Maintaining the integrity and longevity of structures is essential in many industries,such as aerospace,nuclear,and petroleum.To achieve the cost-effectiveness of large-scale systems in petroleum drilling,a strong emp...Maintaining the integrity and longevity of structures is essential in many industries,such as aerospace,nuclear,and petroleum.To achieve the cost-effectiveness of large-scale systems in petroleum drilling,a strong emphasis on structural durability and monitoring is required.This study focuses on the mechanical vibrations that occur in rotary drilling systems,which have a substantial impact on the structural integrity of drilling equipment.The study specifically investigates axial,torsional,and lateral vibrations,which might lead to negative consequences such as bit-bounce,chaotic whirling,and high-frequency stick-slip.These events not only hinder the efficiency of drilling but also lead to exhaustion and harm to the system’s components since they are difficult to be detected and controlled in real time.The study investigates the dynamic interactions of these vibrations,specifically in their high-frequency modes,usingfield data obtained from measurement while drilling.Thefindings have demonstrated the effect of strong coupling between the high-frequency modes of these vibrations on drilling sys-tem performance.The obtained results highlight the importance of considering the interconnected impacts of these vibrations when designing and implementing robust control systems.Therefore,integrating these compo-nents can increase the durability of drill bits and drill strings,as well as improve the ability to monitor and detect damage.Moreover,by exploiting thesefindings,the assessment of structural resilience in rotary drilling systems can be enhanced.Furthermore,the study demonstrates the capacity of structural health monitoring to improve the quality,dependability,and efficiency of rotary drilling systems in the petroleum industry.展开更多
Schizophrenia is characterized by psychotic symptoms,negative symptoms,and cognitive deficits,profoundly affecting individuals and their families.The etiology is multifactorial,involving genetic,endocrine,and immunolo...Schizophrenia is characterized by psychotic symptoms,negative symptoms,and cognitive deficits,profoundly affecting individuals and their families.The etiology is multifactorial,involving genetic,endocrine,and immunological risk factors.It is thought that schizophrenia is exclusively linked to alterations in brain structure and function,while the relationship between the brain and many organs may lack sufficient attention.Increasing evidence indicates abnormalities of the interactions between the brain and many organs in patients with schizophrenia.Inter-organ crosstalk affects the onset,course,and management of schizophrenia.Besides,the complex relationship between autonomic nervous system,endocrine system,and immune system further facilitates the development of schizophrenia.The present review summarizes the relationships between the brain and multiple organ systems in schizophrenia,providing new perspectives on the underlying pathophysiological mechanisms of schizophrenia.展开更多
Rock discontinuities control rock mechanical behaviors and significantly influence the stability of rock masses.However,existing discontinuity mapping algorithms are susceptible to noise,and the calculation results ca...Rock discontinuities control rock mechanical behaviors and significantly influence the stability of rock masses.However,existing discontinuity mapping algorithms are susceptible to noise,and the calculation results cannot be fed back to users timely.To address this issue,we proposed a human-machine interaction(HMI)method for discontinuity mapping.Users can help the algorithm identify the noise and make real-time result judgments and parameter adjustments.For this,a regular cube was selected to illustrate the workflows:(1)point cloud was acquired using remote sensing;(2)the HMI method was employed to select reference points and angle thresholds to detect group discontinuity;(3)individual discontinuities were extracted from the group discontinuity using a density-based cluster algorithm;and(4)the orientation of each discontinuity was measured based on a plane fitting algorithm.The method was applied to a well-studied highway road cut and a complex natural slope.The consistency of the computational results with field measurements demonstrates its good accuracy,and the average error in the dip direction and dip angle for both cases was less than 3.Finally,the computational time of the proposed method was compared with two other popular algorithms,and the reduction in computational time by tens of times proves its high computational efficiency.This method provides geologists and geological engineers with a new idea to map rapidly and accurately rock structures under large amounts of noises or unclear features.展开更多
Food systems are deeply affected by climate change and air pollution,while being key contributors to these environmental challenges.Understanding the complex interactions among food systems,climate change,and air poll...Food systems are deeply affected by climate change and air pollution,while being key contributors to these environmental challenges.Understanding the complex interactions among food systems,climate change,and air pollution is crucial for mitigating climate change,improving air quality,and promoting the sustainable development of food systems.However,the literature lacks a comprehensive review of these interactions,particularly in the current phase of rapid development in the field.To address this gap,this study systematically reviews recent research on the impacts of climate change and air pollution on food systems,as well as the greenhouse gas and air pollutant emissions from agri-food systems and their contribution to global climate change and air pollution.In addition,this study summarizes various strategies for mitigation and adaptation,including adjustments in agricultural practices and food supply chains.Profound changes in food systems are urgently needed to enhance adaptability and reduce emissions.This review offers a critical overview of current research on the interactions among food systems,climate change,and air pollution and highlights future research directions to support the transition to sustainable food systems.展开更多
The coupled nonlocal nonlinear Schrödinger equations with variable coefficients are researched using the nonstandard Hirota bilinear method.The two-soliton and double-hump one-soliton solutions for the equations ...The coupled nonlocal nonlinear Schrödinger equations with variable coefficients are researched using the nonstandard Hirota bilinear method.The two-soliton and double-hump one-soliton solutions for the equations are first obtained.By assigning different functions to the variable coefficients,we obtain V-shaped,Y-shaped,wave-type,exponential solitons,and so on.Next,we reveal the influence of the real and imaginary parts of the wave numbers on the double-hump structure based on the soliton solutions.Finally,by setting different wave numbers,we can change the distance and transmission direction of the solitons to analyze their dynamic behavior during collisions.This study establishes a theoretical framework for controlling the dynamics of optical fiber in nonlocal nonlinear systems.展开更多
