OBJECTIVE:To investigate Acupuncture-herb therapy modulates gut microbiota in abdominal obesity.METHODS:A randomized controlled trial was designed in accordance with standard protocols.Abdominally obese subjects were ...OBJECTIVE:To investigate Acupuncture-herb therapy modulates gut microbiota in abdominal obesity.METHODS:A randomized controlled trial was designed in accordance with standard protocols.Abdominally obese subjects were randomized into four groups:A2(Control):double placebo,A1(Needle):press needle+placebo herb,A3(herb):herbal medicine(Huatan Lishi Fang化痰利湿方)+placebo needle,A4(Combination):press needle+herbal medicine.After 12 weeks of treatment,groups were relabeled B1-B4.Weight,waist circumference,and body mass index were measured monthly.Gut microbiota was analyzed via 16S rRNA sequencing for diversity and abundance.RESULTS:Combined needle-herb therapy significantly reduced waist circumference(P<0.05).All treatments altered gut microbiota composition.The combination group showed significant changes in diversity(Chao1,Shannon,Simpson;P<0.05).Needle therapy increased Bacteroidia;herbs reduced Lachnospiraceae and Megamonas.All results were significant(P<0.05).CONCLUSION:Combined needle-herb treatment modulated 25 key gut flora across multiple taxonomic levels in abdominal obesity.It reduced Firmicutes and Bacteroidota.Bacteroidota,Actinobacteriota,and Prevotellaceae may suppress obesity,whereas Proteobacteria,Lachnospiraceae,and Megamonas may promote it.The combination specifically altered Bacteroidaceae,Lachnospiraceae,Bacteroidia,and Megamonas.展开更多
Objective Adaptive immune responses play a critical role in the pathogenesis of amyotrophic lateral sclerosis(ALS).In this study,we investigated the functional mechanisms of T cell subtypes and assessed the causal lin...Objective Adaptive immune responses play a critical role in the pathogenesis of amyotrophic lateral sclerosis(ALS).In this study,we investigated the functional mechanisms of T cell subtypes and assessed the causal links between CD4+cytotoxic T cell-related genes and ALS risk.Methods Single-cell RNA sequencing(scRNA-seq)of peripheral blood mononuclear cells(PBMCs)from patients with ALS and healthy controls(HC)was used to identify differentially expressed genes(DEGs)in CD4+cytotoxic T cells.Comprehensive analyses of CD4+cytotoxic T cells,including pseudotemporal trajectory,intercellular communication,and metabolic pathway analysis,were performed.Mendelian randomization(MR)analysis evaluated the causal effects of DEGs on ALS risk,with validation using independent genome-wide association study(GWAS)data.Expression patterns of the causal genes were further verified using scRNA-seq,bulk-seq,and clinical samples.Results CD4+cytotoxic T cells were significantly expanded in patients with ALS.The upregulated genes S100A6,SERPINB6,SMAD7,and TPST2 were positively correlated with ALS susceptibility,whereas DIP2A showed a protective association.Conclusion S100A6,SERPINB6,SMAD7,TPST2,and DIP2A were identified as causal genes and potential therapeutic targets in ALS,implicating CD4+cytotoxic T cells in the disease mechanisms.Further studies targeting these genes and neuroinflammatory pathways are warranted.展开更多
The complete convergence for weighted sums of sequences of independent,identically distributed random variables under sublinear expectation space is studied.By moment inequality and truncation methods,we establish the...The complete convergence for weighted sums of sequences of independent,identically distributed random variables under sublinear expectation space is studied.By moment inequality and truncation methods,we establish the equivalent conditions of complete convergence for weighted sums of sequences of independent,identically distributed random variables under sublinear expectation space.The results complement the corresponding results in probability space to those for sequences of independent,identically distributed random variables under sublinear expectation space.展开更多
