A method to extract information of network connection status information from physical memory on Windows Vista operating system is proposed. Using this method, a forensic examiner can extract accurately the informatio...A method to extract information of network connection status information from physical memory on Windows Vista operating system is proposed. Using this method, a forensic examiner can extract accurately the information of current TCP/ IP network connection information, including IDs of processes which established connections, establishing time, local address, local port, remote address, remote port, etc., from a physical memory on Windows Xflsta operating system. This method is reliable and efficient. It is verified on Windows Vista, Windows Vista SP1, Windows Vista SP2.展开更多
Addressing the critical detection range limitation in active electrosensing(AES)for underwater sensing,this study proposes an enhanced AES system via novel array optimization.While AES offers advantages like interfere...Addressing the critical detection range limitation in active electrosensing(AES)for underwater sensing,this study proposes an enhanced AES system via novel array optimization.While AES offers advantages like interference immunity,acoustic stealth detection,and low cost,its short range restricts applicability.A target perturbation model under differential signal acquisition reveals that signal strength increases with local electric field intensity,target size,differential channel spacing,and conductivity contrast,but decreases with target-electrode distance.To extend detection,novel array configurations were explored.Simulations demonstrate that both rectangular and offset arrays significantly outperform the traditional collinear layout.Specifically,an offset array(with 8 m transmitting–receiving spacing)achieved an effective detection range enhancement exceeding 83%under the same distortion threshold while maintaining simplified electrode structure.Experimental validation confirmed a 100%increase in maximum detection distance to 5 m under identical noise thresholds compared to the collinear array.Furthermore,a fully connected neural network-based localization model achieved a mean positioning error of 14.12 cm at 3.15 m in static scenarios.In dynamic scenarios within 1–3 m,mean errors were controlled between 13.19 cm and 27.56 cm.Mechanistic analysis indicates that increasing the array baseline enhances the signal-to-noise ratio by simultaneously suppressing near-field environmental noise and amplifying far-field signal reception.Structural innovations in array design enabled this study to significantly expand the detection range of AES systems without compromising cost efficiency.These advancements directly promote the engineering application of AES technology,offering critical technical support for underwater defense security monitoring,long-range early warning systems,and maritime rights protection.展开更多
A dual‑task parallel machine learning framework was developed by integrating a convolutional autoencoder(CAE)and a fully connected neural network(FCNN)via the gradient‑coupled mechanism,enabling simultaneous data comp...A dual‑task parallel machine learning framework was developed by integrating a convolutional autoencoder(CAE)and a fully connected neural network(FCNN)via the gradient‑coupled mechanism,enabling simultaneous data compression‑reconstruction and structural damage identification.Under the condition where 40% of the sensor nodes are missing,the model successfully reconstructs the full sensor network with an R^(2) of 0.916 and normalized root mean square error(NRMSE)of 0.0288.Even under significant noise contamination with an SNR of 12 dB,the model maintains strong reconstruction performance,achieving a R^(2) of 0.910 and NRMSE of 0.0253.Forty‑six structural damage scenarios were simulated using the scaled bridge model.The accuracy of spatial localization and quantification of the damage severity using the framework exceeds 99.3%.The proposed framework reduces the training time by 54.4%and iteration counts by 45.5% compared to conventional two‑stage machine learning approaches,demonstrating the efficiency of gradient‑coupled optimization.展开更多
In this paper we introduce a minimax model for network connection problems with interval parameters. We consider how to connect given nodes in a network with a path or a spanning tree under a given budget, where each ...In this paper we introduce a minimax model for network connection problems with interval parameters. We consider how to connect given nodes in a network with a path or a spanning tree under a given budget, where each link is associated with an interval and can be established at a cost of any value in the interval. The quality of an individual link （or the risk of link failure, etc.） depends on its construction cost and associated interval. To achieve fairness of the network connection, our model aims at the minimization of the maximum risk over all links used. We propose two algorithms that find optimal paths and spanning trees in polynomial time, respectively. The polynomial solvability indicates salient difference between our minimax model and the model of robust deviation criterion for network connection with interval data, which gives rise to NP-hard optimization problems.展开更多
The efficient development of the urban economy is a major concern of scholars in the fields of geography and urban science.In the context of globalization,informatization,industrialization,and urbanization,the externa...The efficient development of the urban economy is a major concern of scholars in the fields of geography and urban science.In the context of globalization,informatization,industrialization,and urbanization,the external relationships of China's cities are experiencing the joint action of urban scale hierarchies and connection networks(“hierarchy-network”).However,under the interactive effect of the two,the mechanism of urban economic efficiency(UEE)is unclear.Therefore,based on Baidu migration data,the regionalization with dynamically constrained agglomerative clustering and partitioning(REDCAP)method,and a spatial simultaneous equation model,this paper analyzes the UEE spatial pattern and mechanism in China.The results indicate that:(1)the urban economy has a superlinear relationship with the population size.However,the benefit of this superlinear growth is in marginal decline.(2)The UEE shows a pattern of differentiation between China's eastern,then central,and then western region.Also,local differences are found within the three major sub-regions.(3)The increase of urban network centrality can promote UEE,while the impact of urban scale is negative.(4)There is regional heterogeneity of the interactive effect of“hierarchy-network”on UEE.This study reveals the influencing mechanism of UEE and also provides policy implications for the development of UEE.展开更多
