Vortex-induced vibration(VIV)of an underwater manipulator in pulsating flow presents a notable engineering problem in precise control due to the velocity variation in the flow.This study investigates the VIV response ...Vortex-induced vibration(VIV)of an underwater manipulator in pulsating flow presents a notable engineering problem in precise control due to the velocity variation in the flow.This study investigates the VIV response of an underwater manipulator subjected to pulsating flow,focusing on how different postures affect the behavior of the system.The effects of pulsating parameters and manipulator arrangement on the hydrodynamic coefficient,vibration response,motion trajectory,and vortex shedding behaviors were analyzed.Results indicated that the cross flow vibration displacement in pulsating flow increased by 32.14%compared to uniform flow,inducing a shift in the motion trajectory from a crescent shape to a sideward vase shape.In the absence of interference between the upper and lower arms,the lift coefficient of the manipulator substantially increased with rising pulsating frequency,reaching a maximum increment of 67.0%.This increase in the lift coefficient led to a 67.05%rise in the vibration frequency of the manipulator in the in-line direction.As the pulsating amplitude increased,the drag coefficient of the underwater manipulator rose by 36.79%,but the vibration frequency in the cross-flow direction decreased by 56.26%.Additionally,when the upper and lower arms remained in a state of mutual interference,the cross-flow vibration amplitudes of the upper and lower arms were approximately 1.84 and 4.82 times higher in a circular-elliptical arrangement compared to an elliptical-circular arrangement,respectively.Consequently,the flow field shifted from a P+S pattern to a disordered pattern,disrupting the regularity of the motion trajectory.展开更多
The safe driving and operation of trains is a necessary condition for ensuring the safe operation of trains.In particular,heavy-haul trains are characterized by the difficulty in driving and operation.Considering the ...The safe driving and operation of trains is a necessary condition for ensuring the safe operation of trains.In particular,heavy-haul trains are characterized by the difficulty in driving and operation.Considering the uncertainties in train driving and operation,this paper analyzes the relationship between the safety of heavy-haul electric locomotive hauled trains and driving and operation.It studies the auxiliary intelligent driving safety operation control methods.Through K-means to identify the characteristics of drivers'driving manipulation,the hidden Markov model adaptively adjusts the train driving and operation sequence,and conducts auxiliary driving reconstruction for heavy-haul locomotive driving and operation.Based on the train running curve and the locomotive traction/braking characteristics,it smoothly controls the exertion of the traction/braking force of heavy-haul locomotives,thereby optimizing the driving safety control of heavy-haul trains in the vehicle-environment-track system.Finally,the train operation simulation and optimized driving verification are carried out by simulating some track sections.The results show that the proposed method can correct and pre-optimize driving operations,improving the smoothness of heavy-haul trains by approximately 10%.It verifies the effectiveness of the proposed train assisted driving control reconstruction method,facilitating the smooth and safe operation of heavy-haul trains.展开更多
Octopuses,due to their flexible arms,marvelous adaptability,and powerful suckers,are able to effortlessly grasp and disengage various objects in the marine surrounding without causing devastation.However,manipulating ...Octopuses,due to their flexible arms,marvelous adaptability,and powerful suckers,are able to effortlessly grasp and disengage various objects in the marine surrounding without causing devastation.However,manipulating delicate objects such as soft and fragile foods underwater require gentle contact and stable adhesion,which poses a serious challenge to now available soft grippers.Inspired by the sucker infundibulum structure and flexible tentacles of octopus,herein we developed a hydraulically actuated hydrogel soft gripper with adaptive maneuverability by coupling multiple hydrogen bond-mediated supramolecular hydrogels and vat polymerization three-dimensional printing,in which hydrogel bionic sucker is composed of a tunable curvature membrane,a negative pressure cavity,and a pneumatic chamber.The design of the sucker structure with the alterable curvature membrane is conducive to realize the reliable and gentle switchable adhesion of the hydrogel soft gripper.As a proof-of-concept,the adaptive hydrogel soft gripper is capable of implement diversified underwater tasks,including gingerly grasping fragile foods like egg yolks and tofu,as well as underwater robots and vehicles that station-keeping and crawling based on switchable adhesion.This study therefore provides a transformative strategy for the design of novel soft grippers that will render promising utilities for underwater exploration soft robotics.展开更多
Soft robotic manipulators represent a rapidly evolving field characterized by inherent compliance,adaptability,and safe interactions within unstructured environments.Over the past decade(2015-2025),significant advance...Soft robotic manipulators represent a rapidly evolving field characterized by inherent compliance,adaptability,and safe interactions within unstructured environments.Over the past decade(2015-2025),significant advancements have trans-formed their capabilities through novel designs inspired by biological systems,advanced modeling frameworks,sophisti-cated control strategies,and integration into diverse real-world applications.Recent innovations in multifunctional mate-rials and emerging actuation technologies have markedly expanded manipulator performance,reliability,and dexterity.Concurrently,developments in modeling have progressed from simplified geometric methods toward highly accurate physics-based and hybrid data-driven approaches,substantially improving real-time prediction and controllability.Coupled with these developments,adaptive and robust control strategies-including learning-based techniques-have enabled unprec-edented autonomy and precision in challenging application domains such as Minimally Invasive Surgery(MIS),precision agriculture,deep-sea exploration,disaster recovery,and space missions.Despite these remarkable strides,key challenges remain,notably regarding scalability,long-term material durability,robust integrated sensing,and standardized evaluation procedures.This review comprehensively synthesizes recent advances,critically evaluates state-of-the-art methodologies,and systematically identifies existing gaps to provide a clear roadmap and targeted research directions,guiding future developments toward the broader adoption and optimal utilization of soft robotic manipulators.展开更多
With introduction of three heavy manipulations therapy at Dazhui （大椎 GV 14） for unclear enunciation case of acute cerebral infarction, acute attack case of chronic asthmatic bronchitis, amyotrophic lateral scleros...With introduction of three heavy manipulations therapy at Dazhui （大椎 GV 14） for unclear enunciation case of acute cerebral infarction, acute attack case of chronic asthmatic bronchitis, amyotrophic lateral sclerosis case of motor neuron disease, ankylosing spondylitis case and chronic fatigue syndrome case, it is confirmed thatDazhui （大椎 GV 14） combined with three heavy manipulations therapy of blood-letting acupuncture, cupping and moxibust-ion has efficacy for external and endogenous wind, promoting and tonifying yang- qi, strengthening the body timely, removing wind and dampness, and relieving the pain and spasm in the clinical practice.展开更多
