Stroke is a major cause of death and disability worldwide.It is characterized by a highly interconnected and multiphasic neuropathological cascade of events,in which an intense and protracted inflammatory response pla...Stroke is a major cause of death and disability worldwide.It is characterized by a highly interconnected and multiphasic neuropathological cascade of events,in which an intense and protracted inflammatory response plays a crucial role in worsening brain injury.Neuroinflammation,a key player in the pathophysiology of stroke,has a dual role.In the acute phase of stroke,neuroinflammation exacerbates brain injury,contributing to neuronal damage and blood–brain barrier disruption.This aspect of neuroinflammation is associated with poor neurological outcomes.Conversely,in the recovery phase following stroke,neuroinflammation facilitates brain repair processes,including neurogenesis,angiogenesis,and synaptic plasticity.The transition of neuroinflammation from a harmful to a reparative role is not well understood.Therefore,this review seeks to explore the mechanisms underlying this transition,with the goal of informing the development of therapeutic interventions that are both time-and context-specific.This review aims to elucidate the complex and dual role of neuroinflammation in stroke,highlighting the main actors,biomarkers of the disease,and potential therapeutic approaches.展开更多
In this article,by employing the Hirota bilinear approach and the long wave limit method,we not only derive soliton solutions,lump solutions,and hybrid solutions for the(2+1)-dimensional Yu-Toda-Sasa-Fukuyama(YTSF)equ...In this article,by employing the Hirota bilinear approach and the long wave limit method,we not only derive soliton solutions,lump solutions,and hybrid solutions for the(2+1)-dimensional Yu-Toda-Sasa-Fukuyama(YTSF)equation,but also analyze the dynamical behaviors of nonlinear local wave propagation in shallow water.Firstly,based on the Hirota bilinear approach,one to four-order soliton solutions of the YTSF equation are obtained,and the effects of different parameters on the amplitude,propagation trajectory,and displacement of solitons are investigated.Secondly,using the long wave limit approach,one to three-order lump solutions and various physical quantities of the YTSF equation are derived.It is found that the real and imaginary parts of the parameter pi dominate the propagation trajectory and the shape of lump waves,respectively.Furthermore,we construct the hybrid solution for the YTSF equation,leading to the conclusion that the interaction between lumps and solitons constitutes an elastic collision.To intuitively understand the dynamic behaviors of these solutions,we conduct numerical simulations to present vivid three-dimensional visualizations.展开更多
Under complex working conditions,accurate prediction of the remaining useful life(RUL)of lithium-ion batteries is of great significance to ensure the stable operation of energy storage systems,the safe driving of elec...Under complex working conditions,accurate prediction of the remaining useful life(RUL)of lithium-ion batteries is of great significance to ensure the stable operation of energy storage systems,the safe driving of electric vehicles,and the continuous power supply of electronic devices.This paper systematically describes the RUL prediction methods of lithium-ion batteries and comprehensively summarizes the development status and future trends in this field.First,the battery degradation mechanisms and lightweight data acquisition are analyzed.Secondly,a systematic classification model is constructed for the more widely used lithium battery RUL prediction methods,and the application characteristics and implementation limitations of different methods are analyzed in detail.An innovative classification framework for hybrid methods is proposed based on the depth of physical-data interaction.Then,collaborative modelling of calendar ageing and cyclic ageing is discussed,revealing their coupled effects and corresponding RUL prediction methods.Finally,the technical bottlenecks faced by the current RUL prediction of lithium batteries are identified,potential solutions are proposed,and the future development trends are outlined.展开更多
BACKGROUND Due to the increasing rate of thyroid nodules diagnosis,and the desire to avoid the unsightly cervical scar,remote thyroidectomies were invented and are increasingly performed.Transoral endoscopic thyroidec...BACKGROUND Due to the increasing rate of thyroid nodules diagnosis,and the desire to avoid the unsightly cervical scar,remote thyroidectomies were invented and are increasingly performed.Transoral endoscopic thyroidectomy vestibular approach and trans-areolar approaches(TAA)are the two most commonly used remote approaches.No previous meta-analysis has compared postoperative infections and swallowing difficulties among the two procedures.AIM To compared the same among patients undergoing lobectomy for unilateral thyroid carcinoma/benign thyroid nodule.METHODS We searched PubMed MEDLINE,Google Scholar,and Cochrane Library from the date of the first published article up to August 2025.The term used were transoral thyroidectomy vestibular approach,trans areolar thyroidectomy,scarless thyroidectomy,remote thyroidectomy,infections,postoperative,inflammation,dysphagia,and swallowing difficulties.We identified 130 studies,of them,30 full texts were screened and only six studies were included in the final meta-analysis.RESULTS Postoperative infections were not different between the two approaches,odd ratio=1.33,95%confidence interval:0.50-3.53,theχ2 was 1.92 and the P-value for overall effect of 0.57.Similarly,transient swallowing difficulty was not different between the two forms of surgery,with odd ratio=0.91,95%confidence interval:0.35-2.40;theχ2 was 1.32,and the P-value for overall effect of 0.85.CONCLUSION No significant statistical differences were evident between trans-oral endoscopic Mirghani H.Infections and swallowing difficulty in scarless thyroidectomy WJCC https://www.wjgnet.com 2 January 6,2026 Volume 14 Issue 1 thyroidectomy vestibular approach and trans-areolar approach regarding postoperative infection and transient swallowing difficulties.Further longer randomized trials are needed.展开更多
This paper explores the algebraic essence of universal logic functions(ULFs)from an algebraic perspective.Under the framework of semi-tensor product of matrices,the“sequential nature”of ULFs is revealed.Utilizing th...This paper explores the algebraic essence of universal logic functions(ULFs)from an algebraic perspective.Under the framework of semi-tensor product of matrices,the“sequential nature”of ULFs is revealed.Utilizing the nature,a technique called universal transformation method is proposed,by which any ULF can be transformed into an equivalent expression with desired features that facilitate achieving specific objectives,such as modeling,analyzing and synthesizing universal logical systems.Furthermore,several useful logical operators are constructed in a mixed-dimensional situation,including power-raising operator,power-descending operator,erasure operator,and appending operator.Finally,these results are applied to model and analyze finite state machines and their networks,which demonstrate the practical value of the method and operators.展开更多
