Artificial intelligence can be indirectly applied to the repair of peripheral nerve injury.Specifically,it can be used to analyze and process data regarding peripheral nerve injury and repair,while study findings on p...Artificial intelligence can be indirectly applied to the repair of peripheral nerve injury.Specifically,it can be used to analyze and process data regarding peripheral nerve injury and repair,while study findings on peripheral nerve injury and repair can provide valuable data to enrich artificial intelligence algorithms.To investigate advances in the use of artificial intelligence in the diagnosis,rehabilitation,and scientific examination of peripheral nerve injury,we used CiteSpace and VOSviewer software to analyze the relevant literature included in the Web of Science from 1994–2023.We identified the following research hotspots in peripheral nerve injury and repair:(1)diagnosis,classification,and prognostic assessment of peripheral nerve injury using neuroimaging and artificial intelligence techniques,such as corneal confocal microscopy and coherent anti-Stokes Raman spectroscopy;(2)motion control and rehabilitation following peripheral nerve injury using artificial neural networks and machine learning algorithms,such as wearable devices and assisted wheelchair systems;(3)improving the accuracy and effectiveness of peripheral nerve electrical stimulation therapy using artificial intelligence techniques combined with deep learning,such as implantable peripheral nerve interfaces;(4)the application of artificial intelligence technology to brain-machine interfaces for disabled patients and those with reduced mobility,enabling them to control devices such as networked hand prostheses;(5)artificial intelligence robots that can replace doctors in certain procedures during surgery or rehabilitation,thereby reducing surgical risk and complications,and facilitating postoperative recovery.Although artificial intelligence has shown many benefits and potential applications in peripheral nerve injury and repair,there are some limitations to this technology,such as the consequences of missing or imbalanced data,low data accuracy and reproducibility,and ethical issues(e.g.,privacy,data security,research transparency).Future research should address the issue of data collection,as large-scale,high-quality clinical datasets are required to establish effective artificial intelligence models.Multimodal data processing is also necessary,along with interdisciplinary collaboration,medical-industrial integration,and multicenter,large-sample clinical studies.展开更多
In the realm of the synthesis of heat-integrated distillation configurations,the conventional approach for exploring more heat integration possibilities typically entails the splitting of a single column into a twocol...In the realm of the synthesis of heat-integrated distillation configurations,the conventional approach for exploring more heat integration possibilities typically entails the splitting of a single column into a twocolumn configuration.However,this approach frequently necessitates tedious enumeration procedures,resulting in a considerable computational burden.To surmount this formidable challenge,the present study introduces an innovative remedy:The proposition of a superstructure that encompasses both single-column and multiple two-column configurations.Additionally,a simultaneous optimization algorithm is applied to optimize both the process parameters and heat integration structures of the twocolumn configurations.The effectiveness of this approach is demonstrated through a case study focusing on industrial organosilicon separation.The results underscore that the superstructure methodology not only substantially mitigates computational time compared to exhaustive enumeration but also furnishes solutions that exhibit comparable performance.展开更多
Three-dimensional(3D)printing has attracted increasing research interest as an emerging manufacturing technology for devel-oping sophisticated and exquisite architecture through hierarchical printing.It has also been ...Three-dimensional(3D)printing has attracted increasing research interest as an emerging manufacturing technology for devel-oping sophisticated and exquisite architecture through hierarchical printing.It has also been employed in various advanced industrial areas.The development of intelligent biomedical engineering has raised the requirements for 3D printing,such as flexible manufacturing processes and technologies,biocompatible constituents,and alternative bioproducts.However,state-of-the-art 3D printing mainly involves inorganics or polymers and generally focuses on traditional industrial fields,thus severely limiting applications demanding biocompatibility and biodegradability.In this regard,peptide architectonics,which are self-assembled by programmed amino acid sequences that can be flexibly functionalized,have shown promising potential as bioinspired inks for 3D printing.Therefore,the combination of 3D printing and peptide self-assembly poten-tially opens up an alternative avenue of 3D bioprinting for diverse advanced applications.Israel,a small but innovative nation,has significantly contributed to 3D bioprinting in terms of scientific studies,marketization,and peptide architectonics,including modulations and applications,and ranks as a leading area in the 3D bioprinting field.This review summarizes the recent progress in 3D bioprinting in Israel,focusing on scientific studies on printable components,soft devices,and tissue engineering.This paper further delves into the manufacture of industrial products,such as artificial meats and bioinspired supramolecular architectures,and the mechanisms,physicochemical properties,and applications of peptide self-assembly.Undoubtedly,Israel contributes significantly to the field of 3D bioprinting and should thus be appropriately recognized.展开更多
Blockchain technology has garnered significant attention from global organizations and researchers due to its potential as a solution for centralized system challenges.Concurrently,the Internet of Things(IoT)has revol...Blockchain technology has garnered significant attention from global organizations and researchers due to its potential as a solution for centralized system challenges.Concurrently,the Internet of Things(IoT)has revolutionized the Fourth Industrial Revolution by enabling interconnected devices to offer innovative services,ultimately enhancing human lives.This paper presents a new approach utilizing lightweight blockchain technology,effectively reducing the computational burden typically associated with conventional blockchain systems.By integrating this lightweight blockchain with IoT systems,substantial reductions in implementation time and computational complexity can be achieved.Moreover,the paper proposes the utilization of the Okamoto Uchiyama encryption algorithm,renowned for its homomorphic characteristics,to reinforce the privacy and security of IoT-generated data.The integration of homomorphic encryption and blockchain technology establishes a secure and decentralized platformfor storing and analyzing sensitive data of the supply chain data.This platformfacilitates the development of some business models and empowers decentralized applications to perform computations on encrypted data while maintaining data privacy.The results validate the robust security of the proposed system,comparable to standard blockchain implementations,leveraging the distinctive homomorphic attributes of the Okamoto Uchiyama algorithm and the lightweight blockchain paradigm.展开更多
In this study,we present a novel nodal integration-based particle finite element method(N-PFEM)designed for the dynamic analysis of saturated soils.Our approach incorporates the nodal integration technique into a gene...In this study,we present a novel nodal integration-based particle finite element method(N-PFEM)designed for the dynamic analysis of saturated soils.Our approach incorporates the nodal integration technique into a generalised Hellinger-Reissner(HR)variational principle,creating an implicit PFEM formulation.To mitigate the volumetric locking issue in low-order elements,we employ a node-based strain smoothing technique.By discretising field variables at the centre of smoothing cells,we achieve nodal integration over cells,eliminating the need for sophisticated mapping operations after re-meshing in the PFEM.We express the discretised governing equations as a min-max optimisation problem,which is further reformulated as a standard second-order cone programming(SOCP)problem.Stresses,pore water pressure,and displacements are simultaneously determined using the advanced primal-dual interior point method.Consequently,our numerical model offers improved accuracy for stresses and pore water pressure compared to the displacement-based PFEM formulation.Numerical experiments demonstrate that the N-PFEM efficiently captures both transient and long-term hydro-mechanical behaviour of saturated soils with high accuracy,obviating the need for stabilisation or regularisation techniques commonly employed in other nodal integration-based PFEM approaches.This work holds significant implications for the development of robust and accurate numerical tools for studying saturated soil dynamics.展开更多
