The increasing global prevalence of mild cognitive impairment(MCI)necessitates a paradigm shift in early detection strategies.Conventional neuropsychological assessment methods,predominantly paper-and-pencil tests suc...The increasing global prevalence of mild cognitive impairment(MCI)necessitates a paradigm shift in early detection strategies.Conventional neuropsychological assessment methods,predominantly paper-and-pencil tests such as the Mini-Mental State Examination and the Montreal Cognitive Assessment,exhibit inherent limitations with respect to accessibility,administration burden,and sensitivity to subtle cognitive decline,particularly among diverse populations.This commentary critically examines a recent study that champions a novel approach:The integration of gait and handwriting kinematic parameters analyzed via machine learning for MCI screening.The present study positions itself within the broader landscape of MCI detection,with a view to comparing its advantages against established neuropsychological batteries,advanced neuroimaging(e.g.,positron emission tomography,magnetic resonance imaging),and emerging fluid biomarkers(e.g.,cerebrospinal fluid,blood-based assays).While the study demonstrates promising accuracy(74.44%area under the curve 0.74 with gait and graphic handwriting)and addresses key unmet needs in accessibility and objectivity,we highlight its cross-sectional nature,limited sample diversity,and lack of dual-task assessment as areas for future refinement.This commentary posits that kinematic biomarkers offer a distinctive,scalable,and ecologically valid approach to widespread MCI screening,thereby complementing existing methods by providing real-world functional insights.Future research should prioritize longitudinal validation,expansion to diverse cohorts,integration with multimodal data including dual-tasking,and the development of highly portable,artificial intelligence-driven solutions to achieve the democratization of early MCI detection and enable timely interventions.展开更多
As a novel class of purely organic fluores-cent materials,multiple resonance thermal-ly activated delayed fluorescence(MR-TADF)compounds hold significant promise for next-generation display technologies.The efficiency...As a novel class of purely organic fluores-cent materials,multiple resonance thermal-ly activated delayed fluorescence(MR-TADF)compounds hold significant promise for next-generation display technologies.The efficiency of exciton utilization and the overall performance of organic light-emit-ting devices are closely linked to the singlet-triplet energy gap(ΔE_(ST))of MR-TADF emitters.Identifying an economic and accu-rate theoretical approach to predictΔE_(ST)would be beneficial for high-throughput screening and facilitate the inverse design of MR-TADF molecules.In this study,we evaluated the S_(1)state energy(E(S_(1))),T_(1)state ener-gy(E(T_(1))),andΔE_(ST)using three different physical interpretations:adiabatic excitation ener-gy,vertical absorption energy,and vertical emission energy.We employed the time-depen-dent density functional theory(TDDFT)and delta self-consistent field(ΔSCF)methods to calculate E(S_(1)),E(T_(1)),andΔE_(ST)for 20 MR-TADF molecules reported in the literature.We compared these calculated values with experimental data obtained from fluorescence spec-troscopy at room-temperature(or 77 K)and phosphorescence spectroscopy conducted at 77 K.Our findings indicate that the vertical absorption energy at the S0 state minimum,deter-mined by theΔSCF method,accurately predicts the S_(1)state energy.Similarly,the vertical absorption energy at the S0 state minimum,calculated using the TDDFT method,effectively predicts the T_(1)state energy.TheΔE_(ST)derived from the difference between these two excita-tion energies exhibited the smallest mean absolute error of only 0.039 eV compared to the ex-perimental values.This combination represents the most accurate and cost-effective method reported to date for predicting theΔE_(ST)of MR-TADF molecules,and can be integrated into AI-driven inverse design workflows for new emitters.展开更多
Objectives This review aimed to systematically synthesize the available research on the disclosure of diagnosis and related issues in childhood cancer from the perspectives of healthcare professionals,with the goal of...Objectives This review aimed to systematically synthesize the available research on the disclosure of diagnosis and related issues in childhood cancer from the perspectives of healthcare professionals,with the goal of informing the optimization of disclosure processes and meeting the communication needs of affected families.Methods In accordance with the Joanna Briggs Institute(JBI)methodology for mixed methods systematic reviews,the convergent segregated approach was used in this review.Articles were retrieved from 11 databases,including PubMed,Web of Science,CINAHL,CENTRAL,Embase,Ovid/Medline,PsycINFO,PsycArticles,Scopus,ERIC,and China National Knowledge Infrastructure(CNKI).The quality of the selected articles was assessed using the Mixed Method Appraisal Tool(MMAT).The review protocol was registered on PROSPERO(CRD42024542746).Results A total of 21 studies from 10 countries were included.Their methodological quality was generally medium to high,with MMAT scores ranging from 60%to 100%.The synthesis yielded three core themes:1)the spectrum of professional and societal attitudes toward disclosure;2)the dynamic practices of navigating disclosure amid uncertainty,including timing and environment,stakeholders,and content of disclosure;and 3)factors influencing disclosure,including children’s,parental,healthcare professionals’,and socio-cultural factors.Conclusions This review synthesized the perspectives and experiences of healthcare professionals regarding disclosure in childhood cancer,highlighting the complexity and multidimensional nature of this process in clinical practice.Future research should further investigate the experiences and needs of children and their parents,explore cultural variations in disclosure practices,develop context-appropriate assessment tools,and construct multidimensional intervention strategies to enhance the humanistic care and professional effectiveness of the disclosure process.展开更多
The Good Wife is an American TV series that focuses on women’s independence,politics,and law.The drama has been remade in China,Japan,and South Korea.This research aims to use Nida’s Functional Equivalence Theory to...The Good Wife is an American TV series that focuses on women’s independence,politics,and law.The drama has been remade in China,Japan,and South Korea.This research aims to use Nida’s Functional Equivalence Theory to analyze the methods of its English-to-Chinese subtitle translation by considering social,cultural,and historic backgrounds between China and America.After data collection and case analysis,the study found that:(1)Five major translation methods are adopted in the subtitle translation of The Good Wife.They are free translation,variation,literal translation,addition,and omission.Among them,free translation is the most frequently used,while omission is used least.(2)The subtitle translation of films and TV series is limited by time and space restrictions,social-cultural differences,and other factors.When translating,translators should try to use humorous words,euphemism,intonation,and other ways,and combine different methods such as literal translation,free translation,variation,addition,omission,and other methods to seek equivalence both in the meaning and function of subtitles under the guidance of Functional Equivalence Theory.展开更多