Physics-informed neural networks(PINNs)have been shown as powerful tools for solving partial differential equations(PDEs)by embedding physical laws into the network training.Despite their remarkable results,complicate...Physics-informed neural networks(PINNs)have been shown as powerful tools for solving partial differential equations(PDEs)by embedding physical laws into the network training.Despite their remarkable results,complicated problems such as irregular boundary conditions(BCs)and discontinuous or high-frequency behaviors remain persistent challenges for PINNs.For these reasons,we propose a novel two-phase framework,where a neural network is first trained to represent shape functions that can capture the irregularity of BCs in the first phase,and then these neural network-based shape functions are used to construct boundary shape functions(BSFs)that exactly satisfy both essential and natural BCs in PINNs in the second phase.This scheme is integrated into both the strong-form and energy PINN approaches,thereby improving the quality of solution prediction in the cases of irregular BCs.In addition,this study examines the benefits and limitations of these approaches in handling discontinuous and high-frequency problems.Overall,our method offers a unified and flexible solution framework that addresses key limitations of existing PINN methods with higher accuracy and stability for general PDE problems in solid mechanics.展开更多
The capacity of the central nervous system for structural plasticity and regeneration is commonly believed to show a decreasing progression from“small and simple”brains to the larger,more complex brains of mammals.H...The capacity of the central nervous system for structural plasticity and regeneration is commonly believed to show a decreasing progression from“small and simple”brains to the larger,more complex brains of mammals.However,recent findings revealed that some forms of neural plasticity can show a reverse trend.Although plasticity is a well-preserved,transversal feature across the animal world,a variety of cell populations and mechanisms seem to have evolved to enable structural modifications to take place in widely different brains,likely as adaptations to selective pressures.Increasing evidence now indicates that a trade-off has occurred between regenerative(mostly stem cell–driven)plasticity and developmental(mostly juvenile)remodeling,with the latter primarily aimed not at brain repair but rather at“sculpting”the neural circuits based on experience.In particular,an evolutionary trade-off has occurred between neurogenic processes intended to support the possibility of recruiting new neurons throughout life and the different ways of obtaining new neurons,and between the different brain locations in which plasticity occurs.This review first briefly surveys the different types of plasticity and the complexity of their possible outcomes and then focuses on recent findings showing that the mammalian brain has a stem cell–independent integration of new neurons into pre-existing(mature)neural circuits.This process is still largely unknown but involves neuronal cells that have been blocked in arrested maturation since their embryonic origin(also termed“immature”or“dormant”neurons).These cells can then restart maturation throughout the animal's lifespan to become functional neurons in brain regions,such as the cerebral cortex and amygdala,that are relevant to high-order cognition and emotions.Unlike stem cell–driven postnatal/adult neurogenesis,which significantly decreases from small-brained,short-living species to large-brained ones,immature neurons are particularly abundant in large-brained,long-living mammals,including humans.The immature neural cell populations hosted in these complex brains are an interesting example of an“enlarged road”in the phylogenetic trend of plastic potential decreases commonly observed in the animal world.The topic of dormant neurons that covary with brain size and gyrencephaly represents a prospective turning point in the field of neuroplasticity,with important translational outcomes.These cells can represent a reservoir of undifferentiated neurons,potentially granting plasticity within the high-order circuits subserving the most sophisticated cognitive skills that are important in the growing brains of young,healthy individuals and are frequently affected by debilitating neurodevelopmental and degenerative disorders.展开更多
Objective: To analyze the impact of motivational nursing under the solution-focused approach on health behaviors in surgical care for bladder cancer patients. Methods: A sample of 72 bladder cancer patients who underw...Objective: To analyze the impact of motivational nursing under the solution-focused approach on health behaviors in surgical care for bladder cancer patients. Methods: A sample of 72 bladder cancer patients who underwent surgical treatment from September 2024 to September 2025 was randomly divided into groups using a random number table. Group A received motivational nursing under the solution-focused approach, while Group B received conventional nursing. Health behavior scores and complication indicators were compared between the two groups. Results: Group A had higher scores on the Health-Promoting Lifestyle Profile II (HPLP-Ⅱ) than Group B, with p < 0.05. The postoperative complication rate in Group A was lower than that in Group B, with p < 0.05. Conclusion: For bladder cancer patients undergoing surgery, receiving motivational nursing under the solution-focused approach can improve health behaviors, alleviate negative emotions, and is highly feasible and effective.展开更多
Signal transduction in a cell is mostly mediated with biochemical reactions which are noisy and often modeled with chemical master equations or Langevin type of dynamics.Thus stochastic simulation constitutes a major ...Signal transduction in a cell is mostly mediated with biochemical reactions which are noisy and often modeled with chemical master equations or Langevin type of dynamics.Thus stochastic simulation constitutes a major part of computation in cell signaling.Nevertheless,the presence of a wide span of time scales or molecular numbers in various pathways may lead to trouble in computation efficiency or accuracy.To avoid this problem,the commonly employed variational method evolves the whole probability distribution and reduces the stochastic equations to deterministic ones of only a few parameters.However,the design of the left variational basis is essential for its successful application,especially to large networks.In this paper,we extend the conventional polynomial basis to the Fourier and further the Gaussian basis,much facilitating description of multi-peaked or localized non-Gaussian distributions and at the same time avoiding numerical instability and computational complexity frequently encountered with conventional basis.The extension here is demonstrated in several typical biochemical signaling networks and achieves similar accuracy as the benchmark Gillespie algorithm,but with much less running time,which seems to open new opportunities in the variational approach to efficient analysis of noisy dynamics.展开更多
A Cu-1.9Ni-1.9Co-0.9Si(mass fraction,%)alloy with high strength and electrical conductivity was designed by cluster formula approach.The microstructure evolution of the alloy during thermomechanical treatment was syst...A Cu-1.9Ni-1.9Co-0.9Si(mass fraction,%)alloy with high strength and electrical conductivity was designed by cluster formula approach.The microstructure evolution of the alloy during thermomechanical treatment was systematically investigated.The strengthening mechanism and electrical conductivity of the alloy were discussed in detail.The optimal thermomechanical treatment process was as follows:solid solution→80%cold rolling→(450℃,4 h)aging→50%cold rolling→(400℃,4 h)aging.The designed alloy achieved excellent comprehensive properties with a microhardness of HV 260,a yield strength of 843 MPa,a tensile strength of 884 MPa,and an electrical conductivity of 42.6%(IACS).Compared to direct aging treatment,the designed alloy subjected to multi-stage thermomechanical treatment had refined grains,high density of dislocations,and accelerated of precipitation of(Ni,Co)_(2)Si precipitates.High strength was mainly attributed to the combined effect of dislocation strengthening,work hardening and sub-grain strengthening,while good electrical conductivity was maintained through the precipitation of the large number of nanoparticles.展开更多