With the rapid development and application of emerging information technologies such as cloud computing,big data,artificial intelligence,5G,satellite communication,and blockchain in urban rail transit,China’s urban r...With the rapid development and application of emerging information technologies such as cloud computing,big data,artificial intelligence,5G,satellite communication,and blockchain in urban rail transit,China’s urban rail transit has entered an era of intelligent transformation and upgrading.The development of intelligent systems and the construction of smart urban rail transit have formed a consensus in the industry.The electromechanical system is an important component of urban rail transit engineering,covering power supply stations,vehicles,stations,and lines.The depot and control center are important support for promoting the development of urban rail transit towards informatization and intelligence.However,research on the technical standards for the smart urban rail vehicle-ground integrated electromechanical system has just begun,and a technical standards system has not yet been formed,which cannot better support the electromechanical system.Therefore,it is necessary to conduct research on the technical standards system,propose the common criteria structure and standards list of the standards system,which can provide reference and guidance for the planning and establishment of China’s smart urban rail standards system.展开更多
This work provides an overview of distillation processes,including process design for different distillation processes,selection of entrainers for special distillation processes,system integration and intensification ...This work provides an overview of distillation processes,including process design for different distillation processes,selection of entrainers for special distillation processes,system integration and intensification of distillation processes,optimization of process parameters for distillation processes and recent research progress in dynamic control strategies.Firstly,the feasibility of using thermodynamic topological theories such as residual curve,phase equilibrium line and distillation boundary line to analyze different separation regions is discussed,and the rationality of distillation process design is discussed by using its feasibility.Secondly,the application of molecular simulation methods such as molecular dynamics simulation and quantum chemical calculation in the screening of entrainer is discussed for the extractive distillation process.The thermal coupling mechanism of different distillation processes is used to explore the process of different process intensifications.Next,a mixed integer nonlinear optimization strategy for the distillation process based on different algorithms is introduced.Finally,the improvement of dynamic control strategies for different distillation processes in recent years is summarized.This work focuses on the application of process intensification and system optimization in the design of distillation process,and analyzes the challenges,prospects,and development trends of distillation technology in the separation of multicomponent azeotropes.展开更多
Sweat loss monitoring is important for understanding the body’s thermoregulation and hydration status,as well as for comprehensive sweat analysis.Despite recent advances,developing a low-cost,scalable,and universal m...Sweat loss monitoring is important for understanding the body’s thermoregulation and hydration status,as well as for comprehensive sweat analysis.Despite recent advances,developing a low-cost,scalable,and universal method for the fabrication of colorimetric microfluidics designed for sweat loss monitoring remains challenging.In this study,we propose a novel laserengraved surface roughening strategy for various flexible substrates.This process permits the construction of microchannels that show distinct structural reflectance changes before and after sweat filling.By leveraging these unique optical properties,we have developed a fully laser-engraved microfluidic device for the quantification of naked-eye sweat loss.This sweat loss sensor is capable of a volume resolution of 0.5µL and a total volume capacity of 11µL,and can be customized to meet different performance requirements.Moreover,we report the development of a crosstalk-free dual-mode sweat microfluidic system that integrates an Ag/AgCl chloride sensor and a matching wireless measurement flexible printed circuit board.This integrated system enables the real-time monitoring of colorimetric sweat loss signals and potential ion concentration signals without crosstalk.Finally,we demonstrate the potential practical use of this microfluidic sweat loss sensor and its integrated system for sports medicine via on-body studies.展开更多
Genome-wide association mapping studies(GWAS)based on Big Data are a potential approach to improve marker-assisted selection in plant breeding.The number of available phenotypic and genomic data sets in which medium-s...Genome-wide association mapping studies(GWAS)based on Big Data are a potential approach to improve marker-assisted selection in plant breeding.The number of available phenotypic and genomic data sets in which medium-sized populations of several hundred individuals have been studied is rapidly increasing.Combining these data and using them in GWAS could increase both the power of QTL discovery and the accuracy of estimation of underlying genetic effects,but is hindered by data heterogeneity and lack of interoperability.In this study,we used genomic and phenotypic data sets,focusing on Central European winter wheat populations evaluated for heading date.We explored strategies for integrating these data and subsequently the resulting potential for GWAS.Establishing interoperability between data sets was greatly aided by some overlapping genotypes and a linear relationship between the different phenotyping protocols,resulting in high quality integrated phenotypic data.In this context,genomic prediction proved to be a suitable tool to study relevance of interactions between genotypes and experimental series,which was low in our case.Contrary to expectations,fewer associations between markers and traits were found in the larger combined data than in the individual experimental series.However,the predictive power based on the marker-trait associations of the integrated data set was higher across data sets.Therefore,the results show that the integration of medium-sized to Big Data is an approach to increase the power to detect QTL in GWAS.The results encourage further efforts to standardize and share data in the plant breeding community.展开更多
Evidences show that electric fields(EFs)induced by the magnetic stimulation could modulates brain activities by regulating the excitability of GABAergic interneuron.However,it is still unclear how and why the EF-induc...Evidences show that electric fields(EFs)induced by the magnetic stimulation could modulates brain activities by regulating the excitability of GABAergic interneuron.However,it is still unclear how and why the EF-induced polarization affects the interneuron response as the interneuron receives NMDA synaptic inputs.Considering the key role of NMDA receptor-mediated supralinear dendritic integration in neuronal computations,we suppose that the applied EFs could functionally modulate interneurons’response via regulating dendritic integration.At first,we build a simplified multi-dendritic circuit model with inhomogeneous extracellular potentials,which characterizes the relationship among EF-induced spatial polarizations,dendritic integration,and somatic output.By performing model-based singular perturbation analysis,it is found that the equilibrium point of fast subsystem can be used to asymptotically depict the subthreshold input–output(sI/O)relationship of dendritic integration.It predicted that EF-induced strong depolarizations on the distal dendrites reduce the dendritic saturation output by reducing driving force of synaptic input,and it shifts the steep change of sI/O curve left by reducing stimulation threshold of triggering NMDA spike.Also,the EF modulation prefers the global dendritic integration with asymmetric scatter distribution of NMDA synapses.Furthermore,we identify the respective contribution of EF-regulated dendritic integration and EF-induced somatic polarization to an action potential generation and find that they have an antagonistic effect on AP generation due to the varied NMDA spike threshold under EF stimulation.展开更多
