Neuromyelitis optica spectrum disorders are neuroinflammatory demyelinating disorders that lead to permanent visual loss and motor dysfunction.To date,no effective treatment exists as the exact causative mechanism rem...Neuromyelitis optica spectrum disorders are neuroinflammatory demyelinating disorders that lead to permanent visual loss and motor dysfunction.To date,no effective treatment exists as the exact causative mechanism remains unknown.Therefore,experimental models of neuromyelitis optica spectrum disorders are essential for exploring its pathogenesis and in screening for therapeutic targets.Since most patients with neuromyelitis optica spectrum disorders are seropositive for IgG autoantibodies against aquaporin-4,which is highly expressed on the membrane of astrocyte endfeet,most current experimental models are based on aquaporin-4-IgG that initially targets astrocytes.These experimental models have successfully simulated many pathological features of neuromyelitis optica spectrum disorders,such as aquaporin-4 loss,astrocytopathy,granulocyte and macrophage infiltration,complement activation,demyelination,and neuronal loss;however,they do not fully capture the pathological process of human neuromyelitis optica spectrum disorders.In this review,we summarize the currently known pathogenic mechanisms and the development of associated experimental models in vitro,ex vivo,and in vivo for neuromyelitis optica spectrum disorders,suggest potential pathogenic mechanisms for further investigation,and provide guidance on experimental model choices.In addition,this review summarizes the latest information on pathologies and therapies for neuromyelitis optica spectrum disorders based on experimental models of aquaporin-4-IgG-seropositive neuromyelitis optica spectrum disorders,offering further therapeutic targets and a theoretical basis for clinical trials.展开更多
Machinery condition monitoring is beneficial to equipment maintenance and has been receiving much attention from academia and industry.Machine learning,especially deep learning,has become popular for machinery conditi...Machinery condition monitoring is beneficial to equipment maintenance and has been receiving much attention from academia and industry.Machine learning,especially deep learning,has become popular for machinery condition monitoring because that can fully use available data and computational power.Since significant accidents might be caused if wrong fault alarms are given for machine condition monitoring,interpretable machine learning models,integrate signal processing knowledge to enhance trustworthiness of models,are gradually becoming a research hotspot.A previous spectrum-based and interpretable optimized weights method has been proposed to indicate faulty and fundamental frequencies when the analyzed data only contains a healthy type and a fault type.Considering that multiclass fault types are naturally met in practice,this work aims to explore the interpretable optimized weights method for multiclass fault type scenarios.Therefore,a new multiclass optimized weights spectrum(OWS)is proposed and further studied theoretically and numerically.It is found that the multiclass OWS is capable of capturing the characteristic components associated with different conditions and clearly indicating specific fault characteristic frequencies(FCFs)corresponding to each fault condition.This work can provide new insights into spectrum-based fault classification models,and the new multiclass OWS also shows great potential for practical applications.展开更多
Artificial Intelligence(AI)is changing healthcare by helping with diagnosis.However,for doctors to trust AI tools,they need to be both accurate and easy to understand.In this study,we created a new machine learning sy...Artificial Intelligence(AI)is changing healthcare by helping with diagnosis.However,for doctors to trust AI tools,they need to be both accurate and easy to understand.In this study,we created a new machine learning system for the early detection of Autism Spectrum Disorder(ASD)in children.Our main goal was to build a model that is not only good at predicting ASD but also clear in its reasoning.For this,we combined several different models,including Random Forest,XGBoost,and Neural Networks,into a single,more powerful framework.We used two different types of datasets:(i)a standard behavioral dataset and(ii)a more complex multimodal dataset with images,audio,and physiological information.The datasets were carefully preprocessed for missing values,redundant features,and dataset imbalance to ensure fair learning.The results outperformed the state-of-the-art with a Regularized Neural Network,achieving 97.6%accuracy on behavioral data.Whereas,on the multimodal data,the accuracy is 98.2%.Other models also did well with accuracies consistently above 96%.We also used SHAP and LIME on a behavioral dataset for models’explainability.展开更多
