Global climate warming has placed immense pressure on the ecological environment worldwide,and the ecological issues affecting the quality of the living environment have garnered widespread attention.In this context,t...Global climate warming has placed immense pressure on the ecological environment worldwide,and the ecological issues affecting the quality of the living environment have garnered widespread attention.In this context,the question of“how to effectively optimize regional ecological network patterns”has become one of the critical issues that urban and rural planning and ecological geography need to address.This study takes Huzhou,Zhejiang Province,China,as the research area,and uses a combination of landscape type transition matrices and landscape pattern indices to analyze the evolution characteristics of green space landscape patterns from 2017 to 2022.Through geographical detectors and GBDT(Gradient Boosting Decision Tree)algorithms,the study explores the driving factors behind the changes in green space landscape patterns.Based on MSPA(Morphological Spatial Pattern Analysis),key ecological sources in Huzhou are extracted.Using a combination of resistance surfaces and gravity models,ecological corridors and networks are constructed.The study also provides suggestions for the evaluation and optimization of ecological network patterns.The aim is to summarize generalizable patterns of green space landscape evolution and methods for constructing and optimizing regional ecological corridor networks,offering insights and references for the improvement of the living environment and the construction of ecological civilization.展开更多
The phenomenon of data explosion represents a severe challenge for the upcoming big data era.However,the current Internet architecture is insufficient for dealing with a huge amount of traffic owing to an increase in ...The phenomenon of data explosion represents a severe challenge for the upcoming big data era.However,the current Internet architecture is insufficient for dealing with a huge amount of traffic owing to an increase in redundant content transmission and the end-point-based communication model.Information-centric networking(ICN)is a paradigm for the future Internet that can be utilized to resolve the data explosion problem.In this paper,we focus on content-centric networking(CCN),one of the key candidate ICN architectures.CCN has been studied in various network environments with the aim of relieving network and server burden,especially in name-based forwarding and in-network caching functionalities.This paper studies the effect of several caching strategies in the CCN domain from the perspective of network and server overhead.Thus,we comprehensively analyze the in-network caching performance of CCN under several popular cache replication methods(i.e.,cache placement).We evaluate the performance with respect to wellknown Internet traffic patterns that follow certain probabilistic distributions,such as the Zipf/Mandelbrot–Zipf distributions,and flashcrowds.For the experiments,we developed an OPNET-based CCN simulator with a realistic Internet-like topology.展开更多
Residual neural network (ResNet) is a powerful neural network architecture that has proven to be excellent in extracting spatial and channel-wise information of images. ResNet employs a residual learning strategy that...Residual neural network (ResNet) is a powerful neural network architecture that has proven to be excellent in extracting spatial and channel-wise information of images. ResNet employs a residual learning strategy that maps inputs directly to outputs, making it less difficult to optimize. In this paper, we incorporate differential information into the original residual block to improve the representative ability of the ResNet, allowing the modified network to capture more complex and metaphysical features. The proposed DFNet preserves the features after each convolutional operation in the residual block, and combines the feature maps of different levels of abstraction through the differential information. To verify the effectiveness of DFNet on image recognition, we select six distinct classification datasets. The experimental results show that our proposed DFNet has better performance and generalization ability than other state-of-the-art variants of ResNet in terms of classification accuracy and other statistical analysis.展开更多
The rapid development of network technology and its evolution toward heterogeneous networks has increased the demand to support automatic monitoring and the management of heterogeneous wireless communication networks....The rapid development of network technology and its evolution toward heterogeneous networks has increased the demand to support automatic monitoring and the management of heterogeneous wireless communication networks.This paper presents a multilevel pattern mining architecture to support automatic network management by discovering interesting patterns from telecom network monitoring data.This architecture leverages and combines existing frequent itemset discovery over data streams,association rule deduction,frequent sequential pattern mining,and frequent temporal pattern mining techniques while also making use of distributed processing platforms to achieve high-volume throughput.展开更多