Integrated traditional Chinese medicine(TCM)and Western medicine(WM)is a new medical science grounded in the knowledge bases of both TCM and WM,which then forms a unique modern medical system in China.Integrated TCM a...Integrated traditional Chinese medicine(TCM)and Western medicine(WM)is a new medical science grounded in the knowledge bases of both TCM and WM,which then forms a unique modern medical system in China.Integrated TCM and WM has a long history in China,and has made important achievements in the process of clinical diagnosis and treatment.However,the methodological defects in currently published clinical practice guidelines(CPGs)limit its development.The organic integration of TCM and WM is a deeper integration of TCM and WM.To realize the progression of"integration"to"organic integration",a targeted and standardized guideline development methodology is needed.Therefore,the purpose of this study is to establish a standardized development procedure for clinical practice guidelines for the organic integration of TCM and WM to promote the systematic integration of TCM and WM research results into clinical practice guidelines in order to achieve optimal results as the whole is greater than the sum of the parts.展开更多
The performance of optical interconnection has improved dramatically in recent years.Silicon-based optoelectronic heterogeneous integration is the key enabler to achieve high performance optical interconnection,which ...The performance of optical interconnection has improved dramatically in recent years.Silicon-based optoelectronic heterogeneous integration is the key enabler to achieve high performance optical interconnection,which not only provides the optical gain which is absent from native Si substrates and enables complete photonic functionalities on chip,but also improves the system performance through advanced heterogeneous integrated packaging.This paper reviews recent progress of silicon-based optoelectronic heterogeneous integration in high performance optical interconnection.The research status,development trend and application of ultra-low loss optical waveguides,high-speed detectors,high-speed modulators,lasers and 2D,2.5D,3D and monolithic integration are focused on.展开更多
We study the closed range property and the strict singularity of integration operators acting on the spaces F(p,pα-2,s).We completely characterize the closed range property of the Volterra companion operator I_(g)on ...We study the closed range property and the strict singularity of integration operators acting on the spaces F(p,pα-2,s).We completely characterize the closed range property of the Volterra companion operator I_(g)on F(p,pα-2,s),which generalizes the existing results and answers a question raised in[A.Anderson,Integral Equations Operator Theory,69(2011),no.1,87-99].For the Volterra operator J_(g),we show that,for 0<α≤1,J_(g)never has a closed range on F(p,pα-2,s).We then prove that the notions of compactness,weak compactness and strict singularity coincide in the case of J_(g)acting on F(p,p-2,s).展开更多
Plant morphogenesis relies on precise gene expression programs at the proper time and position which is orchestrated by transcription factors(TFs)in intricate regulatory networks in a cell-type specific manner.Here we...Plant morphogenesis relies on precise gene expression programs at the proper time and position which is orchestrated by transcription factors(TFs)in intricate regulatory networks in a cell-type specific manner.Here we introduced a comprehensive single-cell transcriptomic atlas of Arabidopsis seedlings.This atlas is the result of meticulous integration of 63 previously published scRNA-seq datasets,addressing batch effects and conserving biological variance.This integration spans a broad spectrum of tissues,including both below-and above-ground parts.Utilizing a rigorous approach for cell type annotation,we identified 47 distinct cell types or states,largely expanding our current view of plant cell compositions.We systematically constructed cell-type specific gene regulatory networks and uncovered key regulators that act in a coordinated manner to control cell-type specific gene expression.Taken together,our study not only offers extensive plant cell atlas exploration that serves as a valuable resource,but also provides molecular insights into gene-regulatory programs that varies from different cell types.展开更多
With the popularization of the Internet and the development of technology,cyber threats are increasing day by day.Threats such as malware,hacking,and data breaches have had a serious impact on cybersecurity.The networ...With the popularization of the Internet and the development of technology,cyber threats are increasing day by day.Threats such as malware,hacking,and data breaches have had a serious impact on cybersecurity.The network security environment in the era of big data presents the characteristics of large amounts of data,high diversity,and high real-time requirements.Traditional security defense methods and tools have been unable to cope with the complex and changing network security threats.This paper proposes a machine-learning security defense algorithm based on metadata association features.Emphasize control over unauthorized users through privacy,integrity,and availability.The user model is established and the mapping between the user model and the metadata of the data source is generated.By analyzing the user model and its corresponding mapping relationship,the query of the user model can be decomposed into the query of various heterogeneous data sources,and the integration of heterogeneous data sources based on the metadata association characteristics can be realized.Define and classify customer information,automatically identify and perceive sensitive data,build a behavior audit and analysis platform,analyze user behavior trajectories,and complete the construction of a machine learning customer information security defense system.The experimental results show that when the data volume is 5×103 bit,the data storage integrity of the proposed method is 92%.The data accuracy is 98%,and the success rate of data intrusion is only 2.6%.It can be concluded that the data storage method in this paper is safe,the data accuracy is always at a high level,and the data disaster recovery performance is good.This method can effectively resist data intrusion and has high air traffic control security.It can not only detect all viruses in user data storage,but also realize integrated virus processing,and further optimize the security defense effect of user big data.展开更多
El Niño-Southern Oscillation(ENSO)is the strongest interannual climate mode influencing the coupled ocean-atmosphere system in the tropical Pacific,and numerous dynamical and statistical models have been develope...El Niño-Southern Oscillation(ENSO)is the strongest interannual climate mode influencing the coupled ocean-atmosphere system in the tropical Pacific,and numerous dynamical and statistical models have been developed to simulate and predict it.In some simplified coupled ocean-atmosphere models,the relationship between sea surface temperature(SST)anomalies and wind stress(τ)anomalies can be constructed by statistical methods,such as singular value decomposition(SVD).In recent years,the applications of artificial intelligence(AI)to climate modeling have shown promising prospects,and the integrations of AI-based models with dynamical models are active areas of research.This study constructs U-Net models for representing the relationship between SSTAs andτanomalies in the tropical Pacific;the UNet-derivedτmodel,denoted asτUNet,is then used to replace the original SVD-basedτmodel of an intermediate coupled model(ICM),forming a newly AI-integrated ICM,referred to as ICM-UNet.The simulation results obtained from ICM-UNet demonstrate their ability to represent the spatiotemporal variability of oceanic and atmospheric anomaly fields in the equatorial Pacific.In the ocean-only case study,theτUNet-derived wind stress anomaly fields are used to force the ocean component of the ICM,the results of which also indicate reasonable simulations of typical ENSO events.These results demonstrate the feasibility of integrating an AI-derived model with a physics-based dynamical model for ENSO modeling studies.Furthermore,the successful integration of the dynamical ocean models with the AI-based atmospheric wind model provides a novel approach to ocean-atmosphere interaction modeling studies.展开更多
