI): 2.92(1.69-5.06)]. In terms of improving the AMS symptom score on days 1 and 3 in the plateau, R. rosea and G. biloba were superior to the placebo or no treatment [MD(95% CI):-0.98(-1.71,-0.25),-2.05(-3.14,-0.95), respectively]. The other 14 Chinese patent medicines were evaluated in a single trial, and the majority of the results were negative. The subgroup analysis showed that the effect of R. rosea was related to the intervention time, way of ascending, and altitude.Conclusion: R. rosea and G. biloba were effective in improving AMS symptoms but had no effect in reducing the AMS incidence. There was insufficient evidence to support the use of other TCM patent drugs to prevent AMS. More randomized double-blind placebo-controlled trials are warranted to evaluate and screen effective Chinese patent medicines for AMS prevention.

Occurrence Characteristics and Prevention and Control Measures of Spodoptera frugiperda in Maize

Based on practical work experience,this paper analyzed the occurrence characteristics and control measures of Spodoptera frugiperda in maize.The measures including forecasting and early warning,regional prevention and control,agricultural prevention and control,physical prevention and control,chemical prevention and control,and biological prevention and control can effectively control the damage of S.frugiperda and guarantee the safety of food production.The results will provide some reference for the prevention and control of S.frugiperda.

Overview of Occurrence,Prevention and Control of Panonychus citri in China

In order to further promote the prevention and control research of Panonychus citri and improve its control effect,this paper summarizes the main influencing factors of the outbreak,main control technology and drug resistance of P.citri,and puts forward the research focus and control strategy.