I.INTRODUCTION Against the backdrop of profound transformations in the global energy landscape,China,as the world's largest energy producer and consumer,faces multiple challenges,including energy security,energy t...I.INTRODUCTION Against the backdrop of profound transformations in the global energy landscape,China,as the world's largest energy producer and consumer,faces multiple challenges,including energy security,energy transition,and sustainable development.To address these challenges,the Chinese government has formulated a strategic plan to build a unified national energy market and create a new framework for the energy sector.Article 42 of the Energy Law of the People's Republic of China(hereinafter referred to as the Energy Law)explicitly requires the building of a unified national energy trading market and the improvement of transaction mechanisms and rules.展开更多
Human life is not determined by mechanical fatalism or a single material factor;instead,based on the dualistic ontology and active force mechanism in the Unified Complex Systems Theory(UCST),it can be actively designe...Human life is not determined by mechanical fatalism or a single material factor;instead,based on the dualistic ontology and active force mechanism in the Unified Complex Systems Theory(UCST),it can be actively designed under the guidance of mind,in accordance with causal laws,and through systematic interactions.This study integrates the dualistic ontology of UCST,as well as the cooperative mechanism of active force(Fa)and passive force(Fp).Furthermore,by incorporating Master Jiqun’s philosophy of“life design”and the practical principle of“destiny establishment and transformation”from The Four Lessons of Liaofan Yuan,it constructs a three-dimensional framework for life design encompassing the dimensions of science,philosophy,and practice.The significance of this research lies in breaking through the predicament of materialism in the AI(artificial intelligence)era,explaining the autonomy and initiative of life,providing feasible pathways for life design,and ultimately achieving the in-depth integration of scientific rationality and the wisdom of traditional Eastern culture.展开更多
Despite advances in current anti-cancer therapies,challenges such as drug resistance,toxicity,and tumor heterogeneity persist.The limitations of traditional single-target drugs and simple combination therapies are bec...Despite advances in current anti-cancer therapies,challenges such as drug resistance,toxicity,and tumor heterogeneity persist.The limitations of traditional single-target drugs and simple combination therapies are becoming increasingly apparent1.To address these issues,a novel treatment strategy,the artificially intelligent synergistic engineered drug(AISED)paradigm,merits further exploration.This paradigm is based on the systematic engineered integration of multiple active ingredients into a unified single entity through artificial intelligence(AI).This strategy is aimed at developing new anti-cancer drug designs involving multiple ingredients,multiple molecular targets,and multiple biological effects,for multiple cancer types,thereby providing a novel theoretical paradigm for overcoming existing treatment bottlenecks.展开更多
Fractures are typically characterized by roughness that significantlyaffects the mechanical and hydraulic characteristics of reservoirs.However,hydraulic fracturing mechanisms under the influenceof fracture morphology...Fractures are typically characterized by roughness that significantlyaffects the mechanical and hydraulic characteristics of reservoirs.However,hydraulic fracturing mechanisms under the influenceof fracture morphology remain largely unexplored.Leveraging the advantages of the finite-discrete element method(FDEM)for explicitly simulating fracture propagation and the strengths of the unifiedpipe model(UPM)for efficientlymodeling dual-permeability seepage,we propose a new hydromechanical(HM)coupling approach for modeling hydraulic fracturing.Validated against benchmark examples,the proposed FDEM-UPM model is further augmented by incorporating a Fourier-based methodology for reconstructing non-planar fractures,enabling quantitative analysis of hydraulic fracturing behavior within rough discrete fracture networks(DFNs).The FDEM-UPM model demonstrates computational advantages in accurately capturing transient hydraulic seepage phenomena,while the asynchronous time-stepping schemes between hydraulic and mechanical analyses substantially enhanced computational efficiencywithout compromising computational accuracy.Our results show that fracture morphology can affect both macroscopic fracture networks and microscopic interaction types between hydraulic fractures(HFs)and natural fractures(NFs).In an isotropic stress field,the initiation azimuth,propagation direction and microcracking mechanism are significantly influencedby fracture roughness.In an anisotropic stress field,HFs invariably propagate parallel to the direction of the maximum principal stress,reducing the overall complexity of the stimulated fracture networks.Additionally,stress concentration and perturbation attributed to fracture morphology tend to be compromised as the leak-off increases,while the breakdown and propagation pressures remain insensitive to fracture morphology.These findingsprovide new insights into the hydraulic fracturing mechanisms of fractured reservoirs containing complex rough DFNs.展开更多