A number of fractal/multifractal methods are introduced for quantifying the mineral deposit spectrum which include a number-size model, grade-tonnage model, power spectrum model, multifractal model and an eigenvalue s...A number of fractal/multifractal methods are introduced for quantifying the mineral deposit spectrum which include a number-size model, grade-tonnage model, power spectrum model, multifractal model and an eigenvalue spectrum model. The first two models characterize mineral deposits spectra based on relationships among the measures of mineral deposits. These include the number of deposits, size of deposits, concentration and volume of mineral deposits. The last three methods that deal with the spatial-temporal spectra of mineral deposit studies are all expected to be popularized in near future. A case study of hydrothermal gold deposits from the Abitibi area, a world-class mineral district, is used to demonstrate the principle as well as the applications of methods proposed in this paper. It has been shown that fractal and multifractal models are generally applicable to modeling of mineral deposits and occurrences. Clusters of mineral deposits were identified by several methods including the power spectral analysis, singularity analysis and the eigenvalue analysis. These clusters contain most of the known mineral deposits in the Timmins and Kirkland Lake camps.展开更多
Identifying the unknown geometric and material information of a multi-shield object by analyzing the radiation signature measurements is always an important problem in national and global security. In order to identif...Identifying the unknown geometric and material information of a multi-shield object by analyzing the radiation signature measurements is always an important problem in national and global security. In order to identify the unknown shielding layer thicknesses of a source/shield system with gamma-ray spectra, we have developed a derivative-free inverse radiation transport model based on a differential evolution algorithm with global and local neighbourhoods(IRT-DEGL). In the present paper, the IRT-DEGL model is further extended for estimating the unknown thicknesses with random initial guesses and material mass densities of multi-shielding layers as well as their combinations. Using the detected gamma-ray spectra,the illustration of inverse studies is implemented and the main influence factors for inverse results are also analyzed.展开更多
The identification of the inter-electrode gap size in the high frequency group pulse micro-electrochemical machining （HGPECM） is mainly discussed. The auto-regressive（AR） model of group pulse current flowing acros...The identification of the inter-electrode gap size in the high frequency group pulse micro-electrochemical machining （HGPECM） is mainly discussed. The auto-regressive（AR） model of group pulse current flowing across the cathode and the anode are created under different situations with different processing parameters and inter-electrode gap size. The AR model based on the current signals indicates that the order of the AR model is obviously different relating to the different processing conditions and the inter-electrode gap size; Moreover, it is different about the stability of the dynamic system, i.e. the white noise response of the Green＇s function of the dynamic system is diverse. In addition, power spectrum method is used in the analysis of the dynamic time series about the current signals with different inter-electrode gap size, the results show that there exists a strongest power spectrum peak, characteristic power spectrum（CPS）, to the current signals related to the different inter-electrode gap size in the range of 0～5 kHz. Therefore, the CPS of current signals can implement the identification of the inter-electrode gap.展开更多
Autism spectrum disorder(ASD)is typically characterized by common deficits in social skills and repetitive/stereotyped behaviors.It is widely accepted that genetic and environmental factors solely or in combination ca...Autism spectrum disorder(ASD)is typically characterized by common deficits in social skills and repetitive/stereotyped behaviors.It is widely accepted that genetic and environmental factors solely or in combination cause ASD.However,the underlying pathogenic mechanism is unclear due to its highly heterogeneous nature.To better understand the pathogenesis of ASD,various animal models have been generated,which can be generally divided into genetic,environment-induced,and idiopathic animal models.In this review,we summarize the common animals used for ASD study and then discuss the applications,clinical insights,as well as challenges and prospects of current ASD animal models.展开更多
In this paper, a new spatial coherence model of seismic ground motions is proposed by a fitting procedure. The analytical expressions of modal combination （correlation） coefficients of structural response are develo...In this paper, a new spatial coherence model of seismic ground motions is proposed by a fitting procedure. The analytical expressions of modal combination （correlation） coefficients of structural response are developed for multi-support seismic excitations. The coefficients from both the numerical integration and analytical solutions are compared to verify the accuracy of the solutions. It is shown that the analytical expressions of numerical modal combination coefficients are of high accuracy. The results of random responses of an example bridge show that the analytical modal combination coefficients developed in this paper are accurate enough to meet the requirements needed in practice. In addition, the computational efficiency of the analytical solutions of the modal combination coefficients is demonstrated by the response computation of the example bridge. It is found that the time required for the structural response analysis by using the analytical modal combination coefficients is less than 1/20 of that using numerical integral methods.展开更多