Mapping regional spatial patterns of coral reef geomorphology provides the primary information to understand the constructive processes in the reef ecosystem. However, this work is challenged by the pixel-based image ...Mapping regional spatial patterns of coral reef geomorphology provides the primary information to understand the constructive processes in the reef ecosystem. However, this work is challenged by the pixel-based image classification method for its comparatively low accuracy. In this paper, an object-based image analysis(OBIA)method was presented to map intra-reef geomorphology of coral reefs in the Xisha Islands, China using Landsat 8satellite imagery. Following the work of the Millennium Coral Reef Mapping Project, a regional reef class hierarchy with ten geomorphic classes was first defined. Then, incorporating the hierarchical concept and integrating the spectral and additional spatial information such as context, shape and contextual relationships, a large-scale geomorphic map was produced by OBIA with accuracies generally more than 80%. Although the robustness of OBIA has been validated in the applications of coral reef mapping from individual reefs to reef system in this paper, further work is still required to improve its transferability.展开更多
OBJECTIVE:To determine the clinical effect,treatment times,and rheoencephalogram changes in vertebral artery type cervical spondylosis patients treated with innovative Tuina manipulations.METHODS:One hundred and twent...OBJECTIVE:To determine the clinical effect,treatment times,and rheoencephalogram changes in vertebral artery type cervical spondylosis patients treated with innovative Tuina manipulations.METHODS:One hundred and twenty six cervical spondylosis patients(vertebral artery type) were randomly divided into test and control groups.Patients in the test group were treated with innovative Tuina manipulations,while those in the control group were treated with the routine Tuina manipulations according to the textbook of Chinese Massage for Acupuncture and Moxibustion majors.The clinical effects,treatment times,clinical symptoms,and cerebral blood flow were measured.RESULTS:The response to the treatment was 100% in the test group and 88.71% in the control group.Patients in the test group required(7 ± 4) treatments before recovery,while those in the control group required(15 ± 7) treatments before recovery(P<0.05).The clinical symptoms exhibited greater improvement in the test group compared to the control group(P<0.05).There were no differences in cerebral blood flow between the two groups.CONCLUSION:Both innovative Tuina manipulations and routine Tuina manipulations produced satisfactory therapeutic results in vertebral artery type cervical spondylosis patients.However,the innovative manipulation was more effective in improving the functional symptoms,although there were no changes in the cerebral blood flow.展开更多
This paper presents a new framework for object-based classification of high-resolution hyperspectral data.This multi-step framework is based on multi-resolution segmentation(MRS)and Random Forest classifier(RFC)algori...This paper presents a new framework for object-based classification of high-resolution hyperspectral data.This multi-step framework is based on multi-resolution segmentation(MRS)and Random Forest classifier(RFC)algorithms.The first step is to determine of weights of the input features while using the object-based approach with MRS to processing such images.Given the high number of input features,an automatic method is needed for estimation of this parameter.Moreover,we used the Variable Importance(VI),one of the outputs of the RFC,to determine the importance of each image band.Then,based on this parameter and other required parameters,the image is segmented into some homogenous regions.Finally,the RFC is carried out based on the characteristics of segments for converting them into meaningful objects.The proposed method,as well as,the conventional pixel-based RFC and Support Vector Machine(SVM)method was applied to three different hyperspectral data-sets with various spectral and spatial characteristics.These data were acquired by the HyMap,the Airborne Prism Experiment(APEX),and the Compact Airborne Spectrographic Imager(CASI)hyperspectral sensors.The experimental results show that the proposed method is more consistent for land cover mapping in various areas.The overall classification accuracy(OA),obtained by the proposed method was 95.48,86.57,and 84.29%for the HyMap,the APEX,and the CASI datasets,respectively.Moreover,this method showed better efficiency in comparison to the spectralbased classifications because the OAs of the proposed method was 5.67 and 3.75%higher than the conventional RFC and SVM classifiers,respectively.展开更多
The source-sink ratio during grain filling is a critical factor that affects crop yield in wheat,and the main objective of this study was to determine the source-sink relations at both the canopy scale and the individ...The source-sink ratio during grain filling is a critical factor that affects crop yield in wheat,and the main objective of this study was to determine the source-sink relations at both the canopy scale and the individual culm level under two nitrogen(N)levels at the post-jointing stage.Nine widely-used cultivars were chosen for analyzing source-sink relations in southwestern China;and three typical cultivars of different plant types were subjected to artificial manipulation of the grain-filling source-sink ratio to supplement crop growth measurements.A field experiment was conducted over two consecutive seasons under two N rates(N+,150 kg ha^(-1);N-,60 kg ha^(-1)),and three manipulations were imposed after anthesis:control(Ct),removal of flag and penultimate leaves(Lr)and removal of spikelets on one side of each spike(Sr).The results showed that the single grain weights in the three cultivars were significantly decreased by Lr and increased by Sr,which demonstrated that wheat grain yield potential seems more source-limited than sink-limited during grain filling,but the source-sink balance was obviously changed by climatic variations and N deficient environments.Grain yield was highly associated with sink capacity(SICA),grain number,biomass,SPAD values,and leaf area index during grain filling,indicating a higher degree of source limitation with an increase in sink capacity.Therefore,source limitation should be taken into account by breeders when SICA is increased,especially under non-limiting conditions.Chuanmai 104,a half-compact type with a mid-sized spike and a long narrow upper leaf,showed relatively better performance in source-sink relations.Since this cultivar showed the characteristics of a lower reduction in grain weight after Lr,a larger increase after Sr,and a lower reduction in post-anthesis dry matter accumulation,then the greater current photosynthesis during grain filling contributed to the grain after source and sink manipulation.展开更多
Objective: To analyze the effects of twirling reinforcing and reducing manipulations on protein expression in parietal cortex of spontaneously hypertensive rats(SHRs), and elucidate the main mechanisms and differences...Objective: To analyze the effects of twirling reinforcing and reducing manipulations on protein expression in parietal cortex of spontaneously hypertensive rats(SHRs), and elucidate the main mechanisms and differences between two manipulations in hypertension treatment.Methods: Rats were randomly divided into the control, model, twirling reinforcing manipulation(TRFM),and twirling reducing manipulation(TRDM) groups. The control and model groups received catch and fixation stimulations once a day for 14 days. The TRFM and TRDM groups were intervened once a day for 20 min for 14 days. On days 0, 2, 6, 10, and 14 after acupuncture, rat systolic blood pressures(SBPs) were measured. Differential protein(DP) expression in the rat parietal cortices was detected. Thereafter, GO functional significance and KEGG pathway enrichment analyses were performed.Results: Compared with the model group, SBP of rats in the TRDM and TRFM groups decreased on days 6 and 10 of acupuncture, respectively(P=.009;P <.001). Moreover, SBP of the TRDM group was significantly lower than that of the TRFM group on days 10 and 14 of acupuncture(P=.015;P=.013).Compared with control group, 601 and 1040 DPs were up-and downregulated, respectively, in the model group. Compared with model group, 44 and 28 up-and downregulated DPs were expressed, respectively,in the TRFM group. Compared with model group, expression of 616 and 427 up-and downregulated DPs,respectively, was found in the TRDM group. After combining the results of GO and KEGG enrichment analyses, five and one pathways were found to be related to the central antihypertensive mechanism of the parietal cortex during twirling reducing and reinforcing manipulations, respectively.Conclusion: TRDM showed a more effective antihypertensive effect on SHRs than TRFM;this antihypertensive effect was related to the regulation of different proteins and their biological functions.展开更多