The network services today require extremely agile and mobile, however, the traditional IP infrastructures are so rigid that cannot fit services well. A way should be put forward to automate the network to improve res...The network services today require extremely agile and mobile, however, the traditional IP infrastructures are so rigid that cannot fit services well. A way should be put forward to automate the network to improve responsiveness to change. SDN and network virtualization(NV) are two hottest approaches to make networking more automated and scalable to support virtualized and cloud environments. Network virtualization combines hardware and software network resources and network functionality into a single virtual network. SDN is created to simplify traffic management and achieve operational efficiencies by establish and exercising central control over packet forwarding. In this paper, we focus on the situation where SDN controller needs to connect two virtual networks temporarily. We put forward three algorithms to try to make this connection more effective and evaluate these three algorithms.展开更多
BACKGROUND Currently,adolescent depression is one of the most significant public health concerns,markedly influencing emotional,cognitive,and social maturation.Despite advancements in distinguish the neurobiological s...BACKGROUND Currently,adolescent depression is one of the most significant public health concerns,markedly influencing emotional,cognitive,and social maturation.Despite advancements in distinguish the neurobiological substrates underlying depression,the intricate patterns of disrupted brain network connectivity in adolescents warrant further exploration.AIM To elucidate the neural correlates of adolescent depression by examining brain network connectivity using resting-state functional magnetic resonance imaging(rs-fMRI).METHODS The study cohort comprised 74 depressed adolescents and 59 healthy controls aged 12 to 17 years.Participants underwent rs-fMRI to evaluate functional connectivity within and across critical brain networks,including the visual,default mode network(DMN),dorsal attention,salience,somatomotor,and frontoparietal control networks.RESULTS Analyses revealed pronounced functional disparities within key neural circuits among adolescents with depression.The results demonstrated existence of hemispheric asymmetries characterized by enhanced activity in the left visual network,which contrasted the diminished activity in the right hemisphere.The DMN facilitated increased activity within the left prefrontal cortex and reduced engagement in the right hemisphere,implicating disrupted self-referential and emotional processing mechanisms.Additionally,an overactive right dorsal attention network and a hypoactive salience network were identified,underscoring significant abnormalities in attentional and emotional regulation in adolescent depression.CONCLUSION The findings from this study underscore distinct neural connectivity disruptions in adolescent depression,underscoring the critical role of specific neurobiological markers for precise early diagnosis of adolescent depression.The observed functional asymmetries and network-specific deviations elucidate the complex neurobiological architecture of adolescent depression,supporting the development of targeted therapeutic strategies.展开更多
In this paper,we investigate the distributed Nash equilibrium(NE)seeking problem for aggregative games with multiple uncertain Euler–Lagrange(EL)systems over jointly connected and weight-balanced switching networks.T...In this paper,we investigate the distributed Nash equilibrium(NE)seeking problem for aggregative games with multiple uncertain Euler–Lagrange(EL)systems over jointly connected and weight-balanced switching networks.The designed distributed controller consists of two parts:a dynamic average consensus part that asymptotically reproduces the unknown NE,and an adaptive reference-tracking module responsible for steering EL systems’positions to track a desired trajectory.The generalized Barbalat’s Lemma is used to overcome the discontinuity of the closed-loop system caused by the switching networks.The proposed algorithm is illustrated by a sensor network deployment problem.展开更多
Determinations of fracture network connections would help the investigators remove those ＂meaningless＂ no-flow-passing fractures, providing an updated and more effective fracture network that could considerably impr...Determinations of fracture network connections would help the investigators remove those ＂meaningless＂ no-flow-passing fractures, providing an updated and more effective fracture network that could considerably improve the computation efficiency in the pertinent numerical simulations of fluid flow and solute transport. The effective algorithms with higher computational efficiency are needed to accomplish this task in large-scale fractured rock masses. A new approach using R tree indexing was proposed for determining fracture connection in 3D stochastically distributed fracture network. By com- paring with the traditional exhaustion algorithm, it was observed that from the simulation results, this approach was much more effective; and the more the fractures were investigated, the more obvious the advantages of the approach were. Furthermore, it was indicated that the runtime used for creating the R tree indexing has a major part in the total of the runtime used for calculating Minimum Bounding Rectangles （MBRs）, creating the R tree indexing, precisely finding out fracture intersections, and identifying flow paths, which are four important steps to determine fracture connections. This proposed approach for the determination of fracture connections in three-dimensional fractured rocks are expected to provide efficient preprocessing and critical database for practically accomplishing numerical computation of fluid flow and solute transport in large-scale fractured rock masses.展开更多
In responding to the“dual carbon”strategy,intelligent networked new energy vehicle technology plays a crucial role.This type of vehicle combines the advantages of new energy technology and intelligent network techno...In responding to the“dual carbon”strategy,intelligent networked new energy vehicle technology plays a crucial role.This type of vehicle combines the advantages of new energy technology and intelligent network technology,effectively reduces carbon emissions in the transportation sector,improves energy utilization efficiency,and contributes to the green transportation system through intelligent transportation management and collaborative work between vehicles,making significant contributions.This article aims to explore the development of intelligent network-connected new energy vehicle technology and applications under the dual-carbon strategy and lay the foundation for the future development direction of the automotive industry.展开更多