We consider a three-electron system in the Impurity Hubbard model with a coupling between nearest-neighbors. Our research aim consists of studying the structure of essential spectrum and discrete spectra of the energy...We consider a three-electron system in the Impurity Hubbard model with a coupling between nearest-neighbors. Our research aim consists of studying the structure of essential spectrum and discrete spectra of the energy operator of three-electron systems in the impurity Hubbard model in the quartet state of the system in a <em>v</em>-dimensional lattice. We have reduced the study of the spectrum of the three-electron quartet state operator in the impurity Hubbard model to the study of the spectrum of a simpler operator. We proved the essential spectra of the three-electron systems in the Impurity Hubbard model in the quartet state is the union of no more than six segments, and the discrete spectrum of the system is consists of no more than four eigenvalues.展开更多
The improved version of Los Alamos model with the multi-modal fission approach is used to analyse the prompt fission neutron spectrum and multiplicity for the neutron-induced fission of 237Np. The spectra of neutrons ...The improved version of Los Alamos model with the multi-modal fission approach is used to analyse the prompt fission neutron spectrum and multiplicity for the neutron-induced fission of 237Np. The spectra of neutrons emitted from fragments for the three most dominant fission modes （standard Ⅰ, standard Ⅱ and superlong） are calculated separately and the total spectrum is synthesized. The multi-modal parameters contained in the spectrum model are determined on the basis of experimental data of fission fragment mass distributions. The calculated total prompt fission neutron spectrum and multiplicity are better agreement with the experimental data than those obtained from the conventional treatment of the Los Alamos model.展开更多
Microwave remote sensing is one of the most useful methods for observing the ocean parameters. The Doppler frequency or interferometric phase of the radar echoes can be used for an ocean surface current speed retrieva...Microwave remote sensing is one of the most useful methods for observing the ocean parameters. The Doppler frequency or interferometric phase of the radar echoes can be used for an ocean surface current speed retrieval,which is widely used in spaceborne and airborne radars. While the effect of the ocean currents and waves is interactional. It is impossible to retrieve the ocean surface current speed from Doppler frequency shift directly. In order to study the relationship between the ocean surface current speed and the Doppler frequency shift, a numerical ocean surface Doppler spectrum model is established and validated with a reference. The input parameters of ocean Doppler spectrum include an ocean wave elevation model, a directional distribution function, and wind speed and direction. The suitable ocean wave elevation spectrum and the directional distribution function are selected by comparing the ocean Doppler spectrum in C band with an empirical geophysical model function（CDOP）. What is more, the error sensitivities of ocean surface current speed to the wind speed and direction are analyzed. All these simulations are in Ku band. The simulation results show that the ocean surface current speed error is sensitive to the wind speed and direction errors. With VV polarization, the ocean surface current speed error is about 0.15 m/s when the wind speed error is 2 m/s, and the ocean surface current speed error is smaller than 0.3 m/s when the wind direction error is within 20° in the cross wind direction.展开更多
To make the quantitative results of nuclear magnetic resonance(NMR) transverse relaxation(T;) spectrums reflect the type and pore structure of reservoir more directly, an unsupervised clustering method was developed t...To make the quantitative results of nuclear magnetic resonance(NMR) transverse relaxation(T;) spectrums reflect the type and pore structure of reservoir more directly, an unsupervised clustering method was developed to obtain the quantitative pore structure information from the NMR T;spectrums based on the Gaussian mixture model(GMM). Firstly, We conducted the principal component analysis on T;spectrums in order to reduce the dimension data and the dependence of the original variables. Secondly, the dimension-reduced data was fitted using the GMM probability density function, and the model parameters and optimal clustering numbers were obtained according to the expectation-maximization algorithm and the change of the Akaike information criterion. Finally, the T;spectrum features and pore structure types of different clustering groups were analyzed and compared with T;geometric mean and T;arithmetic mean. The effectiveness of the algorithm has been verified by numerical simulation and field NMR logging data. The research shows that the clustering results based on GMM method have good correlations with the shape and distribution of the T;spectrum, pore structure, and petroleum productivity, providing a new means for quantitative identification of pore structure, reservoir grading, and oil and gas productivity evaluation.展开更多
