Classical computation of electronic properties in large-scale materials remains challenging.Quantum computation has the potential to offer advantages in memory footprint and computational scaling.However,general and v...Classical computation of electronic properties in large-scale materials remains challenging.Quantum computation has the potential to offer advantages in memory footprint and computational scaling.However,general and viable quantum algorithms for simulating large-scale materials are still limited.We propose and implement random-state quantum algorithms to calculate electronic-structure properties of real materials.Using a random state circuit on a small number of qubits,we employ real-time evolution with first-order Trotter decomposition and Hadamard test to obtain electronic density of states,and we develop a modified quantum phase estimation algorithm to calculate real-space local density of states via direct quantum measurements.Furthermore,we validate these algorithms by numerically computing the density of states and spatial distributions of electronic states in graphene,twisted bilayer graphene quasicrystals,and fractal lattices,covering system sizes from hundreds to thousands of atoms.Our results manifest that the random-state quantum algorithms provide a general and qubit-efficient route to scalable simulations of electronic properties in large-scale periodic and aperiodic materials.展开更多
In conventional higher-order topological insulators(HOTIs),the emergence of topological states can be explained by using the nonzero bulk polarization index.However,corner states emerge in HOTIs with incomplete bounda...In conventional higher-order topological insulators(HOTIs),the emergence of topological states can be explained by using the nonzero bulk polarization index.However,corner states emerge in HOTIs with incomplete boundary unit cells(i.e.,boundary defects)even though the bulk polarization is zero,which challenges the conventional understanding of HOTIs.Here,based on a Kekul´e-distorted honeycomb lattice with incomplete unit cells,we reveal that incomplete unit cells exhibit fractional charges through the analysis of Wannier centers by developing a compensation method and creating the concept of Wannier center domain(WCD)which is the smallest region that one Wannier center occupies.This method compensates for the missing parts of these boundary incomplete unit cells with additional WCDs to make them complete.The compensated WCDs automatically carry the corresponding charge,and this charge together with that of the incomplete unit cell constitutes the total charge of the complete unit cell after compensation.We conclude that the emergence of corner states is attributed to the filling anomaly,which is a fundamental mechanism.Our results refresh the understanding of HOTIs,especially those with structural discontinuities,and provide a novel design for topological states which have application value in producing optical functional devices.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
The development of collinear resonance ionization spectroscopy for studying the nuclear structure of nickel isotopes far from the stability line relies on high-efficiency two-color two-step photoionization pathways.We...The development of collinear resonance ionization spectroscopy for studying the nuclear structure of nickel isotopes far from the stability line relies on high-efficiency two-color two-step photoionization pathways.We systematically investigated the even-parity autoionization spectrum of atomic nickel through resonance ionization mass spectrometry(RIMS).Fifteen intense single-color photoionization lines and corresponding transitions in the 300-325 nm range were identified and excluded as potential interference peaks for subsequent two-color studies.Fifty-one even-parity autoionization states in the 64000-66800 cm^(-1)range were identified for the first time by scanning from five intermediate excited states of the3d^(8)(^(3)F)4s4p(^(3)P^(o))configuration.Forty-eight of these states were assigned unique total angular momentum quantum numbers(J)based on electric dipole transition selection rules.The autoionization state at 64437.77 cm^(-1)was identified as an optimal final state for enhancing photoionization efficiency in two-color two-step pathways.This study provides comprehensive datasets of even-parity autoionization states of nickel,supporting both the advancement of collinear resonance ionization spectroscopy for exotic nickel isotopes and theoretical modeling of autoionization states.The datasets are openly available at https://doi.org/10.57760/sciencedb.j00113.00280.展开更多