Hydrogel-based triboelectric nanoge nerator(TENG)has a promising applied prospect in wearable electronic devices.However,its low performance,poor stability,insufficient recyclability and inferior self-healing seriousl...Hydrogel-based triboelectric nanoge nerator(TENG)has a promising applied prospect in wearable electronic devices.However,its low performance,poor stability,insufficient recyclability and inferior self-healing seriously hinder its development.Herein,we report a robust route to a liquid metal(LM)/polyvinyl alcohol(PVA)hydrogel-based TENG(LP-TENG).Owing to the intrinsically liquid feature of conductive LM within the flexible PVA hydrogel,the as-prepared LP-TENG exhibited comprehensiye advantages of adaptability,biocompatibility,outstanding electrical performance,superior stability,recyclability and diverse applications,which were unattainable by traditional systems.Concretely,the LP-TENG delivered appealing open circuit voltage of 250 V,short circuit current of 4μA and transferred charge of 120 nC with high stability,outperforming most advanced TENG systems.The LP-TENG was successfully employed for versatile applications with multifunctionality,including human motion detection,handwriting recognition,energy collection,message transmission and human-machine interaction.This work presents significant prospects for crafting advanced materials and devices in the fields of wearable electronics,flexible skin and smart robots.展开更多
As the Internet of Things advances,gesture recognition emerges as a prominent domain in human-machine interaction(HMI).However,interactive wearables based on conductive hydrogels for individuals with single-arm functi...As the Internet of Things advances,gesture recognition emerges as a prominent domain in human-machine interaction(HMI).However,interactive wearables based on conductive hydrogels for individuals with single-arm functionality or disabilities remain underexplored.Here,we devised a wearable one-handed keyboard with gesture recognition,employing machine learning algorithms and hydrogel-based mechanical sensors to boost productivity.PCG(PAM/CMC/rGO)hydrogels are composed of polyacrylamide(PAM),sodium carboxymethyl cellulose(CMC),and reduced graphene oxide(rGO),which function as a strain,pressure sensor,and electrode material.The PAM chains offer the gel’s elasticity by covalent cross-linking,while the biocompatible CMC improves the dispersion of rGO and promotes electromechanical properties.Integrating rGO sheets into the polymer matrix facilitates cross-linking and generates supple-mentary conductive pathways,thereby augmenting the gel system’s elasticity,sensitivity,and durability.Our hydrogel sensors include high sensitivity(gage factor(GF)=8.18,395.6%-551.96%)and superior pressure sensing capabilities(Sensitivity(S)=0.3116 kPa^(-1),0-9.82 kPa).Furthermore,we developed a wearable keyboard with up to 98.13%accuracy using convolutional neural networks and a custom data acquisition system.This study establishes the groundwork for creating multifunctional gel sensors for intelligent machines,wearable devices,and brain-computer interfaces.展开更多
Teleoperation is of great importance in the area of robotics,especially when people are unavailable in the robot workshop.It provides a way for people to control robots remotely using human intelligence.In this paper,...Teleoperation is of great importance in the area of robotics,especially when people are unavailable in the robot workshop.It provides a way for people to control robots remotely using human intelligence.In this paper,a robotic teleoperation system for precise robotic manipulation is established.The data glove and the 7-degrees of freedom(DOFs)force feedback controller are used for the remote control interaction.The control system and the monitor system are designed for the remote precise manipulation.The monitor system contains an image acquisition system and a human-machine interaction module,and aims to simulate and detect the robot running state.Besides,a visual object tracking algorithm is developed to estimate the states of the dynamic system from noisy observations.The established robotic teleoperation systemis applied to a series of experiments,and high-precision results are obtained,showing the effectiveness of the physical system.展开更多
This study addresses security and ethical challenges in LLM-based Multi-Agent Systems, as exemplified in a blockchain fraud detection case study. Leveraging blockchain’s secure architecture, the framework involves sp...This study addresses security and ethical challenges in LLM-based Multi-Agent Systems, as exemplified in a blockchain fraud detection case study. Leveraging blockchain’s secure architecture, the framework involves specialized LLM Agents—ContractMining, Investigative, Ethics, and PerformanceMonitor, coordinated by a ManagerAgent. Baseline LLM models achieved 30% accuracy with a threshold method and 94% accuracy with a random-forest method. The Claude 3.5-powered LLM system reached an accuracy of 92%. Ethical evaluations revealed biases, highlighting the need for fairness-focused refinements. Our approach aims to develop trustworthy and reliable networks of agents capable of functioning even in adversarial environments. To our knowledge, no existing systems employ ethical LLM agents specifically designed to detect fraud, making this a novel contribution. Future work will focus on refining ethical frameworks, scaling the system, and benchmarking it against traditional methods to establish a robust, adaptable, and ethically grounded solution for blockchain fraud detection.展开更多
The intricate interplay between neurotransmitter systems,neural circuits,and neuroendocrine pathways underpins brain function and dysfunction in neurological and psychiatric disorders.This review synthesizes contempor...The intricate interplay between neurotransmitter systems,neural circuits,and neuroendocrine pathways underpins brain function and dysfunction in neurological and psychiatric disorders.This review synthesizes contemporary advances in neuropharmacology,focusing on dopaminergic,serotonergic,glutamatergic,and GABAergic systems,and their roles in regulating motor control,cognition,emotion,and stress responses.Dopaminergic pathways,including the nigrostriatal,mesolimbic,and mesocortical circuits,are explored in the context of Parkinson’s disease,schizophrenia,and addiction,with emphasis on pharmacological agents such as L-DOPA,antipsychotics,and amphetamines.Serotonergic modulation through SSRIs and psychedelics is examined for its impact on mood and neuroplasticity,while glutamatergic and GABAergic systems are discussed in relation to synaptic plasticity,excitotoxicity,and therapeutic innovations like ketamine and benzodiazepines.The neuroendocrine system,particularly the hypothalamic-pituitary-adrenal(HPA)axis,is highlighted for its role in stress-related disorders and interactions with neurotransmitter networks.Despite progress,significant challenges persist,including translational gaps between preclinical models and human trials,species-specifi c receptor disparities,and ethical dilemmas surrounding cognitive enhancers and genetic manipulation.Emerging frontiers such as nanotechnology-enabled drug delivery,optogenetics,and gut-brain axis modulation are reviewed as transformative approaches to overcome these barriers.Personalized medicine,integrating neuroimaging biomarkers and pharmacogenomics,promises to tailor therapies to individual neural and genetic profi les,while biased agonists and closed-loop systems exemplify the shift toward circuit-specifi c interventions.Ethical considerations,including equitable access to advanced therapies and responsible innovation,are underscored as critical to ensuring societal benefi t.By harmonizing molecular precision with systems neuroscience,this review advocates for interdisciplinary strategies to advance neuropharmacology,ultimately aiming to restore dynamic neural and neuroendocrine homeostasis in health and disease.展开更多
