Drilling-based measuring method for the c-φ parameter of rock and its field application

The technology of drilling tests makes it possible to obtain the strength parameter of rock accurately in situ. In this paper, a new rock cutting analysis model that considers the influence of the rock crushing zone(RCZ) is built. The formula for an ultimate cutting force is established based on the limit equilibrium principle. The relationship between digital drilling parameters(DDP) and the c-φ parameter(DDP-cφ formula, where c refers to the cohesion and φ refers to the internal friction angle) is derived, and the response of drilling parameters and cutting ratio to the strength parameters is analyzed. The drillingbased measuring method for the c-φ parameter of rock is constructed. The laboratory verification test is then completed, and the difference in results between the drilling test and the compression test is less than 6%. On this basis, in-situ rock drilling tests in a traffic tunnel and a coal mine roadway are carried out, and the strength parameters of the surrounding rock are effectively tested. The average difference ratio of the results is less than 11%, which verifies the effectiveness of the proposed method for obtaining the strength parameters based on digital drilling. This study provides methodological support for field testing of rock strength parameters.

The evolution of robotics:research and application progress of dental implant robotic systems

The use of robots to augment human capabilities and assist in work has long been an aspiration.Robotics has been developing since the 1960s when the first industrial robot was introduced.As technology has advanced,robotic-assisted surgery has shown numerous advantages,including more precision,efficiency,minimal invasiveness,and safety than is possible with conventional techniques,which are research hotspots and cutting-edge trends.This article reviewed the history of medical robot development and seminal research papers about current research progress.Taking the autonomous dental implant robotic system as an example,the advantages and prospects of medical robotic systems would be discussed which would provide a reference for future research.

Potential industrial applications of photo/electrocatalysis: Recent progress and future challenges

Nowadays,the rapid development of the social economy inevitably leads to global energy and environmental crisis.For this reason,more and more scholars focus on the development of photocatalysis and/or electrocatalysis technology for the advantage in the sustainable production of high-value-added products,and the high efficiency in pollutants remediation.Although there is plenty of outstanding research has been put forward continuously,most of them focuses on catalysis performance and reaction mechanisms in laboratory conditions.Realizing industrial application of photo/electrocatalytic processes is still a challenge that needs to be overcome by social demand.In this regard,this review comprehensively summarized several explorations in thefield of photo/electrocatalytic reduction towards potential industrial applications in recent years.Special attention is paid to the successful attempts and the current status of photo/electrocatalytic water splitting,carbon dioxide conversion,resource utilization from waste,etc.,by using advanced reactors.The key problems and challenges of photo/electrocatalysis in future industrial practice are also discussed,and the possible development directions are also pointed out from the industry view.

MXene-Based Elastomer Mimetic StretchableSensors: Design, Properties, and Applications

Flexible sensors based on MXene-polymer composites are highly prospective for next-generation wearable electronics used in human-machine interfaces.One of the motivating factors behind the progress of flexible sensors is the steady arrival of new conductive materials.MXenes,a new family of 2D nanomaterials,have been draw-ing attention since the last decade due to their high electronic conduc-tivity,processability,mechanical robustness and chemical tunability.In this review,we encompass the fabrication of MXene-based polymeric nanocomposites,their structure-property relationship,and applications in the flexible sensor domain.Moreover,our discussion is not only lim-ited to sensor design,their mechanism,and various modes of sensing platform,but also their future perspective and market throughout the world.With our article,we intend to fortify the bond between flexible matrices and MXenes thus promoting the swift advancement of flexible MXene-sensors for wearable technologies.

Comprehensive Evaluation of Flower Border Application Value of New and Superior Plants in Hefei Area

An analytic hierarchy process(AHP)was employed to assess the applicability of 18 new and superior varieties of flowers in Hefei City flower border applications.A total of 12 indicators were selected from three distinct aspects of adaptability,ornamental characteristics and use traits,in order to establish a comprehensive evaluation model.The results demonstrate that grade I(J≥2.685)exhibits excellent application value,encompassing six species of plants,such asHydrangeamacrophylla‘Endless Summer’;grade II(2.684≤J≤2.420)is also of notable application value,encompassing five species of plants,such asCallistemonrigidus;grade III(2.419≤J≤2.615)is of average application value,including five species of plants,such asCrocosmiacrocosmiflora;grade IV(J≤2.16)is of relatively poor application value.The evaluation results may be utilized as a theoretical reference for the promotion of new and superior varieties in the flower border of Hefei.