Efficient implementation of fundamental matrix operations on quantum computers,such as matrix products and Hadamard operations,holds significant potential for accelerating machine learning algorithms.A critical prereq...Efficient implementation of fundamental matrix operations on quantum computers,such as matrix products and Hadamard operations,holds significant potential for accelerating machine learning algorithms.A critical prerequisite for quantum implementations is the effective encoding of classical data into quantum states.We propose two quantum computing frameworks for preparing the distinct encoded states corresponding to matrix operations,including the matrix product,matrix sum,matrix Hadamard product and division.Quantum algorithms based on the digital encoding computing framework are capable of implementing the matrix Hadamard operation with a time complexity of O(poly log(mn/ε))and the matrix product with a time complexity of O(poly log(mnl/ε)),achieving an exponential speedup in contrast to the classical methods of O(mn)and O(mnl).Quantum algorithms based on the analog-encoding framework are capable of implementing the matrix Hadamard operation with a time complexity of O(k_(1)√mn·poly log(mn/ε))and the matrix product with a time complexity of O(k_(2)√1·poly log(mnl/ε)),where k_(1)and k_(2)are coefficients correlated with the elements of the matrix,achieving a square speedup in contrast to the classical counterparts.As applications,we construct an oracle that can access the trace of a matrix within logarithmic time,and propose several algorithms to respectively estimate the trace of a matrix,the trace of the product of two matrices,and the trace inner product of two matrices within logarithmic time.展开更多
BACKGROUND The prevalence of negative emotional states,such as anxiety and depression,has increased annually.Although personal habits are known to influence emotional regulation,the precise mechanisms underlying this ...BACKGROUND The prevalence of negative emotional states,such as anxiety and depression,has increased annually.Although personal habits are known to influence emotional regulation,the precise mechanisms underlying this relationship remain unclear.AIM To investigate emotion regulation habits impact on students negative emotions during lockdown,using the coronavirus disease 2019 pandemic as a case example.METHODS During the coronavirus disease 2019 lockdown,an online cross-sectional survey was conducted at a Chinese university.Emotional states were assessed using the Depression,Anxiety,and Stress Scale-21(DASS-21),while demographic data and emotion regulation habits were collected concurrently.Data analysis was performed using SPSS version 27.0 and includedχ^(2)-tests for intergroup comparisons,Spearman’s rank-order correlation coefficient analysis to examine associations,and stepwise linear regression modeling to explore the relationships between emotion regulation habits and emotional states.Statistical significance was set atα=0.05.RESULTS Among the 494 valid questionnaires analyzed,the prevalence rates of negative emotional states were as follows:Depression(65.0%),anxiety(69.4%),and stress(50.8%).DASS-21 scores(mean±SD)demonstrated significant symptomatology:Total(48.77±34.88),depression(16.21±12.18),anxiety(14.90±11.91),and stress(17.64±12.07).Significant positive intercorrelations were observed among all DASS-21 subscales(P<0.01).Regression analysis identified key predictors of negative emotions(P<0.05):Risk factors included late-night frequency and academic pressure,while protective factors were the frequency of parental contact and the number of same-gender friends.Additionally,compensatory spending and binge eating positively predicted all negative emotion scores(β>0,P<0.01),whereas appropriate recreational activities negatively predicted these scores(β<0,P<0.01).CONCLUSION High negative emotion prevalence occurred among confined students.Recreational activities were protective,while compensatory spending and binge eating were risk factors,necessitating guided emotion regulation.展开更多
The development of novel quantum many-body computational algorithms relies on robust benchmarking.However,generating such benchmarks is often hindered by the massive computational resources required for exact diagonal...The development of novel quantum many-body computational algorithms relies on robust benchmarking.However,generating such benchmarks is often hindered by the massive computational resources required for exact diagonalization or quantum Monte Carlo simulations,particularly at finite temperatures.In this work,we propose a new algorithm for obtaining thermal pure quantum states,which allows efficient computation of both mechanical and thermodynamic properties at finite temperatures.We implement this algorithm in our open-source C++template library,Physica.Combining the improved algorithm with state-of-the-art software engineering,our implementation achieves high performance and numerical stability.As an example,we demonstrate that for the 4×4 Hubbard model,our method runs approximately 10~3times faster than HΦ3.5.2.Moreover,the accessible temperature range is extended down toβ=32 across arbitrary doping levels.These advances significantly push forward the frontiers of benchmarking for quantum many-body systems.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
