A clock bias data processing method based on interval correlation coefficient wavelet threshold denoising is suggested for minor mistakes in clock bias data in order to increase the efficacy of satellite clock bias pr...A clock bias data processing method based on interval correlation coefficient wavelet threshold denoising is suggested for minor mistakes in clock bias data in order to increase the efficacy of satellite clock bias prediction.Wavelet analysis was first used to break down the satellite clock frequency data into several levels,producing high and low frequency coefficients for each layer.The correlation coefficients of the high and low frequency coefficients in each of the three sub-intervals created by splitting these coefficients were then determined.The major noise region—the sub-interval with the lowest correlation coefficient—was chosen for thresholding treatment and noise threshold computation.The clock frequency data was then processed using wavelet reconstruction and reconverted to clock data.Lastly,three different kinds of satellite clock data—RTS,whu-o,and IGS-F—were used to confirm the produced data.Our method enhanced the stability of the Quadratic Polynomial(QP)model’s predictions for the C16 satellite by about 40%,according to the results.The accuracy and stability of the Auto Regression Integrated Moving Average(ARIMA)model improved up to 41.8%and 14.2%,respectively,whilst the Wavelet Neural Network(WNN)model improved by roughly 27.8%and 63.6%,respectively.Although our method has little effect on forecasting IGS-F series satellites,the experimental findings show that it can improve the accuracy and stability of QP,ARIMA,and WNN model forecasts for RTS and whu-o satellite clock bias.展开更多
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
To address the key scientific challenge of monitoring the dynamic fracturing of surrounding rock in deep roadways,this study systematically investigates the quantitative relationship between stress and charge signals ...To address the key scientific challenge of monitoring the dynamic fracturing of surrounding rock in deep roadways,this study systematically investigates the quantitative relationship between stress and charge signals during coal mass loading.By integrating innovative analytical approaches,introducing quantitative evaluation indices,and developing a charge–stress inversion model,and incorporating underground monitoring practices,significant progress has been achieved in elucidating the correlation between stress variations and charge signals throughout the entire coal mass fracturing process.First,in the field of stress–charge correlation analysis,empirical mode decomposition(EMD)was combined with wavelet coherence analysis for the first time,enabling the removal of slow-varying stress trends while retaining high-frequency fluctuations.This approach allowed for the quantitative characterization of the evolution of coherence between stress variations and charge fluctuations across multiple time scales.Second,coherence skewness and the proportion of high-coherence intervals were innovatively introduced to examine the influence of time scale selection on correlation results.On this basis,a criterion for determining the near-optimal observation scale of charge signals was proposed,providing a quantitative reference for time scale selection in similar signal analyses.Finally,by correlating charge signals with coal damage factors and stress states,a charge-based damage evolution equation was established to achieve effective stress inversion.Combined with in situ monitoring of stress and charge in roadway surrounding rock,this approach revealed the correlation characteristics of stress and charge intensity responses during the dynamic fracturing process.The results indicate,first,that charge signals are not significantly correlated with the absolute stress level of coal but are directly associated with stress variations following coal damage and failure,with the amplitude of charge fluctuations increasing alongside stress fluctuations.Second,coherence between stress and charge signals varies markedly across time scales,with excessively small or large scales leading to distortion,and the scale corresponding to the peak proportion of intervals with coherence>0.8 was identified as the near-optimal observation scale.Third,charge signals can effectively characterize coal damage factors,and the established damage evolution equation can effectively invert stress variation trends.Fourth,in underground roadways,zones of dynamic fracturing in surrounding rock are commonly located in areas where stress concentration overlaps with regions of high charge intensity,further confirming the strong consistency between charge and stress variations.These findings improve the theoretical framework of charge signal responses in loaded coal and provide a scientific basis for precise“stress-charge”monitoring of dynamic disasters,offering practical potential for engineering applications.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
Hydraulic asphalt concrete(HAC)has been increasingly employed as an appropriate impervious structure in hydraulic and hydropower engineering.However,asphalt mortar,usually seen as the matrix of HAC composite,is partic...Hydraulic asphalt concrete(HAC)has been increasingly employed as an appropriate impervious structure in hydraulic and hydropower engineering.However,asphalt mortar,usually seen as the matrix of HAC composite,is particularly prone to damage under combined stress and seepage interactions,and the mesoscale investigations on the damage-seepage coupling behavior of HAC under complex stress states remain limited.This research develops a numerical three-dimensional mesoscale model composed of asphalt mortar and polyhedral aggregate to investigate the stress-damage-seepage coupling behavior in HAC.In this model,asphalt mortar yields the viscoelastic continuum damage law and aggregate obeys the Mazars’elastic-brittle damage law;simultaneously,the effective permeability coefficient of asphalt mortar is assumed to follow an exponential function of damage.The predicted deviatoric stress-strain and hydraulic gradient-seepage curves both are in good agreement with the reported experimental results,which shows the proposed model is valid and reasonable.The simulated results indicate that the damaged asphalt mortar can induce localized areas of high permeability,which in turn affects the overall impervious performance of HAC.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
