Ambient noise tomography(ANT)has been widely used to image crust and upmost mantle structures.ANT assumes that sources of ambient noise are diffuse and evenly distributed in space and the energy of different modes is ...Ambient noise tomography(ANT)has been widely used to image crust and upmost mantle structures.ANT assumes that sources of ambient noise are diffuse and evenly distributed in space and the energy of different modes is equipartitioned.At present,the sources of the primary and the secondary microseisms are well studied,but there are only a few on the studies of long-period ambient noise sources.In this study,we study the effects of large earthquake signals on the recovery of surface waves from seismic ambient noise data recorded by seismic stations from the US permanent networks and Global Seismographic Network(GSN).Our results show that large earthquake signals play an important role on the recovery of long-period surface waves from ambient noise cross-correlation functions.Our results are consistent with previous studies that suggest the contribution of earthquake signals to the recovery of surface waves from cross-correlations of ambient noise is dominant at periods larger than 20–40 s.展开更多
The cyclic cross-correlation between a stationary process and a cyclostationary process at cycle frequency α(≠ 0)is identically zero under an ideal condition, which indicates that a cyclic cross-correlation method p...The cyclic cross-correlation between a stationary process and a cyclostationary process at cycle frequency α(≠ 0)is identically zero under an ideal condition, which indicates that a cyclic cross-correlation method performs much better than the conventional cross-correlation method in suppressing the stationary noise or interference. But unfortunately, the cyclic cross-correlation will not really approach zero due to the limited data length in some real conditions. In this paper, the quantitative relation between the data length and the estimated cyclic cross-correlation is deduced, and some useful conclusions are drawn, which are proven by some computer simulations. The conclusion in this paper is really useful for the practical application of cyclostationary signal processing.展开更多
Model-driven and data-driven inversions are two prominent methods for obtaining P-wave impedance,which is significant in reservoir description and identification.Based on proper initial models,most model-driven method...Model-driven and data-driven inversions are two prominent methods for obtaining P-wave impedance,which is significant in reservoir description and identification.Based on proper initial models,most model-driven methods primarily use the limited frequency bandwidth information of seismic data and can invert P-wave impedance with high accuracy,but not high resolution.Conventional data-driven methods mainly employ the information from well-log data and can provide high-accuracy and highresolution P-wave impedance owing to the superior nonlinear curve fitting capacity of neural networks.However,these methods require a significant number of training samples,which are frequently insufficient.To obtain P-wave impedance with both high accuracy and high resolution,we propose a model-data-driven inversion method using Res Nets and the normalized zero-lag cross-correlation objective function which is effective for avoiding local minima and suppressing random noise.By using initial models and training samples,the proposed model-data-driven method can invert P-wave impedance with satisfactory accuracy and resolution.Tests on synthetic and field data demonstrate the proposed method’s efficacy and practicability.展开更多
The improved cross-correlation algorithm for the strain demodulation of Vernier-effect-based optical fiber sensor(VE-OFS)is proposed in this article.The algorithm identifies the most similar spectrum to the measured o...The improved cross-correlation algorithm for the strain demodulation of Vernier-effect-based optical fiber sensor(VE-OFS)is proposed in this article.The algorithm identifies the most similar spectrum to the measured one from the database of the collected spectra by employing the cross-correlation operation,subsequently deriving the predicted value via weighted calculation.As the algorithm uses the complete information in the measured raw spectrum,more accurate results and larger measurement range can be obtained.Additionally,the improved cross-correlation algorithm also has the potential to improve the measurement speed compared to current standards due to the possibility for the collection using low sampling rate.This work presents an important algorithm towards a simpler,faster way to improve the demodulation performance of VE-OFS.展开更多
Detecting coupling pattern between elements in a complex system is a basic task in data-driven analysis. The trajectory for each specific element is a cooperative result of its intrinsic dynamic, its couplings with ot...Detecting coupling pattern between elements in a complex system is a basic task in data-driven analysis. The trajectory for each specific element is a cooperative result of its intrinsic dynamic, its couplings with other elements, and the environment. It is subsequently composed of many components, only some of which take part in the couplings. In this paper we present a framework to detect the component correlation pattern. Firstly, the interested trajectories are decomposed into components by using decomposing methods such as the Fourier expansion and the Wavelet transformation. Secondly, the cross-correlations between the components are calculated, resulting into a component cross-correlation matrix(network).Finally, the dominant structure in the network is identified to characterize the coupling pattern in the system. Several deterministic dynamical models turn out to be characterized with rich structures such as the clustering of the components. The pattern of correlation between respiratory(RESP) and ECG signals is composed of five sub-clusters that are mainly formed by the components in ECG signal. Interestingly, only 7 components from RESP(scattered in four sub-clusters) take part in the realization of coupling between the two signals.展开更多
Traditional cross-correlation algorithms are prone to time-of-flight(TOF)calculation errors under conditions of strong noise interference and complex temperature gradients,resulting in a decline in the accuracy of ult...Traditional cross-correlation algorithms are prone to time-of-flight(TOF)calculation errors under conditions of strong noise interference and complex temperature gradients,resulting in a decline in the accuracy of ultrasonic temperature measurement.To this end,this paper proposes an ultrasonic temperature measurement method that combines YOLOv11 target detection with energy-type weighted cross-correlation algorithm.The YOLOv11 model is utilized to conduct target detection and key area positioning on the ultrasonic signal waveform diagram,automatically identifying characteristic waveforms such as node waves and end face waves,and achieving adaptive extraction of the effective signal interval.Further introduce the energy-based weighted cross-correlation algorithm.Based on the signal energy distribution,the cross-correlation results are weighted and processed to enhance the main wave response and suppress noise interference.Experiments show that the YOLOv11 model has high detection accuracy(Precision=0.987,Recall=0.958,mAP@50=0.988);The proposed method maintains the stability of time delay estimation under strong noise and high temperature(>1200℃),with the average time delay error reduced by approximately 35%to 50%compared to traditional algorithms.This verifies its high robustness and temperature measurement accuracy in complex environments,and it has a promising engineering application prospect.展开更多