Various factors,including weak tie-lines into the electric power system(EPS)networks,can lead to low-frequency oscillations(LFOs),which are considered an instant,non-threatening situation,but slow-acting and poisonous...Various factors,including weak tie-lines into the electric power system(EPS)networks,can lead to low-frequency oscillations(LFOs),which are considered an instant,non-threatening situation,but slow-acting and poisonous.Considering the challenge mentioned,this article proposes a clustering-based machine learning(ML)framework to enhance the stability of EPS networks by suppressing LFOs through real-time tuning of key power system stabilizer(PSS)parameters.To validate the proposed strategy,two distinct EPS networks are selected:the single-machine infinite-bus(SMIB)with a single-stage PSS and the unified power flow controller(UPFC)coordinated SMIB with a double-stage PSS.To generate data under various loading conditions for both networks,an efficient but offline meta-heuristic algorithm,namely the grey wolf optimizer(GWO),is used,with the loading conditions as inputs and the key PSS parameters as outputs.The generated loading conditions are then clustered using the fuzzy k-means(FKM)clustering method.Finally,the group method of data handling(GMDH)and long short-term memory(LSTM)ML models are developed for clustered data to predict PSS key parameters in real time for any loading condition.A few well-known statistical performance indices(SPI)are considered for validation and robustness of the training and testing procedure of the developed FKM-GMDH and FKM-LSTM models based on the prediction of PSS parameters.The performance of the ML models is also evaluated using three stability indices(i.e.,minimum damping ratio,eigenvalues,and time-domain simulations)after optimally tuned PSS with real-time estimated parameters under changing operating conditions.Besides,the outputs of the offline(GWO-based)metaheuristic model,proposed real-time(FKM-GMDH and FKM-LSTM)machine learning models,and previously reported literature models are compared.According to the results,the proposed methodology outperforms the others in enhancing the stability of the selected EPS networks by damping out the observed unwanted LFOs under various loading conditions.展开更多
For mission-oriented unmanned aerial vehicle(UAV)swarms,mission capability assessment provides an important reference in the design and development process,and is a precondition for mission success.For this multi-crit...For mission-oriented unmanned aerial vehicle(UAV)swarms,mission capability assessment provides an important reference in the design and development process,and is a precondition for mission success.For this multi-criteria decisionmaking(MCDM)problem,the current literature lacks a way to unambiguously present criteria and the popular fuzzy analytic network process(ANP)approaches neglect the hesitancy of subjective judgments.To fill these research gaps,an MCDM method based on unified architecture framework(UAF)and interval-valued spherical fuzzy ANP(IVSF-ANP)is proposed in this paper.Firstly,selected viewpoints in UAF are extended to construct criteria models with standardized representation.Secondly,interval-valued spherical fuzzy sets are introduced to ANP to weight interdependent criteria,handling fuzziness and hesitancy in pairwise comparisons.A method of adjusting weights of experts based on their decision similarities is also included in this process to reduce ambiguity brought by multiple experts.Next,performance characteristics are non-linearly transformed regarding to expectations to get final results.This proposition is applied to assess the mission capability of UAV swarms to search and strike surface vessels.Comparative analysis shows that the proposed method is valid and reasonable.展开更多
对珠子参中皂苷类成分进行定性鉴别分析,建立珠子参皂苷类多成分含量测定方法。采用超高效液相色谱-飞行时间质谱(UPLC-Q-TOF-MS/MS)技术对珠子参进行正、负离子模式扫描,使用UNIFI天然产物信息平台对珠子参所含的化学成分进行定性鉴别...对珠子参中皂苷类成分进行定性鉴别分析,建立珠子参皂苷类多成分含量测定方法。采用超高效液相色谱-飞行时间质谱(UPLC-Q-TOF-MS/MS)技术对珠子参进行正、负离子模式扫描,使用UNIFI天然产物信息平台对珠子参所含的化学成分进行定性鉴别分析;以0.1%磷酸水-乙腈溶液为流动相进行梯度洗脱,柱温30℃,流速0.3 mL/min,进行珠子参皂苷类多成分含量测定。珠子参中共鉴定出39个化学成分,包括37个皂苷类化合物和2个皂苷母核,并总结了皂苷类化合物的裂解规律,建立了UPLC同时测定珠子参中人参皂苷Rb1、人参皂苷Ro、人参皂苷Rb3、竹节参皂苷IV、竹节参皂苷IVa、人参皂苷Rd、姜状三七皂苷R1和金盏花苷E的多指标含量测定方法,该方法中8个待测成分在检测质量浓度范围内线性关系良好,精密度、重复性、稳定性的相对标准偏差(relative standard deviation,RSD)均小于3.0%,样品中人参皂苷Rb1、人参皂苷Ro、人参皂苷Rb3、竹节参皂苷IV、竹节参皂苷IVa、人参皂苷Rd、姜状三七皂苷R1和金盏花苷E的平均加样回收率分别为102.4%、103.1%、97.97%、99.42%、102.7%、102.1%、95.23%、100.5%,RSD分别为1.0%、0.98%、0.81%、2.3%、0.81%、1.9%、0.96%、1.8%。该研究建立的方法可快速、准确地对珠子参中的皂苷类成分进行定性及定量分析。展开更多
If the singularity of the cosmic Big Bang is taken as the origin of the reference coordinate system,the surrounding vacuum in the initial moments of it would exhibit radially-outward right-handed spiral motion at ligh...If the singularity of the cosmic Big Bang is taken as the origin of the reference coordinate system,the surrounding vacuum in the initial moments of it would exhibit radially-outward right-handed spiral motion at light speed.Based on this spatial motion hypothesis,we derive a unified field equation and a set of Maxwell’s equations for vacuum SWs(Scalar Waves)generating a huge spiral force field that drives the energy to spiral inwardly and distort,leading to the formation of mass.Furthermore,they also uncover that mass is fundamentally an ultimate expression of energy,manifesting as the result of spiral motion of space at light speed.And then,we indirectly validate the theory that coherent light waves’collision generate SWs and subsequently mass through the experiment verifying the Breit-Wheeler process.The establishment of our theory offers a new analytical tool for the exploration of mass origin,the cosmic Big Bang,unified field theories.展开更多