Although static program analysis methods are frequently employed to enhance software quality,their efficiency in commercial settings is limited by their high false positive rate.The EUGENE tool can effectively lower t...Although static program analysis methods are frequently employed to enhance software quality,their efficiency in commercial settings is limited by their high false positive rate.The EUGENE tool can effectively lower the false positive rate.However,in continuous integration(CI)environments,the code is always changing,and user feedback from one version of the software cannot be applied to a subsequent version.Additionally,people find it difficult to distinguish between true positives and false positives in the analytical output.In this study,we developed the EUGENE-CI technique to address the CI problem and the EUGENE-rank lightweight heuristic algorithm to rate the reports of the analysis output in accordance with the likelihood that they are true positives.On the three projects ethereum,go-cloud,and kubernetes,we assessed our methodologies.According to the trial findings,EUGENE-CI may drastically reduce false positives while EUGENE-rank can make it much easier for users to identify the real positives among a vast number of reports.We paired our techniques with GoInsight~1 and discovered a vulnerability.We also offered a patch to the community.展开更多
Soursop(Annona muricata L.)is a tropical fruit highly valued for its uniqueflavor,nutritional value,and health-promoting properties.The ripening process of soursop involves complex changes in gene expression and metabo...Soursop(Annona muricata L.)is a tropical fruit highly valued for its uniqueflavor,nutritional value,and health-promoting properties.The ripening process of soursop involves complex changes in gene expression and metabo-lite accumulation,which have been studied using various omics technologies.Transcriptome analysis has provided insights into the regulation of key genes involved in ripening,while metabolic compound analysis has revealed the presence of numerous bioactive compounds with potential health benefits.However,the integration of transcrip-tome and metabolite compound data has not been extensively explored in soursop.Therefore,in this paper,we present a comprehensive analysis of the transcriptome and phenolic compound profiles of soursop during ripen-ing.The integration analysis showed that the genes and phenolic compounds were mainly involved in the starch and sucrose metabolism pathways during soursop ripening.Further,the phenolic compounds Kaempferol 3-Q-galactoside,Procyanidin C1,Procyanidin trimmer C1,and m-Coumaric,as well as the genes Ubiquitin-like protein 5(UBL5_ARATH),ATP-dependent zinc metalloprotease FTSH8(FTSH8_ORYSJ),Zinc transporter 4(ZIP4_AR-ATH),Thioredoxin-like 3-1(TRL31_ORYSJ),Mitogen-activated protein kinase YODA(YODA_ARATH),R-man-delonitrile lyase-like(MGL_ARATH),26s protease regulatory subunit 6A homolog(PRS6_SOLLC),Cytochrome P45072A13(C7A13ARATH),Cytochrome P45084A1(C84A1_ARATH)and Homoserine O-trans-acetylase(MET2-ORYSJ)were correlated and differentially accumulated and expressed,respectively.Our study provides new insights into the molecular mechanisms underlying soursop ripening and may contribute to the development of strategies for improving the nutritional quality and shelf life of this important fruit.展开更多
The rapid development of electric vehicles and portable energy storage systems demands improvements in the energy density and cost-effectiveness of lithium-ion batteries,a domain in which Lithium-rich layered cathode(...The rapid development of electric vehicles and portable energy storage systems demands improvements in the energy density and cost-effectiveness of lithium-ion batteries,a domain in which Lithium-rich layered cathode(LLO)materials inherently excel.However,these materials face practical challenges,such as low initial Coulombic efficiency,inferior cycle/rate performance,and voltage decline during cycling,which limit practical application.Our study introduces a surface multi-component integration strategy that incorporates oxygen vacancies into the pristine LLO material Li1.2Mn_(0.6)Ni_(0.2)O_(2).This process involves a brief citric acid treatment followed by calcination,aiming to explore rate-dependent degradation behavior.The induced surface oxygen vacancies can reduce surface oxygen partial pressure and diminish the generation of O_(2)and other highly reactive oxygen species on the surface,thereby facilitating the activation of Li ions trapped in tetrahedral sites while overcoming transport barriers.Additionally,the formation of a spinel-like phase with 3D Li+diffusion channels significantly improves Li^(+)diffusion kinetics and stabilizes the surface structure.The optimally modified sample boasts a discharge capacity of 299.5 mA h g^(-1)at a 0.1 C and 251.6 mA h g^(-1)at a 1 C during the initial activation cycle,with an impressive capacity of 222.1 mA h g^(-1)at a 5 C.Most notably,it retained nearly 70%of its capacity after 300 cycles at this elevated rate.This straightforward,effective,and highly viable modification strategy provides a crucial resolution for overcoming challenges associated with LLO materials,making them more suitable for practical application.展开更多
Understanding the neural underpinning of human gait and balance is one of the most pertinent challenges for 21st-century translational neuroscience due to the profound impact that falls and mobility disturbances have ...Understanding the neural underpinning of human gait and balance is one of the most pertinent challenges for 21st-century translational neuroscience due to the profound impact that falls and mobility disturbances have on our aging population.Posture and gait control does not happen automatically,as previously believed,but rather requires continuous involvement of central nervous mechanisms.To effectively exert control over the body,the brain must integrate multiple streams of sensory information,including visual,vestibular,and somatosensory signals.The mechanisms which underpin the integration of these multisensory signals are the principal topic of the present work.Existing multisensory integration theories focus on how failure of cognitive processes thought to be involved in multisensory integration leads to falls in older adults.Insufficient emphasis,however,has been placed on specific contributions of individual sensory modalities to multisensory integration processes and cross-modal interactions that occur between the sensory modalities in relation to gait and balance.In the present work,we review the contributions of somatosensory,visual,and vestibular modalities,along with their multisensory intersections to gait and balance in older adults and patients with Parkinson’s disease.We also review evidence of vestibular contributions to multisensory temporal binding windows,previously shown to be highly pertinent to fall risk in older adults.Lastly,we relate multisensory vestibular mechanisms to potential neural substrates,both at the level of neurobiology(concerning positron emission tomography imaging)and at the level of electrophysiology(concerning electroencephalography).We hope that this integrative review,drawing influence across multiple subdisciplines of neuroscience,paves the way for novel research directions and therapeutic neuromodulatory approaches,to improve the lives of older adults and patients with neurodegenerative diseases.展开更多
基金supported by the Capital’s Funds for Health Improvement and Research,No.2022-2-2072(to YG).