Epilepsy is a transient neurological disorder associated with changes in the functional connections of the brain. Abnormal electrical discharges can be observed during an epileptic seizure. However, in the absence of ...Epilepsy is a transient neurological disorder associated with changes in the functional connections of the brain. Abnormal electrical discharges can be observed during an epileptic seizure. However, in the absence of an epileptic seizure, the anatomical structure of the brain and the electrical waves of the brain are not observed, making it difficult to explain the cause. This paper deals with together weighted imaging (DWI) sequence data in functional magnetic resonance imaging (FMRI) of epileptic patients before seizure, using Anatomical Automatic Labeling (AAL) template extracted 116 brain regions and the introduction of time series, a matrix of 116 × 116. Pearson correlation coefficient was calculated to investigate the pathological condition of brain function in epilepsy patients, using of neural network visualization system of innovative visual display and compared with the normal epileptic brain function to connect the image, with 38 cases of epilepsy by 187 cases of normal DWI experiment data, and can confirm the existence of brain function in patients with epilepsy connections. Cerebral neural network visualization system showed partial functional connection loss between frontal lobe and temporal lobe in epileptic group compared with normal control group.展开更多
Mitochondrial DNA variants have been linked to cognitive progression in Parkinson’s disease;however,the mechanisms by which mitochondrial DNA variants or haplogroups contribute to this process remain unclear.In the p...Mitochondrial DNA variants have been linked to cognitive progression in Parkinson’s disease;however,the mechanisms by which mitochondrial DNA variants or haplogroups contribute to this process remain unclear.In the present study,we analyzed single-nucleus RNA sequencing data from 241 post-mortem brain samples across five regions to investigate the dysregulatory mechanisms associated with mitochondrial DNA haplogroup H and haplogroups J,T,and U#.Our findings revealed significant alterations in the proportions of astrocyte subtypes CHI3L1 and GRM3 in the neocortical regions of haplogroup H.Notably,TTR was markedly downregulated in the dorsal motor nucleus of the Xth nerve region of patients with haplogroup H.Pathway analysis highlighted abnormal hypoxic and reactive oxygen species environments in astrocytes,whereas protein complex analysis revealed a consistent and significant elevation in ribosomal subunit complexes within the astrocyte subtypes.By constructing weighted and directed transcriptome-wide gene regulatory networks,we identified significant changes in transcription factor SP1 and homeobox protein HOXA5 activity in the astrocyte subtypes of individuals with haplogroup H.Additionally,widespread dysregulation was observed in the transcriptional control of TTR by multiple transcription factors.Parkinson’s disease patients with haplogroup H also exhibited increased network functional connectivity in specific brain regions.This data-driven study underscores the potential mechanisms by which mitochondrial DNA haplogroups contribute to cognitive progression in Parkinson’s disease,involving cellular composition changes,differential gene expression,pathway disruption,and gene regulatory networks.Our findings suggest that mitochondrial DNA haplogroup H may drive Parkinson’s disease cognitive progression through aberrant TTR expression and a hypoxic environment.展开更多
Globalization and informatization have accelerated city networking process over the world, which makes research on city network a hot topic in the fields of urban geography and economic geography. With Chinese economi...Globalization and informatization have accelerated city networking process over the world, which makes research on city network a hot topic in the fields of urban geography and economic geography. With Chinese economic structure adjustment and city economic growth, producer services have begun to play an increasingly important role in city-region networking. This paper employs the methodology of world city network to analyze and explain the spatial development characteristics of China's urban network system based on the data of nationwide producer services enterprise network. The research result indicated that the distribution of producer services network has a positive effect on the development of Chinese city networks. City network connectivity is closely related to the significance of city in producer services development, and the former will gradually decline with the drop of the latter. Accordingly, the 64 cities can be divided into the national central cities, regional central cities, sub-regional central cities and local central cities in accordance with their position and role in the nationwide producer services network. It is concluded that high-grade cities with quality producer services dominate the pattern of Chinese city networks and there emerges three spatial agglomerations of producer services enterprises in Changjiang (Yangtze) River Delta, Zhujiang (Pearl) River Delta and Beijing-Tianjin-Tangshan Economical Region. Moreover, the distribution of different producer services industry varies from city to city, which also affects the characteristics of network development.展开更多
Studies have shown that functional network connection models can be used to study brain net- work changes in patients with schizophrenia. In this study, we inferred that these models could also be used to explore func...Studies have shown that functional network connection models can be used to study brain net- work changes in patients with schizophrenia. In this study, we inferred that these models could also be used to explore functional network connectivity changes in stroke patients. We used independent component analysis to find the motor areas of stroke patients, which is a novel way to determine these areas. In this study, we collected functional magnetic resonance imaging datasets from healthy controls and right-handed stroke patients following their first ever stroke. Using independent component analysis, six spatially independent components highly correlat- ed to the experimental paradigm were extracted. Then, the functional network connectivity of both patients and controls was established to observe the differences between them. The results showed that there were 11 connections in the model in the stroke patients, while there were only four connections in the healthy controls. Further analysis found that some damaged connections may be compensated for by new indirect connections or circuits produced after stroke. These connections may have a direct correlation with the degree of stroke rehabilitation. Our findings suggest that functional network connectivity in stroke patients is more complex than that in hea- lthy controls, and that there is a compensation loop in the functional network following stroke. This implies that functional network reorganization plays a very important role in the process of rehabilitation after stroke.展开更多