Audio-visual speaker tracking aims to determine the locations of multiple speakers in the scene by leveraging signals captured from multisensor platforms.Multimodal fusion methods can improve both the accuracy and rob...Audio-visual speaker tracking aims to determine the locations of multiple speakers in the scene by leveraging signals captured from multisensor platforms.Multimodal fusion methods can improve both the accuracy and robustness of speaker tracking.However,in complex multispeaker tracking scenarios,critical challenges such as cross-modal feature discrepancy,weak sound source localisation ambiguity and frequent identity switch errors remain unresolved,which severely hinder the modelling of speaker identity consistency and consequently lead to degraded tracking accuracy and unstable tracking trajectories.To this end,this paper proposes a multimodal multispeaker tracking network using audio-visual contrastive learning(AVCLNet).By integrating heterogeneous modal representations into a unified space through audio-visual contrastive learning,which facilitates cross-modal feature alignment,mitigates cross-modal feature bias and enhances identity-consistent representations.In the audio-visual measurement stage,we design a vision-guided weak sound source weighted enhancement method,which leverages visual cues to establish cross-modal mappings and employs a spatiotemporal dynamic weighted mechanism to improve the detectability of weak sound sources.Furthermore,in the data association phase,a dual geometric constraint strategy is introduced by combining the 2D and 3D spatial geometric information,reducing frequent identity switch errors.Experiments on the AV16.3 and CAV3D datasets show that AVCLNet outperforms state-of-the-art methods,demonstrating superior robustness in multispeaker scenarios.展开更多
The exploration of high-performance materials presents a fundamental challenge in materials science,particularly in predicting properties for materials beyond the known range of target property values(extrapolation).T...The exploration of high-performance materials presents a fundamental challenge in materials science,particularly in predicting properties for materials beyond the known range of target property values(extrapolation).This study formally investigated the interpolation-extrapolation trade-off phenomenon in the prediction capabilities of machine learning(ML)models.A new ML scheme was proposed,featuring a newly developed ML model and forward cross-validation-based hyperparameter optimization,which demonstrated superior extrapolation prediction across multiple materials datasets.Based on this ML scheme,multi-objective optimization was performed to systematically identify lightweight Mg-Zn-Al alloys with both high bulk modulus and high Debye temperature.Subsequently,the designed alloys were validated through density functional theory calculations.Furthermore,a three-category classification strategy was summarized through the dual-driven approach combining domain knowledge and data,emphasizing their synergistic potential for materials discovery.The practical framework developed in this study provides a novel research perspective for exploring high-performance materials.展开更多
The neutron-rich nucleus^(22)C,located at the neutron drip line,exhibits intriguing structural properties,such as its Borromean nature and potential two-neutron halo configuration.Despite experimental advancements,unc...The neutron-rich nucleus^(22)C,located at the neutron drip line,exhibits intriguing structural properties,such as its Borromean nature and potential two-neutron halo configuration.Despite experimental advancements,uncertainties persist in the two-neutron separation energy S_(2n)and the radius of matter for this attractive nucleus^(22)C.In this study,we employed the three-body Faddeev approach to investigate the ground-state properties of ^(22)C,constrained by the recently deduced matter radius.By optimizing the neutron-core and three-body interactions to reproduce the experimental radius,the two-neutron separation energy S_(2n) was redetermined,revealing a weakly bound system dominated by the s-wave configuration.Additionally,an excited state exhibiting an Efimov-like pattern was identified by analyzing the specific density distributions and relative distances in the three-body system,highlighting the geometric similarity between the ground and excited states.展开更多
With the rapid development of electric vehicles and grid-scale renewable integration,the demand for lithium-ion batteries(LIBs)has significantly increased with high expectations on enhanced energy density,cycle stabil...With the rapid development of electric vehicles and grid-scale renewable integration,the demand for lithium-ion batteries(LIBs)has significantly increased with high expectations on enhanced energy density,cycle stability,and failure resilience.Electrochemical models(EMs),serving as pivotal mechanismdriven analytical frameworks in battery research and applications,demonstrate unprecedented quantitative fidelity in characterizing intricate multi-physics dynamics for the next-generation battery management systems(BMS).The breakthrough innovations in artificial intelligence(AI)driven methods have revolutionized the dynamic modeling of LIBs.However,the deployment of AI-augmented EMs in BMS faces significant identifiability challenges due to strong parameter coupling.In addition,research on model simplification,parameter determination,and dynamic parameter identification remains largely fragmented.There is a lack of a comprehensive review to pave the way for the cross-domain innovations in BMS.To fill this gap,this paper presents a systematic review of the EMs for LIBs and examines the advancements in parameter determination techniques from both experimental measurement and numerical simulation perspectives.Besides,a comprehensive assessment of the progress in parameter identification from the standpoint of dynamic recognition is presented,encompassing both modelbased approaches and intelligent methods.Additionally,from the BMS standpoint,the strengths and limitations of existing approaches are evaluated.Finally,a coordinated framework for multi-stage identification needs to be established in the future.The potential of digital twins(DT),deep reinforcement learning(DRL),and large language models(LLMs)in enhancing EMs also warrants further exploration.The purpose of this work is to provide insights and guidance for the future development of EMs in LIB applications.展开更多
This paper addresses the three-dimensional(3-D)approach angle constrained cooperative guidance problem for speed-varying missiles against maneuvering targets.First,the guidance problem is formulated in a relative refe...This paper addresses the three-dimensional(3-D)approach angle constrained cooperative guidance problem for speed-varying missiles against maneuvering targets.First,the guidance problem is formulated in a relative reference frame and a virtual control input is selected.Then,the cooperative guidance law is designed on the basis of a prediction-correction framework.The time-to-go under the baseline command is estimated by an efficient prediction method with a realistic aerodynamic model and a biased command is developed by utilizing the time-to-go predictions for synchronizing different missiles'impact times.The design of the biased command is decoupled into the individual design of its direction and magnitude.It is proved that the designed cooperative guidance law can make the time-to-go consensus error converge to zero before interception.Finally,the designed guidance law is validated through a series of numerical simulations.展开更多
