Surface-related multiples frequently propagate into the subsurface and contain abundant information on small reflection angles.Compared with the conventional migration of primaries,migration of multiples offers comple...Surface-related multiples frequently propagate into the subsurface and contain abundant information on small reflection angles.Compared with the conventional migration of primaries,migration of multiples offers complementary illumination and a higher vertical resolution.However,crosstalk artifacts caused by unrelated multiples during reverse time migration(RTM)using multiples severely degrade the reliability and interpretation of the final migration images.Therefore,we proposed RTM using first-order receiver-side water-bottom-related multiples for eliminating crosstalk artifacts and enhancing vertical resolution.We first backward propagate the first-order receiver-side water-bottom-related multiples using a water-layer model,followed by saving the upper boundary wavefield.Then we produce the source wavefield using a seismic wavelet and the receiver wavefield by back-extrapolating the saved boundary.Finally,the cross-correlation imaging condition is applied to generate the final image.This method transforms the receiver-side multiples into primaries,followed by the conventional migration processing procedures.Numerical examples using synthetic datasets demonstrate that our method significantly enhances the imaging quality by eliminating crosstalk artifacts and improving the resolution.展开更多
In this research, we present a seismic trace interpolation method which uses seismic data with surface-related multiples. It is different from conventional seismic data interpolation using information transformation o...In this research, we present a seismic trace interpolation method which uses seismic data with surface-related multiples. It is different from conventional seismic data interpolation using information transformation or extrapolation of adjacent channels for reconstruction of missing seismic data. In this method there are two steps, first, we construct pseudo-primaries by cross-correlation of surface multiple data to extract the missing near- offset information in multiples, which are not displayed in the acquired seismic record. Second, we correct the pseudo-primaries by applying a Least-squares Matching Filter （LMF） and RMS amplitude correction method in time and space sliding windows. Then the corrected pseudo-primaries can be used to fill the data gaps. The method is easy to implement, without the need to separate multiples and primaries. It extracts the seismic information contained by multiples for filling missing traces. The method is suitable for seismic data with surfacerelated multiples.展开更多
Multiple suppression is an important element of marine seismic data processing.Intelligent suppression of multiples us-ing artificial intelligence reduces labor costs,minimizes dependence on unknown prior information,...Multiple suppression is an important element of marine seismic data processing.Intelligent suppression of multiples us-ing artificial intelligence reduces labor costs,minimizes dependence on unknown prior information,and improves data processing ef-ficiency.In this study,we propose an intelligent method for suppressing marine seismic multiples using deep learning approaches.The proposed method enables the intelligent suppression of free-surface-related multiples from seismic records.Initially,we construct a multi-category marine seismic multiple dataset through finite difference forward modeling under different boundary conditions.We use various models and data augmentation methods,including sample rotation,noise addition,and random channel omission.Then,we apply depthwise separable convolution to develop our deep learning Mobilenet-Unet model.The Mobilenet-Unet framework sig-nificantly reduces the number of operations required for multiple elimination without sacrificing model performance,ultimately reali-zing the optimal multiple suppression model.The trained Mobilenet-Unet is applied to the test set for verification.Moreover,to deter-mine its generalization ability,it is implemented to seismic records containing multiples generated by two marine geophysical models that were not included in the training process.The performance of Mobilenet-Unet is also compared with that of different network structures.The results indicate that,despite its small size,our proposed Mobilenet-Unet deep learning model can rapidly and effective-ly separate multiples in marine seismic data,possessing reasonable generalization ability.展开更多
The deep convolutional neural network U-net has been introduced into adaptive subtraction, which is a critical step in effectively suppressing seismic multiples. The U-net approach has higher precision than the tradit...The deep convolutional neural network U-net has been introduced into adaptive subtraction, which is a critical step in effectively suppressing seismic multiples. The U-net approach has higher precision than the traditional linear regression approach. However, the existing 2D U-net approach with 2D data windows can not deal with elaborate discrepancies between the actual and simulated multiples along the gather direction. It may lead to erroneous preservation of primaries or generate obvious vestigial multiples, especially in complex media. To further enhance the multiple suppression accuracy, we present an adaptive subtraction approach utilizing 3D U-net architecture, which can adaptively separate primaries and multiples utilizing 3D windows. The utilization of 3D windows allows for enhanced depiction of spatial continuity and anisotropy of seismic events along the gather direction in comparison to 2D windows. The 3D U-net approach with 3D windows can more effectively preserve the continuity of primaries and manage the complex disparities between the actual and simulated multiples. The proposed 3D U-net approach exhibits 1 dB improvement in the signal-to-noise ratio compared to the 2D U-net approach, as observed in the synthesis data section, and exhibits more outstanding performance in the preservation of primaries and removal of residual multiples in both synthesis and reality data sections. Moreover, to expedite network training in our proposed 3D U-net approach we employ the transfer learning (TL) strategy by utilizing the network parameters of 3D U-net estimated in the preceding data segment as the initial network parameters of 3D U-net for the subsequent data segment. In the reality data section, the 3D U-net approach incorporating TL reduces the computational expense by 70% compared to the one without TL.展开更多
In practical seismic exploration, internal multiples generated when the wave impedance of medium is strong, and seismic records are recorded. The method of virtual event repress internal multiples is to move scattered...In practical seismic exploration, internal multiples generated when the wave impedance of medium is strong, and seismic records are recorded. The method of virtual event repress internal multiples is to move scattered points from underground to the surface, similar to the method of the surface-related multiple elimination (SRME). The method of SRME belongs to the prediction-subtraction approaches to eliminate internal multiples, prediction method is based on building a brand new way of seismic wave propagation (virtual reflection and virtual event), so that it has forward and backward wave propagation, and through convolution with significant wave to predict the internal multiples. Due to required data needing field information of full-wave, the authors use Seislet transform interpolating the missing data to ensure the premise of internal multiples prediction. The test data show that the above method has achieved good results.展开更多
