Forest carbon sinks are crucial for mitigating urban climate change.Their effectiveness depends on the balance between gross carbon losses and gains.However,quantitative and continuous monitoring of forest change/dist...Forest carbon sinks are crucial for mitigating urban climate change.Their effectiveness depends on the balance between gross carbon losses and gains.However,quantitative and continuous monitoring of forest change/disturbance carbon fluxes is still insufficient.To address this gap,we integrated an improved spatial carbon bookkeeping(SBK)model with the continuous change detection and classification(CCDC)algorithm,long-term Landsat observations,and ground measurements to track carbon emissions,uptakes,and net changes from forest cover changes in the Yangtze River Delta(YRD)of China from 2000 to 2020.The SBK model was refined by incorporating heterogeneous carbon response functions.Our results reveal that carbon emissions(-3.88 Tg C·year^(-1))were four times greater than carbon uptakes(0.93 Tg C·year^(-1))from forest cover changes in the YRD during 2000-2020,despite a net forest cover gain of 10.95×10^(4) ha.These findings indicate that the carbon effect per hectare of forest cover loss is approximately 4.5 times that of forest cover gain.The asymmetric carbon effect suggests that forest cover change may act as a carbon source even with net-zero or net-positive forest cover change.Furthermore,carbon uptakes from forest gains in the YRD during 2000-2020 could only offset 0.28% of energy-related carbon emissions from 2000 to 2019.Urban and agricultural expansions accounted for 37% and 10% of carbon emissions,respectively,while the Grain for Green Project contributed to 45% of carbon uptakes.Our findings underscore the necessity of understanding the asymmetric carbon effects of forest cover loss and gain to accurately assess the capacity of forest carbon sinks.展开更多
Deep simulations have gained widespread attention owing to their excellent acceleration performances.However,these methods cannot provide effective collision detection and response strategies.We propose a deep interac...Deep simulations have gained widespread attention owing to their excellent acceleration performances.However,these methods cannot provide effective collision detection and response strategies.We propose a deep interac-tive physical simulation framework that can effectively address tool-object collisions.The framework can predict the dynamic information by considering the collision state.In particular,the graph neural network is chosen as the base model,and a collision-aware recursive regression module is introduced to update the network parameters recursively using interpenetration distances calculated from the vertex-face and edge-edge tests.Additionally,a novel self-supervised collision term is introduced to provide a more compact collision response.This study extensively evaluates the proposed method and shows that it effectively reduces interpenetration artifacts while ensuring high simulation efficiency.展开更多
A stable skeleton is very important to some applications such as vehicle navigation, object represent and pattern recognition. The connection skeleton is just one that not only can be computed stably but also can figu...A stable skeleton is very important to some applications such as vehicle navigation, object represent and pattern recognition. The connection skeleton is just one that not only can be computed stably but also can figure the connectivity structure of contour. A new method named continuous connectivity detection and a new model named approximate regular polygon (ARP) were proposed for connection skeleton extraction. Both the method and the model were tested by the real maps of road network including flyovers, interchanges and other common object contours. Satisfactory results were obtained.展开更多
The Q-ary low-density parity-check（LDPC） coded high order partial response continuous phase modulation（PR-CPM） with double iterative loops is investigated. This scheme shows significant improvements in power and b...The Q-ary low-density parity-check（LDPC） coded high order partial response continuous phase modulation（PR-CPM） with double iterative loops is investigated. This scheme shows significant improvements in power and bandwidth efficiency, but at the expense of long iterative decoding delay and computational complexity induced by the improper match between the demodulator and the decoder. To address this issue, the convergence behavior of Q-ary LDPC coded CPM is investigated for the Q=2 and Q〉2 cases, and an optimized design method based on the extrinsic information transfer chart is proposed to improve the systematic iterative efficiency. Simulation results demonstrate that the proposed method can achieve a perfect tradeoff between iterative decoding delay and bit error rate performance to satisfy real-time applications.展开更多