Superconducting elect rides have attracted growing attention for their potential to achieve high superconducting transition temperatures(T_(C))under pressure.However,many known elect rides are chemically reactive and ...Superconducting elect rides have attracted growing attention for their potential to achieve high superconducting transition temperatures(T_(C))under pressure.However,many known elect rides are chemically reactive and unstable,making high-quality single-crystal growth,characterization,and measurements difficult,and most do not exhibit superconductivity at ambient pressure.In contrast,La_(3) In stands out for its ambient-pressure superconductivity(T_(C)∼9.4 K)and the availability of high-quality single crystals.Here,we investigate its low-energy electronic structure using angle-resolved photoemission spectroscopy and first-principles calculations.The bands near the Fermi energy(E_(F))are mainly derived from La 5d and In 5p orbitals.A saddle point is directly observed at the Brillouin zone(BZ)boundary,while a three-dimensional Van Hove singularity crosses E_(F) at the BZ corner.First-principles calculations further reveal topological Dirac surface states within the bulk energy gap above E_(F).The coexistence of a high density of states and in-gap topological surface states near𝐸F suggests that La3In offers a promising platform for tuning superconductivity and exploring possible topological superconducting phases through doping or external pressure.展开更多
The hybridization gap in strained-layer InAs/In_(x)Ga_(1−x) Sb quantum spin Hall insulators(QSHIs)is significantly enhanced compared to binary InAs/GaSb QSHI structures,where the typical indium composition,x,ranges be...The hybridization gap in strained-layer InAs/In_(x)Ga_(1−x) Sb quantum spin Hall insulators(QSHIs)is significantly enhanced compared to binary InAs/GaSb QSHI structures,where the typical indium composition,x,ranges between 0.2 and 0.4.This enhancement prompts a critical question:to what extent can quantum wells(QWs)be strained while still preserving the fundamental QSHI phase?In this study,we demonstrate the controlled molecular beam epitaxial growth of highly strained-layer QWs with an indium composition of x=0.5.These structures possess a substantial compressive strain within the In_(0.5)Ga_(0.5)Sb QW.Detailed crystal structure analyses confirm the exceptional quality of the resulting epitaxial films,indicating coherent lattice structures and the absence of visible dislocations.Transport measurements further reveal that the QSHI phase in InAs/In_(0.5)Ga_(0.5)Sb QWs is robust and protected by time-reversal symmetry.Notably,the edge states in these systems exhibit giant magnetoresistance when subjected to a modest perpendicular magnetic field.This behavior is in agreement with the𝑍2 topological property predicted by the Bernevig–Hughes–Zhang model,confirming the preservation of topologically protected edge transport in the presence of enhanced bulk strain.展开更多
This paper aims to identify factors that influence the expectations of a wide range of stakeholders on the information disclosure in the Malaysian State Islamic Religious Councils(SIRC)annual reports,employing semi-st...This paper aims to identify factors that influence the expectations of a wide range of stakeholders on the information disclosure in the Malaysian State Islamic Religious Councils(SIRC)annual reports,employing semi-structured interviews.The majority of interviewees perceived accounting standards as the main factor contributing to their expectations and further influenced the reporting practices among accountants in SIRC.Others are state fatwa(Islamic rulings),audit expectations,and individual perceptions.The result of the interviews revealed that on the top of accounting standards and government guidelines on the reporting for all government agencies,SIRC should take into account their greater accountability,which should be reflected in their reporting practices.Therefore,Islamic accountability through fatwa,audit expectations,and public demands could be considered.Such awareness is important in SIRC,to differentiate them from other government agencies.The existence of governance is similar to the board of members in a company,in SIRC through the fatwa committee.Therefore,this study suggests that the extent and quality of disclosure depends on the demand from the regulators,auditors,and funders.The findings suggest that SIRC should have an incentive to provide more information to satisfy various stakeholders’needs.Future studies can be carried out to suggest a set of disclosure items that should be disclosed in the SIRC annual reports in order to increase the level of disclosure,discharging their accountability.展开更多