The crack fault is one of the most common faults in the rotor system,and researchers have paid close attention to its fault diagnosis.However,most studies focus on discussing the dynamic response characteristics cause...The crack fault is one of the most common faults in the rotor system,and researchers have paid close attention to its fault diagnosis.However,most studies focus on discussing the dynamic response characteristics caused by the crack rather than estimating the crack depth and position based on the obtained vibration signals.In this paper,a novel crack fault diagnosis and location method for a dual-disk hollow shaft rotor system based on the Radial basis function(RBF)network and Pattern recognition neural network(PRNN)is presented.Firstly,a rotor system model with a breathing crack suitable for a short-thick hollow shaft rotor is established based on the finite element method,where the crack's periodic opening and closing pattern and different degrees of crack depth are considered.Then,the dynamic response is obtained by the harmonic balance method.By adjusting the crack parameters,the dynamic characteristics related to the crack depth and position are analyzed through the amplitude-frequency responses and waterfall plots.The analysis results show that the first critical speed,first subcritical speed,first critical speed amplitude,and super-harmonic resonance peak at the first subcritical speed can be utilized for the crack fault diagnosis.Based on this,the RBF network and PRNN are adopted to determine the depth and approximate location of the crack respectively by taking the above dynamic characteristics as input.Test results show that the proposed method has high fault diagnosis accuracy.This research proposes a crack detection method adequate for the hollow shaft rotor system,where the crack depth and position are both unknown.展开更多
Dune networks are widely distributed in the world＇s deserts,which include primary ridges and secondary ridges.However,they have not been sufficiently studied in a systematic manner and their origins and spatial and m...Dune networks are widely distributed in the world＇s deserts,which include primary ridges and secondary ridges.However,they have not been sufficiently studied in a systematic manner and their origins and spatial and morphological characteristics remain unclear.To provide information on the geomorphology of dune networks,we analyze the software geomorphologic patterns of the dune networks in China＇s Tengger Desert using matrix and laboratory to process remote-sensing images.Based on analysis of image features and their layout in a topographic map,we identify two types of dune networks （square and rectangular dune networks） with different size and morphological structures in the Tengger Desert.Four important geomorphic pattern parameters,ridge length,spacing,orientation and defect density,are analyzed.The length of primary ridges of dune networks decreases from northwest of the desert to the southeast,resulting an increasing spacing and a transition from rectangular dune networks to square dune networks.Wind regime and sediment supply are responsible for the variation in pattern parameters.We use the spacing and defect density data to estimate the construction time of dune networks and found that the dune networks in the Tengger Desert formed since about 1.3 ka BP.展开更多
Pattern matching is a fundamental approach to detect malicious behaviors and information over Internet, which has been gradually used in high-speed network traffic analysis. However, there is a performance bottleneck ...Pattern matching is a fundamental approach to detect malicious behaviors and information over Internet, which has been gradually used in high-speed network traffic analysis. However, there is a performance bottleneck for multi-pattern matching on online compressed network traffic(CNT), this is because malicious and intrusion codes are often embedded into compressed network traffic. In this paper, we propose an online fast and multi-pattern matching algorithm on compressed network traffic(FMMCN). FMMCN employs two types of jumping, i.e. jumping during sliding window and a string jump scanning strategy to skip unnecessary compressed bytes. Moreover, FMMCN has the ability to efficiently process multiple large volume of networks such as HTTP traffic, vehicles traffic, and other Internet-based services. The experimental results show that FMMCN can ignore more than 89.5% of bytes, and its maximum speed reaches 176.470MB/s in a midrange switches device, which is faster than the current fastest algorithm ACCH by almost 73.15 MB/s.展开更多
Some frequency reuse irregular patterns in radionetwork design are proposed,the characteristic and applica-tion measures of these patterns are analyzed.Then this paperaccounts that frequency reuse irregular patterns i...Some frequency reuse irregular patterns in radionetwork design are proposed,the characteristic and applica-tion measures of these patterns are analyzed.Then this paperaccounts that frequency reuse irregular patterns is a usefulway to impove spectrum efficiency and it is significative forartificial intelligence to be applied in this field.展开更多