This study examined wetland trends in the St.Lawrence Seaway(~500,000 km^(2))in Canada over the past four decades.To this end,historical Landsat data within the Google Earth Engine(GEE)big geo data platform were proce...This study examined wetland trends in the St.Lawrence Seaway(~500,000 km^(2))in Canada over the past four decades.To this end,historical Landsat data within the Google Earth Engine(GEE)big geo data platform were processed.Reference samples were scrutinized using the Continuous Change Detection and Classification(CCDC)algorithm to identify spectrally unchanged samples.These spectrally unchanged samples were subsequently employed as training data within an object-based Random Forest(RF)model to generate wetland maps from 1984 to 2021.Subsequently,a change analysis was conducted to calculate the loss and gain of different wetland types.Overall,it was observed that approximately 45%(184,434 km^(2))and 55%(220,778 km^(2))of the entire study area are covered by wetland and non-wetland categories,respectively.It was also observed that 2.46%(12,495 km^(2))of the study area was changed during 40 years.Overall,there was a decline in the Bog and Fen classes,while the Marsh,Swamp,Forest,Grassland/Shrubland,Cropland,and Barren classes had an increase.Finally,the wetland gain and loss were 6,793 km^(2)and 5,701 km^(2),respectively.This study demonstrated that the use of Landsat data,along with advanced machine learning and GEE,could provide valuable assistance for wetland classification and change studies.展开更多
Single-shot multi-frame phase imaging plays an important role in detecting continuous extreme physical phenomena,particularly suitable for measuring the density of media with non-repeatable changes and uncertainties.H...Single-shot multi-frame phase imaging plays an important role in detecting continuous extreme physical phenomena,particularly suitable for measuring the density of media with non-repeatable changes and uncertainties.However,traditional single-pattern multiplexed imaging faces challenges in retrieving amplitude and phase information of multiple frames without sacrificing spatial resolution and phase accuracy。展开更多
The model of linear frequency modulation continuous wave （LFMCW） applied in underwater detection and the method for the detection of echo signal and the estimation of target parameters were studied. By analyzing the...The model of linear frequency modulation continuous wave （LFMCW） applied in underwater detection and the method for the detection of echo signal and the estimation of target parameters were studied. By analyzing the heterodyne signal, an algorithm with the structure of heterodyne-Practional Fourier Transform （FRFT） was proposed. To reduce the computation of searching targets in a two-dimensional FRFT result, the heterodyne signal would be processed by FRFT at a specific order, after Radon-Ambiguity Transform （RAT） was applied to estimate the sweep rate of the signal. Simulations proved that the algorithm can eliminate the coupling phenomenon of distance and velocity of LFMCW, and estimate targets＇ parameters accurately. The lake trial results showed that the processing gain of LFMCW processed by the algorithm in this paper was 13 dB better than that of the LFM processed by matched filter. The research results indicated that the algorithm applied in LFMCW underwater detection was feasible and effective, and it could estimate targets＇ parameters accurately and obtain a good detection performance.展开更多
Mesoporous silica nanoparticles （MSN） were coated by pH-responsive polymer chitosan-poly （methacrylic acid） （CS-PMAA）. This nano drug delivery system showed good application prospects and the polymer-coated micr...Mesoporous silica nanoparticles （MSN） were coated by pH-responsive polymer chitosan-poly （methacrylic acid） （CS-PMAA）. This nano drug delivery system showed good application prospects and the polymer-coated microspheres were promising site-specific anticancer drug delivery carriers in biomedical field. A continuous detection of pH-responsive drug delivery system in cells in situ, utilizing MSN/CS-PMAA composite microspheres, was pro- posed. Two kinds of different cell lines, tumor cell line （Hela） and normal somatic cells （293T）, were used to inves- tigate the behaviours of the drug loaded system in the cells. Conclusions could be drawn from the fluorescent im- ages obtained by confocal laser scanning microscopy （CLSM）, modified drug-loaded microspheres （MSN/CS-PMAA） were ingested into cells more easily, the uptake of DOX@FITC-MSN/CS-PMAA by HeLa/293T cells were performed at pH 7.4/pH 6.8, DOX was released during the ingestion process, fluorescence intensity de- creased with time because of efflux transport and photo-bleaching. Fluoresence detection by flow cytometry was performed as comparison. The continuous fluorescent observation in situ could be widely used in the pH-responsive releasing process of drug delivery system in the cells.展开更多
