We consider an energy operator of four-electron system in the Impurity Hubbard model with a coupling between nearest-neighbors. The spectrum of the systems in the second triplet state in a ν-dimensional lattice is in...We consider an energy operator of four-electron system in the Impurity Hubbard model with a coupling between nearest-neighbors. The spectrum of the systems in the second triplet state in a ν-dimensional lattice is investigated. For investigation the structure of essential spectra and discrete spectrum of the energy operator of four-electron systems in an impurity Hubbard model, for which the momentum representation is convenient. In addition, we used the tensor products of Hilbert spaces and tensor products of operators in Hilbert spaces and described the structure of essential spectrum and discrete spectrum of the energy operator of four-electron systems in an impurity Hubbard model for the second triplet state of the system. The investigations show that the essential spectrum of the system consists of the union of no more than sixteen segments, and the discrete spectrum of the system consists of no more than eleven eigenvalues.展开更多
Apparel exports China:The decline in exports widened from January to September(-2.4%,compared to-0.2%in January-June).Exports to the EU increased(+5.9%),though the growth rate moderated.Exports to the US saw a larger ...Apparel exports China:The decline in exports widened from January to September(-2.4%,compared to-0.2%in January-June).Exports to the EU increased(+5.9%),though the growth rate moderated.Exports to the US saw a larger contraction(January-June:-1.6%,January-September:-8.2%).While exports to ASEAN countries still fell by over 10%(-17.7%),shipments to the Philippines(+6.9%),Indonesia(+19.0%),and Cambodia(+64.9%)demonstrated stronger growth performance within the year.Regarding tariffs,on October 30,China and the US agreed to lower the rates on goods subject to additional duties(effectively reducing the average tariff rate on Chinese imports to the US from about 57%to approximately 47%,though this remains significantly higher than the 19.5%overall average rate applied to other countries).展开更多
Halide solid-state electrolytes have gained significant attention in recent years due to their high ionic conductivity,making them promising candidates for future all-solid-state batteries.Recent studies have identifi...Halide solid-state electrolytes have gained significant attention in recent years due to their high ionic conductivity,making them promising candidates for future all-solid-state batteries.Recent studies have identified numerous crystal structures with the Li_(3)MX_(6)composition,although many remain unexplored across various chemical systems.In this research,we developed a comprehensive method to examine all conceivable space groups and structures within theLi-M-X system,where M includes In,Ga,and La,and X includes F,Cl,Br,and 1.Our findings revealed two metastable structures:Li_(3)InF_(6)with P3c1 symmetry and Li_(3)InI_(6)with C2/c symmetry,exhibiting ionic conductivities of 0.55 and 2.18mS/cm at 300K,respectively.Notably,the trigonal symmetry of Li3InF6 demonstrates that high ionic conductivities are not limited to monoclinic structures but can also be achieved with trigonal symmetries.The electrochemical stability windows,mechanical properties,and reaction energies of these materials with known cathodes suggest their potential for use in all-solid-state batteries.Additionally,we predicted the stability of novel materials,including Li_(5)InCl_(9),Li_(5)InBr_(9),Li_(5)InI_(8),LiIn_(2)Cl_(9),LiIn_(2)Br_(9),and LiIn_(2)Ig_(9).展开更多
Automated classification of gas flow states in blast furnaces using top-camera imagery typically demands a large volume of labeled data,whose manual annotation is both labor-intensive and cost-prohibitive.To mitigate ...Automated classification of gas flow states in blast furnaces using top-camera imagery typically demands a large volume of labeled data,whose manual annotation is both labor-intensive and cost-prohibitive.To mitigate this challenge,we present an enhanced semi-supervised learning approach based on the Mean Teacher framework,incorporating a novel feature loss module to maximize classification performance with limited labeled samples.The model studies show that the proposed model surpasses both the baseline Mean Teacher model and fully supervised method in accuracy.Specifically,for datasets with 20%,30%,and 40%label ratios,using a single training iteration,the model yields accuracies of 78.61%,82.21%,and 85.2%,respectively,while multiple-cycle training iterations achieves 82.09%,81.97%,and 81.59%,respectively.Furthermore,scenario-specific training schemes are introduced to support diverse deployment need.These findings highlight the potential of the proposed technique in minimizing labeling requirements and advancing intelligent blast furnace diagnostics.展开更多
Surface passivation via two-dimensional(2D)perovskite has emerged as a promising strategy to enhance the performance of perovskite solar cells(PSCs)due to the effective compensation of interfacial states.However,the i...Surface passivation via two-dimensional(2D)perovskite has emerged as a promising strategy to enhance the performance of perovskite solar cells(PSCs)due to the effective compensation of interfacial states.However,the in situ grown 2D perovskite passivation layers typically comprise a mixture of multiple dimensionalities at the interface,where band alignment has only been portrayed qualitatively and empirically.Herein,the interface states for precisely phase-tailored 2D perovskite passivated PSCs are quantitatively investigated.In comparison to traditional passivation molecules,2D perovskite layers based on 4-trifluoromethyl-phenylethylammonium iodide(CF3PEAI)exhibit an increased work function,introducing desirable downward band bending to eliminate the Schottky Barrier.Furthermore,precisely phase-tailored 2D layers could modulate the interface trap density and energetics.The n=1 film delivers optimal performance with a hole extraction efficiency of 95.1%.The optimized n-i-p PSCs in the two-step method significantly improve PCE to 25.40%,along with enhanced photostability and negligible hysteresis.It highlights that tailoring in the composition and phase distribution of the 2D perovskite layer could modulate the interface states at the 2D/3D interface.展开更多
The methanol oxidation reaction(MOR)to formic acid offers a promising alternative to the anodic oxygen evolution reaction(OER)in water electrolysis.However,the development of efficient and cost-effective catalysts rem...The methanol oxidation reaction(MOR)to formic acid offers a promising alternative to the anodic oxygen evolution reaction(OER)in water electrolysis.However,the development of efficient and cost-effective catalysts remains a primary challenge.In this study,an enhancement in catalytic MOR performance is achieved through the incorporation of Mn atoms with unsaturated t_(2g)orbitals into Ni_(3)Se_(4).Comprehensive experimental analyses and theoretical calculations reveal that substituting Ni with Mn induces strong electron-withdrawing effects,effectively modulating the local coordination environment of the metal centers.The presence of Mn also elongates Ni–Se(O)bonds,which reduces eg orbital occupancy and modifies the spin state of the material.Electrochemical measurements demonstrate that electrodes based on this optimized material exhibit a high spin state and deliver excellent catalytic activity,achieving a MOR current density up to∼190 mA cm^(−2)at 1.6 V.This performance enhancement is attributed to the favorable electronic configuration and reduced reaction energy barriers associated with the high-spin state.展开更多