1.Background In the chemical industry,process plants-commonly referred to as plantwide systems-typically consist of many process units(unit operations).Driven by the considerable economic efficiency offered by complex...1.Background In the chemical industry,process plants-commonly referred to as plantwide systems-typically consist of many process units(unit operations).Driven by the considerable economic efficiency offered by complex and interactive process designs,modern plantwide systems are becoming increasingly sophisticated.The operation of these processes is typically characterized by the complexity of individual units(subsystems)and the intricate interactions between geographically distributed units through networks of material and energy flows,as well as control loops[1].展开更多
This study introduces a Transformer-based multimodal fusion framework for simulating multiphase flow and heat transfer in carbon dioxide(CO_(2))–water enhanced geothermal systems(EGS).The model integrates geological ...This study introduces a Transformer-based multimodal fusion framework for simulating multiphase flow and heat transfer in carbon dioxide(CO_(2))–water enhanced geothermal systems(EGS).The model integrates geological parameters,thermal gradients,and control schedules to enable fast and accurate prediction of complex reservoir dynamics.The main contributions are:(i)development of a workflow that couples physics-based reservoir simulation with a Transformer neural network architecture,(ii)design of physics-guided loss functions to enforce conservation of mass and energy,(iii)application of the surrogate model to closed-loop optimization using a differential evolution(DE)algorithm,and(iv)incorporation of economic performance metrics,such as net present value(NPV),into decision support.The proposed framework achieves root mean square error(RMSE)of 3–5%,mean absolute error(MAE)below 4%,and coefficients of determination greater than 0.95 across multiple prediction targets,including production rates,pressure distributions,and temperature fields.When compared with recurrent neural network(RNN)baselines such as gated recurrent units(GRU)and long short-term memory networks(LSTM),as well as a physics-informed reduced-order model,the Transformer-based approach demonstrates superior accuracy and computational efficiency.Optimization experiments further show a 15–20%improvement in NPV,highlighting the framework’s potential for real-time forecasting,optimization,and decision-making in geothermal reservoir engineering.展开更多
Electromyography(EMG)has already been broadly used in human-machine interaction(HMI)applications.Determining how to decode the information inside EMG signals robustly and accurately is a key problem for which we urgen...Electromyography(EMG)has already been broadly used in human-machine interaction(HMI)applications.Determining how to decode the information inside EMG signals robustly and accurately is a key problem for which we urgently need a solution.Recently,many EMG pattern recognition tasks have been addressed using deep learning methods.In this paper,we analyze recent papers and present a literature review describing the role that deep learning plays in EMG-based HMI.An overview of typical network structures and processing schemes will be provided.Recent progress in typical tasks such as movement classification,joint angle prediction,and force/torque estimation will be introduced.New issues,including multimodal sensing,inter-subject/inter-session,and robustness toward disturbances will be discussed.We attempt to provide a comprehensive analysis of current research by discussing the advantages,challenges,and opportunities brought by deep learning.We hope that deep learning can aid in eliminating factors that hinder the development of EMG-based HMI systems.Furthermore,possible future directions will be presented to pave the way for future research.展开更多
Artificial light-harvesting systems(LHSs) have drawn increasing research interest in recent times due to the energy crisis worldwide. Concurrently, macrocycle-based host–vip interactions have played an important ro...Artificial light-harvesting systems(LHSs) have drawn increasing research interest in recent times due to the energy crisis worldwide. Concurrently, macrocycle-based host–vip interactions have played an important role in the development of supramolecular chemistry. In recent years, studies towards artificial LHSs driven by macrocycle-based host–vip interactions are gradually being disclosed. In this mini-review, we briefly introduce the burgeoning progress of artificial LHSs driven by host–vip interactions. We believe that an increasing number of reports of artificial LHSs driven by host–vip interactions will appear in the near future and will provide a viable alternative for the future production of renewable energy.展开更多
The Kandi basin is located in northeast Benin (West Africa). This study is focused on the estimation of water fluxes exchanged between the river Niger (and its tributaries) and the transboundary Iullemeden Aquifer Sys...The Kandi basin is located in northeast Benin (West Africa). This study is focused on the estimation of water fluxes exchanged between the river Niger (and its tributaries) and the transboundary Iullemeden Aquifer System. In that framework, an innovative approach based on the application of the Bayesian Mixing Model (MixSIAR) analysis on water isotopes (oxygen-18, deuterium and tritium) was performed. Moreover, to assess the relevance of the model outputs, Pearson’s correlation and Principal Component Analysis (PCA) have been done. A complex relationship between surface water and groundwater has been found. Sixty percent (60%) of groundwater samples are made of more than 70% river water and rainwater;while 31.25% of surface water samples are made of about 84% groundwater. To safeguard sustainable water resources for the well-being of the local communities, surface water and groundwater must be managed as a unique component in the Kandi basin.展开更多