The Application of Bilayer Artificial Dermis Combined with VSD Technology in Chronic Wounds

Background: Bilayer artificial dermis promotes wound healing and offers a treatment option for chronic wounds. Aim: Examine the clinical efficacy of bilayer artificial dermis combined with Vacuum Sealing Drainage (VSD) technology in the treatment of chronic wounds. Method: From June 2021 to December 2023, our hospital treated 24 patients with chronic skin tissue wounds on their limbs using a novel tissue engineering product, the bilayer artificial dermis, in combination with VSD technology to repair the wounds. The bilayer artificial dermis protects subcutaneous tissue, blood vessels, nerves, muscles, and tendons, and also promotes the growth of granulation tissue and blood vessels to aid in wound healing when used in conjunction with VSD technology for wound dressing changes in chronic wounds. Results: In this study, 24 cases of chronic wounds with exposed bone or tendon larger than 1.0 cm2 were treated with a bilayer artificial skin combined with VSD dressing after wound debridement. The wounds were not suitable for immediate skin grafting. At 2 - 3 weeks post-treatment, good granulation tissue growth was observed. Subsequent procedures included thick skin grafting or wound dressing changes until complete wound healing. Patients were followed up on average for 3 months (range: 1 - 12 months) post-surgery. Comparative analysis of the appearance, function, skin color, elasticity, and sensation of the healed chronic wounds revealed superior outcomes compared to traditional skin fl repairs, resulting in significantly higher satisfaction levels among patients and their families. Conclusion: The application of bilayer artificial dermis combined with VSD technology for the repair of chronic wounds proves to be a viable method, yielding satisfactory therapeutic effects compared to traditional skin flap procedures.

Spatiotemporal variations of sand hydraulic conductivity by microbial application methods

The spatiotemporal distributions of microbes in soil by different methods could affect the efficacy of the microbes to reduce the soil hydraulic conductivity.In this study,the specimens of bio-mediated sands were prepared using three different methods,i.e.injecting,mixing,and pouring a given microbial so-lution onto compacted sand specimens.The hydraulic conductivity was measured by constant-head tests,while any soil microstructural changes due to addition of the microbes were observed by scan-ning electron microscope(SEM)and mercury intrusion porosimetry(MIP)tests.The amount of dextran concentration produced by microbes in each type of specimen was quantified by a refractometer.Results show that dextran production increased exponentially after 5-7 d of microbial settling with the supply of culture medium.The injection and mixing methods resulted in a similar amount and uniform dis-tribution of dextran in the specimens.The pouring method,however,produced a nonuniform distri-bution,with a higher concentration near the specimen surface.As the supply of culture medium discontinued,the dextran content near the surface produced by the pouring method decreased dramatically due to high competition for nutrients with foreign colonies.Average dextran concentration was negatively and correlated with hydraulic conductivity of bio-mediated soils exponentially,due to the clogging of large soil pores by dextran.The hydraulic conductivity of the injection and mixing cases did not change significantly when the supply of culture medium was absent.

Study on the Application of Refined Nursing Care in The Care for Elderly Patients with Reflux Esophagitis

Objective: To investigate the application effect of refined nursing care in the care for elderly patients with reflux esophagitis. Methods: Following the difference in nursing style, 84 cases of elderly patients with reflux esophagitis admitted to our hospital from May 2022 to May 2023 were randomly grouped into a control group and a research group, with 42 cases each. The control group was given conventional nursing care and the research group was given refined nursing care. The psychological state and treatment adherence of the two groups of patients after the nursing intervention were compared. Results: After the nursing intervention, the self-rating anxiety scale (SAS) and self-rating depression scale (SDS) scores of the research group were lower than those of the control group (P < 0.05). The treatment compliance of the research group was better than the control group (P < 0.05). Conclusion: The implementation of refined nursing care for elderly patients with reflux esophagitis exhibited a significant effect on improving the patient’s psychological state, treatment compliance, and rehabilitation.