Accurate crop distribution mapping is required for crop yield prediction and field management. Due to rapid progress in remote sensing technology, fine spatial resolution(FSR) remotely sensed imagery now offers great ...Accurate crop distribution mapping is required for crop yield prediction and field management. Due to rapid progress in remote sensing technology, fine spatial resolution(FSR) remotely sensed imagery now offers great opportunities for mapping crop types in great detail. However, within-class variance can hamper attempts to discriminate crop classes at fine resolutions. Multi-temporal FSR remotely sensed imagery provides a means of increasing crop classification from FSR imagery, although current methods do not exploit the available information fully. In this research, a novel Temporal Sequence Object-based Convolutional Neural Network(TS-OCNN) was proposed to classify agricultural crop type from FSR image time-series. An object-based CNN(OCNN) model was adopted in the TS-OCNN to classify images at the object level(i.e., segmented objects or crop parcels), thus, maintaining the precise boundary information of crop parcels. The combination of image time-series was first utilized as the input to the OCNN model to produce an ‘original’ or baseline classification. Then the single-date images were fed automatically into the deep learning model scene-by-scene in order of image acquisition date to increase successively the crop classification accuracy. By doing so, the joint information in the FSR multi-temporal observations and the unique individual information from the single-date images were exploited comprehensively for crop classification. The effectiveness of the proposed approach was investigated using multitemporal SAR and optical imagery, respectively, over two heterogeneous agricultural areas. The experimental results demonstrated that the newly proposed TS-OCNN approach consistently increased crop classification accuracy, and achieved the greatest accuracies(82.68% and 87.40%) in comparison with state-of-the-art benchmark methods, including the object-based CNN(OCNN)(81.63% and85.88%), object-based image analysis(OBIA)(78.21% and 84.83%), and standard pixel-wise CNN(79.18%and 82.90%). The proposed approach is the first known attempt to explore simultaneously the joint information from image time-series with the unique information from single-date images for crop classification using a deep learning framework. The TS-OCNN, therefore, represents a new approach for agricultural landscape classification from multi-temporal FSR imagery. Besides, it is readily generalizable to other landscapes(e.g., forest landscapes), with a wide application prospect.展开更多
Efficient and accurate access to coastal land cover information is of great significance for marine disaster prevention and mitigation.Although the popular and common sensors of land resource satellites provide free a...Efficient and accurate access to coastal land cover information is of great significance for marine disaster prevention and mitigation.Although the popular and common sensors of land resource satellites provide free and valuable images to map the land cover,coastal areas often encounter significant cloud cover,especially in tropical areas,which makes the classification in those areas non-ideal.To solve this problem,we proposed a framework of combining medium-resolution optical images and synthetic aperture radar(SAR)data with the recently popular object-based image analysis(OBIA)method and used the Landsat Operational Land Imager(OLI)and Phased Array type L-band Synthetic Aperture Radar(PALSAR)images acquired in Singapore in 2017 as a case study.We designed experiments to confirm two critical factors of this framework:one is the segmentation scale that determines the average object size,and the other is the classification feature.Accuracy assessments of the land cover indicated that the optimal segmentation scale was between 40 and 80,and the features of the combination of OLI and SAR resulted in higher accuracy than any individual features,especially in areas with cloud cover.Based on the land cover generated by this framework,we assessed the vulnerability of the marine disasters of Singapore in 2008 and 2017 and found that the high-vulnerability areas mainly located in the southeast and increased by 118.97 km2 over the past decade.To clarify the disaster response plan for different geographical environments,we classified risk based on altitude and distance from shore.The newly increased high-vulnerability regions within 4 km offshore and below 30 m above sea level are at high risk;these regions may need to focus on strengthening disaster prevention construction.This study serves as a typical example of using remote sensing techniques for the vulnerability assessment of marine disasters,especially those in cloudy coastal areas.展开更多
Gully feature mapping is an indispensable prerequisite for the motioning and control of gully erosion which is a widespread natural hazard. The increasing availability of high-resolution Digital Elevation Model(DEM) a...Gully feature mapping is an indispensable prerequisite for the motioning and control of gully erosion which is a widespread natural hazard. The increasing availability of high-resolution Digital Elevation Model(DEM) and remote sensing imagery, combined with developed object-based methods enables automatic gully feature mapping. But still few studies have specifically focused on gully feature mapping on different scales. In this study, an object-based approach to two-level gully feature mapping, including gully-affected areas and bank gullies, was developed and tested on 1-m DEM and Worldview-3 imagery of a catchment in the Chinese Loess Plateau. The methodology includes a sequence of data preparation, image segmentation, metric calculation, and random forest based classification. The results of the two-level mapping were based on a random forest model after investigating the effects of feature selection and class-imbalance problem. Results show that the segmentation strategy adopted in this paper which considers the topographic information and optimal parameter combination can improve the segmentation results. The distribution of the gully-affected area is closely related to topographic information, however, the spectral features are more dominant for bank gully mapping. The highest overall accuracy of the gully-affected area mapping was 93.06% with four topographic features. The highest overall accuracy of bank gully mapping is 78.5% when all features are adopted. The proposed approach is a creditable option for hierarchical mapping of gully feature information, which is suitable for the application in hily Loess Plateau region.展开更多
Contactless acoustic manipulation of micro/nanoscale particles has attracted considerable attention owing to its near independence of the physical and chemical properties of the targets,making it universally applicabl...Contactless acoustic manipulation of micro/nanoscale particles has attracted considerable attention owing to its near independence of the physical and chemical properties of the targets,making it universally applicable to almost all biological systems.Thin-film bulk acoustic wave(BAW)resonators operating at gigahertz(GHz)frequencies have been demonstrated to generate localized high-speed microvortices through acoustic streaming effects.Benefitting from the strong drag forces of the high-speed vortices,BAW-enabled GHz acoustic streaming tweezers(AST)have been applied to the trapping and enrichment of particles ranging in size from micrometers to less than 100 nm.However,the behavior of particles in such 3D microvortex systems is still largely unknown.In this work,the particle behavior(trapping,enrichment,and separation)in GHz AST is studied by theoretical analyses,3D simulations,and microparticle tracking experiments.It is found that the particle motion in the vortices is determined mainly by the balance between the acoustic streaming drag force and the acoustic radiation force.This work can provide basic design principles for AST-based lab-on-a-chip systems for a variety of applications.展开更多
