It is known that correlation does not imply causality.Some relationships identified in the analysis of data are coincidental or unknown,and some are produced by real-world causality of the situation,which is problemat...It is known that correlation does not imply causality.Some relationships identified in the analysis of data are coincidental or unknown,and some are produced by real-world causality of the situation,which is problematic,since there is a need to differentiate between these two scenarios.Until recently,the proper−semantic−causality of the relationship could have been determined only by human experts from the area of expertise of the studied data.This has changed with the advance of large language models,which are often utilized as surrogates for such human experts,making the process automated and readily available to all data analysts.This motivates the main objective of this work,which is to introduce the design and implementation of a large language model-based semantic causality evaluator based on correlation analysis,together with its visual analysis model called Causal heatmap.After the implementation itself,the model is evaluated from the point of view of the quality of the visual model,from the point of view of the quality of causal evaluation based on large language models,and from the point of view of comparative analysis,while the results reached in the study highlight the usability of large language models in the task and the potential of the proposed approach in the analysis of unknown datasets.The results of the experimental evaluation demonstrate the usefulness of the Causal heatmap method,supported by the evident highlighting of interesting relationships,while suppressing irrelevant ones.展开更多
The respiratory-circulatory system, including organs such as the nose, pharynx, larynx, trachea, bronchi, and heart, is an organic community responsible for ventilation and gas exchange. The integrity of its anatomica...The respiratory-circulatory system, including organs such as the nose, pharynx, larynx, trachea, bronchi, and heart, is an organic community responsible for ventilation and gas exchange. The integrity of its anatomical structure directly affects the evolution of pathological processes, and the analysis of their correlation is a core entry point for clinical disease diagnosis, treatment, and mechanism research. Based on this, this paper mainly explores the correlation between the anatomical and pathological characteristics of the respiratory-circulatory system, aiming to provide anatomical and pathological theoretical support for clinical accurate diagnosis, targeted therapy, and prognosis evaluation.展开更多
Objective: To understand the current status of peer caring behavior and empathy among undergraduate nursing students and to explore the relationship between the two. Method: Using the convenience sampling method, a qu...Objective: To understand the current status of peer caring behavior and empathy among undergraduate nursing students and to explore the relationship between the two. Method: Using the convenience sampling method, a questionnaire survey was conducted among 292 nursing students from a medical college in Jiangxi Province, using the Peer Caring Behavior Scale and the Jefferson Scale of Empathy. Results: The score for peer caring behavior among undergraduate nursing students was 85.00 (78.00-92.00), and the score for empathy was 101.00 (92.00-110.00). A positive correlation was found between the two (r = 0.362, p < 0.05). Conclusion: The level of peer caring behavior among undergraduate nursing students is above average, while their empathy level is moderate, with a positive correlation between the two. This suggests that nursing educators should strengthen the development of peer caring behavior, which may help enhance the empathy of undergraduate nursing students.展开更多
The Kagome metal CsV3Sb5 transitions from a weakly correlated state to a strongly correlated state upon Cr substitution;however,the mechanism driving this enhancement remains an open question.Here,we employed a combin...The Kagome metal CsV3Sb5 transitions from a weakly correlated state to a strongly correlated state upon Cr substitution;however,the mechanism driving this enhancement remains an open question.Here,we employed a combination of density functional theory and dynamical mean-field theory(DFT+DMFT)to systematically investigate the evolution of electronic correlations in the CsV_(3−x)Cr_(x)Sb_(5)(x=0,1,and 3)series.Our calculations revealed that Cr doping drives the system into a strongly correlated Hund’s metal phase,which is characterized by significant and orbital-dependent enhancements in the quasiparticle effective masses and electronic scattering rates.We trace the origin of this transition to the doping-induced shift from low-to high-spin atomic configurations.This preference for high-spin states,which is promoted by near-half-filling of the Cr-d orbitals,induces a pronounced orbital blocking effect that strengthens the correlations.Our findings establish that Hund’s coupling is the decisive factor governing the rich correlation physics in the CsV_(3−x)Cr_(x)Sb_(5) family,providing a tunable platform for exploring Hund’s metallicity.展开更多
BACKGROUND Anxiety,depression,and other negative emotions are common among patients with chronic renal failure(CRF).Analyzing the factors related to negative emotions is necessary to provide targeted nursing care.AIM ...BACKGROUND Anxiety,depression,and other negative emotions are common among patients with chronic renal failure(CRF).Analyzing the factors related to negative emotions is necessary to provide targeted nursing care.AIM To explore the correlations among life satisfaction,pleasure levels,and negative emotions in patients with CRF.METHODS One hundred patients with CRF who received therapy at the First Affiliated Hospital of Jinzhou Medical University between December 2022 and February 2025 were included.The Depression,Anxiety,and Stress Scale(DASS-21),Satisfaction with Life Scale(SWLS),and Temporal Experience of Pleasure Scale(TEPS)were used to evaluate negative emotions,life satisfaction,and pleasure level,respectively.Pearson’s correlation coefficient analyzed the correlation between life satisfaction,pleasure level,and negative emotions.Linear regression analysis identified the factors affecting negative emotions.RESULTS The average DASS-21 score among patients with CRF was 51.90±2.30,with subscale scores of 17.90±1.50 for depression,18.53±1.18 for anxiety,and 15.47±2.36 for stress,all significantly higher than the domestic norm(P<0.05).The average SWLS score was 22.17±4.90.Correlation analysis revealed a negative correlation between the SWLS and total DASS-21 scores(P<0.05),but not with the individual depression,anxiety,or stress dimensions.The average TEPS score was 67.80±8.34.TEPS scores were negatively correlated with the DASS-21 score and the stress dimension(P<0.05),but not with depression or anxiety.Linear regression analysis showed that TEPS scores significantly influenced DASS-21 scores(P<0.05).CONCLUSION Patients with CRF experience high levels of negative emotions,which are negatively correlated with life satisfaction and pleasure.Furthermore,pleasure level had an impact on negative emotions.展开更多