The(2 + 1)-dimensional Ito equation is extended to a general form including some nonintegrable effects via introducing generalized bilinear operators. It is pointed out that the nonintegrable(2 + 1)-dimensional Ito eq...The(2 + 1)-dimensional Ito equation is extended to a general form including some nonintegrable effects via introducing generalized bilinear operators. It is pointed out that the nonintegrable(2 + 1)-dimensional Ito equation contains lump solutions and interaction solutions between lump and stripe solitons. The result shows that the lump soliton will be swallowed or arisen by a stripe soliton in a fixed time. Furthermore, by the interaction between a lump and a paired resonant stripe soliton, the lump will be transformed to an instanton or a rogue wave.展开更多
It is known that structural stiffness and strength distributions have an important role in the seismic response of buildings. The effect of using different code-specified lateral load patterns on the seismic performan...It is known that structural stiffness and strength distributions have an important role in the seismic response of buildings. The effect of using different code-specified lateral load patterns on the seismic performance of fixed-base buildings has been investigated by researchers during the past two decades. However, no investigation has yet been carried out for the case of soil-structure systems. In the present study, through intensive parametric analyses of 21,600 linear and nonlinear MDOF systems and considering five different shear strength and stiffness distribution patterns, including three code-specified patterns as well as uniform and concentric patterns subjected to a group of earthquakes recorded on alluvium and soft soils, the effect of structural characteristics distribution on the strength demand and ductility reduction factor of MDOF fixed-base and soil-structure systems are parametrically investigated. The results of this study show that depending on the level of inelasticity, soil flexibility and number of degrees-of-freedoms (DOFs), structural characteristics distribution can significantly affect the strength demand and ductility reduction factor of MDOF systems. It is also found that at high levels of inelasticity, the ductility reduction factor of low-rise MDOF soil-structure systems could be significantly less than that of fixed-base structures and the reduction is less pronounced as the number of stories increases.展开更多
Nervous system emerges from complex signaling interactions where extrinsic (neurotransmitters and trophic factors, among others) and intrinsic factors (transcription factors) interplay in the developing tissue to cont...Nervous system emerges from complex signaling interactions where extrinsic (neurotransmitters and trophic factors, among others) and intrinsic factors (transcription factors) interplay in the developing tissue to control gene activity promoting chronic changes in cell genesis, migration, differentiation and death. The retinal microenvironment is regulated by a broad variety of chemicals, including endocannabinoids and nucleotides that modulate embryonic progenitor-neuron-Müller glia signaling in very early developing or pathophysiological conditions.展开更多
Speech recognition rate will deteriorate greatly in human-machine interaction when the speaker's speech mixes with a bystander's voice. This paper proposes a time-frequency approach for Blind Source Seperation...Speech recognition rate will deteriorate greatly in human-machine interaction when the speaker's speech mixes with a bystander's voice. This paper proposes a time-frequency approach for Blind Source Seperation (BSS) for intelligent Human-Machine Interaction(HMI). Main idea of the algorithm is to simultaneously diagonalize the correlation matrix of the pre-whitened signals at different time delays for every frequency bins in time-frequency domain. The prososed method has two merits: (1) fast convergence speed; (2) high signal to interference ratio of the separated signals. Numerical evaluations are used to compare the performance of the proposed algorithm with two other deconvolution algorithms. An efficient algorithm to resolve permutation ambiguity is also proposed in this paper. The algorithm proposed saves more than 10% of computational time with properly selected parameters and achieves good performances for both simulated convolutive mixtures and real room recorded speeches.展开更多
The interface mechanical behavior of a monopile is an important component of the overall offshore wind turbine structure design.Understanding the soil-structure interaction,particularly the initial soil-structure stif...The interface mechanical behavior of a monopile is an important component of the overall offshore wind turbine structure design.Understanding the soil-structure interaction,particularly the initial soil-structure stiffness,has a significant impact on the study of natural frequency and dynamic response of the monopile.In this paper,a simplified method for estimating the interface mechanical behavior of monopiles under initial lateral loads is proposed.Depending on the principle of minimum potential energy and virtual work theory,the functions of soil reaction components at the interface of monopiles are derived;MATLAB programming has been used to simplify the functions of the initial stiffness by fitting a large number of examples;then the functions are validated against the field test data and FDM results.This method can modify the modulus of the subgrade reaction in the p-y curve method for the monopile-supported offshore wind turbine system.展开更多
文摘Maintaining the integrity and longevity of structures is essential in many industries,such as aerospace,nuclear,and petroleum.To achieve the cost-effectiveness of large-scale systems in petroleum drilling,a strong emphasis on structural durability and monitoring is required.This study focuses on the mechanical vibrations that occur in rotary drilling systems,which have a substantial impact on the structural integrity of drilling equipment.The study specifically investigates axial,torsional,and lateral vibrations,which might lead to negative consequences such as bit-bounce,chaotic whirling,and high-frequency stick-slip.These events not only hinder the efficiency of drilling but also lead to exhaustion and harm to the system’s components since they are difficult to be detected and controlled in real time.The study investigates the dynamic interactions of these vibrations,specifically in their high-frequency modes,usingfield data obtained from measurement while drilling.Thefindings have demonstrated the effect of strong coupling between the high-frequency modes of these vibrations on drilling sys-tem performance.The obtained results highlight the importance of considering the interconnected impacts of these vibrations when designing and implementing robust control systems.Therefore,integrating these compo-nents can increase the durability of drill bits and drill strings,as well as improve the ability to monitor and detect damage.Moreover,by exploiting thesefindings,the assessment of structural resilience in rotary drilling systems can be enhanced.Furthermore,the study demonstrates the capacity of structural health monitoring to improve the quality,dependability,and efficiency of rotary drilling systems in the petroleum industry.