To address the issue of low measurement accuracy caused by noise interference in the acquisition of low fluid flow rate signals with ultrasonic Doppler flow meters,a novel signal processing algorithm that combines ens...To address the issue of low measurement accuracy caused by noise interference in the acquisition of low fluid flow rate signals with ultrasonic Doppler flow meters,a novel signal processing algorithm that combines ensemble empirical mode decomposition(EEMD)and cross-correlation algorithm was proposed.Firstly,a fast Fourier transform(FFT)spectrum analysis was utilized to ascertain the frequency range of the signal.Secondly,data acquisition was conducted at an appropriate sampling frequency,and the acquired Doppler flow rate signal was then decomposed into a series of intrinsic mode functions(IMFs)by EEMD.Subsequently,these decomposed IMFs were recombined based on their energy entropy,and then the noise of the recombined Doppler flow rate signal was removed by cross-correlation filtering.Finally,an ideal ultrasonic Doppler flow rate signal was extracted.Simulation and experimental verification show that the proposed Doppler flow signal processing method can effectively enhance the signal-to-noise ratio(SNR)and extend the lower limit of measurement of the ultrasonic Doppler flow meter.展开更多
Gauss radial basis functions(GRBF)are frequently employed in data fitting and machine learning.Their linear independence property can theoretically guarantee the avoidance of data redundancy.In this paper,one of the m...Gauss radial basis functions(GRBF)are frequently employed in data fitting and machine learning.Their linear independence property can theoretically guarantee the avoidance of data redundancy.In this paper,one of the main contributions is proving this property using linear algebra instead of profound knowledge.This makes it easy to read and understand this fundamental fact.The proof of linear independence of a set of Gauss functions relies on the constructing method for one-dimensional space and on the deducing method for higher dimensions.Additionally,under the condition of preserving the same moments between the original function and interpolating function,both the interpolating existence and uniqueness are proven for GRBF in one-dimensional space.The final work demonstrates the application of the GRBF method to locate lunar olivine.By combining preprocessed data using GRBF with the removing envelope curve method,a program is created to find the position of lunar olivine based on spectrum data,and the numerical experiment shows that it is an effective scheme.展开更多
Spinal cord injury represents a severe form of central nervous system trauma for which effective treatments remain limited.Microglia is the resident immune cells of the central nervous system,play a critical role in s...Spinal cord injury represents a severe form of central nervous system trauma for which effective treatments remain limited.Microglia is the resident immune cells of the central nervous system,play a critical role in spinal cord injury.Previous studies have shown that microglia can promote neuronal survival by phagocytosing dead cells and debris and by releasing neuroprotective and anti-inflammatory factors.However,excessive activation of microglia can lead to persistent inflammation and contribute to the formation of glial scars,which hinder axonal regeneration.Despite this,the precise role and mechanisms of microglia during the acute phase of spinal cord injury remain controversial and poorly understood.To elucidate the role of microglia in spinal cord injury,we employed the colony-stimulating factor 1 receptor inhibitor PLX5622 to deplete microglia.We observed that sustained depletion of microglia resulted in an expansion of the lesion area,downregulation of brain-derived neurotrophic factor,and impaired functional recovery after spinal cord injury.Next,we generated a transgenic mouse line with conditional overexpression of brain-derived neurotrophic factor specifically in microglia.We found that brain-derived neurotrophic factor overexpression in microglia increased angiogenesis and blood flow following spinal cord injury and facilitated the recovery of hindlimb motor function.Additionally,brain-derived neurotrophic factor overexpression in microglia reduced inflammation and neuronal apoptosis during the acute phase of spinal cord injury.Furthermore,through using specific transgenic mouse lines,TMEM119,and the colony-stimulating factor 1 receptor inhibitor PLX73086,we demonstrated that the neuroprotective effects were predominantly due to brain-derived neurotrophic factor overexpression in microglia rather than macrophages.In conclusion,our findings suggest the critical role of microglia in the formation of protective glial scars.Depleting microglia is detrimental to recovery of spinal cord injury,whereas targeting brain-derived neurotrophic factor overexpression in microglia represents a promising and novel therapeutic strategy to enhance motor function recovery in patients with spinal cord injury.展开更多
By using the linear approximation method, the intensity correlation function is calculated for a single-mode laser modulated by a bias signal and driven by colored pump and quantum noises with colored cross-correlatio...By using the linear approximation method, the intensity correlation function is calculated for a single-mode laser modulated by a bias signal and driven by colored pump and quantum noises with colored cross-correlation. We found that, when the correlation time between the two noises is very short, the behavior of the intensity correlation function versus the time, in addition to decreasing monotonously, also exhibits several cases, such as one maximum, one minimum, and two extrema. When the correlation time between the two noises is very long, the behavior of the intensity correlation function exhibits oscillation and the envelope is similar to the case of short cross-correlation time.展开更多
Functional gastrointestinal disorders(FGIDs),including irritable bowel syndrome(IBS),functional dyspepsia(FD),and gastroesophageal reflux disease(GERD),present persistent diagnostic and therapeutic challenges due to s...Functional gastrointestinal disorders(FGIDs),including irritable bowel syndrome(IBS),functional dyspepsia(FD),and gastroesophageal reflux disease(GERD),present persistent diagnostic and therapeutic challenges due to symptom heterogeneity and the absence of reliable biomarkers.Artificial intelligence(AI)enables the integration of multimodal data to enhance FGID management through precision diagnostics and preventive healthcare.This minireview summarizes recent advancements in AI applications for FGIDs,highlighting progress in diagnostic accuracy,subtype classification,personalized interventions,and preventive strategies inspired by the traditional Chinese medicine concept of“treating the undiseased”.Machine learning and deep learning algorithms have demonstrated value in improving IBS diagnosis,refining FD neuro-gastrointestinal subtyping,and screening for GERD-related complications.Moreover,AI supports dietary,psychological,and integrative medicine-based interventions to improve patient adherence and quality of life.Nonetheless,key challenges remain,including data heterogeneity,limited model interpretability,and the need for robust clinical validation.Future directions emphasize interdisciplinary collaboration,the development of multimodal and explainable AI models,and the creation of patientcentered platforms to facilitate a shift from reactive treatment to proactive prevention.This review provides a systematic framework to guide the clinical application and theoretical innovation of AI in FGIDs.展开更多