The attenuation of prestack internal multiples based on virtual seismic events is computationally costly and hinders seismic data processing. We propose a multiples attenuation method for poststack seismic data by app...The attenuation of prestack internal multiples based on virtual seismic events is computationally costly and hinders seismic data processing. We propose a multiples attenuation method for poststack seismic data by approximating conventional virtual events. The proposed method is iterative. The proposed method is tested using 2D synthetic and the field poststack seismic datasets. Compared with the conventional virtual events method, the proposed method does not require data regularization and offers higher computation efficiency. The method requires to know the travel time of the primary reflection waves. The results of the application to 2D field datasets suggest that the proposed method attenuates the internal multiples while highlighting the deep primaries.展开更多
In marine seismic exploration,especially in deep-water and hard ocean-bottom cases,free-surface multiples are strongly developed.Compared with primary waves,the wider illumination aperture of the multiples is benefici...In marine seismic exploration,especially in deep-water and hard ocean-bottom cases,free-surface multiples are strongly developed.Compared with primary waves,the wider illumination aperture of the multiples is beneficial for high-resolution seismic imaging.In this study,by introducing a new compound source composed of primaries and free-surface multiples and by ignoring internal multiples,we derive a new linearized forward problem(free-surface-multiple prediction model)under a weak-scattering assumption(i.e.,first-order Born approximation).On the basis of the new linearized problem,we propose a joint inversion-imaging method by simultaneously using the primaries and free-surface multiples under the general framework of least square inversion.To eliminate the crosstalk artifacts introduced by the cross-correlation of multiples with different orders,we prove that the crosstalk artifacts can be gradually eliminated during the inversion if a proper step length is selected.Synthetic-andfield-data tests demonstrate the effectiveness of the proposed method.展开更多
A new three-dimensional fundamental solution to the Stokes flow was proposed by transforming the solid harmonic functions in Lamb's solution into expressions in terms Of the oblate spheroidal coordinates. These fu...A new three-dimensional fundamental solution to the Stokes flow was proposed by transforming the solid harmonic functions in Lamb's solution into expressions in terms Of the oblate spheroidal coordinates. These fundamental solutions are advantageous in treating flows past an arbitrary number of arbitrarily positioned and oriented oblate spheroids. The least squares technique was adopted herein so that the convergence difficulties often encountered in solving three-dimensional problems were completely avoided. The examples demonstrate that present approach is highly accurate, consistently stable and computationally efficient. The oblate spheroid may be used to model a variety of particle shapes between a circular disk and a sphere. For the first time, the effect of various geometric factors on the forces and torques exerted on two oblate spheroids were systematically studied by using the proposed fundamental solutions. The generality of this approach was illustrated by two problems of three spheroids.展开更多
The Hartree-Fock equation is non-linear and has, in principle, multiple solutions. The ωth HF extreme and its associated virtual spin-orbitals furnish an orthogonal base Bω of the full configuration interaction spac...The Hartree-Fock equation is non-linear and has, in principle, multiple solutions. The ωth HF extreme and its associated virtual spin-orbitals furnish an orthogonal base Bω of the full configuration interaction space. Although all Bω bases generate the same CI space, the corresponding configurations of each Bω base have distinct quantum-mechanical information contents. In previous works, we have introduced a multi-reference configuration interaction method, based on the multiple extremes of the Hartree-Fock problem. This method was applied to calculate the permanent electrical dipole and quadrupole moments of some small molecules using minimal and double, triple and polarized double-zeta bases. In all cases were possible, using a reduced number of configurations, to obtain dipole and quadrupole moments in close agreement with the experimental values and energies without compromising the energy of the state function. These results show the positive effect of the use of the multi-reference Hartree-Fock bases that allowed a better extraction of quantum mechanical information from the several Bω bases. But to extend these ideas for larger systems and atomic bases, it is necessary to develop criteria to build the multireference Hartree-Fock bases. In this project, we are beginning a study of the non-uniform distribution of quantum-mechanical information content of the Bω bases, searching identify the factors that allowed obtain the good results cited展开更多
The theoretical relationship between water injection multiple(i.e.injected pore volume)and water saturation is inferred from theoretical concepts of reservoir engineering.A mathematical model based on core displacemen...The theoretical relationship between water injection multiple(i.e.injected pore volume)and water saturation is inferred from theoretical concepts of reservoir engineering.A mathematical model based on core displacement tests is established for the entire injection process that satisfies both initial displacement and extreme displacement,simultaneously.The results show that prior to the flooding,the water injection multiple has a linear relationship with the water saturation,and the utilization rate of the injected water is the highest.As water breakthrough at the production end,the water-cut increases,and the injection multiple increases exponentially while the utilization efficiency of the injected water gradually decreases.When the injection multiple approaches infinity,the utilization efficiency of the injected water gradually decreases to 0,by which time the water-cut at the production end is always 1.At this time,the water saturation no longer changes,and the water flooding recovery rate reaches its limit.Based on the experimental test data,a mathematical model of the entire process of injection multiple and water saturation is established,which has high fitting accuracy that can predict the injection multiple in the different stages of development of a mature oil reservoir.The dynamically changing index of the injection water utilization efficiency in reservoir development by reactive water flooding can be obtained through reasonable transformation of the mathematical model.This is of great significance in guiding evaluations of the effects of reservoir development and formulating countermeasures.展开更多