基金Supported by Beijing Traditional Chinese Medicine Scientific and Technological Development Fund Project,No.BJZYYB-2023-66Beijing Natural Science Foundation,No.7212050the Capital’s Funds for Health Improvement and Research,No.2020-4-2126.
文摘Schizophrenia is characterized by psychotic symptoms,negative symptoms,and cognitive deficits,profoundly affecting individuals and their families.The etiology is multifactorial,involving genetic,endocrine,and immunological risk factors.It is thought that schizophrenia is exclusively linked to alterations in brain structure and function,while the relationship between the brain and many organs may lack sufficient attention.Increasing evidence indicates abnormalities of the interactions between the brain and many organs in patients with schizophrenia.Inter-organ crosstalk affects the onset,course,and management of schizophrenia.Besides,the complex relationship between autonomic nervous system,endocrine system,and immune system further facilitates the development of schizophrenia.The present review summarizes the relationships between the brain and multiple organ systems in schizophrenia,providing new perspectives on the underlying pathophysiological mechanisms of schizophrenia.
基金supported by the National Key R&D Program of China(No.2023YFC3081200)the National Natural Science Foundation of China(No.42077264)the Scientific Research Project of PowerChina Huadong Engineering Corporation Limited(HDEC-2022-0301).
文摘Rock discontinuities control rock mechanical behaviors and significantly influence the stability of rock masses.However,existing discontinuity mapping algorithms are susceptible to noise,and the calculation results cannot be fed back to users timely.To address this issue,we proposed a human-machine interaction(HMI)method for discontinuity mapping.Users can help the algorithm identify the noise and make real-time result judgments and parameter adjustments.For this,a regular cube was selected to illustrate the workflows:(1)point cloud was acquired using remote sensing;(2)the HMI method was employed to select reference points and angle thresholds to detect group discontinuity;(3)individual discontinuities were extracted from the group discontinuity using a density-based cluster algorithm;and(4)the orientation of each discontinuity was measured based on a plane fitting algorithm.The method was applied to a well-studied highway road cut and a complex natural slope.The consistency of the computational results with field measurements demonstrates its good accuracy,and the average error in the dip direction and dip angle for both cases was less than 3.Finally,the computational time of the proposed method was compared with two other popular algorithms,and the reduction in computational time by tens of times proves its high computational efficiency.This method provides geologists and geological engineers with a new idea to map rapidly and accurately rock structures under large amounts of noises or unclear features.
基金supported by the National Natural Science Foundation of China(42277087,42130708,42471021,42277482,and 42361144876)the Natural Science Foundation of Guangdong Province(2024A1515012550)+3 种基金the Hainan Institute of National Park grant(KY-23ZK01)the Tsinghua Shenzhen International Graduate School Cross-disciplinary Research and Innovation Fund Research Plan(JC2022011)the Shenzhen Science and Technology Program(JCYJ20240813112106009 and ZDSYS20220606100806014)the Scientific Research Start-up Funds(QD2021030C)from Tsinghua Shenzhen International Graduate School。
文摘Food systems are deeply affected by climate change and air pollution,while being key contributors to these environmental challenges.Understanding the complex interactions among food systems,climate change,and air pollution is crucial for mitigating climate change,improving air quality,and promoting the sustainable development of food systems.However,the literature lacks a comprehensive review of these interactions,particularly in the current phase of rapid development in the field.To address this gap,this study systematically reviews recent research on the impacts of climate change and air pollution on food systems,as well as the greenhouse gas and air pollutant emissions from agri-food systems and their contribution to global climate change and air pollution.In addition,this study summarizes various strategies for mitigation and adaptation,including adjustments in agricultural practices and food supply chains.Profound changes in food systems are urgently needed to enhance adaptability and reduce emissions.This review offers a critical overview of current research on the interactions among food systems,climate change,and air pollution and highlights future research directions to support the transition to sustainable food systems.
基金supported by the National Key R&D Program of China(Grant No.2022YFA1604200)the National Natural Science Foundation of China(Grant No.12261131495)Institute of Systems Science,Beijing Wuzi University(Grant No.BWUISS21).