Maternal drinking during pregnancy can result in a wide spectrum of cognitive and behavioral abnormalities termed fetal alcohol spectrum disorders (FASD). The heterogeneity observed in FASD-related phenotypes can be a...Maternal drinking during pregnancy can result in a wide spectrum of cognitive and behavioral abnormalities termed fetal alcohol spectrum disorders (FASD). The heterogeneity observed in FASD-related phenotypes can be attributed to a number of environmental and genetic factors;however, ethanol dose and timing of exposure may have significant influences. Here, we report the behavioral effects of acute, binge-like ethanol exposure at three neurodevelopmental times corresponding to the first, second, and third trimester of human development in C57BL/6J mice. Results show that developmental ethanol exposure consistently delays the development of basic motor skill reflexes and coordination as well as impairs spatial learning and memory. Observed changes in activity and anxiety-related behaviors, however, appear to be dependent on timing of alcohol exposure. The variability in behaviors between different treatment models suggests that these may be useful in evaluating the mechanisms disrupted by ethanol at specific neurodevelopmental times. The results provide further evidence that, regardless of developmental stage, the developing brain is acutely sensitive to alcohol exposure.展开更多
A neurological abnormality called autism spectrum disorder(ASD)affects how a person perceives and interacts with others,leading to social interaction and communication issues.Limited and recurring behavioural patterns...A neurological abnormality called autism spectrum disorder(ASD)affects how a person perceives and interacts with others,leading to social interaction and communication issues.Limited and recurring behavioural patterns are another feature of the illness.Multiple mutations throughout development are the source of the neurodevelopmental disorder autism.However,a well-established model and perfect treatment for this spectrum disease has not been discovered.The rising era of the clustered regularly interspaced palindromic repeats(CRISPR)-associated protein 9(Cas9)system can streamline the complexity underlying the pathogenesis of ASD.The CRISPR-Cas9 system is a powerful genetic engineering tool used to edit the genome at the targeted site in a precise manner.The major hurdle in studying ASD is the lack of appropriate animal models presenting the complex symptoms of ASD.Therefore,CRISPR-Cas9 is being used worldwide to mimic the ASD-like pathology in various systems like in vitro cell lines,in vitro 3D organoid models and in vivo animal models.Apart from being used in establishing ASD models,CRISPR-Cas9 can also be used to treat the complexities of ASD.The aim of this review was to summarize and critically analyse the CRISPRCas9-mediated discoveries in the field of ASD.展开更多
We consider a five-electron system in the Hubbard model with a coupling between nearest-neighbors. The structure of essential spectrum and discrete spectrum of the systems in the third and fourth doublet states in a &...We consider a five-electron system in the Hubbard model with a coupling between nearest-neighbors. The structure of essential spectrum and discrete spectrum of the systems in the third and fourth doublet states in a <em>v</em>-dimensional lattice is investigated. We prove that the essential spectrum of the system in a third doublet state consists is the union of at most four segments, and discrete spectrum of the system is empty. We show that the essential spectrum of the system in a fourth doublet state consists of the union of at most seven segments, and discrete spectrum of the system consists of no more than one point.展开更多
Capillary and capillary-gravity waves possess a random character, and the slope wavenumber spectra of them can be used to represent mean distributions of wave energy with respect to spatial scale of variability. But s...Capillary and capillary-gravity waves possess a random character, and the slope wavenumber spectra of them can be used to represent mean distributions of wave energy with respect to spatial scale of variability. But simple and practical models of the slope wavenumber spectra have not been put forward so far. In this article, we address the accurate definition of the slope wavenumber spectra of water surface capillary and capillary-gravity waves. By combining the existing slope wavenumber models and using the dispersion relation of water surface waves, we derive the slope wavenumber spectrum models of capillary and capillary-gravity waves. Simultaneously, by using the slope wavenumber models, the dependence of the slope wavenumber spectrum on wind speed is analyzed using data obtained in an experiment which was performed in a laboratory wind wave tank. Generally speaking, the slope wavenumber spectra are influenced profoundly by the wind speed above water surface. The slope wavenumber spectrum increases with wind speed obviously and do not cross each other for different wind speeds. But, for the same wind speed, the slope wavenumber spectra are essentially identical, even though the capillary and capillary-gravity waves are excited at different times and locations. Furthermore, the slope wavenumber spectra obtained from the models agree quite well with experimental results as regards both the values and the shape of the curve.展开更多
