In recent times,various power control and clustering approaches have been proposed to enhance overall performance for cell-free massive multipleinput multiple-output(CF-mMIMO)networks.With the emergence of deep reinfo...In recent times,various power control and clustering approaches have been proposed to enhance overall performance for cell-free massive multipleinput multiple-output(CF-mMIMO)networks.With the emergence of deep reinforcement learning(DRL),significant progress has been made in the field of network optimization as DRL holds great promise for improving network performance and efficiency.In this work,our focus delves into the intricate challenge of joint cooperation clustering and downlink power control within CF-mMIMO networks.Leveraging the potent deep deterministic policy gradient(DDPG)algorithm,our objective is to maximize the proportional fairness(PF)for user rates,thereby aiming to achieve optimal network performance and resource utilization.Moreover,we harness the concept of“divide and conquer”strategy,introducing two innovative methods termed alternating DDPG(A-DDPG)and hierarchical DDPG(H-DDPG).These approaches aim to decompose the intricate joint optimization problem into more manageable sub-problems,thereby facilitating a more efficient resolution process.Our findings unequivo-cally showcase the superior efficacy of our proposed DDPG approach over the baseline schemes in both clustering and downlink power control.Furthermore,the A-DDPG and H-DDPG obtain higher performance gain than DDPG with lower computational complexity.展开更多
Organizations are adopting the Bring Your Own Device(BYOD)concept to enhance productivity and reduce expenses.However,this trend introduces security challenges,such as unauthorized access.Traditional access control sy...Organizations are adopting the Bring Your Own Device(BYOD)concept to enhance productivity and reduce expenses.However,this trend introduces security challenges,such as unauthorized access.Traditional access control systems,such as Attribute-Based Access Control(ABAC)and Role-Based Access Control(RBAC),are limited in their ability to enforce access decisions due to the variability and dynamism of attributes related to users and resources.This paper proposes a method for enforcing access decisions that is adaptable and dynamic,based on multilayer hybrid deep learning techniques,particularly the Tabular Deep Neural Network Tabular DNN method.This technique transforms all input attributes in an access request into a binary classification(allow or deny)using multiple layers,ensuring accurate and efficient access decision-making.The proposed solution was evaluated using the Kaggle Amazon access control policy dataset and demonstrated its effectiveness by achieving a 94%accuracy rate.Additionally,the proposed solution enhances the implementation of access decisions based on a variety of resource and user attributes while ensuring privacy through indirect communication with the Policy Administration Point(PAP).This solution significantly improves the flexibility of access control systems,making themmore dynamic and adaptable to the evolving needs ofmodern organizations.Furthermore,it offers a scalable approach to manage the complexities associated with the BYOD environment,providing a robust framework for secure and efficient access management.展开更多
Smart grids and their technologies transform the traditional electric grids to assure safe,secure,cost-effective,and reliable power transmission.Non-linear phenomena in power systems,such as voltage collapse and oscil...Smart grids and their technologies transform the traditional electric grids to assure safe,secure,cost-effective,and reliable power transmission.Non-linear phenomena in power systems,such as voltage collapse and oscillatory phenomena,can be investigated by chaos theory.Recently,renewable energy resources,such as wind turbines,and solar photovoltaic(PV)arrays,have been widely used for electric power generation.The design of the controller for the direct Current(DC)converter in a PV system is performed based on the linearized model at an appropriate operating point.However,these operating points are everchanging in a PV system,and the design of the controller is usually accomplished based on a low irradiance level.This study designs a fractional-order proportional-integrated-derivative(FOPID)controller using deep learning(DL)with quasi-oppositional Archimedes Optimization algorithm(FOPID-QOAOA)for cascaded DC-DC converters in micro-grid applications.The presented FOPIDQOAOA model is designed to enhance the overall efficiency of the cascaded DC-DC boost converter.In addition,the proposed model develops a FOPID controller using a stacked sparse autoencoder(SSAE)model to regulate the converter output voltage.To tune the hyper-parameters related to the SSAE model,the QOAOA is derived by the including of the quasi-oppositional based learning(QOBL)with traditional AOA.Moreover,an objective function with the including of the integral of time multiplied by squared error(ITSE)is considered in this study.For validating the efficiency of the FOPID-QOAOA method,a sequence of simulations was performed under distinct aspects.A comparative study on cascaded buck and boost converters is carried out to authenticate the effectiveness and performance of the designed techniques.展开更多
This paper reviews the major achievements in terms of mechanical behaviors of coal measures,mining stress distribution characteristics and ground control in China’s deep underground coal mining.The three main aspects...This paper reviews the major achievements in terms of mechanical behaviors of coal measures,mining stress distribution characteristics and ground control in China’s deep underground coal mining.The three main aspects of this review are coal measure mechanics,mining disturbance mechanics,and rock support mechanics.Previous studies related to these three topics are reviewed,including the geo-mechanical properties of coal measures,distribution and evolution characteristics of mining-induced stresses,evolution characteristics of mining-induced structures,and principles and technologies of ground control in both deep roadways and longwall faces.A discussion is made to explain the structural and mechanical properties of coal measures in China’s deep coal mining practices,the types and dis-tribution characteristics of in situ stresses in underground coal mines,and the distribution of mining-induced stress that forms under different geological and engineering conditions.The theory of pre-tensioned rock bolting has been proved to be suitable for ground control of deep underground coal roadways.The use of combined ground control technology(e.g.ground support,rock mass modification,and destressing)has been demonstrated to be an effective measure for rock control of deep roadways.The developed hydraulic shields for 1000 m deep ultra-long working face can effectively improve the stability of surrounding rocks and mining efficiency in the longwall face.The ground control challenges in deep underground coal mines in China are discussed,and further research is recommended in terms of theory and technology for ground control in deep roadways and longwall faces.展开更多
The natural cracking of crude oils in deep reservoirs has gained great interest due to continuously increasing depth of petroleum exploration and exploitation.Complex oil compositions and surroundings as well as compl...The natural cracking of crude oils in deep reservoirs has gained great interest due to continuously increasing depth of petroleum exploration and exploitation.Complex oil compositions and surroundings as well as complicated geological evolutions make oil cracking in nature much more complex than industrial pyrolysis.So far,numerous studies,focused on this topic,have made considerable progress although there still exist some drawbacks.However,a comprehensive review on crude oil cracking is yet to be conducted.This article systematically reviews the controlling factors of oil cracking from six aspects,namely,oil compositions,temperature and time,pressure,water,minerals and solid organic matter.We compare previous experimental and modelling results and present new field cases.In the following,we evaluate the prevailing estimation methods for the extent of oil cracking,and elucidate other factors that may interfere with the application of these estimation methods.This review will be helpful for further investigations of crude oil cracking and provides a guide for estimation of the cracking extent of crude oils.展开更多