文摘Artificial intelligence can be indirectly applied to the repair of peripheral nerve injury.Specifically,it can be used to analyze and process data regarding peripheral nerve injury and repair,while study findings on peripheral nerve injury and repair can provide valuable data to enrich artificial intelligence algorithms.To investigate advances in the use of artificial intelligence in the diagnosis,rehabilitation,and scientific examination of peripheral nerve injury,we used CiteSpace and VOSviewer software to analyze the relevant literature included in the Web of Science from 1994–2023.We identified the following research hotspots in peripheral nerve injury and repair:(1)diagnosis,classification,and prognostic assessment of peripheral nerve injury using neuroimaging and artificial intelligence techniques,such as corneal confocal microscopy and coherent anti-Stokes Raman spectroscopy;(2)motion control and rehabilitation following peripheral nerve injury using artificial neural networks and machine learning algorithms,such as wearable devices and assisted wheelchair systems;(3)improving the accuracy and effectiveness of peripheral nerve electrical stimulation therapy using artificial intelligence techniques combined with deep learning,such as implantable peripheral nerve interfaces;(4)the application of artificial intelligence technology to brain-machine interfaces for disabled patients and those with reduced mobility,enabling them to control devices such as networked hand prostheses;(5)artificial intelligence robots that can replace doctors in certain procedures during surgery or rehabilitation,thereby reducing surgical risk and complications,and facilitating postoperative recovery.Although artificial intelligence has shown many benefits and potential applications in peripheral nerve injury and repair,there are some limitations to this technology,such as the consequences of missing or imbalanced data,low data accuracy and reproducibility,and ethical issues(e.g.,privacy,data security,research transparency).Future research should address the issue of data collection,as large-scale,high-quality clinical datasets are required to establish effective artificial intelligence models.Multimodal data processing is also necessary,along with interdisciplinary collaboration,medical-industrial integration,and multicenter,large-sample clinical studies.
文摘In the realm of the synthesis of heat-integrated distillation configurations,the conventional approach for exploring more heat integration possibilities typically entails the splitting of a single column into a twocolumn configuration.However,this approach frequently necessitates tedious enumeration procedures,resulting in a considerable computational burden.To surmount this formidable challenge,the present study introduces an innovative remedy:The proposition of a superstructure that encompasses both single-column and multiple two-column configurations.Additionally,a simultaneous optimization algorithm is applied to optimize both the process parameters and heat integration structures of the twocolumn configurations.The effectiveness of this approach is demonstrated through a case study focusing on industrial organosilicon separation.The results underscore that the superstructure methodology not only substantially mitigates computational time compared to exhaustive enumeration but also furnishes solutions that exhibit comparable performance.
基金supported by the National Key R&D Program of China within the China-Israel Cooperative Scientific Research(No.2022YFE0100800)(Israeli No.3-18130)the National Natural Science Foundation of China(Nos.52175551,22072181)+1 种基金the Leading Innovative and Entrepreneur Team Introduction Program of Zhejiang Province,China(No.2022R01001)the Zhejiang University Global Partnership Fund and Open Foundation of the State Key Laboratory of Fluid Power and Mechatronic Systems(No.GZKF-202224).
文摘Three-dimensional(3D)printing has attracted increasing research interest as an emerging manufacturing technology for devel-oping sophisticated and exquisite architecture through hierarchical printing.It has also been employed in various advanced industrial areas.The development of intelligent biomedical engineering has raised the requirements for 3D printing,such as flexible manufacturing processes and technologies,biocompatible constituents,and alternative bioproducts.However,state-of-the-art 3D printing mainly involves inorganics or polymers and generally focuses on traditional industrial fields,thus severely limiting applications demanding biocompatibility and biodegradability.In this regard,peptide architectonics,which are self-assembled by programmed amino acid sequences that can be flexibly functionalized,have shown promising potential as bioinspired inks for 3D printing.Therefore,the combination of 3D printing and peptide self-assembly poten-tially opens up an alternative avenue of 3D bioprinting for diverse advanced applications.Israel,a small but innovative nation,has significantly contributed to 3D bioprinting in terms of scientific studies,marketization,and peptide architectonics,including modulations and applications,and ranks as a leading area in the 3D bioprinting field.This review summarizes the recent progress in 3D bioprinting in Israel,focusing on scientific studies on printable components,soft devices,and tissue engineering.This paper further delves into the manufacture of industrial products,such as artificial meats and bioinspired supramolecular architectures,and the mechanisms,physicochemical properties,and applications of peptide self-assembly.Undoubtedly,Israel contributes significantly to the field of 3D bioprinting and should thus be appropriately recognized.
文摘Blockchain technology has garnered significant attention from global organizations and researchers due to its potential as a solution for centralized system challenges.Concurrently,the Internet of Things(IoT)has revolutionized the Fourth Industrial Revolution by enabling interconnected devices to offer innovative services,ultimately enhancing human lives.This paper presents a new approach utilizing lightweight blockchain technology,effectively reducing the computational burden typically associated with conventional blockchain systems.By integrating this lightweight blockchain with IoT systems,substantial reductions in implementation time and computational complexity can be achieved.Moreover,the paper proposes the utilization of the Okamoto Uchiyama encryption algorithm,renowned for its homomorphic characteristics,to reinforce the privacy and security of IoT-generated data.The integration of homomorphic encryption and blockchain technology establishes a secure and decentralized platformfor storing and analyzing sensitive data of the supply chain data.This platformfacilitates the development of some business models and empowers decentralized applications to perform computations on encrypted data while maintaining data privacy.The results validate the robust security of the proposed system,comparable to standard blockchain implementations,leveraging the distinctive homomorphic attributes of the Okamoto Uchiyama algorithm and the lightweight blockchain paradigm.
基金supported by the Swiss National Science Foundation(Grant No.189882)the National Natural Science Foundation of China(Grant No.41961134032)support provided by the New Investigator Award grant from the UK Engineering and Physical Sciences Research Council(Grant No.EP/V012169/1).