Well logging technology has accumulated a large amount of historical data through four generations of technological development,which forms the basis of well logging big data and digital assets.However,the value of th...Well logging technology has accumulated a large amount of historical data through four generations of technological development,which forms the basis of well logging big data and digital assets.However,the value of these data has not been well stored,managed and mined.With the development of cloud computing technology,it provides a rare development opportunity for logging big data private cloud.The traditional petrophysical evaluation and interpretation model has encountered great challenges in the face of new evaluation objects.The solution research of logging big data distributed storage,processing and learning functions integrated in logging big data private cloud has not been carried out yet.To establish a distributed logging big-data private cloud platform centered on a unifi ed learning model,which achieves the distributed storage and processing of logging big data and facilitates the learning of novel knowledge patterns via the unifi ed logging learning model integrating physical simulation and data models in a large-scale functional space,thus resolving the geo-engineering evaluation problem of geothermal fi elds.Based on the research idea of“logging big data cloud platform-unifi ed logging learning model-large function space-knowledge learning&discovery-application”,the theoretical foundation of unified learning model,cloud platform architecture,data storage and learning algorithm,arithmetic power allocation and platform monitoring,platform stability,data security,etc.have been carried on analysis.The designed logging big data cloud platform realizes parallel distributed storage and processing of data and learning algorithms.The feasibility of constructing a well logging big data cloud platform based on a unifi ed learning model of physics and data is analyzed in terms of the structure,ecology,management and security of the cloud platform.The case study shows that the logging big data cloud platform has obvious technical advantages over traditional logging evaluation methods in terms of knowledge discovery method,data software and results sharing,accuracy,speed and complexity.展开更多
Downloads of national standards exceed 10 million times in the first half of 2025 In response to social needs,State Administration for Market Regulation(SAMR)had steadily promoted the full-text disclosure and free dow...Downloads of national standards exceed 10 million times in the first half of 2025 In response to social needs,State Administration for Market Regulation(SAMR)had steadily promoted the full-text disclosure and free download of over 30,000 national standards that do not adopt international standards since the beginning of this year.In the first half of 2025,downloads exceeded 10 million times,providing strong support for the construction of a unified national market.Social groups accessing national standards for free increased significantly.In the first half of this year,the average monthly downloads of national standards surged tenfold from 190,000 times last year to 2.03 million times.Online reading reached nearly 15 million times,and page views hit 89 million times.The disclosure of national standards for free has effectively broken information barriers in standards,ensuring equal rights for business entities to read and download national standards.展开更多
Vehicle recognition plays a vital role in intelligent transportation systems,law enforcement,access control,and security operations—domains that are becoming increasingly dynamic and complex.Despite advancements,most...Vehicle recognition plays a vital role in intelligent transportation systems,law enforcement,access control,and security operations—domains that are becoming increasingly dynamic and complex.Despite advancements,most existing solutions remain siloed,addressing individual tasks such as vehicle make and model recognition(VMMR),automatic number plate recognition(ANPR),and color classification separately.This fragmented approach limits real-world efficiency,leading to slower processing,reduced accuracy,and increased operational costs,particularly in traffic monitoring and surveillance scenarios.To address these limitations,we present a unified framework that consolidates all three recognition tasks into a single,lightweight system.The framework utilizes MobileNetV2 for efficient VMMR,YOLO(You Only Look Once)for accurate license plate detection,and histogram-based clustering in the HSV color space for precise color identification.Rather than optimizing each module in isolation,our approach emphasizes tight integration,enabling improved performance and reliability.The system also features adaptive image calibration and robust algorithmic enhancements to ensure consistent results under varying environmental conditions.Experimental evaluations demonstrate that the proposedmodel achieves a combined accuracy of 93.3%,outperforming traditional methods and offering practical scalability for deployment in real-world transportation infrastructures.展开更多
In March 2025,prominent Chinese automaker NIO(Shanghai,China),the global leader in electric vehicle(EV)battery swapping,and Contemporary Amperex Technology Co.,Ltd.(CATL)(Nindge,China),the world’s biggest manufacture...In March 2025,prominent Chinese automaker NIO(Shanghai,China),the global leader in electric vehicle(EV)battery swapping,and Contemporary Amperex Technology Co.,Ltd.(CATL)(Nindge,China),the world’s biggest manufacturer of EV batteries,announced a strategic partnership to build the world’s largest battery swapping network,while also promoting unified standards and technologies[1].Just weeks later,CATL announced another partnership,this one with Chinese state-owned oil giant Sinopec(Beijing,China)to build 10000 new battery swapping stations in China,at least 500 in 2025[2].展开更多
As important natural and pharmaceutical motifs,the catalytic construction of structurally diverse 3,3-disubstituted oxindoles often requires elaborate synthetic efforts on optimizations.Herein,we developed a simple an...As important natural and pharmaceutical motifs,the catalytic construction of structurally diverse 3,3-disubstituted oxindoles often requires elaborate synthetic efforts on optimizations.Herein,we developed a simple and divergent approach for constructing reverse-prenylated and prenylated oxindoles launched by Ni catalysis with bulk chemical isoprene.Using C3-unsubstituted oxindoles as starting materials,mono reverse-prenylation was demonstrated in high chemo-and regioselectivities facilitated by the combination of Ni(0)and monodentate phosphine ligand.Using the obtained reverse-prenylated oxindoles as versatile synthon,substitutions at the pseudobenzylic position with various electrophiles created vicinal quaternary centers in a concise way.With the help of additives(PPh3 and NaH),air could be directly used as green oxidant to construct prenylated and reverse-prenylatedα-hydroxy-oxindoles divergently from the same substrates.In situ esterification of prenylatedα-hydroxy-oxindoles allowed subsequent Friedel-Crafts substitutions with diverse nucleophiles to deliver prenyl substituted dimeric or spiro-oxindoles.This protocol provides a divergent synthetic approach for the construction of highly functionalized 3,3-disubstituted oxindoles,which have been otherwise difficult to access in a unified approach.展开更多