文摘Neuromyelitis optica spectrum disorders are neuroinflammatory demyelinating disorders that lead to permanent visual loss and motor dysfunction.To date,no effective treatment exists as the exact causative mechanism remains unknown.Therefore,experimental models of neuromyelitis optica spectrum disorders are essential for exploring its pathogenesis and in screening for therapeutic targets.Since most patients with neuromyelitis optica spectrum disorders are seropositive for IgG autoantibodies against aquaporin-4,which is highly expressed on the membrane of astrocyte endfeet,most current experimental models are based on aquaporin-4-IgG that initially targets astrocytes.These experimental models have successfully simulated many pathological features of neuromyelitis optica spectrum disorders,such as aquaporin-4 loss,astrocytopathy,granulocyte and macrophage infiltration,complement activation,demyelination,and neuronal loss;however,they do not fully capture the pathological process of human neuromyelitis optica spectrum disorders.In this review,we summarize the currently known pathogenic mechanisms and the development of associated experimental models in vitro,ex vivo,and in vivo for neuromyelitis optica spectrum disorders,suggest potential pathogenic mechanisms for further investigation,and provide guidance on experimental model choices.In addition,this review summarizes the latest information on pathologies and therapies for neuromyelitis optica spectrum disorders based on experimental models of aquaporin-4-IgG-seropositive neuromyelitis optica spectrum disorders,offering further therapeutic targets and a theoretical basis for clinical trials.
基金supported by the National Natural Science Foundation of China under Grant Nos.523B2043 and 52475112.
文摘Machinery condition monitoring is beneficial to equipment maintenance and has been receiving much attention from academia and industry.Machine learning,especially deep learning,has become popular for machinery condition monitoring because that can fully use available data and computational power.Since significant accidents might be caused if wrong fault alarms are given for machine condition monitoring,interpretable machine learning models,integrate signal processing knowledge to enhance trustworthiness of models,are gradually becoming a research hotspot.A previous spectrum-based and interpretable optimized weights method has been proposed to indicate faulty and fundamental frequencies when the analyzed data only contains a healthy type and a fault type.Considering that multiclass fault types are naturally met in practice,this work aims to explore the interpretable optimized weights method for multiclass fault type scenarios.Therefore,a new multiclass optimized weights spectrum(OWS)is proposed and further studied theoretically and numerically.It is found that the multiclass OWS is capable of capturing the characteristic components associated with different conditions and clearly indicating specific fault characteristic frequencies(FCFs)corresponding to each fault condition.This work can provide new insights into spectrum-based fault classification models,and the new multiclass OWS also shows great potential for practical applications.
基金the King Salman center for Disability Research for funding this work through Research Group No.KSRG-2024-050.
文摘Artificial Intelligence(AI)is changing healthcare by helping with diagnosis.However,for doctors to trust AI tools,they need to be both accurate and easy to understand.In this study,we created a new machine learning system for the early detection of Autism Spectrum Disorder(ASD)in children.Our main goal was to build a model that is not only good at predicting ASD but also clear in its reasoning.For this,we combined several different models,including Random Forest,XGBoost,and Neural Networks,into a single,more powerful framework.We used two different types of datasets:(i)a standard behavioral dataset and(ii)a more complex multimodal dataset with images,audio,and physiological information.The datasets were carefully preprocessed for missing values,redundant features,and dataset imbalance to ensure fair learning.The results outperformed the state-of-the-art with a Regularized Neural Network,achieving 97.6%accuracy on behavioral data.Whereas,on the multimodal data,the accuracy is 98.2%.Other models also did well with accuracies consistently above 96%.We also used SHAP and LIME on a behavioral dataset for models’explainability.