The Baltic Sea is a brackish, mediterranean sea located in the middle latitudes of Europe. It is seasonally covered with ice. The ice covered areas during a typical winter are the Bothnian Bay, the Gulf of Finnland an...The Baltic Sea is a brackish, mediterranean sea located in the middle latitudes of Europe. It is seasonally covered with ice. The ice covered areas during a typical winter are the Bothnian Bay, the Gulf of Finnland and the Gulf of Riga. Sea ice plays an important role in dynamic and thermodynamic processes and also has a strong impact on the heat budget of the sea. Also a large part of transport goes by sea, and there is a need to create ice charts to make the marine transport safe. Because of high cloudiness in winter season and small amount of light in the northern part of the Baltic Sea, radar data are the most important remote sensing source of sea ice information. The main goal of the following studies is classification of the Baltic sea ice cover using radar data. The ENVISAT ASAR （Advanced Synthetic Aperture Radar） acquires data in five different modes. In the following studies ASAR Wide Swath Mode data were used. The Wide Swath Mode, using the ScanSAR technique provides medium resolution images （150 m） over a swath of 405 kin, at HH or VV polarization. In following work data from February 13th, February 24th and April 6th, 2011, representing three different sea ice situations were chosen. OBIA （object-based image analysis） methods and texture parameters were used to create sea ice extent and sea ice concentration charts. Based on object-based methods, it can separate single sea ice floes within the ice pack and calculate more accurately sea ice concentration.展开更多
The detection of impervious surface (IS) in heterogeneous urban areas is one of the most challenging tasks in urban remote sensing. One of the limitations in IS detection at the parcel level is the lack of sufficient ...The detection of impervious surface (IS) in heterogeneous urban areas is one of the most challenging tasks in urban remote sensing. One of the limitations in IS detection at the parcel level is the lack of sufficient training data. In this study, a generic model of spatial distribution of roof materials is considered to overcome this limitation. A generic model that is based on spectral, spatial and textural information which is extracted from available training data is proposed. An object-based approach is used to extract the information inherent in the image. Furthermore, linear discriminant analysis is used for dimensionality reduction and to discriminate between different spatial, spectral and textural attributes. The generic model is composed of a discriminant function based on linear combinations of the predictor variables that provide the best discrimination among the groups. The discriminate analysis result shows that of the 54 attributes extracted from the WorldView-2 image, only 13 attributes related to spatial, spectral and textural information are useful for discriminating different roof materials. Finally, this model is applied to different WorldView-2 images from different areas and proves that this model has good potential to predict roof materials from the WorldView-2 images without using training data.展开更多
An object-based approach is proposed for land cover classification using optimal polarimetric parameters.The ability to identify targets is effectively enhanced by the integration of SAR and optical images.The innovat...An object-based approach is proposed for land cover classification using optimal polarimetric parameters.The ability to identify targets is effectively enhanced by the integration of SAR and optical images.The innovation of the presented method can be summarized in the following two main points:①estimating polarimetric parameters(H-A-Alpha decomposition)through the optical image as a driver;②a multi-resolution segmentation based on the optical image only is deployed to refine classification results.The proposed method is verified by using Sentinel-1/2 datasets over the Bakersfield area,California.The results are compared against those from pixel-based SVM classification using the ground truth from the National Land Cover Database(NLCD).A detailed accuracy assessment complied with seven classes shows that the proposed method outperforms the conventional approach by around 10%,with an overall accuracy of 92.6%over regions with rich texture.展开更多
Many researches have been performed comparing object-based classification (OBC) and pixel-based classification (PBC), particularly in classifying high-resolution satellite images. VNREDSat-1 is the first optical remot...Many researches have been performed comparing object-based classification (OBC) and pixel-based classification (PBC), particularly in classifying high-resolution satellite images. VNREDSat-1 is the first optical remote sensing satellite of Vietnam with resolution of 2.5 m (Panchromatic) and 10 m (Multispectral). The objective of this research is to compare two classification approaches using VNREDSat-1 image for mapping mangrove forest in Vien An Dong commune, Ngoc Hien district, Ca Mau province. ISODATA algorithm (in PBC method) and membership function classifier (in OBC method) were chosen to classify the same image. The results show that the overall accuracies of OBC and PBC are 73% and 62.16% respectively, and OBC solved the “salt and pepper” which is the main issue of PBC as well. Therefore, OBC is supposed to be the better approach to classify VNREDSat-1 for mapping mangrove forest in Ngoc Hien commune.展开更多
Acupuncture and moxibustion therapy non-specifically raises the pain threshold, relieves regional muscular tension, improves local blood circulation, accelerates elimination of algogenic substances such as acid metabo...Acupuncture and moxibustion therapy non-specifically raises the pain threshold, relieves regional muscular tension, improves local blood circulation, accelerates elimination of algogenic substances such as acid metabolites, and promotes neural regeneration and functional rehabilitation. However, the effects of acupuncture are synthetically influenced by multiple factors, which vary with acu-puncture point, intensity, and manipulation. The present study explored the analgesic effects and mechanisms of specific Sancai acupuncture manipulation for sciatica. Results revealed that Sancai acupuncture manipulation significantly reduced inflammatory factor interleukin-6 expression in the blood serum of rats with sciatica, exhibited anti-inflammatory effects and promoted rehabilitation of injured nerves. In addition, Sancai acupuncture manipulation exhibited superior curative effects over conventional acupuncture manipulation.展开更多
With the deterioration of the environment,it is imperative to protect coastal wetlands.Using multi-source remote sensing data and object-based hierarchical classification to classify coastal wetlands is an effective m...With the deterioration of the environment,it is imperative to protect coastal wetlands.Using multi-source remote sensing data and object-based hierarchical classification to classify coastal wetlands is an effective method.The object-based hierarchical classification using remote sensing indices(OBH-RSI)for coastal wetland is proposed to achieve fine classification of coastal wetland.First,the original categories are divided into four groups according to the category characteristics.Second,the training and test maps of each group are extracted according to the remote sensing indices.Third,four groups are passed through the classifier in order.Finally,the results of the four groups are combined to get the final classification result map.The experimental results demonstrate that the overall accuracy,average accuracy and kappa coefficient of the proposed strategy are over 94%using the Yellow River Delta dataset.展开更多
基金Supported by the National Natural Science Foundation of China(No.51905211)A Project of the“20 Regulations for New Universities”Funding Program of Jinan(No.202228116).