This mixed-methods study investigated how AI-enhanced English as a Foreign Language(EFL)learning environments influence students’psychological well-being through the mediating roles of motivation and language learnin...This mixed-methods study investigated how AI-enhanced English as a Foreign Language(EFL)learning environments influence students’psychological well-being through the mediating roles of motivation and language learning anxiety and the moderating role of trust.Participants were Chinese university students(N=310,62%female,mean age=18.9,SD=0.8),of whom 15 completed interviews to both add to and to clarify the evidence from the surveys.Structural equation modeling results revealed that AI use had significant indirect effects on well-being through increased motivation and reduced language learning anxiety.Trust in AI significantly moderated both paths,amplifying the motivational benefits and anxiety reduction associated with AI use.Thematic analysis supported these results,identifying three experiential themes:(1)motivational empowerment through personalization,(2)anxiety regulation through safe practice and feedback,and(3)trust as the emotional bridge between AI and well-being.The study extends AI psychology applications by empirically linking technology engagement with affective outcomes and underscores the need for human-centered and trust-enhancing design in AI-supported education.From these findings,we conclude that adaptive,transparent,and autonomy-supportive AI systems promote self-determined motivation,emotional safety,and overall psychological health among EFL learners.展开更多
Geological prospecting and the identification of adverse geological features are essential in tunnel construction,providing critical information to ensure safety and guide engineering decisions.As tunnel projects exte...Geological prospecting and the identification of adverse geological features are essential in tunnel construction,providing critical information to ensure safety and guide engineering decisions.As tunnel projects extend into deeper and more mountainous terrains,engineers face increasingly complex geological conditions,including high water pressure,intense geo-stress,elevated geothermal gradients,and active fault zones.These conditions pose substantial risks such as high-pressure water inrush,largescale collapses,and tunnel boring machine(TBM)blockages.Addressing these challenges requires advanced detection technologies capable of long-distance,high-precision,and intelligent assessments of adverse geology.This paper presents a comprehensive review of recent advancements in tunnel geological ahead prospecting methods.It summarizes the fundamental principles,technical maturity,key challenges,development trends,and real-world applications of various detection techniques.Airborne and semi-airborne geophysical methods enable large-scale reconnaissance for initial surveys in complex terrain.Tunnel-and borehole-based approaches offer high-resolution detection during excavation,including seismic ahead prospecting(SAP),TBM rock-breaking source seismic methods,fulltime-domain tunnel induced polarization(TIP),borehole electrical resistivity,and ground penetrating radar(GPR).To address scenarios involving multiple,coexisting adverse geologies,intelligent inversion and geological identification methods have been developed based on multi-source data fusion and artificial intelligence(AI)techniques.Overall,these advances significantly improve detection range,resolution,and geological characterization capabilities.The methods demonstrate strong adaptability to complex environments and provide reliable subsurface information,supporting safer and more efficient tunnel construction.展开更多
The vast diversity of morphologies,body size,and lifestyles of snakes represents an important source of information that can be used to derive bio-inspired robots through a biology-push and pull process.An understandi...The vast diversity of morphologies,body size,and lifestyles of snakes represents an important source of information that can be used to derive bio-inspired robots through a biology-push and pull process.An understanding of the detailed kinematics of swimming snakes is a fundamental prerequisite to conceive and design bio-inspired aquatic snake robots.However,only limited information is available on the kinematics of swimming snake.Fast and accurate methods are needed to fill this knowledge gap.In the present paper,three existing methods were compared to test their capacity to characterize the kinematics of swimming snakes.(1)Marker tracking(Deftac),(2)Markerless pose estimation(DeepLabCut),and(3)Motion capture were considered.(4)We also designed and tested an automatic video processing method.All methods provided different albeit complementary data sets;they also involved different technical issues in terms of experimental conditions,snake manipulation,or processing resources.Marker tracking provided accurate data that can be used to calibrate other methods.Motion capture posed technical difficulties but can provide limited 3D data.Markerless pose estimation required deep learning(thus time)but was efficient to extract the data under various experimental conditions.Finally,automatic video processing was particularly efficient to extract a wide range of data useful for both biology and robotics but required a specific experimental setting.展开更多
Modal parameters can accurately characterize the structural dynamic properties and assess the physical state of the structure.Therefore,it is particularly significant to identify the structural modal parameters accordi...Modal parameters can accurately characterize the structural dynamic properties and assess the physical state of the structure.Therefore,it is particularly significant to identify the structural modal parameters according to the monitoring data information in the structural health monitoring(SHM)system,so as to provide a scientific basis for structural damage identification and dynamic model modification.In view of this,this paper reviews methods for identifying structural modal parameters under environmental excitation and briefly describes how to identify structural damages based on the derived modal parameters.The paper primarily introduces data-driven modal parameter recognition methods(e.g.,time-domain,frequency-domain,and time-frequency-domain methods,etc.),briefly describes damage identification methods based on the variations of modal parameters(e.g.,natural frequency,modal shapes,and curvature modal shapes,etc.)and modal validation methods(e.g.,Stability Diagram and Modal Assurance Criterion,etc.).The current status of the application of artificial intelligence(AI)methods in the direction of modal parameter recognition and damage identification is further discussed.Based on the pre-vious analysis,the main development trends of structural modal parameter recognition and damage identification methods are given to provide scientific references for the optimized design and functional upgrading of SHM systems.展开更多
To investigate the forward kinematics problem of parallel mechanisms with complex limbs and to expand the applicability of the powerful tool of Conformal Geometric Algebra(CGA),a CGA-based modeling and solution method...To investigate the forward kinematics problem of parallel mechanisms with complex limbs and to expand the applicability of the powerful tool of Conformal Geometric Algebra(CGA),a CGA-based modeling and solution method for a class of parallel platforms with 3-RE structure after locking the actuated joints is proposed in this paper.Given that the angle between specific joint axes of limbs remains constant,a set of geometric constraints for the forward kinematics of parallel mechanisms(PM)are determined.After translating unit direction vectors of these joint axes to the common starting point,the geometric constraints of the angle between the vectors are transformed into the distances between the endpoints of the vectors,making them easier to handle.Under the framework of CGA,the positions of key points that determine the position and orientation of the moving platform can be intuitively determined by the intersection,division,and duality of basic geometric entities.By employing the tangent half-angle substitution,the forward kinematic analysis of the parallel mechanisms leads to a high-order univariate polynomial equation without the need for any complex algebraic elimination operations.After solving this equation and back substitution,the position and pose of the MP can be obtained indirectly.A numerical case is utilized to confirm the effectiveness of the proposed method.展开更多