Sensor networks tend to support different traffic patterns since more and more emerging applications have diverse needs. We present MGRP, a Multi-Gradient Routing Protocol for wireless sensor networks, which is fully ...Sensor networks tend to support different traffic patterns since more and more emerging applications have diverse needs. We present MGRP, a Multi-Gradient Routing Protocol for wireless sensor networks, which is fully distributed and efficiently supports endto-end, one-to-many and many-to-one traffic patterns by effectively construct and maintain a gradient vector for each node. We further combine neighbor link estimation with routing information to reduce packet exchange on network dynamics and node failures. We have implemented MGRP on Tiny OS and evaluated its performance on real-world testbeds. The result shows MGRP achieves lower end-to-end packet delay in different traffic patterns compared to the state of the art routing protocols while still remains high packet delivery ratio.展开更多
Training neural network to recognize targets needs a lot of samples.People usually get these samples in a non-systematic way,which can miss or overemphasize some target information.To improve this situation,a new meth...Training neural network to recognize targets needs a lot of samples.People usually get these samples in a non-systematic way,which can miss or overemphasize some target information.To improve this situation,a new method based on virtual model and invariant moments was proposed to generate training samples.The method was composed of the following steps：use computer and simulation software to build target object＇s virtual model and then simulate the environment,light condition,camera parameter,etc.;rotate the model by spin and nutation of inclination to get the image sequence by virtual camera;preprocess each image and transfer them into binary image;calculate the invariant moments for each image and get a vectors＇ sequence.The vectors＇ sequence which was proved to be complete became the training samples together with the target outputs.The simulated results showed that the proposed method could be used to recognize the real targets and improve the accuracy of target recognition effectively when the sampling interval was short enough and the circumstance simulation was close enough.展开更多
This study explores the impact of street pattern measurements on urban heat islands(UHI)in the arid climate of Mashhad,Iran.The Landsat-8 top-of-the-atmosphere(TOA)brightness images from 2013 to 2021,average values of...This study explores the impact of street pattern measurements on urban heat islands(UHI)in the arid climate of Mashhad,Iran.The Landsat-8 top-of-the-atmosphere(TOA)brightness images from 2013 to 2021,average values of normalized difference vegetation index(NDvI)and land surface temperature(LST)were calculated.Street pattern measurements,including closeness-centrality,straightness,and street orientation,were employed to analyse the patterns in each district.The results indicated that districts with higher straightness and lower closeness-centrality exhibit,cooler surface temperatures.Strong correlations were observed between LST and NDVl,straightness,and local closeness-centrality.The research highlighted the importance of considering street network measurements in long-term urban planning and design to mitigate the UHI effect in arid regions.A moderate grid street pattern with a reasonable distribution of green spaces throughout the region is suggested to reduce surface temperatures sustainably.Street pattern indexes,such as straightness and local closeness-centrality,are identified as significant factors in urban design to mitigate UHl.These findings have implications for urban planners,who can use this information to create street network patterns with lower UHI effects by reducing local closeness-centrality and increasing straightness.展开更多
As transparent electrodes,patterned silver nanowire(AgNW)networks suffer from noticeable pattern visibility,which is an unsettled issue for practical applications such as display.Here,we introduce a Gibbs-Thomson effe...As transparent electrodes,patterned silver nanowire(AgNW)networks suffer from noticeable pattern visibility,which is an unsettled issue for practical applications such as display.Here,we introduce a Gibbs-Thomson effect(GTE)-based patterning method to effectively reduce pattern visibility.Unlike conventional top-down and bottom-up strategies that rely on selective etching,removal,or deposition of AgNWs,our approach focuses on fragmenting nanowires primarily at the junctions through the GTE.This is realized by modifying AgNWs with a compound of diphenyliodonium nitrate and silver nitrate,which aggregates into nanoparticles at the junctions of AgNWs.These nanoparticles can boost the fragmentation of nanowires at the junctions under an ultralow temperature(75℃),allow pattern transfer through a photolithographic masking operation,and enhance plasmonic welding during UV exposure.The resultant patterned electrodes have trivial differences in transmittance(ΔT=1.4%)and haze(ΔH=0.3%)between conductive and insulative regions,with high-resolution patterning size down to 10μm.To demonstrate the practicality of this novel method,we constructed a highly transparent,optoelectrical interactive tactile e-skin using the patterned AgNW electrodes.展开更多