文摘A number of fractal/multifractal methods are introduced for quantifying the mineral deposit spectrum which include a number-size model, grade-tonnage model, power spectrum model, multifractal model and an eigenvalue spectrum model. The first two models characterize mineral deposits spectra based on relationships among the measures of mineral deposits. These include the number of deposits, size of deposits, concentration and volume of mineral deposits. The last three methods that deal with the spatial-temporal spectra of mineral deposit studies are all expected to be popularized in near future. A case study of hydrothermal gold deposits from the Abitibi area, a world-class mineral district, is used to demonstrate the principle as well as the applications of methods proposed in this paper. It has been shown that fractal and multifractal models are generally applicable to modeling of mineral deposits and occurrences. Clusters of mineral deposits were identified by several methods including the power spectral analysis, singularity analysis and the eigenvalue analysis. These clusters contain most of the known mineral deposits in the Timmins and Kirkland Lake camps.
基金supported by the National Natural Science Foundation of China(Nos.11605163 and 21504085)the China Academy of Engineering Physics Foundation for Development of Science and Technology(No.201580103014 and No.2015B0301063)+1 种基金the Foundation for Special Talents in China Academy of Engineering Physics(No.TP201502-3)the Sichuan Science and Technology Development Foundation for Young Scientists(No.2017Q0050)
文摘Identifying the unknown geometric and material information of a multi-shield object by analyzing the radiation signature measurements is always an important problem in national and global security. In order to identify the unknown shielding layer thicknesses of a source/shield system with gamma-ray spectra, we have developed a derivative-free inverse radiation transport model based on a differential evolution algorithm with global and local neighbourhoods(IRT-DEGL). In the present paper, the IRT-DEGL model is further extended for estimating the unknown thicknesses with random initial guesses and material mass densities of multi-shielding layers as well as their combinations. Using the detected gamma-ray spectra,the illustration of inverse studies is implemented and the main influence factors for inverse results are also analyzed.
基金This project is supported by the 10th Five-year Plan Pre-research Project Foundation of China Weapon Industry Company, China(No.42001080701).
文摘The identification of the inter-electrode gap size in the high frequency group pulse micro-electrochemical machining （HGPECM） is mainly discussed. The auto-regressive（AR） model of group pulse current flowing across the cathode and the anode are created under different situations with different processing parameters and inter-electrode gap size. The AR model based on the current signals indicates that the order of the AR model is obviously different relating to the different processing conditions and the inter-electrode gap size; Moreover, it is different about the stability of the dynamic system, i.e. the white noise response of the Green＇s function of the dynamic system is diverse. In addition, power spectrum method is used in the analysis of the dynamic time series about the current signals with different inter-electrode gap size, the results show that there exists a strongest power spectrum peak, characteristic power spectrum（CPS）, to the current signals related to the different inter-electrode gap size in the range of 0～5 kHz. Therefore, the CPS of current signals can implement the identification of the inter-electrode gap.
基金This work was supported by the National Natural Science Foundation of China(82071540)and Yunnan University(CZ21623201)。
文摘Autism spectrum disorder(ASD)is typically characterized by common deficits in social skills and repetitive/stereotyped behaviors.It is widely accepted that genetic and environmental factors solely or in combination cause ASD.However,the underlying pathogenic mechanism is unclear due to its highly heterogeneous nature.To better understand the pathogenesis of ASD,various animal models have been generated,which can be generally divided into genetic,environment-induced,and idiopathic animal models.In this review,we summarize the common animals used for ASD study and then discuss the applications,clinical insights,as well as challenges and prospects of current ASD animal models.
基金National Natural Science Foundation of China Under Grant No. 50478112
文摘In this paper, a new spatial coherence model of seismic ground motions is proposed by a fitting procedure. The analytical expressions of modal combination （correlation） coefficients of structural response are developed for multi-support seismic excitations. The coefficients from both the numerical integration and analytical solutions are compared to verify the accuracy of the solutions. It is shown that the analytical expressions of numerical modal combination coefficients are of high accuracy. The results of random responses of an example bridge show that the analytical modal combination coefficients developed in this paper are accurate enough to meet the requirements needed in practice. In addition, the computational efficiency of the analytical solutions of the modal combination coefficients is demonstrated by the response computation of the example bridge. It is found that the time required for the structural response analysis by using the analytical modal combination coefficients is less than 1/20 of that using numerical integral methods.