With the increasing complexity of substation inspection tasks,achieving efficient and safe path planning for Unmanned Aerial Vehicles in densely populated and structurally complex three-dimensional(3D)environments rem...With the increasing complexity of substation inspection tasks,achieving efficient and safe path planning for Unmanned Aerial Vehicles in densely populated and structurally complex three-dimensional(3D)environments remains a critical challenge.To address this problem,this paper proposes an improved path planning algorithm—Random Geometric Graph(RGG)-guided Rapidly-exploring Random Tree(R-RRT)—based on the classical Rapidly-exploring Random Tree(RRT)framework.First,a refined 3D occupancy grid map is constructed from Light Detection and Ranging point cloud data through ground filtering,noise removal,coordinate transformation,and obstacle inflation using spherical structuring elements.During the planning stage,a dynamic goal-biasing strategy is introduced to adaptively adjust the sampling direction,the sampling distribution is optimized using a pre-generated RGG,and collision detection is accelerated via a K-Dimensional Tree structure.After initial trajectory generation,redundant nodes are eliminated via greedy pruning,and a curvature-minimizing gradient-based optimizationmethod is applied to smooth the trajectory.Experimental results conducted in a simulated substation environment demonstrate that,compared with mainstream path planning algorithms,the proposed R-RRT achieves superior performance in terms of path length,planning time,and trajectory smoothness.Comprehensive analysis shows that the proposed method significantly enhances trajectory quality,planning efficiency,and operational safety,validating its applicability and advantages for high-precision 3D path planning in complex substation inspection scenarios.展开更多
Objectives:To explore the efficacy and safety of virtual reality(VR)in relieving negative emotions in patients with breast cancer with different personalities.Methods:A randomized controlled trial was conducted.Betwee...Objectives:To explore the efficacy and safety of virtual reality(VR)in relieving negative emotions in patients with breast cancer with different personalities.Methods:A randomized controlled trial was conducted.Between April 2023 and October 2023,we enrolled patients with breast cancer treated in the Department of Breast Cancer and Oncology at Sun Yat-Sen Memorial Hospital,Sun Yat-Sen University,Guangdong Province.The patients were randomly divided into an intervention group(n=118)and a control group(n=119)using block randomization.The intervention group received the VR intervention 3-5 times over 5±2 weeks using natural landscapes with music or relaxation guidance,and the duration of each VR intervention was 15±3 min.The control group received routine nursing care,including disease education and psychological counseling.Patients were assessed using the Type D Scale,Positive and Negative Affect Scale,and Distress Thermometer,and adverse events during the intervention were recorded.Results:Overall,85 patients completed the study(44 in the intervention group and 41 in the control group).Patients with Type D personalities showed more negative emotions[25.0(21.5,27.5)vs.19.0(16.0,24.0),P=0.001]and distressed attitudes[4.0(2.0,5.0)vs.3.0(1.0,4.0),P=0.020]with fewer positive emotions(27.2±5.6 vs.31.0±5.9,P=0.014)than those with non-Type D personalities.Total population analysis revealed no significant differences between the groups.However,in the subgroup analysis,patients with Type D personalities in the intervention group showed greater relief from negative emotions than those in the control group[median difference,-5.0(-9.0,-2.5)vs.-2.0(-4.0,2.0),P=0.046].No significant differences were found between groups of patients with non-Type D personality traits.The proportion of adverse events was not significantly different between groups(P=0.110).Conclusions:Breast cancer patients with Type D personalities suffer more severe negative emotions and distress,and more attention should be paid to them.VR intervention significantly and safely reduced negative emotions in patients with Type D personalities.展开更多
The rapid rise of antibiotic-resistant bacteria has created an urgent need for alternative treatments,such as bacteriophage therapy,which relies on phages to selectively eliminate specific bacterial pathogens.However,...The rapid rise of antibiotic-resistant bacteria has created an urgent need for alternative treatments,such as bacteriophage therapy,which relies on phages to selectively eliminate specific bacterial pathogens.However,the success of phage therapy hinges on accurately matching phages to their bacterial hosts,and predicting these phage–host interactions(PHIs)remains a significant challenge.The existing computational approaches for PHI prediction have major limitations.For example,the PredPHI model achieves less than 70%accuracy,and most methods predict only broad host categories(e.g.,genus levels)rather than pinpointing the exact bacterial strain.To address these