Enriching Iodine and Regulating Grain Aroma,Appearance Quality,and Yield in Aromatic Rice by Foliar Application of Sodium Iodide

Applying iodine fertilizers to cultivate iodine-rich crops for daily intake is an effective approach for iodine supplementation,especially for aromatic rice.Field experiments were conducted during the early growing seasons of 2021 and 2022 to evaluate the impacts of foliar application of iodine fertilizer on aromatic rice and to explore the optimal iodine fertilizer concentration.At the full heading stage,six different concentrations of sodium iodide solutions of 0%(CK),0.010%(T1),0.025%(T2),0.050%(T3),0.075%(T4),and 0.100%(T5)were applied to indica aromatic rice cultivars Meixiangzhan 2 and Xiangyaxiangzhan.The results showed that sodium iodide treatments significantly increased the iodine and sodium contents in both leaves and grains.Compared with the CK,the T1 and T2 treatments increased the 2-acetyl-1-pyrroline(2-AP)content in mature grains by 8.41%-101.66%and 13.58%-74.60%,respectively.Improvements in the contents of 1-pyrroline-5-carboxylic acid,proline,1-pyrroline,and methylglyoxal,as well as the activity of proline dehydrogenase were also detected.Additionally,sodium iodide treatments remarkably decreased the chalky grain rate,chalkiness area,and chalkiness degree of aromatic rice,with the T2 treatment exhibiting a 17.79%-47.42%decrease in chalkiness degree compared with the CK.Meanwhile,T1 and T2 treatments showed beneficial impacts on chlorophyll content,photosynthetic characteristics,and yield components,while T3,T4,and T5 treatments exhibited adverse effects on leaf and grain yields.The linear discriminant analysis revealed significant differences between treatments.The correlation analysis and piecewise structural equation modeling showed that the iodine and sodium influenced the photosynthetic characteristics and chlorophyll content of the leaves,thereby regulating the 2-AP biosynthesis and yield components,ultimately affecting the 2-AP content and yield.Overall,this study suggests that foliar application of 0.025%sodium iodide is an effective method to enrich the iodine content in rice grains,improve the grain aroma and appearance quality of aromatic rice,without detrimental effects on grain yield.

In Situ Polymer Gel Electrolyte in Boosting Scalable Fibre Lithium Battery Applications

The poor interfacial stability not only deteriorates fibre lithium-ion batteries(FLBs)performance but also impacts their scalable applications.To efficiently address these challenges,Prof.Huisheng Peng team proposed a generalized channel structures strategy with optimized in situ polymerization technology in their recent study.The resultant FLBs can be woven into different-sized powering textiles,providing a high energy density output of 128 Wh kg^(-1) and simultaneously demonstrating good durability even under harsh conditions.Such a promising strategy expands the horizon in developing FLB with particular polymer gel electrolytes,and significantly ever-deepening understanding of the scaled wearable energy textile system toward a sustainable future.

PDOL-Based Solid Electrolyte Toward Practical Application:Opportunities and Challenges

Polymer solid-state lithium batteries(SSLB)are regarded as a promising energy storage technology to meet growing demand due to their high energy density and safety.Ion conductivity,interface stability and battery assembly process are still the main challenges to hurdle the commercialization of SSLB.As the main component of SSLB,poly(1,3-dioxolane)(PDOL)-based solid polymer electrolytes polymerized in-situ are becoming a promising candidate solid elec-trolyte,for their high ion conductivity at room temperature,good battery elec-trochemical performances,and simple assembly process.This review analyzes opportunities and challenges of PDOL electrolytes toward practical application for polymer SSLB.The focuses include exploring the polymerization mechanism of DOL,the performance of PDOL composite electrolytes,and the application of PDOL.Furthermore,we provide a perspective on future research directions that need to be emphasized for commercialization of PDOL-based electrolytes in SSLB.The exploration of these schemes facilitates a comprehensive and profound understanding of PDOL-based polymer electrolyte and provides new research ideas to boost them toward practical application in solid-state batteries.