Most existing work on survivability in mobile ad-hoc networks(MANETs) focuses on two dimensional(2D) networks.However,many real applications run in three dimensional(3D) networks,e.g.,climate and ocean monitoring,and ...Most existing work on survivability in mobile ad-hoc networks(MANETs) focuses on two dimensional(2D) networks.However,many real applications run in three dimensional(3D) networks,e.g.,climate and ocean monitoring,and air defense systems.The impact on network survivability due to node behaviors was presented,and a quantitative analysis method on survivability was developed in 3D MANETs by modeling node behaviors and analyzing 3D network connectivity.Node behaviors were modeled by using a semi-Markov process.The node minimum degree of 3D MANETs was discussed.An effective approach to derive the survivability of k-connected networks was proposed through analyzing the connectivity of 3D MANETs caused by node misbehaviors,based on the model of node isolation.The quantitative analysis of node misbehaviors on the survivability in 3D MANETs is obtained through mathematical description,and the effectiveness and rationality of the proposed approach are verified through numerical analysis.The analytical results show that the effect from black and gray attack on network survivability is much severer than other misbehaviors.展开更多
As a new sort of mobile ad hoc network(MANET), aeronautical ad hoc network(AANET) has fleet-moving airborne nodes(ANs) and suffers from frequent network partitioning due to the rapid-changing topology. In this work, t...As a new sort of mobile ad hoc network(MANET), aeronautical ad hoc network(AANET) has fleet-moving airborne nodes(ANs) and suffers from frequent network partitioning due to the rapid-changing topology. In this work, the additional relay nodes(RNs) is employed to repair the network and maintain connectivity in AANET. As ANs move, RNs need to move as well in order to re-establish the topology as quickly as possible. The network model and problem definition are firstly given, and then an online approach for RNs' movement control is presented to make ANs achieve certain connectivity requirement during run time. By defining the minimum cost feasible moving matrix(MCFM), a fast algorithm is proposed for RNs' movement control problem. Simulations demonstrate that the proposed algorithm outperforms other control approaches in the highly-dynamic environment and is of great potential to be applied in AANET.展开更多
Examining the spontaneous BOLD activity to understand the neural mechanism of Parkinson’s disease(PD)with mild cognitive impairment(MCI)is a focus in resting-state functional MRI(rs-fMRI)studies.This study aimed to i...Examining the spontaneous BOLD activity to understand the neural mechanism of Parkinson’s disease(PD)with mild cognitive impairment(MCI)is a focus in resting-state functional MRI(rs-fMRI)studies.This study aimed to investigate the alteration of brain functional connectivity in PD with MCI in a systematical way at two levels:functional connectivity analysis within resting state networks(RSNs)and functional network connectivity(FNC)analysis.Using group independent component analysis(ICA)on rs-fMRI data acquired from 30 participants(14 healthy controls and 16 PD patients with MCI),16 RSNs were identified,and functional connectivity analysis within the RSNs and FNC analysis were carried out between groups.Compared to controls,patients with PD showed decreased functional connectivity within putamen network,thalamus network,cerebellar network,attention network,and self-referential network,and increased functional connectivity within execution network.Globally disturbed,mostly increased functional connectivity of FNC was observed in PD group,and insular network and execution network were the dominant network with extensively increased functional connectivity with other RSNs.Cerebellar network showed decreased functional connectivity with caudate network,insular network,and self-referential network.In general,decreased functional connectivity within RSNs and globally disturbed,mostly increased functional connectivity of FNC may be characteristics of PD.Increased functional connectivity within execution network may be an early marker of PD.The multi-perspective study based on RSNs may be a valuable means to assess functional changes corresponding to specific RSN,contributing to the understanding of the neural mechanism of PD.展开更多
Background： Functional magnetic resonance imaging （fMRI） is a novel method for studying the changes of brain networks due to acupuncture treatment. In recent years, more and more studies have focused on the brain f...Background： Functional magnetic resonance imaging （fMRI） is a novel method for studying the changes of brain networks due to acupuncture treatment. In recent years, more and more studies have focused on the brain functional connectivity network of acupuncture stimulation. Objective： To offer an overview of the different influences of acupuncture on the brain functional connec- tivity network from studies using resting-state fMRI. Search strategy： The authors performed a systematic search according to PRISMA guidelines, The database PubMed was searched from January 1, 2006 to December 31, 2016 with restriction to human studies in English language. Inclusion criteria： Electronic searches were conducted in PubMed using the keywords ＂acupuncture＂ and ＂neuroimaging＂ or ＂resting-state fMRI＂ or ＂functional connectivity＂, Data extraction and analysis： Selection of included articles, data extraction and methodological quality assessments were respectively conducted by two review authors. Results： Forty-four resting-state fMRI studies were included in this systematic review according to inclu- sion criteria. Thirteen studies applied manual acupuncture vs. sham, four studies applied electro- acupuncture vs. sham, two studies also compared transcutaneous electrical acupoint stimulation vs. sham, and nine applied sham acupoint as control. Nineteen studies with a total number of 574 healthy subjects selected to perform fMRI only considered healthy adult volunteers. The brain functional connec- tivity of the patients had varying degrees of change. Compared with sham acupuncture, verum acupunc- ture could increase default mode network and sensorimotor network connectivity with pain-, affective- and memory-related brain areas. It has significantly greater connectivity of genuine acupuncture between the periaqueductal gray, anterior cingulate cortex, left posterior cingulate cortex, right anterior insula, limbic/paralimbic and precuneus compared with sham acupuncture. Some research had also shown that acupuncture could adjust the limbic-paralimbic-neocortical network, brainstem, cerebellum, subcortical and hippocampus brain areas. Conclusion： It can be presumed that the functional connectivity network is closely related to the mech- anism of acupuncture, and central integration plays a critical role in the acupuncture mechanism.展开更多
基金This work is supported by the National Natural Science Foundation of China （61070163） and Shandong Natural Science Foundation （Y2008G35）.