We investigate numerically the effects of long-range temporal and spatial correlations based on the rescaled distributions of the squared interface width W^(2)(L, t) and the interface height h(x, t)in the(1+1)-dimensi...We investigate numerically the effects of long-range temporal and spatial correlations based on the rescaled distributions of the squared interface width W^(2)(L, t) and the interface height h(x, t)in the(1+1)-dimensional Kardar-Parisi-Zhang(KPZ) growth system within the early growth regime. Through extensive numerical simulations, we find that long-range temporally correlated noise does not significantly impact the distribution form of the interface width. Generally,W^(2)(L, t) approximately obeys a lognormal distribution when the temporal correlation exponentθ ≥0. On the other hand, the effects of long-range spatially correlated noise are evidently different from the temporally correlated case. Our results show that, when the spatial correlation exponent ρ ≤ 0.20, the distribution forms of W^(2)(L, t) approach the lognormal distribution, and when ρ > 0.20, the distribution becomes more asymmetric, steep, and fat-tailed, and tends to an unknown distribution form. As a comparison, probability distributions of the interface height are also provided in the temporally and spatially correlated KPZ system, exhibiting quite different characteristics from each other within the whole correlated strengths. For the temporal correlation, the height distributions follow Tracy-Widom Gaussian orthogonal ensemble(TW-GOE) when θ → 0, and with increasing θ, the height distributions crossover continuously to an unknown distribution. However, for the spatial correlation, the height distributions gradually transition from the TW-GOE distribution to the standard Gaussian form.展开更多
In multi-orbital systems,the correlation strength is typically attributed to Coulomb interactions and Hund's couplings.However,this study demonstrates that on-site inter-orbital hybridization can also significant ...In multi-orbital systems,the correlation strength is typically attributed to Coulomb interactions and Hund's couplings.However,this study demonstrates that on-site inter-orbital hybridization can also significant influence the correlation strength of the system.We investigate the impact of on-site inter-orbital hybridization on the correlation strength of a two-orbital Hubbard model on a square lattice using the dynamical mean-field theory combined with Lanczos exact diagonalization.Our findings reveal a distinct Janus effect:on-site inter-orbital hybridization enhances correlation strength in the non-half-filled regime while suppresses it at half-filling.This dual role of on-site inter-orbital hybridization provides a fundamental mechanism for tuning the strength of correlations in multi-orbital systems.展开更多
Programmable two-particle quantum walks are crucial for advancing quantum simulation,computation,and information processing.Although disorder is traditionally associated with information loss,it can also facilitate em...Programmable two-particle quantum walks are crucial for advancing quantum simulation,computation,and information processing.Although disorder is traditionally associated with information loss,it can also facilitate emergent phenomena such as enhanced energy transport.Here,we experimentally realize a 12-step discrete-time quantum walk in programmable integrated photonic circuits,introducing tunable static and dynamic disorder to explore quantum transport dynamics.In periodic lattices,disorder induces light localization and drives a transition from quantum ballistic to classical diffusive behavior.In particular,quantum walks of correlated photons exhibit a disorder-induced bunching effect,accompanied by enhanced nonclassical correlations.Our platform provides a scalable framework for investigating multiparticle quantum dynamics in engineered environments,promoting the development of quantum optics toward large-scale applications.展开更多
The energy correlations of prompt fission neutrons have not yet been considered in the related coincidence and multiplication measurement techniques.To measure and verify the energy correlations,an experiment was perf...The energy correlations of prompt fission neutrons have not yet been considered in the related coincidence and multiplication measurement techniques.To measure and verify the energy correlations,an experiment was performed with a total measurement duration of approximately 1200 h.In the experiment,eight CLYC detectors and sixteen EJ309 liquid scintillation detectors were utilized,and the fission moment was tagged with the measured fissionγ-rays.The relative ratios of the energy spectra of the neutrons correlated with different energy neutrons to the^(252)Cf fission neutron energy spectra were obtained.The present results may be helpful for studying fission physics and nuclear technology applications.展开更多
When two layers of graphene are stacked with a twist angle of approximately 1.1°,strong interlayer coupling gives rise to a pair of flat bands in twisted bilayer graphene(TBG),resulting in pronounced electron–el...When two layers of graphene are stacked with a twist angle of approximately 1.1°,strong interlayer coupling gives rise to a pair of flat bands in twisted bilayer graphene(TBG),resulting in pronounced electron–electron interactions.At half filling of the flat bands,TBG exhibits correlated insulating states.Here,we investigate the electrical transport properties of heterostructures composed of TBG and the antiferromagnetic insulator chromium oxychloride(CrOCl),and propose a strategy to modulate the correlated insulating states in TBG.During the transition from a conventional phase to a strong interfacial coupling phase,kink-like features are observed in the charge neutrality point(CNP),correlated insulating state,and band insulating state.Under a perpendicular magnetic field,the system exhibits broadened quantum Hall plateaus in the strong interfacial coupling regime.Electrons localized in the CrOCl layer screen the bottom gate,rendering the carrier density in TBG less sensitive to variations in the bottom gate voltage.These phenomena are well captured by a charge-transfer model between TBG and CrOCl.Our results provide insights into the control of electronic correlations and topological states in graphene moirésystems via interfacial charge coupling.展开更多