AWeb Application Fingerprint Recognition Method Based on Machine Learning

Web application fingerprint recognition is an effective security technology designed to identify and classify web applications,thereby enhancing the detection of potential threats and attacks.Traditional fingerprint recognition methods,which rely on preannotated feature matching,face inherent limitations due to the ever-evolving nature and diverse landscape of web applications.In response to these challenges,this work proposes an innovative web application fingerprint recognition method founded on clustering techniques.The method involves extensive data collection from the Tranco List,employing adjusted feature selection built upon Wappalyzer and noise reduction through truncated SVD dimensionality reduction.The core of the methodology lies in the application of the unsupervised OPTICS clustering algorithm,eliminating the need for preannotated labels.By transforming web applications into feature vectors and leveraging clustering algorithms,our approach accurately categorizes diverse web applications,providing comprehensive and precise fingerprint recognition.The experimental results,which are obtained on a dataset featuring various web application types,affirm the efficacy of the method,demonstrating its ability to achieve high accuracy and broad coverage.This novel approach not only distinguishes between different web application types effectively but also demonstrates superiority in terms of classification accuracy and coverage,offering a robust solution to the challenges of web application fingerprint recognition.

Advancing 5G Network Applications Lifecycle Security:An ML-Driven Approach

As 5th Generation(5G)and Beyond 5G(B5G)networks become increasingly prevalent,ensuring not only networksecurity but also the security and reliability of the applications,the so-called network applications,becomesof paramount importance.This paper introduces a novel integrated model architecture,combining a networkapplication validation framework with an AI-driven reactive system to enhance security in real-time.The proposedmodel leverages machine learning(ML)and artificial intelligence(AI)to dynamically monitor and respond tosecurity threats,effectively mitigating potential risks before they impact the network infrastructure.This dualapproach not only validates the functionality and performance of network applications before their real deploymentbut also enhances the network’s ability to adapt and respond to threats as they arise.The implementation ofthis model,in the shape of an architecture deployed in two distinct sites,demonstrates its practical viability andeffectiveness.Integrating application validation with proactive threat detection and response,the proposed modeladdresses critical security challenges unique to 5G infrastructures.This paper details the model,architecture’sdesign,implementation,and evaluation of this solution,illustrating its potential to improve network securitymanagement in 5G environments significantly.Our findings highlight the architecture’s capability to ensure boththe operational integrity of network applications and the security of the underlying infrastructure,presenting asignificant advancement in network security.

Time Parameter Based Low-Energy Data Encryption Method for Mobile Applications

Various mobile devices and applications are now used in daily life.These devices require high-speed data processing,low energy consumption,low communication latency,and secure data transmission,especially in 5G and 6G mobile networks.High-security cryptography guarantees that essential data can be transmitted securely;however,it increases energy consumption and reduces data processing speed.Therefore,this study proposes a low-energy data encryption(LEDE)algorithm based on the Advanced Encryption Standard(AES)for improving data transmission security and reducing the energy consumption of encryption in Internet-of-Things(IoT)devices.In the proposed LEDE algorithm,the system time parameter is employed to create a dynamic S-Box to replace the static S-Box of AES.Tests indicated that six-round LEDE encryption achieves the same security level as 10-round conventional AES encryption.This reduction in encryption time results in the LEDE algorithm having a 67.4%lower energy consumption and 43.9%shorter encryption time than conventional AES;thus,the proposed LEDE algorithm can improve the performance and the energy consumption of IoT edge devices.

Selection and application of four QTLs for grain protein content in modern wheat cultivars

The grain protein content(GPC)is the key parameter for wheat grain nutritional quality.This study conducted a resampling GWAS analysis using 406 wheat accessions across eight environments,and identified four previously reported GPC QTLs.An analysis of 87 landraces and 259 modern cultivars revealed the loss of superior GPC haplotypes,especially in Chinese cultivars.These haplotypes were preferentially adopted in different agroecological zones and had broad effects on wheat yield and agronomic traits.Most GPC QTLs did not significantly reduce yield,suggesting that high GPC can be achieved without a yield penalty.The results of this study provide a reference for future GPC breeding in wheat using the four identified QTLs.