文摘The coupled nonlocal nonlinear Schrödinger equations with variable coefficients are researched using the nonstandard Hirota bilinear method.The two-soliton and double-hump one-soliton solutions for the equations are first obtained.By assigning different functions to the variable coefficients,we obtain V-shaped,Y-shaped,wave-type,exponential solitons,and so on.Next,we reveal the influence of the real and imaginary parts of the wave numbers on the double-hump structure based on the soliton solutions.Finally,by setting different wave numbers,we can change the distance and transmission direction of the solitons to analyze their dynamic behavior during collisions.This study establishes a theoretical framework for controlling the dynamics of optical fiber in nonlocal nonlinear systems.
基金financially supported by the Natural Science Foundation of China(Nos.22109120,62104170 and 82202757)Zhejiang Provincial Natural Science Foundation of China(Nos.LQ21B030002 and LY23F040001)。
文摘Hydrogel-based triboelectric nanoge nerator(TENG)has a promising applied prospect in wearable electronic devices.However,its low performance,poor stability,insufficient recyclability and inferior self-healing seriously hinder its development.Herein,we report a robust route to a liquid metal(LM)/polyvinyl alcohol(PVA)hydrogel-based TENG(LP-TENG).Owing to the intrinsically liquid feature of conductive LM within the flexible PVA hydrogel,the as-prepared LP-TENG exhibited comprehensiye advantages of adaptability,biocompatibility,outstanding electrical performance,superior stability,recyclability and diverse applications,which were unattainable by traditional systems.Concretely,the LP-TENG delivered appealing open circuit voltage of 250 V,short circuit current of 4μA and transferred charge of 120 nC with high stability,outperforming most advanced TENG systems.The LP-TENG was successfully employed for versatile applications with multifunctionality,including human motion detection,handwriting recognition,energy collection,message transmission and human-machine interaction.This work presents significant prospects for crafting advanced materials and devices in the fields of wearable electronics,flexible skin and smart robots.
基金supported by the China Postdoctoral Science Foundation(No.2022BG011)the Fundamental Research Funds for Central Universities(No.2020CDJ-LHZZ-077)+1 种基金the Natural Science Foundation of Chongqing,China(No.c stc2020jcyj-msxmX0397)the Fundamental Research Funds for Central Universities(No.00007717).
文摘As the Internet of Things advances,gesture recognition emerges as a prominent domain in human-machine interaction(HMI).However,interactive wearables based on conductive hydrogels for individuals with single-arm functionality or disabilities remain underexplored.Here,we devised a wearable one-handed keyboard with gesture recognition,employing machine learning algorithms and hydrogel-based mechanical sensors to boost productivity.PCG(PAM/CMC/rGO)hydrogels are composed of polyacrylamide(PAM),sodium carboxymethyl cellulose(CMC),and reduced graphene oxide(rGO),which function as a strain,pressure sensor,and electrode material.The PAM chains offer the gel’s elasticity by covalent cross-linking,while the biocompatible CMC improves the dispersion of rGO and promotes electromechanical properties.Integrating rGO sheets into the polymer matrix facilitates cross-linking and generates supple-mentary conductive pathways,thereby augmenting the gel system’s elasticity,sensitivity,and durability.Our hydrogel sensors include high sensitivity(gage factor(GF)=8.18,395.6%-551.96%)and superior pressure sensing capabilities(Sensitivity(S)=0.3116 kPa^(-1),0-9.82 kPa).Furthermore,we developed a wearable keyboard with up to 98.13%accuracy using convolutional neural networks and a custom data acquisition system.This study establishes the groundwork for creating multifunctional gel sensors for intelligent machines,wearable devices,and brain-computer interfaces.
基金NSFC-Shenzhen Robotics Research Center Project(No.U2013207)the Beijing Science and Technology Plan Project(No.Z191100008019008)。
文摘Teleoperation is of great importance in the area of robotics,especially when people are unavailable in the robot workshop.It provides a way for people to control robots remotely using human intelligence.In this paper,a robotic teleoperation system for precise robotic manipulation is established.The data glove and the 7-degrees of freedom(DOFs)force feedback controller are used for the remote control interaction.The control system and the monitor system are designed for the remote precise manipulation.The monitor system contains an image acquisition system and a human-machine interaction module,and aims to simulate and detect the robot running state.Besides,a visual object tracking algorithm is developed to estimate the states of the dynamic system from noisy observations.The established robotic teleoperation systemis applied to a series of experiments,and high-precision results are obtained,showing the effectiveness of the physical system.
文摘This study addresses security and ethical challenges in LLM-based Multi-Agent Systems, as exemplified in a blockchain fraud detection case study. Leveraging blockchain’s secure architecture, the framework involves specialized LLM Agents—ContractMining, Investigative, Ethics, and PerformanceMonitor, coordinated by a ManagerAgent. Baseline LLM models achieved 30% accuracy with a threshold method and 94% accuracy with a random-forest method. The Claude 3.5-powered LLM system reached an accuracy of 92%. Ethical evaluations revealed biases, highlighting the need for fairness-focused refinements. Our approach aims to develop trustworthy and reliable networks of agents capable of functioning even in adversarial environments. To our knowledge, no existing systems employ ethical LLM agents specifically designed to detect fraud, making this a novel contribution. Future work will focus on refining ethical frameworks, scaling the system, and benchmarking it against traditional methods to establish a robust, adaptable, and ethically grounded solution for blockchain fraud detection.