The South China Sea where water depth is up to 5000 m is the most promising oil and gas exploration area in China in the future.The seismic data acquired in the South China Sea contain various types of multiples that ...The South China Sea where water depth is up to 5000 m is the most promising oil and gas exploration area in China in the future.The seismic data acquired in the South China Sea contain various types of multiples that need to be removed before imaging can be developed.However,compared with the conventional reflection migration,multiples carry more information of the underground structure that helps provide better subsurface imaging.This paper presents a method to modify the conventional reverse time migration so that multiple reflections can migrate to their correct locations in the subsurface.This approach replaces the numerical impulsive source with the recorded data including primaries and multiples on the surface,and replaces the recorded primary reflection data with multiples.In the reverse time migration process,multiples recorded on the surface are extrapolated backward in time to each depth level,while primaries and multiples recorded on the surface are extrapolated forward in time to the same depth levels.By matching the difference between the primary and multiple images using an objective function,this algorithm improves the primary resultant image.Synthetic tests on Sigsbee2 B show that the proposed method can obtain a greater range and better underground illumination.Images of deep water in the South China Sea are obtained using multiples and their matching with primaries.They demonstrate that multiples can make up for the reflection illumination and the migration of multiples is an important research direction in the future.展开更多
Active inflammation in“inactive”progressive multiple sclerosis:Traditionally,the distinction between relapsing-remitting multiple sclerosis and progressive multiple sclerosis(PMS)has been framed as an inflammatory v...Active inflammation in“inactive”progressive multiple sclerosis:Traditionally,the distinction between relapsing-remitting multiple sclerosis and progressive multiple sclerosis(PMS)has been framed as an inflammatory versus degenerative dichotomy.This was based on a broad misconception regarding essentially all neurodegenerative conditions,depicting the degenerative process as passive and immune-independent occurring as a late byproduct of active inflammation in the central nervous system(CNS),which is(solely)systemically driven.展开更多
Safer,smarter,faster...In China,people prefer high-speed trains to flights if the journey time is under five hours.High-speed train travel is set to become even more attractive with the addition of a new member to the...Safer,smarter,faster...In China,people prefer high-speed trains to flights if the journey time is under five hours.High-speed train travel is set to become even more attractive with the addition of a new member to the high-speed train family:the CR450,the world’s fastest electric multiple unit(EMU).展开更多
BACKGROUND The accurate prediction of lymph node metastasis(LNM)is crucial for managing locally advanced(T3/T4)colorectal cancer(CRC).However,both traditional histopathology and standard slide-level deep learning ofte...BACKGROUND The accurate prediction of lymph node metastasis(LNM)is crucial for managing locally advanced(T3/T4)colorectal cancer(CRC).However,both traditional histopathology and standard slide-level deep learning often fail to capture the sparse and diagnostically critical features of metastatic potential.AIM To develop and validate a case-level multiple-instance learning(MIL)framework mimicking a pathologist's comprehensive review and improve T3/T4 CRC LNM prediction.METHODS The whole-slide images of 130 patients with T3/T4 CRC were retrospectively collected.A case-level MIL framework utilising the CONCH v1.5 and UNI2-h deep learning models was trained on features from all haematoxylin and eosinstained primary tumour slides for each patient.These pathological features were subsequently integrated with clinical data,and model performance was evaluated using the area under the curve(AUC).RESULTS The case-level framework demonstrated superior LNM prediction over slide-level training,with the CONCH v1.5 model achieving a mean AUC(±SD)of 0.899±0.033 vs 0.814±0.083,respectively.Integrating pathology features with clinical data further enhanced performance,yielding a top model with a mean AUC of 0.904±0.047,in sharp contrast to a clinical-only model(mean AUC 0.584±0.084).Crucially,a pathologist’s review confirmed that the model-identified high-attention regions correspond to known high-risk histopathological features.CONCLUSION A case-level MIL framework provides a superior approach for predicting LNM in advanced CRC.This method shows promise for risk stratification and therapy decisions,requiring further validation.展开更多
Peroxisome proliferator-activated receptor alpha is a member of the nuclear hormone receptor superfamily and functions as a transcription factor involved in regulating cellular metabolism.Previous studies have shown t...Peroxisome proliferator-activated receptor alpha is a member of the nuclear hormone receptor superfamily and functions as a transcription factor involved in regulating cellular metabolism.Previous studies have shown that PPARαplays a key role in the onset and progression of neurodegenerative diseases.Consequently,peroxisome proliferator-activated receptor alpha agonists have garnered increasing attention as potential treatments for neurological disorders.This review aims to clarify the research progress regarding peroxisome proliferator-activated receptor alpha in nervous system diseases.Peroxisome proliferator-activated receptor alpha is present in all cell types within adult mouse and adult neural tissues.Although it is conventionally believed to be primarily localized in the nucleus,its function may be regulated by a dynamic balance between cytoplasmic and nuclear shuttling.Both endogenous and exogenous peroxisome proliferator-activated receptor alpha agonists bind to the peroxisome proliferator-activated response element to exert their biological effects.Peroxisome proliferator-activated receptor alpha plays a significant therapeutic role in neurodegenerative diseases.For instance,peroxisome proliferator-activated receptor alpha agonist gemfibrozil has been shown to reduce levels of soluble and insoluble amyloid-beta in the hippocampus of Alzheimer's disease mouse models through the autophagy-lysosomal pathway.Additionally,peroxisome proliferator-activated receptor alpha is essential for the normal development and functional maintenance of the substantia nigra,and it can mitigate motor dysfunction in Parkinson's disease mouse models.Furthermore,peroxisome proliferator-activated receptor alpha has been found to reduce neuroinflammation and oxidative stress in various neurological diseases.In summary,peroxisome proliferator-activated receptor alpha plays a crucial role in the onset and progression of multiple nervous system diseases,and peroxisome proliferator-activated receptor alpha agonists hold promise as new therapeutic agents for the treatment of neurodegenerative diseases,providing new options for patient care.展开更多
Neuroinflammation is a key process in the pathogenesis of various neurodegenerative diseases,such as multiple sclerosis(MS),Alzheimer's disease,and traumatic brain injury.Even for disorders historically unrelated ...Neuroinflammation is a key process in the pathogenesis of various neurodegenerative diseases,such as multiple sclerosis(MS),Alzheimer's disease,and traumatic brain injury.Even for disorders historically unrelated to neuroinflammation,such as Alzheimer's disease,it is now shown to precede pathological protein aggregations.展开更多