文摘A method to extract information of network connection status information from physical memory on Windows Vista operating system is proposed. Using this method, a forensic examiner can extract accurately the information of current TCP/ IP network connection information, including IDs of processes which established connections, establishing time, local address, local port, remote address, remote port, etc., from a physical memory on Windows Xflsta operating system. This method is reliable and efficient. It is verified on Windows Vista, Windows Vista SP1, Windows Vista SP2.
基金supported in part by National Natural Science Foundation of China(Grant No.62273075).
文摘Addressing the critical detection range limitation in active electrosensing(AES)for underwater sensing,this study proposes an enhanced AES system via novel array optimization.While AES offers advantages like interference immunity,acoustic stealth detection,and low cost,its short range restricts applicability.A target perturbation model under differential signal acquisition reveals that signal strength increases with local electric field intensity,target size,differential channel spacing,and conductivity contrast,but decreases with target-electrode distance.To extend detection,novel array configurations were explored.Simulations demonstrate that both rectangular and offset arrays significantly outperform the traditional collinear layout.Specifically,an offset array(with 8 m transmitting–receiving spacing)achieved an effective detection range enhancement exceeding 83%under the same distortion threshold while maintaining simplified electrode structure.Experimental validation confirmed a 100%increase in maximum detection distance to 5 m under identical noise thresholds compared to the collinear array.Furthermore,a fully connected neural network-based localization model achieved a mean positioning error of 14.12 cm at 3.15 m in static scenarios.In dynamic scenarios within 1–3 m,mean errors were controlled between 13.19 cm and 27.56 cm.Mechanistic analysis indicates that increasing the array baseline enhances the signal-to-noise ratio by simultaneously suppressing near-field environmental noise and amplifying far-field signal reception.Structural innovations in array design enabled this study to significantly expand the detection range of AES systems without compromising cost efficiency.These advancements directly promote the engineering application of AES technology,offering critical technical support for underwater defense security monitoring,long-range early warning systems,and maritime rights protection.
基金The National Natural Science Foundation of China(No.52361165658,U24A20169).
文摘A dual‑task parallel machine learning framework was developed by integrating a convolutional autoencoder(CAE)and a fully connected neural network(FCNN)via the gradient‑coupled mechanism,enabling simultaneous data compression‑reconstruction and structural damage identification.Under the condition where 40% of the sensor nodes are missing,the model successfully reconstructs the full sensor network with an R^(2) of 0.916 and normalized root mean square error(NRMSE)of 0.0288.Even under significant noise contamination with an SNR of 12 dB,the model maintains strong reconstruction performance,achieving a R^(2) of 0.910 and NRMSE of 0.0253.Forty‑six structural damage scenarios were simulated using the scaled bridge model.The accuracy of spatial localization and quantification of the damage severity using the framework exceeds 99.3%.The proposed framework reduces the training time by 54.4%and iteration counts by 45.5% compared to conventional two‑stage machine learning approaches,demonstrating the efficiency of gradient‑coupled optimization.
基金Supported by the National Natural Science Foundation of China(No.10531070,10771209,10721101,70631001)Chinese Academy of Sciences under Grant No.kjcx-yw-s7
文摘In this paper we introduce a minimax model for network connection problems with interval parameters. We consider how to connect given nodes in a network with a path or a spanning tree under a given budget, where each link is associated with an interval and can be established at a cost of any value in the interval. The quality of an individual link （or the risk of link failure, etc.） depends on its construction cost and associated interval. To achieve fairness of the network connection, our model aims at the minimization of the maximum risk over all links used. We propose two algorithms that find optimal paths and spanning trees in polynomial time, respectively. The polynomial solvability indicates salient difference between our minimax model and the model of robust deviation criterion for network connection with interval data, which gives rise to NP-hard optimization problems.
基金National Natural Science Foundation of China,No.42371222,No.41971167Fundamental Scientific Research Funds of Central China Normal University,No.CCNU24ZZ120,No.CCNU22JC026。
文摘The efficient development of the urban economy is a major concern of scholars in the fields of geography and urban science.In the context of globalization,informatization,industrialization,and urbanization,the external relationships of China's cities are experiencing the joint action of urban scale hierarchies and connection networks(“hierarchy-network”).However,under the interactive effect of the two,the mechanism of urban economic efficiency(UEE)is unclear.Therefore,based on Baidu migration data,the regionalization with dynamically constrained agglomerative clustering and partitioning(REDCAP)method,and a spatial simultaneous equation model,this paper analyzes the UEE spatial pattern and mechanism in China.The results indicate that:(1)the urban economy has a superlinear relationship with the population size.However,the benefit of this superlinear growth is in marginal decline.(2)The UEE shows a pattern of differentiation between China's eastern,then central,and then western region.Also,local differences are found within the three major sub-regions.(3)The increase of urban network centrality can promote UEE,while the impact of urban scale is negative.(4)There is regional heterogeneity of the interactive effect of“hierarchy-network”on UEE.This study reveals the influencing mechanism of UEE and also provides policy implications for the development of UEE.