The development of pattern-based traditional Chinese medicine(TCM)compound preparations constitutes a core domain that represents the principle of pattern differentiation-based treatment,a hallmark of TCM.However,the ...The development of pattern-based traditional Chinese medicine(TCM)compound preparations constitutes a core domain that represents the principle of pattern differentiation-based treatment,a hallmark of TCM.However,the field has long been constrained by scientific and regulatory challenges in animal modeling,efficacy evaluation,and clinical positioning.This article proposes a new research and development(R&D)paradigm strategically based on human use experience(HUE)and centered on the patient as the key to overcoming these bottlenecks and achieving high-quality progress.We systematically dissect the traditional problems in this field and demonstrate the pivotal role of high-quality HUE in enabling precise clinical positioning and optimizing R&D pathways(e.g.,applying for exemptions from non-clinical studies).HUE guides the implementation of the“pattern-symptom integration”model.Furthermore,we detail the implementation of the patient-centered concept throughout the process of clinical trial design,collection of patients’experience data,clinical outcome assessment,and benefit-risk assessment.The integrative application of artificial intelligence in the R&D of pattern-based TCM drugs is also specifically explored.By synthesizing the“TCM theory,HUE,and clinical trials”evidence system,this article aims to provide a systematic strategic framework for establishing an R&D pathway that adheres to the intrinsic principles of TCM while simultaneously meeting modern scientific standards.展开更多
Groundwater modeling remains challenging due to heterogeneity and complexity of aquifer systems,necessitating endeavors to quantify Groundwater Levels(GWL)dynamics to inform policymakers and hydrogeologists.This study...Groundwater modeling remains challenging due to heterogeneity and complexity of aquifer systems,necessitating endeavors to quantify Groundwater Levels(GWL)dynamics to inform policymakers and hydrogeologists.This study introduces a novel Fuzzy Nonlinear Additive Regression(FNAR)model to predict monthly GWL in an unconfined aquifer in eastern Iran,using a 19-year(1998–2017)dataset from 11 piezometric wells.Under three distinct scenarios with progressively increasing input complexity,the study utilized readily available climate data,including Precipitation(Prc),Temperature(Tave),Relative Humidity(RH),and Evapotranspiration(ETo).The dataset was split into training(70%)and validation(30%)subsets.Results showed that among three input scenarios,Scenario 3(Sc3,incorporating all four variables)achieved the best predictive performance,with RMSE ranging from 0.305 m to 0.768 m,MAE from 0.203 m to 0.522 m,NSE from 0.661 to 0.980,and PBIAS from 0.771%to 0.981%,indicating low bias and high reliability.However,Sc2(excluding ETo)with RMSE ranging from 0.4226 m to 0.9909 m,MAE from 0.3418 m to 0.8173 m,NSE from 0.2831 to 0.9674,and PBIAS from−0.598%to 0.968%across different months offers practical advantages in data-scarce settings.The FNAR model outperforms conventional Fuzzy Least Squares Regression(FLSR)and holds promise for GWL forecasting in data-scarce regions where physical or numerical models are impractical.Future research should focus on integrating FNAR with deep learning algorithms and real-time data assimilation expanding applications across diverse hydrogeological settings.展开更多
The photoacoustic imaging of lipid is intrinsically constrained by the feeble nature of endogenous lipid signals,posing a persistent sensitivity challenge that demands innovative solutions.Although adopting high-effic...The photoacoustic imaging of lipid is intrinsically constrained by the feeble nature of endogenous lipid signals,posing a persistent sensitivity challenge that demands innovative solutions.Although adopting high-efficiency excitation and detection elements may improve the imaging sensitivity to a certain extent,the application of the elements is inevitably subject to various limitations in practical applications,particularly during in vivo imaging and endoscopic imaging.In this study,we propose a multi-combinatorial approach to enhance the sensitivity of lipid photoacoustic imaging.The approach involves wavelet transform processing of one-dimensional A-line signals,gradient-based denoising of two-dimensional B-scan images,and finally,threedimensional spatial weighted averaging of the data processed by the previous two steps.This method not only significantly improves the signal-to-noise ratio(SNR)in distinguished feature regions of the image by around 10 dB,but also efficiently extracts weak signals with no distinct features in the original image.After processing with this method,the images acquired under single scanning were compared with those obtained under multiple scanning.The results showed highly consistent image features,with the structural similarity index increasing from 0.2 to 0.8,confirming the accuracy and reliability of the multi-combinatorial approach.展开更多
The 17 Sustainable Development Goals(SDGs)for 2030,adopted by all United Nations member states in 2015,are facing a range of challenges.Factors such as climate change,regional conflicts and economic recession are havi...The 17 Sustainable Development Goals(SDGs)for 2030,adopted by all United Nations member states in 2015,are facing a range of challenges.Factors such as climate change,regional conflicts and economic recession are having a significant impact,particularly on global poverty governance.As a platform for dialogue,exchange and technical cooperation,the 2025 International Seminar on Global Poverty Reduction Partnerships was held in Beijing on 10 December 2025.展开更多
High-Mach-number plasma jets have been extensively investigated in both astrophysical and laboratory contexts.In this work,we revisit the framework of magnetohydrodynamic(MHD)theory and introduce a new analytical appr...High-Mach-number plasma jets have been extensively investigated in both astrophysical and laboratory contexts.In this work,we revisit the framework of magnetohydrodynamic(MHD)theory and introduce a new analytical approach for examining plasma jets generated by intense laser-plasma interactions.Specifically,we reformulate the fundamental MHD equations to elucidate the governing factors of local plasma density evolution.Furthermore,MHD simulations of laser irradiation on planar targets demonstrate that impact pressure plays a dominant role in the propagation of high-Mach-number plasma jets.In addition,a pronounced dependence on the atomic number is identified:higher-Z materials amplify the impact pressure,suggesting that metallicity exerts a significant influence on the morphology and dynamics of astrophysical jets.展开更多
基金supported by European Union-NextGeneration EU under the Italian University and Research(MUR)National Innovation Ecosystem grant ECS00000041-VITALITY-CUP E13C22001060006(to MdA)。
文摘Stroke is a major cause of death and disability worldwide.It is characterized by a highly interconnected and multiphasic neuropathological cascade of events,in which an intense and protracted inflammatory response plays a crucial role in worsening brain injury.Neuroinflammation,a key player in the pathophysiology of stroke,has a dual role.In the acute phase of stroke,neuroinflammation exacerbates brain injury,contributing to neuronal damage and blood–brain barrier disruption.This aspect of neuroinflammation is associated with poor neurological outcomes.Conversely,in the recovery phase following stroke,neuroinflammation facilitates brain repair processes,including neurogenesis,angiogenesis,and synaptic plasticity.The transition of neuroinflammation from a harmful to a reparative role is not well understood.Therefore,this review seeks to explore the mechanisms underlying this transition,with the goal of informing the development of therapeutic interventions that are both time-and context-specific.This review aims to elucidate the complex and dual role of neuroinflammation in stroke,highlighting the main actors,biomarkers of the disease,and potential therapeutic approaches.