文摘In this study,we present a novel nodal integration-based particle finite element method(N-PFEM)designed for the dynamic analysis of saturated soils.Our approach incorporates the nodal integration technique into a generalised Hellinger-Reissner(HR)variational principle,creating an implicit PFEM formulation.To mitigate the volumetric locking issue in low-order elements,we employ a node-based strain smoothing technique.By discretising field variables at the centre of smoothing cells,we achieve nodal integration over cells,eliminating the need for sophisticated mapping operations after re-meshing in the PFEM.We express the discretised governing equations as a min-max optimisation problem,which is further reformulated as a standard second-order cone programming(SOCP)problem.Stresses,pore water pressure,and displacements are simultaneously determined using the advanced primal-dual interior point method.Consequently,our numerical model offers improved accuracy for stresses and pore water pressure compared to the displacement-based PFEM formulation.Numerical experiments demonstrate that the N-PFEM efficiently captures both transient and long-term hydro-mechanical behaviour of saturated soils with high accuracy,obviating the need for stabilisation or regularisation techniques commonly employed in other nodal integration-based PFEM approaches.This work holds significant implications for the development of robust and accurate numerical tools for studying saturated soil dynamics.
文摘With the rapid development and application of emerging information technologies such as cloud computing,big data,artificial intelligence,5G,satellite communication,and blockchain in urban rail transit,China’s urban rail transit has entered an era of intelligent transformation and upgrading.The development of intelligent systems and the construction of smart urban rail transit have formed a consensus in the industry.The electromechanical system is an important component of urban rail transit engineering,covering power supply stations,vehicles,stations,and lines.The depot and control center are important support for promoting the development of urban rail transit towards informatization and intelligence.However,research on the technical standards for the smart urban rail vehicle-ground integrated electromechanical system has just begun,and a technical standards system has not yet been formed,which cannot better support the electromechanical system.Therefore,it is necessary to conduct research on the technical standards system,propose the common criteria structure and standards list of the standards system,which can provide reference and guidance for the planning and establishment of China’s smart urban rail standards system.
文摘This work provides an overview of distillation processes,including process design for different distillation processes,selection of entrainers for special distillation processes,system integration and intensification of distillation processes,optimization of process parameters for distillation processes and recent research progress in dynamic control strategies.Firstly,the feasibility of using thermodynamic topological theories such as residual curve,phase equilibrium line and distillation boundary line to analyze different separation regions is discussed,and the rationality of distillation process design is discussed by using its feasibility.Secondly,the application of molecular simulation methods such as molecular dynamics simulation and quantum chemical calculation in the screening of entrainer is discussed for the extractive distillation process.The thermal coupling mechanism of different distillation processes is used to explore the process of different process intensifications.Next,a mixed integer nonlinear optimization strategy for the distillation process based on different algorithms is introduced.Finally,the improvement of dynamic control strategies for different distillation processes in recent years is summarized.This work focuses on the application of process intensification and system optimization in the design of distillation process,and analyzes the challenges,prospects,and development trends of distillation technology in the separation of multicomponent azeotropes.
基金support from the National Natural Science Foundation of China(No.62174152)。
文摘Sweat loss monitoring is important for understanding the body’s thermoregulation and hydration status,as well as for comprehensive sweat analysis.Despite recent advances,developing a low-cost,scalable,and universal method for the fabrication of colorimetric microfluidics designed for sweat loss monitoring remains challenging.In this study,we propose a novel laserengraved surface roughening strategy for various flexible substrates.This process permits the construction of microchannels that show distinct structural reflectance changes before and after sweat filling.By leveraging these unique optical properties,we have developed a fully laser-engraved microfluidic device for the quantification of naked-eye sweat loss.This sweat loss sensor is capable of a volume resolution of 0.5µL and a total volume capacity of 11µL,and can be customized to meet different performance requirements.Moreover,we report the development of a crosstalk-free dual-mode sweat microfluidic system that integrates an Ag/AgCl chloride sensor and a matching wireless measurement flexible printed circuit board.This integrated system enables the real-time monitoring of colorimetric sweat loss signals and potential ion concentration signals without crosstalk.Finally,we demonstrate the potential practical use of this microfluidic sweat loss sensor and its integrated system for sports medicine via on-body studies.
基金funding within the Wheat BigData Project(German Federal Ministry of Food and Agriculture,FKZ2818408B18)。
文摘Genome-wide association mapping studies(GWAS)based on Big Data are a potential approach to improve marker-assisted selection in plant breeding.The number of available phenotypic and genomic data sets in which medium-sized populations of several hundred individuals have been studied is rapidly increasing.Combining these data and using them in GWAS could increase both the power of QTL discovery and the accuracy of estimation of underlying genetic effects,but is hindered by data heterogeneity and lack of interoperability.In this study,we used genomic and phenotypic data sets,focusing on Central European winter wheat populations evaluated for heading date.We explored strategies for integrating these data and subsequently the resulting potential for GWAS.Establishing interoperability between data sets was greatly aided by some overlapping genotypes and a linear relationship between the different phenotyping protocols,resulting in high quality integrated phenotypic data.In this context,genomic prediction proved to be a suitable tool to study relevance of interactions between genotypes and experimental series,which was low in our case.Contrary to expectations,fewer associations between markers and traits were found in the larger combined data than in the individual experimental series.However,the predictive power based on the marker-trait associations of the integrated data set was higher across data sets.Therefore,the results show that the integration of medium-sized to Big Data is an approach to increase the power to detect QTL in GWAS.The results encourage further efforts to standardize and share data in the plant breeding community.
基金Project supported by the National Natural Science Foundation of China(Grant No.62171312)the Tianjin Municipal Education Commission Scientific Research Project,China(Grant No.2020KJ114).
文摘Evidences show that electric fields(EFs)induced by the magnetic stimulation could modulates brain activities by regulating the excitability of GABAergic interneuron.However,it is still unclear how and why the EF-induced polarization affects the interneuron response as the interneuron receives NMDA synaptic inputs.Considering the key role of NMDA receptor-mediated supralinear dendritic integration in neuronal computations,we suppose that the applied EFs could functionally modulate interneurons’response via regulating dendritic integration.At first,we build a simplified multi-dendritic circuit model with inhomogeneous extracellular potentials,which characterizes the relationship among EF-induced spatial polarizations,dendritic integration,and somatic output.By performing model-based singular perturbation analysis,it is found that the equilibrium point of fast subsystem can be used to asymptotically depict the subthreshold input–output(sI/O)relationship of dendritic integration.It predicted that EF-induced strong depolarizations on the distal dendrites reduce the dendritic saturation output by reducing driving force of synaptic input,and it shifts the steep change of sI/O curve left by reducing stimulation threshold of triggering NMDA spike.Also,the EF modulation prefers the global dendritic integration with asymmetric scatter distribution of NMDA synapses.Furthermore,we identify the respective contribution of EF-regulated dendritic integration and EF-induced somatic polarization to an action potential generation and find that they have an antagonistic effect on AP generation due to the varied NMDA spike threshold under EF stimulation.