Deep oil exploration coring technology cannot accurately maintain the in-situ pressure and temperature of samples, which leads to a distortion of deep oil and gas resource reserve evaluations based on conventional cor...Deep oil exploration coring technology cannot accurately maintain the in-situ pressure and temperature of samples, which leads to a distortion of deep oil and gas resource reserve evaluations based on conventional cores and cannot guide the development of deep oil and gas resources on Earth. The fundamental reason is the lack of temperature and pressure control in in-situ coring environments. In this paper, a pressure control method of a coring device is studied. The theory and method of deep intelligent temperature-pressure coupling control are innovatively proposed, and a multifield coupling dynamic sealing model is established. The optimal cardinality three term PID (Proportional-Integral-Differential) intelligent control algorithm of pressure system is developed. The temperature-pressure characteristic of the gas-liquid two-phase cavity is analyzed, and the pressure intelligent control is carried out based on three term PID control algorithms. An in-situ condition-preserved coring (ICP-Coring) device is developed, and an intelligent control system for the temperature and pressure of the coring device is designed and verified by experiments. The results show that the temperature-pressure coupling control system can effectively realize stable sealing under temperature-pressure fields of 140 MPa and 150 °C. The temperature-pressure coupling control method can accurately realize a constant pressure inside the coring device. The maximum working pressure is 140 MPa, and the effective pressure compensation range is 20 MPa. The numerical simulation experiment of pressure system control algorithm is carried out, and the optimal cardinality and three term coefficients are obtained. The pressure steady-state error is less than 0.01%. The method of temperature-pressure coupling control has guiding significance for coring device research, and is also the basis for temperature-pressure decoupling control in ICP-Coring.展开更多
Deep foundation pit excavation is a basic and key step involved in modern building construction.In order to ensure the construction quality and safety of deep foundation pits,this paper takes a project as an example t...Deep foundation pit excavation is a basic and key step involved in modern building construction.In order to ensure the construction quality and safety of deep foundation pits,this paper takes a project as an example to analyze deep foundation pit excavation technology,including the nature of this construction project,the main technical measures in the construction of deep foundation pit,and the analysis of the safety risk prevention and control measures.The purpose of this analysis is to provide scientific reference for the construction quality and safety of deep foundation pits.展开更多
Static Poisson’s ratio(vs)is crucial for determining geomechanical properties in petroleum applications,namely sand production.Some models have been used to predict vs;however,the published models were limited to spe...Static Poisson’s ratio(vs)is crucial for determining geomechanical properties in petroleum applications,namely sand production.Some models have been used to predict vs;however,the published models were limited to specific data ranges with an average absolute percentage relative error(AAPRE)of more than 10%.The published gated recurrent unit(GRU)models do not consider trend analysis to show physical behaviors.In this study,we aim to develop a GRU model using trend analysis and three inputs for predicting n s based on a broad range of data,n s(value of 0.1627-0.4492),bulk formation density(RHOB)(0.315-2.994 g/mL),compressional time(DTc)(44.43-186.9 μs/ft),and shear time(DTs)(72.9-341.2μ s/ft).The GRU model was evaluated using different approaches,including statistical error an-alyses.The GRU model showed the proper trends,and the model data ranges were wider than previous ones.The GRU model has the largest correlation coefficient(R)of 0.967 and the lowest AAPRE,average percent relative error(APRE),root mean square error(RMSE),and standard deviation(SD)of 3.228%,1.054%,4.389,and 0.013,respectively,compared to other models.The GRU model has a high accuracy for the different datasets:training,validation,testing,and the whole datasets with R and AAPRE values were 0.981 and 2.601%,0.966 and 3.274%,0.967 and 3.228%,and 0.977 and 2.861%,respectively.The group error analyses of all inputs show that the GRU model has less than 5% AAPRE for all input ranges,which is superior to other models that have different AAPRE values of more than 10% at various ranges of inputs.展开更多
The vehicular ad hoc network(VANET)is an emerging network tech-nology that has gained popularity because to its low cost,flexibility,and seamless services.Software defined networking(SDN)technology plays a critical role...The vehicular ad hoc network(VANET)is an emerging network tech-nology that has gained popularity because to its low cost,flexibility,and seamless services.Software defined networking(SDN)technology plays a critical role in network administration in the future generation of VANET withfifth generation(5G)networks.Regardless of the benefits of VANET,energy economy and traffic control are significant architectural challenges.Accurate and real-time trafficflow prediction(TFP)becomes critical for managing traffic effectively in the VANET.SDN controllers are a critical issue in VANET,which has garnered much interest in recent years.With this objective,this study develops the SDNTFP-C technique,a revolutionary SDN controller-based real-time trafficflow forecasting technique for clustered VANETs.The proposed SDNTFP-C technique combines the SDN controller’s scalability,flexibility,and adaptability with deep learning(DL)mod-els.Additionally,a novel arithmetic optimization-based clustering technique(AOCA)is developed to cluster automobiles in a VANET.The TFP procedure is then performed using a hybrid convolutional neural network model with atten-tion-based bidirectional long short-term memory(HCNN-ABLSTM).To optimise the performance of the HCNN-ABLSTM model,the dingo optimization techni-que was used to tune the hyperparameters(DOA).The experimental results ana-lysis reveals that the suggested method outperforms other current techniques on a variety of evaluation metrics.展开更多
Under the dual influence of the mining disturbance of the previous working face and the advanced mining of the working face,the roadway is prone to large deformation,failure,and rockburst.Roadway stabilization has alw...Under the dual influence of the mining disturbance of the previous working face and the advanced mining of the working face,the roadway is prone to large deformation,failure,and rockburst.Roadway stabilization has always significantly influenced deep mining safety.In this article we used the research background of the large deformation failure roadway of Fa-er Coal Mine in Guizhou Province of China to propose two control methods:bolt-cable-mesh+concrete blocks+directional energy-gathering blasting(BCM-CBDE method)and 1st Generation-Negative Poisson’s Ratio(1G NPR)cable+directional energy-gathering blasting+dynamic pressure stage support(πgirder+single hydraulic prop+retractable U steel)(NPR-DEDP method).Meantime,we compared the validity of the large deformation failure control method in a deep gob-side roadway based on theoretical analysis,numerical simulations,and field experiments.The results show that directional energy-gathering blasting can weaken the pressure acting on the concrete blocks.However,the vertical stress of the surrounding rock of the roadway is still concentrated in the entity coal side and the concrete blocks,showing a’bimodal’distribution.BCM-CBDE method cannot effectively control the stability of the roadway.NPR-DEDP method removed the concrete blocks.It shows using the 1G NPR cable with periodic slipping-sticking characteristics can adapt to repeated mining disturbances.The peak value of the vertical stress of the roadway is reduced and transferred to the deep part of the surrounding rock mass,which promotes the collapse of the gangue in the goaf and fills the goaf.The pressure of the roadway roof is reduced,and the gob-side roadway is fundamentally protected.Meantime,the dynamic pressure stage support method withπgirder+single hydraulic prop+retractable U steel as the core effectively protects the roadway from dynamic pressure impact when the main roof is periodically broken.After the on-site implementation of NPR-DEDP method,the deformation of the roadway is reduced by more than 45%,and the deformation rate is reduced by more than 50%.展开更多
In response to the challenges of generating Attribute-Based Access Control(ABAC)policies,this paper proposes a deep learning-based method to automatically generate ABAC policies from natural language documents.This me...In response to the challenges of generating Attribute-Based Access Control(ABAC)policies,this paper proposes a deep learning-based method to automatically generate ABAC policies from natural language documents.This method is aimed at organizations such as companies and schools that are transitioning from traditional access control models to the ABAC model.The manual retrieval and analysis involved in this transition are inefficient,prone to errors,and costly.Most organizations have high-level specifications defined for security policies that include a set of access control policies,which often exist in the form of natural language documents.Utilizing this rich source of information,our method effectively identifies and extracts the necessary attributes and rules for access control from natural language documents,thereby constructing and optimizing access control policies.This work transforms the problem of policy automation generation into two tasks:extraction of access control statements andmining of access control attributes.First,the Chat General Language Model(ChatGLM)isemployed to extract access control-related statements from a wide range of natural language documents by constructing unique prompts and leveraging the model’s In-Context Learning to contextualize the statements.Then,the Iterated Dilated-Convolutions-Conditional Random Field(ID-CNN-CRF)model is used to annotate access control attributes within these extracted statements,including subject attributes,object attributes,and action attributes,thus reassembling new access control policies.Experimental results show that our method,compared to baseline methods,achieved the highest F1 score of 0.961,confirming the model’s effectiveness and accuracy.展开更多