基金Supported by the National Natural Science Foundation of China(12001424,12271324)the Natural Science Basic research program of Shaanxi Province(2021JZ-21)+1 种基金the China Postdoctoral Science Foundation(2020M673332)Xi’an University,Xi’an Science and Technology Plan Wutongshu Technology Transfer Action Innovation Team(25WTZD07)。
文摘In this article,by employing the Hirota bilinear approach and the long wave limit method,we not only derive soliton solutions,lump solutions,and hybrid solutions for the(2+1)-dimensional Yu-Toda-Sasa-Fukuyama(YTSF)equation,but also analyze the dynamical behaviors of nonlinear local wave propagation in shallow water.Firstly,based on the Hirota bilinear approach,one to four-order soliton solutions of the YTSF equation are obtained,and the effects of different parameters on the amplitude,propagation trajectory,and displacement of solitons are investigated.Secondly,using the long wave limit approach,one to three-order lump solutions and various physical quantities of the YTSF equation are derived.It is found that the real and imaginary parts of the parameter pi dominate the propagation trajectory and the shape of lump waves,respectively.Furthermore,we construct the hybrid solution for the YTSF equation,leading to the conclusion that the interaction between lumps and solitons constitutes an elastic collision.To intuitively understand the dynamic behaviors of these solutions,we conduct numerical simulations to present vivid three-dimensional visualizations.
基金supported by the National Natural Science Foundation of China(No.U23A20651)the Central Government Guides Local Science and Technology Development Foundation(No.2023ZYDF022)+1 种基金the Sichuan Science and Technology Program(2024ZDZX0031)the Open Fund Project of State Key Laboratory of Mining Response and Disaster Prevention and Control in Deep Coal Mines(No.SKLMRDPC23KF19).
文摘Under complex working conditions,accurate prediction of the remaining useful life(RUL)of lithium-ion batteries is of great significance to ensure the stable operation of energy storage systems,the safe driving of electric vehicles,and the continuous power supply of electronic devices.This paper systematically describes the RUL prediction methods of lithium-ion batteries and comprehensively summarizes the development status and future trends in this field.First,the battery degradation mechanisms and lightweight data acquisition are analyzed.Secondly,a systematic classification model is constructed for the more widely used lithium battery RUL prediction methods,and the application characteristics and implementation limitations of different methods are analyzed in detail.An innovative classification framework for hybrid methods is proposed based on the depth of physical-data interaction.Then,collaborative modelling of calendar ageing and cyclic ageing is discussed,revealing their coupled effects and corresponding RUL prediction methods.Finally,the technical bottlenecks faced by the current RUL prediction of lithium batteries are identified,potential solutions are proposed,and the future development trends are outlined.
文摘BACKGROUND Due to the increasing rate of thyroid nodules diagnosis,and the desire to avoid the unsightly cervical scar,remote thyroidectomies were invented and are increasingly performed.Transoral endoscopic thyroidectomy vestibular approach and trans-areolar approaches(TAA)are the two most commonly used remote approaches.No previous meta-analysis has compared postoperative infections and swallowing difficulties among the two procedures.AIM To compared the same among patients undergoing lobectomy for unilateral thyroid carcinoma/benign thyroid nodule.METHODS We searched PubMed MEDLINE,Google Scholar,and Cochrane Library from the date of the first published article up to August 2025.The term used were transoral thyroidectomy vestibular approach,trans areolar thyroidectomy,scarless thyroidectomy,remote thyroidectomy,infections,postoperative,inflammation,dysphagia,and swallowing difficulties.We identified 130 studies,of them,30 full texts were screened and only six studies were included in the final meta-analysis.RESULTS Postoperative infections were not different between the two approaches,odd ratio=1.33,95%confidence interval:0.50-3.53,theχ2 was 1.92 and the P-value for overall effect of 0.57.Similarly,transient swallowing difficulty was not different between the two forms of surgery,with odd ratio=0.91,95%confidence interval:0.35-2.40;theχ2 was 1.32,and the P-value for overall effect of 0.85.CONCLUSION No significant statistical differences were evident between trans-oral endoscopic Mirghani H.Infections and swallowing difficulty in scarless thyroidectomy WJCC https://www.wjgnet.com 2 January 6,2026 Volume 14 Issue 1 thyroidectomy vestibular approach and trans-areolar approach regarding postoperative infection and transient swallowing difficulties.Further longer randomized trials are needed.
基金supported in part by the National Natural Science Foundation of China under Grants 62073124 and U1804150.
文摘This paper explores the algebraic essence of universal logic functions(ULFs)from an algebraic perspective.Under the framework of semi-tensor product of matrices,the“sequential nature”of ULFs is revealed.Utilizing the nature,a technique called universal transformation method is proposed,by which any ULF can be transformed into an equivalent expression with desired features that facilitate achieving specific objectives,such as modeling,analyzing and synthesizing universal logical systems.Furthermore,several useful logical operators are constructed in a mixed-dimensional situation,including power-raising operator,power-descending operator,erasure operator,and appending operator.Finally,these results are applied to model and analyze finite state machines and their networks,which demonstrate the practical value of the method and operators.