With the growing advancement of wireless communication technologies,WiFi-based human sensing has gained increasing attention as a non-intrusive and device-free solution.Among the available signal types,Channel State I...With the growing advancement of wireless communication technologies,WiFi-based human sensing has gained increasing attention as a non-intrusive and device-free solution.Among the available signal types,Channel State Information(CSI)offers fine-grained temporal,frequency,and spatial insights into multipath propagation,making it a crucial data source for human-centric sensing.Recently,the integration of deep learning has significantly improved the robustness and automation of feature extraction from CSI in complex environments.This paper provides a comprehensive review of deep learning-enhanced human sensing based on CSI.We first outline mainstream CSI acquisition tools and their hardware specifications,then provide a detailed discussion of preprocessing methods such as denoising,time–frequency transformation,data segmentation,and augmentation.Subsequently,we categorize deep learning approaches according to sensing tasks—namely detection,localization,and recognition—and highlight representative models across application scenarios.Finally,we examine key challenges including domain generalization,multi-user interference,and limited data availability,and we propose future research directions involving lightweight model deployment,multimodal data fusion,and semantic-level sensing.展开更多
The global population is rapidly expanding,driving an increasing demand for intelligent healthcare systems.Artificial intelligence(AI)applications in remote patient monitoring and diagnosis have achieved remarkable pr...The global population is rapidly expanding,driving an increasing demand for intelligent healthcare systems.Artificial intelligence(AI)applications in remote patient monitoring and diagnosis have achieved remarkable progress and are emerging as a major development trend.Among these applications,mouth motion tracking and mouth-state detection represent an important direction,providing valuable support for diagnosing neuromuscular disorders such as dysphagia,Bell’s palsy,and Parkinson’s disease.In this study,we focus on developing a real-time system capable of monitoring and detecting mouth state that can be efficiently deployed on edge devices.The proposed system integrates the Facial Landmark Detection technique with an optimized model combining a Bidirectional Gated Recurrent Unit(BiGRU)and Comprehensive Learning Particle Swarm Optimization(CLPSO).We conducted a comprehensive comparison and evaluation of the proposed model against several traditional models using multiple performance metrics,including accuracy,precision,recall,F1-score,cosine similarity,ROC–AUC,and the precision–recall curve.The proposed method achieved an impressive accuracy of 96.57%with an excellent precision of 98.25%on our self-collected dataset,outperforming traditional models and related works in the same field.These findings highlight the potential of the proposed approach for implementation in real-time patient monitoring systems,contributing to improved diagnostic accuracy and supporting healthcare professionals in patient treatment and care.展开更多
Accurate estimation of the State of Charge(SOC),State of Health(SOH),and Terminal Resistance(TR)is crucial for the effective operation of Battery Management Systems(BMS)in lithium-ion batteries.This study conducts a c...Accurate estimation of the State of Charge(SOC),State of Health(SOH),and Terminal Resistance(TR)is crucial for the effective operation of Battery Management Systems(BMS)in lithium-ion batteries.This study conducts a comprehensive comparative analysis of four Kalman filter variants Extended Kalman Filter(EKF),Extended Kalman-Bucy Filter(EKBF),Unscented Kalman Filter(UKF),and Unscented Kalman-Bucy Filter(UKBF)under varying battery parameter conditions.These include temperature fluctuation,self-discharge,current direction,cell capacity,process noise,and measurement noise.Our findings reveal significant variations in the performance of SOC and SOH predictions across filters,emphasizing that UKF demonstrates superior robustness to noise,while EKF performs better under accurate system dynamics.The study underscores the need for adaptive filtering strategies that can dynamically adjust to evolving battery parameters,thereby enhancing BMS reliability and extending battery lifespan.展开更多
Precisely estimating the state of health(SOH)of lithium-ion batteries is essential for battery management systems(BMS),as it plays a key role in ensuring the safe and reliable operation of battery systems.However,curr...Precisely estimating the state of health(SOH)of lithium-ion batteries is essential for battery management systems(BMS),as it plays a key role in ensuring the safe and reliable operation of battery systems.However,current SOH estimation methods often overlook the valuable temperature information that can effectively characterize battery aging during capacity degradation.Additionally,the Elman neural network,which is commonly employed for SOH estimation,exhibits several drawbacks,including slow training speed,a tendency to become trapped in local minima,and the initialization of weights and thresholds using pseudo-random numbers,leading to unstable model performance.To address these issues,this study addresses the challenge of precise and effective SOH detection by proposing a method for estimating the SOH of lithium-ion batteries based on differential thermal voltammetry(DTV)and an SSA-Elman neural network.Firstly,two health features(HFs)considering temperature factors and battery voltage are extracted fromthe differential thermal voltammetry curves and incremental capacity curves.Next,the Sparrow Search Algorithm(SSA)is employed to optimize the initial weights and thresholds of the Elman neural network,forming the SSA-Elman neural network model.To validate the performance,various neural networks,including the proposed SSA-Elman network,are tested using the Oxford battery aging dataset.The experimental results demonstrate that the method developed in this study achieves superior accuracy and robustness,with a mean absolute error(MAE)of less than 0.9%and a rootmean square error(RMSE)below 1.4%.展开更多
In both Traditional Chinese Medicine(TCM)and modern medicine,they agree that the integrity and healthy structure of the vascular endothelium are essential for normal hemodynamics.Damage to the vascular endothelium can...In both Traditional Chinese Medicine(TCM)and modern medicine,they agree that the integrity and healthy structure of the vascular endothelium are essential for normal hemodynamics.Damage to the vascular endothelium can quickly activate the extrinsic coagulation pathway by triggering the tissue factor(TF)and lead to coagulation.This damage,along with a loss of anticoagulant properties through antithrombinⅢ(ATⅢ),TF pathway inhibitors,and the protein C system,can result in a hypercoagulable state and even thrombosis.Hypercoagulability is not only a common feature of many cancers but also an important factor promoting tumor development and metastasis,which corresponds to the TCM theory of“blood stasis leading to tumors.”The pharmacological effects of heparin and aspirin have similarities with TCM's“activating blood circulation and removing blood stasis”theory in improving blood circulation,treating related diseases,and their anti-inflammatory effects.展开更多