Previous collision detection methods for virtual disassembly mainly detect collisions at discrete time intervals and use oriented bounding boxes to speed up the process. However, these discrete methods cannot guarante...Previous collision detection methods for virtual disassembly mainly detect collisions at discrete time intervals and use oriented bounding boxes to speed up the process. However, these discrete methods cannot guarantee no penetration occurs when the components move. Meanwhile, because some of the components are embedded into each other, these components cannot be separated in the subsequent process. To solve these problems, we propose an approach for real-time collision handling by utilizing the computational power of modern GPUs. First we present a novel GPU-based collision handling framework for virtual disassembly. Second we use a collision-streams based continuous collision detection to guarantee no collision missed. Finally we introduce a triangle intersection detection algorithm to solve the problem that collision cannot be detected when the components are embedded into each other at the initial configuration. The experimental results show that our method can improve the overall performance of collision detection and achieve real-time simulation.展开更多
Wetlands provide vital ecological services for both humans and environment,necessitating continuous,refined and up-to-date mapping of wetlands for conservation and management.in this study,we developed an automated an...Wetlands provide vital ecological services for both humans and environment,necessitating continuous,refined and up-to-date mapping of wetlands for conservation and management.in this study,we developed an automated and refined wetland mapping framework integrating training sample migration method,supervised machine learning and knowledge-driven rules using Google Earth Engine(GEE)platform and open-source geospatial tools.We applied the framework to temporally dense Sentinel-1/2 imagery to produce annual refined wetland maps of the Dongting Lake Wetland(DLW)during 2015-2021.First,the continuous change detection(CCD)algorithm was utilized to migrate stable training samples.Then,annual 10 m preliminary land cover maps with 9 classes were produced using random forest algorithm and migrated samples.Ultimately,annual 10 m refined wetland maps were generated based on preliminary land cover maps via knowledge-driven rules from geometric features and available water-related inventories,with Overall Accuracy(OA)ranging from 81.82%(2015)to 93.84%(2020)and Kappa Coefficient(KC)between 0.73(2015)and 0.91(2020),demonstrating satisfactory performance and substantial potential for accurate,timely and type-refined wetland mapping.Our methodological framework allows rapid and accurate monitoring of wetland dynamics and could provide valuable information and methodological support for monitoring,conservation and sustainable development of wetland ecosystem.展开更多
基金supported by the Natural Science Foundation of Zhejiang Province(No.ZCLQN25C0301)the National Key Research and Development Program of China(No.2016YFC0502700)the General Program of Education Department of Zhejiang(No.23056209-F).
文摘Forest carbon sinks are crucial for mitigating urban climate change.Their effectiveness depends on the balance between gross carbon losses and gains.However,quantitative and continuous monitoring of forest change/disturbance carbon fluxes is still insufficient.To address this gap,we integrated an improved spatial carbon bookkeeping(SBK)model with the continuous change detection and classification(CCDC)algorithm,long-term Landsat observations,and ground measurements to track carbon emissions,uptakes,and net changes from forest cover changes in the Yangtze River Delta(YRD)of China from 2000 to 2020.The SBK model was refined by incorporating heterogeneous carbon response functions.Our results reveal that carbon emissions(-3.88 Tg C·year^(-1))were four times greater than carbon uptakes(0.93 Tg C·year^(-1))from forest cover changes in the YRD during 2000-2020,despite a net forest cover gain of 10.95×10^(4) ha.These findings indicate that the carbon effect per hectare of forest cover loss is approximately 4.5 times that of forest cover gain.The asymmetric carbon effect suggests that forest cover change may act as a carbon source even with net-zero or net-positive forest cover change.Furthermore,carbon uptakes from forest gains in the YRD during 2000-2020 could only offset 0.28% of energy-related carbon emissions from 2000 to 2019.Urban and agricultural expansions accounted for 37% and 10% of carbon emissions,respectively,while the Grain for Green Project contributed to 45% of carbon uptakes.Our findings underscore the necessity of understanding the asymmetric carbon effects of forest cover loss and gain to accurately assess the capacity of forest carbon sinks.