基金Project supported by the Basic Science Research Program through the National Research Foundation(NRF)of Korea funded by the Ministry of Science and ICT(No.RS-2024-00337001)。
文摘Physics-informed neural networks(PINNs)have been shown as powerful tools for solving partial differential equations(PDEs)by embedding physical laws into the network training.Despite their remarkable results,complicated problems such as irregular boundary conditions(BCs)and discontinuous or high-frequency behaviors remain persistent challenges for PINNs.For these reasons,we propose a novel two-phase framework,where a neural network is first trained to represent shape functions that can capture the irregularity of BCs in the first phase,and then these neural network-based shape functions are used to construct boundary shape functions(BSFs)that exactly satisfy both essential and natural BCs in PINNs in the second phase.This scheme is integrated into both the strong-form and energy PINN approaches,thereby improving the quality of solution prediction in the cases of irregular BCs.In addition,this study examines the benefits and limitations of these approaches in handling discontinuous and high-frequency problems.Overall,our method offers a unified and flexible solution framework that addresses key limitations of existing PINN methods with higher accuracy and stability for general PDE problems in solid mechanics.
基金supported by Progetto Trapezio,Compagnia di San Paolo(67935-2021.2174),to LBFondazione CRT(Cassa di Risparmio di Torino,RF=2022.0618),to LBPRIN2022(grant 2022LB4X3N),to LB。
文摘The capacity of the central nervous system for structural plasticity and regeneration is commonly believed to show a decreasing progression from“small and simple”brains to the larger,more complex brains of mammals.However,recent findings revealed that some forms of neural plasticity can show a reverse trend.Although plasticity is a well-preserved,transversal feature across the animal world,a variety of cell populations and mechanisms seem to have evolved to enable structural modifications to take place in widely different brains,likely as adaptations to selective pressures.Increasing evidence now indicates that a trade-off has occurred between regenerative(mostly stem cell–driven)plasticity and developmental(mostly juvenile)remodeling,with the latter primarily aimed not at brain repair but rather at“sculpting”the neural circuits based on experience.In particular,an evolutionary trade-off has occurred between neurogenic processes intended to support the possibility of recruiting new neurons throughout life and the different ways of obtaining new neurons,and between the different brain locations in which plasticity occurs.This review first briefly surveys the different types of plasticity and the complexity of their possible outcomes and then focuses on recent findings showing that the mammalian brain has a stem cell–independent integration of new neurons into pre-existing(mature)neural circuits.This process is still largely unknown but involves neuronal cells that have been blocked in arrested maturation since their embryonic origin(also termed“immature”or“dormant”neurons).These cells can then restart maturation throughout the animal's lifespan to become functional neurons in brain regions,such as the cerebral cortex and amygdala,that are relevant to high-order cognition and emotions.Unlike stem cell–driven postnatal/adult neurogenesis,which significantly decreases from small-brained,short-living species to large-brained ones,immature neurons are particularly abundant in large-brained,long-living mammals,including humans.The immature neural cell populations hosted in these complex brains are an interesting example of an“enlarged road”in the phylogenetic trend of plastic potential decreases commonly observed in the animal world.The topic of dormant neurons that covary with brain size and gyrencephaly represents a prospective turning point in the field of neuroplasticity,with important translational outcomes.These cells can represent a reservoir of undifferentiated neurons,potentially granting plasticity within the high-order circuits subserving the most sophisticated cognitive skills that are important in the growing brains of young,healthy individuals and are frequently affected by debilitating neurodevelopmental and degenerative disorders.
文摘Objective: To analyze the impact of motivational nursing under the solution-focused approach on health behaviors in surgical care for bladder cancer patients. Methods: A sample of 72 bladder cancer patients who underwent surgical treatment from September 2024 to September 2025 was randomly divided into groups using a random number table. Group A received motivational nursing under the solution-focused approach, while Group B received conventional nursing. Health behavior scores and complication indicators were compared between the two groups. Results: Group A had higher scores on the Health-Promoting Lifestyle Profile II (HPLP-Ⅱ) than Group B, with p < 0.05. The postoperative complication rate in Group A was lower than that in Group B, with p < 0.05. Conclusion: For bladder cancer patients undergoing surgery, receiving motivational nursing under the solution-focused approach can improve health behaviors, alleviate negative emotions, and is highly feasible and effective.
基金supported by the National Natural Science Foundation of China under Grants No.12375030。
文摘Signal transduction in a cell is mostly mediated with biochemical reactions which are noisy and often modeled with chemical master equations or Langevin type of dynamics.Thus stochastic simulation constitutes a major part of computation in cell signaling.Nevertheless,the presence of a wide span of time scales or molecular numbers in various pathways may lead to trouble in computation efficiency or accuracy.To avoid this problem,the commonly employed variational method evolves the whole probability distribution and reduces the stochastic equations to deterministic ones of only a few parameters.However,the design of the left variational basis is essential for its successful application,especially to large networks.In this paper,we extend the conventional polynomial basis to the Fourier and further the Gaussian basis,much facilitating description of multi-peaked or localized non-Gaussian distributions and at the same time avoiding numerical instability and computational complexity frequently encountered with conventional basis.The extension here is demonstrated in several typical biochemical signaling networks and achieves similar accuracy as the benchmark Gillespie algorithm,but with much less running time,which seems to open new opportunities in the variational approach to efficient analysis of noisy dynamics.
基金the financial support by the National Natural Science Foundation of China(No.U2202255)the Hunan Provincial Natural Science Foundation of China(No.2024JJ2076)the Key Research and Development Program of Ningbo,China(No.2023Z092)。
文摘A Cu-1.9Ni-1.9Co-0.9Si(mass fraction,%)alloy with high strength and electrical conductivity was designed by cluster formula approach.The microstructure evolution of the alloy during thermomechanical treatment was systematically investigated.The strengthening mechanism and electrical conductivity of the alloy were discussed in detail.The optimal thermomechanical treatment process was as follows:solid solution→80%cold rolling→(450℃,4 h)aging→50%cold rolling→(400℃,4 h)aging.The designed alloy achieved excellent comprehensive properties with a microhardness of HV 260,a yield strength of 843 MPa,a tensile strength of 884 MPa,and an electrical conductivity of 42.6%(IACS).Compared to direct aging treatment,the designed alloy subjected to multi-stage thermomechanical treatment had refined grains,high density of dislocations,and accelerated of precipitation of(Ni,Co)_(2)Si precipitates.High strength was mainly attributed to the combined effect of dislocation strengthening,work hardening and sub-grain strengthening,while good electrical conductivity was maintained through the precipitation of the large number of nanoparticles.
基金supported by the National Natural Science Foundation of China(62403345)the Guangdong Provincial Key Laboratory of Ultra High Definition Immersive Media Technology(2024B1212010006)the Shanxi Provincial Department of Science and Technology Basic Research Project(202403021212174,202403021221074).