Serial-parallel manipulators are of great interest to academic community in recent years,especially those composed of classical parallel mechanisms.There have been many studies around 2(3RPS)and 2(3SPR)S-PMs,but unfor...Serial-parallel manipulators are of great interest to academic community in recent years,especially those composed of classical parallel mechanisms.There have been many studies around 2(3RPS)and 2(3SPR)S-PMs,but unfortunately their inverse kinematics have not yet been resolved.This paper discovers that the unknown kinematic parameters of middle platform are responsible for the unresolvable of inverse kinematics,meanwhile the unknown kinematic parameters of middle platform also have huge coupling relationships.Therefore,to break through this challenges,the huge coupling relationships are decoupled layer by layer,the kinematic parameters of middle platform are solved by combining Sylvester's elimination method,and the inverse displacements of 2(3RPS)and 2(3SPR)S-PMs are obtained subsequently.This paper not only solves the inverse kinematics of classical 2(3RPS)and 2(3SPR)S-PMs,but also reveals the essence of the inverse kinematics of general(3-DOF)+(3-DOF)6-DOF S-PMs and proposes a corresponding solution.展开更多
As pivotal supporting technologies for smart manufacturing and digital engineering,model-based and data-driven methods have been widely applied in many industrial fields,such as product design,process monitoring,and s...As pivotal supporting technologies for smart manufacturing and digital engineering,model-based and data-driven methods have been widely applied in many industrial fields,such as product design,process monitoring,and smart maintenance.While promising,both methods have issues that need to be addressed.For example,model-based methods are limited by low computational accuracy and a high computational burden,and data-driven methods always suffer from poor interpretability and redundant features.To address these issues,the concept of data-model fusion(DMF)emerges as a promising solution.DMF involves integrating model-based methods with data-driven methods by incorporating big data into model-based methods or embedding relevant domain knowledge into data-driven methods.Despite growing efforts in the field of DMF,a unanimous definition of DMF remains elusive,and a general framework of DMF has been rarely discussed.This paper aims to address this gap by providing a thorough overview and categorization of both data-driven methods and model-based methods.Subsequently,this paper also presents the definition and categorization of DMF and discusses the general framework of DMF.Moreover,the primary seven applications of DMF are reviewed within the context of smart manufacturing and digital engineering.Finally,this paper directs the future directions of DMF.展开更多
Soil improvement is one of the most important issues in geotechnical engineering practice.The wide application of traditional improvement techniques(cement/chemical materials)are limited due to damage ecological en-vi...Soil improvement is one of the most important issues in geotechnical engineering practice.The wide application of traditional improvement techniques(cement/chemical materials)are limited due to damage ecological en-vironment and intensify carbon emissions.However,the use of microbially induced calcium carbonate pre-cipitation(MICP)to obtain bio-cement is a novel technique with the potential to induce soil stability,providing a low-carbon,environment-friendly,and sustainable integrated solution for some geotechnical engineering pro-blems in the environment.This paper presents a comprehensive review of the latest progress in soil improvement based on the MICP strategy.It systematically summarizes and overviews the mineralization mechanism,influ-encing factors,improved methods,engineering characteristics,and current field application status of the MICP.Additionally,it also explores the limitations and correspondingly proposes prospective applications via the MICP approach for soil improvement.This review indicates that the utilization of different environmental calcium-based wastes in MICP and combination of materials and MICP are conducive to meeting engineering and market demand.Furthermore,we recommend and encourage global collaborative study and practice with a view to commercializing MICP technique in the future.The current review purports to provide insights for engineers and interdisciplinary researchers,and guidance for future engineering applications.展开更多
The separation-of-variable(SOV)methods,such as the improved SOV method,the variational SOV method,and the extended SOV method,have been proposed by the present authors and coworkers to obtain the closed-form analytica...The separation-of-variable(SOV)methods,such as the improved SOV method,the variational SOV method,and the extended SOV method,have been proposed by the present authors and coworkers to obtain the closed-form analytical solutions for free vibration and eigenbuckling of rectangular plates and circular cylindrical shells.By taking the free vibration of rectangular thin plates as an example,this work presents the theoretical framework of the SOV methods in an instructive way,and the bisection–based solution procedures for a group of nonlinear eigenvalue equations.Besides,the explicit equations of nodal lines of the SOV methods are presented,and the relations of nodal line patterns and frequency orders are investigated.It is concluded that the highly accurate SOV methods have the same accuracy for all frequencies,the mode shapes about repeated frequencies can also be precisely captured,and the SOV methods do not have the problem of missing roots as well.展开更多
The microstructures of pharmaceutical preparations play a pivotal role in determining their critical quality attributes(CQAs),such as drug release,content uniformity,and stability,which greatly impact the safety and e...The microstructures of pharmaceutical preparations play a pivotal role in determining their critical quality attributes(CQAs),such as drug release,content uniformity,and stability,which greatly impact the safety and efficacy of drugs.Unlike the inherent molecular structures of active pharmaceutical ingredients(APIs)and excipients,the microstructures of pharmaceutical preparations are developed during the formulation process,presenting unique analytical challenges.In this review,we primarily focus on presenting the research methods used to elucidate the microstructures of pharmaceutical preparations,including X-ray imaging(XRI),scanning electron microscopy(SEM),atomic force microscopy(AFM),Raman spectroscopy,infrared(IR)spectroscopy,and rheometer technology.Subsequently,we highlight the applications,advantages,and limitations of these methods.Finally,we discuss the current challenges and future perspectives in this field.This review aims to provide a comprehensive reference for understanding the microstructures of pharmaceutical preparations,offering new insights and potential advancements in their development.展开更多
With the continuous increase of aeroengine flight ceiling(>20 km),the thin atmosphere at high altitudes and the size effect all cause the compressor component inlet Reynolds number to decrease rapidly to a critical...With the continuous increase of aeroengine flight ceiling(>20 km),the thin atmosphere at high altitudes and the size effect all cause the compressor component inlet Reynolds number to decrease rapidly to a critical value(approximately 2.0×10^(5)),and the significant transition process on the blade/endwall surface leads to the sharp degradation of compressor performance,which seriously affects the engine fuel consumption and working stability at high altitudes.In this paper,the research progress on the internal flow mechanism and flow control methods of axial compressors at low Reynolds numbers is reviewed from the aspects of quantification and prediction of performance variation,flow loss mechanism related to separation and transition,efficient transition control and flow field organization.The development trend of the low-Reynolds-number effect of axial flow compressors is noted,and the difficulties and application prospects of aerodynamic design and efficient flow control methods for compressors under low Reynolds numbers at high altitudes are discussed.展开更多
In order to solve the problem of the variable coefficient ordinary differen-tial equation on the bounded domain,the Lagrange interpolation method is used to approximate the exact solution of the equation,and the error...In order to solve the problem of the variable coefficient ordinary differen-tial equation on the bounded domain,the Lagrange interpolation method is used to approximate the exact solution of the equation,and the error between the numerical solution and the exact solution is obtained,and then compared with the error formed by the difference method,it is concluded that the Lagrange interpolation method is more effective in solving the variable coefficient ordinary differential equation.展开更多