Magnesium fertilizer application increases peanut growth and pod yield under reduced nitrogen application in southern China

This study investigated the effect of magnesium application on peanut growth and yield under two nitrogen(N)application rates in acidic soil in southern China.The chlorophyll content,net photosynthetic rate and dry matter accumulation of the N-sensitive cultivar decreased under reduced N treatments,whereas no effect was observed on the relevant indicators in the N-insensitive variety GH1026.Mg application increased the net photosynthetic rate by increasing the expression of genes involved in chlorophyll synthesis and Rubisco activity in the leaves during the pegging stage under 50%N treatment,while no effect on the net photosynthetic rate was observed under the 100%N treatment.The rate of dry matter accumulation at the early growth stage,total dry matter accumulation and pod yield at harvest increased after Mg application under 50%N treatment by increasing the transportation of assimilates from stems and leaves to pods in both peanut varieties,whereas no effect was found under 100%N treatment.Moreover,Mg application increased the NUE under 50%N treatment.No improvement of NUE in either peanut variety was found under 100%N treatment,while Mg application under the 50%N treatment can obtain a higher economic benefit than the 100%N treatment.In acidic soil,application of 307.5 kg ha^(-1)of Mg sulfate fertilizer under 50%reduced nitrogen application is a suitable fertilizer management measure for improving carbon assimilation,NUE and achieve high peanut yields in southern China.

Big Data Application Simulation Platform Design for Onboard Distributed Processing of LEO Mega-Constellation Networks

Due to the restricted satellite payloads in LEO mega-constellation networks(LMCNs),remote sensing image analysis,online learning and other big data services desirably need onboard distributed processing(OBDP).In existing technologies,the efficiency of big data applications(BDAs)in distributed systems hinges on the stable-state and low-latency links between worker nodes.However,LMCNs with high-dynamic nodes and long-distance links can not provide the above conditions,which makes the performance of OBDP hard to be intuitively measured.To bridge this gap,a multidimensional simulation platform is indispensable that can simulate the network environment of LMCNs and put BDAs in it for performance testing.Using STK's APIs and parallel computing framework,we achieve real-time simulation for thousands of satellite nodes,which are mapped as application nodes through software defined network(SDN)and container technologies.We elaborate the architecture and mechanism of the simulation platform,and take the Starlink and Hadoop as realistic examples for simulations.The results indicate that LMCNs have dynamic end-to-end latency which fluctuates periodically with the constellation movement.Compared to ground data center networks(GDCNs),LMCNs deteriorate the computing and storage job throughput,which can be alleviated by the utilization of erasure codes and data flow scheduling of worker nodes.

A novel fracture-cavity reservoir outcrop geological knowledge base construction method considering parameter collection and processing,mutual transformation of data-knowledge,application and update

This study endeavors to formulate a comprehensive methodology for establishing a Geological Knowledge Base(GKB)tailored to fracture-cavity reservoir outcrops within the North Tarim Basin.The acquisition of quantitative geological parameters was accomplished through diverse means such as outcrop observations,thin section studies,unmanned aerial vehicle scanning,and high-resolution cameras.Subsequently,a three-dimensional digital outcrop model was generated,and the parameters were standardized.An assessment of traditional geological knowledge was conducted to delineate the knowledge framework,content,and system of the GKB.The basic parameter knowledge was extracted using multiscale fine characterization techniques,including core statistics,field observations,and microscopic thin section analysis.Key mechanism knowledge was identified by integrating trace elements from filling,isotope geochemical tests,and water-rock simulation experiments.Significant representational knowledge was then extracted by employing various methods such as multiple linear regression,neural network technology,and discriminant classification.Subsequently,an analogy study was performed on the karst fracture-cavity system(KFCS)in both outcrop and underground reservoir settings.The results underscored several key findings:(1)Utilization of a diverse range of techniques,including outcrop observations,core statistics,unmanned aerial vehicle scanning,high-resolution cameras,thin section analysis,and electron scanning imaging,enabled the acquisition and standardization of data.This facilitated effective management and integration of geological parameter data from multiple sources and scales.(2)The GKB for fracture-cavity reservoir outcrops,encompassing basic parameter knowledge,key mechanism knowledge,and significant representational knowledge,provides robust data support and systematic geological insights for the intricate and in-depth examination of the genetic mechanisms of fracture-cavity reservoirs.(3)The developmental characteristics of fracturecavities in karst outcrops offer effective,efficient,and accurate guidance for fracture-cavity research in underground karst reservoirs.The outlined construction method of the outcrop geological knowledge base is applicable to various fracture-cavity reservoirs in different layers and regions worldwide.