Myelination,the continuous ensheathment of neuronal axons,is a lifelong process in the nervous system that is essential for the precise,temporospatial conduction of action potentials between neurons.Myelin also provid...Myelination,the continuous ensheathment of neuronal axons,is a lifelong process in the nervous system that is essential for the precise,temporospatial conduction of action potentials between neurons.Myelin also provides intercellular metabolic support to axons.Even minor disruptions in the integrity of myelin can impair neural performance and increase susceptibility to neurological diseases.In fact,myelin degeneration is a well-known neuropathological condition that is associated with normal aging and several neurodegenerative diseases,including multiple sclerosis and Alzheimer’s disease.In the central nervous system,compact myelin sheaths are formed by fully mature oligodendrocytes.However,the entire oligodendrocyte lineage is susceptible to changes in the biological microenvironment and other risk factors that arise as the brain ages.In addition to their well-known role in action potential propagation,oligodendrocytes also provide intercellular metabolic support to axons by transferring energy metabolites and delivering exosomes.Therefore,myelin degeneration in the aging central nervous system is a significant contributor to the development of neurodegenerative diseases.Interventions that mitigate age-related myelin degeneration can improve neurological function in aging individuals.In this review,we investigate the changes in myelin that are associated with aging and their underlying mechanisms.We also discuss recent advances in understanding how myelin degeneration in the aging brain contributes to neurodegenerative diseases and explore the factors that can prevent,slow down,or even reverse age-related myelin degeneration.Future research will enhance our understanding of how reducing age-related myelin degeneration can be used as a therapeutic target for delaying or preventing neurodegenerative diseases.展开更多
Alpha-synuclein and Parkinson's disease:Neuronal damage and inflammation caused by the aggregation of alpha-synuclein(α-syn)are central to a group of disorders known as synucleopathies,which includes Parkinson...Alpha-synuclein and Parkinson's disease:Neuronal damage and inflammation caused by the aggregation of alpha-synuclein(α-syn)are central to a group of disorders known as synucleopathies,which includes Parkinson's disease(PD),dementia with Lewy bodies,and multiple system atrophy,among others.PD,the most common synucleinopathy,is the second most prevalent neurodegenerative disease after Alzheimer's disease,and it is the fastest growing.Its primary hallmark is the degeneration of dopaminergic neurons in the substantia nigra pars compacta,disrupting the communication with the striatum.展开更多
Multi-organ-on-a-chip(MOOC)technology represents a pivotal direction in the organ-on-a-chip field,seeking to emulate the complex interactions of multiple human organs in vitro through microfluidic systems.This technol...Multi-organ-on-a-chip(MOOC)technology represents a pivotal direction in the organ-on-a-chip field,seeking to emulate the complex interactions of multiple human organs in vitro through microfluidic systems.This technology overcomes the limitations of traditional single-organ models,providing a novel platform for investigating complex disease mechanisms and evaluating drug efficacy and toxicity.Although it demonstrates broad application prospects,its development still faces critical bottlenecks,including inadequate physiological coupling between organs,short functional maintenance durations,and limited real-time monitoring capabilities.Contemporary research is advancing along three key directions,including functional coupling,sensor integration,and full-process automation systems,to propel the technology toward enhanced levels of physiological relevance and predictive accuracy.展开更多
Chemical exchange saturation transfer magnetic resonance imaging is an advanced imaging technique that enables the detection of compounds at low concentrations with high sensitivity and spatial resolution and has been...Chemical exchange saturation transfer magnetic resonance imaging is an advanced imaging technique that enables the detection of compounds at low concentrations with high sensitivity and spatial resolution and has been extensively studied for diagnosing malignancy and stroke.In recent years,the emerging exploration of chemical exchange saturation transfer magnetic resonance imaging for detecting pathological changes in neurodegenerative diseases has opened up new possibilities for early detection and repetitive scans without ionizing radiation.This review serves as an overview of chemical exchange saturation transfer magnetic resonance imaging with detailed information on contrast mechanisms and processing methods and summarizes recent developments in both clinical and preclinical studies of chemical exchange saturation transfer magnetic resonance imaging for Alzheimer’s disease,Parkinson’s disease,multiple sclerosis,and Huntington’s disease.A comprehensive literature search was conducted using databases such as PubMed and Google Scholar,focusing on peer-reviewed articles from the past 15 years relevant to clinical and preclinical applications.The findings suggest that chemical exchange saturation transfer magnetic resonance imaging has the potential to detect molecular changes and altered metabolism,which may aid in early diagnosis and assessment of the severity of neurodegenerative diseases.Although promising results have been observed in selected clinical and preclinical trials,further validations are needed to evaluate their clinical value.When combined with other imaging modalities and advanced analytical methods,chemical exchange saturation transfer magnetic resonance imaging shows potential as an in vivo biomarker,enhancing the understanding of neuropathological mechanisms in neurodegenerative diseases.展开更多
基金partially funded by the National Natural Science Foundation of China(Grant No.41730425)the Special Fund of the Institute of Geophysics,China Earthquake Administration(Grant No.DQJB20K42)the Institute of Geology and Geophysics,Chinese Academy of Sciences Project(Grant No.IGGCAS-2019031)。
文摘Surface-related multiples frequently propagate into the subsurface and contain abundant information on small reflection angles.Compared with the conventional migration of primaries,migration of multiples offers complementary illumination and a higher vertical resolution.However,crosstalk artifacts caused by unrelated multiples during reverse time migration(RTM)using multiples severely degrade the reliability and interpretation of the final migration images.Therefore,we proposed RTM using first-order receiver-side water-bottom-related multiples for eliminating crosstalk artifacts and enhancing vertical resolution.We first backward propagate the first-order receiver-side water-bottom-related multiples using a water-layer model,followed by saving the upper boundary wavefield.Then we produce the source wavefield using a seismic wavelet and the receiver wavefield by back-extrapolating the saved boundary.Finally,the cross-correlation imaging condition is applied to generate the final image.This method transforms the receiver-side multiples into primaries,followed by the conventional migration processing procedures.Numerical examples using synthetic datasets demonstrate that our method significantly enhances the imaging quality by eliminating crosstalk artifacts and improving the resolution.