基金supported by the National Natural Science Foundation of China(82174230)the Fundamental Research Funds for the Central Universities(2042022kf1213)。
文摘Integrated traditional Chinese medicine(TCM)and Western medicine(WM)is a new medical science grounded in the knowledge bases of both TCM and WM,which then forms a unique modern medical system in China.Integrated TCM and WM has a long history in China,and has made important achievements in the process of clinical diagnosis and treatment.However,the methodological defects in currently published clinical practice guidelines(CPGs)limit its development.The organic integration of TCM and WM is a deeper integration of TCM and WM.To realize the progression of"integration"to"organic integration",a targeted and standardized guideline development methodology is needed.Therefore,the purpose of this study is to establish a standardized development procedure for clinical practice guidelines for the organic integration of TCM and WM to promote the systematic integration of TCM and WM research results into clinical practice guidelines in order to achieve optimal results as the whole is greater than the sum of the parts.
基金Project supported in part by the National Key Research and Development Program of China(Grant No.2021YFB2206504)the National Natural Science Foundation of China(Grant No.62235017)the China Postdoctoral Science Foundation(Grant No.2021M703125).
文摘The performance of optical interconnection has improved dramatically in recent years.Silicon-based optoelectronic heterogeneous integration is the key enabler to achieve high performance optical interconnection,which not only provides the optical gain which is absent from native Si substrates and enables complete photonic functionalities on chip,but also improves the system performance through advanced heterogeneous integrated packaging.This paper reviews recent progress of silicon-based optoelectronic heterogeneous integration in high performance optical interconnection.The research status,development trend and application of ultra-low loss optical waveguides,high-speed detectors,high-speed modulators,lasers and 2D,2.5D,3D and monolithic integration are focused on.
基金partially supported by the Fundamental Research Funds for the Central Universities(GK202207018)of China。
文摘We study the closed range property and the strict singularity of integration operators acting on the spaces F(p,pα-2,s).We completely characterize the closed range property of the Volterra companion operator I_(g)on F(p,pα-2,s),which generalizes the existing results and answers a question raised in[A.Anderson,Integral Equations Operator Theory,69(2011),no.1,87-99].For the Volterra operator J_(g),we show that,for 0<α≤1,J_(g)never has a closed range on F(p,pα-2,s).We then prove that the notions of compactness,weak compactness and strict singularity coincide in the case of J_(g)acting on F(p,p-2,s).
基金supported by the National Natural Science Foundation of China (No.32070656)the Nanjing University Deng Feng Scholars Program+1 种基金the Priority Academic Program Development (PAPD) of Jiangsu Higher Education Institutions,China Postdoctoral Science Foundation funded project (No.2022M711563)Jiangsu Funding Program for Excellent Postdoctoral Talent (No.2022ZB50)
文摘Plant morphogenesis relies on precise gene expression programs at the proper time and position which is orchestrated by transcription factors(TFs)in intricate regulatory networks in a cell-type specific manner.Here we introduced a comprehensive single-cell transcriptomic atlas of Arabidopsis seedlings.This atlas is the result of meticulous integration of 63 previously published scRNA-seq datasets,addressing batch effects and conserving biological variance.This integration spans a broad spectrum of tissues,including both below-and above-ground parts.Utilizing a rigorous approach for cell type annotation,we identified 47 distinct cell types or states,largely expanding our current view of plant cell compositions.We systematically constructed cell-type specific gene regulatory networks and uncovered key regulators that act in a coordinated manner to control cell-type specific gene expression.Taken together,our study not only offers extensive plant cell atlas exploration that serves as a valuable resource,but also provides molecular insights into gene-regulatory programs that varies from different cell types.
基金This work was supported by the National Natural Science Foundation of China(U2133208,U20A20161).
文摘With the popularization of the Internet and the development of technology,cyber threats are increasing day by day.Threats such as malware,hacking,and data breaches have had a serious impact on cybersecurity.The network security environment in the era of big data presents the characteristics of large amounts of data,high diversity,and high real-time requirements.Traditional security defense methods and tools have been unable to cope with the complex and changing network security threats.This paper proposes a machine-learning security defense algorithm based on metadata association features.Emphasize control over unauthorized users through privacy,integrity,and availability.The user model is established and the mapping between the user model and the metadata of the data source is generated.By analyzing the user model and its corresponding mapping relationship,the query of the user model can be decomposed into the query of various heterogeneous data sources,and the integration of heterogeneous data sources based on the metadata association characteristics can be realized.Define and classify customer information,automatically identify and perceive sensitive data,build a behavior audit and analysis platform,analyze user behavior trajectories,and complete the construction of a machine learning customer information security defense system.The experimental results show that when the data volume is 5×103 bit,the data storage integrity of the proposed method is 92%.The data accuracy is 98%,and the success rate of data intrusion is only 2.6%.It can be concluded that the data storage method in this paper is safe,the data accuracy is always at a high level,and the data disaster recovery performance is good.This method can effectively resist data intrusion and has high air traffic control security.It can not only detect all viruses in user data storage,but also realize integrated virus processing,and further optimize the security defense effect of user big data.
基金supported by the National Natural Science Foundation of China(NFSCGrant No.42030410)+2 种基金Laoshan Laboratory(No.LSKJ202202402)the Strategic Priority Research Program of the Chinese Academy of Sciences(Grant No.XDB40000000)the Startup Foundation for Introducing Talent of NUIST.
文摘El Niño-Southern Oscillation(ENSO)is the strongest interannual climate mode influencing the coupled ocean-atmosphere system in the tropical Pacific,and numerous dynamical and statistical models have been developed to simulate and predict it.In some simplified coupled ocean-atmosphere models,the relationship between sea surface temperature(SST)anomalies and wind stress(τ)anomalies can be constructed by statistical methods,such as singular value decomposition(SVD).In recent years,the applications of artificial intelligence(AI)to climate modeling have shown promising prospects,and the integrations of AI-based models with dynamical models are active areas of research.This study constructs U-Net models for representing the relationship between SSTAs andτanomalies in the tropical Pacific;the UNet-derivedτmodel,denoted asτUNet,is then used to replace the original SVD-basedτmodel of an intermediate coupled model(ICM),forming a newly AI-integrated ICM,referred to as ICM-UNet.The simulation results obtained from ICM-UNet demonstrate their ability to represent the spatiotemporal variability of oceanic and atmospheric anomaly fields in the equatorial Pacific.In the ocean-only case study,theτUNet-derived wind stress anomaly fields are used to force the ocean component of the ICM,the results of which also indicate reasonable simulations of typical ENSO events.These results demonstrate the feasibility of integrating an AI-derived model with a physics-based dynamical model for ENSO modeling studies.Furthermore,the successful integration of the dynamical ocean models with the AI-based atmospheric wind model provides a novel approach to ocean-atmosphere interaction modeling studies.