gaps,we present a novel data-driven framework that predicts PHIs at the individual host strain level using only protein amino acid sequence data as input.Our approach extracts informative features from protein sequences—including amino acid composition(AAC),key chemical element abundance(AC),and molecular weight(MW)—and employs a one-dimensional convolutional neural network(1D CNN)tailored for sequential protein data.To further increase the prediction accuracy and mitigate class imbalance,we train multiple CNN models on different subsets of the data and integrate their outputs via a weighted ensemble strategy.This ensemble 1D CNN model achieves an AUC of 0.968,an AUPR of 0.976,an accuracy of 88%,and a sensitivity of 0.911,with a Matthews correlation coefficient(MCC)approximately 40%greater than that of PredPHI.Overall,this data-driven bioinformatics approach provides a powerful tool for rapid phage–host matching and custom phage design,potentially accelerating the development of targeted phage therapy.展开更多
This study introduces a novel method for reconstructing the 3D model of aluminum foam using cross-sectional sequence images.Combining precision milling and image acquisition,high-qual-ity cross-sectional images are ob...This study introduces a novel method for reconstructing the 3D model of aluminum foam using cross-sectional sequence images.Combining precision milling and image acquisition,high-qual-ity cross-sectional images are obtained.Pore structures are segmented by the U-shaped network(U-Net)neural network integrated with the Canny edge detection operator,ensuring accurate pore delineation and edge extraction.The trained U-Net achieves 98.55%accuracy.The 2D data are superimposed and processed into 3D point clouds,enabling reconstruction of the pore structure and aluminum skeleton.Analysis of pore 01 shows the cross-sectional area initially increases,and then decreases with milling depth,with a uniform point distribution of 40 per layer.The reconstructed model exhibits a porosity of 77.5%,with section overlap rates between the 2D pore segmentation and the reconstructed model exceeding 96%,confirming high fidelity.Equivalent sphere diameters decrease with size,averaging 1.95 mm.Compression simulations reveal that the stress-strain curve of the 3D reconstruction model of aluminum foam exhibits fluctuations,and the stresses in the reconstruction model concentrate on thin cell walls,leading to localized deformations.This method accurately restores the aluminum foam’s complex internal structure,improving reconstruction preci-sion and simulation reliability.The approach offers a cost-efficient,high-precision technique for optimizing material performance in engineering applications.展开更多
In this article, the authors study some limit properties for sequences of pairwise NQD random variables, which are not necessarily identically distributed. They obtain Baum and Katz complete convergence and the strong...In this article, the authors study some limit properties for sequences of pairwise NQD random variables, which are not necessarily identically distributed. They obtain Baum and Katz complete convergence and the strong stability of Jamison＇s weighted sums for pairwise NQD random variables, which may have different distributions. Some wellknown results are improved and extended.展开更多
This paper discusses complete convergence properties of the sums of -mixing random sequences.As a result,we improve the corresponding results of Wu Qunying(2001). And extended the Baum and Katz complete convergence ...This paper discusses complete convergence properties of the sums of -mixing random sequences.As a result,we improve the corresponding results of Wu Qunying(2001). And extended the Baum and Katz complete convergence to the case of -mixing random sequences by moment inequality and truncating without necessarily adding any extra conditions.展开更多
Random numbers play a crucial role in modern security schemes. Couple to the rapid development of cryptography, the strength of security protocols and encryption algorithms consumingly relies on the quality of random ...Random numbers play a crucial role in modern security schemes. Couple to the rapid development of cryptography, the strength of security protocols and encryption algorithms consumingly relies on the quality of random number. With simple architecture and faster speed, linear feedback shift register often is selected in many applications. However, the random sequence generated by LFSR can not meet the demand of unpredictability for secure mechanism. Genetic algorithm improves the linear property of LFSR and constructs a novel random sequence generator with longer period and complex architecture.展开更多