BACKGROUND An echocardiogram is an essential tool in the evaluation of potential kidney transplant recipients(KTRs).Despite cardiac clearance,potential KTRs still have structural and functional abnormalities.Identifyi...BACKGROUND An echocardiogram is an essential tool in the evaluation of potential kidney transplant recipients(KTRs).Despite cardiac clearance,potential KTRs still have structural and functional abnormalities.Identifying the prevalence of these abnormalities and understanding their predictors is vital for optimizing pretransplant risk stratification and improving post-transplant outcomes.AIM To determine the prevalence of left ventricular hypertrophy(LVH),left ventricular systolic dysfunction(LVSD),diastolic dysfunction(DD),pulmonary hypertension(PH),and their predictors,and to assess their impact on graft function in pre-transplant candidates.METHODS The study included all successful transplant candidates older than 14 who had a baseline echocardiogram.Binary logistic regression models were constructed to identify factors associated with LVH,LVSD,DD,and PH.RESULTS Out of 259 patients,LVH was present in 64%(166),12%(31)had LVSD,27.5%(71)had DD,and 66(25.5%)had PH.Independent predictors of LVH included male gender[odds ratio(OR):2.51;95%CI:1.17-5.41 P=0.02],PH(OR=2.07;95%CI:1.11-3.86;P=0.02),DD(OR:2.47;95%CI:1.29-4.73;P=0.006),and dyslipidemia(OR=1.94;95%CI:1.07-3.53;P=0.03).Predictors for LVSD included patients with DD(OR=3.3,95%CI:1.41-7.81;P=0.006)and a family history of coronary artery disease(OR=4.50,95%CI:1.33-15.20;P=0.015).Peritoneal dialysis was an independent predictor for DD(OR=10.03;95%CI:1.71-58.94,P=0.011).The presence of LVH(OR=3.32,95%CI:1.05-10.55,P=0.04)and mild to moderate or moderate to severe mitral regurgitation(OR=4.63,95%CI:1.45-14.78,P=0.01)were significant factors associated with PH.These abnormalities had no significant impact on estimated glomerular filtration at discharge,6 months,1 year,or 2 years post-transplant.CONCLUSION Significant echocardiographic abnormalities persist in a potential transplant candidate despite cardiac clearance,although they don’t affect future graft function.Understanding the risk factors associated with these abnormalities may help clinicians address these factors pre-and post-transplant to achieve better outcomes.展开更多
BACKGROUND Suicide constitutes the second leading cause of death among adolescents globally and represents a critical public health concern.The neural mechanisms underlying suicidal behavior in adolescents with major ...BACKGROUND Suicide constitutes the second leading cause of death among adolescents globally and represents a critical public health concern.The neural mechanisms underlying suicidal behavior in adolescents with major depressive disorder(MDD)remain poorly understood.Aberrant resting-state functional connectivity(rsFC)in the amygdala,a key region implicated in emotional regulation and threat detection,is strongly implicated in depression and suicidal behavior.AIM To investigate rsFC alterations between amygdala subregions and whole-brain networks in adolescent patients with depression and suicide attempts.METHODS Resting-state functional magnetic resonance imaging data were acquired from 32 adolescents with MDD and suicide attempts(sMDD)group,33 adolescents with MDD but without suicide attempts(nsMDD)group,and 34 demographically matched healthy control(HC)group,with the lateral and medial amygdala(MeA)defined as regions of interest.The rsFC patterns of amygdala subregions were compared across the three groups,and associations between aberrant rsFC values and clinical symptom severity scores were examined.RESULTS Compared with the nsMDD group,the sMDD group exhibited reduced rsFC between the right lateral amygdala(LA)and the right inferior occipital gyrus as well as the left middle occipital gyrus.Compared with the HC group,the abnormal brain regions of rsFC in the sMDD group and nsMDD group involve the parahippocampal gyrus(PHG)and fusiform gyrus.In the sMDD group,right MeA and right temporal pole:Superior temporal gyrus rsFC value negatively correlated with the Rosenberg Self-Esteem Scale scores(r=-0.409,P=0.025),while left LA and right PHG rsFC value positively correlated with the Adolescent Self-Rating Life Events Checklist interpersonal relationship scores(r=0.372,P=0.043).CONCLUSION Aberrant rsFC changes between amygdala subregions and these brain regions provide novel insights into the underlying neural mechanisms of suicide attempts in adolescents with MDD.展开更多
BACKGROUND Dry eye disease(DED)is a multifactorial ocular surface disorder with rising prevalence.It is closely related to systemic health and psychological factors,such as sleep and mood disorders,which significantly...BACKGROUND Dry eye disease(DED)is a multifactorial ocular surface disorder with rising prevalence.It is closely related to systemic health and psychological factors,such as sleep and mood disorders,which significantly impact the quality of life of patients.AIM To explore the correlations between ocular surface function,sleep quality,and anxiety/depression in patients with DED.METHODS This was a cross-sectional investigative study that included 358 patients with DED between January 2022 and January 2025.Ocular surface was assessed using the ocular surface disease index(OSDI),tear film break-up time,fluorescein staining score,and Schirmer I test.The Pittsburgh Sleep Quality Index(PSQI),Self-Rating Anxiety Scale(SAS),and Self-Rating Depression Scale(SDS)were used to evaluate sleep quality and anxiety/depression levels.Correlation and linear regression analyses were used to explore the relationships.RESULTS The mean PSQI score of the patients was 9.94±2.18;the mean SAS score was 47.30±4.90,and the mean SDS score was 50.08±5.52.These suggested a prevalence of sleep and psychological abnormalities.There was a significant correlation between the indicators of ocular surface function(OSDI,tear film break-up time,fluorescein staining,and Schirmer I test)and PSQI,SAS,and SDS scores(P<0.05).Moreover,multiple regression revealed that age≥50 years(β=1.55,P=0.029),PSQI scores(β=0.58,P<0.001),SAS scores(β=0.17,P=0.017),and SDS scores(β=0.15,P=0.019)were independent predictors of the OSDI scores.CONCLUSION Ocular surface function in patients with DED is closely related to sleep quality and anxiety/depression,emphasizing the need for holistic clinical management.展开更多
BACKGROUND The therapeutic role of neurodynamic mobilization in improving lower limb function in patients with mild post-traumatic knee osteoarthritis remains poorly understood.AIM To further elucidate the role of neu...BACKGROUND The therapeutic role of neurodynamic mobilization in improving lower limb function in patients with mild post-traumatic knee osteoarthritis remains poorly understood.AIM To further elucidate the role of neurodynamic mobilization in facilitating knee joint functional recovery.METHODS Thirty-two patients with post-traumatic knee osteoarthritis treated at Chonghua Hospital of Traditional Chinese Medicine(Guilin)from March 2024 to August 2025 were randomly assigned to a control group(n=16)or an intervention group(n=16).Both groups received eight weeks of conventional treatment;and the intervention group additionally underwent neurodynamic mobilization.Outcomes including pain assessed by the visual analogue scale,active range of motion,Lysholm score,stork stand test,single hop test,and Y-balance test were assessed before and after the intervention.RESULTS There were no significant differences between the two groups in baseline characteristics,including gender,age,body mass index,or surgical side(P>0.05).Two-way repeated-measures analysis of variance demonstrated significant time×group interaction effects for the visual analogue scale score(F=13.364,P<0.05),Lysholm knee score(F=20.385,P<0.05),stork stand test(F=103.756,P<0.05),and Y-balance test score(F=8.089,P<0.05).CONCLUSION Neurodynamic mobilization effectively reduces pain,improves knee function,and enhances lower limb balance in patients with mild post-traumatic knee osteoarthritis.展开更多