Unmanned aerial vehicles(UAVs)have become crucial tools in moving target tracking due to their agility and ability to operate in complex,dynamic environments.UAVs must meet several requirements to achieve stable track...Unmanned aerial vehicles(UAVs)have become crucial tools in moving target tracking due to their agility and ability to operate in complex,dynamic environments.UAVs must meet several requirements to achieve stable tracking,including maintaining continuous target visibility amidst occlusions,ensuring flight safety,and achieving smooth trajectory planning.This paper reviews the latest advancements in UAV-based target tracking,highlighting information prediction,tracking strategies,and swarm cooperation.To address challenges including target visibility and occlusion,real-time prediction and tracking in dynamic environments,flight safety and coordination,resource management and energy efficiency,the paper identifies future research directions aimed at improving the performance,reliability,and scalability of UAV tracking system.展开更多
Ocean energy has progressively gained considerable interest due to its sufficient potential to meet the world’s energy demand,and the blade is the core component in electricity generation from the ocean current.Howev...Ocean energy has progressively gained considerable interest due to its sufficient potential to meet the world’s energy demand,and the blade is the core component in electricity generation from the ocean current.However,the widened hydraulic excitation frequency may satisfy the blade resonance due to the time variation in the velocity and angle of attack of the ocean current,even resulting in blade fatigue and destructively interfering with grid stability.A key parameter that determines the resonance amplitude of the blade is the hydrodynamic damping ratio(HDR).However,HDR is difficult to obtain due to the complex fluid-structure interaction(FSI).Therefore,a literature review was conducted on the hydrodynamic damping characteristics of blade-like structures.The experimental and simulation methods used to identify and obtain the HDR quantitatively were described,placing emphasis on the experimental processes and simulation setups.Moreover,the accuracy and efficiency of different simulation methods were compared,and the modal work approach was recommended.The effects of key typical parameters,including flow velocity,angle of attack,gap,rotational speed,and cavitation,on the HDR were then summarized,and the suggestions on operating conditions were presented from the perspective of increasing the HDR.Subsequently,considering multiple flow parameters,several theoretical derivations and semi-empirical prediction formulas for HDR were introduced,and the accuracy and application were discussed.Based on the shortcomings of the existing research,the direction of future research was finally determined.The current work offers a clear understanding of the HDR of blade-like structures,which could improve the evaluation accuracy of flow-induced vibration in the design stage.展开更多
Objective:To investigate the effects of“Three Methods and Three Acupoints”(TMTP)Tuina therapy on spinal microcirculation in sciatic nerve injury(SNI).Methods:Thirty-six SpragueeDawley rats were randomly assigned to ...Objective:To investigate the effects of“Three Methods and Three Acupoints”(TMTP)Tuina therapy on spinal microcirculation in sciatic nerve injury(SNI).Methods:Thirty-six SpragueeDawley rats were randomly assigned to four groups:normal,sham operation,model,and TMTP Tuina.Successful model induction was confirmed by observable hind limb lameness.After 20 sessions,hind limb grip strength and motor nerve conduction velocity(MNCV)were measured at baseline and following the 10th and 20th intervention.CD31 and a-SMA in the ventral horn of SNI model rats were detected using immunofluorescence.Motor neurons in the ventral horn were detected by Nissl staining.PTEN levels in the ventral horn were measured by ELISA,and PI3K,Akt,BDNF,VEGF,and HIF-1a expression was determined by RT-PCR.Spinal cord microcirculation was evaluated by western blotting analysis of the levels of Akt,p-Akt,BDNF,and VEGF.Results:Hind limb grip strength and MNCV significantly improved in the TMTP Tuina group compared to the model group(both P<.001).Morphology of ventral horn motor neurons in the TMTP Tuina group improved compared to the model group,with increased expressions of a-SMA(P=.002)and CD31(P=.006).Western blot analysis indicated increased expression of VEGF(P=.005),p-Akt(P<.001),and BDNF(P=.008)in the ventral horn following Tuina treatment.RT-PCR analysis revealed increased expression of PI3K,Akt,BDNF,VEGF and HIF-1a(all P<.05).In contrast,expression of PTEN decreased compared to the model group(P<.001).Conclusion:TMTP Tuina therapy may restore motor function in rats,enhance ventral horn motor neuron morphology,and promote angiogenesis and vascular smooth muscle proliferation.The mechanism may involve the activation of the PI3K/Akt signaling pathway.展开更多
Cable-driven parallel robots(CDPRs)have advantages of larger workspace and load capacity than conventional parallel robots while existing interference problems among cables,workpieces and the end-effector.In order to ...Cable-driven parallel robots(CDPRs)have advantages of larger workspace and load capacity than conventional parallel robots while existing interference problems among cables,workpieces and the end-effector.In order to avoid collision and improve the flexibility of the robots,this study proposes a reconfigurable cable-driven parallel robot(RCDPR)having characteristics of large load-to-weight ratio,easy modularity and variable stiffness.Adjustable brackets are connected to the moving platform to adjust the position of the pull-out point with the movement of the end-effector.In addition,a variable stiffness actuator(VSA)accompanied by finite element analysis is designed to optimize the cable tension to adapt different task requirements.Firstly,a new idea of reconfiguration is given,and an inverse kinematic model is established using the vector closure principle to derive its inverse kinematic expressions focusing on one of the configurations.Second,the VSA is attached to each cable to achieve stiffness adjustment,and the system stiffness is derived in detail.Finally,the rationality and accuracy of the robot are verified through numerical analysis,providing a reference for subsequent trajectory planning with implications.展开更多
文摘The increasing global prevalence of mild cognitive impairment(MCI)necessitates a paradigm shift in early detection strategies.Conventional neuropsychological assessment methods,predominantly paper-and-pencil tests such as the Mini-Mental State Examination and the Montreal Cognitive Assessment,exhibit inherent limitations with respect to accessibility,administration burden,and sensitivity to subtle cognitive decline,particularly among diverse populations.This commentary critically examines a recent study that champions a novel approach:The integration of gait and handwriting kinematic parameters analyzed via machine learning for MCI screening.The present study positions itself within the broader landscape of MCI detection,with a view to comparing its advantages against established neuropsychological batteries,advanced neuroimaging(e.g.,positron emission tomography,magnetic resonance imaging),and emerging fluid biomarkers(e.g.,cerebrospinal fluid,blood-based assays).While the study demonstrates promising accuracy(74.44%area under the curve 0.74 with gait and graphic handwriting)and addresses key unmet needs in accessibility and objectivity,we highlight its cross-sectional nature,limited sample diversity,and lack of dual-task assessment as areas for future refinement.This commentary posits that kinematic biomarkers offer a distinctive,scalable,and ecologically valid approach to widespread MCI screening,thereby complementing existing methods by providing real-world functional insights.Future research should prioritize longitudinal validation,expansion to diverse cohorts,integration with multimodal data including dual-tasking,and the development of highly portable,artificial intelligence-driven solutions to achieve the democratization of early MCI detection and enable timely interventions.