文摘Vortex-induced vibration(VIV)of an underwater manipulator in pulsating flow presents a notable engineering problem in precise control due to the velocity variation in the flow.This study investigates the VIV response of an underwater manipulator subjected to pulsating flow,focusing on how different postures affect the behavior of the system.The effects of pulsating parameters and manipulator arrangement on the hydrodynamic coefficient,vibration response,motion trajectory,and vortex shedding behaviors were analyzed.Results indicated that the cross flow vibration displacement in pulsating flow increased by 32.14%compared to uniform flow,inducing a shift in the motion trajectory from a crescent shape to a sideward vase shape.In the absence of interference between the upper and lower arms,the lift coefficient of the manipulator substantially increased with rising pulsating frequency,reaching a maximum increment of 67.0%.This increase in the lift coefficient led to a 67.05%rise in the vibration frequency of the manipulator in the in-line direction.As the pulsating amplitude increased,the drag coefficient of the underwater manipulator rose by 36.79%,but the vibration frequency in the cross-flow direction decreased by 56.26%.Additionally,when the upper and lower arms remained in a state of mutual interference,the cross-flow vibration amplitudes of the upper and lower arms were approximately 1.84 and 4.82 times higher in a circular-elliptical arrangement compared to an elliptical-circular arrangement,respectively.Consequently,the flow field shifted from a P+S pattern to a disordered pattern,disrupting the regularity of the motion trajectory.
基金Project(U2034211)supported by the National Natural Science Foundation of ChinaProject(20232ACE01013)supported by the Major Scientific and Technological Research and Development Special Project of Jiangxi Province,China。
文摘The safe driving and operation of trains is a necessary condition for ensuring the safe operation of trains.In particular,heavy-haul trains are characterized by the difficulty in driving and operation.Considering the uncertainties in train driving and operation,this paper analyzes the relationship between the safety of heavy-haul electric locomotive hauled trains and driving and operation.It studies the auxiliary intelligent driving safety operation control methods.Through K-means to identify the characteristics of drivers'driving manipulation,the hidden Markov model adaptively adjusts the train driving and operation sequence,and conducts auxiliary driving reconstruction for heavy-haul locomotive driving and operation.Based on the train running curve and the locomotive traction/braking characteristics,it smoothly controls the exertion of the traction/braking force of heavy-haul locomotives,thereby optimizing the driving safety control of heavy-haul trains in the vehicle-environment-track system.Finally,the train operation simulation and optimized driving verification are carried out by simulating some track sections.The results show that the proposed method can correct and pre-optimize driving operations,improving the smoothness of heavy-haul trains by approximately 10%.It verifies the effectiveness of the proposed train assisted driving control reconstruction method,facilitating the smooth and safe operation of heavy-haul trains.
基金the financial support from the Strategic Priority Research Program of the Chinese Academy of Sciences (XDB0470303)the National Key Research and Development Program of China (2022YFB4600101)+5 种基金the National Natural Science Foundation of China (52175201)the Research Program of Science and Technology Department of Gansu Province (24JRRA059, 24JRRA044, and 24YFFA014)the Science Fund of Shandong Laboratory of Advanced Materials and Green Manufacturing at Yantai (AMGM2024F12)the Major Program (ZYFZFX-2) of the Lanzhou Institute of Chemical Physics, CASthe Special Research Assistant Project of the Chinese Academy of Sciencesthe Oasis Scholar of Shihezi University
文摘Octopuses,due to their flexible arms,marvelous adaptability,and powerful suckers,are able to effortlessly grasp and disengage various objects in the marine surrounding without causing devastation.However,manipulating delicate objects such as soft and fragile foods underwater require gentle contact and stable adhesion,which poses a serious challenge to now available soft grippers.Inspired by the sucker infundibulum structure and flexible tentacles of octopus,herein we developed a hydraulically actuated hydrogel soft gripper with adaptive maneuverability by coupling multiple hydrogen bond-mediated supramolecular hydrogels and vat polymerization three-dimensional printing,in which hydrogel bionic sucker is composed of a tunable curvature membrane,a negative pressure cavity,and a pneumatic chamber.The design of the sucker structure with the alterable curvature membrane is conducive to realize the reliable and gentle switchable adhesion of the hydrogel soft gripper.As a proof-of-concept,the adaptive hydrogel soft gripper is capable of implement diversified underwater tasks,including gingerly grasping fragile foods like egg yolks and tofu,as well as underwater robots and vehicles that station-keeping and crawling based on switchable adhesion.This study therefore provides a transformative strategy for the design of novel soft grippers that will render promising utilities for underwater exploration soft robotics.
基金Open access funding provided by The Science,Technology&Innovation Funding Authority(STDF)in cooperation with The Egyptian Knowledge Bank(EKB).
文摘Soft robotic manipulators represent a rapidly evolving field characterized by inherent compliance,adaptability,and safe interactions within unstructured environments.Over the past decade(2015-2025),significant advancements have trans-formed their capabilities through novel designs inspired by biological systems,advanced modeling frameworks,sophisti-cated control strategies,and integration into diverse real-world applications.Recent innovations in multifunctional mate-rials and emerging actuation technologies have markedly expanded manipulator performance,reliability,and dexterity.Concurrently,developments in modeling have progressed from simplified geometric methods toward highly accurate physics-based and hybrid data-driven approaches,substantially improving real-time prediction and controllability.Coupled with these developments,adaptive and robust control strategies-including learning-based techniques-have enabled unprec-edented autonomy and precision in challenging application domains such as Minimally Invasive Surgery(MIS),precision agriculture,deep-sea exploration,disaster recovery,and space missions.Despite these remarkable strides,key challenges remain,notably regarding scalability,long-term material durability,robust integrated sensing,and standardized evaluation procedures.This review comprehensively synthesizes recent advances,critically evaluates state-of-the-art methodologies,and systematically identifies existing gaps to provide a clear roadmap and targeted research directions,guiding future developments toward the broader adoption and optimal utilization of soft robotic manipulators.
文摘With introduction of three heavy manipulations therapy at Dazhui （大椎 GV 14） for unclear enunciation case of acute cerebral infarction, acute attack case of chronic asthmatic bronchitis, amyotrophic lateral sclerosis case of motor neuron disease, ankylosing spondylitis case and chronic fatigue syndrome case, it is confirmed thatDazhui （大椎 GV 14） combined with three heavy manipulations therapy of blood-letting acupuncture, cupping and moxibust-ion has efficacy for external and endogenous wind, promoting and tonifying yang- qi, strengthening the body timely, removing wind and dampness, and relieving the pain and spasm in the clinical practice.