The octupole correlations of the K^(π)=5/2^(+)ground state and the rotational spectrum built on it in^(229)Th are studied using the microscopic relativistic density functional theory on a three-dimensional lattice sp...The octupole correlations of the K^(π)=5/2^(+)ground state and the rotational spectrum built on it in^(229)Th are studied using the microscopic relativistic density functional theory on a three-dimensional lattice space and the reflection-asymmetric triaxial particle rotor model.It is found that^(229)Th has a ground state with static axial octupole and quadrupole deformations.The occurrence of octupole correlations,driven by the octupole deformation,is analyzed through the evolution of single-particle levels around the Fermi surface.The experimental energy spectrum and the electromagnetic transition probabilities,including B(E2)and B(M1),are reasonably well reproduced.展开更多
An important feature of quantum chromodynamics(QCD)is that the strong force grows as the distance between partons increases,which confines partons into hadrons,commonly known as QCD confinement.Perturbative QCD(pQCD)d...An important feature of quantum chromodynamics(QCD)is that the strong force grows as the distance between partons increases,which confines partons into hadrons,commonly known as QCD confinement.Perturbative QCD(pQCD)does not work at large distance,such as the length scale of a hadron,which is the regime of non-perturbative QCD.The detailed QCD mechanisms through which confinement occurs from partons to hadrons(usually known as hadronization),and how it manifests itself in partonic structure of hadrons(usually known as parton distribution),remain unresolved puzzles of first-principle QCD calculations.展开更多
Ironmaking process(IP)is indispensable to modern iron and steel industry,where real-time monitoring is crucial for achieving high molten iron quality(MIQ)with low energy consumption.While neural network-based models s...Ironmaking process(IP)is indispensable to modern iron and steel industry,where real-time monitoring is crucial for achieving high molten iron quality(MIQ)with low energy consumption.While neural network-based models show some promising results,they are generally limited by non-negligible drawbacks such as interpretability issues of feature learning.To address these issues,we propose a novel concept based on the shallow-to-deep correlation network representation regression(Sh-to-De CNRR).Our approach,shallow correlation network representation regression(ShCNRR),combines neural network and canonical correlation analysis thoughts to generate explainable features via shallow correlation network representation(CNR).A twin inverse network is then derived to obtain the explicit model output,leveraging the shallow CNR.To capture deeper nonlinear information,we extend ShCNRR into a hierarchical deep correlation network representation regression(DeCNRR)model that features stacked neural networks,enabling us to learn deeper CNR from process data.The feasibility and advantages of our proposals are validated by theoretical derivations and practical IP cases,which contain one MIQ regression and three MIQ-related fault detection tasks.The results reveal that highly fused statistical and neural network models yield superior monitoring performance compared to current state-of-the-art models,while statistical tests verify the convincing feature mining.展开更多
Understanding the properties of warm dense hydrogen is of key importance for the modeling of compact astrophysical objects and to understand and further optimize inertial confinement fusion applications.The workhorse ...Understanding the properties of warm dense hydrogen is of key importance for the modeling of compact astrophysical objects and to understand and further optimize inertial confinement fusion applications.The workhorse of warm dense matter theory is thermal density functional theory(DFT),which,however,suffers from two limitations:(i)its accuracy can depend on the utilized exchange-correlation functional,which has to be approximated,and(ii)it is generally limited to single-electron properties such as the density distribution.Here,we present a new ansatz combining time-dependent DFT results for the dynamic structure factor S_(ee)(q,ω)with static DFT results for the density response.This allows us to estimate the electron-electron static structure factor S_(ee)(q)of warm dense hydrogen with high accuracy over a broad range of densities and temperatures.In addition to its value for the study of warm dense matter,our work opens up new avenues for the future study of electronic correlations exclusively within the framework of DFT for a host of applications.展开更多
Identifying inter-frame forgery is a hot topic in video forensics. In this paper, we propose a method based on the assumption that the correlation coefficients of gray values is consistent in an original video, while ...Identifying inter-frame forgery is a hot topic in video forensics. In this paper, we propose a method based on the assumption that the correlation coefficients of gray values is consistent in an original video, while in forgeries the consistency will be destroyed. We first extract the consistency of correlation coefficients of gray values (CCCoGV for short) after normalization and quantization as distinguishing feature to identify interframe forgeries. Then we test the CCCoGV in a large database with the help of SVM (Support Vector Machine). Experimental results show that the proposed method is efficient in classifying original videos and forgeries. Furthermore, the proposed method performs also pretty well in classifying frame insertion and frame deletion forgeries.展开更多
Video snapshot compressive imaging(Video SCI) modulates scenes using various encoding masks and captures compressed measurements with a low-speed camera during a single exposure. Subsequently, reconstruction algorithm...Video snapshot compressive imaging(Video SCI) modulates scenes using various encoding masks and captures compressed measurements with a low-speed camera during a single exposure. Subsequently, reconstruction algorithms restore image sequences of dynamic scenes, offering advantages such as reduced bandwidth and storage space requirements. The temporal correlation in video data is crucial for Video SCI, as it leverages the temporal relationships among frames to enhance the efficiency and quality of reconstruction algorithms, particularly for fast-moving objects.This paper discretizes video frames to create image datasets with the same data volume but differing temporal correlations. We utilized the state-of-the-art(SOTA) reconstruction framework, EfficientSCI++, to train various compressed reconstruction models with these differing temporal correlations. Evaluating the reconstruction results from these models, our simulation experiments confirm that a reduction in temporal correlation leads to decreased reconstruction accuracy. Additionally, we simulated the reconstruction outcomes of datasets devoid of temporal correlation, illustrating that models trained on non-temporal data affect the temporal feature extraction capabilities of transformers, resulting in negligible impacts on the evaluation of reconstruction results for non-temporal correlation test datasets.展开更多