基金sponsored by:the National Basic Research Program of China (973 Program) (2007CB209605)the National Natural Science Foundation of China (40974073)the National Hi-tech Research and Development Program of China (863 Program) (2009AA06Z206)
文摘In this research, we present a seismic trace interpolation method which uses seismic data with surface-related multiples. It is different from conventional seismic data interpolation using information transformation or extrapolation of adjacent channels for reconstruction of missing seismic data. In this method there are two steps, first, we construct pseudo-primaries by cross-correlation of surface multiple data to extract the missing near- offset information in multiples, which are not displayed in the acquired seismic record. Second, we correct the pseudo-primaries by applying a Least-squares Matching Filter （LMF） and RMS amplitude correction method in time and space sliding windows. Then the corrected pseudo-primaries can be used to fill the data gaps. The method is easy to implement, without the need to separate multiples and primaries. It extracts the seismic information contained by multiples for filling missing traces. The method is suitable for seismic data with surfacerelated multiples.
基金supported by the Key Laboratory of Ma-rine Mineral Resources,Ministry of Natural Resources,Guangzhou(No.KLMMR-2022-G09)the Guangzhou Ba-sic Research Program-Basic and Basic Applied Research Project(No.2023A04J0917)the PI Project of South-ern Marine Science and Engineering Guangdong Labora-tory(Guangzhou)(No.GML2020GD0802).
文摘Multiple suppression is an important element of marine seismic data processing.Intelligent suppression of multiples us-ing artificial intelligence reduces labor costs,minimizes dependence on unknown prior information,and improves data processing ef-ficiency.In this study,we propose an intelligent method for suppressing marine seismic multiples using deep learning approaches.The proposed method enables the intelligent suppression of free-surface-related multiples from seismic records.Initially,we construct a multi-category marine seismic multiple dataset through finite difference forward modeling under different boundary conditions.We use various models and data augmentation methods,including sample rotation,noise addition,and random channel omission.Then,we apply depthwise separable convolution to develop our deep learning Mobilenet-Unet model.The Mobilenet-Unet framework sig-nificantly reduces the number of operations required for multiple elimination without sacrificing model performance,ultimately reali-zing the optimal multiple suppression model.The trained Mobilenet-Unet is applied to the test set for verification.Moreover,to deter-mine its generalization ability,it is implemented to seismic records containing multiples generated by two marine geophysical models that were not included in the training process.The performance of Mobilenet-Unet is also compared with that of different network structures.The results indicate that,despite its small size,our proposed Mobilenet-Unet deep learning model can rapidly and effective-ly separate multiples in marine seismic data,possessing reasonable generalization ability.
基金supported by National Natural Science Foundation of China(42364008,41804110)in part by Guizhou Provincial Basic Research Program(Natural Science)(ZK[2022]060)+1 种基金in part by China Postdoctoral Science Foundation(2022M723127)in part by Youth Innovation Team Project of Shandong Provincial Education Department(2022KJ141).
文摘The deep convolutional neural network U-net has been introduced into adaptive subtraction, which is a critical step in effectively suppressing seismic multiples. The U-net approach has higher precision than the traditional linear regression approach. However, the existing 2D U-net approach with 2D data windows can not deal with elaborate discrepancies between the actual and simulated multiples along the gather direction. It may lead to erroneous preservation of primaries or generate obvious vestigial multiples, especially in complex media. To further enhance the multiple suppression accuracy, we present an adaptive subtraction approach utilizing 3D U-net architecture, which can adaptively separate primaries and multiples utilizing 3D windows. The utilization of 3D windows allows for enhanced depiction of spatial continuity and anisotropy of seismic events along the gather direction in comparison to 2D windows. The 3D U-net approach with 3D windows can more effectively preserve the continuity of primaries and manage the complex disparities between the actual and simulated multiples. The proposed 3D U-net approach exhibits 1 dB improvement in the signal-to-noise ratio compared to the 2D U-net approach, as observed in the synthesis data section, and exhibits more outstanding performance in the preservation of primaries and removal of residual multiples in both synthesis and reality data sections. Moreover, to expedite network training in our proposed 3D U-net approach we employ the transfer learning (TL) strategy by utilizing the network parameters of 3D U-net estimated in the preceding data segment as the initial network parameters of 3D U-net for the subsequent data segment. In the reality data section, the 3D U-net approach incorporating TL reduces the computational expense by 70% compared to the one without TL.