文摘Audio-visual speaker tracking aims to determine the locations of multiple speakers in the scene by leveraging signals captured from multisensor platforms.Multimodal fusion methods can improve both the accuracy and robustness of speaker tracking.However,in complex multispeaker tracking scenarios,critical challenges such as cross-modal feature discrepancy,weak sound source localisation ambiguity and frequent identity switch errors remain unresolved,which severely hinder the modelling of speaker identity consistency and consequently lead to degraded tracking accuracy and unstable tracking trajectories.To this end,this paper proposes a multimodal multispeaker tracking network using audio-visual contrastive learning(AVCLNet).By integrating heterogeneous modal representations into a unified space through audio-visual contrastive learning,which facilitates cross-modal feature alignment,mitigates cross-modal feature bias and enhances identity-consistent representations.In the audio-visual measurement stage,we design a vision-guided weak sound source weighted enhancement method,which leverages visual cues to establish cross-modal mappings and employs a spatiotemporal dynamic weighted mechanism to improve the detectability of weak sound sources.Furthermore,in the data association phase,a dual geometric constraint strategy is introduced by combining the 2D and 3D spatial geometric information,reducing frequent identity switch errors.Experiments on the AV16.3 and CAV3D datasets show that AVCLNet outperforms state-of-the-art methods,demonstrating superior robustness in multispeaker scenarios.
基金supported by National Natural Science Foundation of China(No.51671075 and 51971086)Natural Science Foundation of Heilongjiang Province of China(No.LH2022E081).
文摘The exploration of high-performance materials presents a fundamental challenge in materials science,particularly in predicting properties for materials beyond the known range of target property values(extrapolation).This study formally investigated the interpolation-extrapolation trade-off phenomenon in the prediction capabilities of machine learning(ML)models.A new ML scheme was proposed,featuring a newly developed ML model and forward cross-validation-based hyperparameter optimization,which demonstrated superior extrapolation prediction across multiple materials datasets.Based on this ML scheme,multi-objective optimization was performed to systematically identify lightweight Mg-Zn-Al alloys with both high bulk modulus and high Debye temperature.Subsequently,the designed alloys were validated through density functional theory calculations.Furthermore,a three-category classification strategy was summarized through the dual-driven approach combining domain knowledge and data,emphasizing their synergistic potential for materials discovery.The practical framework developed in this study provides a novel research perspective for exploring high-performance materials.
基金supported by the National Natural Science Foundation of China(Nos.12075121 and 12375122)the Natural Science Foundation of Jiangsu Province(No.BK20190067)the Fundamental Research Funds for the Central Universities(Nos.30922010312 and B230201022)。
文摘The neutron-rich nucleus^(22)C,located at the neutron drip line,exhibits intriguing structural properties,such as its Borromean nature and potential two-neutron halo configuration.Despite experimental advancements,uncertainties persist in the two-neutron separation energy S_(2n)and the radius of matter for this attractive nucleus^(22)C.In this study,we employed the three-body Faddeev approach to investigate the ground-state properties of ^(22)C,constrained by the recently deduced matter radius.By optimizing the neutron-core and three-body interactions to reproduce the experimental radius,the two-neutron separation energy S_(2n) was redetermined,revealing a weakly bound system dominated by the s-wave configuration.Additionally,an excited state exhibiting an Efimov-like pattern was identified by analyzing the specific density distributions and relative distances in the three-body system,highlighting the geometric similarity between the ground and excited states.
基金supported by the National Natural Science Foundation of China(52477222)the Key Research and Development Program of Shaanxi Province(2024GX-YBXM-442)the Xinjiang Uygur Autonomous Region Key R&D Program under Grant(2022B01019-2)。
文摘With the rapid development of electric vehicles and grid-scale renewable integration,the demand for lithium-ion batteries(LIBs)has significantly increased with high expectations on enhanced energy density,cycle stability,and failure resilience.Electrochemical models(EMs),serving as pivotal mechanismdriven analytical frameworks in battery research and applications,demonstrate unprecedented quantitative fidelity in characterizing intricate multi-physics dynamics for the next-generation battery management systems(BMS).The breakthrough innovations in artificial intelligence(AI)driven methods have revolutionized the dynamic modeling of LIBs.However,the deployment of AI-augmented EMs in BMS faces significant identifiability challenges due to strong parameter coupling.In addition,research on model simplification,parameter determination,and dynamic parameter identification remains largely fragmented.There is a lack of a comprehensive review to pave the way for the cross-domain innovations in BMS.To fill this gap,this paper presents a systematic review of the EMs for LIBs and examines the advancements in parameter determination techniques from both experimental measurement and numerical simulation perspectives.Besides,a comprehensive assessment of the progress in parameter identification from the standpoint of dynamic recognition is presented,encompassing both modelbased approaches and intelligent methods.Additionally,from the BMS standpoint,the strengths and limitations of existing approaches are evaluated.Finally,a coordinated framework for multi-stage identification needs to be established in the future.The potential of digital twins(DT),deep reinforcement learning(DRL),and large language models(LLMs)in enhancing EMs also warrants further exploration.The purpose of this work is to provide insights and guidance for the future development of EMs in LIB applications.
基金supported by Key R&D Program(Soft Science Project)of Shandong Province,China(No.2020CXGC011502)National Natural Science Foundation of China(Nos.62273043 and 62103049).
文摘This paper addresses the three-dimensional(3-D)approach angle constrained cooperative guidance problem for speed-varying missiles against maneuvering targets.First,the guidance problem is formulated in a relative reference frame and a virtual control input is selected.Then,the cooperative guidance law is designed on the basis of a prediction-correction framework.The time-to-go under the baseline command is estimated by an efficient prediction method with a realistic aerodynamic model and a biased command is developed by utilizing the time-to-go predictions for synchronizing different missiles'impact times.The design of the biased command is decoupled into the individual design of its direction and magnitude.It is proved that the designed cooperative guidance law can make the time-to-go consensus error converge to zero before interception.Finally,the designed guidance law is validated through a series of numerical simulations.
基金supported by the Key Laboratory of Clinical Evaluation Technology for Human Experience with Chinese Medicine,Science and Technology Innovation Project of Guangdong Provincial Medical Products Administration(2022ZDB06)the Jointly Funded Project by Guangzhou Science and Technology Bureau,Research Institutes and Enterprises(2024A03j0355)+1 种基金the State Key Laboratory of Traditional Chinese Medicine Syndrome"Unveiling the List and Taking on Leadership"Project(SKLKY2025C0013)the National Key Research and Development Program of China(2025YFC3507902).