文摘We consider a three-electron system in the Impurity Hubbard model with a coupling between nearest-neighbors. Our research aim consists of studying the structure of essential spectrum and discrete spectra of the energy operator of three-electron systems in the impurity Hubbard model in the quartet state of the system in a <em>v</em>-dimensional lattice. We have reduced the study of the spectrum of the three-electron quartet state operator in the impurity Hubbard model to the study of the spectrum of a simpler operator. We proved the essential spectra of the three-electron systems in the Impurity Hubbard model in the quartet state is the union of no more than six segments, and the discrete spectrum of the system is consists of no more than four eigenvalues.
基金Project supported by the State Key Development Program for Basic Research of China (Grant Nos 2008CB717803 and 2007ID103)the Research Fund for the Doctoral Program of Higher Education of China (Gant No 200610001023)
文摘The improved version of Los Alamos model with the multi-modal fission approach is used to analyse the prompt fission neutron spectrum and multiplicity for the neutron-induced fission of 237Np. The spectra of neutrons emitted from fragments for the three most dominant fission modes （standard Ⅰ, standard Ⅱ and superlong） are calculated separately and the total spectrum is synthesized. The multi-modal parameters contained in the spectrum model are determined on the basis of experimental data of fission fragment mass distributions. The calculated total prompt fission neutron spectrum and multiplicity are better agreement with the experimental data than those obtained from the conventional treatment of the Los Alamos model.
基金The National Natural Science Foundation of China under contract No.41606202the National Key Research and Development Program of China under contract No.2016YFC1401002the Open Fund of Key Laboratory of State Oceanic Administration(SOA) for Space Ocean Remote Sensing and Application under contract No.201601001
文摘Microwave remote sensing is one of the most useful methods for observing the ocean parameters. The Doppler frequency or interferometric phase of the radar echoes can be used for an ocean surface current speed retrieval,which is widely used in spaceborne and airborne radars. While the effect of the ocean currents and waves is interactional. It is impossible to retrieve the ocean surface current speed from Doppler frequency shift directly. In order to study the relationship between the ocean surface current speed and the Doppler frequency shift, a numerical ocean surface Doppler spectrum model is established and validated with a reference. The input parameters of ocean Doppler spectrum include an ocean wave elevation model, a directional distribution function, and wind speed and direction. The suitable ocean wave elevation spectrum and the directional distribution function are selected by comparing the ocean Doppler spectrum in C band with an empirical geophysical model function（CDOP）. What is more, the error sensitivities of ocean surface current speed to the wind speed and direction are analyzed. All these simulations are in Ku band. The simulation results show that the ocean surface current speed error is sensitive to the wind speed and direction errors. With VV polarization, the ocean surface current speed error is about 0.15 m/s when the wind speed error is 2 m/s, and the ocean surface current speed error is smaller than 0.3 m/s when the wind direction error is within 20° in the cross wind direction.
基金Supported by the National Natural Science Foundation of China (42174142)National Science and Technology Major Project (2017ZX05039-002)+2 种基金Operation Fund of China National Petroleum Corporation Logging Key Laboratory (2021DQ20210107-11)Fundamental Research Funds for Central Universities (19CX02006A)Major Science and Technology Project of China National Petroleum Corporation (ZD2019-183-006)。
文摘To make the quantitative results of nuclear magnetic resonance(NMR) transverse relaxation(T;) spectrums reflect the type and pore structure of reservoir more directly, an unsupervised clustering method was developed to obtain the quantitative pore structure information from the NMR T;spectrums based on the Gaussian mixture model(GMM). Firstly, We conducted the principal component analysis on T;spectrums in order to reduce the dimension data and the dependence of the original variables. Secondly, the dimension-reduced data was fitted using the GMM probability density function, and the model parameters and optimal clustering numbers were obtained according to the expectation-maximization algorithm and the change of the Akaike information criterion. Finally, the T;spectrum features and pore structure types of different clustering groups were analyzed and compared with T;geometric mean and T;arithmetic mean. The effectiveness of the algorithm has been verified by numerical simulation and field NMR logging data. The research shows that the clustering results based on GMM method have good correlations with the shape and distribution of the T;spectrum, pore structure, and petroleum productivity, providing a new means for quantitative identification of pore structure, reservoir grading, and oil and gas productivity evaluation.