文摘The intricate interplay between neurotransmitter systems,neural circuits,and neuroendocrine pathways underpins brain function and dysfunction in neurological and psychiatric disorders.This review synthesizes contemporary advances in neuropharmacology,focusing on dopaminergic,serotonergic,glutamatergic,and GABAergic systems,and their roles in regulating motor control,cognition,emotion,and stress responses.Dopaminergic pathways,including the nigrostriatal,mesolimbic,and mesocortical circuits,are explored in the context of Parkinson’s disease,schizophrenia,and addiction,with emphasis on pharmacological agents such as L-DOPA,antipsychotics,and amphetamines.Serotonergic modulation through SSRIs and psychedelics is examined for its impact on mood and neuroplasticity,while glutamatergic and GABAergic systems are discussed in relation to synaptic plasticity,excitotoxicity,and therapeutic innovations like ketamine and benzodiazepines.The neuroendocrine system,particularly the hypothalamic-pituitary-adrenal(HPA)axis,is highlighted for its role in stress-related disorders and interactions with neurotransmitter networks.Despite progress,significant challenges persist,including translational gaps between preclinical models and human trials,species-specifi c receptor disparities,and ethical dilemmas surrounding cognitive enhancers and genetic manipulation.Emerging frontiers such as nanotechnology-enabled drug delivery,optogenetics,and gut-brain axis modulation are reviewed as transformative approaches to overcome these barriers.Personalized medicine,integrating neuroimaging biomarkers and pharmacogenomics,promises to tailor therapies to individual neural and genetic profi les,while biased agonists and closed-loop systems exemplify the shift toward circuit-specifi c interventions.Ethical considerations,including equitable access to advanced therapies and responsible innovation,are underscored as critical to ensuring societal benefi t.By harmonizing molecular precision with systems neuroscience,this review advocates for interdisciplinary strategies to advance neuropharmacology,ultimately aiming to restore dynamic neural and neuroendocrine homeostasis in health and disease.
基金the National Natural Science Foundation of China(NSFC)(62103283)the Australia Research Council’s Discovery Pro-jects Scheme(DP220100355).
文摘1.Background In the chemical industry,process plants-commonly referred to as plantwide systems-typically consist of many process units(unit operations).Driven by the considerable economic efficiency offered by complex and interactive process designs,modern plantwide systems are becoming increasingly sophisticated.The operation of these processes is typically characterized by the complexity of individual units(subsystems)and the intricate interactions between geographically distributed units through networks of material and energy flows,as well as control loops[1].
文摘This study introduces a Transformer-based multimodal fusion framework for simulating multiphase flow and heat transfer in carbon dioxide(CO_(2))–water enhanced geothermal systems(EGS).The model integrates geological parameters,thermal gradients,and control schedules to enable fast and accurate prediction of complex reservoir dynamics.The main contributions are:(i)development of a workflow that couples physics-based reservoir simulation with a Transformer neural network architecture,(ii)design of physics-guided loss functions to enforce conservation of mass and energy,(iii)application of the surrogate model to closed-loop optimization using a differential evolution(DE)algorithm,and(iv)incorporation of economic performance metrics,such as net present value(NPV),into decision support.The proposed framework achieves root mean square error(RMSE)of 3–5%,mean absolute error(MAE)below 4%,and coefficients of determination greater than 0.95 across multiple prediction targets,including production rates,pressure distributions,and temperature fields.When compared with recurrent neural network(RNN)baselines such as gated recurrent units(GRU)and long short-term memory networks(LSTM),as well as a physics-informed reduced-order model,the Transformer-based approach demonstrates superior accuracy and computational efficiency.Optimization experiments further show a 15–20%improvement in NPV,highlighting the framework’s potential for real-time forecasting,optimization,and decision-making in geothermal reservoir engineering.
基金supported in part by the National Natural Science Foundation of China(U181321461773369+2 种基金61903360)the Selfplanned Project of the State Key Laboratory of Robotics(2020-Z12)China Postdoctoral Science Foundation funded project(2019M661155)。
文摘Electromyography(EMG)has already been broadly used in human-machine interaction(HMI)applications.Determining how to decode the information inside EMG signals robustly and accurately is a key problem for which we urgently need a solution.Recently,many EMG pattern recognition tasks have been addressed using deep learning methods.In this paper,we analyze recent papers and present a literature review describing the role that deep learning plays in EMG-based HMI.An overview of typical network structures and processing schemes will be provided.Recent progress in typical tasks such as movement classification,joint angle prediction,and force/torque estimation will be introduced.New issues,including multimodal sensing,inter-subject/inter-session,and robustness toward disturbances will be discussed.We attempt to provide a comprehensive analysis of current research by discussing the advantages,challenges,and opportunities brought by deep learning.We hope that deep learning can aid in eliminating factors that hinder the development of EMG-based HMI systems.Furthermore,possible future directions will be presented to pave the way for future research.
基金financial support of the National Natural Science Foundation of China (No. 21702020)
文摘Artificial light-harvesting systems(LHSs) have drawn increasing research interest in recent times due to the energy crisis worldwide. Concurrently, macrocycle-based host–vip interactions have played an important role in the development of supramolecular chemistry. In recent years, studies towards artificial LHSs driven by macrocycle-based host–vip interactions are gradually being disclosed. In this mini-review, we briefly introduce the burgeoning progress of artificial LHSs driven by host–vip interactions. We believe that an increasing number of reports of artificial LHSs driven by host–vip interactions will appear in the near future and will provide a viable alternative for the future production of renewable energy.