This paper deals with the problem of devastation of cultural heritage by the Islamic State.The great emphasis is put on distinguishing reasons and aims of such behaviours and devastation performed on the ancient Mesop...This paper deals with the problem of devastation of cultural heritage by the Islamic State.The great emphasis is put on distinguishing reasons and aims of such behaviours and devastation performed on the ancient Mesopotamian artefacts,monuments,and artistic relics of the past civilization.The focus was put on Akkadian,Assyrian,and Sumerian heirloom due to its immense impact on the consecutive cultures of the region,neighbouring lands,and several distant societies.Problem of destruction is presented alongside with the short history of the Islamic State group emergence and its characteristics.Furthermore,this paper recalls the UNESCO definition of the term“cultural heritage”.展开更多
In this paper we aim to address,through an innovative neuroscientific view,a significant recruitment strategy implemented by ISIS targeting individuals with disabilities.The use of strategies that reinforce empathy an...In this paper we aim to address,through an innovative neuroscientific view,a significant recruitment strategy implemented by ISIS targeting individuals with disabilities.The use of strategies that reinforce empathy and the encouragement of the belief that one is capable of achieving a given goal,are strategically effective messages in terms of recruitment.Self-efficacy,which is the set of beliefs the individual holds about his or her own abilities,is another tool used to effectively recruit someone with a disability.The use of media messages also reinforces the“know how”and the feeling of“being”,that is,recognizing oneself in rewarding values.In analyzing the Entertainment-Education method,we identified some elements of persuasive storytelling that even in people with disabilities has led to success in terms of recruitment.An innovative multidisciplinary contrast activity with the contribution of neuroscience may therefore be effective in identifying behaviors and recruitment strategies that are effective with people with disabilities.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
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
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
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
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
基金supported by the Major Project for the Integration of ScienceEducation and Industry (Grant No.2025ZDZX02)。
文摘Classical computation of electronic properties in large-scale materials remains challenging.Quantum computation has the potential to offer advantages in memory footprint and computational scaling.However,general and viable quantum algorithms for simulating large-scale materials are still limited.We propose and implement random-state quantum algorithms to calculate electronic-structure properties of real materials.Using a random state circuit on a small number of qubits,we employ real-time evolution with first-order Trotter decomposition and Hadamard test to obtain electronic density of states,and we develop a modified quantum phase estimation algorithm to calculate real-space local density of states via direct quantum measurements.Furthermore,we validate these algorithms by numerically computing the density of states and spatial distributions of electronic states in graphene,twisted bilayer graphene quasicrystals,and fractal lattices,covering system sizes from hundreds to thousands of atoms.Our results manifest that the random-state quantum algorithms provide a general and qubit-efficient route to scalable simulations of electronic properties in large-scale periodic and aperiodic materials.
基金supported by the Natural Science Basic Research Program of Shaanxi Province (Grant Nos.2024JC-JCQN-06 and2025JC-QYCX-006)the National Natural Science Foundation of China (Grant No.12474337)Chinese Academy of Sciences Project (Grant Nos.E4BA270100,E4Z127010F,E4Z6270100,and E53327020D)。
文摘In conventional higher-order topological insulators(HOTIs),the emergence of topological states can be explained by using the nonzero bulk polarization index.However,corner states emerge in HOTIs with incomplete boundary unit cells(i.e.,boundary defects)even though the bulk polarization is zero,which challenges the conventional understanding of HOTIs.Here,based on a Kekul´e-distorted honeycomb lattice with incomplete unit cells,we reveal that incomplete unit cells exhibit fractional charges through the analysis of Wannier centers by developing a compensation method and creating the concept of Wannier center domain(WCD)which is the smallest region that one Wannier center occupies.This method compensates for the missing parts of these boundary incomplete unit cells with additional WCDs to make them complete.The compensated WCDs automatically carry the corresponding charge,and this charge together with that of the incomplete unit cell constitutes the total charge of the complete unit cell after compensation.We conclude that the emergence of corner states is attributed to the filling anomaly,which is a fundamental mechanism.Our results refresh the understanding of HOTIs,especially those with structural discontinuities,and provide a novel design for topological states which have application value in producing optical functional devices.