As an important mechanism in multi-agent interaction,communication can make agents form complex team relationships rather than constitute a simple set of multiple independent agents.However,the existing communication ...As an important mechanism in multi-agent interaction,communication can make agents form complex team relationships rather than constitute a simple set of multiple independent agents.However,the existing communication schemes can bring much timing redundancy and irrelevant messages,which seriously affects their practical application.To solve this problem,this paper proposes a targeted multiagent communication algorithm based on state control(SCTC).The SCTC uses a gating mechanism based on state control to reduce the timing redundancy of communication between agents and determines the interaction relationship between agents and the importance weight of a communication message through a series connection of hard-and self-attention mechanisms,realizing targeted communication message processing.In addition,by minimizing the difference between the fusion message generated from a real communication message of each agent and a fusion message generated from the buffered message,the correctness of the final action choice of the agent is ensured.Our evaluation using a challenging set of Star Craft II benchmarks indicates that the SCTC can significantly improve the learning performance and reduce the communication overhead between agents,thus ensuring better cooperation between agents.展开更多
The freezing acidolysis solution of the nitric acid-phosphate fertilizer process has a high calcium content,which makes it difficult to produce fine phosphate and high water-soluble phosphate fertilizer products.Here,...The freezing acidolysis solution of the nitric acid-phosphate fertilizer process has a high calcium content,which makes it difficult to produce fine phosphate and high water-soluble phosphate fertilizer products.Here,based on the potential crystallization principle of calcium sulfate in NH_(4)NO_(3)-H_(3)PO_(4)-H_(2)O,the deep decalcification(i.e.calcium removal)technology to achieveα-high-strength gypsum originated from freezing acidolysis-solutions has been firstly proposed and investigated.Typically,calcium can be removed from the factory-provided freezing acidolysis-solution by neutralizing it with ammonia,followed by the addition of ammonium sulfate solution.As a result,the formation of calcium sulfate in the reaction system undergoes the nucleation and growth of CaSO_(4)·2H_(2)O(DH),as well as its dissolution and crystallization into short columnarα-CaSO_(4)·0.5H_(2)O(α-HH).Remarkably,with the molar ratio of SO_(4)^(2-)/Ca^(2+)at 1.8,the degree of neutralization(NH_(3)/HNO_(3) molar ratio)at 1.7,the reaction temperature of 94℃,and the reaction time of 300 min,the decalcification rate can reach 86.89%,of which the high-strengthα-CaSO_(4)·0.5H_(2)O(α-HH)will be obtained.Noteworthy,the deep decalcification product meets the standards for the production of fine phosphates and highly water-soluble phosphate fertilizers.Consequently,the 2 h flexural strength ofα-HH is 5.3 MPa and the dry compressive strength is 36.8 MPa,which is up to the standard of commercialα-HH.展开更多
The pivotal areas for the extensive and effective exploitation of shale gas in the Southern Sichuan Basin have recently transitioned from mid-deep layers to deep layers.Given challenges such as intricate data analysis...The pivotal areas for the extensive and effective exploitation of shale gas in the Southern Sichuan Basin have recently transitioned from mid-deep layers to deep layers.Given challenges such as intricate data analysis,absence of effective assessment methodologies,real-time control strategies,and scarce knowledge of the factors influencing deep gas wells in the so-called flowback stage,a comprehensive study was undertaken on over 160 deep gas wells in Luzhou block utilizing linear flow models and advanced big data analytics techniques.The research results show that:(1)The flowback stage of a deep gas well presents the characteristics of late gas channeling,high flowback rate after gas channeling,low 30-day flowback rate,and high flowback rate corresponding to peak production;(2)The comprehensive parameter AcmKm1/2 in the flowback stage exhibits a strong correlation with the Estimated Ultimate Recovery(EUR),allowing for the establishment of a standardized chart to evaluate EUR classification in typical shale gas wells during this stage.This enables quantitative assessment of gas well EUR,providing valuable insights into production potential and performance;(3)The spacing range and the initial productivity of gas wells have a significant impact on the overall effectiveness of gas wells.Therefore,it is crucial to further explore rational well patterns and spacing,as well as optimize initial drainage and production technical strategies in order to improve their performance.展开更多
Background Synthesizing dance motions to match musical inputs is a significant challenge in animation research.Compared to functional human motions,such as locomotion,dance motions are creative and artistic,often infl...Background Synthesizing dance motions to match musical inputs is a significant challenge in animation research.Compared to functional human motions,such as locomotion,dance motions are creative and artistic,often influenced by music,and can be independent body language expressions.Dance choreography requires motion content to follow a general dance genre,whereas dance performances under musical influence are infused with diverse impromptu motion styles.Considering the high expressiveness and variations in space and time,providing accessible and effective user control for tuning dance motion styles remains an open problem.Methods In this study,we present a hierarchical framework that decouples the dance synthesis task into independent modules.We use a high-level choreography module built as a Transformer-based sequence model to predict the long-term structure of a dance genre and a low-level realization module that implements dance stylization and synchronization to match the musical input or user preferences.This novel framework allows the individual modules to be trained separately.Because of the decoupling,dance composition can fully utilize existing high-quality dance datasets that do not have musical accompaniments,and the dance implementation can conveniently incorporate user controls and edit motions through a decoder network.Each module is replaceable at runtime,which adds flexibility to the synthesis of dance sequences.Results Synthesized results demonstrate that our framework generates high-quality diverse dance motions that are well adapted to varying musical conditions and user controls.展开更多
The grouted bolt,combining rock bolting with grouting techniques,provides an effective solution for controlling the surrounding rock in deep soft rock and fractured roadways.It has been extensively applied in numerous...The grouted bolt,combining rock bolting with grouting techniques,provides an effective solution for controlling the surrounding rock in deep soft rock and fractured roadways.It has been extensively applied in numerous deep mining areas characterized by soft rock roadways,where it has demonstrated remarkable control results.This article systematically explores the evolution of grouted bolting,covering its theoretical foundations,design methods,materials,construction processes,monitoring measures,and methods for assessing its effectiveness.The overview encompassed several key elements,delving into anchoring theory and grouting reinforcement theory.The new principle of high pretensioned high-pressure splitting grouted bolting collaborative active control is introduced.A fresh method for dynamic information design is also highlighted.The discussion touches on both conventional grouting rock bolts and cable bolts,as well as innovative grouted rock bolts and cables characterized by their high pretension,strength,and sealing hole pressure.An examination of the merits and demerits of standard inorganic and organic grouting materials versus the new inorganic–organic composite materials,including their specific application conditions,was conducted.Additionally,the article presents various methods and instruments to assess the support effect of grouting rock bolts,cable bolts,and grouting reinforcement.Furthermore,it provides a foundation for understanding the factors influencing decisions on grouted bolting timing,the sequence of grouting,the pressure applied,the volume of grout used,and the strategic arrangement of grouted rock bolts and cable bolts.The application of the high pretensioned high-pressure splitting grouted bolting collaborative control technology in a typical kilometer-deep soft rock mine in China—the soft coal seam and soft rock roadway in the Kouzidong coal mine,Huainan coal mining area,was introduced.Finally,the existing problems in grouted bolting control technology for deep soft rock roadways are analyzed,and the future development trend of grouted bolting control technology is anticipated.展开更多