文摘The Kandi basin is located in northeast Benin (West Africa). This study is focused on the estimation of water fluxes exchanged between the river Niger (and its tributaries) and the transboundary Iullemeden Aquifer System. In that framework, an innovative approach based on the application of the Bayesian Mixing Model (MixSIAR) analysis on water isotopes (oxygen-18, deuterium and tritium) was performed. Moreover, to assess the relevance of the model outputs, Pearson’s correlation and Principal Component Analysis (PCA) have been done. A complex relationship between surface water and groundwater has been found. Sixty percent (60%) of groundwater samples are made of more than 70% river water and rainwater;while 31.25% of surface water samples are made of about 84% groundwater. To safeguard sustainable water resources for the well-being of the local communities, surface water and groundwater must be managed as a unique component in the Kandi basin.
基金Supported by the National Natural Science Foundation of China under Grant No.1143505sponsored by K.C.Wong Magna Fund in Ningbo University
文摘The(2 + 1)-dimensional Ito equation is extended to a general form including some nonintegrable effects via introducing generalized bilinear operators. It is pointed out that the nonintegrable(2 + 1)-dimensional Ito equation contains lump solutions and interaction solutions between lump and stripe solitons. The result shows that the lump soliton will be swallowed or arisen by a stripe soliton in a fixed time. Furthermore, by the interaction between a lump and a paired resonant stripe soliton, the lump will be transformed to an instanton or a rogue wave.
文摘It is known that structural stiffness and strength distributions have an important role in the seismic response of buildings. The effect of using different code-specified lateral load patterns on the seismic performance of fixed-base buildings has been investigated by researchers during the past two decades. However, no investigation has yet been carried out for the case of soil-structure systems. In the present study, through intensive parametric analyses of 21,600 linear and nonlinear MDOF systems and considering five different shear strength and stiffness distribution patterns, including three code-specified patterns as well as uniform and concentric patterns subjected to a group of earthquakes recorded on alluvium and soft soils, the effect of structural characteristics distribution on the strength demand and ductility reduction factor of MDOF fixed-base and soil-structure systems are parametrically investigated. The results of this study show that depending on the level of inelasticity, soil flexibility and number of degrees-of-freedoms (DOFs), structural characteristics distribution can significantly affect the strength demand and ductility reduction factor of MDOF systems. It is also found that at high levels of inelasticity, the ductility reduction factor of low-rise MDOF soil-structure systems could be significantly less than that of fixed-base structures and the reduction is less pronounced as the number of stories increases.
基金supported by Coordenaqao de Aperfeigoamento dePessoal de Nivel Superior (CAPES),No.oo1 and PROCAD-2013(both to RAM)Conselho Nacional de Desenvolvimento Cientificoe Tecnologico (CNPq),No.303018/2016-0 (to ALMV)+1 种基金FundacaoCarlos Chagas Filho de Amparo a Pesquisa do Estado do Rio deJaneiro (FAPERJ),No.2016/02 (to GRF)Instituto Nacional de Cienciae Tecnologia de Neurociencia Translacional (INNT/INCT),No.465346/2014-6 (to RAMR).
文摘Nervous system emerges from complex signaling interactions where extrinsic (neurotransmitters and trophic factors, among others) and intrinsic factors (transcription factors) interplay in the developing tissue to control gene activity promoting chronic changes in cell genesis, migration, differentiation and death. The retinal microenvironment is regulated by a broad variety of chemicals, including endocannabinoids and nucleotides that modulate embryonic progenitor-neuron-Müller glia signaling in very early developing or pathophysiological conditions.
文摘Speech recognition rate will deteriorate greatly in human-machine interaction when the speaker's speech mixes with a bystander's voice. This paper proposes a time-frequency approach for Blind Source Seperation (BSS) for intelligent Human-Machine Interaction(HMI). Main idea of the algorithm is to simultaneously diagonalize the correlation matrix of the pre-whitened signals at different time delays for every frequency bins in time-frequency domain. The prososed method has two merits: (1) fast convergence speed; (2) high signal to interference ratio of the separated signals. Numerical evaluations are used to compare the performance of the proposed algorithm with two other deconvolution algorithms. An efficient algorithm to resolve permutation ambiguity is also proposed in this paper. The algorithm proposed saves more than 10% of computational time with properly selected parameters and achieves good performances for both simulated convolutive mixtures and real room recorded speeches.
基金financially supported by the National Natural Science Foundation of China(Grant Nos.52201324,52078128,and52278355)the Natural Science Foundation of the Jiangsu Higher Education Institution of China(Grant No.22KJB560015)the Postgraduate Research&Practice Innovation Program of Jiangsu Province(Grant No.SJCX21_1794)。
文摘The interface mechanical behavior of a monopile is an important component of the overall offshore wind turbine structure design.Understanding the soil-structure interaction,particularly the initial soil-structure stiffness,has a significant impact on the study of natural frequency and dynamic response of the monopile.In this paper,a simplified method for estimating the interface mechanical behavior of monopiles under initial lateral loads is proposed.Depending on the principle of minimum potential energy and virtual work theory,the functions of soil reaction components at the interface of monopiles are derived;MATLAB programming has been used to simplify the functions of the initial stiffness by fitting a large number of examples;then the functions are validated against the field test data and FDM results.This method can modify the modulus of the subgrade reaction in the p-y curve method for the monopile-supported offshore wind turbine system.