基金support provided by the National Natural Science Foundation of China(No.22273043).
文摘As a novel class of purely organic fluores-cent materials,multiple resonance thermal-ly activated delayed fluorescence(MR-TADF)compounds hold significant promise for next-generation display technologies.The efficiency of exciton utilization and the overall performance of organic light-emit-ting devices are closely linked to the singlet-triplet energy gap(ΔE_(ST))of MR-TADF emitters.Identifying an economic and accu-rate theoretical approach to predictΔE_(ST)would be beneficial for high-throughput screening and facilitate the inverse design of MR-TADF molecules.In this study,we evaluated the S_(1)state energy(E(S_(1))),T_(1)state ener-gy(E(T_(1))),andΔE_(ST)using three different physical interpretations:adiabatic excitation ener-gy,vertical absorption energy,and vertical emission energy.We employed the time-depen-dent density functional theory(TDDFT)and delta self-consistent field(ΔSCF)methods to calculate E(S_(1)),E(T_(1)),andΔE_(ST)for 20 MR-TADF molecules reported in the literature.We compared these calculated values with experimental data obtained from fluorescence spec-troscopy at room-temperature(or 77 K)and phosphorescence spectroscopy conducted at 77 K.Our findings indicate that the vertical absorption energy at the S0 state minimum,deter-mined by theΔSCF method,accurately predicts the S_(1)state energy.Similarly,the vertical absorption energy at the S0 state minimum,calculated using the TDDFT method,effectively predicts the T_(1)state energy.TheΔE_(ST)derived from the difference between these two excita-tion energies exhibited the smallest mean absolute error of only 0.039 eV compared to the ex-perimental values.This combination represents the most accurate and cost-effective method reported to date for predicting theΔE_(ST)of MR-TADF molecules,and can be integrated into AI-driven inverse design workflows for new emitters.
基金supported by the Fuxing Nursing Research Foundation of Fudan University[FNF202352].
文摘Objectives This review aimed to systematically synthesize the available research on the disclosure of diagnosis and related issues in childhood cancer from the perspectives of healthcare professionals,with the goal of informing the optimization of disclosure processes and meeting the communication needs of affected families.Methods In accordance with the Joanna Briggs Institute(JBI)methodology for mixed methods systematic reviews,the convergent segregated approach was used in this review.Articles were retrieved from 11 databases,including PubMed,Web of Science,CINAHL,CENTRAL,Embase,Ovid/Medline,PsycINFO,PsycArticles,Scopus,ERIC,and China National Knowledge Infrastructure(CNKI).The quality of the selected articles was assessed using the Mixed Method Appraisal Tool(MMAT).The review protocol was registered on PROSPERO(CRD42024542746).Results A total of 21 studies from 10 countries were included.Their methodological quality was generally medium to high,with MMAT scores ranging from 60%to 100%.The synthesis yielded three core themes:1)the spectrum of professional and societal attitudes toward disclosure;2)the dynamic practices of navigating disclosure amid uncertainty,including timing and environment,stakeholders,and content of disclosure;and 3)factors influencing disclosure,including children’s,parental,healthcare professionals’,and socio-cultural factors.Conclusions This review synthesized the perspectives and experiences of healthcare professionals regarding disclosure in childhood cancer,highlighting the complexity and multidimensional nature of this process in clinical practice.Future research should further investigate the experiences and needs of children and their parents,explore cultural variations in disclosure practices,develop context-appropriate assessment tools,and construct multidimensional intervention strategies to enhance the humanistic care and professional effectiveness of the disclosure process.
文摘The Good Wife is an American TV series that focuses on women’s independence,politics,and law.The drama has been remade in China,Japan,and South Korea.This research aims to use Nida’s Functional Equivalence Theory to analyze the methods of its English-to-Chinese subtitle translation by considering social,cultural,and historic backgrounds between China and America.After data collection and case analysis,the study found that:(1)Five major translation methods are adopted in the subtitle translation of The Good Wife.They are free translation,variation,literal translation,addition,and omission.Among them,free translation is the most frequently used,while omission is used least.(2)The subtitle translation of films and TV series is limited by time and space restrictions,social-cultural differences,and other factors.When translating,translators should try to use humorous words,euphemism,intonation,and other ways,and combine different methods such as literal translation,free translation,variation,addition,omission,and other methods to seek equivalence both in the meaning and function of subtitles under the guidance of Functional Equivalence Theory.