River capture is of great significance to landform evolution and hominine migration.In the Qinling-Daba Mountains,there is a viewpoint that Jialing River captured Hanjiang River,but this is still controversial.In this...River capture is of great significance to landform evolution and hominine migration.In the Qinling-Daba Mountains,there is a viewpoint that Jialing River captured Hanjiang River,but this is still controversial.In this paper,we discuss the drainage evolution processes in intermountain basins at the Qinling-Daba Mountains based on a combination of detrital zircon UPb geochronology and geomorphic indexes.We suggest that the Hanjiang River gradually captured the Jialing River from east to west,accompanied by the evolution of the ancient Yangtze River.In terms of geomorphic evidences,wide valleys did not match with discharge,and a series of wind gaps developed in the Shiquan-Ankang basin.In addition,the valley shapes and width-toheight ratios(Vf)indicate two possible rapid incisions.The hypsometric integrals(HI)reflect that the landform gradually changes from the old stage to the youth stage from west to east.Theχvalues show that the drainage divide is moving to the side of the Yuehe River,and the Yuehe River is gradually shrinking.According to the sedimentary records,the zircon U-Pb age distributions indicate the provenance change.The high-altitude terraces show three age peaks(200–250,400–505,and 700–900 Ma),with the dominant Indosinian age peak(200–250 Ma),while the modern fluvial sediments only show a single peak of Jinning(700–900 Ma).These data show that there are two major river captures:(1)The ancient Hanjiang River cut through the regional compression ridge,and then captured the Hanzhong Basin river system(a part of the ancient Jialing river system)from east to west,and(2)The southern tributary captured the trunk with the uplift of the divide in the Shiquan-Ankang Basin,forming the modern drainage pattern in the upper Hanjiang River.The activities of the regional strike-slip fault,and the associated compression uplift played a key role in the river captures,the drainage evolution,and related landforms in the Shiquan-Ankang basin.In addition,it is shown that the evolution of the upper tributary basins lagged behind the response of the trunk channel to the tectonic activities and river captures.The interconnected wide valleys caused by river capture may have provided convenient geomorphological conditions for human migration into the Qinling-Daba Mountains along those river valleys.展开更多
Background： Electroconvulsive therapy （ECT） can alleviate the symptoms of treatment-resistant depression （TRD）. Functional network connectivity （FNC） is a newly developed method to investigate the brain＇s func...Background： Electroconvulsive therapy （ECT） can alleviate the symptoms of treatment-resistant depression （TRD）. Functional network connectivity （FNC） is a newly developed method to investigate the brain＇s functional connectivity patterns. The first aim of this study was to investigate FNC alterations between TRD patients and healthy controls. The second aim was to explore the relationship between the ECT treatment response and pre-ECT treatment FNC alterations in individual TRD patients. Methods： This study included 82 TRD patients and 41 controls. Patients were screened at baseline and after 2 weeks of treatment with a combination of ECT and antidepressants. Group information guided-independent component analysis （G1G-ICA） was used to compute subject-specific functional networks （FNs）. Grassmann maniibld and step-wise forward component selection using support vector machines were adopted to perform the FNC measure and extract the functional networks＇ connectivity patterns （FCP）. Pearson＇s correlation analysis was used to calculate the correlations between the FCP and ECT response. Results： A total of 82 TRD patients in the ECT group were successfully treated. On an average, 8.50 ~ 2.00 ECT sessions were conducted. After ECT treatment, only 42 TRD patients had an improved response to ECT （the Hamilton scores reduction rate was more than 50%）, response rate 51%. 8 FNs （anterior and posterior default mode network, bilateral frontoparietal network, audio network, visual network, dorsal attention network, and sensorimotor network） were obtained using GIG-ICA. We did not found that FCPs were significantly different between TRD patients and healthy controls. Moreover, the baseline FCP was unrelated to the ECT treatment response. Conclusions： The FNC was not significantly different between the TRD patients and healthy controls, and the baseline FCP was unrelated to the ECT treatment response. These findings will necessitate that we modify the experimental scheme to explore the mechanisms underlying ECT＇s effects on depression and explore the specific predictors of the effects of ECT based on the pre-ECT treatment magnetic resonance imaging.展开更多
基金Major Program of National Fund of Philosophy and Social Science of China(24&ZD148).