Ground reinforcement is crucial for tunnel construction, especially in soft rock tunnels. Existing analytical models are inadequate for predicting the ground reaction curves (GRCs) for reinforced tunnels in strain-sof...Ground reinforcement is crucial for tunnel construction, especially in soft rock tunnels. Existing analytical models are inadequate for predicting the ground reaction curves (GRCs) for reinforced tunnels in strain-softening (SS) rock masses. This study proposes a novel analytical model to determine the GRCs of SS rock masses, incorporating ground reinforcement and intermediate principal stress (IPS). The SS constitutive model captures the progressive post- peak failure, while the elastic-brittle model simulates reinforced rock masses. Nine combined states are innovatively investigated to analyze plastic zone development in natural and reinforced regions. Each region is analyzed separately, and coupled through boundary conditions at interface. Comparison with three types of existing models indicates that these models overestimate reinforcement effects. The deformation prediction errors of single geological material models may exceed 75%. Furthermore, neglecting softening and residual zones in natural regions could lead to errors over 50%. Considering the IPS can effectively utilize the rock strength to reduce tunnel deformation by at least 30%, thereby saving on reinforcement and support costs. The computational results show a satisfactory agreement with the monitoring data from a model test and two tunnel projects. The proposed model may offer valuable insights into the design and construction of reinforced tunnel engineering.展开更多
The stress gradient of surrounding rock and reasonable prestress of support are the keys to ensuring the stability of roadways.The elastic-plastic analytical solution for surrounding rock was derived based on unified ...The stress gradient of surrounding rock and reasonable prestress of support are the keys to ensuring the stability of roadways.The elastic-plastic analytical solution for surrounding rock was derived based on unified strength theory.A model for solving the stress gradient of the surrounding rock with the intermediate principal stress parameter b was established.The correctness and applicability of the solution for the stress gradient in the roadway surrounding rock was verified via multiple methods.Furthermore,the laws of stress,displacement,and the plastic zone of the surrounding rock with different b values and prestresses were revealed.As b increases,the stress gradient in the plastic zone increases,and the displacement and plastic zone radius decrease.As the prestress increases,the peak stress shifts toward the sidewalls,and the stress and stress gradient increments decrease.In addition,the displacement increment and plastic zone increment were proposed to characterize the support effect.The balance point of the plastic zone area appears before that of the displacement zone.The relationship between the stress gradient compensation coefficient and the prestress is obtained.This study provides a research method and idea for determining the reasonable prestress of support in roadways.展开更多
This paper presents a multi-scale experimental investigation of the weathering degradation of red mudstone.Natural rocks were extracted from the surface ground to 120 m,inwhich three sets of samples were selected to c...This paper presents a multi-scale experimental investigation of the weathering degradation of red mudstone.Natural rocks were extracted from the surface ground to 120 m,inwhich three sets of samples were selected to consider the different initial rock fabrics.The long-term relative humidity(RH)cycles under two amplitudes were imposed on red mudstone to simulate the weathering process.After RH cycles,a series of uniaxial compression tests,Brazilian splitting tests and bender-extender element tests were carried out to examine the reduction in strength and stiffness.The objective of this study is to develop an extended stress-volume framework characterizing the degradation of natural red mudstone both at microscale and macroscale.Accompanied by the irreversible swelling of the rock specimen is the progressive degradation of strength,stiffness and Poisson's ratio.A unified exponential degradation model in terms of the irreversible volumetric strain was thus proposed to capture such a degradation pattern.The effect of the initial rock fabric was evident.The highest degradation rate and potential were identified in slightly weathered specimens.Significant slaking of aggregates and crack propagation were confirmed by scanning electron microscope(SEM)micrographs,which were considered as the main consequence of structure damage leading to degradation of mechanical properties.The structure damage during RH cycles denoted the hysteresis nature in the response to the cycling hydraulic reaction,in turn causing the increase in volumetric strain.Thus,the stress-volume relation rather than the suction relation was found in more reasonable agreement with the experimental results.展开更多
基金research result of the Chongqing Social Science Fund Project,entitled Legal Pathways for the Governance Optimization of Financial Holding Companies(No.21SKJD036).