AIM:To investigate the effects of shortening the duration of silicone oil tamponade on retinal structure and function in patients undergoing silicone oil removal(SOR)after surgery for primary rhegmatogenous retinal de...AIM:To investigate the effects of shortening the duration of silicone oil tamponade on retinal structure and function in patients undergoing silicone oil removal(SOR)after surgery for primary rhegmatogenous retinal detachment(RRD).METHODS:A total of 58 eligible patients were enrolled and randomly assigned to two groups based on tamponade duration:the short-term group(30-45d)and the conventional group(≥90d).Comprehensive evaluations were performed before and after SOR,including slitlamp examination,best-corrected visual acuity(BCVA)measurement,intraocular pressure(IOP)testing,optical coherence tomography(OCT),optical coherence tomography angiography(OCTA),microperimetry,electroretinography(ERG),and visual evoked potential(VEP)assessment.RESULTS:A total of 33 patients(23 males and 10 females;33 eyes)were enrolled in the short-term SO tamponade group with mean age of 52.45±9.35y,and 25 patients(15 males and 10 females;25 eyes)were enrolled in the conventional SO tamponade group with mean age of 50.80±12.06y.Compared with the conventional group,the short-term silicone oil tamponade group had a significantly lower incidence of silicone oil emulsification and cataract progression,with no significant difference in retinal reattachment success rate.Structurally,short-term tamponade was associated with increased thickness of the retinal ganglion cell layer(RGCL)in the nasal and superior macular regions and improved recovery of superficial retinal vascular density in these areas.Functionally,the shortterm group showed better BCVA and retinal sensitivity both before and 1mo after SOR;additionally,the P100 amplitude in VEP tests was significantly increased in this group.CONCLUSION:Shortening the duration of silicone oil tamponade effectively reduces damage to retinal structure and function without compromising the success rate of retinal reattachment in patients with primary RRD.展开更多
Amphibious vehicles are more prone to attitude instability compared to ships,making it crucial to develop effective methods for monitoring instability risks.However,large inclination events,which can lead to instabili...Amphibious vehicles are more prone to attitude instability compared to ships,making it crucial to develop effective methods for monitoring instability risks.However,large inclination events,which can lead to instability,occur frequently in both experimental and operational data.This infrequency causes events to be overlooked by existing prediction models,which lack the precision to accurately predict inclination attitudes in amphibious vehicles.To address this gap in predicting attitudes near extreme inclination points,this study introduces a novel loss function,termed generalized extreme value loss.Subsequently,a deep learning model for improved waterborne attitude prediction,termed iInformer,was developed using a Transformer-based approach.During the embedding phase,a text prototype is created based on the vehicle’s operation log data is constructed to help the model better understand the vehicle’s operating environment.Data segmentation techniques are used to highlight local data variation features.Furthermore,to mitigate issues related to poor convergence and slow training speeds caused by the extreme value loss function,a teacher forcing mechanism is integrated into the model,enhancing its convergence capabilities.Experimental results validate the effectiveness of the proposed method,demonstrating its ability to handle data imbalance challenges.Specifically,the model achieves over a 60%improvement in root mean square error under extreme value conditions,with significant improvements observed across additional metrics.展开更多
Spinal cord injury(SCI) often results in permanent dysfunction of locomotion,sensation,and autonomic regulation,imposing a substantial burden on both individuals and society(Anjum et al.,2020).SCI has a complex pathop...Spinal cord injury(SCI) often results in permanent dysfunction of locomotion,sensation,and autonomic regulation,imposing a substantial burden on both individuals and society(Anjum et al.,2020).SCI has a complex pathophysiology:an initial primary injury(mechanical trauma,axonal disruption,and hemorrhage) is followed by a progressive secondary injury cascade that involves ischemia,neuronal loss,and inflammation.Given the challenges in achieving regeneration of the injured spinal cord,neuroprotection has been at the forefront of clinical research.展开更多
Exogenous neural stem cell transplantation has become one of the most promising treatment methods for chronic stroke.Recent studies have shown that most ischemia-reperfusion model rats recover spontaneously after inju...Exogenous neural stem cell transplantation has become one of the most promising treatment methods for chronic stroke.Recent studies have shown that most ischemia-reperfusion model rats recover spontaneously after injury,which limits the ability to observe long-term behavioral recovery.Here,we used a severe stroke rat model with 150 minutes of ischemia,which produced severe behavioral deficiencies that persisted at 12 weeks,to study the therapeutic effect of neural stem cells on neural restoration in chronic stroke.Our study showed that stroke model rats treated with human neural stem cells had long-term sustained recovery of motor function,reduced infarction volume,long-term human neural stem cell survival,and improved local inflammatory environment and angiogenesis.We also demonstrated that transplanted human neural stem cells differentiated into mature neurons in vivo,formed stable functional synaptic connections with host neurons,and exhibited the electrophysiological properties of functional mature neurons,indicating that they replaced the damaged host neurons.The findings showed that human fetal-derived neural stem cells had long-term effects for neurological recovery in a model of severe stroke,which suggests that human neural stem cells-based therapy may be effective for repairing damaged neural circuits in stroke patients.展开更多
The organization of biological neuronal networks into functional modules has intrigued scientists and inspired engineers to develop artificial systems.These networks are characterized by two key properties.First,they ...The organization of biological neuronal networks into functional modules has intrigued scientists and inspired engineers to develop artificial systems.These networks are characterized by two key properties.First,they exhibit dense interconnectivity(Braitenburg and Schüz,1998;Campagnola et al.,2022).The strength and probability of connectivity depend on cell type,inter-neuronal distance,and species.Still,every cortical neuron receives input from thousands of other neurons while transmitting output to a similar number of neurons.Second,communication between neurons occurs primarily via chemical or electrical synapses.展开更多
基金supported by the National Natural Science Foundation of China(No.41874058).