An internal state variable(ISV)model was established according to the experimental results of hot plane strain compression(PSC)to predict the microstructure evolution during hot spinning of ZK61 alloy.The effects of t...An internal state variable(ISV)model was established according to the experimental results of hot plane strain compression(PSC)to predict the microstructure evolution during hot spinning of ZK61 alloy.The effects of the internal variables were considered in this ISV model,and the parameters were optimized by genetic algorithm.After validation,the ISV model was used to simulate the evolution of grain size(GS)and dynamic recrystallization(DRX)fraction during hot spinning via Abaqus and its subroutine Vumat.By comparing the simulated results with the experimental results,the application of the ISV model was proven to be reliable.Meanwhile,the strength of the thin-walled spun ZK61 tube increased from 303 to 334 MPa due to grain refinement by DRX and texture strengthening.Besides,some ultrafine grains(0.5μm)that played an important role in mechanical properties were formed due to the proliferation,movement,and entanglement of dislocations during the spinning process.展开更多
1.Introduction.Cold Spray(CS)is a highly advanced solid-state metal depo-sition process that was first developed in the 1980s.This innovative technique involves the high-speed(300-1200 m/s)impact deposition of micron-...1.Introduction.Cold Spray(CS)is a highly advanced solid-state metal depo-sition process that was first developed in the 1980s.This innovative technique involves the high-speed(300-1200 m/s)impact deposition of micron-sized particles(5-50μm)to fabricate coatings[1-3].CS has been extensively used in a variety of coating applications,such as aerospace,automotive,energy,medical,marine,and others,to provide protection against high temperatures,corrosion,erosion,oxidation,and chemicals[4,5].Nowadays,the technical interest in CS is twofold:(i)as a repair process for damaged components,and(ii)as a solid-state additive manufacturing process.Compared to other fusion-based additive manufacturing(AM)technologies,Cold Spray Additive Manufacturing(CSAM)is a new member of the AM family that can enable the fabrication of deposits without undergoing melting.The chemical composition has been largely preserved from the powder to the deposit due to the minimal oxidation.The significant advantages of CSAM over other additive manufacturing processes include a high production rate,unlimited deposition size,high flexibility,and suitability for repairing damaged parts.展开更多
In order to address the widespread data shortage problem in battery research,this paper proposes a generative adversarial network model that combines it with deep convolutional networks,the Wasserstein distance,and th...In order to address the widespread data shortage problem in battery research,this paper proposes a generative adversarial network model that combines it with deep convolutional networks,the Wasserstein distance,and the gradient penalty to achieve data augmentation.To lower the threshold for implementing the proposed method,transfer learning is further introduced.The W-DC-GAN-GP-TL framework is thereby formed.This framework is evaluated on 3 different publicly available datasets to judge the quality of generated data.Through visual comparisons and the examination of two visualization methods(probability density function(PDF)and principal component analysis(PCA)),it is demonstrated that the generated data is hard to distinguish from the real data.The application of generated data for training a battery state model using transfer learning is further evaluated.Specifically,Bi-GRU-based and Transformer-based methods are implemented on 2 separate datasets for estimating state of health(SOH)and state of charge(SOC),respectively.The results indicate that the proposed framework demonstrates satisfactory performance in different scenarios:for the data replacement scenario,where real data are removed and replaced with generated data,the state estimator accuracy decreases only slightly;for the data enhancement scenario,the estimator accuracy is further improved.The estimation accuracy of SOH and SOC is as low as 0.69%and 0.58%root mean square error(RMSE)after applying the proposed framework.This framework provides a reliable method for enriching battery measurement data.It is a generalized framework capable of generating a variety of time series data.展开更多
Implementing quantum wireless multi-hop network communication is essential to improve the global quantum network system. In this paper, we employ eight-level GHZ states as quantum channels to realize multi-hop quantum...Implementing quantum wireless multi-hop network communication is essential to improve the global quantum network system. In this paper, we employ eight-level GHZ states as quantum channels to realize multi-hop quantum communication, and utilize the logical relationship between the measurements of each node to derive the unitary operation performed by the end node. The hierarchical simultaneous entanglement switching(HSES) method is adopted, resulting in a significant reduction in the consumption of classical information compared to multi-hop quantum teleportation(QT)based on general simultaneous entanglement switching(SES). In addition, the proposed protocol is simulated on the IBM Quantum Experiment platform(IBM QE). Then, the data obtained from the experiment are analyzed using quantum state tomography, which verifies the protocol's good fidelity and accuracy. Finally, by calculating fidelity, we analyze the impact of four different types of noise(phase-damping, amplitude-damping, phase-flip and bit-flip) in this protocol.展开更多
Repetitive transcranial magnetic stimulation(rTMS)is a rapid and effective therapy for major depressive disorder;however,there is significant variability in therapeutic outcomes both within and across individuals,with...Repetitive transcranial magnetic stimulation(rTMS)is a rapid and effective therapy for major depressive disorder;however,there is significant variability in therapeutic outcomes both within and across individuals,with approximately 50% of patients showing no response to rTMS treatment.Many studies have personalized the stimulation parameters of rTMS(e.g.,location and intensity of stimulation)according to the anatomical and functional structure of the brain.In addition to these parameters,the internal states of the individual,such as circadian rhythm,behavior/cognition,neural oscillation,and neuroplasticity,also contribute to the variation in rTMS effects.In this review,we summarize the current literature on the interaction between rTMS and internal states.We propose two possible methods,multimodal treatment,and adaptive closed-loop treatment,to integrate patients'internal states to achieve better rTMS treatment for depression.展开更多