基金The National Natural Science Foundation of China under contract No.41201328the Science Foundation for Young Scholars of China’s State Oceanic Administration under contract No.2013415
文摘Mapping regional spatial patterns of coral reef geomorphology provides the primary information to understand the constructive processes in the reef ecosystem. However, this work is challenged by the pixel-based image classification method for its comparatively low accuracy. In this paper, an object-based image analysis(OBIA)method was presented to map intra-reef geomorphology of coral reefs in the Xisha Islands, China using Landsat 8satellite imagery. Following the work of the Millennium Coral Reef Mapping Project, a regional reef class hierarchy with ten geomorphic classes was first defined. Then, incorporating the hierarchical concept and integrating the spectral and additional spatial information such as context, shape and contextual relationships, a large-scale geomorphic map was produced by OBIA with accuracies generally more than 80%. Although the robustness of OBIA has been validated in the applications of coral reef mapping from individual reefs to reef system in this paper, further work is still required to improve its transferability.
基金Supported by the Fund of Capital Medical Development and Research(No.Ⅲ-11)the Subject Growth Fund of Guang'anmen Hospital,China Academy of Chinese Medical Sciences(No.81392)
文摘OBJECTIVE:To determine the clinical effect,treatment times,and rheoencephalogram changes in vertebral artery type cervical spondylosis patients treated with innovative Tuina manipulations.METHODS:One hundred and twenty six cervical spondylosis patients(vertebral artery type) were randomly divided into test and control groups.Patients in the test group were treated with innovative Tuina manipulations,while those in the control group were treated with the routine Tuina manipulations according to the textbook of Chinese Massage for Acupuncture and Moxibustion majors.The clinical effects,treatment times,clinical symptoms,and cerebral blood flow were measured.RESULTS:The response to the treatment was 100% in the test group and 88.71% in the control group.Patients in the test group required(7 ± 4) treatments before recovery,while those in the control group required(15 ± 7) treatments before recovery(P<0.05).The clinical symptoms exhibited greater improvement in the test group compared to the control group(P<0.05).There were no differences in cerebral blood flow between the two groups.CONCLUSION:Both innovative Tuina manipulations and routine Tuina manipulations produced satisfactory therapeutic results in vertebral artery type cervical spondylosis patients.However,the innovative manipulation was more effective in improving the functional symptoms,although there were no changes in the cerebral blood flow.
文摘This paper presents a new framework for object-based classification of high-resolution hyperspectral data.This multi-step framework is based on multi-resolution segmentation(MRS)and Random Forest classifier(RFC)algorithms.The first step is to determine of weights of the input features while using the object-based approach with MRS to processing such images.Given the high number of input features,an automatic method is needed for estimation of this parameter.Moreover,we used the Variable Importance(VI),one of the outputs of the RFC,to determine the importance of each image band.Then,based on this parameter and other required parameters,the image is segmented into some homogenous regions.Finally,the RFC is carried out based on the characteristics of segments for converting them into meaningful objects.The proposed method,as well as,the conventional pixel-based RFC and Support Vector Machine(SVM)method was applied to three different hyperspectral data-sets with various spectral and spatial characteristics.These data were acquired by the HyMap,the Airborne Prism Experiment(APEX),and the Compact Airborne Spectrographic Imager(CASI)hyperspectral sensors.The experimental results show that the proposed method is more consistent for land cover mapping in various areas.The overall classification accuracy(OA),obtained by the proposed method was 95.48,86.57,and 84.29%for the HyMap,the APEX,and the CASI datasets,respectively.Moreover,this method showed better efficiency in comparison to the spectralbased classifications because the OAs of the proposed method was 5.67 and 3.75%higher than the conventional RFC and SVM classifiers,respectively.
基金supported by the National Natural Science Foundation of China (31571590, 31972960)the earmarked fund for China Agriculture Research System of MOF and MARA (CARS-3-22)the Key Project of Crop Breeding of Sichuan Province, China (2021YFYZ0005)
文摘The source-sink ratio during grain filling is a critical factor that affects crop yield in wheat,and the main objective of this study was to determine the source-sink relations at both the canopy scale and the individual culm level under two nitrogen(N)levels at the post-jointing stage.Nine widely-used cultivars were chosen for analyzing source-sink relations in southwestern China;and three typical cultivars of different plant types were subjected to artificial manipulation of the grain-filling source-sink ratio to supplement crop growth measurements.A field experiment was conducted over two consecutive seasons under two N rates(N+,150 kg ha^(-1);N-,60 kg ha^(-1)),and three manipulations were imposed after anthesis:control(Ct),removal of flag and penultimate leaves(Lr)and removal of spikelets on one side of each spike(Sr).The results showed that the single grain weights in the three cultivars were significantly decreased by Lr and increased by Sr,which demonstrated that wheat grain yield potential seems more source-limited than sink-limited during grain filling,but the source-sink balance was obviously changed by climatic variations and N deficient environments.Grain yield was highly associated with sink capacity(SICA),grain number,biomass,SPAD values,and leaf area index during grain filling,indicating a higher degree of source limitation with an increase in sink capacity.Therefore,source limitation should be taken into account by breeders when SICA is increased,especially under non-limiting conditions.Chuanmai 104,a half-compact type with a mid-sized spike and a long narrow upper leaf,showed relatively better performance in source-sink relations.Since this cultivar showed the characteristics of a lower reduction in grain weight after Lr,a larger increase after Sr,and a lower reduction in post-anthesis dry matter accumulation,then the greater current photosynthesis during grain filling contributed to the grain after source and sink manipulation.
基金supported by the National Natural Science Foundation of China (81774413 and 82074553)。
文摘Objective: To analyze the effects of twirling reinforcing and reducing manipulations on protein expression in parietal cortex of spontaneously hypertensive rats(SHRs), and elucidate the main mechanisms and differences between two manipulations in hypertension treatment.Methods: Rats were randomly divided into the control, model, twirling reinforcing manipulation(TRFM),and twirling reducing manipulation(TRDM) groups. The control and model groups received catch and fixation stimulations once a day for 14 days. The TRFM and TRDM groups were intervened once a day for 20 min for 14 days. On days 0, 2, 6, 10, and 14 after acupuncture, rat systolic blood pressures(SBPs) were measured. Differential protein(DP) expression in the rat parietal cortices was detected. Thereafter, GO functional significance and KEGG pathway enrichment analyses were performed.Results: Compared with the model group, SBP of rats in the TRDM and TRFM groups decreased on days 6 and 10 of acupuncture, respectively(P=.009;P <.001). Moreover, SBP of the TRDM group was significantly lower than that of the TRFM group on days 10 and 14 of acupuncture(P=.015;P=.013).Compared with control group, 601 and 1040 DPs were up-and downregulated, respectively, in the model group. Compared with model group, 44 and 28 up-and downregulated DPs were expressed, respectively,in the TRFM group. Compared with model group, expression of 616 and 427 up-and downregulated DPs,respectively, was found in the TRDM group. After combining the results of GO and KEGG enrichment analyses, five and one pathways were found to be related to the central antihypertensive mechanism of the parietal cortex during twirling reducing and reinforcing manipulations, respectively.Conclusion: TRDM showed a more effective antihypertensive effect on SHRs than TRFM;this antihypertensive effect was related to the regulation of different proteins and their biological functions.