文摘Ambient noise tomography(ANT)has been widely used to image crust and upmost mantle structures.ANT assumes that sources of ambient noise are diffuse and evenly distributed in space and the energy of different modes is equipartitioned.At present,the sources of the primary and the secondary microseisms are well studied,but there are only a few on the studies of long-period ambient noise sources.In this study,we study the effects of large earthquake signals on the recovery of surface waves from seismic ambient noise data recorded by seismic stations from the US permanent networks and Global Seismographic Network(GSN).Our results show that large earthquake signals play an important role on the recovery of long-period surface waves from ambient noise cross-correlation functions.Our results are consistent with previous studies that suggest the contribution of earthquake signals to the recovery of surface waves from cross-correlations of ambient noise is dominant at periods larger than 20–40 s.
文摘The cyclic cross-correlation between a stationary process and a cyclostationary process at cycle frequency α(≠ 0)is identically zero under an ideal condition, which indicates that a cyclic cross-correlation method performs much better than the conventional cross-correlation method in suppressing the stationary noise or interference. But unfortunately, the cyclic cross-correlation will not really approach zero due to the limited data length in some real conditions. In this paper, the quantitative relation between the data length and the estimated cyclic cross-correlation is deduced, and some useful conclusions are drawn, which are proven by some computer simulations. The conclusion in this paper is really useful for the practical application of cyclostationary signal processing.
基金financially supported by the Important National Science&Technology Specific Project of China(Grant No.2017ZX05018-005)
文摘Model-driven and data-driven inversions are two prominent methods for obtaining P-wave impedance,which is significant in reservoir description and identification.Based on proper initial models,most model-driven methods primarily use the limited frequency bandwidth information of seismic data and can invert P-wave impedance with high accuracy,but not high resolution.Conventional data-driven methods mainly employ the information from well-log data and can provide high-accuracy and highresolution P-wave impedance owing to the superior nonlinear curve fitting capacity of neural networks.However,these methods require a significant number of training samples,which are frequently insufficient.To obtain P-wave impedance with both high accuracy and high resolution,we propose a model-data-driven inversion method using Res Nets and the normalized zero-lag cross-correlation objective function which is effective for avoiding local minima and suppressing random noise.By using initial models and training samples,the proposed model-data-driven method can invert P-wave impedance with satisfactory accuracy and resolution.Tests on synthetic and field data demonstrate the proposed method’s efficacy and practicability.
文摘The improved cross-correlation algorithm for the strain demodulation of Vernier-effect-based optical fiber sensor(VE-OFS)is proposed in this article.The algorithm identifies the most similar spectrum to the measured one from the database of the collected spectra by employing the cross-correlation operation,subsequently deriving the predicted value via weighted calculation.As the algorithm uses the complete information in the measured raw spectrum,more accurate results and larger measurement range can be obtained.Additionally,the improved cross-correlation algorithm also has the potential to improve the measurement speed compared to current standards due to the possibility for the collection using low sampling rate.This work presents an important algorithm towards a simpler,faster way to improve the demodulation performance of VE-OFS.
基金Project supported by the National Natural Science Foundation of China (Grant Nos. 11875042 and 11505114)the Shanghai Project for Construction of Top Disciplines (Grant No. USST-SYS-01)。
文摘Detecting coupling pattern between elements in a complex system is a basic task in data-driven analysis. The trajectory for each specific element is a cooperative result of its intrinsic dynamic, its couplings with other elements, and the environment. It is subsequently composed of many components, only some of which take part in the couplings. In this paper we present a framework to detect the component correlation pattern. Firstly, the interested trajectories are decomposed into components by using decomposing methods such as the Fourier expansion and the Wavelet transformation. Secondly, the cross-correlations between the components are calculated, resulting into a component cross-correlation matrix(network).Finally, the dominant structure in the network is identified to characterize the coupling pattern in the system. Several deterministic dynamical models turn out to be characterized with rich structures such as the clustering of the components. The pattern of correlation between respiratory(RESP) and ECG signals is composed of five sub-clusters that are mainly formed by the components in ECG signal. Interestingly, only 7 components from RESP(scattered in four sub-clusters) take part in the realization of coupling between the two signals.
文摘Traditional cross-correlation algorithms are prone to time-of-flight(TOF)calculation errors under conditions of strong noise interference and complex temperature gradients,resulting in a decline in the accuracy of ultrasonic temperature measurement.To this end,this paper proposes an ultrasonic temperature measurement method that combines YOLOv11 target detection with energy-type weighted cross-correlation algorithm.The YOLOv11 model is utilized to conduct target detection and key area positioning on the ultrasonic signal waveform diagram,automatically identifying characteristic waveforms such as node waves and end face waves,and achieving adaptive extraction of the effective signal interval.Further introduce the energy-based weighted cross-correlation algorithm.Based on the signal energy distribution,the cross-correlation results are weighted and processed to enhance the main wave response and suppress noise interference.Experiments show that the YOLOv11 model has high detection accuracy(Precision=0.987,Recall=0.958,mAP@50=0.988);The proposed method maintains the stability of time delay estimation under strong noise and high temperature(>1200℃),with the average time delay error reduced by approximately 35%to 50%compared to traditional algorithms.This verifies its high robustness and temperature measurement accuracy in complex environments,and it has a promising engineering application prospect.