As the first gold mine discovered at the sea in China and the only coastal gold mine currently mined there,Sanshandao Gold Mine faces unique challenges.The mine's safety is under continual threat from its faulted ...As the first gold mine discovered at the sea in China and the only coastal gold mine currently mined there,Sanshandao Gold Mine faces unique challenges.The mine's safety is under continual threat from its faulted structure coupled with the overlying water.As the mining proceeds deeper,the risk of water inrush increases.The mine's maximum water yield reaches 15000 m3/day,which is attributable to water channels present in fault zones.Predominantly composed of soil–rock mixtures(SRM),these fault zones'seepage characteristics significantly impact water inrush risk.Consequently,investigating the seepage characteristics of SRM is of paramount importance.However,the existing literature mostly concentrates on a single stress state.Therefore,this study examined the characteristics of the permeability coefficient under three distinct stress states:osmotic,osmotic–uniaxial,and osmotic–triaxial pressure.The SRM samples utilized in this study were extracted from in situ fault zones and then reshaped in the laboratory.In addition,the micromechanical properties of the SRM samples were analyzed using computed tomography scanning.The findings reveal that the permeability coefficient is the highest under osmotic pressure and lowest under osmotic–triaxial pressure.The sensitivity coefficient shows a higher value when the rock block percentage ranges between 30%and 40%,but it falls below 1.0 when this percentage exceeds 50%under no confining pressure.Notably,rock block percentages of 40%and 60%represent the two peak points of the sensitivity coefficient under osmotic–triaxial pressure.However,SRM samples with a 40%rock block percentage consistently show the lowest permeability coefficient under all stress states.This study establishes that a power function can model the relationship between the permeability coefficient and osmotic pressure,while its relationship with axial pressure can be described using an exponential function.These insights are invaluable for developing water inrush prevention and control strategies in mining environments.展开更多
An equation of state(EOS)was obtained that accurately describes the thermodynamics of the system H_(2)O–CO_(2) at temperatures of 50–350°C and pressures of 0.2–3.5 kbar.The equation is based on experimental da...An equation of state(EOS)was obtained that accurately describes the thermodynamics of the system H_(2)O–CO_(2) at temperatures of 50–350°C and pressures of 0.2–3.5 kbar.The equation is based on experimental data on the compositions of the coexisting liquid and gas phases and the Van Laar model,within which the values of the Van Laar parameters A12 and A21 were found for each experimental P-T point.For the resulting sets A12(P,T),A21(P,T),approximation formulas describing the dependences of these quantities on temperature and pressure were found and the parameters contained in the formulas were fitted.This two-stage approach made it possible to obtain an adequate thermodynamic description of the system,which allows,in addition to determining the phase state of the system(homogeneous or heterogeneous),to calculate the excess free energy of mixing of H_(2)O and CO_(2),the activities of H_(2)O and CO_(2),and other thermodynamic characteristics of the system.The possibility of such calculations creates the basis for using the obtained EOS in thermodynamic models of more complicated fluid systems in P-T conditions of the middle and upper crust.These fluids play an important role in many geological processes including the transport of ore matter and forming hydrothermal ore deposits,in particular,the most of the world’s gold deposits.The knowledge of thermodynamics of these fluids is important in the technology of drilling oil and gas wells.In particular,this concerns the prevention of precipitation of solid salts in the well.展开更多
The effects of plasma screening on the ^(1)P^(o) resonance states of H-and He below the n=3 and n=4 thresholds of the respective subsystemsare investigated using the stabilization method and correlated exponential wav...The effects of plasma screening on the ^(1)P^(o) resonance states of H-and He below the n=3 and n=4 thresholds of the respective subsystemsare investigated using the stabilization method and correlated exponential wave functions.Two plasma mediums,namely,the Debye plasma and quantum plasma environments are considered.The screened Coulomb potential(SCP)obtained from Debye-Hückel model is used to represent Debye plasma environments and the exponential cosine screened Coulomb potential(ECSCP)obtained from a modified Debye-Hückel model is used to represent quantum plasma environments.The resonance parameters(resonance positions and widths)are presented in terms of the screening parameters.展开更多
This paper presents a new type of triangular Sharp Eagle wave energy converter(WEC)platform.On the basis of the linear potential flow theory and the finite element analysis method,the hydrodynamic performance and stru...This paper presents a new type of triangular Sharp Eagle wave energy converter(WEC)platform.On the basis of the linear potential flow theory and the finite element analysis method,the hydrodynamic performance and structural response of the platform are studied,considering the actual platform motion and free surface rise under extreme sea states.First,the effects of the wave frequency and direction on the wave-induced loads and dynamic responses were examined.The motion at a wave direction angle of 0°is relatively low.On this basis,the angle constrained by the two sides of the Sharp Eagle floaters should be aligned with the main wave direction to avoid significant platform motion under extreme sea states.Additionally,the structural response of the platform,including the wave-absorbing floaters,is investigated.The results highlighted that the conditions or locations where yielding,buckling,and fatigue failures occur were different.In this context,the connection area of the Sharp Eagle floaters and platform is prone to yielding failure under oblique wave action,whereas the pontoon and side of the Sharp Eagle floaters are prone to buckling failure during significant vertical motion.Additionally,fatigue damage is most likely to occur at the connection between the middle column on both sides of the Sharp Eagle floaters and the pontoons.The findings of this paper revealed an intrinsic connection between wave-induced loads and the dynamic and structural responses of the platform,which provides a useful reference for the improved design of WECs.展开更多
文摘We consider an energy operator of four-electron system in the Impurity Hubbard model with a coupling between nearest-neighbors. The spectrum of the systems in the second triplet state in a ν-dimensional lattice is investigated. For investigation the structure of essential spectra and discrete spectrum of the energy operator of four-electron systems in an impurity Hubbard model, for which the momentum representation is convenient. In addition, we used the tensor products of Hilbert spaces and tensor products of operators in Hilbert spaces and described the structure of essential spectrum and discrete spectrum of the energy operator of four-electron systems in an impurity Hubbard model for the second triplet state of the system. The investigations show that the essential spectrum of the system consists of the union of no more than sixteen segments, and the discrete spectrum of the system consists of no more than eleven eigenvalues.