基金supported under the National High Technology Research and Development Program(863)of China(No.2015AA016101)the National Natural Science Funds(No.61300184+1 种基金61302089)Beijing Nova Program(No.Z151100000315078)
文摘The network services today require extremely agile and mobile, however, the traditional IP infrastructures are so rigid that cannot fit services well. A way should be put forward to automate the network to improve responsiveness to change. SDN and network virtualization(NV) are two hottest approaches to make networking more automated and scalable to support virtualized and cloud environments. Network virtualization combines hardware and software network resources and network functionality into a single virtual network. SDN is created to simplify traffic management and achieve operational efficiencies by establish and exercising central control over packet forwarding. In this paper, we focus on the situation where SDN controller needs to connect two virtual networks temporarily. We put forward three algorithms to try to make this connection more effective and evaluate these three algorithms.
基金Supported by the Medical Research Project of the Chongqing Municipal Health Commission,No.2024WSJK110.
文摘BACKGROUND Currently,adolescent depression is one of the most significant public health concerns,markedly influencing emotional,cognitive,and social maturation.Despite advancements in distinguish the neurobiological substrates underlying depression,the intricate patterns of disrupted brain network connectivity in adolescents warrant further exploration.AIM To elucidate the neural correlates of adolescent depression by examining brain network connectivity using resting-state functional magnetic resonance imaging(rs-fMRI).METHODS The study cohort comprised 74 depressed adolescents and 59 healthy controls aged 12 to 17 years.Participants underwent rs-fMRI to evaluate functional connectivity within and across critical brain networks,including the visual,default mode network(DMN),dorsal attention,salience,somatomotor,and frontoparietal control networks.RESULTS Analyses revealed pronounced functional disparities within key neural circuits among adolescents with depression.The results demonstrated existence of hemispheric asymmetries characterized by enhanced activity in the left visual network,which contrasted the diminished activity in the right hemisphere.The DMN facilitated increased activity within the left prefrontal cortex and reduced engagement in the right hemisphere,implicating disrupted self-referential and emotional processing mechanisms.Additionally,an overactive right dorsal attention network and a hypoactive salience network were identified,underscoring significant abnormalities in attentional and emotional regulation in adolescent depression.CONCLUSION The findings from this study underscore distinct neural connectivity disruptions in adolescent depression,underscoring the critical role of specific neurobiological markers for precise early diagnosis of adolescent depression.The observed functional asymmetries and network-specific deviations elucidate the complex neurobiological architecture of adolescent depression,supporting the development of targeted therapeutic strategies.
基金supported by the Research Grants Council of the Hong Kong Special Administration Region under the Grant No.14201621。
文摘In this paper,we investigate the distributed Nash equilibrium(NE)seeking problem for aggregative games with multiple uncertain Euler–Lagrange(EL)systems over jointly connected and weight-balanced switching networks.The designed distributed controller consists of two parts:a dynamic average consensus part that asymptotically reproduces the unknown NE,and an adaptive reference-tracking module responsible for steering EL systems’positions to track a desired trajectory.The generalized Barbalat’s Lemma is used to overcome the discontinuity of the closed-loop system caused by the switching networks.The proposed algorithm is illustrated by a sensor network deployment problem.
基金Supported by the Major State Basic Research Development Program of China （973 Program） （2010CB428804） the National Science Foundation ot China （40672172） and the Major Science and Technology Program for Water Pollution Control and Treatment（2009ZX07212-003）
文摘Determinations of fracture network connections would help the investigators remove those ＂meaningless＂ no-flow-passing fractures, providing an updated and more effective fracture network that could considerably improve the computation efficiency in the pertinent numerical simulations of fluid flow and solute transport. The effective algorithms with higher computational efficiency are needed to accomplish this task in large-scale fractured rock masses. A new approach using R tree indexing was proposed for determining fracture connection in 3D stochastically distributed fracture network. By com- paring with the traditional exhaustion algorithm, it was observed that from the simulation results, this approach was much more effective; and the more the fractures were investigated, the more obvious the advantages of the approach were. Furthermore, it was indicated that the runtime used for creating the R tree indexing has a major part in the total of the runtime used for calculating Minimum Bounding Rectangles （MBRs）, creating the R tree indexing, precisely finding out fracture intersections, and identifying flow paths, which are four important steps to determine fracture connections. This proposed approach for the determination of fracture connections in three-dimensional fractured rocks are expected to provide efficient preprocessing and critical database for practically accomplishing numerical computation of fluid flow and solute transport in large-scale fractured rock masses.
文摘In responding to the“dual carbon”strategy,intelligent networked new energy vehicle technology plays a crucial role.This type of vehicle combines the advantages of new energy technology and intelligent network technology,effectively reduces carbon emissions in the transportation sector,improves energy utilization efficiency,and contributes to the green transportation system through intelligent transportation management and collaborative work between vehicles,making significant contributions.This article aims to explore the development of intelligent network-connected new energy vehicle technology and applications under the dual-carbon strategy and lay the foundation for the future development direction of the automotive industry.