基金This project was funded by Natural Science Foundation of Guangdong Province,No.2020B010165004。
文摘Deep simulations have gained widespread attention owing to their excellent acceleration performances.However,these methods cannot provide effective collision detection and response strategies.We propose a deep interac-tive physical simulation framework that can effectively address tool-object collisions.The framework can predict the dynamic information by considering the collision state.In particular,the graph neural network is chosen as the base model,and a collision-aware recursive regression module is introduced to update the network parameters recursively using interpenetration distances calculated from the vertex-face and edge-edge tests.Additionally,a novel self-supervised collision term is introduced to provide a more compact collision response.This study extensively evaluates the proposed method and shows that it effectively reduces interpenetration artifacts while ensuring high simulation efficiency.
文摘A stable skeleton is very important to some applications such as vehicle navigation, object represent and pattern recognition. The connection skeleton is just one that not only can be computed stably but also can figure the connectivity structure of contour. A new method named continuous connectivity detection and a new model named approximate regular polygon (ARP) were proposed for connection skeleton extraction. Both the method and the model were tested by the real maps of road network including flyovers, interchanges and other common object contours. Satisfactory results were obtained.
基金supported by the National Natural Science Foundation of China(61403093)the Science Foundation of Heilongjiang Province of China for Returned Scholars(LC2013C22)the Assisted Project by Heilongjiang Province of China Postdoctoral Funds for Scientific Research Initiation(LBH-Q14048)
文摘The Q-ary low-density parity-check（LDPC） coded high order partial response continuous phase modulation（PR-CPM） with double iterative loops is investigated. This scheme shows significant improvements in power and bandwidth efficiency, but at the expense of long iterative decoding delay and computational complexity induced by the improper match between the demodulator and the decoder. To address this issue, the convergence behavior of Q-ary LDPC coded CPM is investigated for the Q=2 and Q〉2 cases, and an optimized design method based on the extrinsic information transfer chart is proposed to improve the systematic iterative efficiency. Simulation results demonstrate that the proposed method can achieve a perfect tradeoff between iterative decoding delay and bit error rate performance to satisfy real-time applications.
文摘This study examined wetland trends in the St.Lawrence Seaway(~500,000 km^(2))in Canada over the past four decades.To this end,historical Landsat data within the Google Earth Engine(GEE)big geo data platform were processed.Reference samples were scrutinized using the Continuous Change Detection and Classification(CCDC)algorithm to identify spectrally unchanged samples.These spectrally unchanged samples were subsequently employed as training data within an object-based Random Forest(RF)model to generate wetland maps from 1984 to 2021.Subsequently,a change analysis was conducted to calculate the loss and gain of different wetland types.Overall,it was observed that approximately 45%(184,434 km^(2))and 55%(220,778 km^(2))of the entire study area are covered by wetland and non-wetland categories,respectively.It was also observed that 2.46%(12,495 km^(2))of the study area was changed during 40 years.Overall,there was a decline in the Bog and Fen classes,while the Marsh,Swamp,Forest,Grassland/Shrubland,Cropland,and Barren classes had an increase.Finally,the wetland gain and loss were 6,793 km^(2)and 5,701 km^(2),respectively.This study demonstrated that the use of Landsat data,along with advanced machine learning and GEE,could provide valuable assistance for wetland classification and change studies.
基金China Postdoctoral Science Foundation(2023M743252,2024T170846)Key Research and Development Program of Zhejiang Province(2024SSYS0014)National Natural Science Foundation of China(62205304).
文摘Single-shot multi-frame phase imaging plays an important role in detecting continuous extreme physical phenomena,particularly suitable for measuring the density of media with non-repeatable changes and uncertainties.However,traditional single-pattern multiplexed imaging faces challenges in retrieving amplitude and phase information of multiple frames without sacrificing spatial resolution and phase accuracy。
文摘The model of linear frequency modulation continuous wave （LFMCW） applied in underwater detection and the method for the detection of echo signal and the estimation of target parameters were studied. By analyzing the heterodyne signal, an algorithm with the structure of heterodyne-Practional Fourier Transform （FRFT） was proposed. To reduce the computation of searching targets in a two-dimensional FRFT result, the heterodyne signal would be processed by FRFT at a specific order, after Radon-Ambiguity Transform （RAT） was applied to estimate the sweep rate of the signal. Simulations proved that the algorithm can eliminate the coupling phenomenon of distance and velocity of LFMCW, and estimate targets＇ parameters accurately. The lake trial results showed that the processing gain of LFMCW processed by the algorithm in this paper was 13 dB better than that of the LFM processed by matched filter. The research results indicated that the algorithm applied in LFMCW underwater detection was feasible and effective, and it could estimate targets＇ parameters accurately and obtain a good detection performance.