The research progress of deep and ultra-deep drilling fluid technology systematically reviewed,the key problems existing are analyzed,and the future development direction is proposed.In view of the high temperature,hi...The research progress of deep and ultra-deep drilling fluid technology systematically reviewed,the key problems existing are analyzed,and the future development direction is proposed.In view of the high temperature,high pressure and high stress,fracture development,wellbore instability,drilling fluid lost circulation and other problems faced in the process of deep and ultra-deep complex oil and gas drilling,scholars have developed deep and ultra-deep high-temperature and high-salt resistant water-based drilling fluid technology,high-temperature resistant oil-based/synthetic drilling fluid technology,drilling fluid technology for reservoir protection and drilling fluid lost circulation control technology.However,there are still some key problems such as insufficient resistance to high temperature,high pressure and high stress,wellbore instability and serious lost circulation.Therefore,the development direction of deep and ultra-deep drilling fluid technology in the future is proposed:(1)The technology of high-temperature and high-salt resistant water-based drilling fluid should focus on improving high temperature stability,improving rheological properties,strengthening filtration control and improving compatibility with formation.(2)The technology of oil-based/synthetic drilling fluid resistant to high temperature should further study in the aspects of easily degradable environmental protection additives with low toxicity such as high temperature stabilizer,rheological regulator and related supporting technologies.(3)The drilling fluid technology for reservoir protection should be devoted to the development of new high-performance additives and materials,and further improve the real-time monitoring technology by introducing advanced sensor networks and artificial intelligence algorithms.(4)The lost circulation control of drilling fluid should pay more attention to the integration and application of intelligent technology,the research and application of high-performance plugging materials,the exploration of diversified plugging techniques and methods,and the improvement of environmental protection and production safety awareness.展开更多
Purpose: Few studies have evaluated the association between malnutrition and the risk of preoperative deep vein thrombosis (DVT) in patients undergoing primary total joint arthroplasty. This study aimed to investigate...Purpose: Few studies have evaluated the association between malnutrition and the risk of preoperative deep vein thrombosis (DVT) in patients undergoing primary total joint arthroplasty. This study aimed to investigate the prevalence of preoperative DVT in Japanese patients undergoing total knee arthroplasty (TKA) and the importance of malnutrition in the risk of preoperative DVT. Methods: We retrospectively analyzed 394 patients admitted for primary TKA at our institution between January 2019 and December 2023. All patients scheduled for TKA at our institution had serum D-dimer levels measured preoperatively. Lower-limb ultrasonography was examined to confirm the presence of DVT in patients with D-dimer levels ≥ 1.0 µg/mL or who were considered to be at high risk of DVT by the treating physician. Based on the results of lower-limb ultrasonography, all patients were divided into the non-DVT and DVT groups. The incidence of and risk factors for preoperative DVT were investigated, as well as the correlation of DVT with the patient’s nutritional parameters. We used two representative tools for nutritional assessment: the Geriatric Nutritional Risk Index (GNRI) and Controlling Nutritional Status Score. Results: The mean age was 77.8 ± 6.9 years. Preoperative DVT was diagnosed in 57 of the 394 (14.5%) patients. Multivariate logistic regression analysis showed that advanced age and malnutrition status, assessed using the GNRI, were independent risk factors for preoperative DVT. Conclusion: A high incidence of preoperative DVT was observed in patients who underwent TKA. Malnutrition status, as assessed using the GNRI, increased the risk of preoperative DVT. Our findings suggest that clinicians should consider these factors when tailoring preventive strategies to mitigate DVT risk in patients undergoing TKA.展开更多
Aiming at the problems of large deformation and difficult maintenance of deep soft rock roadway under the influence of high ground stress and strong dynamic pressure, taking the surrounding rock control of 1105 lane i...Aiming at the problems of large deformation and difficult maintenance of deep soft rock roadway under the influence of high ground stress and strong dynamic pressure, taking the surrounding rock control of 1105 lane in Hudi Coal Industry as an example, the deformation characteristics and surrounding rock control measures of deep soft rock roadway are analyzed and discussed by means of geological data analysis, roadway deformation monitoring, rock crack drilling and field test. The results show that the main causes of roadway deformation are high ground stress, synclinal tectonic stress, advance mining stress, roadway penetration and surrounding rock fissure development. Based on the deformation characteristics and mechanism of lane 1105, the supporting countermeasures of “roof synergic support, layered grouting, anchor cable beam support, closed hardening of roadway surface” are proposed, which can provide reference for the control of deep roadway surrounding rock under similar conditions.展开更多
Deep-Litter System is a high yield approach to raise swine with pollution free in a lower cost. In the research, based on the heat stress in summer caused by fermentation, three temperature-control systems were design...Deep-Litter System is a high yield approach to raise swine with pollution free in a lower cost. In the research, based on the heat stress in summer caused by fermentation, three temperature-control systems were designed, including natural ventilation through transoms, forced ventilation via fans, and cooling by hyperbaric spray system. Specifically, the latter intermittent auto-pressurized spray system developed in our lab, which could spray successively via pressure from storage tubes without wetting the fermentation bed, is suitable for the promotion with the deep-litter technology in rural regions , since the power consumption is only 1 kwh per day.展开更多
基金supported by Guangdong Basic and Applied Basic Research Foundation under Grant 2024A1515012015supported in part by the National Natural Science Foundation of China under Grant 62201336+4 种基金in part by Guangdong Basic and Applied Basic Research Foundation under Grant 2024A1515011541supported in part by the National Natural Science Foundation of China under Grant 62371344in part by the Fundamental Research Funds for the Central Universitiessupported in part by Knowledge Innovation Program of Wuhan-Shuguang Project under Grant 2023010201020316in part by Guangdong Basic and Applied Basic Research Foundation under Grant 2024A1515010247。
文摘In recent times,various power control and clustering approaches have been proposed to enhance overall performance for cell-free massive multipleinput multiple-output(CF-mMIMO)networks.With the emergence of deep reinforcement learning(DRL),significant progress has been made in the field of network optimization as DRL holds great promise for improving network performance and efficiency.In this work,our focus delves into the intricate challenge of joint cooperation clustering and downlink power control within CF-mMIMO networks.Leveraging the potent deep deterministic policy gradient(DDPG)algorithm,our objective is to maximize the proportional fairness(PF)for user rates,thereby aiming to achieve optimal network performance and resource utilization.Moreover,we harness the concept of“divide and conquer”strategy,introducing two innovative methods termed alternating DDPG(A-DDPG)and hierarchical DDPG(H-DDPG).These approaches aim to decompose the intricate joint optimization problem into more manageable sub-problems,thereby facilitating a more efficient resolution process.Our findings unequivo-cally showcase the superior efficacy of our proposed DDPG approach over the baseline schemes in both clustering and downlink power control.Furthermore,the A-DDPG and H-DDPG obtain higher performance gain than DDPG with lower computational complexity.