Heating of nanoparticles and their environment by laser radiation and applications

This review considers the fundamental dynamic processes involved in the laser heating of metal nanoparticles and their subsequent cooling.Of particular interest are the absorption of laser energy by nanoparticles,the heating of a single nanoparticle or an ensemble thereof,and the dissipation of the energy of nanoparticles due to heat exchange with the environment.The goal is to consider the dependences and values of the temperatures of the nanoparticles and the environment,their time scales,and other parameters that describe these processes.Experimental results and analytical studies on the heating of single metal nanoparticles by laser pulses are discussed,including the laser thresholds for initiating subsequent photothermal processes,how temperature influences the optical properties,and the heating of gold nanoparticles by laser pulses.Experimental studies of the heating of an ensemble of nanoparticles and the results of an analytical study of the heating of an ensemble of nanoparticles and the environment by laser radiation are considered.Nanothermometry methods for nanoparticles under laser heating are considered,including changes in the refractive indices of metals and spectral thermometry of optical scattering of nanoparticles,Raman spectroscopy,the thermal distortion of the refractive index of an environment heated by a nanoparticle,and thermochemical phase transitions in lipid bilayers surrounding a heated nanoparticle.Understanding the sequence of events after radiation absorption and their time scales underlies many applications of nanoparticles.The applicationfields for the laser heating of nanoparticles are reviewed,including thermochemical reactions and selective nanophotothermolysis initiated in the environment by laser-heated nanoparticles,thermal radiation emission by nanoparticles and laser-induced incandescence,electron and ion emission of heated nanoparticles,and optothermal chemical catalysis.Applications of the laser heating of nanoparticles in laser nanomedicine are of particular interest.Significant emphasis is given to the proposed analytical approaches to modeling and calculating the heating processes under the action of a laser pulse on metal nanoparticles,taking into account the temperature dependences of the parameters.The proposed models can be used to estimate the parameters of lasers and nanoparticles in the various applicationfields for the laser heating of nanoparticles.

Hybrid Approach for Cost Efficient Application Placement in Fog-Cloud Computing Environments

Fog computing has recently developed as a new paradigm with the aim of addressing time-sensitive applications better than with cloud computing by placing and processing tasks in close proximity to the data sources.However,the majority of the fog nodes in this environment are geographically scattered with resources that are limited in terms of capabilities compared to cloud nodes,thus making the application placement problem more complex than that in cloud computing.An approach for cost-efficient application placement in fog-cloud computing environments that combines the benefits of both fog and cloud computing to optimize the placement of applications and services while minimizing costs.This approach is particularly relevant in scenarios where latency,resource constraints,and cost considerations are crucial factors for the deployment of applications.In this study,we propose a hybrid approach that combines a genetic algorithm(GA)with the Flamingo Search Algorithm(FSA)to place application modules while minimizing cost.We consider four cost-types for application deployment:Computation,communication,energy consumption,and violations.The proposed hybrid approach is called GA-FSA and is designed to place the application modules considering the deadline of the application and deploy them appropriately to fog or cloud nodes to curtail the overall cost of the system.An extensive simulation is conducted to assess the performance of the proposed approach compared to other state-of-the-art approaches.The results demonstrate that GA-FSA approach is superior to the other approaches with respect to task guarantee ratio(TGR)and total cost.