基金the National Natural Science Foundation of China，the Shanghai Committee of Science and Technology
文摘Mesoporous silica nanoparticles （MSN） were coated by pH-responsive polymer chitosan-poly （methacrylic acid） （CS-PMAA）. This nano drug delivery system showed good application prospects and the polymer-coated microspheres were promising site-specific anticancer drug delivery carriers in biomedical field. A continuous detection of pH-responsive drug delivery system in cells in situ, utilizing MSN/CS-PMAA composite microspheres, was pro- posed. Two kinds of different cell lines, tumor cell line （Hela） and normal somatic cells （293T）, were used to inves- tigate the behaviours of the drug loaded system in the cells. Conclusions could be drawn from the fluorescent im- ages obtained by confocal laser scanning microscopy （CLSM）, modified drug-loaded microspheres （MSN/CS-PMAA） were ingested into cells more easily, the uptake of DOX@FITC-MSN/CS-PMAA by HeLa/293T cells were performed at pH 7.4/pH 6.8, DOX was released during the ingestion process, fluorescence intensity de- creased with time because of efflux transport and photo-bleaching. Fluoresence detection by flow cytometry was performed as comparison. The continuous fluorescent observation in situ could be widely used in the pH-responsive releasing process of drug delivery system in the cells.
基金This work was supported by the National Natural Science Foundation of China under Grant No. 61472111, the Zhejiang Provincial Natural Science Foundation of China under Grant No. LQ13F020016, the Foundation of Zhejiang Educational Committee under Grant No. Y201224034, and the Scientific Research Start Foundation of Hangzhou Dianzi University under Grant No. KYS225613032.
文摘Previous collision detection methods for virtual disassembly mainly detect collisions at discrete time intervals and use oriented bounding boxes to speed up the process. However, these discrete methods cannot guarantee no penetration occurs when the components move. Meanwhile, because some of the components are embedded into each other, these components cannot be separated in the subsequent process. To solve these problems, we propose an approach for real-time collision handling by utilizing the computational power of modern GPUs. First we present a novel GPU-based collision handling framework for virtual disassembly. Second we use a collision-streams based continuous collision detection to guarantee no collision missed. Finally we introduce a triangle intersection detection algorithm to solve the problem that collision cannot be detected when the components are embedded into each other at the initial configuration. The experimental results show that our method can improve the overall performance of collision detection and achieve real-time simulation.
基金supported by the National Natural Science Foundation of China(grant numbers 42071393,U1901219 and U21A2022).
文摘Wetlands provide vital ecological services for both humans and environment,necessitating continuous,refined and up-to-date mapping of wetlands for conservation and management.in this study,we developed an automated and refined wetland mapping framework integrating training sample migration method,supervised machine learning and knowledge-driven rules using Google Earth Engine(GEE)platform and open-source geospatial tools.We applied the framework to temporally dense Sentinel-1/2 imagery to produce annual refined wetland maps of the Dongting Lake Wetland(DLW)during 2015-2021.First,the continuous change detection(CCD)algorithm was utilized to migrate stable training samples.Then,annual 10 m preliminary land cover maps with 9 classes were produced using random forest algorithm and migrated samples.Ultimately,annual 10 m refined wetland maps were generated based on preliminary land cover maps via knowledge-driven rules from geometric features and available water-related inventories,with Overall Accuracy(OA)ranging from 81.82%(2015)to 93.84%(2020)and Kappa Coefficient(KC)between 0.73(2015)and 0.91(2020),demonstrating satisfactory performance and substantial potential for accurate,timely and type-refined wetland mapping.Our methodological framework allows rapid and accurate monitoring of wetland dynamics and could provide valuable information and methodological support for monitoring,conservation and sustainable development of wetland ecosystem.