基金supported by National Natural Science Foundation of China(No.61973234)Tianjin Science and Technology Plan Project(No.22YDTPJC00090)。
文摘To address the issue of low measurement accuracy caused by noise interference in the acquisition of low fluid flow rate signals with ultrasonic Doppler flow meters,a novel signal processing algorithm that combines ensemble empirical mode decomposition(EEMD)and cross-correlation algorithm was proposed.Firstly,a fast Fourier transform(FFT)spectrum analysis was utilized to ascertain the frequency range of the signal.Secondly,data acquisition was conducted at an appropriate sampling frequency,and the acquired Doppler flow rate signal was then decomposed into a series of intrinsic mode functions(IMFs)by EEMD.Subsequently,these decomposed IMFs were recombined based on their energy entropy,and then the noise of the recombined Doppler flow rate signal was removed by cross-correlation filtering.Finally,an ideal ultrasonic Doppler flow rate signal was extracted.Simulation and experimental verification show that the proposed Doppler flow signal processing method can effectively enhance the signal-to-noise ratio(SNR)and extend the lower limit of measurement of the ultrasonic Doppler flow meter.
基金Supported by the National Basic Research Program of China(2012CB025904)Zhengzhou Shengda University of Economics,Business and Management(SD-YB2025085)。
文摘Gauss radial basis functions(GRBF)are frequently employed in data fitting and machine learning.Their linear independence property can theoretically guarantee the avoidance of data redundancy.In this paper,one of the main contributions is proving this property using linear algebra instead of profound knowledge.This makes it easy to read and understand this fundamental fact.The proof of linear independence of a set of Gauss functions relies on the constructing method for one-dimensional space and on the deducing method for higher dimensions.Additionally,under the condition of preserving the same moments between the original function and interpolating function,both the interpolating existence and uniqueness are proven for GRBF in one-dimensional space.The final work demonstrates the application of the GRBF method to locate lunar olivine.By combining preprocessed data using GRBF with the removing envelope curve method,a program is created to find the position of lunar olivine based on spectrum data,and the numerical experiment shows that it is an effective scheme.
基金supported by the National Natural Science Foundation of China,Nos.82072165 and 82272256(both to XM)the Key Project of Xiangyang Central Hospital,No.2023YZ03(to RM)。
文摘Spinal cord injury represents a severe form of central nervous system trauma for which effective treatments remain limited.Microglia is the resident immune cells of the central nervous system,play a critical role in spinal cord injury.Previous studies have shown that microglia can promote neuronal survival by phagocytosing dead cells and debris and by releasing neuroprotective and anti-inflammatory factors.However,excessive activation of microglia can lead to persistent inflammation and contribute to the formation of glial scars,which hinder axonal regeneration.Despite this,the precise role and mechanisms of microglia during the acute phase of spinal cord injury remain controversial and poorly understood.To elucidate the role of microglia in spinal cord injury,we employed the colony-stimulating factor 1 receptor inhibitor PLX5622 to deplete microglia.We observed that sustained depletion of microglia resulted in an expansion of the lesion area,downregulation of brain-derived neurotrophic factor,and impaired functional recovery after spinal cord injury.Next,we generated a transgenic mouse line with conditional overexpression of brain-derived neurotrophic factor specifically in microglia.We found that brain-derived neurotrophic factor overexpression in microglia increased angiogenesis and blood flow following spinal cord injury and facilitated the recovery of hindlimb motor function.Additionally,brain-derived neurotrophic factor overexpression in microglia reduced inflammation and neuronal apoptosis during the acute phase of spinal cord injury.Furthermore,through using specific transgenic mouse lines,TMEM119,and the colony-stimulating factor 1 receptor inhibitor PLX73086,we demonstrated that the neuroprotective effects were predominantly due to brain-derived neurotrophic factor overexpression in microglia rather than macrophages.In conclusion,our findings suggest the critical role of microglia in the formation of protective glial scars.Depleting microglia is detrimental to recovery of spinal cord injury,whereas targeting brain-derived neurotrophic factor overexpression in microglia represents a promising and novel therapeutic strategy to enhance motor function recovery in patients with spinal cord injury.
文摘By using the linear approximation method, the intensity correlation function is calculated for a single-mode laser modulated by a bias signal and driven by colored pump and quantum noises with colored cross-correlation. We found that, when the correlation time between the two noises is very short, the behavior of the intensity correlation function versus the time, in addition to decreasing monotonously, also exhibits several cases, such as one maximum, one minimum, and two extrema. When the correlation time between the two noises is very long, the behavior of the intensity correlation function exhibits oscillation and the envelope is similar to the case of short cross-correlation time.
基金Supported by The Natural Science Foundation of China,No.82374292the Plans for Major Provincial Science and Technology Projects of Anhui Province,No.202303a07020003the Innovation Team and Talents Cultivation Program of the National Administration of Traditional Chinese Medicine,No.ZYYCXTD-C-202401.
文摘Functional gastrointestinal disorders(FGIDs),including irritable bowel syndrome(IBS),functional dyspepsia(FD),and gastroesophageal reflux disease(GERD),present persistent diagnostic and therapeutic challenges due to symptom heterogeneity and the absence of reliable biomarkers.Artificial intelligence(AI)enables the integration of multimodal data to enhance FGID management through precision diagnostics and preventive healthcare.This minireview summarizes recent advancements in AI applications for FGIDs,highlighting progress in diagnostic accuracy,subtype classification,personalized interventions,and preventive strategies inspired by the traditional Chinese medicine concept of“treating the undiseased”.Machine learning and deep learning algorithms have demonstrated value in improving IBS diagnosis,refining FD neuro-gastrointestinal subtyping,and screening for GERD-related complications.Moreover,AI supports dietary,psychological,and integrative medicine-based interventions to improve patient adherence and quality of life.Nonetheless,key challenges remain,including data heterogeneity,limited model interpretability,and the need for robust clinical validation.Future directions emphasize interdisciplinary collaboration,the development of multimodal and explainable AI models,and the creation of patientcentered platforms to facilitate a shift from reactive treatment to proactive prevention.This review provides a systematic framework to guide the clinical application and theoretical innovation of AI in FGIDs.