文摘I.INTRODUCTION Against the backdrop of profound transformations in the global energy landscape,China,as the world's largest energy producer and consumer,faces multiple challenges,including energy security,energy transition,and sustainable development.To address these challenges,the Chinese government has formulated a strategic plan to build a unified national energy market and create a new framework for the energy sector.Article 42 of the Energy Law of the People's Republic of China(hereinafter referred to as the Energy Law)explicitly requires the building of a unified national energy trading market and the improvement of transaction mechanisms and rules.
基金supported by the start-up funding from Westlake University under Grant Number 041030150118 and the scientific research project of Westlake University“Theoretical Research and Demonstration Application of Complex Systems and Deep-Sea Technology(Phase I)”under Grant Number WU2025A006.
文摘Human life is not determined by mechanical fatalism or a single material factor;instead,based on the dualistic ontology and active force mechanism in the Unified Complex Systems Theory(UCST),it can be actively designed under the guidance of mind,in accordance with causal laws,and through systematic interactions.This study integrates the dualistic ontology of UCST,as well as the cooperative mechanism of active force(Fa)and passive force(Fp).Furthermore,by incorporating Master Jiqun’s philosophy of“life design”and the practical principle of“destiny establishment and transformation”from The Four Lessons of Liaofan Yuan,it constructs a three-dimensional framework for life design encompassing the dimensions of science,philosophy,and practice.The significance of this research lies in breaking through the predicament of materialism in the AI(artificial intelligence)era,explaining the autonomy and initiative of life,providing feasible pathways for life design,and ultimately achieving the in-depth integration of scientific rationality and the wisdom of traditional Eastern culture.
文摘Despite advances in current anti-cancer therapies,challenges such as drug resistance,toxicity,and tumor heterogeneity persist.The limitations of traditional single-target drugs and simple combination therapies are becoming increasingly apparent1.To address these issues,a novel treatment strategy,the artificially intelligent synergistic engineered drug(AISED)paradigm,merits further exploration.This paradigm is based on the systematic engineered integration of multiple active ingredients into a unified single entity through artificial intelligence(AI).This strategy is aimed at developing new anti-cancer drug designs involving multiple ingredients,multiple molecular targets,and multiple biological effects,for multiple cancer types,thereby providing a novel theoretical paradigm for overcoming existing treatment bottlenecks.
基金supported by the National Natural Science Foundation of China(Grant Nos.52574103 and 42277150).
文摘Fractures are typically characterized by roughness that significantlyaffects the mechanical and hydraulic characteristics of reservoirs.However,hydraulic fracturing mechanisms under the influenceof fracture morphology remain largely unexplored.Leveraging the advantages of the finite-discrete element method(FDEM)for explicitly simulating fracture propagation and the strengths of the unifiedpipe model(UPM)for efficientlymodeling dual-permeability seepage,we propose a new hydromechanical(HM)coupling approach for modeling hydraulic fracturing.Validated against benchmark examples,the proposed FDEM-UPM model is further augmented by incorporating a Fourier-based methodology for reconstructing non-planar fractures,enabling quantitative analysis of hydraulic fracturing behavior within rough discrete fracture networks(DFNs).The FDEM-UPM model demonstrates computational advantages in accurately capturing transient hydraulic seepage phenomena,while the asynchronous time-stepping schemes between hydraulic and mechanical analyses substantially enhanced computational efficiencywithout compromising computational accuracy.Our results show that fracture morphology can affect both macroscopic fracture networks and microscopic interaction types between hydraulic fractures(HFs)and natural fractures(NFs).In an isotropic stress field,the initiation azimuth,propagation direction and microcracking mechanism are significantly influencedby fracture roughness.In an anisotropic stress field,HFs invariably propagate parallel to the direction of the maximum principal stress,reducing the overall complexity of the stimulated fracture networks.Additionally,stress concentration and perturbation attributed to fracture morphology tend to be compromised as the leak-off increases,while the breakdown and propagation pressures remain insensitive to fracture morphology.These findingsprovide new insights into the hydraulic fracturing mechanisms of fractured reservoirs containing complex rough DFNs.
基金supported by the Deanship of Research at the King Fahd University of Petroleum&Minerals,Dhahran,31261,Saudi Arabia,under Project No.EC241001.