文摘Epilepsy is a transient neurological disorder associated with changes in the functional connections of the brain. Abnormal electrical discharges can be observed during an epileptic seizure. However, in the absence of an epileptic seizure, the anatomical structure of the brain and the electrical waves of the brain are not observed, making it difficult to explain the cause. This paper deals with together weighted imaging (DWI) sequence data in functional magnetic resonance imaging (FMRI) of epileptic patients before seizure, using Anatomical Automatic Labeling (AAL) template extracted 116 brain regions and the introduction of time series, a matrix of 116 × 116. Pearson correlation coefficient was calculated to investigate the pathological condition of brain function in epilepsy patients, using of neural network visualization system of innovative visual display and compared with the normal epileptic brain function to connect the image, with 38 cases of epilepsy by 187 cases of normal DWI experiment data, and can confirm the existence of brain function in patients with epilepsy connections. Cerebral neural network visualization system showed partial functional connection loss between frontal lobe and temporal lobe in epileptic group compared with normal control group.
基金supported by the Shenzhen Fundamental Research Program,No.JCYJ20240813151132042the National Natural Science Foundation of China,Nos.32270701 and 32470708+1 种基金Young Talent Recruitment Project of Guangdong,No.2019QN01Y139the Science and Technology Planning Project of Guangdong Province,No.2023B1212060018(all to GL).
文摘Mitochondrial DNA variants have been linked to cognitive progression in Parkinson’s disease;however,the mechanisms by which mitochondrial DNA variants or haplogroups contribute to this process remain unclear.In the present study,we analyzed single-nucleus RNA sequencing data from 241 post-mortem brain samples across five regions to investigate the dysregulatory mechanisms associated with mitochondrial DNA haplogroup H and haplogroups J,T,and U#.Our findings revealed significant alterations in the proportions of astrocyte subtypes CHI3L1 and GRM3 in the neocortical regions of haplogroup H.Notably,TTR was markedly downregulated in the dorsal motor nucleus of the Xth nerve region of patients with haplogroup H.Pathway analysis highlighted abnormal hypoxic and reactive oxygen species environments in astrocytes,whereas protein complex analysis revealed a consistent and significant elevation in ribosomal subunit complexes within the astrocyte subtypes.By constructing weighted and directed transcriptome-wide gene regulatory networks,we identified significant changes in transcription factor SP1 and homeobox protein HOXA5 activity in the astrocyte subtypes of individuals with haplogroup H.Additionally,widespread dysregulation was observed in the transcriptional control of TTR by multiple transcription factors.Parkinson’s disease patients with haplogroup H also exhibited increased network functional connectivity in specific brain regions.This data-driven study underscores the potential mechanisms by which mitochondrial DNA haplogroups contribute to cognitive progression in Parkinson’s disease,involving cellular composition changes,differential gene expression,pathway disruption,and gene regulatory networks.Our findings suggest that mitochondrial DNA haplogroup H may drive Parkinson’s disease cognitive progression through aberrant TTR expression and a hypoxic environment.
基金Under the auspices of National Natural Science Foundation of China(No.40971094)
文摘Globalization and informatization have accelerated city networking process over the world, which makes research on city network a hot topic in the fields of urban geography and economic geography. With Chinese economic structure adjustment and city economic growth, producer services have begun to play an increasingly important role in city-region networking. This paper employs the methodology of world city network to analyze and explain the spatial development characteristics of China's urban network system based on the data of nationwide producer services enterprise network. The research result indicated that the distribution of producer services network has a positive effect on the development of Chinese city networks. City network connectivity is closely related to the significance of city in producer services development, and the former will gradually decline with the drop of the latter. Accordingly, the 64 cities can be divided into the national central cities, regional central cities, sub-regional central cities and local central cities in accordance with their position and role in the nationwide producer services network. It is concluded that high-grade cities with quality producer services dominate the pattern of Chinese city networks and there emerges three spatial agglomerations of producer services enterprises in Changjiang (Yangtze) River Delta, Zhujiang (Pearl) River Delta and Beijing-Tianjin-Tangshan Economical Region. Moreover, the distribution of different producer services industry varies from city to city, which also affects the characteristics of network development.
基金supported by the National Natural Science Foundation of China,No.60905024
文摘Studies have shown that functional network connection models can be used to study brain net- work changes in patients with schizophrenia. In this study, we inferred that these models could also be used to explore functional network connectivity changes in stroke patients. We used independent component analysis to find the motor areas of stroke patients, which is a novel way to determine these areas. In this study, we collected functional magnetic resonance imaging datasets from healthy controls and right-handed stroke patients following their first ever stroke. Using independent component analysis, six spatially independent components highly correlat- ed to the experimental paradigm were extracted. Then, the functional network connectivity of both patients and controls was established to observe the differences between them. The results showed that there were 11 connections in the model in the stroke patients, while there were only four connections in the healthy controls. Further analysis found that some damaged connections may be compensated for by new indirect connections or circuits produced after stroke. These connections may have a direct correlation with the degree of stroke rehabilitation. Our findings suggest that functional network connectivity in stroke patients is more complex than that in hea- lthy controls, and that there is a compensation loop in the functional network following stroke. This implies that functional network reorganization plays a very important role in the process of rehabilitation after stroke.