文摘This mixed-methods study investigated how AI-enhanced English as a Foreign Language(EFL)learning environments influence students’psychological well-being through the mediating roles of motivation and language learning anxiety and the moderating role of trust.Participants were Chinese university students(N=310,62%female,mean age=18.9,SD=0.8),of whom 15 completed interviews to both add to and to clarify the evidence from the surveys.Structural equation modeling results revealed that AI use had significant indirect effects on well-being through increased motivation and reduced language learning anxiety.Trust in AI significantly moderated both paths,amplifying the motivational benefits and anxiety reduction associated with AI use.Thematic analysis supported these results,identifying three experiential themes:(1)motivational empowerment through personalization,(2)anxiety regulation through safe practice and feedback,and(3)trust as the emotional bridge between AI and well-being.The study extends AI psychology applications by empirically linking technology engagement with affective outcomes and underscores the need for human-centered and trust-enhancing design in AI-supported education.From these findings,we conclude that adaptive,transparent,and autonomy-supportive AI systems promote self-determined motivation,emotional safety,and overall psychological health among EFL learners.
基金supported by the National Natural Science Foundation of China(Grant Nos.52021005,52325904,and 51991391)。
文摘Geological prospecting and the identification of adverse geological features are essential in tunnel construction,providing critical information to ensure safety and guide engineering decisions.As tunnel projects extend into deeper and more mountainous terrains,engineers face increasingly complex geological conditions,including high water pressure,intense geo-stress,elevated geothermal gradients,and active fault zones.These conditions pose substantial risks such as high-pressure water inrush,largescale collapses,and tunnel boring machine(TBM)blockages.Addressing these challenges requires advanced detection technologies capable of long-distance,high-precision,and intelligent assessments of adverse geology.This paper presents a comprehensive review of recent advancements in tunnel geological ahead prospecting methods.It summarizes the fundamental principles,technical maturity,key challenges,development trends,and real-world applications of various detection techniques.Airborne and semi-airborne geophysical methods enable large-scale reconnaissance for initial surveys in complex terrain.Tunnel-and borehole-based approaches offer high-resolution detection during excavation,including seismic ahead prospecting(SAP),TBM rock-breaking source seismic methods,fulltime-domain tunnel induced polarization(TIP),borehole electrical resistivity,and ground penetrating radar(GPR).To address scenarios involving multiple,coexisting adverse geologies,intelligent inversion and geological identification methods have been developed based on multi-source data fusion and artificial intelligence(AI)techniques.Overall,these advances significantly improve detection range,resolution,and geological characterization capabilities.The methods demonstrate strong adaptability to complex environments and provide reliable subsurface information,supporting safer and more efficient tunnel construction.
基金Agence Nationale de la recherche(Grant no.ANR-20-CE02-0010).
文摘The vast diversity of morphologies,body size,and lifestyles of snakes represents an important source of information that can be used to derive bio-inspired robots through a biology-push and pull process.An understanding of the detailed kinematics of swimming snakes is a fundamental prerequisite to conceive and design bio-inspired aquatic snake robots.However,only limited information is available on the kinematics of swimming snake.Fast and accurate methods are needed to fill this knowledge gap.In the present paper,three existing methods were compared to test their capacity to characterize the kinematics of swimming snakes.(1)Marker tracking(Deftac),(2)Markerless pose estimation(DeepLabCut),and(3)Motion capture were considered.(4)We also designed and tested an automatic video processing method.All methods provided different albeit complementary data sets;they also involved different technical issues in terms of experimental conditions,snake manipulation,or processing resources.Marker tracking provided accurate data that can be used to calibrate other methods.Motion capture posed technical difficulties but can provide limited 3D data.Markerless pose estimation required deep learning(thus time)but was efficient to extract the data under various experimental conditions.Finally,automatic video processing was particularly efficient to extract a wide range of data useful for both biology and robotics but required a specific experimental setting.
基金supported by the Innovation Foundation of Provincial Education Department of Gansu(2024B-005)the Gansu Province National Science Foundation(22YF7GA182)the Fundamental Research Funds for the Central Universities(No.lzujbky2022-kb01)。
文摘Modal parameters can accurately characterize the structural dynamic properties and assess the physical state of the structure.Therefore,it is particularly significant to identify the structural modal parameters according to the monitoring data information in the structural health monitoring(SHM)system,so as to provide a scientific basis for structural damage identification and dynamic model modification.In view of this,this paper reviews methods for identifying structural modal parameters under environmental excitation and briefly describes how to identify structural damages based on the derived modal parameters.The paper primarily introduces data-driven modal parameter recognition methods(e.g.,time-domain,frequency-domain,and time-frequency-domain methods,etc.),briefly describes damage identification methods based on the variations of modal parameters(e.g.,natural frequency,modal shapes,and curvature modal shapes,etc.)and modal validation methods(e.g.,Stability Diagram and Modal Assurance Criterion,etc.).The current status of the application of artificial intelligence(AI)methods in the direction of modal parameter recognition and damage identification is further discussed.Based on the pre-vious analysis,the main development trends of structural modal parameter recognition and damage identification methods are given to provide scientific references for the optimized design and functional upgrading of SHM systems.
基金Supported by National Natural Science Foundation of China (Grant No. 52175019)Beijing Municipal Natural Science Foundation of China (Grant No. L222038)+3 种基金Beijing Nova Programme Interdisciplinary Cooperation Project of China (Grant No. 20240484699)Joint Funds of Industry-University-Research of Shanghai Academy of Spaceflight Technology of China (Grant No. SAST2022-017)Beijing Municipal Key Laboratory of Space-ground Interconnection and Convergence of ChinaKey Laboratory of IoT Monitoring and Early Warning,Ministry of Emergency Management of China
文摘To investigate the forward kinematics problem of parallel mechanisms with complex limbs and to expand the applicability of the powerful tool of Conformal Geometric Algebra(CGA),a CGA-based modeling and solution method for a class of parallel platforms with 3-RE structure after locking the actuated joints is proposed in this paper.Given that the angle between specific joint axes of limbs remains constant,a set of geometric constraints for the forward kinematics of parallel mechanisms(PM)are determined.After translating unit direction vectors of these joint axes to the common starting point,the geometric constraints of the angle between the vectors are transformed into the distances between the endpoints of the vectors,making them easier to handle.Under the framework of CGA,the positions of key points that determine the position and orientation of the moving platform can be intuitively determined by the intersection,division,and duality of basic geometric entities.By employing the tangent half-angle substitution,the forward kinematic analysis of the parallel mechanisms leads to a high-order univariate polynomial equation without the need for any complex algebraic elimination operations.After solving this equation and back substitution,the position and pose of the MP can be obtained indirectly.A numerical case is utilized to confirm the effectiveness of the proposed method.