基金Supported by the National Natural Science Foundation of China(40974054,41174080)the National Basic Research Program of China(973 Program)(2009CB219301)+1 种基金the National Innovation Research Project for Exploration and Development of Oil Shale(OSP-02,OSR-02)the National Public Benefit Scientific Research Foundation of China(201011078)
文摘In practical seismic exploration, internal multiples generated when the wave impedance of medium is strong, and seismic records are recorded. The method of virtual event repress internal multiples is to move scattered points from underground to the surface, similar to the method of the surface-related multiple elimination (SRME). The method of SRME belongs to the prediction-subtraction approaches to eliminate internal multiples, prediction method is based on building a brand new way of seismic wave propagation (virtual reflection and virtual event), so that it has forward and backward wave propagation, and through convolution with significant wave to predict the internal multiples. Due to required data needing field information of full-wave, the authors use Seislet transform interpolating the missing data to ensure the premise of internal multiples prediction. The test data show that the above method has achieved good results.
基金supported by the National Natural Science Foundation of China(No.41674122)National Science and Technology Major Project of China(No.2016ZX05004003)National Basic Research Program of China(No.2013CB228602)
文摘The attenuation of prestack internal multiples based on virtual seismic events is computationally costly and hinders seismic data processing. We propose a multiples attenuation method for poststack seismic data by approximating conventional virtual events. The proposed method is iterative. The proposed method is tested using 2D synthetic and the field poststack seismic datasets. Compared with the conventional virtual events method, the proposed method does not require data regularization and offers higher computation efficiency. The method requires to know the travel time of the primary reflection waves. The results of the application to 2D field datasets suggest that the proposed method attenuates the internal multiples while highlighting the deep primaries.
基金the sponsors of the WPI group for their financial supportfinancially supported by the National Key R&D Program of China (Grant Number: 2018YFA0702503, 2019YFC0312004)+2 种基金National Natural Science Foundation of China (Grant Number: 41774126)Southern Marine Science and Engineering Guangdong Laboratory (Zhanjiang) (ZJW-2019-04)National Science and Technology Major Project of China (Grant Number: 2016ZX05024-001, 2016ZX05006-002)。
文摘In marine seismic exploration,especially in deep-water and hard ocean-bottom cases,free-surface multiples are strongly developed.Compared with primary waves,the wider illumination aperture of the multiples is beneficial for high-resolution seismic imaging.In this study,by introducing a new compound source composed of primaries and free-surface multiples and by ignoring internal multiples,we derive a new linearized forward problem(free-surface-multiple prediction model)under a weak-scattering assumption(i.e.,first-order Born approximation).On the basis of the new linearized problem,we propose a joint inversion-imaging method by simultaneously using the primaries and free-surface multiples under the general framework of least square inversion.To eliminate the crosstalk artifacts introduced by the cross-correlation of multiples with different orders,we prove that the crosstalk artifacts can be gradually eliminated during the inversion if a proper step length is selected.Synthetic-andfield-data tests demonstrate the effectiveness of the proposed method.
文摘A new three-dimensional fundamental solution to the Stokes flow was proposed by transforming the solid harmonic functions in Lamb's solution into expressions in terms Of the oblate spheroidal coordinates. These fundamental solutions are advantageous in treating flows past an arbitrary number of arbitrarily positioned and oriented oblate spheroids. The least squares technique was adopted herein so that the convergence difficulties often encountered in solving three-dimensional problems were completely avoided. The examples demonstrate that present approach is highly accurate, consistently stable and computationally efficient. The oblate spheroid may be used to model a variety of particle shapes between a circular disk and a sphere. For the first time, the effect of various geometric factors on the forces and torques exerted on two oblate spheroids were systematically studied by using the proposed fundamental solutions. The generality of this approach was illustrated by two problems of three spheroids.
文摘The Hartree-Fock equation is non-linear and has, in principle, multiple solutions. The ωth HF extreme and its associated virtual spin-orbitals furnish an orthogonal base Bω of the full configuration interaction space. Although all Bω bases generate the same CI space, the corresponding configurations of each Bω base have distinct quantum-mechanical information contents. In previous works, we have introduced a multi-reference configuration interaction method, based on the multiple extremes of the Hartree-Fock problem. This method was applied to calculate the permanent electrical dipole and quadrupole moments of some small molecules using minimal and double, triple and polarized double-zeta bases. In all cases were possible, using a reduced number of configurations, to obtain dipole and quadrupole moments in close agreement with the experimental values and energies without compromising the energy of the state function. These results show the positive effect of the use of the multi-reference Hartree-Fock bases that allowed a better extraction of quantum mechanical information from the several Bω bases. But to extend these ideas for larger systems and atomic bases, it is necessary to develop criteria to build the multireference Hartree-Fock bases. In this project, we are beginning a study of the non-uniform distribution of quantum-mechanical information content of the Bω bases, searching identify the factors that allowed obtain the good results cited
文摘The theoretical relationship between water injection multiple(i.e.injected pore volume)and water saturation is inferred from theoretical concepts of reservoir engineering.A mathematical model based on core displacement tests is established for the entire injection process that satisfies both initial displacement and extreme displacement,simultaneously.The results show that prior to the flooding,the water injection multiple has a linear relationship with the water saturation,and the utilization rate of the injected water is the highest.As water breakthrough at the production end,the water-cut increases,and the injection multiple increases exponentially while the utilization efficiency of the injected water gradually decreases.When the injection multiple approaches infinity,the utilization efficiency of the injected water gradually decreases to 0,by which time the water-cut at the production end is always 1.At this time,the water saturation no longer changes,and the water flooding recovery rate reaches its limit.Based on the experimental test data,a mathematical model of the entire process of injection multiple and water saturation is established,which has high fitting accuracy that can predict the injection multiple in the different stages of development of a mature oil reservoir.The dynamically changing index of the injection water utilization efficiency in reservoir development by reactive water flooding can be obtained through reasonable transformation of the mathematical model.This is of great significance in guiding evaluations of the effects of reservoir development and formulating countermeasures.