基金partly supported by the University of Malaya Impact Oriented Interdisci-plinary Research Grant under Grant IIRG008(A,B,C)-19IISS.
文摘Organizations are adopting the Bring Your Own Device(BYOD)concept to enhance productivity and reduce expenses.However,this trend introduces security challenges,such as unauthorized access.Traditional access control systems,such as Attribute-Based Access Control(ABAC)and Role-Based Access Control(RBAC),are limited in their ability to enforce access decisions due to the variability and dynamism of attributes related to users and resources.This paper proposes a method for enforcing access decisions that is adaptable and dynamic,based on multilayer hybrid deep learning techniques,particularly the Tabular Deep Neural Network Tabular DNN method.This technique transforms all input attributes in an access request into a binary classification(allow or deny)using multiple layers,ensuring accurate and efficient access decision-making.The proposed solution was evaluated using the Kaggle Amazon access control policy dataset and demonstrated its effectiveness by achieving a 94%accuracy rate.Additionally,the proposed solution enhances the implementation of access decisions based on a variety of resource and user attributes while ensuring privacy through indirect communication with the Policy Administration Point(PAP).This solution significantly improves the flexibility of access control systems,making themmore dynamic and adaptable to the evolving needs ofmodern organizations.Furthermore,it offers a scalable approach to manage the complexities associated with the BYOD environment,providing a robust framework for secure and efficient access management.
文摘Smart grids and their technologies transform the traditional electric grids to assure safe,secure,cost-effective,and reliable power transmission.Non-linear phenomena in power systems,such as voltage collapse and oscillatory phenomena,can be investigated by chaos theory.Recently,renewable energy resources,such as wind turbines,and solar photovoltaic(PV)arrays,have been widely used for electric power generation.The design of the controller for the direct Current(DC)converter in a PV system is performed based on the linearized model at an appropriate operating point.However,these operating points are everchanging in a PV system,and the design of the controller is usually accomplished based on a low irradiance level.This study designs a fractional-order proportional-integrated-derivative(FOPID)controller using deep learning(DL)with quasi-oppositional Archimedes Optimization algorithm(FOPID-QOAOA)for cascaded DC-DC converters in micro-grid applications.The presented FOPIDQOAOA model is designed to enhance the overall efficiency of the cascaded DC-DC boost converter.In addition,the proposed model develops a FOPID controller using a stacked sparse autoencoder(SSAE)model to regulate the converter output voltage.To tune the hyper-parameters related to the SSAE model,the QOAOA is derived by the including of the quasi-oppositional based learning(QOBL)with traditional AOA.Moreover,an objective function with the including of the integral of time multiplied by squared error(ITSE)is considered in this study.For validating the efficiency of the FOPID-QOAOA method,a sequence of simulations was performed under distinct aspects.A comparative study on cascaded buck and boost converters is carried out to authenticate the effectiveness and performance of the designed techniques.
基金This work has been supported by the National Key Research and Development Program(Grant No.2017YFC0603000)which was jointly completed by the Coal Mining Research Branch of CCRI,China University of Mining and Technology(Xuzhou and Beijing),Henan Polytechnic UniversityXinji Energy Company Limited of China Coal Energy Group.This work was also supported by the National Natural Science Foundation of China(Grant No.51927807)。
文摘This paper reviews the major achievements in terms of mechanical behaviors of coal measures,mining stress distribution characteristics and ground control in China’s deep underground coal mining.The three main aspects of this review are coal measure mechanics,mining disturbance mechanics,and rock support mechanics.Previous studies related to these three topics are reviewed,including the geo-mechanical properties of coal measures,distribution and evolution characteristics of mining-induced stresses,evolution characteristics of mining-induced structures,and principles and technologies of ground control in both deep roadways and longwall faces.A discussion is made to explain the structural and mechanical properties of coal measures in China’s deep coal mining practices,the types and dis-tribution characteristics of in situ stresses in underground coal mines,and the distribution of mining-induced stress that forms under different geological and engineering conditions.The theory of pre-tensioned rock bolting has been proved to be suitable for ground control of deep underground coal roadways.The use of combined ground control technology(e.g.ground support,rock mass modification,and destressing)has been demonstrated to be an effective measure for rock control of deep roadways.The developed hydraulic shields for 1000 m deep ultra-long working face can effectively improve the stability of surrounding rocks and mining efficiency in the longwall face.The ground control challenges in deep underground coal mines in China are discussed,and further research is recommended in terms of theory and technology for ground control in deep roadways and longwall faces.
基金This study is supported by the National Natural Science Foundation of China(Grants 41730424,41961144023 and 42002162)。
文摘The natural cracking of crude oils in deep reservoirs has gained great interest due to continuously increasing depth of petroleum exploration and exploitation.Complex oil compositions and surroundings as well as complicated geological evolutions make oil cracking in nature much more complex than industrial pyrolysis.So far,numerous studies,focused on this topic,have made considerable progress although there still exist some drawbacks.However,a comprehensive review on crude oil cracking is yet to be conducted.This article systematically reviews the controlling factors of oil cracking from six aspects,namely,oil compositions,temperature and time,pressure,water,minerals and solid organic matter.We compare previous experimental and modelling results and present new field cases.In the following,we evaluate the prevailing estimation methods for the extent of oil cracking,and elucidate other factors that may interfere with the application of these estimation methods.This review will be helpful for further investigations of crude oil cracking and provides a guide for estimation of the cracking extent of crude oils.