文摘BACKGROUND An echocardiogram is an essential tool in the evaluation of potential kidney transplant recipients(KTRs).Despite cardiac clearance,potential KTRs still have structural and functional abnormalities.Identifying the prevalence of these abnormalities and understanding their predictors is vital for optimizing pretransplant risk stratification and improving post-transplant outcomes.AIM To determine the prevalence of left ventricular hypertrophy(LVH),left ventricular systolic dysfunction(LVSD),diastolic dysfunction(DD),pulmonary hypertension(PH),and their predictors,and to assess their impact on graft function in pre-transplant candidates.METHODS The study included all successful transplant candidates older than 14 who had a baseline echocardiogram.Binary logistic regression models were constructed to identify factors associated with LVH,LVSD,DD,and PH.RESULTS Out of 259 patients,LVH was present in 64%(166),12%(31)had LVSD,27.5%(71)had DD,and 66(25.5%)had PH.Independent predictors of LVH included male gender[odds ratio(OR):2.51;95%CI:1.17-5.41 P=0.02],PH(OR=2.07;95%CI:1.11-3.86;P=0.02),DD(OR:2.47;95%CI:1.29-4.73;P=0.006),and dyslipidemia(OR=1.94;95%CI:1.07-3.53;P=0.03).Predictors for LVSD included patients with DD(OR=3.3,95%CI:1.41-7.81;P=0.006)and a family history of coronary artery disease(OR=4.50,95%CI:1.33-15.20;P=0.015).Peritoneal dialysis was an independent predictor for DD(OR=10.03;95%CI:1.71-58.94,P=0.011).The presence of LVH(OR=3.32,95%CI:1.05-10.55,P=0.04)and mild to moderate or moderate to severe mitral regurgitation(OR=4.63,95%CI:1.45-14.78,P=0.01)were significant factors associated with PH.These abnormalities had no significant impact on estimated glomerular filtration at discharge,6 months,1 year,or 2 years post-transplant.CONCLUSION Significant echocardiographic abnormalities persist in a potential transplant candidate despite cardiac clearance,although they don’t affect future graft function.Understanding the risk factors associated with these abnormalities may help clinicians address these factors pre-and post-transplant to achieve better outcomes.
基金Supported by Suzhou Clinical Medical Center for Mood Disorders,No.Szlcyxzx202109Suzhou Key Laboratory,No.SZS2024016Multicenter Clinical Research on Major Diseases in Suzhou,No.DZXYJ202413.
文摘BACKGROUND Suicide constitutes the second leading cause of death among adolescents globally and represents a critical public health concern.The neural mechanisms underlying suicidal behavior in adolescents with major depressive disorder(MDD)remain poorly understood.Aberrant resting-state functional connectivity(rsFC)in the amygdala,a key region implicated in emotional regulation and threat detection,is strongly implicated in depression and suicidal behavior.AIM To investigate rsFC alterations between amygdala subregions and whole-brain networks in adolescent patients with depression and suicide attempts.METHODS Resting-state functional magnetic resonance imaging data were acquired from 32 adolescents with MDD and suicide attempts(sMDD)group,33 adolescents with MDD but without suicide attempts(nsMDD)group,and 34 demographically matched healthy control(HC)group,with the lateral and medial amygdala(MeA)defined as regions of interest.The rsFC patterns of amygdala subregions were compared across the three groups,and associations between aberrant rsFC values and clinical symptom severity scores were examined.RESULTS Compared with the nsMDD group,the sMDD group exhibited reduced rsFC between the right lateral amygdala(LA)and the right inferior occipital gyrus as well as the left middle occipital gyrus.Compared with the HC group,the abnormal brain regions of rsFC in the sMDD group and nsMDD group involve the parahippocampal gyrus(PHG)and fusiform gyrus.In the sMDD group,right MeA and right temporal pole:Superior temporal gyrus rsFC value negatively correlated with the Rosenberg Self-Esteem Scale scores(r=-0.409,P=0.025),while left LA and right PHG rsFC value positively correlated with the Adolescent Self-Rating Life Events Checklist interpersonal relationship scores(r=0.372,P=0.043).CONCLUSION Aberrant rsFC changes between amygdala subregions and these brain regions provide novel insights into the underlying neural mechanisms of suicide attempts in adolescents with MDD.
文摘BACKGROUND Dry eye disease(DED)is a multifactorial ocular surface disorder with rising prevalence.It is closely related to systemic health and psychological factors,such as sleep and mood disorders,which significantly impact the quality of life of patients.AIM To explore the correlations between ocular surface function,sleep quality,and anxiety/depression in patients with DED.METHODS This was a cross-sectional investigative study that included 358 patients with DED between January 2022 and January 2025.Ocular surface was assessed using the ocular surface disease index(OSDI),tear film break-up time,fluorescein staining score,and Schirmer I test.The Pittsburgh Sleep Quality Index(PSQI),Self-Rating Anxiety Scale(SAS),and Self-Rating Depression Scale(SDS)were used to evaluate sleep quality and anxiety/depression levels.Correlation and linear regression analyses were used to explore the relationships.RESULTS The mean PSQI score of the patients was 9.94±2.18;the mean SAS score was 47.30±4.90,and the mean SDS score was 50.08±5.52.These suggested a prevalence of sleep and psychological abnormalities.There was a significant correlation between the indicators of ocular surface function(OSDI,tear film break-up time,fluorescein staining,and Schirmer I test)and PSQI,SAS,and SDS scores(P<0.05).Moreover,multiple regression revealed that age≥50 years(β=1.55,P=0.029),PSQI scores(β=0.58,P<0.001),SAS scores(β=0.17,P=0.017),and SDS scores(β=0.15,P=0.019)were independent predictors of the OSDI scores.CONCLUSION Ocular surface function in patients with DED is closely related to sleep quality and anxiety/depression,emphasizing the need for holistic clinical management.
基金Supported by the Central Guided Local Science and Technology Development Fund Project for Science and Technology Innovation Base Construction,No.Guike ZY24212046National Natural Science Foundation of China,No.U22A2092+3 种基金Guangxi Education Science“the 14th Five-Year Plan”2024 Special Project“Research on Steam Education Practice in Rehabilitation Engineering”,No.2024ZJY304the Research Basic Ability Enhancement Program for Young and Middle-aged Teachers of Guangxi,No.2025KY2255the Innovation Project of GUET Graduate Education,No.2025YCXB010Natural Science Research Project of Guilin Life and Health Career Technical College,No.2025GKKY04.