基金supported by the National Basic Research Program of China(Grant No.2009CB219405)the National Oil and Gas Program(Grant No.2011ZX05008-006)the National Natural Science Foundation of China(Grant Nos.40930421,41074091)
文摘The South China Sea where water depth is up to 5000 m is the most promising oil and gas exploration area in China in the future.The seismic data acquired in the South China Sea contain various types of multiples that need to be removed before imaging can be developed.However,compared with the conventional reflection migration,multiples carry more information of the underground structure that helps provide better subsurface imaging.This paper presents a method to modify the conventional reverse time migration so that multiple reflections can migrate to their correct locations in the subsurface.This approach replaces the numerical impulsive source with the recorded data including primaries and multiples on the surface,and replaces the recorded primary reflection data with multiples.In the reverse time migration process,multiples recorded on the surface are extrapolated backward in time to each depth level,while primaries and multiples recorded on the surface are extrapolated forward in time to the same depth levels.By matching the difference between the primary and multiple images using an objective function,this algorithm improves the primary resultant image.Synthetic tests on Sigsbee2 B show that the proposed method can obtain a greater range and better underground illumination.Images of deep water in the South China Sea are obtained using multiples and their matching with primaries.They demonstrate that multiples can make up for the reflection illumination and the migration of multiples is an important research direction in the future.
文摘Active inflammation in“inactive”progressive multiple sclerosis:Traditionally,the distinction between relapsing-remitting multiple sclerosis and progressive multiple sclerosis(PMS)has been framed as an inflammatory versus degenerative dichotomy.This was based on a broad misconception regarding essentially all neurodegenerative conditions,depicting the degenerative process as passive and immune-independent occurring as a late byproduct of active inflammation in the central nervous system(CNS),which is(solely)systemically driven.
文摘Safer,smarter,faster...In China,people prefer high-speed trains to flights if the journey time is under five hours.High-speed train travel is set to become even more attractive with the addition of a new member to the high-speed train family:the CR450,the world’s fastest electric multiple unit(EMU).
基金Supported by Chongqing Medical Scientific Research Project(Joint Project of Chongqing Health Commission and Science and Technology Bureau),No.2023MSXM060.
文摘BACKGROUND The accurate prediction of lymph node metastasis(LNM)is crucial for managing locally advanced(T3/T4)colorectal cancer(CRC).However,both traditional histopathology and standard slide-level deep learning often fail to capture the sparse and diagnostically critical features of metastatic potential.AIM To develop and validate a case-level multiple-instance learning(MIL)framework mimicking a pathologist's comprehensive review and improve T3/T4 CRC LNM prediction.METHODS The whole-slide images of 130 patients with T3/T4 CRC were retrospectively collected.A case-level MIL framework utilising the CONCH v1.5 and UNI2-h deep learning models was trained on features from all haematoxylin and eosinstained primary tumour slides for each patient.These pathological features were subsequently integrated with clinical data,and model performance was evaluated using the area under the curve(AUC).RESULTS The case-level framework demonstrated superior LNM prediction over slide-level training,with the CONCH v1.5 model achieving a mean AUC(±SD)of 0.899±0.033 vs 0.814±0.083,respectively.Integrating pathology features with clinical data further enhanced performance,yielding a top model with a mean AUC of 0.904±0.047,in sharp contrast to a clinical-only model(mean AUC 0.584±0.084).Crucially,a pathologist’s review confirmed that the model-identified high-attention regions correspond to known high-risk histopathological features.CONCLUSION A case-level MIL framework provides a superior approach for predicting LNM in advanced CRC.This method shows promise for risk stratification and therapy decisions,requiring further validation.
基金supported by grants from Tianjin Scientific Research Project in Key Areas of Traditional Chinese Medicine,Tianjin Municipal Health Commission,No.2024012(to JL)Tianjin Municipal Education Commission Project,No.2021KJ217(to CS)。
文摘Peroxisome proliferator-activated receptor alpha is a member of the nuclear hormone receptor superfamily and functions as a transcription factor involved in regulating cellular metabolism.Previous studies have shown that PPARαplays a key role in the onset and progression of neurodegenerative diseases.Consequently,peroxisome proliferator-activated receptor alpha agonists have garnered increasing attention as potential treatments for neurological disorders.This review aims to clarify the research progress regarding peroxisome proliferator-activated receptor alpha in nervous system diseases.Peroxisome proliferator-activated receptor alpha is present in all cell types within adult mouse and adult neural tissues.Although it is conventionally believed to be primarily localized in the nucleus,its function may be regulated by a dynamic balance between cytoplasmic and nuclear shuttling.Both endogenous and exogenous peroxisome proliferator-activated receptor alpha agonists bind to the peroxisome proliferator-activated response element to exert their biological effects.Peroxisome proliferator-activated receptor alpha plays a significant therapeutic role in neurodegenerative diseases.For instance,peroxisome proliferator-activated receptor alpha agonist gemfibrozil has been shown to reduce levels of soluble and insoluble amyloid-beta in the hippocampus of Alzheimer's disease mouse models through the autophagy-lysosomal pathway.Additionally,peroxisome proliferator-activated receptor alpha is essential for the normal development and functional maintenance of the substantia nigra,and it can mitigate motor dysfunction in Parkinson's disease mouse models.Furthermore,peroxisome proliferator-activated receptor alpha has been found to reduce neuroinflammation and oxidative stress in various neurological diseases.In summary,peroxisome proliferator-activated receptor alpha plays a crucial role in the onset and progression of multiple nervous system diseases,and peroxisome proliferator-activated receptor alpha agonists hold promise as new therapeutic agents for the treatment of neurodegenerative diseases,providing new options for patient care.