基金supported by the National Natural Science Foundation of China(grant numbers 51827901,51805340)funded by the Program for Guangdong Introducing Innovative and Enterpreneurial Teams(No.2019ZT08G315)Shenzhen Basic Research Program(General Program)(No.JCYJ20190808153416970).
文摘Deep oil exploration coring technology cannot accurately maintain the in-situ pressure and temperature of samples, which leads to a distortion of deep oil and gas resource reserve evaluations based on conventional cores and cannot guide the development of deep oil and gas resources on Earth. The fundamental reason is the lack of temperature and pressure control in in-situ coring environments. In this paper, a pressure control method of a coring device is studied. The theory and method of deep intelligent temperature-pressure coupling control are innovatively proposed, and a multifield coupling dynamic sealing model is established. The optimal cardinality three term PID (Proportional-Integral-Differential) intelligent control algorithm of pressure system is developed. The temperature-pressure characteristic of the gas-liquid two-phase cavity is analyzed, and the pressure intelligent control is carried out based on three term PID control algorithms. An in-situ condition-preserved coring (ICP-Coring) device is developed, and an intelligent control system for the temperature and pressure of the coring device is designed and verified by experiments. The results show that the temperature-pressure coupling control system can effectively realize stable sealing under temperature-pressure fields of 140 MPa and 150 °C. The temperature-pressure coupling control method can accurately realize a constant pressure inside the coring device. The maximum working pressure is 140 MPa, and the effective pressure compensation range is 20 MPa. The numerical simulation experiment of pressure system control algorithm is carried out, and the optimal cardinality and three term coefficients are obtained. The pressure steady-state error is less than 0.01%. The method of temperature-pressure coupling control has guiding significance for coring device research, and is also the basis for temperature-pressure decoupling control in ICP-Coring.
文摘Deep foundation pit excavation is a basic and key step involved in modern building construction.In order to ensure the construction quality and safety of deep foundation pits,this paper takes a project as an example to analyze deep foundation pit excavation technology,including the nature of this construction project,the main technical measures in the construction of deep foundation pit,and the analysis of the safety risk prevention and control measures.The purpose of this analysis is to provide scientific reference for the construction quality and safety of deep foundation pits.
基金The authors thank the Yayasan Universiti Teknologi PETRONAS(YUTP FRG Grant No.015LC0-428)at Universiti Teknologi PETRO-NAS for supporting this study.
文摘Static Poisson’s ratio(vs)is crucial for determining geomechanical properties in petroleum applications,namely sand production.Some models have been used to predict vs;however,the published models were limited to specific data ranges with an average absolute percentage relative error(AAPRE)of more than 10%.The published gated recurrent unit(GRU)models do not consider trend analysis to show physical behaviors.In this study,we aim to develop a GRU model using trend analysis and three inputs for predicting n s based on a broad range of data,n s(value of 0.1627-0.4492),bulk formation density(RHOB)(0.315-2.994 g/mL),compressional time(DTc)(44.43-186.9 μs/ft),and shear time(DTs)(72.9-341.2μ s/ft).The GRU model was evaluated using different approaches,including statistical error an-alyses.The GRU model showed the proper trends,and the model data ranges were wider than previous ones.The GRU model has the largest correlation coefficient(R)of 0.967 and the lowest AAPRE,average percent relative error(APRE),root mean square error(RMSE),and standard deviation(SD)of 3.228%,1.054%,4.389,and 0.013,respectively,compared to other models.The GRU model has a high accuracy for the different datasets:training,validation,testing,and the whole datasets with R and AAPRE values were 0.981 and 2.601%,0.966 and 3.274%,0.967 and 3.228%,and 0.977 and 2.861%,respectively.The group error analyses of all inputs show that the GRU model has less than 5% AAPRE for all input ranges,which is superior to other models that have different AAPRE values of more than 10% at various ranges of inputs.
文摘The vehicular ad hoc network(VANET)is an emerging network tech-nology that has gained popularity because to its low cost,flexibility,and seamless services.Software defined networking(SDN)technology plays a critical role in network administration in the future generation of VANET withfifth generation(5G)networks.Regardless of the benefits of VANET,energy economy and traffic control are significant architectural challenges.Accurate and real-time trafficflow prediction(TFP)becomes critical for managing traffic effectively in the VANET.SDN controllers are a critical issue in VANET,which has garnered much interest in recent years.With this objective,this study develops the SDNTFP-C technique,a revolutionary SDN controller-based real-time trafficflow forecasting technique for clustered VANETs.The proposed SDNTFP-C technique combines the SDN controller’s scalability,flexibility,and adaptability with deep learning(DL)mod-els.Additionally,a novel arithmetic optimization-based clustering technique(AOCA)is developed to cluster automobiles in a VANET.The TFP procedure is then performed using a hybrid convolutional neural network model with atten-tion-based bidirectional long short-term memory(HCNN-ABLSTM).To optimise the performance of the HCNN-ABLSTM model,the dingo optimization techni-que was used to tune the hyperparameters(DOA).The experimental results ana-lysis reveals that the suggested method outperforms other current techniques on a variety of evaluation metrics.
基金funded by National Natural Science Foundation of China(52074300)Yueqi Young Scholars Project of China University of Mining and Technology Beijing(2602021RC84)+1 种基金China University of Mining and Technology(Beijing)fundamental scientific research funds—Doctoral students Top-notch Innovative Talents Fostering Funds(BBJ2023047)Guizhou Provincial Science and Technology Planning Project([2020]2Y030)。
文摘Under the dual influence of the mining disturbance of the previous working face and the advanced mining of the working face,the roadway is prone to large deformation,failure,and rockburst.Roadway stabilization has always significantly influenced deep mining safety.In this article we used the research background of the large deformation failure roadway of Fa-er Coal Mine in Guizhou Province of China to propose two control methods:bolt-cable-mesh+concrete blocks+directional energy-gathering blasting(BCM-CBDE method)and 1st Generation-Negative Poisson’s Ratio(1G NPR)cable+directional energy-gathering blasting+dynamic pressure stage support(πgirder+single hydraulic prop+retractable U steel)(NPR-DEDP method).Meantime,we compared the validity of the large deformation failure control method in a deep gob-side roadway based on theoretical analysis,numerical simulations,and field experiments.The results show that directional energy-gathering blasting can weaken the pressure acting on the concrete blocks.However,the vertical stress of the surrounding rock of the roadway is still concentrated in the entity coal side and the concrete blocks,showing a’bimodal’distribution.BCM-CBDE method cannot effectively control the stability of the roadway.NPR-DEDP method removed the concrete blocks.It shows using the 1G NPR cable with periodic slipping-sticking characteristics can adapt to repeated mining disturbances.The peak value of the vertical stress of the roadway is reduced and transferred to the deep part of the surrounding rock mass,which promotes the collapse of the gangue in the goaf and fills the goaf.The pressure of the roadway roof is reduced,and the gob-side roadway is fundamentally protected.Meantime,the dynamic pressure stage support method withπgirder+single hydraulic prop+retractable U steel as the core effectively protects the roadway from dynamic pressure impact when the main roof is periodically broken.After the on-site implementation of NPR-DEDP method,the deformation of the roadway is reduced by more than 45%,and the deformation rate is reduced by more than 50%.