文摘Various factors,including weak tie-lines into the electric power system(EPS)networks,can lead to low-frequency oscillations(LFOs),which are considered an instant,non-threatening situation,but slow-acting and poisonous.Considering the challenge mentioned,this article proposes a clustering-based machine learning(ML)framework to enhance the stability of EPS networks by suppressing LFOs through real-time tuning of key power system stabilizer(PSS)parameters.To validate the proposed strategy,two distinct EPS networks are selected:the single-machine infinite-bus(SMIB)with a single-stage PSS and the unified power flow controller(UPFC)coordinated SMIB with a double-stage PSS.To generate data under various loading conditions for both networks,an efficient but offline meta-heuristic algorithm,namely the grey wolf optimizer(GWO),is used,with the loading conditions as inputs and the key PSS parameters as outputs.The generated loading conditions are then clustered using the fuzzy k-means(FKM)clustering method.Finally,the group method of data handling(GMDH)and long short-term memory(LSTM)ML models are developed for clustered data to predict PSS key parameters in real time for any loading condition.A few well-known statistical performance indices(SPI)are considered for validation and robustness of the training and testing procedure of the developed FKM-GMDH and FKM-LSTM models based on the prediction of PSS parameters.The performance of the ML models is also evaluated using three stability indices(i.e.,minimum damping ratio,eigenvalues,and time-domain simulations)after optimally tuned PSS with real-time estimated parameters under changing operating conditions.Besides,the outputs of the offline(GWO-based)metaheuristic model,proposed real-time(FKM-GMDH and FKM-LSTM)machine learning models,and previously reported literature models are compared.According to the results,the proposed methodology outperforms the others in enhancing the stability of the selected EPS networks by damping out the observed unwanted LFOs under various loading conditions.
基金supported by the National Natural Science Foundation of China(62073267,61903305)the Fundamental Research Funds for the Central Universities(HXGJXM202214)。
文摘For mission-oriented unmanned aerial vehicle(UAV)swarms,mission capability assessment provides an important reference in the design and development process,and is a precondition for mission success.For this multi-criteria decisionmaking(MCDM)problem,the current literature lacks a way to unambiguously present criteria and the popular fuzzy analytic network process(ANP)approaches neglect the hesitancy of subjective judgments.To fill these research gaps,an MCDM method based on unified architecture framework(UAF)and interval-valued spherical fuzzy ANP(IVSF-ANP)is proposed in this paper.Firstly,selected viewpoints in UAF are extended to construct criteria models with standardized representation.Secondly,interval-valued spherical fuzzy sets are introduced to ANP to weight interdependent criteria,handling fuzziness and hesitancy in pairwise comparisons.A method of adjusting weights of experts based on their decision similarities is also included in this process to reduce ambiguity brought by multiple experts.Next,performance characteristics are non-linearly transformed regarding to expectations to get final results.This proposition is applied to assess the mission capability of UAV swarms to search and strike surface vessels.Comparative analysis shows that the proposed method is valid and reasonable.
文摘对珠子参中皂苷类成分进行定性鉴别分析,建立珠子参皂苷类多成分含量测定方法。采用超高效液相色谱-飞行时间质谱(UPLC-Q-TOF-MS/MS)技术对珠子参进行正、负离子模式扫描,使用UNIFI天然产物信息平台对珠子参所含的化学成分进行定性鉴别分析;以0.1%磷酸水-乙腈溶液为流动相进行梯度洗脱,柱温30℃,流速0.3 mL/min,进行珠子参皂苷类多成分含量测定。珠子参中共鉴定出39个化学成分,包括37个皂苷类化合物和2个皂苷母核,并总结了皂苷类化合物的裂解规律,建立了UPLC同时测定珠子参中人参皂苷Rb1、人参皂苷Ro、人参皂苷Rb3、竹节参皂苷IV、竹节参皂苷IVa、人参皂苷Rd、姜状三七皂苷R1和金盏花苷E的多指标含量测定方法,该方法中8个待测成分在检测质量浓度范围内线性关系良好,精密度、重复性、稳定性的相对标准偏差(relative standard deviation,RSD)均小于3.0%,样品中人参皂苷Rb1、人参皂苷Ro、人参皂苷Rb3、竹节参皂苷IV、竹节参皂苷IVa、人参皂苷Rd、姜状三七皂苷R1和金盏花苷E的平均加样回收率分别为102.4%、103.1%、97.97%、99.42%、102.7%、102.1%、95.23%、100.5%,RSD分别为1.0%、0.98%、0.81%、2.3%、0.81%、1.9%、0.96%、1.8%。该研究建立的方法可快速、准确地对珠子参中的皂苷类成分进行定性及定量分析。
文摘If the singularity of the cosmic Big Bang is taken as the origin of the reference coordinate system,the surrounding vacuum in the initial moments of it would exhibit radially-outward right-handed spiral motion at light speed.Based on this spatial motion hypothesis,we derive a unified field equation and a set of Maxwell’s equations for vacuum SWs(Scalar Waves)generating a huge spiral force field that drives the energy to spiral inwardly and distort,leading to the formation of mass.Furthermore,they also uncover that mass is fundamentally an ultimate expression of energy,manifesting as the result of spiral motion of space at light speed.And then,we indirectly validate the theory that coherent light waves’collision generate SWs and subsequently mass through the experiment verifying the Breit-Wheeler process.The establishment of our theory offers a new analytical tool for the exploration of mass origin,the cosmic Big Bang,unified field theories.