基金supported by the Strategic Priority Research Program of the Chinese Academy of Sciences (XDA28070503)the National Key Research and Development Program of China(2021YFD1500100)+2 种基金the Open Fund of State Laboratory of Information Engineering in Surveying,Mapping and Remote Sensing,Wuhan University (20R04)Land Observation Satellite Supporting Platform of National Civil Space Infrastructure Project(CASPLOS-CCSI)a PhD studentship ‘‘Deep Learning in massive area,multi-scale resolution remotely sensed imagery”(EAA7369),sponsored by Lancaster University and Ordnance Survey (the national mapping agency of Great Britain)。
文摘Accurate crop distribution mapping is required for crop yield prediction and field management. Due to rapid progress in remote sensing technology, fine spatial resolution(FSR) remotely sensed imagery now offers great opportunities for mapping crop types in great detail. However, within-class variance can hamper attempts to discriminate crop classes at fine resolutions. Multi-temporal FSR remotely sensed imagery provides a means of increasing crop classification from FSR imagery, although current methods do not exploit the available information fully. In this research, a novel Temporal Sequence Object-based Convolutional Neural Network(TS-OCNN) was proposed to classify agricultural crop type from FSR image time-series. An object-based CNN(OCNN) model was adopted in the TS-OCNN to classify images at the object level(i.e., segmented objects or crop parcels), thus, maintaining the precise boundary information of crop parcels. The combination of image time-series was first utilized as the input to the OCNN model to produce an ‘original’ or baseline classification. Then the single-date images were fed automatically into the deep learning model scene-by-scene in order of image acquisition date to increase successively the crop classification accuracy. By doing so, the joint information in the FSR multi-temporal observations and the unique individual information from the single-date images were exploited comprehensively for crop classification. The effectiveness of the proposed approach was investigated using multitemporal SAR and optical imagery, respectively, over two heterogeneous agricultural areas. The experimental results demonstrated that the newly proposed TS-OCNN approach consistently increased crop classification accuracy, and achieved the greatest accuracies(82.68% and 87.40%) in comparison with state-of-the-art benchmark methods, including the object-based CNN(OCNN)(81.63% and85.88%), object-based image analysis(OBIA)(78.21% and 84.83%), and standard pixel-wise CNN(79.18%and 82.90%). The proposed approach is the first known attempt to explore simultaneously the joint information from image time-series with the unique information from single-date images for crop classification using a deep learning framework. The TS-OCNN, therefore, represents a new approach for agricultural landscape classification from multi-temporal FSR imagery. Besides, it is readily generalizable to other landscapes(e.g., forest landscapes), with a wide application prospect.
基金Supported by the National Key Research and Development Program of China(No.2016YFC1402003)the CAS Earth Big Data Science Project(No.XDA19060303)the Innovation Project of the State Key Laboratory of Resources and Environmental Information System(No.O88RAA01YA)
文摘Efficient and accurate access to coastal land cover information is of great significance for marine disaster prevention and mitigation.Although the popular and common sensors of land resource satellites provide free and valuable images to map the land cover,coastal areas often encounter significant cloud cover,especially in tropical areas,which makes the classification in those areas non-ideal.To solve this problem,we proposed a framework of combining medium-resolution optical images and synthetic aperture radar(SAR)data with the recently popular object-based image analysis(OBIA)method and used the Landsat Operational Land Imager(OLI)and Phased Array type L-band Synthetic Aperture Radar(PALSAR)images acquired in Singapore in 2017 as a case study.We designed experiments to confirm two critical factors of this framework:one is the segmentation scale that determines the average object size,and the other is the classification feature.Accuracy assessments of the land cover indicated that the optimal segmentation scale was between 40 and 80,and the features of the combination of OLI and SAR resulted in higher accuracy than any individual features,especially in areas with cloud cover.Based on the land cover generated by this framework,we assessed the vulnerability of the marine disasters of Singapore in 2008 and 2017 and found that the high-vulnerability areas mainly located in the southeast and increased by 118.97 km2 over the past decade.To clarify the disaster response plan for different geographical environments,we classified risk based on altitude and distance from shore.The newly increased high-vulnerability regions within 4 km offshore and below 30 m above sea level are at high risk;these regions may need to focus on strengthening disaster prevention construction.This study serves as a typical example of using remote sensing techniques for the vulnerability assessment of marine disasters,especially those in cloudy coastal areas.
基金Under the auspices of Priority Academic Program Development of Jiangsu Higher Education Institutions,National Natural Science Foundation of China(No.41271438,41471316,41401440,41671389)
文摘Gully feature mapping is an indispensable prerequisite for the motioning and control of gully erosion which is a widespread natural hazard. The increasing availability of high-resolution Digital Elevation Model(DEM) and remote sensing imagery, combined with developed object-based methods enables automatic gully feature mapping. But still few studies have specifically focused on gully feature mapping on different scales. In this study, an object-based approach to two-level gully feature mapping, including gully-affected areas and bank gullies, was developed and tested on 1-m DEM and Worldview-3 imagery of a catchment in the Chinese Loess Plateau. The methodology includes a sequence of data preparation, image segmentation, metric calculation, and random forest based classification. The results of the two-level mapping were based on a random forest model after investigating the effects of feature selection and class-imbalance problem. Results show that the segmentation strategy adopted in this paper which considers the topographic information and optimal parameter combination can improve the segmentation results. The distribution of the gully-affected area is closely related to topographic information, however, the spectral features are more dominant for bank gully mapping. The highest overall accuracy of the gully-affected area mapping was 93.06% with four topographic features. The highest overall accuracy of bank gully mapping is 78.5% when all features are adopted. The proposed approach is a creditable option for hierarchical mapping of gully feature information, which is suitable for the application in hily Loess Plateau region.
基金The authors gratefully acknowledge financial support from the National Key R&D Program of China(2018YFE0118700)the Natural Science Foundation of China(NSFC No.62174119)+1 种基金Tianjin Applied Basic Research and Advanced Technology(17JCJQJC43600)the 111 Project(B07014).