基金supported by the National Natural Science Foundation of China Project(No.62302540),please visit their website at https://www.nsfc.gov.cn/(accessed on 18 June 2024)The Open Foundation of Henan Key Laboratory of Cyberspace Situation Awareness(No.HNTS2022020),Further details can be found at http://xt.hnkjt.gov.cn/data/pingtai/(accessed on 18 June 2024)Natural Science Foundation of Henan Province Youth Science Fund Project(No.232300420422),you can visit https://kjt.henan.gov.cn/2022/09-02/2599082.html(accessed on 18 June 2024).
文摘In response to the challenges of generating Attribute-Based Access Control(ABAC)policies,this paper proposes a deep learning-based method to automatically generate ABAC policies from natural language documents.This method is aimed at organizations such as companies and schools that are transitioning from traditional access control models to the ABAC model.The manual retrieval and analysis involved in this transition are inefficient,prone to errors,and costly.Most organizations have high-level specifications defined for security policies that include a set of access control policies,which often exist in the form of natural language documents.Utilizing this rich source of information,our method effectively identifies and extracts the necessary attributes and rules for access control from natural language documents,thereby constructing and optimizing access control policies.This work transforms the problem of policy automation generation into two tasks:extraction of access control statements andmining of access control attributes.First,the Chat General Language Model(ChatGLM)isemployed to extract access control-related statements from a wide range of natural language documents by constructing unique prompts and leveraging the model’s In-Context Learning to contextualize the statements.Then,the Iterated Dilated-Convolutions-Conditional Random Field(ID-CNN-CRF)model is used to annotate access control attributes within these extracted statements,including subject attributes,object attributes,and action attributes,thus reassembling new access control policies.Experimental results show that our method,compared to baseline methods,achieved the highest F1 score of 0.961,confirming the model’s effectiveness and accuracy.
文摘As an important mechanism in multi-agent interaction,communication can make agents form complex team relationships rather than constitute a simple set of multiple independent agents.However,the existing communication schemes can bring much timing redundancy and irrelevant messages,which seriously affects their practical application.To solve this problem,this paper proposes a targeted multiagent communication algorithm based on state control(SCTC).The SCTC uses a gating mechanism based on state control to reduce the timing redundancy of communication between agents and determines the interaction relationship between agents and the importance weight of a communication message through a series connection of hard-and self-attention mechanisms,realizing targeted communication message processing.In addition,by minimizing the difference between the fusion message generated from a real communication message of each agent and a fusion message generated from the buffered message,the correctness of the final action choice of the agent is ensured.Our evaluation using a challenging set of Star Craft II benchmarks indicates that the SCTC can significantly improve the learning performance and reduce the communication overhead between agents,thus ensuring better cooperation between agents.
基金supported by the National Key Research and Development Program of China(2018YFC1900206-2)Science&Technology Plan Projects of Guizhou Province(Qiankehe Service Enterprises[2018]4011)Science and Technology Support Plan Project of Guizhou Provincial:Qiankehe Support[2021]General 487。
文摘The freezing acidolysis solution of the nitric acid-phosphate fertilizer process has a high calcium content,which makes it difficult to produce fine phosphate and high water-soluble phosphate fertilizer products.Here,based on the potential crystallization principle of calcium sulfate in NH_(4)NO_(3)-H_(3)PO_(4)-H_(2)O,the deep decalcification(i.e.calcium removal)technology to achieveα-high-strength gypsum originated from freezing acidolysis-solutions has been firstly proposed and investigated.Typically,calcium can be removed from the factory-provided freezing acidolysis-solution by neutralizing it with ammonia,followed by the addition of ammonium sulfate solution.As a result,the formation of calcium sulfate in the reaction system undergoes the nucleation and growth of CaSO_(4)·2H_(2)O(DH),as well as its dissolution and crystallization into short columnarα-CaSO_(4)·0.5H_(2)O(α-HH).Remarkably,with the molar ratio of SO_(4)^(2-)/Ca^(2+)at 1.8,the degree of neutralization(NH_(3)/HNO_(3) molar ratio)at 1.7,the reaction temperature of 94℃,and the reaction time of 300 min,the decalcification rate can reach 86.89%,of which the high-strengthα-CaSO_(4)·0.5H_(2)O(α-HH)will be obtained.Noteworthy,the deep decalcification product meets the standards for the production of fine phosphates and highly water-soluble phosphate fertilizers.Consequently,the 2 h flexural strength ofα-HH is 5.3 MPa and the dry compressive strength is 36.8 MPa,which is up to the standard of commercialα-HH.
文摘The pivotal areas for the extensive and effective exploitation of shale gas in the Southern Sichuan Basin have recently transitioned from mid-deep layers to deep layers.Given challenges such as intricate data analysis,absence of effective assessment methodologies,real-time control strategies,and scarce knowledge of the factors influencing deep gas wells in the so-called flowback stage,a comprehensive study was undertaken on over 160 deep gas wells in Luzhou block utilizing linear flow models and advanced big data analytics techniques.The research results show that:(1)The flowback stage of a deep gas well presents the characteristics of late gas channeling,high flowback rate after gas channeling,low 30-day flowback rate,and high flowback rate corresponding to peak production;(2)The comprehensive parameter AcmKm1/2 in the flowback stage exhibits a strong correlation with the Estimated Ultimate Recovery(EUR),allowing for the establishment of a standardized chart to evaluate EUR classification in typical shale gas wells during this stage.This enables quantitative assessment of gas well EUR,providing valuable insights into production potential and performance;(3)The spacing range and the initial productivity of gas wells have a significant impact on the overall effectiveness of gas wells.Therefore,it is crucial to further explore rational well patterns and spacing,as well as optimize initial drainage and production technical strategies in order to improve their performance.
基金Supported by Startup Fund 20019495,McMaster University。
文摘Background Synthesizing dance motions to match musical inputs is a significant challenge in animation research.Compared to functional human motions,such as locomotion,dance motions are creative and artistic,often influenced by music,and can be independent body language expressions.Dance choreography requires motion content to follow a general dance genre,whereas dance performances under musical influence are infused with diverse impromptu motion styles.Considering the high expressiveness and variations in space and time,providing accessible and effective user control for tuning dance motion styles remains an open problem.Methods In this study,we present a hierarchical framework that decouples the dance synthesis task into independent modules.We use a high-level choreography module built as a Transformer-based sequence model to predict the long-term structure of a dance genre and a low-level realization module that implements dance stylization and synchronization to match the musical input or user preferences.This novel framework allows the individual modules to be trained separately.Because of the decoupling,dance composition can fully utilize existing high-quality dance datasets that do not have musical accompaniments,and the dance implementation can conveniently incorporate user controls and edit motions through a decoder network.Each module is replaceable at runtime,which adds flexibility to the synthesis of dance sequences.Results Synthesized results demonstrate that our framework generates high-quality diverse dance motions that are well adapted to varying musical conditions and user controls.