文摘Global climate warming has placed immense pressure on the ecological environment worldwide,and the ecological issues affecting the quality of the living environment have garnered widespread attention.In this context,the question of“how to effectively optimize regional ecological network patterns”has become one of the critical issues that urban and rural planning and ecological geography need to address.This study takes Huzhou,Zhejiang Province,China,as the research area,and uses a combination of landscape type transition matrices and landscape pattern indices to analyze the evolution characteristics of green space landscape patterns from 2017 to 2022.Through geographical detectors and GBDT(Gradient Boosting Decision Tree)algorithms,the study explores the driving factors behind the changes in green space landscape patterns.Based on MSPA(Morphological Spatial Pattern Analysis),key ecological sources in Huzhou are extracted.Using a combination of resistance surfaces and gravity models,ecological corridors and networks are constructed.The study also provides suggestions for the evaluation and optimization of ecological network patterns.The aim is to summarize generalizable patterns of green space landscape evolution and methods for constructing and optimizing regional ecological corridor networks,offering insights and references for the improvement of the living environment and the construction of ecological civilization.
基金supported by Basic Science Research Program through the National Research Foundation of Korea(NRF)funded by the Ministry of Education(2014R1A1A2057796)and(2015R1D1A1A01059049)
文摘The phenomenon of data explosion represents a severe challenge for the upcoming big data era.However,the current Internet architecture is insufficient for dealing with a huge amount of traffic owing to an increase in redundant content transmission and the end-point-based communication model.Information-centric networking(ICN)is a paradigm for the future Internet that can be utilized to resolve the data explosion problem.In this paper,we focus on content-centric networking(CCN),one of the key candidate ICN architectures.CCN has been studied in various network environments with the aim of relieving network and server burden,especially in name-based forwarding and in-network caching functionalities.This paper studies the effect of several caching strategies in the CCN domain from the perspective of network and server overhead.Thus,we comprehensively analyze the in-network caching performance of CCN under several popular cache replication methods(i.e.,cache placement).We evaluate the performance with respect to wellknown Internet traffic patterns that follow certain probabilistic distributions,such as the Zipf/Mandelbrot–Zipf distributions,and flashcrowds.For the experiments,we developed an OPNET-based CCN simulator with a realistic Internet-like topology.
基金supported by the Japan Society for the Promotion of Science(JSPS)KAKENHI under Grant JP22H03643Japan Science and Technology Agency(JST)Support for Pioneering Research Initiated by the Next Generation(SPRING)under Grant JPMJSP2145JST through the Establishment of University Fellowships towards the Creation of Science Technology Innovation under Grant JPMJFS2115.
文摘Residual neural network (ResNet) is a powerful neural network architecture that has proven to be excellent in extracting spatial and channel-wise information of images. ResNet employs a residual learning strategy that maps inputs directly to outputs, making it less difficult to optimize. In this paper, we incorporate differential information into the original residual block to improve the representative ability of the ResNet, allowing the modified network to capture more complex and metaphysical features. The proposed DFNet preserves the features after each convolutional operation in the residual block, and combines the feature maps of different levels of abstraction through the differential information. To verify the effectiveness of DFNet on image recognition, we select six distinct classification datasets. The experimental results show that our proposed DFNet has better performance and generalization ability than other state-of-the-art variants of ResNet in terms of classification accuracy and other statistical analysis.
基金funded by the Enterprise Ireland Innovation Partnership Programme with Ericsson under grant agreement IP/2011/0135[6]supported by the National Natural Science Foundation of China(No.61373131,61303039,61232016,61501247)+1 种基金the PAPDCICAEET funds
文摘The rapid development of network technology and its evolution toward heterogeneous networks has increased the demand to support automatic monitoring and the management of heterogeneous wireless communication networks.This paper presents a multilevel pattern mining architecture to support automatic network management by discovering interesting patterns from telecom network monitoring data.This architecture leverages and combines existing frequent itemset discovery over data streams,association rule deduction,frequent sequential pattern mining,and frequent temporal pattern mining techniques while also making use of distributed processing platforms to achieve high-volume throughput.