We first obtain the Petrov theorem for pairwise NQD（negative quadrant dependent） random variables which may have different distributions.Some well-known results are improved and extended.Next,we give an example to c...We first obtain the Petrov theorem for pairwise NQD（negative quadrant dependent） random variables which may have different distributions.Some well-known results are improved and extended.Next,we give an example to clarify one of the important properties of sequences of pairwise NQD random variables,so that we can point out some mistakes that have appeared in recent published papers.展开更多
We give some theorems of strong law of large numbers and complete convergence for sequences of φ-mixing random variables. In particular, Wittmann＇s strong law of large numbers and Teicher＇s strong law of large nnum...We give some theorems of strong law of large numbers and complete convergence for sequences of φ-mixing random variables. In particular, Wittmann＇s strong law of large numbers and Teicher＇s strong law of large nnumbers for independent random variables are generalized to the case of φ -minxing random variables.展开更多
Let （Xn）n∈EN be a sequence of arbitrary continuous random variables, by the notion of relative entropy hμ^μ（w） as a measure of dissimilarity between probability measure # and reference measure μ, the explicit,...Let （Xn）n∈EN be a sequence of arbitrary continuous random variables, by the notion of relative entropy hμ^μ（w） as a measure of dissimilarity between probability measure # and reference measure μ, the explicit, general bounds for the partial sums of arbitrary continuous random variables under suitable conditions are developed. The argument uses the known and elementary lcmma of convergence for likelihood ratio.展开更多
In this paper, a random sequence generator based on chaotic circuits is presented.Fundamental principle and experimental circuit have been carried out in case of Chua's circuit.The statistical results are in good ...In this paper, a random sequence generator based on chaotic circuits is presented.Fundamental principle and experimental circuit have been carried out in case of Chua's circuit.The statistical results are in good agreement with probability characteristics of random sequence.展开更多
This paper proved the statement that a good linear block encoder is in fact a good local-random sequence generator. Furthermore, this statement discovers the deep relationship between the error-correcting coding theor...This paper proved the statement that a good linear block encoder is in fact a good local-random sequence generator. Furthermore, this statement discovers the deep relationship between the error-correcting coding theory and the modern cryptography.展开更多
We mainly study the almost sure limiting behavior of weighted sums of the form ∑ni=1 aiXi/bn , where {Xn, n ≥ 1} is an arbitrary Banach space valued random element sequence or Banach space valued martingale differen...We mainly study the almost sure limiting behavior of weighted sums of the form ∑ni=1 aiXi/bn , where {Xn, n ≥ 1} is an arbitrary Banach space valued random element sequence or Banach space valued martingale difference sequence and {an, n ≥ 1} and {bn,n ≥ 1} are two sequences of positive constants. Some new strong laws of large numbers for such weighted sums are proved under mild conditions.展开更多
In this paper, we obtain the Hejek-Renyi-type inequality for a class of random variable sequences and give some applications for associated random variable sequences, strongly positive dependent stochastic sequences a...In this paper, we obtain the Hejek-Renyi-type inequality for a class of random variable sequences and give some applications for associated random variable sequences, strongly positive dependent stochastic sequences and martingale difference sequences which generalize and improve the results of Prakasa Rao and Soo published in Statist. Probab. Lett., 57（2002） and 78（2008）. Using this result, we get the integrability of supremum and the strong law of large numbers for a class of random variable sequences.展开更多