Ten physical and environmental variables collected from an on-the-go soil sensor at two field sites (MF3E and MF11S) in Mississippi, USA, were analyzed to assess soil variability and the interrelationships among the m...Ten physical and environmental variables collected from an on-the-go soil sensor at two field sites (MF3E and MF11S) in Mississippi, USA, were analyzed to assess soil variability and the interrelationships among the measurements. At MF3E, moderate variability was observed in apparent electrical conductivity shallow (ECas), slope, and ECa ratio measurements, with coefficients of variation ranging from 20% to 27%. In contrast, MF11S exhibited higher variability, particularly in ECas and ECad (deep) measurements, which exceeded 30% in their coefficient of variation values, indicating significant differences in soil composition and moisture content. Correlation analysis revealed strong positive relationships between the near-infrared-to-red ratio and red reflectance (r = 0.897***) soil values at MF3E. MF11S demonstrated a strong negative correlation between ECas and ECad readings with the x-coordinate (r ***). Scatter plots and fitted models illustrated the complexity of relationships, with many showing nonlinear trends. These findings emphasize the need for continuous monitoring and advanced modeling to understand the dynamic nature of soil properties and their implications for agricultural practices. Future research should explore the underlying mechanisms driving variability in the soil characteristics to enhance soil management strategies at the study sites.展开更多
By introducing noncanonical vortex pairs to partially coherent beams, spatial correlation singularity (SCS) and orbital angular momenta (OAM) of the resulting beams are studied using the Fraunhofer diffraction integra...By introducing noncanonical vortex pairs to partially coherent beams, spatial correlation singularity (SCS) and orbital angular momenta (OAM) of the resulting beams are studied using the Fraunhofer diffraction integral. The effect of noncanonical strength, off-axis distance and vortex sign on spatial correlation singularities in far field is stressed. Furthermore, far-field OAM spectra and densities are also investigated, and the OAM detection and crosstalk probabilities are discussed. The results show that the number of dislocations of SCS always equals the sum of absolute values of topological charges for canonical or noncanonical vortex pairs. Although the sum of the product of each OAM mode and its power weight equals the algebraic sum of topological charges for canonical vortex pairs, the relationship no longer holds in the noncanonical case except for opposite-charge vortex pairs. The changes of off-axis distance, noncanonical strength or coherence length can lead to a more dominant power in adjacent mode than that in center detection mode, which also indicates that crosstalk probabilities of adjacent modes exceed the center detection probability. This work may provide potential applications in OAM-based optical communication, imaging, sensing and computing.展开更多
Since antiquity,humans have been involved in designing materials through alloying strategies to meet the ever-growing technological demands.In 2004,this endeavor witnessed a significant breakthrough with the discovery...Since antiquity,humans have been involved in designing materials through alloying strategies to meet the ever-growing technological demands.In 2004,this endeavor witnessed a significant breakthrough with the discovery of high-entropy alloys(HEAs)comprising multi-principal elements.Owing to the four“core-effects”,these alloys exhibit exceptional properties including better structural stability,high strength and ductility,improved fatigue/fracture toughness,high corrosion and oxidation resistance,superconductiv-ity,magnetic properties,and good thermal properties.Different synthesis routes have been designed and used to meet the properties of interest for particular applications with varying dimensions.How-ever,HEAs are providing new opportunities and challenges for computational modelling of the complex structure-property correlations and in predictions of phase stability necessary for optimum performance of the alloy.Several attempts have been made to understand these alloys by empirical and computa-tional models,and data-driven approaches to accelerate the materials discovery with a desired set of properties.The present review discusses advances and inferences from simulations and models spanning multiple length and time scales explaining a comprehensive set of structure-properties relations.Addi-tionally,the role of machine learning approaches is also reviewed,underscoring the transformative role of computational modelling in unravelling the multifaceted properties and applications of HEAs,and the scope for future efforts in this direction.展开更多
Geomagnetic observatory data are crucial for all branches of geophysics because they can contribute to earthquake research by detecting anomalies in the Earth’s magnetic field.Recently,data records from the Misallat(...Geomagnetic observatory data are crucial for all branches of geophysics because they can contribute to earthquake research by detecting anomalies in the Earth’s magnetic field.Recently,data records from the Misallat(MLT)and Abu Simbel(ABS)Egyptian geomagnetic observatories were processed and found to be of good quality.In this study,Egyptian observatory data were tested during both quiet and disturbed events and compared with data from INTERMAGNET observatories worldwide at different latitudes and within a narrow range of longitudes in both hemispheres.This study investigated the relationships between magnetic field components from Egyptian observatories and those from INTERMAGNET observatories using graphical representations of the X components;Pearson’s correlation for the X,Y,Z,and F components;cross-correlation for the X component;and wavelet coherence for the F component.The results of this study showed a high correlation between Egyptian observatories and all utilized INTERMAGNET stations,except those located at high latitudes,during both quiet and disturbed events.Additionally,the study confirmed the observed consistency between Egyptian observatories and selected INTERMAGNET stations.Therefore,Egyptian observatories can feasibly fill the gap in the Middle East and North Africa.展开更多
基金supported by University Grant Agency of Matej Bel University in Banská Bystrica project number UGA-14-PDS-2025.