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 China National Nuclear Corporation Basic Research Project(Grant No.CNNC-JCYJ-202327)。
文摘The development of collinear resonance ionization spectroscopy for studying the nuclear structure of nickel isotopes far from the stability line relies on high-efficiency two-color two-step photoionization pathways.We systematically investigated the even-parity autoionization spectrum of atomic nickel through resonance ionization mass spectrometry(RIMS).Fifteen intense single-color photoionization lines and corresponding transitions in the 300-325 nm range were identified and excluded as potential interference peaks for subsequent two-color studies.Fifty-one even-parity autoionization states in the 64000-66800 cm^(-1)range were identified for the first time by scanning from five intermediate excited states of the3d^(8)(^(3)F)4s4p(^(3)P^(o))configuration.Forty-eight of these states were assigned unique total angular momentum quantum numbers(J)based on electric dipole transition selection rules.The autoionization state at 64437.77 cm^(-1)was identified as an optimal final state for enhancing photoionization efficiency in two-color two-step pathways.This study provides comprehensive datasets of even-parity autoionization states of nickel,supporting both the advancement of collinear resonance ionization spectroscopy for exotic nickel isotopes and theoretical modeling of autoionization states.The datasets are openly available at https://doi.org/10.57760/sciencedb.j00113.00280.
基金Project supported by the National Natural Science Foundation of China(Grant No.61573266)the Natural Science Basic Research Program of Shaanxi(Grant No.2021JM-133)the Fundamental Research Funds for the Central Universities and the Innovation Fund of Xidian University(Grant No.YJSJ25009)。
文摘Efficient implementation of fundamental matrix operations on quantum computers,such as matrix products and Hadamard operations,holds significant potential for accelerating machine learning algorithms.A critical prerequisite for quantum implementations is the effective encoding of classical data into quantum states.We propose two quantum computing frameworks for preparing the distinct encoded states corresponding to matrix operations,including the matrix product,matrix sum,matrix Hadamard product and division.Quantum algorithms based on the digital encoding computing framework are capable of implementing the matrix Hadamard operation with a time complexity of O(poly log(mn/ε))and the matrix product with a time complexity of O(poly log(mnl/ε)),achieving an exponential speedup in contrast to the classical methods of O(mn)and O(mnl).Quantum algorithms based on the analog-encoding framework are capable of implementing the matrix Hadamard operation with a time complexity of O(k_(1)√mn·poly log(mn/ε))and the matrix product with a time complexity of O(k_(2)√1·poly log(mnl/ε)),where k_(1)and k_(2)are coefficients correlated with the elements of the matrix,achieving a square speedup in contrast to the classical counterparts.As applications,we construct an oracle that can access the trace of a matrix within logarithmic time,and propose several algorithms to respectively estimate the trace of a matrix,the trace of the product of two matrices,and the trace inner product of two matrices within logarithmic time.