基金supported by FWO(Fonds voor Wetenschappelijk Onderzoek),grant number G07562NFWO(to BB)。
文摘Neuroinflammation is a key process in the pathogenesis of various neurodegenerative diseases,such as multiple sclerosis(MS),Alzheimer's disease,and traumatic brain injury.Even for disorders historically unrelated to neuroinflammation,such as Alzheimer's disease,it is now shown to precede pathological protein aggregations.
基金supported by grants from Guangdong Basic and Applied Basic Research Foundation,No.2021A1515110801(to SW)the National Natural Science Foundation of China,No.82301511(to SW)+1 种基金“Double First-Class”Construction Project of NPU,Nos.0515023GH0202320(to JC),0515023SH0201320(to JC)973 Program,No.2011CB504100(to JC).
文摘Myelination,the continuous ensheathment of neuronal axons,is a lifelong process in the nervous system that is essential for the precise,temporospatial conduction of action potentials between neurons.Myelin also provides intercellular metabolic support to axons.Even minor disruptions in the integrity of myelin can impair neural performance and increase susceptibility to neurological diseases.In fact,myelin degeneration is a well-known neuropathological condition that is associated with normal aging and several neurodegenerative diseases,including multiple sclerosis and Alzheimer’s disease.In the central nervous system,compact myelin sheaths are formed by fully mature oligodendrocytes.However,the entire oligodendrocyte lineage is susceptible to changes in the biological microenvironment and other risk factors that arise as the brain ages.In addition to their well-known role in action potential propagation,oligodendrocytes also provide intercellular metabolic support to axons by transferring energy metabolites and delivering exosomes.Therefore,myelin degeneration in the aging central nervous system is a significant contributor to the development of neurodegenerative diseases.Interventions that mitigate age-related myelin degeneration can improve neurological function in aging individuals.In this review,we investigate the changes in myelin that are associated with aging and their underlying mechanisms.We also discuss recent advances in understanding how myelin degeneration in the aging brain contributes to neurodegenerative diseases and explore the factors that can prevent,slow down,or even reverse age-related myelin degeneration.Future research will enhance our understanding of how reducing age-related myelin degeneration can be used as a therapeutic target for delaying or preventing neurodegenerative diseases.
基金supported by the Spanish Ministry of Science and Innovation via a doctoral grant[FPU22/03656].supported by the Spanish Ministry of Science and Innovation(PID2022-137963OB-I00)Generalitat de Catalunya(2021-SGR-00635 AGAUR)+1 种基金CERCA Programme(Generalitat de Catalunya)by ICREA,ICREA-Academia 2020(to SV)。
文摘Alpha-synuclein and Parkinson's disease:Neuronal damage and inflammation caused by the aggregation of alpha-synuclein(α-syn)are central to a group of disorders known as synucleopathies,which includes Parkinson's disease(PD),dementia with Lewy bodies,and multiple system atrophy,among others.PD,the most common synucleinopathy,is the second most prevalent neurodegenerative disease after Alzheimer's disease,and it is the fastest growing.Its primary hallmark is the degeneration of dopaminergic neurons in the substantia nigra pars compacta,disrupting the communication with the striatum.
基金supported by the Shenzhen Medical Research Fund(Grant No.A2303049)Guangdong Basic and Applied Basic Research(Grant No.2023A1515010647)+1 种基金National Natural Science Foundation of China(Grant No.22004135)Shenzhen Science and Technology Program(Grant No.RCBS20210706092409020,GXWD20201231165807008,20200824162253002).
文摘Multi-organ-on-a-chip(MOOC)technology represents a pivotal direction in the organ-on-a-chip field,seeking to emulate the complex interactions of multiple human organs in vitro through microfluidic systems.This technology overcomes the limitations of traditional single-organ models,providing a novel platform for investigating complex disease mechanisms and evaluating drug efficacy and toxicity.Although it demonstrates broad application prospects,its development still faces critical bottlenecks,including inadequate physiological coupling between organs,short functional maintenance durations,and limited real-time monitoring capabilities.Contemporary research is advancing along three key directions,including functional coupling,sensor integration,and full-process automation systems,to propel the technology toward enhanced levels of physiological relevance and predictive accuracy.
基金supported by The University of Hong Kong,China(109000487,109001694,204610401,and 204610519)National Natural Science Foundation of China(82402225)(to JH).
文摘Chemical exchange saturation transfer magnetic resonance imaging is an advanced imaging technique that enables the detection of compounds at low concentrations with high sensitivity and spatial resolution and has been extensively studied for diagnosing malignancy and stroke.In recent years,the emerging exploration of chemical exchange saturation transfer magnetic resonance imaging for detecting pathological changes in neurodegenerative diseases has opened up new possibilities for early detection and repetitive scans without ionizing radiation.This review serves as an overview of chemical exchange saturation transfer magnetic resonance imaging with detailed information on contrast mechanisms and processing methods and summarizes recent developments in both clinical and preclinical studies of chemical exchange saturation transfer magnetic resonance imaging for Alzheimer’s disease,Parkinson’s disease,multiple sclerosis,and Huntington’s disease.A comprehensive literature search was conducted using databases such as PubMed and Google Scholar,focusing on peer-reviewed articles from the past 15 years relevant to clinical and preclinical applications.The findings suggest that chemical exchange saturation transfer magnetic resonance imaging has the potential to detect molecular changes and altered metabolism,which may aid in early diagnosis and assessment of the severity of neurodegenerative diseases.Although promising results have been observed in selected clinical and preclinical trials,further validations are needed to evaluate their clinical value.When combined with other imaging modalities and advanced analytical methods,chemical exchange saturation transfer magnetic resonance imaging shows potential as an in vivo biomarker,enhancing the understanding of neuropathological mechanisms in neurodegenerative diseases.