We first design a discrete hyperchaotic system via piece-wise linear state feedback. The states of the closed loop system are locally expanding in two directions but absolutely bounded on the whole, which implies hype...We first design a discrete hyperchaotic system via piece-wise linear state feedback. The states of the closed loop system are locally expanding in two directions but absolutely bounded on the whole, which implies hyperchaos. Then, we use three suchlike hyperchaotic systems with different feedback gain matrices to design a pseudo-random sequence generator (PRSG). Through a threshold function, three sub-sequences generated from the output of piecewise linear functions are changed into 0-1 sequences. Then, followed by XOR operation, an unpredictable pseudo-random sequence (PRS) is ultimately obtained. The analysis and simulation results indicate that the PRS, generated with hyperchaotic systems, has desirable statistical features.展开更多
基金Supported by National Key R&D Program of China:Clinical Evaluation Research on Intervention Technologies for Abdominal Obesitythe Role of Gut Microbiota in the Effects of Combined Acupuncture and Medication on Abdominal Obesity:an Exploration with 16S rRNA Technology(Project Code:2019YFC1710102)。
文摘OBJECTIVE:To investigate Acupuncture-herb therapy modulates gut microbiota in abdominal obesity.METHODS:A randomized controlled trial was designed in accordance with standard protocols.Abdominally obese subjects were randomized into four groups:A2(Control):double placebo,A1(Needle):press needle+placebo herb,A3(herb):herbal medicine(Huatan Lishi Fang化痰利湿方)+placebo needle,A4(Combination):press needle+herbal medicine.After 12 weeks of treatment,groups were relabeled B1-B4.Weight,waist circumference,and body mass index were measured monthly.Gut microbiota was analyzed via 16S rRNA sequencing for diversity and abundance.RESULTS:Combined needle-herb therapy significantly reduced waist circumference(P<0.05).All treatments altered gut microbiota composition.The combination group showed significant changes in diversity(Chao1,Shannon,Simpson;P<0.05).Needle therapy increased Bacteroidia;herbs reduced Lachnospiraceae and Megamonas.All results were significant(P<0.05).CONCLUSION:Combined needle-herb treatment modulated 25 key gut flora across multiple taxonomic levels in abdominal obesity.It reduced Firmicutes and Bacteroidota.Bacteroidota,Actinobacteriota,and Prevotellaceae may suppress obesity,whereas Proteobacteria,Lachnospiraceae,and Megamonas may promote it.The combination specifically altered Bacteroidaceae,Lachnospiraceae,Bacteroidia,and Megamonas.
文摘Objective Adaptive immune responses play a critical role in the pathogenesis of amyotrophic lateral sclerosis(ALS).In this study,we investigated the functional mechanisms of T cell subtypes and assessed the causal links between CD4+cytotoxic T cell-related genes and ALS risk.Methods Single-cell RNA sequencing(scRNA-seq)of peripheral blood mononuclear cells(PBMCs)from patients with ALS and healthy controls(HC)was used to identify differentially expressed genes(DEGs)in CD4+cytotoxic T cells.Comprehensive analyses of CD4+cytotoxic T cells,including pseudotemporal trajectory,intercellular communication,and metabolic pathway analysis,were performed.Mendelian randomization(MR)analysis evaluated the causal effects of DEGs on ALS risk,with validation using independent genome-wide association study(GWAS)data.Expression patterns of the causal genes were further verified using scRNA-seq,bulk-seq,and clinical samples.Results CD4+cytotoxic T cells were significantly expanded in patients with ALS.The upregulated genes S100A6,SERPINB6,SMAD7,and TPST2 were positively correlated with ALS susceptibility,whereas DIP2A showed a protective association.Conclusion S100A6,SERPINB6,SMAD7,TPST2,and DIP2A were identified as causal genes and potential therapeutic targets in ALS,implicating CD4+cytotoxic T cells in the disease mechanisms.Further studies targeting these genes and neuroinflammatory pathways are warranted.
基金supported by Doctoral Scientific Research Starting Foundation of Jingdezhen Ceramic University(Grant No.102/01003002031)Re-accompanying Funding Project of Academic Achievements of Jingdezhen Ceramic University(Grant Nos.215/20506277,215/20506341)。
文摘The complete convergence for weighted sums of sequences of independent,identically distributed random variables under sublinear expectation space is studied.By moment inequality and truncation methods,we establish the equivalent conditions of complete convergence for weighted sums of sequences of independent,identically distributed random variables under sublinear expectation space.The results complement the corresponding results in probability space to those for sequences of independent,identically distributed random variables under sublinear expectation space.