基金the Project"Research on the protection technology of endogenous safety for industrial control system"supported by National Science and Technology Major Project(2016YFB08002)。
文摘Although static program analysis methods are frequently employed to enhance software quality,their efficiency in commercial settings is limited by their high false positive rate.The EUGENE tool can effectively lower the false positive rate.However,in continuous integration(CI)environments,the code is always changing,and user feedback from one version of the software cannot be applied to a subsequent version.Additionally,people find it difficult to distinguish between true positives and false positives in the analytical output.In this study,we developed the EUGENE-CI technique to address the CI problem and the EUGENE-rank lightweight heuristic algorithm to rate the reports of the analysis output in accordance with the likelihood that they are true positives.On the three projects ethereum,go-cloud,and kubernetes,we assessed our methodologies.According to the trial findings,EUGENE-CI may drastically reduce false positives while EUGENE-rank can make it much easier for users to identify the real positives among a vast number of reports.We paired our techniques with GoInsight~1 and discovered a vulnerability.We also offered a patch to the community.
基金funding from CONAHCYT by the grant Ciencia Básica y/o Ciencia de Frontera Modalidad Paradigmas y Controversias de la Ciencia,Grant Number 319996:“Análisis integral de datos transcriptómicos y metabolómicos asociados a la calidad de los frutos de guanábana(Annona muricata L.)durante almacenamiento poscosecha”.
文摘Soursop(Annona muricata L.)is a tropical fruit highly valued for its uniqueflavor,nutritional value,and health-promoting properties.The ripening process of soursop involves complex changes in gene expression and metabo-lite accumulation,which have been studied using various omics technologies.Transcriptome analysis has provided insights into the regulation of key genes involved in ripening,while metabolic compound analysis has revealed the presence of numerous bioactive compounds with potential health benefits.However,the integration of transcrip-tome and metabolite compound data has not been extensively explored in soursop.Therefore,in this paper,we present a comprehensive analysis of the transcriptome and phenolic compound profiles of soursop during ripen-ing.The integration analysis showed that the genes and phenolic compounds were mainly involved in the starch and sucrose metabolism pathways during soursop ripening.Further,the phenolic compounds Kaempferol 3-Q-galactoside,Procyanidin C1,Procyanidin trimmer C1,and m-Coumaric,as well as the genes Ubiquitin-like protein 5(UBL5_ARATH),ATP-dependent zinc metalloprotease FTSH8(FTSH8_ORYSJ),Zinc transporter 4(ZIP4_AR-ATH),Thioredoxin-like 3-1(TRL31_ORYSJ),Mitogen-activated protein kinase YODA(YODA_ARATH),R-man-delonitrile lyase-like(MGL_ARATH),26s protease regulatory subunit 6A homolog(PRS6_SOLLC),Cytochrome P45072A13(C7A13ARATH),Cytochrome P45084A1(C84A1_ARATH)and Homoserine O-trans-acetylase(MET2-ORYSJ)were correlated and differentially accumulated and expressed,respectively.Our study provides new insights into the molecular mechanisms underlying soursop ripening and may contribute to the development of strategies for improving the nutritional quality and shelf life of this important fruit.
基金supported by the National Key R&D Program of China(2021YFB2401800)the National Natural Science Foundation of China(21875022,22179008)+4 种基金the Yibin‘Jie Bang Gua Shuai’(2022JB004)the support from the Beijing Nova Program(20230484241)the support from the Postdoctoral Fellowship Program of CPSF(GZB20230931)the support from the 4B7B beam line of Beijing Synchrotron Radiation Facility(2021-BEPC-PT-005924,2021-BEPC-PT-005967)BL08U1A beam line of Shanghai Synchrotron Radiation Facility(2021-SSRF-PT-017710)。
文摘The rapid development of electric vehicles and portable energy storage systems demands improvements in the energy density and cost-effectiveness of lithium-ion batteries,a domain in which Lithium-rich layered cathode(LLO)materials inherently excel.However,these materials face practical challenges,such as low initial Coulombic efficiency,inferior cycle/rate performance,and voltage decline during cycling,which limit practical application.Our study introduces a surface multi-component integration strategy that incorporates oxygen vacancies into the pristine LLO material Li1.2Mn_(0.6)Ni_(0.2)O_(2).This process involves a brief citric acid treatment followed by calcination,aiming to explore rate-dependent degradation behavior.The induced surface oxygen vacancies can reduce surface oxygen partial pressure and diminish the generation of O_(2)and other highly reactive oxygen species on the surface,thereby facilitating the activation of Li ions trapped in tetrahedral sites while overcoming transport barriers.Additionally,the formation of a spinel-like phase with 3D Li+diffusion channels significantly improves Li^(+)diffusion kinetics and stabilizes the surface structure.The optimally modified sample boasts a discharge capacity of 299.5 mA h g^(-1)at a 0.1 C and 251.6 mA h g^(-1)at a 1 C during the initial activation cycle,with an impressive capacity of 222.1 mA h g^(-1)at a 5 C.Most notably,it retained nearly 70%of its capacity after 300 cycles at this elevated rate.This straightforward,effective,and highly viable modification strategy provides a crucial resolution for overcoming challenges associated with LLO materials,making them more suitable for practical application.
文摘Understanding the neural underpinning of human gait and balance is one of the most pertinent challenges for 21st-century translational neuroscience due to the profound impact that falls and mobility disturbances have on our aging population.Posture and gait control does not happen automatically,as previously believed,but rather requires continuous involvement of central nervous mechanisms.To effectively exert control over the body,the brain must integrate multiple streams of sensory information,including visual,vestibular,and somatosensory signals.The mechanisms which underpin the integration of these multisensory signals are the principal topic of the present work.Existing multisensory integration theories focus on how failure of cognitive processes thought to be involved in multisensory integration leads to falls in older adults.Insufficient emphasis,however,has been placed on specific contributions of individual sensory modalities to multisensory integration processes and cross-modal interactions that occur between the sensory modalities in relation to gait and balance.In the present work,we review the contributions of somatosensory,visual,and vestibular modalities,along with their multisensory intersections to gait and balance in older adults and patients with Parkinson’s disease.We also review evidence of vestibular contributions to multisensory temporal binding windows,previously shown to be highly pertinent to fall risk in older adults.Lastly,we relate multisensory vestibular mechanisms to potential neural substrates,both at the level of neurobiology(concerning positron emission tomography imaging)and at the level of electrophysiology(concerning electroencephalography).We hope that this integrative review,drawing influence across multiple subdisciplines of neuroscience,paves the way for novel research directions and therapeutic neuromodulatory approaches,to improve the lives of older adults and patients with neurodegenerative diseases.