文摘BACKGROUND The therapeutic role of neurodynamic mobilization in improving lower limb function in patients with mild post-traumatic knee osteoarthritis remains poorly understood.AIM To further elucidate the role of neurodynamic mobilization in facilitating knee joint functional recovery.METHODS Thirty-two patients with post-traumatic knee osteoarthritis treated at Chonghua Hospital of Traditional Chinese Medicine(Guilin)from March 2024 to August 2025 were randomly assigned to a control group(n=16)or an intervention group(n=16).Both groups received eight weeks of conventional treatment;and the intervention group additionally underwent neurodynamic mobilization.Outcomes including pain assessed by the visual analogue scale,active range of motion,Lysholm score,stork stand test,single hop test,and Y-balance test were assessed before and after the intervention.RESULTS There were no significant differences between the two groups in baseline characteristics,including gender,age,body mass index,or surgical side(P>0.05).Two-way repeated-measures analysis of variance demonstrated significant time×group interaction effects for the visual analogue scale score(F=13.364,P<0.05),Lysholm knee score(F=20.385,P<0.05),stork stand test(F=103.756,P<0.05),and Y-balance test score(F=8.089,P<0.05).CONCLUSION Neurodynamic mobilization effectively reduces pain,improves knee function,and enhances lower limb balance in patients with mild post-traumatic knee osteoarthritis.
基金Supported by the Key Science&Technology Project of Guangzhou(No.202103000045)the National Natural Science Foundation of China(No.82070972,No.82271093).
文摘AIM:To investigate the effects of shortening the duration of silicone oil tamponade on retinal structure and function in patients undergoing silicone oil removal(SOR)after surgery for primary rhegmatogenous retinal detachment(RRD).METHODS:A total of 58 eligible patients were enrolled and randomly assigned to two groups based on tamponade duration:the short-term group(30-45d)and the conventional group(≥90d).Comprehensive evaluations were performed before and after SOR,including slitlamp examination,best-corrected visual acuity(BCVA)measurement,intraocular pressure(IOP)testing,optical coherence tomography(OCT),optical coherence tomography angiography(OCTA),microperimetry,electroretinography(ERG),and visual evoked potential(VEP)assessment.RESULTS:A total of 33 patients(23 males and 10 females;33 eyes)were enrolled in the short-term SO tamponade group with mean age of 52.45±9.35y,and 25 patients(15 males and 10 females;25 eyes)were enrolled in the conventional SO tamponade group with mean age of 50.80±12.06y.Compared with the conventional group,the short-term silicone oil tamponade group had a significantly lower incidence of silicone oil emulsification and cataract progression,with no significant difference in retinal reattachment success rate.Structurally,short-term tamponade was associated with increased thickness of the retinal ganglion cell layer(RGCL)in the nasal and superior macular regions and improved recovery of superficial retinal vascular density in these areas.Functionally,the shortterm group showed better BCVA and retinal sensitivity both before and 1mo after SOR;additionally,the P100 amplitude in VEP tests was significantly increased in this group.CONCLUSION:Shortening the duration of silicone oil tamponade effectively reduces damage to retinal structure and function without compromising the success rate of retinal reattachment in patients with primary RRD.
基金Supported by the National Defense Basic Scientific Research Program of China.
文摘Amphibious vehicles are more prone to attitude instability compared to ships,making it crucial to develop effective methods for monitoring instability risks.However,large inclination events,which can lead to instability,occur frequently in both experimental and operational data.This infrequency causes events to be overlooked by existing prediction models,which lack the precision to accurately predict inclination attitudes in amphibious vehicles.To address this gap in predicting attitudes near extreme inclination points,this study introduces a novel loss function,termed generalized extreme value loss.Subsequently,a deep learning model for improved waterborne attitude prediction,termed iInformer,was developed using a Transformer-based approach.During the embedding phase,a text prototype is created based on the vehicle’s operation log data is constructed to help the model better understand the vehicle’s operating environment.Data segmentation techniques are used to highlight local data variation features.Furthermore,to mitigate issues related to poor convergence and slow training speeds caused by the extreme value loss function,a teacher forcing mechanism is integrated into the model,enhancing its convergence capabilities.Experimental results validate the effectiveness of the proposed method,demonstrating its ability to handle data imbalance challenges.Specifically,the model achieves over a 60%improvement in root mean square error under extreme value conditions,with significant improvements observed across additional metrics.
文摘Spinal cord injury(SCI) often results in permanent dysfunction of locomotion,sensation,and autonomic regulation,imposing a substantial burden on both individuals and society(Anjum et al.,2020).SCI has a complex pathophysiology:an initial primary injury(mechanical trauma,axonal disruption,and hemorrhage) is followed by a progressive secondary injury cascade that involves ischemia,neuronal loss,and inflammation.Given the challenges in achieving regeneration of the injured spinal cord,neuroprotection has been at the forefront of clinical research.
文摘Exogenous neural stem cell transplantation has become one of the most promising treatment methods for chronic stroke.Recent studies have shown that most ischemia-reperfusion model rats recover spontaneously after injury,which limits the ability to observe long-term behavioral recovery.Here,we used a severe stroke rat model with 150 minutes of ischemia,which produced severe behavioral deficiencies that persisted at 12 weeks,to study the therapeutic effect of neural stem cells on neural restoration in chronic stroke.Our study showed that stroke model rats treated with human neural stem cells had long-term sustained recovery of motor function,reduced infarction volume,long-term human neural stem cell survival,and improved local inflammatory environment and angiogenesis.We also demonstrated that transplanted human neural stem cells differentiated into mature neurons in vivo,formed stable functional synaptic connections with host neurons,and exhibited the electrophysiological properties of functional mature neurons,indicating that they replaced the damaged host neurons.The findings showed that human fetal-derived neural stem cells had long-term effects for neurological recovery in a model of severe stroke,which suggests that human neural stem cells-based therapy may be effective for repairing damaged neural circuits in stroke patients.
基金supported in part by the Rosetrees Trust(#CF-2023-I-2_113)by the Israel Ministry of Innovation,Science,and Technology(#7393)(to ES).
文摘The organization of biological neuronal networks into functional modules has intrigued scientists and inspired engineers to develop artificial systems.These networks are characterized by two key properties.First,they exhibit dense interconnectivity(Braitenburg and Schüz,1998;Campagnola et al.,2022).The strength and probability of connectivity depend on cell type,inter-neuronal distance,and species.Still,every cortical neuron receives input from thousands of other neurons while transmitting output to a similar number of neurons.Second,communication between neurons occurs primarily via chemical or electrical synapses.