基金Project(07JJ1010) supported by the Hunan Provincial Natural Science Foundation of China for Distinguished Young ScholarsProjects(61073037,60773013) supported by the National Natural Science Foundation of China
文摘Most existing work on survivability in mobile ad-hoc networks(MANETs) focuses on two dimensional(2D) networks.However,many real applications run in three dimensional(3D) networks,e.g.,climate and ocean monitoring,and air defense systems.The impact on network survivability due to node behaviors was presented,and a quantitative analysis method on survivability was developed in 3D MANETs by modeling node behaviors and analyzing 3D network connectivity.Node behaviors were modeled by using a semi-Markov process.The node minimum degree of 3D MANETs was discussed.An effective approach to derive the survivability of k-connected networks was proposed through analyzing the connectivity of 3D MANETs caused by node misbehaviors,based on the model of node isolation.The quantitative analysis of node misbehaviors on the survivability in 3D MANETs is obtained through mathematical description,and the effectiveness and rationality of the proposed approach are verified through numerical analysis.The analytical results show that the effect from black and gray attack on network survivability is much severer than other misbehaviors.
文摘As a new sort of mobile ad hoc network(MANET), aeronautical ad hoc network(AANET) has fleet-moving airborne nodes(ANs) and suffers from frequent network partitioning due to the rapid-changing topology. In this work, the additional relay nodes(RNs) is employed to repair the network and maintain connectivity in AANET. As ANs move, RNs need to move as well in order to re-establish the topology as quickly as possible. The network model and problem definition are firstly given, and then an online approach for RNs' movement control is presented to make ANs achieve certain connectivity requirement during run time. By defining the minimum cost feasible moving matrix(MCFM), a fast algorithm is proposed for RNs' movement control problem. Simulations demonstrate that the proposed algorithm outperforms other control approaches in the highly-dynamic environment and is of great potential to be applied in AANET.
基金This work was supported by the Natural Science Foundation of Jiangsu Province(Grant No.BK20181310)the National Natural Science Foundation of China(Grant No.52079039).
基金This project was supported by grants from National Natural Science Foundation of China(No.81701655 and No.81600317)Platform Research Foundation of Union Hospital,Tongji Medical College,Huazhong university of Science and Technology(No.02.03.2017-14).
文摘Examining the spontaneous BOLD activity to understand the neural mechanism of Parkinson’s disease(PD)with mild cognitive impairment(MCI)is a focus in resting-state functional MRI(rs-fMRI)studies.This study aimed to investigate the alteration of brain functional connectivity in PD with MCI in a systematical way at two levels:functional connectivity analysis within resting state networks(RSNs)and functional network connectivity(FNC)analysis.Using group independent component analysis(ICA)on rs-fMRI data acquired from 30 participants(14 healthy controls and 16 PD patients with MCI),16 RSNs were identified,and functional connectivity analysis within the RSNs and FNC analysis were carried out between groups.Compared to controls,patients with PD showed decreased functional connectivity within putamen network,thalamus network,cerebellar network,attention network,and self-referential network,and increased functional connectivity within execution network.Globally disturbed,mostly increased functional connectivity of FNC was observed in PD group,and insular network and execution network were the dominant network with extensively increased functional connectivity with other RSNs.Cerebellar network showed decreased functional connectivity with caudate network,insular network,and self-referential network.In general,decreased functional connectivity within RSNs and globally disturbed,mostly increased functional connectivity of FNC may be characteristics of PD.Increased functional connectivity within execution network may be an early marker of PD.The multi-perspective study based on RSNs may be a valuable means to assess functional changes corresponding to specific RSN,contributing to the understanding of the neural mechanism of PD.
基金supported by the National Natural Science Foundation of China(No.81473784)University Science Research Project of Anhui Province of China(No.KJ2017A298)+1 种基金the Key Project of the Youth Elite Support Plan in Universities of Anhui Province of China(No.gxyq ZD2016134)Construction Project of Scientific Research Innovation Platform of Anhui Province of China(No.2015TD033)
文摘Background： Functional magnetic resonance imaging （fMRI） is a novel method for studying the changes of brain networks due to acupuncture treatment. In recent years, more and more studies have focused on the brain functional connectivity network of acupuncture stimulation. Objective： To offer an overview of the different influences of acupuncture on the brain functional connec- tivity network from studies using resting-state fMRI. Search strategy： The authors performed a systematic search according to PRISMA guidelines, The database PubMed was searched from January 1, 2006 to December 31, 2016 with restriction to human studies in English language. Inclusion criteria： Electronic searches were conducted in PubMed using the keywords ＂acupuncture＂ and ＂neuroimaging＂ or ＂resting-state fMRI＂ or ＂functional connectivity＂, Data extraction and analysis： Selection of included articles, data extraction and methodological quality assessments were respectively conducted by two review authors. Results： Forty-four resting-state fMRI studies were included in this systematic review according to inclu- sion criteria. Thirteen studies applied manual acupuncture vs. sham, four studies applied electro- acupuncture vs. sham, two studies also compared transcutaneous electrical acupoint stimulation vs. sham, and nine applied sham acupoint as control. Nineteen studies with a total number of 574 healthy subjects selected to perform fMRI only considered healthy adult volunteers. The brain functional connec- tivity of the patients had varying degrees of change. Compared with sham acupuncture, verum acupunc- ture could increase default mode network and sensorimotor network connectivity with pain-, affective- and memory-related brain areas. It has significantly greater connectivity of genuine acupuncture between the periaqueductal gray, anterior cingulate cortex, left posterior cingulate cortex, right anterior insula, limbic/paralimbic and precuneus compared with sham acupuncture. Some research had also shown that acupuncture could adjust the limbic-paralimbic-neocortical network, brainstem, cerebellum, subcortical and hippocampus brain areas. Conclusion： It can be presumed that the functional connectivity network is closely related to the mech- anism of acupuncture, and central integration plays a critical role in the acupuncture mechanism.