基金Supported by National Natural Science Foundation of China (Grant No.11972129)National Science and Technology Major Project of China (Grant No.2017-IV-0008-0045)+1 种基金Heilongjiang Provincial Natural Science Foundation (Grant No.YQ2022A008)the Fundamental Research Funds for the Central Universities。
文摘The crack fault is one of the most common faults in the rotor system,and researchers have paid close attention to its fault diagnosis.However,most studies focus on discussing the dynamic response characteristics caused by the crack rather than estimating the crack depth and position based on the obtained vibration signals.In this paper,a novel crack fault diagnosis and location method for a dual-disk hollow shaft rotor system based on the Radial basis function(RBF)network and Pattern recognition neural network(PRNN)is presented.Firstly,a rotor system model with a breathing crack suitable for a short-thick hollow shaft rotor is established based on the finite element method,where the crack's periodic opening and closing pattern and different degrees of crack depth are considered.Then,the dynamic response is obtained by the harmonic balance method.By adjusting the crack parameters,the dynamic characteristics related to the crack depth and position are analyzed through the amplitude-frequency responses and waterfall plots.The analysis results show that the first critical speed,first subcritical speed,first critical speed amplitude,and super-harmonic resonance peak at the first subcritical speed can be utilized for the crack fault diagnosis.Based on this,the RBF network and PRNN are adopted to determine the depth and approximate location of the crack respectively by taking the above dynamic characteristics as input.Test results show that the proposed method has high fault diagnosis accuracy.This research proposes a crack detection method adequate for the hollow shaft rotor system,where the crack depth and position are both unknown.
基金funding from the Ministry of Science and Technology of the People’s Republic of China (2013CB956000)the National Natural Science Foundation of China (41130533)
文摘Dune networks are widely distributed in the world＇s deserts,which include primary ridges and secondary ridges.However,they have not been sufficiently studied in a systematic manner and their origins and spatial and morphological characteristics remain unclear.To provide information on the geomorphology of dune networks,we analyze the software geomorphologic patterns of the dune networks in China＇s Tengger Desert using matrix and laboratory to process remote-sensing images.Based on analysis of image features and their layout in a topographic map,we identify two types of dune networks （square and rectangular dune networks） with different size and morphological structures in the Tengger Desert.Four important geomorphic pattern parameters,ridge length,spacing,orientation and defect density,are analyzed.The length of primary ridges of dune networks decreases from northwest of the desert to the southeast,resulting an increasing spacing and a transition from rectangular dune networks to square dune networks.Wind regime and sediment supply are responsible for the variation in pattern parameters.We use the spacing and defect density data to estimate the construction time of dune networks and found that the dune networks in the Tengger Desert formed since about 1.3 ka BP.
基金supported by China MOST project (No.2012BAH46B04)
文摘Pattern matching is a fundamental approach to detect malicious behaviors and information over Internet, which has been gradually used in high-speed network traffic analysis. However, there is a performance bottleneck for multi-pattern matching on online compressed network traffic(CNT), this is because malicious and intrusion codes are often embedded into compressed network traffic. In this paper, we propose an online fast and multi-pattern matching algorithm on compressed network traffic(FMMCN). FMMCN employs two types of jumping, i.e. jumping during sliding window and a string jump scanning strategy to skip unnecessary compressed bytes. Moreover, FMMCN has the ability to efficiently process multiple large volume of networks such as HTTP traffic, vehicles traffic, and other Internet-based services. The experimental results show that FMMCN can ignore more than 89.5% of bytes, and its maximum speed reaches 176.470MB/s in a midrange switches device, which is faster than the current fastest algorithm ACCH by almost 73.15 MB/s.
文摘Some frequency reuse irregular patterns in radionetwork design are proposed,the characteristic and applica-tion measures of these patterns are analyzed.Then this paperaccounts that frequency reuse irregular patterns is a usefulway to impove spectrum efficiency and it is significative forartificial intelligence to be applied in this field.