文摘It is known that correlation does not imply causality.Some relationships identified in the analysis of data are coincidental or unknown,and some are produced by real-world causality of the situation,which is problematic,since there is a need to differentiate between these two scenarios.Until recently,the proper−semantic−causality of the relationship could have been determined only by human experts from the area of expertise of the studied data.This has changed with the advance of large language models,which are often utilized as surrogates for such human experts,making the process automated and readily available to all data analysts.This motivates the main objective of this work,which is to introduce the design and implementation of a large language model-based semantic causality evaluator based on correlation analysis,together with its visual analysis model called Causal heatmap.After the implementation itself,the model is evaluated from the point of view of the quality of the visual model,from the point of view of the quality of causal evaluation based on large language models,and from the point of view of comparative analysis,while the results reached in the study highlight the usability of large language models in the task and the potential of the proposed approach in the analysis of unknown datasets.The results of the experimental evaluation demonstrate the usefulness of the Causal heatmap method,supported by the evident highlighting of interesting relationships,while suppressing irrelevant ones.
文摘The respiratory-circulatory system, including organs such as the nose, pharynx, larynx, trachea, bronchi, and heart, is an organic community responsible for ventilation and gas exchange. The integrity of its anatomical structure directly affects the evolution of pathological processes, and the analysis of their correlation is a core entry point for clinical disease diagnosis, treatment, and mechanism research. Based on this, this paper mainly explores the correlation between the anatomical and pathological characteristics of the respiratory-circulatory system, aiming to provide anatomical and pathological theoretical support for clinical accurate diagnosis, targeted therapy, and prognosis evaluation.
基金2024 University-level Research Project of Fuzhou Medical College,Fuzhou Medical College of Nanchang University(Project No.:fykj202406)。
文摘Objective: To understand the current status of peer caring behavior and empathy among undergraduate nursing students and to explore the relationship between the two. Method: Using the convenience sampling method, a questionnaire survey was conducted among 292 nursing students from a medical college in Jiangxi Province, using the Peer Caring Behavior Scale and the Jefferson Scale of Empathy. Results: The score for peer caring behavior among undergraduate nursing students was 85.00 (78.00-92.00), and the score for empathy was 101.00 (92.00-110.00). A positive correlation was found between the two (r = 0.362, p < 0.05). Conclusion: The level of peer caring behavior among undergraduate nursing students is above average, while their empathy level is moderate, with a positive correlation between the two. This suggests that nursing educators should strengthen the development of peer caring behavior, which may help enhance the empathy of undergraduate nursing students.
基金supported by the Development Program of China and the National Key Research (Grant Nos.2023YFA1406200 and 2022YFA1402304)the National Natural Science Foundation of China (Grant Nos.12274169 and 12122405)+3 种基金the Fundamental Research Funds for the Central Universitiesthe Innovation Team for Functional Materials and Devices for Informatics at Anhui Higher Education Institutes (Grant No.2024AH010024)the Natural Science Research Project of Education Department of Anhui Province (Grant No.2025AHGXZK31203)the PHD Research Startup Foundation of Fuyang Normal University (Grant No.2025KYQD0072)。
文摘The Kagome metal CsV3Sb5 transitions from a weakly correlated state to a strongly correlated state upon Cr substitution;however,the mechanism driving this enhancement remains an open question.Here,we employed a combination of density functional theory and dynamical mean-field theory(DFT+DMFT)to systematically investigate the evolution of electronic correlations in the CsV_(3−x)Cr_(x)Sb_(5)(x=0,1,and 3)series.Our calculations revealed that Cr doping drives the system into a strongly correlated Hund’s metal phase,which is characterized by significant and orbital-dependent enhancements in the quasiparticle effective masses and electronic scattering rates.We trace the origin of this transition to the doping-induced shift from low-to high-spin atomic configurations.This preference for high-spin states,which is promoted by near-half-filling of the Cr-d orbitals,induces a pronounced orbital blocking effect that strengthens the correlations.Our findings establish that Hund’s coupling is the decisive factor governing the rich correlation physics in the CsV_(3−x)Cr_(x)Sb_(5) family,providing a tunable platform for exploring Hund’s metallicity.
文摘BACKGROUND Anxiety,depression,and other negative emotions are common among patients with chronic renal failure(CRF).Analyzing the factors related to negative emotions is necessary to provide targeted nursing care.AIM To explore the correlations among life satisfaction,pleasure levels,and negative emotions in patients with CRF.METHODS One hundred patients with CRF who received therapy at the First Affiliated Hospital of Jinzhou Medical University between December 2022 and February 2025 were included.The Depression,Anxiety,and Stress Scale(DASS-21),Satisfaction with Life Scale(SWLS),and Temporal Experience of Pleasure Scale(TEPS)were used to evaluate negative emotions,life satisfaction,and pleasure level,respectively.Pearson’s correlation coefficient analyzed the correlation between life satisfaction,pleasure level,and negative emotions.Linear regression analysis identified the factors affecting negative emotions.RESULTS The average DASS-21 score among patients with CRF was 51.90±2.30,with subscale scores of 17.90±1.50 for depression,18.53±1.18 for anxiety,and 15.47±2.36 for stress,all significantly higher than the domestic norm(P<0.05).The average SWLS score was 22.17±4.90.Correlation analysis revealed a negative correlation between the SWLS and total DASS-21 scores(P<0.05),but not with the individual depression,anxiety,or stress dimensions.The average TEPS score was 67.80±8.34.TEPS scores were negatively correlated with the DASS-21 score and the stress dimension(P<0.05),but not with depression or anxiety.Linear regression analysis showed that TEPS scores significantly influenced DASS-21 scores(P<0.05).CONCLUSION Patients with CRF experience high levels of negative emotions,which are negatively correlated with life satisfaction and pleasure.Furthermore,pleasure level had an impact on negative emotions.