文摘Apparel exports China:The decline in exports widened from January to September(-2.4%,compared to-0.2%in January-June).Exports to the EU increased(+5.9%),though the growth rate moderated.Exports to the US saw a larger contraction(January-June:-1.6%,January-September:-8.2%).While exports to ASEAN countries still fell by over 10%(-17.7%),shipments to the Philippines(+6.9%),Indonesia(+19.0%),and Cambodia(+64.9%)demonstrated stronger growth performance within the year.Regarding tariffs,on October 30,China and the US agreed to lower the rates on goods subject to additional duties(effectively reducing the average tariff rate on Chinese imports to the US from about 57%to approximately 47%,though this remains significantly higher than the 19.5%overall average rate applied to other countries).
基金supported by the Higher Education and Science Committee of Armenia in the frames of the research projects 20TTSG-2F010,23AA-2F033 and ANSEF(EN-matsc-2660)grantConvex hull calculations were done on the Oracle HPC clouds provided by the Oracle for Research grant(16576595)The USPEX calculations were performed on the Armenian National Supercomputing Center(ANSCC).MLIP training and ionic conductivity calculations were performed with the support of the Russian Science。
文摘Halide solid-state electrolytes have gained significant attention in recent years due to their high ionic conductivity,making them promising candidates for future all-solid-state batteries.Recent studies have identified numerous crystal structures with the Li_(3)MX_(6)composition,although many remain unexplored across various chemical systems.In this research,we developed a comprehensive method to examine all conceivable space groups and structures within theLi-M-X system,where M includes In,Ga,and La,and X includes F,Cl,Br,and 1.Our findings revealed two metastable structures:Li_(3)InF_(6)with P3c1 symmetry and Li_(3)InI_(6)with C2/c symmetry,exhibiting ionic conductivities of 0.55 and 2.18mS/cm at 300K,respectively.Notably,the trigonal symmetry of Li3InF6 demonstrates that high ionic conductivities are not limited to monoclinic structures but can also be achieved with trigonal symmetries.The electrochemical stability windows,mechanical properties,and reaction energies of these materials with known cathodes suggest their potential for use in all-solid-state batteries.Additionally,we predicted the stability of novel materials,including Li_(5)InCl_(9),Li_(5)InBr_(9),Li_(5)InI_(8),LiIn_(2)Cl_(9),LiIn_(2)Br_(9),and LiIn_(2)Ig_(9).
基金financial support provided by the Natural Science Foundation of Hebei Province,China(No.E2024105036)the Tangshan Talent Funding Project,China(Nos.B202302007 and A2021110015)+1 种基金the National Natural Science Foundation of China(No.52264042)the Australian Research Council(No.IH230100010)。
文摘Automated classification of gas flow states in blast furnaces using top-camera imagery typically demands a large volume of labeled data,whose manual annotation is both labor-intensive and cost-prohibitive.To mitigate this challenge,we present an enhanced semi-supervised learning approach based on the Mean Teacher framework,incorporating a novel feature loss module to maximize classification performance with limited labeled samples.The model studies show that the proposed model surpasses both the baseline Mean Teacher model and fully supervised method in accuracy.Specifically,for datasets with 20%,30%,and 40%label ratios,using a single training iteration,the model yields accuracies of 78.61%,82.21%,and 85.2%,respectively,while multiple-cycle training iterations achieves 82.09%,81.97%,and 81.59%,respectively.Furthermore,scenario-specific training schemes are introduced to support diverse deployment need.These findings highlight the potential of the proposed technique in minimizing labeling requirements and advancing intelligent blast furnace diagnostics.
基金supported by the National Natural Science Foundation of China(Nos.62304111,62304110,22579136)the National Key Research and Development Program of China(2024YFE0201800)+6 种基金the China Postdoctoral Science Foundation(No.2024M761492)the Project of State Key Laboratory of Organic Electronics and Information Displays(Nos.GDX2022010009,GZR2023010046)the Natural Science Research Start-up Foundation of Recruiting Talents of Nanjing University of Posts and Telecommunications(No.NY223053)the Science and Technology Project of Jiangsu(Science and Technology Cooperation Project of HongKong,Macao and Taiwan,No.BZ2023059)Shaanxi Fundamental Science Research Project for Mathematics and Physics(No.22jSY015)Young Talent Fund of Xi'an Association for Science and Technology(No.959202313020)Guangdong Provincial Key Laboratory of Semiconductor Optoelectronic Materials and Intelligent Photonic Systems(No.2023B1212010003).
文摘Surface passivation via two-dimensional(2D)perovskite has emerged as a promising strategy to enhance the performance of perovskite solar cells(PSCs)due to the effective compensation of interfacial states.However,the in situ grown 2D perovskite passivation layers typically comprise a mixture of multiple dimensionalities at the interface,where band alignment has only been portrayed qualitatively and empirically.Herein,the interface states for precisely phase-tailored 2D perovskite passivated PSCs are quantitatively investigated.In comparison to traditional passivation molecules,2D perovskite layers based on 4-trifluoromethyl-phenylethylammonium iodide(CF3PEAI)exhibit an increased work function,introducing desirable downward band bending to eliminate the Schottky Barrier.Furthermore,precisely phase-tailored 2D layers could modulate the interface trap density and energetics.The n=1 film delivers optimal performance with a hole extraction efficiency of 95.1%.The optimized n-i-p PSCs in the two-step method significantly improve PCE to 25.40%,along with enhanced photostability and negligible hysteresis.It highlights that tailoring in the composition and phase distribution of the 2D perovskite layer could modulate the interface states at the 2D/3D interface.
基金financially supported by the Sichuan Science and Technology Program(Grant No.2025NSFSC0139)the China Postdoctoral Science Foundation(Grant No.2023MD734228)+5 种基金The authors extend their gratitude to Ms.Zhou Yuke(from Scientific Compass www.shiyanjia.com)for providing invaluable assistance with the XPS analysis.ICN2 acknowledges funding from Generalitat de Catalunya 2021SGR00457This study is part of the Advanced Materials programme and was supported by MCIN with funding from European Union NextGenerationEU(PRTR-C17.I1)by Generalitat de Catalunya(In-CAEM Project)The authors thank the support from the project AMaDE(PID2023-149158OB-C43)funded by MCIN/AEI/10.13039/501100011033/and by“ERDF A way of making Europe”,by the“European Union”.ICN2 is supported by the Severo Ochoa program from Spanish MCIN/AEI(Grant No.:CEX2021-001214-S)is funded by the CERCA Programme/Generalitat de Catalunya.Part of the present work has been performed in the framework of Universitat Autònoma de Barcelona Materials Science PhD program.JY has received funding from the CSC-UAB PhD scholarship program.ICN2 is founding member of e-DREAM[87].