基金supported by National Key Technologies Research and Development Program of China under Grant No.2014BAH14F01National Science and Technology Major Project of China under Grant No.2012ZX03005007+1 种基金National NSF of China Grant No.61402372Fundamental Research Funds for the Central Universities Grant No.3102014JSJ0003
文摘Sensor networks tend to support different traffic patterns since more and more emerging applications have diverse needs. We present MGRP, a Multi-Gradient Routing Protocol for wireless sensor networks, which is fully distributed and efficiently supports endto-end, one-to-many and many-to-one traffic patterns by effectively construct and maintain a gradient vector for each node. We further combine neighbor link estimation with routing information to reduce packet exchange on network dynamics and node failures. We have implemented MGRP on Tiny OS and evaluated its performance on real-world testbeds. The result shows MGRP achieves lower end-to-end packet delay in different traffic patterns compared to the state of the art routing protocols while still remains high packet delivery ratio.
基金Supported by the Ministerial Level Research Foundation(404040401)
文摘Training neural network to recognize targets needs a lot of samples.People usually get these samples in a non-systematic way,which can miss or overemphasize some target information.To improve this situation,a new method based on virtual model and invariant moments was proposed to generate training samples.The method was composed of the following steps：use computer and simulation software to build target object＇s virtual model and then simulate the environment,light condition,camera parameter,etc.;rotate the model by spin and nutation of inclination to get the image sequence by virtual camera;preprocess each image and transfer them into binary image;calculate the invariant moments for each image and get a vectors＇ sequence.The vectors＇ sequence which was proved to be complete became the training samples together with the target outputs.The simulated results showed that the proposed method could be used to recognize the real targets and improve the accuracy of target recognition effectively when the sampling interval was short enough and the circumstance simulation was close enough.
文摘This study explores the impact of street pattern measurements on urban heat islands(UHI)in the arid climate of Mashhad,Iran.The Landsat-8 top-of-the-atmosphere(TOA)brightness images from 2013 to 2021,average values of normalized difference vegetation index(NDvI)and land surface temperature(LST)were calculated.Street pattern measurements,including closeness-centrality,straightness,and street orientation,were employed to analyse the patterns in each district.The results indicated that districts with higher straightness and lower closeness-centrality exhibit,cooler surface temperatures.Strong correlations were observed between LST and NDVl,straightness,and local closeness-centrality.The research highlighted the importance of considering street network measurements in long-term urban planning and design to mitigate the UHI effect in arid regions.A moderate grid street pattern with a reasonable distribution of green spaces throughout the region is suggested to reduce surface temperatures sustainably.Street pattern indexes,such as straightness and local closeness-centrality,are identified as significant factors in urban design to mitigate UHl.These findings have implications for urban planners,who can use this information to create street network patterns with lower UHI effects by reducing local closeness-centrality and increasing straightness.
基金supported by the Basic and Applied Basic Research Foundation of Guangdong Province(2024A1515030155,2022A1515010272,2024A1515012609,2023A1515011459)National Natural Science Foundation of China(61904067,62475101,62175094,62275109)+2 种基金open funding from the State Key Laboratory of Optoelectronic Materials and Technologies(Sun Yat-Sen University,OEMT-2022-KF-08)National Innovation and Entrepreneurship Training Program For Undergraduate(202410559004)Fundamental Research Funds for the Central Universities(11621405).
文摘As transparent electrodes,patterned silver nanowire(AgNW)networks suffer from noticeable pattern visibility,which is an unsettled issue for practical applications such as display.Here,we introduce a Gibbs-Thomson effect(GTE)-based patterning method to effectively reduce pattern visibility.Unlike conventional top-down and bottom-up strategies that rely on selective etching,removal,or deposition of AgNWs,our approach focuses on fragmenting nanowires primarily at the junctions through the GTE.This is realized by modifying AgNWs with a compound of diphenyliodonium nitrate and silver nitrate,which aggregates into nanoparticles at the junctions of AgNWs.These nanoparticles can boost the fragmentation of nanowires at the junctions under an ultralow temperature(75℃),allow pattern transfer through a photolithographic masking operation,and enhance plasmonic welding during UV exposure.The resultant patterned electrodes have trivial differences in transmittance(ΔT=1.4%)and haze(ΔH=0.3%)between conductive and insulative regions,with high-resolution patterning size down to 10μm.To demonstrate the practicality of this novel method,we constructed a highly transparent,optoelectrical interactive tactile e-skin using the patterned AgNW electrodes.