基金Supported by National Natural Science Foundation of China(Grant No.52275033)National Natural Science Youth Foundation of China(Grant No.52205033)Hebei Provincial Natural Science Foundation of China(Grant No.E2021203019)。
文摘Serial-parallel manipulators are of great interest to academic community in recent years,especially those composed of classical parallel mechanisms.There have been many studies around 2(3RPS)and 2(3SPR)S-PMs,but unfortunately their inverse kinematics have not yet been resolved.This paper discovers that the unknown kinematic parameters of middle platform are responsible for the unresolvable of inverse kinematics,meanwhile the unknown kinematic parameters of middle platform also have huge coupling relationships.Therefore,to break through this challenges,the huge coupling relationships are decoupled layer by layer,the kinematic parameters of middle platform are solved by combining Sylvester's elimination method,and the inverse displacements of 2(3RPS)and 2(3SPR)S-PMs are obtained subsequently.This paper not only solves the inverse kinematics of classical 2(3RPS)and 2(3SPR)S-PMs,but also reveals the essence of the inverse kinematics of general(3-DOF)+(3-DOF)6-DOF S-PMs and proposes a corresponding solution.
基金supported in part by the National Natural Science Foundation of China(NSFC)under Grants(52275471 and 52120105008)the Beijing Outstanding Young Scientist Program,and the New Cornerstone Science Foundation through the XPLORER PRIZE.
文摘As pivotal supporting technologies for smart manufacturing and digital engineering,model-based and data-driven methods have been widely applied in many industrial fields,such as product design,process monitoring,and smart maintenance.While promising,both methods have issues that need to be addressed.For example,model-based methods are limited by low computational accuracy and a high computational burden,and data-driven methods always suffer from poor interpretability and redundant features.To address these issues,the concept of data-model fusion(DMF)emerges as a promising solution.DMF involves integrating model-based methods with data-driven methods by incorporating big data into model-based methods or embedding relevant domain knowledge into data-driven methods.Despite growing efforts in the field of DMF,a unanimous definition of DMF remains elusive,and a general framework of DMF has been rarely discussed.This paper aims to address this gap by providing a thorough overview and categorization of both data-driven methods and model-based methods.Subsequently,this paper also presents the definition and categorization of DMF and discusses the general framework of DMF.Moreover,the primary seven applications of DMF are reviewed within the context of smart manufacturing and digital engineering.Finally,this paper directs the future directions of DMF.
基金funded by the National Natural Science Foundation of China(No.41962016)the Natural Science Foundation of NingXia(Nos.2023AAC02023,2023A1218,and 2021AAC02006).
文摘Soil improvement is one of the most important issues in geotechnical engineering practice.The wide application of traditional improvement techniques(cement/chemical materials)are limited due to damage ecological en-vironment and intensify carbon emissions.However,the use of microbially induced calcium carbonate pre-cipitation(MICP)to obtain bio-cement is a novel technique with the potential to induce soil stability,providing a low-carbon,environment-friendly,and sustainable integrated solution for some geotechnical engineering pro-blems in the environment.This paper presents a comprehensive review of the latest progress in soil improvement based on the MICP strategy.It systematically summarizes and overviews the mineralization mechanism,influ-encing factors,improved methods,engineering characteristics,and current field application status of the MICP.Additionally,it also explores the limitations and correspondingly proposes prospective applications via the MICP approach for soil improvement.This review indicates that the utilization of different environmental calcium-based wastes in MICP and combination of materials and MICP are conducive to meeting engineering and market demand.Furthermore,we recommend and encourage global collaborative study and practice with a view to commercializing MICP technique in the future.The current review purports to provide insights for engineers and interdisciplinary researchers,and guidance for future engineering applications.
基金supported by the National Natural Science Foundation of China(12172023).
文摘The separation-of-variable(SOV)methods,such as the improved SOV method,the variational SOV method,and the extended SOV method,have been proposed by the present authors and coworkers to obtain the closed-form analytical solutions for free vibration and eigenbuckling of rectangular plates and circular cylindrical shells.By taking the free vibration of rectangular thin plates as an example,this work presents the theoretical framework of the SOV methods in an instructive way,and the bisection–based solution procedures for a group of nonlinear eigenvalue equations.Besides,the explicit equations of nodal lines of the SOV methods are presented,and the relations of nodal line patterns and frequency orders are investigated.It is concluded that the highly accurate SOV methods have the same accuracy for all frequencies,the mode shapes about repeated frequencies can also be precisely captured,and the SOV methods do not have the problem of missing roots as well.
文摘The microstructures of pharmaceutical preparations play a pivotal role in determining their critical quality attributes(CQAs),such as drug release,content uniformity,and stability,which greatly impact the safety and efficacy of drugs.Unlike the inherent molecular structures of active pharmaceutical ingredients(APIs)and excipients,the microstructures of pharmaceutical preparations are developed during the formulation process,presenting unique analytical challenges.In this review,we primarily focus on presenting the research methods used to elucidate the microstructures of pharmaceutical preparations,including X-ray imaging(XRI),scanning electron microscopy(SEM),atomic force microscopy(AFM),Raman spectroscopy,infrared(IR)spectroscopy,and rheometer technology.Subsequently,we highlight the applications,advantages,and limitations of these methods.Finally,we discuss the current challenges and future perspectives in this field.This review aims to provide a comprehensive reference for understanding the microstructures of pharmaceutical preparations,offering new insights and potential advancements in their development.
基金co-supported by the National Natural Science Foundation of China(No.52306053)the Science Center for Gas Turbine Project,China(No.P2022-B-Ⅱ-005-001)the National Science and Technology Major Project of China(No.2017-Ⅱ-0010-0024)。
文摘With the continuous increase of aeroengine flight ceiling(>20 km),the thin atmosphere at high altitudes and the size effect all cause the compressor component inlet Reynolds number to decrease rapidly to a critical value(approximately 2.0×10^(5)),and the significant transition process on the blade/endwall surface leads to the sharp degradation of compressor performance,which seriously affects the engine fuel consumption and working stability at high altitudes.In this paper,the research progress on the internal flow mechanism and flow control methods of axial compressors at low Reynolds numbers is reviewed from the aspects of quantification and prediction of performance variation,flow loss mechanism related to separation and transition,efficient transition control and flow field organization.The development trend of the low-Reynolds-number effect of axial flow compressors is noted,and the difficulties and application prospects of aerodynamic design and efficient flow control methods for compressors under low Reynolds numbers at high altitudes are discussed.