文摘Contactless acoustic manipulation of micro/nanoscale particles has attracted considerable attention owing to its near independence of the physical and chemical properties of the targets,making it universally applicable to almost all biological systems.Thin-film bulk acoustic wave(BAW)resonators operating at gigahertz(GHz)frequencies have been demonstrated to generate localized high-speed microvortices through acoustic streaming effects.Benefitting from the strong drag forces of the high-speed vortices,BAW-enabled GHz acoustic streaming tweezers(AST)have been applied to the trapping and enrichment of particles ranging in size from micrometers to less than 100 nm.However,the behavior of particles in such 3D microvortex systems is still largely unknown.In this work,the particle behavior(trapping,enrichment,and separation)in GHz AST is studied by theoretical analyses,3D simulations,and microparticle tracking experiments.It is found that the particle motion in the vortices is determined mainly by the balance between the acoustic streaming drag force and the acoustic radiation force.This work can provide basic design principles for AST-based lab-on-a-chip systems for a variety of applications.
文摘The Baltic Sea is a brackish, mediterranean sea located in the middle latitudes of Europe. It is seasonally covered with ice. The ice covered areas during a typical winter are the Bothnian Bay, the Gulf of Finnland and the Gulf of Riga. Sea ice plays an important role in dynamic and thermodynamic processes and also has a strong impact on the heat budget of the sea. Also a large part of transport goes by sea, and there is a need to create ice charts to make the marine transport safe. Because of high cloudiness in winter season and small amount of light in the northern part of the Baltic Sea, radar data are the most important remote sensing source of sea ice information. The main goal of the following studies is classification of the Baltic sea ice cover using radar data. The ENVISAT ASAR （Advanced Synthetic Aperture Radar） acquires data in five different modes. In the following studies ASAR Wide Swath Mode data were used. The Wide Swath Mode, using the ScanSAR technique provides medium resolution images （150 m） over a swath of 405 kin, at HH or VV polarization. In following work data from February 13th, February 24th and April 6th, 2011, representing three different sea ice situations were chosen. OBIA （object-based image analysis） methods and texture parameters were used to create sea ice extent and sea ice concentration charts. Based on object-based methods, it can separate single sea ice floes within the ice pack and calculate more accurately sea ice concentration.
文摘The detection of impervious surface (IS) in heterogeneous urban areas is one of the most challenging tasks in urban remote sensing. One of the limitations in IS detection at the parcel level is the lack of sufficient training data. In this study, a generic model of spatial distribution of roof materials is considered to overcome this limitation. A generic model that is based on spectral, spatial and textural information which is extracted from available training data is proposed. An object-based approach is used to extract the information inherent in the image. Furthermore, linear discriminant analysis is used for dimensionality reduction and to discriminate between different spatial, spectral and textural attributes. The generic model is composed of a discriminant function based on linear combinations of the predictor variables that provide the best discrimination among the groups. The discriminate analysis result shows that of the 54 attributes extracted from the WorldView-2 image, only 13 attributes related to spatial, spectral and textural information are useful for discriminating different roof materials. Finally, this model is applied to different WorldView-2 images from different areas and proves that this model has good potential to predict roof materials from the WorldView-2 images without using training data.
基金The National Key Research and Development Program of China(No.2018YFC0407900)The National Natural Science Foundation of China(No.41774003)+2 种基金The Natural Science Foundation of Jiangsu Province(No.BK20171432)The Fundamental Research Funds for the Central Universities(No.2018B177142019B60714)。
文摘An object-based approach is proposed for land cover classification using optimal polarimetric parameters.The ability to identify targets is effectively enhanced by the integration of SAR and optical images.The innovation of the presented method can be summarized in the following two main points:①estimating polarimetric parameters(H-A-Alpha decomposition)through the optical image as a driver;②a multi-resolution segmentation based on the optical image only is deployed to refine classification results.The proposed method is verified by using Sentinel-1/2 datasets over the Bakersfield area,California.The results are compared against those from pixel-based SVM classification using the ground truth from the National Land Cover Database(NLCD).A detailed accuracy assessment complied with seven classes shows that the proposed method outperforms the conventional approach by around 10%,with an overall accuracy of 92.6%over regions with rich texture.
文摘Many researches have been performed comparing object-based classification (OBC) and pixel-based classification (PBC), particularly in classifying high-resolution satellite images. VNREDSat-1 is the first optical remote sensing satellite of Vietnam with resolution of 2.5 m (Panchromatic) and 10 m (Multispectral). The objective of this research is to compare two classification approaches using VNREDSat-1 image for mapping mangrove forest in Vien An Dong commune, Ngoc Hien district, Ca Mau province. ISODATA algorithm (in PBC method) and membership function classifier (in OBC method) were chosen to classify the same image. The results show that the overall accuracies of OBC and PBC are 73% and 62.16% respectively, and OBC solved the “salt and pepper” which is the main issue of PBC as well. Therefore, OBC is supposed to be the better approach to classify VNREDSat-1 for mapping mangrove forest in Ngoc Hien commune.
基金the Science and Technology Development Program of High Institutes of Liaoning Provincial Educational Department,No.2007T118
文摘Acupuncture and moxibustion therapy non-specifically raises the pain threshold, relieves regional muscular tension, improves local blood circulation, accelerates elimination of algogenic substances such as acid metabolites, and promotes neural regeneration and functional rehabilitation. However, the effects of acupuncture are synthetically influenced by multiple factors, which vary with acu-puncture point, intensity, and manipulation. The present study explored the analgesic effects and mechanisms of specific Sancai acupuncture manipulation for sciatica. Results revealed that Sancai acupuncture manipulation significantly reduced inflammatory factor interleukin-6 expression in the blood serum of rats with sciatica, exhibited anti-inflammatory effects and promoted rehabilitation of injured nerves. In addition, Sancai acupuncture manipulation exhibited superior curative effects over conventional acupuncture manipulation.
基金supported by the Beijing Natural Science Foundation(No.JQ20021)the National Natural Science Foundation of China(Nos.61922013,61421001 and U1833203)the Remote Sensing Monitoring Project of Geographical Elements in Shandong Yellow River Delta National Nature Reserve。
文摘With the deterioration of the environment,it is imperative to protect coastal wetlands.Using multi-source remote sensing data and object-based hierarchical classification to classify coastal wetlands is an effective method.The object-based hierarchical classification using remote sensing indices(OBH-RSI)for coastal wetland is proposed to achieve fine classification of coastal wetland.First,the original categories are divided into four groups according to the category characteristics.Second,the training and test maps of each group are extracted according to the remote sensing indices.Third,four groups are passed through the classifier in order.Finally,the results of the four groups are combined to get the final classification result map.The experimental results demonstrate that the overall accuracy,average accuracy and kappa coefficient of the proposed strategy are over 94%using the Yellow River Delta dataset.