基金This work was supported by the National Natural Science Foundation of China(Grant Nos.41971005,41522101,41901004)the Second Tibet Plateau Scientific Research(Grant No.2019QZKK0205)the Major Program of National Social Science Foundation of China(Grant No.19ZDA225).
文摘River capture is of great significance to landform evolution and hominine migration.In the Qinling-Daba Mountains,there is a viewpoint that Jialing River captured Hanjiang River,but this is still controversial.In this paper,we discuss the drainage evolution processes in intermountain basins at the Qinling-Daba Mountains based on a combination of detrital zircon UPb geochronology and geomorphic indexes.We suggest that the Hanjiang River gradually captured the Jialing River from east to west,accompanied by the evolution of the ancient Yangtze River.In terms of geomorphic evidences,wide valleys did not match with discharge,and a series of wind gaps developed in the Shiquan-Ankang basin.In addition,the valley shapes and width-toheight ratios(Vf)indicate two possible rapid incisions.The hypsometric integrals(HI)reflect that the landform gradually changes from the old stage to the youth stage from west to east.Theχvalues show that the drainage divide is moving to the side of the Yuehe River,and the Yuehe River is gradually shrinking.According to the sedimentary records,the zircon U-Pb age distributions indicate the provenance change.The high-altitude terraces show three age peaks(200–250,400–505,and 700–900 Ma),with the dominant Indosinian age peak(200–250 Ma),while the modern fluvial sediments only show a single peak of Jinning(700–900 Ma).These data show that there are two major river captures:(1)The ancient Hanjiang River cut through the regional compression ridge,and then captured the Hanzhong Basin river system(a part of the ancient Jialing river system)from east to west,and(2)The southern tributary captured the trunk with the uplift of the divide in the Shiquan-Ankang Basin,forming the modern drainage pattern in the upper Hanjiang River.The activities of the regional strike-slip fault,and the associated compression uplift played a key role in the river captures,the drainage evolution,and related landforms in the Shiquan-Ankang basin.In addition,it is shown that the evolution of the upper tributary basins lagged behind the response of the trunk channel to the tectonic activities and river captures.The interconnected wide valleys caused by river capture may have provided convenient geomorphological conditions for human migration into the Qinling-Daba Mountains along those river valleys.
文摘Background： Electroconvulsive therapy （ECT） can alleviate the symptoms of treatment-resistant depression （TRD）. Functional network connectivity （FNC） is a newly developed method to investigate the brain＇s functional connectivity patterns. The first aim of this study was to investigate FNC alterations between TRD patients and healthy controls. The second aim was to explore the relationship between the ECT treatment response and pre-ECT treatment FNC alterations in individual TRD patients. Methods： This study included 82 TRD patients and 41 controls. Patients were screened at baseline and after 2 weeks of treatment with a combination of ECT and antidepressants. Group information guided-independent component analysis （G1G-ICA） was used to compute subject-specific functional networks （FNs）. Grassmann maniibld and step-wise forward component selection using support vector machines were adopted to perform the FNC measure and extract the functional networks＇ connectivity patterns （FCP）. Pearson＇s correlation analysis was used to calculate the correlations between the FCP and ECT response. Results： A total of 82 TRD patients in the ECT group were successfully treated. On an average, 8.50 ~ 2.00 ECT sessions were conducted. After ECT treatment, only 42 TRD patients had an improved response to ECT （the Hamilton scores reduction rate was more than 50%）, response rate 51%. 8 FNs （anterior and posterior default mode network, bilateral frontoparietal network, audio network, visual network, dorsal attention network, and sensorimotor network） were obtained using GIG-ICA. We did not found that FCPs were significantly different between TRD patients and healthy controls. Moreover, the baseline FCP was unrelated to the ECT treatment response. Conclusions： The FNC was not significantly different between the TRD patients and healthy controls, and the baseline FCP was unrelated to the ECT treatment response. These findings will necessitate that we modify the experimental scheme to explore the mechanisms underlying ECT＇s effects on depression and explore the specific predictors of the effects of ECT based on the pre-ECT treatment magnetic resonance imaging.