基金supported By Grant (PLN2022-14) of State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation (Southwest Petroleum University)。
文摘Well logging technology has accumulated a large amount of historical data through four generations of technological development,which forms the basis of well logging big data and digital assets.However,the value of these data has not been well stored,managed and mined.With the development of cloud computing technology,it provides a rare development opportunity for logging big data private cloud.The traditional petrophysical evaluation and interpretation model has encountered great challenges in the face of new evaluation objects.The solution research of logging big data distributed storage,processing and learning functions integrated in logging big data private cloud has not been carried out yet.To establish a distributed logging big-data private cloud platform centered on a unifi ed learning model,which achieves the distributed storage and processing of logging big data and facilitates the learning of novel knowledge patterns via the unifi ed logging learning model integrating physical simulation and data models in a large-scale functional space,thus resolving the geo-engineering evaluation problem of geothermal fi elds.Based on the research idea of“logging big data cloud platform-unifi ed logging learning model-large function space-knowledge learning&discovery-application”,the theoretical foundation of unified learning model,cloud platform architecture,data storage and learning algorithm,arithmetic power allocation and platform monitoring,platform stability,data security,etc.have been carried on analysis.The designed logging big data cloud platform realizes parallel distributed storage and processing of data and learning algorithms.The feasibility of constructing a well logging big data cloud platform based on a unifi ed learning model of physics and data is analyzed in terms of the structure,ecology,management and security of the cloud platform.The case study shows that the logging big data cloud platform has obvious technical advantages over traditional logging evaluation methods in terms of knowledge discovery method,data software and results sharing,accuracy,speed and complexity.
文摘Downloads of national standards exceed 10 million times in the first half of 2025 In response to social needs,State Administration for Market Regulation(SAMR)had steadily promoted the full-text disclosure and free download of over 30,000 national standards that do not adopt international standards since the beginning of this year.In the first half of 2025,downloads exceeded 10 million times,providing strong support for the construction of a unified national market.Social groups accessing national standards for free increased significantly.In the first half of this year,the average monthly downloads of national standards surged tenfold from 190,000 times last year to 2.03 million times.Online reading reached nearly 15 million times,and page views hit 89 million times.The disclosure of national standards for free has effectively broken information barriers in standards,ensuring equal rights for business entities to read and download national standards.
基金supported in part by Multimedia University Research Fellow under Grant MMUI/250008in part by Telekom Research and Development Sdn Bhd under Grant RDTC/241149.
文摘Vehicle recognition plays a vital role in intelligent transportation systems,law enforcement,access control,and security operations—domains that are becoming increasingly dynamic and complex.Despite advancements,most existing solutions remain siloed,addressing individual tasks such as vehicle make and model recognition(VMMR),automatic number plate recognition(ANPR),and color classification separately.This fragmented approach limits real-world efficiency,leading to slower processing,reduced accuracy,and increased operational costs,particularly in traffic monitoring and surveillance scenarios.To address these limitations,we present a unified framework that consolidates all three recognition tasks into a single,lightweight system.The framework utilizes MobileNetV2 for efficient VMMR,YOLO(You Only Look Once)for accurate license plate detection,and histogram-based clustering in the HSV color space for precise color identification.Rather than optimizing each module in isolation,our approach emphasizes tight integration,enabling improved performance and reliability.The system also features adaptive image calibration and robust algorithmic enhancements to ensure consistent results under varying environmental conditions.Experimental evaluations demonstrate that the proposedmodel achieves a combined accuracy of 93.3%,outperforming traditional methods and offering practical scalability for deployment in real-world transportation infrastructures.
文摘In March 2025,prominent Chinese automaker NIO(Shanghai,China),the global leader in electric vehicle(EV)battery swapping,and Contemporary Amperex Technology Co.,Ltd.(CATL)(Nindge,China),the world’s biggest manufacturer of EV batteries,announced a strategic partnership to build the world’s largest battery swapping network,while also promoting unified standards and technologies[1].Just weeks later,CATL announced another partnership,this one with Chinese state-owned oil giant Sinopec(Beijing,China)to build 10000 new battery swapping stations in China,at least 500 in 2025[2].