文摘The methanol oxidation reaction(MOR)to formic acid offers a promising alternative to the anodic oxygen evolution reaction(OER)in water electrolysis.However,the development of efficient and cost-effective catalysts remains a primary challenge.In this study,an enhancement in catalytic MOR performance is achieved through the incorporation of Mn atoms with unsaturated t_(2g)orbitals into Ni_(3)Se_(4).Comprehensive experimental analyses and theoretical calculations reveal that substituting Ni with Mn induces strong electron-withdrawing effects,effectively modulating the local coordination environment of the metal centers.The presence of Mn also elongates Ni–Se(O)bonds,which reduces eg orbital occupancy and modifies the spin state of the material.Electrochemical measurements demonstrate that electrodes based on this optimized material exhibit a high spin state and deliver excellent catalytic activity,achieving a MOR current density up to∼190 mA cm^(−2)at 1.6 V.This performance enhancement is attributed to the favorable electronic configuration and reduced reaction energy barriers associated with the high-spin state.
基金supported by National Natural Science Foundation of China(NSFC)under grant U23A20310.
文摘With the growing advancement of wireless communication technologies,WiFi-based human sensing has gained increasing attention as a non-intrusive and device-free solution.Among the available signal types,Channel State Information(CSI)offers fine-grained temporal,frequency,and spatial insights into multipath propagation,making it a crucial data source for human-centric sensing.Recently,the integration of deep learning has significantly improved the robustness and automation of feature extraction from CSI in complex environments.This paper provides a comprehensive review of deep learning-enhanced human sensing based on CSI.We first outline mainstream CSI acquisition tools and their hardware specifications,then provide a detailed discussion of preprocessing methods such as denoising,time–frequency transformation,data segmentation,and augmentation.Subsequently,we categorize deep learning approaches according to sensing tasks—namely detection,localization,and recognition—and highlight representative models across application scenarios.Finally,we examine key challenges including domain generalization,multi-user interference,and limited data availability,and we propose future research directions involving lightweight model deployment,multimodal data fusion,and semantic-level sensing.
基金supported by the National Science and Technology Council,Taiwan,with grant numbers NSTC 114-2622-8-992-007-TD1 and 112-2811-E-992-003-MY3.
文摘The global population is rapidly expanding,driving an increasing demand for intelligent healthcare systems.Artificial intelligence(AI)applications in remote patient monitoring and diagnosis have achieved remarkable progress and are emerging as a major development trend.Among these applications,mouth motion tracking and mouth-state detection represent an important direction,providing valuable support for diagnosing neuromuscular disorders such as dysphagia,Bell’s palsy,and Parkinson’s disease.In this study,we focus on developing a real-time system capable of monitoring and detecting mouth state that can be efficiently deployed on edge devices.The proposed system integrates the Facial Landmark Detection technique with an optimized model combining a Bidirectional Gated Recurrent Unit(BiGRU)and Comprehensive Learning Particle Swarm Optimization(CLPSO).We conducted a comprehensive comparison and evaluation of the proposed model against several traditional models using multiple performance metrics,including accuracy,precision,recall,F1-score,cosine similarity,ROC–AUC,and the precision–recall curve.The proposed method achieved an impressive accuracy of 96.57%with an excellent precision of 98.25%on our self-collected dataset,outperforming traditional models and related works in the same field.These findings highlight the potential of the proposed approach for implementation in real-time patient monitoring systems,contributing to improved diagnostic accuracy and supporting healthcare professionals in patient treatment and care.
基金supported by the Royal Academy of Engineering,UK,in the scheme of Distinguished International Associate(DIA-2424-5-134).
文摘Accurate estimation of the State of Charge(SOC),State of Health(SOH),and Terminal Resistance(TR)is crucial for the effective operation of Battery Management Systems(BMS)in lithium-ion batteries.This study conducts a comprehensive comparative analysis of four Kalman filter variants Extended Kalman Filter(EKF),Extended Kalman-Bucy Filter(EKBF),Unscented Kalman Filter(UKF),and Unscented Kalman-Bucy Filter(UKBF)under varying battery parameter conditions.These include temperature fluctuation,self-discharge,current direction,cell capacity,process noise,and measurement noise.Our findings reveal significant variations in the performance of SOC and SOH predictions across filters,emphasizing that UKF demonstrates superior robustness to noise,while EKF performs better under accurate system dynamics.The study underscores the need for adaptive filtering strategies that can dynamically adjust to evolving battery parameters,thereby enhancing BMS reliability and extending battery lifespan.
基金supported by the National Natural Science Foundation of China(NSFC)under Grant(No.51677058).
文摘Precisely estimating the state of health(SOH)of lithium-ion batteries is essential for battery management systems(BMS),as it plays a key role in ensuring the safe and reliable operation of battery systems.However,current SOH estimation methods often overlook the valuable temperature information that can effectively characterize battery aging during capacity degradation.Additionally,the Elman neural network,which is commonly employed for SOH estimation,exhibits several drawbacks,including slow training speed,a tendency to become trapped in local minima,and the initialization of weights and thresholds using pseudo-random numbers,leading to unstable model performance.To address these issues,this study addresses the challenge of precise and effective SOH detection by proposing a method for estimating the SOH of lithium-ion batteries based on differential thermal voltammetry(DTV)and an SSA-Elman neural network.Firstly,two health features(HFs)considering temperature factors and battery voltage are extracted fromthe differential thermal voltammetry curves and incremental capacity curves.Next,the Sparrow Search Algorithm(SSA)is employed to optimize the initial weights and thresholds of the Elman neural network,forming the SSA-Elman neural network model.To validate the performance,various neural networks,including the proposed SSA-Elman network,are tested using the Oxford battery aging dataset.The experimental results demonstrate that the method developed in this study achieves superior accuracy and robustness,with a mean absolute error(MAE)of less than 0.9%and a rootmean square error(RMSE)below 1.4%.