文摘We investigate numerically the effects of long-range temporal and spatial correlations based on the rescaled distributions of the squared interface width W^(2)(L, t) and the interface height h(x, t)in the(1+1)-dimensional Kardar-Parisi-Zhang(KPZ) growth system within the early growth regime. Through extensive numerical simulations, we find that long-range temporally correlated noise does not significantly impact the distribution form of the interface width. Generally,W^(2)(L, t) approximately obeys a lognormal distribution when the temporal correlation exponentθ ≥0. On the other hand, the effects of long-range spatially correlated noise are evidently different from the temporally correlated case. Our results show that, when the spatial correlation exponent ρ ≤ 0.20, the distribution forms of W^(2)(L, t) approach the lognormal distribution, and when ρ > 0.20, the distribution becomes more asymmetric, steep, and fat-tailed, and tends to an unknown distribution form. As a comparison, probability distributions of the interface height are also provided in the temporally and spatially correlated KPZ system, exhibiting quite different characteristics from each other within the whole correlated strengths. For the temporal correlation, the height distributions follow Tracy-Widom Gaussian orthogonal ensemble(TW-GOE) when θ → 0, and with increasing θ, the height distributions crossover continuously to an unknown distribution. However, for the spatial correlation, the height distributions gradually transition from the TW-GOE distribution to the standard Gaussian form.
基金Project supported by the National Natural Science Foundation of China(Grant No.12174327)the Natural Science Foundation of Shandong Province,China(Grant No.ZR2023ZD09)。
文摘In multi-orbital systems,the correlation strength is typically attributed to Coulomb interactions and Hund's couplings.However,this study demonstrates that on-site inter-orbital hybridization can also significant influence the correlation strength of the system.We investigate the impact of on-site inter-orbital hybridization on the correlation strength of a two-orbital Hubbard model on a square lattice using the dynamical mean-field theory combined with Lanczos exact diagonalization.Our findings reveal a distinct Janus effect:on-site inter-orbital hybridization enhances correlation strength in the non-half-filled regime while suppresses it at half-filling.This dual role of on-site inter-orbital hybridization provides a fundamental mechanism for tuning the strength of correlations in multi-orbital systems.
基金supported by the National Natural Science Foundation of China(Grant Nos.T2325022,U23A2074,12204462,62275240,62435009,12474494,and 12204468)the Chinese Academy of Sciences(CAS)Project for Young Scientists in Basic Research(Grant No.253 YSBR-049)+3 种基金the Key Research and Development Program of Anhui Province(Grant No.2022b1302007)the China Postdoctoral Science Foundation(Grant No.2024M753083)the National Postdoctoral Program for Innovative Talents(Grant No.BX20240353)the Fundamental Research Funds for the Central Universities(Grant Nos.WK2030000107,WK2030000108,and WK2030000081)。
文摘Programmable two-particle quantum walks are crucial for advancing quantum simulation,computation,and information processing.Although disorder is traditionally associated with information loss,it can also facilitate emergent phenomena such as enhanced energy transport.Here,we experimentally realize a 12-step discrete-time quantum walk in programmable integrated photonic circuits,introducing tunable static and dynamic disorder to explore quantum transport dynamics.In periodic lattices,disorder induces light localization and drives a transition from quantum ballistic to classical diffusive behavior.In particular,quantum walks of correlated photons exhibit a disorder-induced bunching effect,accompanied by enhanced nonclassical correlations.Our platform provides a scalable framework for investigating multiparticle quantum dynamics in engineered environments,promoting the development of quantum optics toward large-scale applications.
基金supported by the National Natural Science Foundation of China(No.12105257)the Research and Development Fund(No.JMJJ202401)。
文摘The energy correlations of prompt fission neutrons have not yet been considered in the related coincidence and multiplication measurement techniques.To measure and verify the energy correlations,an experiment was performed with a total measurement duration of approximately 1200 h.In the experiment,eight CLYC detectors and sixteen EJ309 liquid scintillation detectors were utilized,and the fission moment was tagged with the measured fissionγ-rays.The relative ratios of the energy spectra of the neutrons correlated with different energy neutrons to the^(252)Cf fission neutron energy spectra were obtained.The present results may be helpful for studying fission physics and nuclear technology applications.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.52225207 and 52350001)the Shanghai Pilot Program for Basic Research–Fudan University 21TQ1400100(Grant No.21TQ006)the Shanghai Municipal Science and Technology Major Project(Grant No.2019SHZDZX01)。
文摘When two layers of graphene are stacked with a twist angle of approximately 1.1°,strong interlayer coupling gives rise to a pair of flat bands in twisted bilayer graphene(TBG),resulting in pronounced electron–electron interactions.At half filling of the flat bands,TBG exhibits correlated insulating states.Here,we investigate the electrical transport properties of heterostructures composed of TBG and the antiferromagnetic insulator chromium oxychloride(CrOCl),and propose a strategy to modulate the correlated insulating states in TBG.During the transition from a conventional phase to a strong interfacial coupling phase,kink-like features are observed in the charge neutrality point(CNP),correlated insulating state,and band insulating state.Under a perpendicular magnetic field,the system exhibits broadened quantum Hall plateaus in the strong interfacial coupling regime.Electrons localized in the CrOCl layer screen the bottom gate,rendering the carrier density in TBG less sensitive to variations in the bottom gate voltage.These phenomena are well captured by a charge-transfer model between TBG and CrOCl.Our results provide insights into the control of electronic correlations and topological states in graphene moirésystems via interfacial charge coupling.