文摘As important natural and pharmaceutical motifs,the catalytic construction of structurally diverse 3,3-disubstituted oxindoles often requires elaborate synthetic efforts on optimizations.Herein,we developed a simple and divergent approach for constructing reverse-prenylated and prenylated oxindoles launched by Ni catalysis with bulk chemical isoprene.Using C3-unsubstituted oxindoles as starting materials,mono reverse-prenylation was demonstrated in high chemo-and regioselectivities facilitated by the combination of Ni(0)and monodentate phosphine ligand.Using the obtained reverse-prenylated oxindoles as versatile synthon,substitutions at the pseudobenzylic position with various electrophiles created vicinal quaternary centers in a concise way.With the help of additives(PPh3 and NaH),air could be directly used as green oxidant to construct prenylated and reverse-prenylatedα-hydroxy-oxindoles divergently from the same substrates.In situ esterification of prenylatedα-hydroxy-oxindoles allowed subsequent Friedel-Crafts substitutions with diverse nucleophiles to deliver prenyl substituted dimeric or spiro-oxindoles.This protocol provides a divergent synthetic approach for the construction of highly functionalized 3,3-disubstituted oxindoles,which have been otherwise difficult to access in a unified approach.
基金Projects(52208382, 52278387, 51738002) supported by the National Natural Science Foundation of ChinaProject(2022YJS072) supported by the Fundamental Research Funds for the Central Universities,China。
文摘Ground reinforcement is crucial for tunnel construction, especially in soft rock tunnels. Existing analytical models are inadequate for predicting the ground reaction curves (GRCs) for reinforced tunnels in strain-softening (SS) rock masses. This study proposes a novel analytical model to determine the GRCs of SS rock masses, incorporating ground reinforcement and intermediate principal stress (IPS). The SS constitutive model captures the progressive post- peak failure, while the elastic-brittle model simulates reinforced rock masses. Nine combined states are innovatively investigated to analyze plastic zone development in natural and reinforced regions. Each region is analyzed separately, and coupled through boundary conditions at interface. Comparison with three types of existing models indicates that these models overestimate reinforcement effects. The deformation prediction errors of single geological material models may exceed 75%. Furthermore, neglecting softening and residual zones in natural regions could lead to errors over 50%. Considering the IPS can effectively utilize the rock strength to reduce tunnel deformation by at least 30%, thereby saving on reinforcement and support costs. The computational results show a satisfactory agreement with the monitoring data from a model test and two tunnel projects. The proposed model may offer valuable insights into the design and construction of reinforced tunnel engineering.
基金Project(52274130)supported by the National Natural Science Foundation of ChinaProject(ZR2024ZD22)supported by the Major Basic Research Project of the Shandong Provincial Natural Science Foundation,China+2 种基金Project(2023375)supported by the Guizhou University Research and Innovation Team,ChinaProject(Leading Fund(2023)09)supported by the Natural Science Research Fund of Guizhou University,ChinaProject(JYBSYS2021101)supported by the Open Fund of Key Laboratory of Safe and Effective Coal Mining,Ministry of Education,China。
文摘The stress gradient of surrounding rock and reasonable prestress of support are the keys to ensuring the stability of roadways.The elastic-plastic analytical solution for surrounding rock was derived based on unified strength theory.A model for solving the stress gradient of the surrounding rock with the intermediate principal stress parameter b was established.The correctness and applicability of the solution for the stress gradient in the roadway surrounding rock was verified via multiple methods.Furthermore,the laws of stress,displacement,and the plastic zone of the surrounding rock with different b values and prestresses were revealed.As b increases,the stress gradient in the plastic zone increases,and the displacement and plastic zone radius decrease.As the prestress increases,the peak stress shifts toward the sidewalls,and the stress and stress gradient increments decrease.In addition,the displacement increment and plastic zone increment were proposed to characterize the support effect.The balance point of the plastic zone area appears before that of the displacement zone.The relationship between the stress gradient compensation coefficient and the prestress is obtained.This study provides a research method and idea for determining the reasonable prestress of support in roadways.
基金The financial support from Project(Grant Nos.52278432,and 52168066)of National Natural Science Foundation of China and Project(Grant No.K2023G033)of the Science and Technology Research and Development Plan of China National Railway Group Co.,Ltd.were greatly appreciated.
文摘This paper presents a multi-scale experimental investigation of the weathering degradation of red mudstone.Natural rocks were extracted from the surface ground to 120 m,inwhich three sets of samples were selected to consider the different initial rock fabrics.The long-term relative humidity(RH)cycles under two amplitudes were imposed on red mudstone to simulate the weathering process.After RH cycles,a series of uniaxial compression tests,Brazilian splitting tests and bender-extender element tests were carried out to examine the reduction in strength and stiffness.The objective of this study is to develop an extended stress-volume framework characterizing the degradation of natural red mudstone both at microscale and macroscale.Accompanied by the irreversible swelling of the rock specimen is the progressive degradation of strength,stiffness and Poisson's ratio.A unified exponential degradation model in terms of the irreversible volumetric strain was thus proposed to capture such a degradation pattern.The effect of the initial rock fabric was evident.The highest degradation rate and potential were identified in slightly weathered specimens.Significant slaking of aggregates and crack propagation were confirmed by scanning electron microscope(SEM)micrographs,which were considered as the main consequence of structure damage leading to degradation of mechanical properties.The structure damage during RH cycles denoted the hysteresis nature in the response to the cycling hydraulic reaction,in turn causing the increase in volumetric strain.Thus,the stress-volume relation rather than the suction relation was found in more reasonable agreement with the experimental results.