基金supported by the Guizhou Provincial Basic Research Program(Natural Science)Youth Guidance Project{Qian Kehe Foundation-[2024]Youth 307}。
文摘In both Traditional Chinese Medicine(TCM)and modern medicine,they agree that the integrity and healthy structure of the vascular endothelium are essential for normal hemodynamics.Damage to the vascular endothelium can quickly activate the extrinsic coagulation pathway by triggering the tissue factor(TF)and lead to coagulation.This damage,along with a loss of anticoagulant properties through antithrombinⅢ(ATⅢ),TF pathway inhibitors,and the protein C system,can result in a hypercoagulable state and even thrombosis.Hypercoagulability is not only a common feature of many cancers but also an important factor promoting tumor development and metastasis,which corresponds to the TCM theory of“blood stasis leading to tumors.”The pharmacological effects of heparin and aspirin have similarities with TCM's“activating blood circulation and removing blood stasis”theory in improving blood circulation,treating related diseases,and their anti-inflammatory effects.
基金supported by the National Natural Science Foundation of China(No.51905123)Major Scientific and Technological Innovation Program of Shandong Province,China(Nos.2020CXGC010303,2022ZLGX04)Key R&D Programme of Shandong Province,China(No.2022JMRH0308).
文摘An internal state variable(ISV)model was established according to the experimental results of hot plane strain compression(PSC)to predict the microstructure evolution during hot spinning of ZK61 alloy.The effects of the internal variables were considered in this ISV model,and the parameters were optimized by genetic algorithm.After validation,the ISV model was used to simulate the evolution of grain size(GS)and dynamic recrystallization(DRX)fraction during hot spinning via Abaqus and its subroutine Vumat.By comparing the simulated results with the experimental results,the application of the ISV model was proven to be reliable.Meanwhile,the strength of the thin-walled spun ZK61 tube increased from 303 to 334 MPa due to grain refinement by DRX and texture strengthening.Besides,some ultrafine grains(0.5μm)that played an important role in mechanical properties were formed due to the proliferation,movement,and entanglement of dislocations during the spinning process.
基金supported by the National Natural Science Foundation of China(No.52061135101 and 52001078)the German Research Foundation(DFG,No.448318292)+3 种基金the Technology Innovation Guidance Special Foundation of Shaanxi Province(No.2023GXLH-085)the Fundamental Research Funds for the Central Universities(No.D5000240161)the Project of Key areas of innovation team in Shaanxi Province(No.2024RS-CXTD-20)The author Yingchun Xie thanks the support from the National Key R&D Program(No.2023YFE0108000).
文摘1.Introduction.Cold Spray(CS)is a highly advanced solid-state metal depo-sition process that was first developed in the 1980s.This innovative technique involves the high-speed(300-1200 m/s)impact deposition of micron-sized particles(5-50μm)to fabricate coatings[1-3].CS has been extensively used in a variety of coating applications,such as aerospace,automotive,energy,medical,marine,and others,to provide protection against high temperatures,corrosion,erosion,oxidation,and chemicals[4,5].Nowadays,the technical interest in CS is twofold:(i)as a repair process for damaged components,and(ii)as a solid-state additive manufacturing process.Compared to other fusion-based additive manufacturing(AM)technologies,Cold Spray Additive Manufacturing(CSAM)is a new member of the AM family that can enable the fabrication of deposits without undergoing melting.The chemical composition has been largely preserved from the powder to the deposit due to the minimal oxidation.The significant advantages of CSAM over other additive manufacturing processes include a high production rate,unlimited deposition size,high flexibility,and suitability for repairing damaged parts.
基金funded by the Bavarian State Ministry of Science,Research and Art(Grant number:H.2-F1116.WE/52/2)。
文摘In order to address the widespread data shortage problem in battery research,this paper proposes a generative adversarial network model that combines it with deep convolutional networks,the Wasserstein distance,and the gradient penalty to achieve data augmentation.To lower the threshold for implementing the proposed method,transfer learning is further introduced.The W-DC-GAN-GP-TL framework is thereby formed.This framework is evaluated on 3 different publicly available datasets to judge the quality of generated data.Through visual comparisons and the examination of two visualization methods(probability density function(PDF)and principal component analysis(PCA)),it is demonstrated that the generated data is hard to distinguish from the real data.The application of generated data for training a battery state model using transfer learning is further evaluated.Specifically,Bi-GRU-based and Transformer-based methods are implemented on 2 separate datasets for estimating state of health(SOH)and state of charge(SOC),respectively.The results indicate that the proposed framework demonstrates satisfactory performance in different scenarios:for the data replacement scenario,where real data are removed and replaced with generated data,the state estimator accuracy decreases only slightly;for the data enhancement scenario,the estimator accuracy is further improved.The estimation accuracy of SOH and SOC is as low as 0.69%and 0.58%root mean square error(RMSE)after applying the proposed framework.This framework provides a reliable method for enriching battery measurement data.It is a generalized framework capable of generating a variety of time series data.
基金Project supported by the Open Fund of Anhui Key Laboratory of Mine Intelligent Equipment and Technology (Grant No. ZKSYS202204)the Talent Introduction Fund of Anhui University of Science and Technology (Grant No. 2021yjrc34)the Scientific Research Fund of Anhui Provincial Education Department (Grant No. KJ2020A0301)。
文摘Implementing quantum wireless multi-hop network communication is essential to improve the global quantum network system. In this paper, we employ eight-level GHZ states as quantum channels to realize multi-hop quantum communication, and utilize the logical relationship between the measurements of each node to derive the unitary operation performed by the end node. The hierarchical simultaneous entanglement switching(HSES) method is adopted, resulting in a significant reduction in the consumption of classical information compared to multi-hop quantum teleportation(QT)based on general simultaneous entanglement switching(SES). In addition, the proposed protocol is simulated on the IBM Quantum Experiment platform(IBM QE). Then, the data obtained from the experiment are analyzed using quantum state tomography, which verifies the protocol's good fidelity and accuracy. Finally, by calculating fidelity, we analyze the impact of four different types of noise(phase-damping, amplitude-damping, phase-flip and bit-flip) in this protocol.