基金Funding for this research was provided by the Program for Scientific Research Innovation Team in Colleges and Universities of Anhui Province(No.2022AH010095)the Hefei Key Technology R&D“Champion-Based Selection”Project(No.2023SGJ011).
文摘With the increasing complexity of substation inspection tasks,achieving efficient and safe path planning for Unmanned Aerial Vehicles in densely populated and structurally complex three-dimensional(3D)environments remains a critical challenge.To address this problem,this paper proposes an improved path planning algorithm—Random Geometric Graph(RGG)-guided Rapidly-exploring Random Tree(R-RRT)—based on the classical Rapidly-exploring Random Tree(RRT)framework.First,a refined 3D occupancy grid map is constructed from Light Detection and Ranging point cloud data through ground filtering,noise removal,coordinate transformation,and obstacle inflation using spherical structuring elements.During the planning stage,a dynamic goal-biasing strategy is introduced to adaptively adjust the sampling direction,the sampling distribution is optimized using a pre-generated RGG,and collision detection is accelerated via a K-Dimensional Tree structure.After initial trajectory generation,redundant nodes are eliminated via greedy pruning,and a curvature-minimizing gradient-based optimizationmethod is applied to smooth the trajectory.Experimental results conducted in a simulated substation environment demonstrate that,compared with mainstream path planning algorithms,the proposed R-RRT achieves superior performance in terms of path length,planning time,and trajectory smoothness.Comprehensive analysis shows that the proposed method significantly enhances trajectory quality,planning efficiency,and operational safety,validating its applicability and advantages for high-precision 3D path planning in complex substation inspection scenarios.
基金supported by a project of the National Natural Science Foundation of China:Research on the integration of artificial intelligence and virtual reality technology to promote psychological rehabilitation of breast cancer patients with different personalities(project approval no.82073408).
文摘Objectives:To explore the efficacy and safety of virtual reality(VR)in relieving negative emotions in patients with breast cancer with different personalities.Methods:A randomized controlled trial was conducted.Between April 2023 and October 2023,we enrolled patients with breast cancer treated in the Department of Breast Cancer and Oncology at Sun Yat-Sen Memorial Hospital,Sun Yat-Sen University,Guangdong Province.The patients were randomly divided into an intervention group(n=118)and a control group(n=119)using block randomization.The intervention group received the VR intervention 3-5 times over 5±2 weeks using natural landscapes with music or relaxation guidance,and the duration of each VR intervention was 15±3 min.The control group received routine nursing care,including disease education and psychological counseling.Patients were assessed using the Type D Scale,Positive and Negative Affect Scale,and Distress Thermometer,and adverse events during the intervention were recorded.Results:Overall,85 patients completed the study(44 in the intervention group and 41 in the control group).Patients with Type D personalities showed more negative emotions[25.0(21.5,27.5)vs.19.0(16.0,24.0),P=0.001]and distressed attitudes[4.0(2.0,5.0)vs.3.0(1.0,4.0),P=0.020]with fewer positive emotions(27.2±5.6 vs.31.0±5.9,P=0.014)than those with non-Type D personalities.Total population analysis revealed no significant differences between the groups.However,in the subgroup analysis,patients with Type D personalities in the intervention group showed greater relief from negative emotions than those in the control group[median difference,-5.0(-9.0,-2.5)vs.-2.0(-4.0,2.0),P=0.046].No significant differences were found between groups of patients with non-Type D personality traits.The proportion of adverse events was not significantly different between groups(P=0.110).Conclusions:Breast cancer patients with Type D personalities suffer more severe negative emotions and distress,and more attention should be paid to them.VR intervention significantly and safely reduced negative emotions in patients with Type D personalities.
基金supported by the Beijing Genomics Institute under grant numbers 62203134,6220020329 and 62176164Scientific Foundation for Youth Scholars of Shenzhen University 868-000001033385.The author gratefully acknowledges the support provided by the“Design of phage tail protein based on adversarial machine learning”project and the“Construction of artificial phage model based on deep generative adversarial network learning”project.And the datasets is provided by BGI-Shenzhen.