文摘Maternal drinking during pregnancy can result in a wide spectrum of cognitive and behavioral abnormalities termed fetal alcohol spectrum disorders (FASD). The heterogeneity observed in FASD-related phenotypes can be attributed to a number of environmental and genetic factors;however, ethanol dose and timing of exposure may have significant influences. Here, we report the behavioral effects of acute, binge-like ethanol exposure at three neurodevelopmental times corresponding to the first, second, and third trimester of human development in C57BL/6J mice. Results show that developmental ethanol exposure consistently delays the development of basic motor skill reflexes and coordination as well as impairs spatial learning and memory. Observed changes in activity and anxiety-related behaviors, however, appear to be dependent on timing of alcohol exposure. The variability in behaviors between different treatment models suggests that these may be useful in evaluating the mechanisms disrupted by ethanol at specific neurodevelopmental times. The results provide further evidence that, regardless of developmental stage, the developing brain is acutely sensitive to alcohol exposure.
文摘A neurological abnormality called autism spectrum disorder(ASD)affects how a person perceives and interacts with others,leading to social interaction and communication issues.Limited and recurring behavioural patterns are another feature of the illness.Multiple mutations throughout development are the source of the neurodevelopmental disorder autism.However,a well-established model and perfect treatment for this spectrum disease has not been discovered.The rising era of the clustered regularly interspaced palindromic repeats(CRISPR)-associated protein 9(Cas9)system can streamline the complexity underlying the pathogenesis of ASD.The CRISPR-Cas9 system is a powerful genetic engineering tool used to edit the genome at the targeted site in a precise manner.The major hurdle in studying ASD is the lack of appropriate animal models presenting the complex symptoms of ASD.Therefore,CRISPR-Cas9 is being used worldwide to mimic the ASD-like pathology in various systems like in vitro cell lines,in vitro 3D organoid models and in vivo animal models.Apart from being used in establishing ASD models,CRISPR-Cas9 can also be used to treat the complexities of ASD.The aim of this review was to summarize and critically analyse the CRISPRCas9-mediated discoveries in the field of ASD.
文摘We consider a five-electron system in the Hubbard model with a coupling between nearest-neighbors. The structure of essential spectrum and discrete spectrum of the systems in the third and fourth doublet states in a <em>v</em>-dimensional lattice is investigated. We prove that the essential spectrum of the system in a third doublet state consists is the union of at most four segments, and discrete spectrum of the system is empty. We show that the essential spectrum of the system in a fourth doublet state consists of the union of at most seven segments, and discrete spectrum of the system consists of no more than one point.
基金Supported by the National Natural Science Foundation of China (No. 60372077)
文摘Capillary and capillary-gravity waves possess a random character, and the slope wavenumber spectra of them can be used to represent mean distributions of wave energy with respect to spatial scale of variability. But simple and practical models of the slope wavenumber spectra have not been put forward so far. In this article, we address the accurate definition of the slope wavenumber spectra of water surface capillary and capillary-gravity waves. By combining the existing slope wavenumber models and using the dispersion relation of water surface waves, we derive the slope wavenumber spectrum models of capillary and capillary-gravity waves. Simultaneously, by using the slope wavenumber models, the dependence of the slope wavenumber spectrum on wind speed is analyzed using data obtained in an experiment which was performed in a laboratory wind wave tank. Generally speaking, the slope wavenumber spectra are influenced profoundly by the wind speed above water surface. The slope wavenumber spectrum increases with wind speed obviously and do not cross each other for different wind speeds. But, for the same wind speed, the slope wavenumber spectra are essentially identical, even though the capillary and capillary-gravity waves are excited at different times and locations. Furthermore, the slope wavenumber spectra obtained from the models agree quite well with experimental results as regards both the values and the shape of the curve.