基金supported by the National Natural Science Foundation of China(Grant Nos.12205097,12141501,12475117,and 12435006)the National Key Laboratory of Neutron Science and Technology(Grant No.NST202401016)+1 种基金the National Key R&D Program of China(Grant Nos.2024YFA1612600 and 2024YFE0109803)the High-performance Computing Platform of Peking University。
文摘The octupole correlations of the K^(π)=5/2^(+)ground state and the rotational spectrum built on it in^(229)Th are studied using the microscopic relativistic density functional theory on a three-dimensional lattice space and the reflection-asymmetric triaxial particle rotor model.It is found that^(229)Th has a ground state with static axial octupole and quadrupole deformations.The occurrence of octupole correlations,driven by the octupole deformation,is analyzed through the evolution of single-particle levels around the Fermi surface.The experimental energy spectrum and the electromagnetic transition probabilities,including B(E2)and B(M1),are reasonably well reproduced.
基金supported in part by the National Natural Science Foundation of China(No.12575145)the National Key Research and Development Program of China(No.2022YFA1604900)。
文摘An important feature of quantum chromodynamics(QCD)is that the strong force grows as the distance between partons increases,which confines partons into hadrons,commonly known as QCD confinement.Perturbative QCD(pQCD)does not work at large distance,such as the length scale of a hadron,which is the regime of non-perturbative QCD.The detailed QCD mechanisms through which confinement occurs from partons to hadrons(usually known as hadronization),and how it manifests itself in partonic structure of hadrons(usually known as parton distribution),remain unresolved puzzles of first-principle QCD calculations.
基金supported in part by the Pioneer Research and Development Program of Zhejiang(2025C01021)Zhejiang Province Postdoctoral Research Project Selection Fund(ZJ2025061)+3 种基金the National Science and Technology Major Project-Intelligent Manufacturing Systems and Robotics of China(2025ZD1602000,2025ZD1601800)the National Natural Science Foundation of China(61933015,62273030,62573387)the Natural Science Foundation of Zhejiang province,China(LY24F030004)the Fundamental Research Funds of Zhejiang Sci-Tech University(25222139-Y)。
文摘Ironmaking process(IP)is indispensable to modern iron and steel industry,where real-time monitoring is crucial for achieving high molten iron quality(MIQ)with low energy consumption.While neural network-based models show some promising results,they are generally limited by non-negligible drawbacks such as interpretability issues of feature learning.To address these issues,we propose a novel concept based on the shallow-to-deep correlation network representation regression(Sh-to-De CNRR).Our approach,shallow correlation network representation regression(ShCNRR),combines neural network and canonical correlation analysis thoughts to generate explainable features via shallow correlation network representation(CNR).A twin inverse network is then derived to obtain the explicit model output,leveraging the shallow CNR.To capture deeper nonlinear information,we extend ShCNRR into a hierarchical deep correlation network representation regression(DeCNRR)model that features stacked neural networks,enabling us to learn deeper CNR from process data.The feasibility and advantages of our proposals are validated by theoretical derivations and practical IP cases,which contain one MIQ regression and three MIQ-related fault detection tasks.The results reveal that highly fused statistical and neural network models yield superior monitoring performance compared to current state-of-the-art models,while statistical tests verify the convincing feature mining.
基金partially supported by the Center for Advanced Systems Understanding (CASUS), financed by Germany’s Federal Ministry of Education and Research and the Saxon State Government out of the State Budget approved by the Saxon State Parliamentthe European Union’s Just Transition Fund (JTF) within the project Röntgenlaser Optimierung der Laserfusion (ROLF), Contract No. 5086999001, co-financed by the Saxon State Government out of the State Budget approved by the Saxon State Parliament+3 种基金the European Research Council (ERC) under the European Union’s Horizon 2022 Research and Innovation Programme (Grant Agreement No. 101076233, “PREXTREME”)Computations were performed on a Bull Cluster at the Center for Information Services and High-Performance Computing (ZIH) at Technische Universität Dresden and at the Norddeutscher Verbund für Hoch- und Höchstleistungsrechnen (HLRN) under Grant No. mvp00024support by the National Natural Science Foundation of China under Grant No. 12274171support by the Advanced Materials–National Science and Technology Major Project (Grant No. 2024ZD0606900)
文摘Understanding the properties of warm dense hydrogen is of key importance for the modeling of compact astrophysical objects and to understand and further optimize inertial confinement fusion applications.The workhorse of warm dense matter theory is thermal density functional theory(DFT),which,however,suffers from two limitations:(i)its accuracy can depend on the utilized exchange-correlation functional,which has to be approximated,and(ii)it is generally limited to single-electron properties such as the density distribution.Here,we present a new ansatz combining time-dependent DFT results for the dynamic structure factor S_(ee)(q,ω)with static DFT results for the density response.This allows us to estimate the electron-electron static structure factor S_(ee)(q)of warm dense hydrogen with high accuracy over a broad range of densities and temperatures.In addition to its value for the study of warm dense matter,our work opens up new avenues for the future study of electronic correlations exclusively within the framework of DFT for a host of applications.
文摘Identifying inter-frame forgery is a hot topic in video forensics. In this paper, we propose a method based on the assumption that the correlation coefficients of gray values is consistent in an original video, while in forgeries the consistency will be destroyed. We first extract the consistency of correlation coefficients of gray values (CCCoGV for short) after normalization and quantization as distinguishing feature to identify interframe forgeries. Then we test the CCCoGV in a large database with the help of SVM (Support Vector Machine). Experimental results show that the proposed method is efficient in classifying original videos and forgeries. Furthermore, the proposed method performs also pretty well in classifying frame insertion and frame deletion forgeries.