文摘BACKGROUND The prevalence of negative emotional states,such as anxiety and depression,has increased annually.Although personal habits are known to influence emotional regulation,the precise mechanisms underlying this relationship remain unclear.AIM To investigate emotion regulation habits impact on students negative emotions during lockdown,using the coronavirus disease 2019 pandemic as a case example.METHODS During the coronavirus disease 2019 lockdown,an online cross-sectional survey was conducted at a Chinese university.Emotional states were assessed using the Depression,Anxiety,and Stress Scale-21(DASS-21),while demographic data and emotion regulation habits were collected concurrently.Data analysis was performed using SPSS version 27.0 and includedχ^(2)-tests for intergroup comparisons,Spearman’s rank-order correlation coefficient analysis to examine associations,and stepwise linear regression modeling to explore the relationships between emotion regulation habits and emotional states.Statistical significance was set atα=0.05.RESULTS Among the 494 valid questionnaires analyzed,the prevalence rates of negative emotional states were as follows:Depression(65.0%),anxiety(69.4%),and stress(50.8%).DASS-21 scores(mean±SD)demonstrated significant symptomatology:Total(48.77±34.88),depression(16.21±12.18),anxiety(14.90±11.91),and stress(17.64±12.07).Significant positive intercorrelations were observed among all DASS-21 subscales(P<0.01).Regression analysis identified key predictors of negative emotions(P<0.05):Risk factors included late-night frequency and academic pressure,while protective factors were the frequency of parental contact and the number of same-gender friends.Additionally,compensatory spending and binge eating positively predicted all negative emotion scores(β>0,P<0.01),whereas appropriate recreational activities negatively predicted these scores(β<0,P<0.01).CONCLUSION High negative emotion prevalence occurred among confined students.Recreational activities were protective,while compensatory spending and binge eating were risk factors,necessitating guided emotion regulation.
基金Fu-Zhou Chen for helpful discussions.The work is partly supported by the National Key Research and Development Program of China(Grant No.2022YFA1402704)the National Natural Science Foundation of China(Grant No.12247101)。
文摘The development of novel quantum many-body computational algorithms relies on robust benchmarking.However,generating such benchmarks is often hindered by the massive computational resources required for exact diagonalization or quantum Monte Carlo simulations,particularly at finite temperatures.In this work,we propose a new algorithm for obtaining thermal pure quantum states,which allows efficient computation of both mechanical and thermodynamic properties at finite temperatures.We implement this algorithm in our open-source C++template library,Physica.Combining the improved algorithm with state-of-the-art software engineering,our implementation achieves high performance and numerical stability.As an example,we demonstrate that for the 4×4 Hubbard model,our method runs approximately 10~3times faster than HΦ3.5.2.Moreover,the accessible temperature range is extended down toβ=32 across arbitrary doping levels.These advances significantly push forward the frontiers of benchmarking for quantum many-body systems.
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 Natural Science Foundation of China(Grant Nos.12222413,12174443,12274459,and 12404266)the National Key R&D Program of China(Grant Nos.2023YFA1406500,2022YFA1403800,and 2022YFA1403103)+3 种基金the Natural Science Foundation of Shanghai (Grant No.23ZR1482200)the Natural Science Foundation of Ningbo (Grant No.2024J019)the Science Research Project of Hebei Education Department (Grant No.BJ2025060)the funding of Ningbo Yongjiang Talent Program。
文摘Superconducting elect rides have attracted growing attention for their potential to achieve high superconducting transition temperatures(T_(C))under pressure.However,many known elect rides are chemically reactive and unstable,making high-quality single-crystal growth,characterization,and measurements difficult,and most do not exhibit superconductivity at ambient pressure.In contrast,La_(3) In stands out for its ambient-pressure superconductivity(T_(C)∼9.4 K)and the availability of high-quality single crystals.Here,we investigate its low-energy electronic structure using angle-resolved photoemission spectroscopy and first-principles calculations.The bands near the Fermi energy(E_(F))are mainly derived from La 5d and In 5p orbitals.A saddle point is directly observed at the Brillouin zone(BZ)boundary,while a three-dimensional Van Hove singularity crosses E_(F) at the BZ corner.First-principles calculations further reveal topological Dirac surface states within the bulk energy gap above E_(F).The coexistence of a high density of states and in-gap topological surface states near𝐸F suggests that La3In offers a promising platform for tuning superconductivity and exploring possible topological superconducting phases through doping or external pressure.