文摘The rapid rise of antibiotic-resistant bacteria has created an urgent need for alternative treatments,such as bacteriophage therapy,which relies on phages to selectively eliminate specific bacterial pathogens.However,the success of phage therapy hinges on accurately matching phages to their bacterial hosts,and predicting these phage–host interactions(PHIs)remains a significant challenge.The existing computational approaches for PHI prediction have major limitations.For example,the PredPHI model achieves less than 70%accuracy,and most methods predict only broad host categories(e.g.,genus levels)rather than pinpointing the exact bacterial strain.To address these gaps,we present a novel data-driven framework that predicts PHIs at the individual host strain level using only protein amino acid sequence data as input.Our approach extracts informative features from protein sequences—including amino acid composition(AAC),key chemical element abundance(AC),and molecular weight(MW)—and employs a one-dimensional convolutional neural network(1D CNN)tailored for sequential protein data.To further increase the prediction accuracy and mitigate class imbalance,we train multiple CNN models on different subsets of the data and integrate their outputs via a weighted ensemble strategy.This ensemble 1D CNN model achieves an AUC of 0.968,an AUPR of 0.976,an accuracy of 88%,and a sensitivity of 0.911,with a Matthews correlation coefficient(MCC)approximately 40%greater than that of PredPHI.Overall,this data-driven bioinformatics approach provides a powerful tool for rapid phage–host matching and custom phage design,potentially accelerating the development of targeted phage therapy.
基金supported by the Key Research and DevelopmentPlan in Shanxi Province of China(No.201803D421045)the Natural Science Foundation of Shanxi Province(No.2021-0302-123104)。
文摘This study introduces a novel method for reconstructing the 3D model of aluminum foam using cross-sectional sequence images.Combining precision milling and image acquisition,high-qual-ity cross-sectional images are obtained.Pore structures are segmented by the U-shaped network(U-Net)neural network integrated with the Canny edge detection operator,ensuring accurate pore delineation and edge extraction.The trained U-Net achieves 98.55%accuracy.The 2D data are superimposed and processed into 3D point clouds,enabling reconstruction of the pore structure and aluminum skeleton.Analysis of pore 01 shows the cross-sectional area initially increases,and then decreases with milling depth,with a uniform point distribution of 40 per layer.The reconstructed model exhibits a porosity of 77.5%,with section overlap rates between the 2D pore segmentation and the reconstructed model exceeding 96%,confirming high fidelity.Equivalent sphere diameters decrease with size,averaging 1.95 mm.Compression simulations reveal that the stress-strain curve of the 3D reconstruction model of aluminum foam exhibits fluctuations,and the stresses in the reconstruction model concentrate on thin cell walls,leading to localized deformations.This method accurately restores the aluminum foam’s complex internal structure,improving reconstruction preci-sion and simulation reliability.The approach offers a cost-efficient,high-precision technique for optimizing material performance in engineering applications.
基金the National Natural Science Foundation of China(10671149)
文摘In this article, the authors study some limit properties for sequences of pairwise NQD random variables, which are not necessarily identically distributed. They obtain Baum and Katz complete convergence and the strong stability of Jamison＇s weighted sums for pairwise NQD random variables, which may have different distributions. Some wellknown results are improved and extended.
基金Supported by the National Natural Science Foundation of China（11061012） Supported by the Natural Science Foundation of Guangxi（2010GXNSFA013121）
文摘This paper discusses complete convergence properties of the sums of -mixing random sequences.As a result,we improve the corresponding results of Wu Qunying(2001). And extended the Baum and Katz complete convergence to the case of -mixing random sequences by moment inequality and truncating without necessarily adding any extra conditions.