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
Although traditional gamma-gamma density(GGD)logging technology is widely utilized,its potential environmental risks have prompted the development of more environmentally friendly neutron-gamma density(NGD)logging tec...Although traditional gamma-gamma density(GGD)logging technology is widely utilized,its potential environmental risks have prompted the development of more environmentally friendly neutron-gamma density(NGD)logging technology.However,NGD measurements are influenced by both neutron and gamma radiations.In the logging environment,variations in the formation composition indicate different elemental compositions,which affect the neutron-gamma reaction cross-sections and gamma generation.Compared to traditional gamma sources such as Cs-137,these changes significantly affect the generation and transport of neutron-induced inelastic gamma rays and hinder accurate measurements.To address this,a novel method is proposed that incorporates the mass attenuation coefficient function to account for the effects of various lithologies and pore contents on gamma-ray attenuation,thereby achieving more accurate density measurements by clarifying the transport processes of inelastic gamma rays with varying energies and spatial distributions in varied logging environments.The proposed method avoids the complex correction of neutron transport and is verified through Monte Carlo simulations for its applicability across various lithologies and pore contents,demonstrating absolute density errors that are less than 0.02 g/cm^(3)in clean formations and indicating good accuracy.This study clarifies the NGD mechanism and provides theoretical guidance for the application of NGD logging methods.Further studies will be conducted on extreme environmental conditions and tool calibration.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
Reconfigurable array architecture has become an important hardware platform for edge-side deployment of convolutional neural networks due to their high parallelism and flexible programmability.However,traditional mult...Reconfigurable array architecture has become an important hardware platform for edge-side deployment of convolutional neural networks due to their high parallelism and flexible programmability.However,traditional multi-branch convolutional networks suffer from computational redundancy,high memory access overhead,and inefficient branch fusion.Therefore,this paper proposes an adaptive multi-branch convolutional module(AMBC)that integrates software-hardware co-optimization.During training,the learnable fusion coefficients are introduced to enable adaptive fusion of multi-scale features,while in the inference phase,the multiple branches and their normalization parameters are merged with the fusion coefficients into a single 3×3 convolutional kernel through operator fusion.On the SIREA-288 reconfigurable platform,compared with unoptimized multi-branch networks,the proposed AMBC reduces external memory accesses by 47.91%and inference latency by 47.20%,achieving a 1.90×speedup.This approach maximizes the utilization of the reconfigurable logic while minimizing both reconfiguration and data-movement overheads in edge inference.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
We analyzed the infrared 0R）-near infrared （NIR） 2D correlation spectra of drugs perturbed by temperature. By identification of functional groups by IR spectrum and by the correlation analysis of IR-NIR spectrum, w...We analyzed the infrared 0R）-near infrared （NIR） 2D correlation spectra of drugs perturbed by temperature. By identification of functional groups by IR spectrum and by the correlation analysis of IR-NIR spectrum, we identified the characteristic spectral bands that were closely related to the structure of a drug substance of interest. These characteristic spectral bands were relatively less interfered by other ingredients for analysis by the NIR correlation coefficient method. With these characteristic spectral bands, the accuracy of screening illegally added Sildenafil citrate, Tadalafil and Metforrnin hydrochloride in Chinese patent drugs and healthcare products reached about 90%, which met the requirements of rapid screening.展开更多
The phenomenon of stochastic resonance （SR） based on the correlation coefficient in a parallel array of threshold devices is discussed. For four representative noises： the Gaussian noise, the uniform noise, the Lap...The phenomenon of stochastic resonance （SR） based on the correlation coefficient in a parallel array of threshold devices is discussed. For four representative noises： the Gaussian noise, the uniform noise, the Laplace noise and the Cauchy noise, when the signal is subthreshold, noise can improve the correlation coefficient and SR exists. The efficacy of SR can be significantly enhanced and the maximum of the correlation coefficient can dramatically approach to one as the number of the threshold devices in the parallel array increases. Two theorems are presented to prove that SR has some robustness to noises in the parallel array. These results further extend the applicability of SR in signal processing.展开更多
基金2023 Liaoning Institute of Science and Technology Doctoral Program Launch fund(No.2307B29).