基金supported in part by the National Natural Science Foundation of China (No. U23B2011)。
文摘Video snapshot compressive imaging(Video SCI) modulates scenes using various encoding masks and captures compressed measurements with a low-speed camera during a single exposure. Subsequently, reconstruction algorithms restore image sequences of dynamic scenes, offering advantages such as reduced bandwidth and storage space requirements. The temporal correlation in video data is crucial for Video SCI, as it leverages the temporal relationships among frames to enhance the efficiency and quality of reconstruction algorithms, particularly for fast-moving objects.This paper discretizes video frames to create image datasets with the same data volume but differing temporal correlations. We utilized the state-of-the-art(SOTA) reconstruction framework, EfficientSCI++, to train various compressed reconstruction models with these differing temporal correlations. Evaluating the reconstruction results from these models, our simulation experiments confirm that a reduction in temporal correlation leads to decreased reconstruction accuracy. Additionally, we simulated the reconstruction outcomes of datasets devoid of temporal correlation, illustrating that models trained on non-temporal data affect the temporal feature extraction capabilities of transformers, resulting in negligible impacts on the evaluation of reconstruction results for non-temporal correlation test datasets.
文摘Ten physical and environmental variables collected from an on-the-go soil sensor at two field sites (MF3E and MF11S) in Mississippi, USA, were analyzed to assess soil variability and the interrelationships among the measurements. At MF3E, moderate variability was observed in apparent electrical conductivity shallow (ECas), slope, and ECa ratio measurements, with coefficients of variation ranging from 20% to 27%. In contrast, MF11S exhibited higher variability, particularly in ECas and ECad (deep) measurements, which exceeded 30% in their coefficient of variation values, indicating significant differences in soil composition and moisture content. Correlation analysis revealed strong positive relationships between the near-infrared-to-red ratio and red reflectance (r = 0.897***) soil values at MF3E. MF11S demonstrated a strong negative correlation between ECas and ECad readings with the x-coordinate (r ***). Scatter plots and fitted models illustrated the complexity of relationships, with many showing nonlinear trends. These findings emphasize the need for continuous monitoring and advanced modeling to understand the dynamic nature of soil properties and their implications for agricultural practices. Future research should explore the underlying mechanisms driving variability in the soil characteristics to enhance soil management strategies at the study sites.
文摘By introducing noncanonical vortex pairs to partially coherent beams, spatial correlation singularity (SCS) and orbital angular momenta (OAM) of the resulting beams are studied using the Fraunhofer diffraction integral. The effect of noncanonical strength, off-axis distance and vortex sign on spatial correlation singularities in far field is stressed. Furthermore, far-field OAM spectra and densities are also investigated, and the OAM detection and crosstalk probabilities are discussed. The results show that the number of dislocations of SCS always equals the sum of absolute values of topological charges for canonical or noncanonical vortex pairs. Although the sum of the product of each OAM mode and its power weight equals the algebraic sum of topological charges for canonical vortex pairs, the relationship no longer holds in the noncanonical case except for opposite-charge vortex pairs. The changes of off-axis distance, noncanonical strength or coherence length can lead to a more dominant power in adjacent mode than that in center detection mode, which also indicates that crosstalk probabilities of adjacent modes exceed the center detection probability. This work may provide potential applications in OAM-based optical communication, imaging, sensing and computing.
基金the Science and Engineering Re-search Board(SERB),India for providing the financial assistance to support this work(Project No.SRG/2020/002449).
文摘Since antiquity,humans have been involved in designing materials through alloying strategies to meet the ever-growing technological demands.In 2004,this endeavor witnessed a significant breakthrough with the discovery of high-entropy alloys(HEAs)comprising multi-principal elements.Owing to the four“core-effects”,these alloys exhibit exceptional properties including better structural stability,high strength and ductility,improved fatigue/fracture toughness,high corrosion and oxidation resistance,superconductiv-ity,magnetic properties,and good thermal properties.Different synthesis routes have been designed and used to meet the properties of interest for particular applications with varying dimensions.How-ever,HEAs are providing new opportunities and challenges for computational modelling of the complex structure-property correlations and in predictions of phase stability necessary for optimum performance of the alloy.Several attempts have been made to understand these alloys by empirical and computa-tional models,and data-driven approaches to accelerate the materials discovery with a desired set of properties.The present review discusses advances and inferences from simulations and models spanning multiple length and time scales explaining a comprehensive set of structure-properties relations.Addi-tionally,the role of machine learning approaches is also reviewed,underscoring the transformative role of computational modelling in unravelling the multifaceted properties and applications of HEAs,and the scope for future efforts in this direction.
文摘Geomagnetic observatory data are crucial for all branches of geophysics because they can contribute to earthquake research by detecting anomalies in the Earth’s magnetic field.Recently,data records from the Misallat(MLT)and Abu Simbel(ABS)Egyptian geomagnetic observatories were processed and found to be of good quality.In this study,Egyptian observatory data were tested during both quiet and disturbed events and compared with data from INTERMAGNET observatories worldwide at different latitudes and within a narrow range of longitudes in both hemispheres.This study investigated the relationships between magnetic field components from Egyptian observatories and those from INTERMAGNET observatories using graphical representations of the X components;Pearson’s correlation for the X,Y,Z,and F components;cross-correlation for the X component;and wavelet coherence for the F component.The results of this study showed a high correlation between Egyptian observatories and all utilized INTERMAGNET stations,except those located at high latitudes,during both quiet and disturbed events.Additionally,the study confirmed the observed consistency between Egyptian observatories and selected INTERMAGNET stations.Therefore,Egyptian observatories can feasibly fill the gap in the Middle East and North Africa.