基金Supported by the National Natural Science Foundation of China (60373087, 90104005 and 60473023)
文摘Random numbers play a crucial role in modern security schemes. Couple to the rapid development of cryptography, the strength of security protocols and encryption algorithms consumingly relies on the quality of random number. With simple architecture and faster speed, linear feedback shift register often is selected in many applications. However, the random sequence generated by LFSR can not meet the demand of unpredictability for secure mechanism. Genetic algorithm improves the linear property of LFSR and constructs a novel random sequence generator with longer period and complex architecture.
基金Supported by the National Natural Science Foundation of China (10671149)
文摘We first obtain the Petrov theorem for pairwise NQD（negative quadrant dependent） random variables which may have different distributions.Some well-known results are improved and extended.Next,we give an example to clarify one of the important properties of sequences of pairwise NQD random variables,so that we can point out some mistakes that have appeared in recent published papers.
基金Supported by the National Natural Science Foundation of China (10671149)
文摘We give some theorems of strong law of large numbers and complete convergence for sequences of φ-mixing random variables. In particular, Wittmann＇s strong law of large numbers and Teicher＇s strong law of large nnumbers for independent random variables are generalized to the case of φ -minxing random variables.
基金Supported by the NNSF of China(10571076) Anhui High Education Research Grant( 2006Kj246B).
文摘Let （Xn）n∈EN be a sequence of arbitrary continuous random variables, by the notion of relative entropy hμ^μ（w） as a measure of dissimilarity between probability measure # and reference measure μ, the explicit, general bounds for the partial sums of arbitrary continuous random variables under suitable conditions are developed. The argument uses the known and elementary lcmma of convergence for likelihood ratio.
基金Supported by the Doctoral Fund of the State Education Committee of Chinathe Nature Science Foundation of Zhejiang Province
文摘In this paper, a random sequence generator based on chaotic circuits is presented.Fundamental principle and experimental circuit have been carried out in case of Chua's circuit.The statistical results are in good agreement with probability characteristics of random sequence.
基金Supported by Trans-century Training Program Foundation for the Talents by the State Education Commission
文摘This paper proved the statement that a good linear block encoder is in fact a good local-random sequence generator. Furthermore, this statement discovers the deep relationship between the error-correcting coding theory and the modern cryptography.
基金Supported by the National Natural Science Foundationof China (10671149)
文摘We mainly study the almost sure limiting behavior of weighted sums of the form ∑ni=1 aiXi/bn , where {Xn, n ≥ 1} is an arbitrary Banach space valued random element sequence or Banach space valued martingale difference sequence and {an, n ≥ 1} and {bn,n ≥ 1} are two sequences of positive constants. Some new strong laws of large numbers for such weighted sums are proved under mild conditions.
基金The NSF(10871001,60803059) of ChinaTalents Youth Fund(2010SQRL016ZD) of Anhi Province Universities+2 种基金Youth Science Research Fund(2009QN011A) of Anhui UniversityProvincial Natural Science Research Project of Anhui Colleges(KJ2010A005)Academic innovation team of Anhui University (KJTD001B)
文摘In this paper, we obtain the Hejek-Renyi-type inequality for a class of random variable sequences and give some applications for associated random variable sequences, strongly positive dependent stochastic sequences and martingale difference sequences which generalize and improve the results of Prakasa Rao and Soo published in Statist. Probab. Lett., 57（2002） and 78（2008）. Using this result, we get the integrability of supremum and the strong law of large numbers for a class of random variable sequences.
基金This project was supported by the National Natural Science Foundation of China (69874025).
文摘We first design a discrete hyperchaotic system via piece-wise linear state feedback. The states of the closed loop system are locally expanding in two directions but absolutely bounded on the whole, which implies hyperchaos. Then, we use three suchlike hyperchaotic systems with different feedback gain matrices to design a pseudo-random sequence generator (PRSG). Through a threshold function, three sub-sequences generated from the output of piecewise linear functions are changed into 0-1 sequences. Then, followed by XOR operation, an unpredictable pseudo-random sequence (PRS) is ultimately obtained. The analysis and simulation results indicate that the PRS, generated with hyperchaotic systems, has desirable statistical features.