文摘A clock bias data processing method based on interval correlation coefficient wavelet threshold denoising is suggested for minor mistakes in clock bias data in order to increase the efficacy of satellite clock bias prediction.Wavelet analysis was first used to break down the satellite clock frequency data into several levels,producing high and low frequency coefficients for each layer.The correlation coefficients of the high and low frequency coefficients in each of the three sub-intervals created by splitting these coefficients were then determined.The major noise region—the sub-interval with the lowest correlation coefficient—was chosen for thresholding treatment and noise threshold computation.The clock frequency data was then processed using wavelet reconstruction and reconverted to clock data.Lastly,three different kinds of satellite clock data—RTS,whu-o,and IGS-F—were used to confirm the produced data.Our method enhanced the stability of the Quadratic Polynomial(QP)model’s predictions for the C16 satellite by about 40%,according to the results.The accuracy and stability of the Auto Regression Integrated Moving Average(ARIMA)model improved up to 41.8%and 14.2%,respectively,whilst the Wavelet Neural Network(WNN)model improved by roughly 27.8%and 63.6%,respectively.Although our method has little effect on forecasting IGS-F series satellites,the experimental findings show that it can improve the accuracy and stability of QP,ARIMA,and WNN model forecasts for RTS and whu-o satellite clock bias.
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supported by the Research Fund of the National Natural Science Foundation of China(No.52374205)the Fundamental Research Project of the Educational Department of Liaoning Province(No.JYTMS20230793)the Research Fund of the State Key Laboratory of Coal Resources and Safe Mining,CUMT(No.YJY-XD-2024-A-016).
文摘To address the key scientific challenge of monitoring the dynamic fracturing of surrounding rock in deep roadways,this study systematically investigates the quantitative relationship between stress and charge signals during coal mass loading.By integrating innovative analytical approaches,introducing quantitative evaluation indices,and developing a charge–stress inversion model,and incorporating underground monitoring practices,significant progress has been achieved in elucidating the correlation between stress variations and charge signals throughout the entire coal mass fracturing process.First,in the field of stress–charge correlation analysis,empirical mode decomposition(EMD)was combined with wavelet coherence analysis for the first time,enabling the removal of slow-varying stress trends while retaining high-frequency fluctuations.This approach allowed for the quantitative characterization of the evolution of coherence between stress variations and charge fluctuations across multiple time scales.Second,coherence skewness and the proportion of high-coherence intervals were innovatively introduced to examine the influence of time scale selection on correlation results.On this basis,a criterion for determining the near-optimal observation scale of charge signals was proposed,providing a quantitative reference for time scale selection in similar signal analyses.Finally,by correlating charge signals with coal damage factors and stress states,a charge-based damage evolution equation was established to achieve effective stress inversion.Combined with in situ monitoring of stress and charge in roadway surrounding rock,this approach revealed the correlation characteristics of stress and charge intensity responses during the dynamic fracturing process.The results indicate,first,that charge signals are not significantly correlated with the absolute stress level of coal but are directly associated with stress variations following coal damage and failure,with the amplitude of charge fluctuations increasing alongside stress fluctuations.Second,coherence between stress and charge signals varies markedly across time scales,with excessively small or large scales leading to distortion,and the scale corresponding to the peak proportion of intervals with coherence>0.8 was identified as the near-optimal observation scale.Third,charge signals can effectively characterize coal damage factors,and the established damage evolution equation can effectively invert stress variation trends.Fourth,in underground roadways,zones of dynamic fracturing in surrounding rock are commonly located in areas where stress concentration overlaps with regions of high charge intensity,further confirming the strong consistency between charge and stress variations.These findings improve the theoretical framework of charge signal responses in loaded coal and provide a scientific basis for precise“stress-charge”monitoring of dynamic disasters,offering practical potential for engineering applications.
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supported by the National Key Research and Development Program of China(Grant No.2022YFC3005603-01)the Natural Science Foundation Science of Anhui Province(Grant No.2308085US02).