基金supported by STI2030-Major Projects(2021ZD0204300 and 2021ZD0200800)the National Natural Science Foundation of China(82271528)the Fundamental Research Funds for the Central Universities(Peking University Medicine Fund for World's Leading Discipline or Discipline Cluster Development,BMU2022DJXK007).
文摘Repetitive transcranial magnetic stimulation(rTMS)is a rapid and effective therapy for major depressive disorder;however,there is significant variability in therapeutic outcomes both within and across individuals,with approximately 50% of patients showing no response to rTMS treatment.Many studies have personalized the stimulation parameters of rTMS(e.g.,location and intensity of stimulation)according to the anatomical and functional structure of the brain.In addition to these parameters,the internal states of the individual,such as circadian rhythm,behavior/cognition,neural oscillation,and neuroplasticity,also contribute to the variation in rTMS effects.In this review,we summarize the current literature on the interaction between rTMS and internal states.We propose two possible methods,multimodal treatment,and adaptive closed-loop treatment,to integrate patients'internal states to achieve better rTMS treatment for depression.
基金State Key Research Development Program of China,Grant/Award Number:2021YFC3001301。
文摘As the first gold mine discovered at the sea in China and the only coastal gold mine currently mined there,Sanshandao Gold Mine faces unique challenges.The mine's safety is under continual threat from its faulted structure coupled with the overlying water.As the mining proceeds deeper,the risk of water inrush increases.The mine's maximum water yield reaches 15000 m3/day,which is attributable to water channels present in fault zones.Predominantly composed of soil–rock mixtures(SRM),these fault zones'seepage characteristics significantly impact water inrush risk.Consequently,investigating the seepage characteristics of SRM is of paramount importance.However,the existing literature mostly concentrates on a single stress state.Therefore,this study examined the characteristics of the permeability coefficient under three distinct stress states:osmotic,osmotic–uniaxial,and osmotic–triaxial pressure.The SRM samples utilized in this study were extracted from in situ fault zones and then reshaped in the laboratory.In addition,the micromechanical properties of the SRM samples were analyzed using computed tomography scanning.The findings reveal that the permeability coefficient is the highest under osmotic pressure and lowest under osmotic–triaxial pressure.The sensitivity coefficient shows a higher value when the rock block percentage ranges between 30%and 40%,but it falls below 1.0 when this percentage exceeds 50%under no confining pressure.Notably,rock block percentages of 40%and 60%represent the two peak points of the sensitivity coefficient under osmotic–triaxial pressure.However,SRM samples with a 40%rock block percentage consistently show the lowest permeability coefficient under all stress states.This study establishes that a power function can model the relationship between the permeability coefficient and osmotic pressure,while its relationship with axial pressure can be described using an exponential function.These insights are invaluable for developing water inrush prevention and control strategies in mining environments.
基金funded by the Research program FMUW-2021-0002 of the IPGG RAS.
文摘An equation of state(EOS)was obtained that accurately describes the thermodynamics of the system H_(2)O–CO_(2) at temperatures of 50–350°C and pressures of 0.2–3.5 kbar.The equation is based on experimental data on the compositions of the coexisting liquid and gas phases and the Van Laar model,within which the values of the Van Laar parameters A12 and A21 were found for each experimental P-T point.For the resulting sets A12(P,T),A21(P,T),approximation formulas describing the dependences of these quantities on temperature and pressure were found and the parameters contained in the formulas were fitted.This two-stage approach made it possible to obtain an adequate thermodynamic description of the system,which allows,in addition to determining the phase state of the system(homogeneous or heterogeneous),to calculate the excess free energy of mixing of H_(2)O and CO_(2),the activities of H_(2)O and CO_(2),and other thermodynamic characteristics of the system.The possibility of such calculations creates the basis for using the obtained EOS in thermodynamic models of more complicated fluid systems in P-T conditions of the middle and upper crust.These fluids play an important role in many geological processes including the transport of ore matter and forming hydrothermal ore deposits,in particular,the most of the world’s gold deposits.The knowledge of thermodynamics of these fluids is important in the technology of drilling oil and gas wells.In particular,this concerns the prevention of precipitation of solid salts in the well.
基金Supported by the Natural Science Foundation of Heilongjiang Province(LH2024A025)。
文摘The effects of plasma screening on the ^(1)P^(o) resonance states of H-and He below the n=3 and n=4 thresholds of the respective subsystemsare investigated using the stabilization method and correlated exponential wave functions.Two plasma mediums,namely,the Debye plasma and quantum plasma environments are considered.The screened Coulomb potential(SCP)obtained from Debye-Hückel model is used to represent Debye plasma environments and the exponential cosine screened Coulomb potential(ECSCP)obtained from a modified Debye-Hückel model is used to represent quantum plasma environments.The resonance parameters(resonance positions and widths)are presented in terms of the screening parameters.
基金supported by the National Key Research and Development Program of China(Grant No.2022YFC3003805)Youth Innovation Promotion Association of the Chinese Academy of Sciences(Grant No.2022356)Guangzhou Basic and Applied Basic Research Project(Grant No.2023A04J0955).
文摘This paper presents a new type of triangular Sharp Eagle wave energy converter(WEC)platform.On the basis of the linear potential flow theory and the finite element analysis method,the hydrodynamic performance and structural response of the platform are studied,considering the actual platform motion and free surface rise under extreme sea states.First,the effects of the wave frequency and direction on the wave-induced loads and dynamic responses were examined.The motion at a wave direction angle of 0°is relatively low.On this basis,the angle constrained by the two sides of the Sharp Eagle floaters should be aligned with the main wave direction to avoid significant platform motion under extreme sea states.Additionally,the structural response of the platform,including the wave-absorbing floaters,is investigated.The results highlighted that the conditions or locations where yielding,buckling,and fatigue failures occur were different.In this context,the connection area of the Sharp Eagle floaters and platform is prone to yielding failure under oblique wave action,whereas the pontoon and side of the Sharp Eagle floaters are prone to buckling failure during significant vertical motion.Additionally,fatigue damage is most likely to occur at the connection between the middle column on both sides of the Sharp Eagle floaters and the pontoons.The findings of this paper revealed an intrinsic connection between wave-induced loads and the dynamic and structural responses of the platform,which provides a useful reference for the improved design of WECs.