基金the National Natural Science Foundation of China(Nos.52304141 and 52074154)。
文摘The grouted bolt,combining rock bolting with grouting techniques,provides an effective solution for controlling the surrounding rock in deep soft rock and fractured roadways.It has been extensively applied in numerous deep mining areas characterized by soft rock roadways,where it has demonstrated remarkable control results.This article systematically explores the evolution of grouted bolting,covering its theoretical foundations,design methods,materials,construction processes,monitoring measures,and methods for assessing its effectiveness.The overview encompassed several key elements,delving into anchoring theory and grouting reinforcement theory.The new principle of high pretensioned high-pressure splitting grouted bolting collaborative active control is introduced.A fresh method for dynamic information design is also highlighted.The discussion touches on both conventional grouting rock bolts and cable bolts,as well as innovative grouted rock bolts and cables characterized by their high pretension,strength,and sealing hole pressure.An examination of the merits and demerits of standard inorganic and organic grouting materials versus the new inorganic–organic composite materials,including their specific application conditions,was conducted.Additionally,the article presents various methods and instruments to assess the support effect of grouting rock bolts,cable bolts,and grouting reinforcement.Furthermore,it provides a foundation for understanding the factors influencing decisions on grouted bolting timing,the sequence of grouting,the pressure applied,the volume of grout used,and the strategic arrangement of grouted rock bolts and cable bolts.The application of the high pretensioned high-pressure splitting grouted bolting collaborative control technology in a typical kilometer-deep soft rock mine in China—the soft coal seam and soft rock roadway in the Kouzidong coal mine,Huainan coal mining area,was introduced.Finally,the existing problems in grouted bolting control technology for deep soft rock roadways are analyzed,and the future development trend of grouted bolting control technology is anticipated.
基金Supported by the Projects of National Natural Science Foundation of China(52288101,52174014,52374023)。
文摘The research progress of deep and ultra-deep drilling fluid technology systematically reviewed,the key problems existing are analyzed,and the future development direction is proposed.In view of the high temperature,high pressure and high stress,fracture development,wellbore instability,drilling fluid lost circulation and other problems faced in the process of deep and ultra-deep complex oil and gas drilling,scholars have developed deep and ultra-deep high-temperature and high-salt resistant water-based drilling fluid technology,high-temperature resistant oil-based/synthetic drilling fluid technology,drilling fluid technology for reservoir protection and drilling fluid lost circulation control technology.However,there are still some key problems such as insufficient resistance to high temperature,high pressure and high stress,wellbore instability and serious lost circulation.Therefore,the development direction of deep and ultra-deep drilling fluid technology in the future is proposed:(1)The technology of high-temperature and high-salt resistant water-based drilling fluid should focus on improving high temperature stability,improving rheological properties,strengthening filtration control and improving compatibility with formation.(2)The technology of oil-based/synthetic drilling fluid resistant to high temperature should further study in the aspects of easily degradable environmental protection additives with low toxicity such as high temperature stabilizer,rheological regulator and related supporting technologies.(3)The drilling fluid technology for reservoir protection should be devoted to the development of new high-performance additives and materials,and further improve the real-time monitoring technology by introducing advanced sensor networks and artificial intelligence algorithms.(4)The lost circulation control of drilling fluid should pay more attention to the integration and application of intelligent technology,the research and application of high-performance plugging materials,the exploration of diversified plugging techniques and methods,and the improvement of environmental protection and production safety awareness.
文摘Purpose: Few studies have evaluated the association between malnutrition and the risk of preoperative deep vein thrombosis (DVT) in patients undergoing primary total joint arthroplasty. This study aimed to investigate the prevalence of preoperative DVT in Japanese patients undergoing total knee arthroplasty (TKA) and the importance of malnutrition in the risk of preoperative DVT. Methods: We retrospectively analyzed 394 patients admitted for primary TKA at our institution between January 2019 and December 2023. All patients scheduled for TKA at our institution had serum D-dimer levels measured preoperatively. Lower-limb ultrasonography was examined to confirm the presence of DVT in patients with D-dimer levels ≥ 1.0 µg/mL or who were considered to be at high risk of DVT by the treating physician. Based on the results of lower-limb ultrasonography, all patients were divided into the non-DVT and DVT groups. The incidence of and risk factors for preoperative DVT were investigated, as well as the correlation of DVT with the patient’s nutritional parameters. We used two representative tools for nutritional assessment: the Geriatric Nutritional Risk Index (GNRI) and Controlling Nutritional Status Score. Results: The mean age was 77.8 ± 6.9 years. Preoperative DVT was diagnosed in 57 of the 394 (14.5%) patients. Multivariate logistic regression analysis showed that advanced age and malnutrition status, assessed using the GNRI, were independent risk factors for preoperative DVT. Conclusion: A high incidence of preoperative DVT was observed in patients who underwent TKA. Malnutrition status, as assessed using the GNRI, increased the risk of preoperative DVT. Our findings suggest that clinicians should consider these factors when tailoring preventive strategies to mitigate DVT risk in patients undergoing TKA.
文摘Aiming at the problems of large deformation and difficult maintenance of deep soft rock roadway under the influence of high ground stress and strong dynamic pressure, taking the surrounding rock control of 1105 lane in Hudi Coal Industry as an example, the deformation characteristics and surrounding rock control measures of deep soft rock roadway are analyzed and discussed by means of geological data analysis, roadway deformation monitoring, rock crack drilling and field test. The results show that the main causes of roadway deformation are high ground stress, synclinal tectonic stress, advance mining stress, roadway penetration and surrounding rock fissure development. Based on the deformation characteristics and mechanism of lane 1105, the supporting countermeasures of “roof synergic support, layered grouting, anchor cable beam support, closed hardening of roadway surface” are proposed, which can provide reference for the control of deep roadway surrounding rock under similar conditions.
基金Supported by the Agricultural Science and Technology Innovation Funds of Jiangsu(cx(12)1001-04)~~
文摘Deep-Litter System is a high yield approach to raise swine with pollution free in a lower cost. In the research, based on the heat stress in summer caused by fermentation, three temperature-control systems were designed, including natural ventilation through transoms, forced ventilation via fans, and cooling by hyperbaric spray system. Specifically, the latter intermittent auto-pressurized spray system developed in our lab, which could spray successively via pressure from storage tubes without wetting the fermentation bed, is suitable for the promotion with the deep-litter technology in rural regions , since the power consumption is only 1 kwh per day.