文摘In order to solve the problem of the variable coefficient ordinary differen-tial equation on the bounded domain,the Lagrange interpolation method is used to approximate the exact solution of the equation,and the error between the numerical solution and the exact solution is obtained,and then compared with the error formed by the difference method,it is concluded that the Lagrange interpolation method is more effective in solving the variable coefficient ordinary differential equation.
基金financial support provided by the Natural Science Foundation of Hunan Province of China(Grant No.2021JJ10045)the Open Research Subject of State Key Laboratory of Intelligent Game(Grant No.ZBKF-24-01)+1 种基金the Postdoctoral Fellowship Program of CPSF(Grant No.GZB20240989)the China Postdoctoral Science Foundation(Grant No.2024M754304)。
文摘Unmanned aerial vehicles(UAVs)have become crucial tools in moving target tracking due to their agility and ability to operate in complex,dynamic environments.UAVs must meet several requirements to achieve stable tracking,including maintaining continuous target visibility amidst occlusions,ensuring flight safety,and achieving smooth trajectory planning.This paper reviews the latest advancements in UAV-based target tracking,highlighting information prediction,tracking strategies,and swarm cooperation.To address challenges including target visibility and occlusion,real-time prediction and tracking in dynamic environments,flight safety and coordination,resource management and energy efficiency,the paper identifies future research directions aimed at improving the performance,reliability,and scalability of UAV tracking system.
基金Supported by the National Natural Science Foundation of China(Nos.52222904 and 52309117)China Postdoctoral Science Foundation(Nos.2022TQ0168 and 2023M731895).
文摘Ocean energy has progressively gained considerable interest due to its sufficient potential to meet the world’s energy demand,and the blade is the core component in electricity generation from the ocean current.However,the widened hydraulic excitation frequency may satisfy the blade resonance due to the time variation in the velocity and angle of attack of the ocean current,even resulting in blade fatigue and destructively interfering with grid stability.A key parameter that determines the resonance amplitude of the blade is the hydrodynamic damping ratio(HDR).However,HDR is difficult to obtain due to the complex fluid-structure interaction(FSI).Therefore,a literature review was conducted on the hydrodynamic damping characteristics of blade-like structures.The experimental and simulation methods used to identify and obtain the HDR quantitatively were described,placing emphasis on the experimental processes and simulation setups.Moreover,the accuracy and efficiency of different simulation methods were compared,and the modal work approach was recommended.The effects of key typical parameters,including flow velocity,angle of attack,gap,rotational speed,and cavitation,on the HDR were then summarized,and the suggestions on operating conditions were presented from the perspective of increasing the HDR.Subsequently,considering multiple flow parameters,several theoretical derivations and semi-empirical prediction formulas for HDR were introduced,and the accuracy and application were discussed.Based on the shortcomings of the existing research,the direction of future research was finally determined.The current work offers a clear understanding of the HDR of blade-like structures,which could improve the evaluation accuracy of flow-induced vibration in the design stage.
基金supported by the National Natural Science Foundation of China(82274675&82074573)the Beijing Natural Science Foundation(7232278).
文摘Objective:To investigate the effects of“Three Methods and Three Acupoints”(TMTP)Tuina therapy on spinal microcirculation in sciatic nerve injury(SNI).Methods:Thirty-six SpragueeDawley rats were randomly assigned to four groups:normal,sham operation,model,and TMTP Tuina.Successful model induction was confirmed by observable hind limb lameness.After 20 sessions,hind limb grip strength and motor nerve conduction velocity(MNCV)were measured at baseline and following the 10th and 20th intervention.CD31 and a-SMA in the ventral horn of SNI model rats were detected using immunofluorescence.Motor neurons in the ventral horn were detected by Nissl staining.PTEN levels in the ventral horn were measured by ELISA,and PI3K,Akt,BDNF,VEGF,and HIF-1a expression was determined by RT-PCR.Spinal cord microcirculation was evaluated by western blotting analysis of the levels of Akt,p-Akt,BDNF,and VEGF.Results:Hind limb grip strength and MNCV significantly improved in the TMTP Tuina group compared to the model group(both P<.001).Morphology of ventral horn motor neurons in the TMTP Tuina group improved compared to the model group,with increased expressions of a-SMA(P=.002)and CD31(P=.006).Western blot analysis indicated increased expression of VEGF(P=.005),p-Akt(P<.001),and BDNF(P=.008)in the ventral horn following Tuina treatment.RT-PCR analysis revealed increased expression of PI3K,Akt,BDNF,VEGF and HIF-1a(all P<.05).In contrast,expression of PTEN decreased compared to the model group(P<.001).Conclusion:TMTP Tuina therapy may restore motor function in rats,enhance ventral horn motor neuron morphology,and promote angiogenesis and vascular smooth muscle proliferation.The mechanism may involve the activation of the PI3K/Akt signaling pathway.
基金Supported by National Natural Science Foundation of China(Grant Nos.52335002,52205014,52275033)the Fundamental Research Funds for the Central Universities(Grant No.JZ2024HGTB0245).
文摘Cable-driven parallel robots(CDPRs)have advantages of larger workspace and load capacity than conventional parallel robots while existing interference problems among cables,workpieces and the end-effector.In order to avoid collision and improve the flexibility of the robots,this study proposes a reconfigurable cable-driven parallel robot(RCDPR)having characteristics of large load-to-weight ratio,easy modularity and variable stiffness.Adjustable brackets are connected to the moving platform to adjust the position of the pull-out point with the movement of the end-effector.In addition,a variable stiffness actuator(VSA)accompanied by finite element analysis is designed to optimize the cable tension to adapt different task requirements.Firstly,a new idea of reconfiguration is given,and an inverse kinematic model is established using the vector closure principle to derive its inverse kinematic expressions focusing on one of the configurations.Second,the VSA is attached to each cable to achieve stiffness adjustment,and the system stiffness is derived in detail.Finally,the rationality and accuracy of the robot are verified through numerical analysis,providing a reference for subsequent trajectory planning with implications.