基金supported by the Strategic Priority Research Program of Chinese Academy of Sciences (Grant Nos.XDB28000000 and XDB0460000)the Quantum Science and Technology-National Science and Technology Major Project (Grant No.2021ZD0302600)the National Key Research and Development Program of China(Grant No.2024YFA1409002)。
文摘The hybridization gap in strained-layer InAs/In_(x)Ga_(1−x) Sb quantum spin Hall insulators(QSHIs)is significantly enhanced compared to binary InAs/GaSb QSHI structures,where the typical indium composition,x,ranges between 0.2 and 0.4.This enhancement prompts a critical question:to what extent can quantum wells(QWs)be strained while still preserving the fundamental QSHI phase?In this study,we demonstrate the controlled molecular beam epitaxial growth of highly strained-layer QWs with an indium composition of x=0.5.These structures possess a substantial compressive strain within the In_(0.5)Ga_(0.5)Sb QW.Detailed crystal structure analyses confirm the exceptional quality of the resulting epitaxial films,indicating coherent lattice structures and the absence of visible dislocations.Transport measurements further reveal that the QSHI phase in InAs/In_(0.5)Ga_(0.5)Sb QWs is robust and protected by time-reversal symmetry.Notably,the edge states in these systems exhibit giant magnetoresistance when subjected to a modest perpendicular magnetic field.This behavior is in agreement with the𝑍2 topological property predicted by the Bernevig–Hughes–Zhang model,confirming the preservation of topologically protected edge transport in the presence of enhanced bulk strain.
文摘This paper aims to identify factors that influence the expectations of a wide range of stakeholders on the information disclosure in the Malaysian State Islamic Religious Councils(SIRC)annual reports,employing semi-structured interviews.The majority of interviewees perceived accounting standards as the main factor contributing to their expectations and further influenced the reporting practices among accountants in SIRC.Others are state fatwa(Islamic rulings),audit expectations,and individual perceptions.The result of the interviews revealed that on the top of accounting standards and government guidelines on the reporting for all government agencies,SIRC should take into account their greater accountability,which should be reflected in their reporting practices.Therefore,Islamic accountability through fatwa,audit expectations,and public demands could be considered.Such awareness is important in SIRC,to differentiate them from other government agencies.The existence of governance is similar to the board of members in a company,in SIRC through the fatwa committee.Therefore,this study suggests that the extent and quality of disclosure depends on the demand from the regulators,auditors,and funders.The findings suggest that SIRC should have an incentive to provide more information to satisfy various stakeholders’needs.Future studies can be carried out to suggest a set of disclosure items that should be disclosed in the SIRC annual reports in order to increase the level of disclosure,discharging their accountability.
文摘This paper deals with the problem of devastation of cultural heritage by the Islamic State.The great emphasis is put on distinguishing reasons and aims of such behaviours and devastation performed on the ancient Mesopotamian artefacts,monuments,and artistic relics of the past civilization.The focus was put on Akkadian,Assyrian,and Sumerian heirloom due to its immense impact on the consecutive cultures of the region,neighbouring lands,and several distant societies.Problem of destruction is presented alongside with the short history of the Islamic State group emergence and its characteristics.Furthermore,this paper recalls the UNESCO definition of the term“cultural heritage”.
文摘In this paper we aim to address,through an innovative neuroscientific view,a significant recruitment strategy implemented by ISIS targeting individuals with disabilities.The use of strategies that reinforce empathy and the encouragement of the belief that one is capable of achieving a given goal,are strategically effective messages in terms of recruitment.Self-efficacy,which is the set of beliefs the individual holds about his or her own abilities,is another tool used to effectively recruit someone with a disability.The use of media messages also reinforces the“know how”and the feeling of“being”,that is,recognizing oneself in rewarding values.In analyzing the Entertainment-Education method,we identified some elements of persuasive storytelling that even in people with disabilities has led to success in terms of recruitment.An innovative multidisciplinary contrast activity with the contribution of neuroscience may therefore be effective in identifying behaviors and recruitment strategies that are effective with people with disabilities.
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.