文摘The development of pattern-based traditional Chinese medicine(TCM)compound preparations constitutes a core domain that represents the principle of pattern differentiation-based treatment,a hallmark of TCM.However,the field has long been constrained by scientific and regulatory challenges in animal modeling,efficacy evaluation,and clinical positioning.This article proposes a new research and development(R&D)paradigm strategically based on human use experience(HUE)and centered on the patient as the key to overcoming these bottlenecks and achieving high-quality progress.We systematically dissect the traditional problems in this field and demonstrate the pivotal role of high-quality HUE in enabling precise clinical positioning and optimizing R&D pathways(e.g.,applying for exemptions from non-clinical studies).HUE guides the implementation of the“pattern-symptom integration”model.Furthermore,we detail the implementation of the patient-centered concept throughout the process of clinical trial design,collection of patients’experience data,clinical outcome assessment,and benefit-risk assessment.The integrative application of artificial intelligence in the R&D of pattern-based TCM drugs is also specifically explored.By synthesizing the“TCM theory,HUE,and clinical trials”evidence system,this article aims to provide a systematic strategic framework for establishing an R&D pathway that adheres to the intrinsic principles of TCM while simultaneously meeting modern scientific standards.
基金supported by the Iran National Science Foundation(INSF)the University of Birjand under grant number 4034771.
文摘Groundwater modeling remains challenging due to heterogeneity and complexity of aquifer systems,necessitating endeavors to quantify Groundwater Levels(GWL)dynamics to inform policymakers and hydrogeologists.This study introduces a novel Fuzzy Nonlinear Additive Regression(FNAR)model to predict monthly GWL in an unconfined aquifer in eastern Iran,using a 19-year(1998–2017)dataset from 11 piezometric wells.Under three distinct scenarios with progressively increasing input complexity,the study utilized readily available climate data,including Precipitation(Prc),Temperature(Tave),Relative Humidity(RH),and Evapotranspiration(ETo).The dataset was split into training(70%)and validation(30%)subsets.Results showed that among three input scenarios,Scenario 3(Sc3,incorporating all four variables)achieved the best predictive performance,with RMSE ranging from 0.305 m to 0.768 m,MAE from 0.203 m to 0.522 m,NSE from 0.661 to 0.980,and PBIAS from 0.771%to 0.981%,indicating low bias and high reliability.However,Sc2(excluding ETo)with RMSE ranging from 0.4226 m to 0.9909 m,MAE from 0.3418 m to 0.8173 m,NSE from 0.2831 to 0.9674,and PBIAS from−0.598%to 0.968%across different months offers practical advantages in data-scarce settings.The FNAR model outperforms conventional Fuzzy Least Squares Regression(FLSR)and holds promise for GWL forecasting in data-scarce regions where physical or numerical models are impractical.Future research should focus on integrating FNAR with deep learning algorithms and real-time data assimilation expanding applications across diverse hydrogeological settings.
基金supported by the National Key Research and Development Program of China(2022YFC2402400)the National Natural Science Foundation of China(82027803,62275062)+7 种基金the Guangdong Provincial Key Laboratory of Biomedical Optical Imaging Technology(2020B121201010)the Shenzhen Science and Technology Innovation Committee under Grant(JCYJ20220818101417039)the Shenzhen Key Laboratory for Molecular lmaging(ZDSY20130401165820357)the Shenzhen Medical Research Fund(D2404002)the Project of Shandong Innovation and Startup Community of High-end Medical Apparatus and Instruments(2023-SGTTXM-002 and 2024-SGTTXM-005)the Shandong Province Technology Innovation Guidance Plan(Central Leading Local Science and Technology Development Fund)(YDZX2023115)the Taishan Scholar Special Funding Project of Shandong Provinceand the Shandong Laboratory of Advanced Biomaterials and Medical Devices in Weihai(ZL202402).
文摘The photoacoustic imaging of lipid is intrinsically constrained by the feeble nature of endogenous lipid signals,posing a persistent sensitivity challenge that demands innovative solutions.Although adopting high-efficiency excitation and detection elements may improve the imaging sensitivity to a certain extent,the application of the elements is inevitably subject to various limitations in practical applications,particularly during in vivo imaging and endoscopic imaging.In this study,we propose a multi-combinatorial approach to enhance the sensitivity of lipid photoacoustic imaging.The approach involves wavelet transform processing of one-dimensional A-line signals,gradient-based denoising of two-dimensional B-scan images,and finally,threedimensional spatial weighted averaging of the data processed by the previous two steps.This method not only significantly improves the signal-to-noise ratio(SNR)in distinguished feature regions of the image by around 10 dB,but also efficiently extracts weak signals with no distinct features in the original image.After processing with this method,the images acquired under single scanning were compared with those obtained under multiple scanning.The results showed highly consistent image features,with the structural similarity index increasing from 0.2 to 0.8,confirming the accuracy and reliability of the multi-combinatorial approach.
文摘The 17 Sustainable Development Goals(SDGs)for 2030,adopted by all United Nations member states in 2015,are facing a range of challenges.Factors such as climate change,regional conflicts and economic recession are having a significant impact,particularly on global poverty governance.As a platform for dialogue,exchange and technical cooperation,the 2025 International Seminar on Global Poverty Reduction Partnerships was held in Beijing on 10 December 2025.
基金supported by the National Natural Science Foundation of China(Grant Nos.12325305,12175018,and 12135001)the National Key RD Program of China(Grant Nos.2022YFA1603200 and 2022YFA1603203).
文摘High-Mach-number plasma jets have been extensively investigated in both astrophysical and laboratory contexts.In this work,we revisit the framework of magnetohydrodynamic(MHD)theory and introduce a new analytical approach for examining plasma jets generated by intense laser-plasma interactions.Specifically,we reformulate the fundamental MHD equations to elucidate the governing factors of local plasma density evolution.Furthermore,MHD simulations of laser irradiation on planar targets demonstrate that impact pressure plays a dominant role in the propagation of high-Mach-number plasma jets.In addition,a pronounced dependence on the atomic number is identified:higher-Z materials amplify the impact pressure,suggesting that metallicity exerts a significant influence on the morphology and dynamics of astrophysical jets.