文摘Hydraulic asphalt concrete(HAC)has been increasingly employed as an appropriate impervious structure in hydraulic and hydropower engineering.However,asphalt mortar,usually seen as the matrix of HAC composite,is particularly prone to damage under combined stress and seepage interactions,and the mesoscale investigations on the damage-seepage coupling behavior of HAC under complex stress states remain limited.This research develops a numerical three-dimensional mesoscale model composed of asphalt mortar and polyhedral aggregate to investigate the stress-damage-seepage coupling behavior in HAC.In this model,asphalt mortar yields the viscoelastic continuum damage law and aggregate obeys the Mazars’elastic-brittle damage law;simultaneously,the effective permeability coefficient of asphalt mortar is assumed to follow an exponential function of damage.The predicted deviatoric stress-strain and hydraulic gradient-seepage curves both are in good agreement with the reported experimental results,which shows the proposed model is valid and reasonable.The simulated results indicate that the damaged asphalt mortar can induce localized areas of high permeability,which in turn affects the overall impervious performance of HAC.
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(U23B20151 and 52171253).
文摘Although traditional gamma-gamma density(GGD)logging technology is widely utilized,its potential environmental risks have prompted the development of more environmentally friendly neutron-gamma density(NGD)logging technology.However,NGD measurements are influenced by both neutron and gamma radiations.In the logging environment,variations in the formation composition indicate different elemental compositions,which affect the neutron-gamma reaction cross-sections and gamma generation.Compared to traditional gamma sources such as Cs-137,these changes significantly affect the generation and transport of neutron-induced inelastic gamma rays and hinder accurate measurements.To address this,a novel method is proposed that incorporates the mass attenuation coefficient function to account for the effects of various lithologies and pore contents on gamma-ray attenuation,thereby achieving more accurate density measurements by clarifying the transport processes of inelastic gamma rays with varying energies and spatial distributions in varied logging environments.The proposed method avoids the complex correction of neutron transport and is verified through Monte Carlo simulations for its applicability across various lithologies and pore contents,demonstrating absolute density errors that are less than 0.02 g/cm^(3)in clean formations and indicating good accuracy.This study clarifies the NGD mechanism and provides theoretical guidance for the application of NGD logging methods.Further studies will be conducted on extreme environmental conditions and tool calibration.
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 Science and Technology Major Project of China(2022ZD0119005)the Natural Science Project of Shaanxi Province(2025JC-YBMS-754,2024JC-YBMS-539)。
文摘Reconfigurable array architecture has become an important hardware platform for edge-side deployment of convolutional neural networks due to their high parallelism and flexible programmability.However,traditional multi-branch convolutional networks suffer from computational redundancy,high memory access overhead,and inefficient branch fusion.Therefore,this paper proposes an adaptive multi-branch convolutional module(AMBC)that integrates software-hardware co-optimization.During training,the learnable fusion coefficients are introduced to enable adaptive fusion of multi-scale features,while in the inference phase,the multiple branches and their normalization parameters are merged with the fusion coefficients into a single 3×3 convolutional kernel through operator fusion.On the SIREA-288 reconfigurable platform,compared with unoptimized multi-branch networks,the proposed AMBC reduces external memory accesses by 47.91%and inference latency by 47.20%,achieving a 1.90×speedup.This approach maximizes the utilization of the reconfigurable logic while minimizing both reconfiguration and data-movement overheads in edge inference.
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National Key Technology R & D Program-On-site Rapid Identification of Drug Research Project (Grant No. 2008BAI55B06)
文摘We analyzed the infrared 0R）-near infrared （NIR） 2D correlation spectra of drugs perturbed by temperature. By identification of functional groups by IR spectrum and by the correlation analysis of IR-NIR spectrum, we identified the characteristic spectral bands that were closely related to the structure of a drug substance of interest. These characteristic spectral bands were relatively less interfered by other ingredients for analysis by the NIR correlation coefficient method. With these characteristic spectral bands, the accuracy of screening illegally added Sildenafil citrate, Tadalafil and Metforrnin hydrochloride in Chinese patent drugs and healthcare products reached about 90%, which met the requirements of rapid screening.
文摘The phenomenon of stochastic resonance （SR） based on the correlation coefficient in a parallel array of threshold devices is discussed. For four representative noises： the Gaussian noise, the uniform noise, the Laplace noise and the Cauchy noise, when the signal is subthreshold, noise can improve the correlation coefficient and SR exists. The efficacy of SR can be significantly enhanced and the maximum of the correlation coefficient can dramatically approach to one as the number of the threshold devices in the parallel array increases. Two theorems are presented to prove that SR has some robustness to noises in the parallel array. These results further extend the applicability of SR in signal processing.
