As one of the important wintering areas along the East Asian-Australasian Flyway,wetlands in the Yangtze River floodplain face threats from land-use changes,yet its effects on wintering waterbirds at the landscape lev...As one of the important wintering areas along the East Asian-Australasian Flyway,wetlands in the Yangtze River floodplain face threats from land-use changes,yet its effects on wintering waterbirds at the landscape level remain understudied,impeding conservation practice.Here,using survey data collected across 14 inland lakes in Jiangsu Province in 2022,we calculated wintering waterbirds diversity(taxonomic,functional,phylogenetic)and assembly patterns(MPD/MNTD of functional and phylogenetic).Then,we interpreted satellite imagery of lake areas and buffer zones(5 km),and partitioned them into three land-use and landscape index categories(anthropogenic,ecological,and lake landscape).Finally,we employed multiple linear regression and hierarchical partitioning to explain the influence of landscape scales on wintering waterbird communities.Our results showed that the diversity and assembly of regional wintering waterbird communities tended to be consistent across taxonomic,functional,and phylogenetic dimensions.The standardized diversity indices indicated that functional assembly of communities tends to be clustered at both local and regional scale.In contrast,the phylogenetic structure showed a predominantly overdispersed pattern in most lakes at the local scale,while neutral processes dominated at the regional scale.Modeling showed that selected variables explained waterbird diversity and assembly well.Lake fragmentation increased species evenness but reduced other diversity indices,while landscape evenness was negatively associated with functional and phylogenetic assembly.Among anthropogenic factors,aquaculture ponds and impervious surfaces reduced all diversity dimensions,whereas cropland connectivity enhanced phylogenetic diversity.These factors had consistent effects on community assembly.For ecological variables,grassland area enhanced functional and phylogenetic diversity but led to more clustered functional assembly.Overall,maintaining the integrity and connectivity of lakes and their surrounding landscapes is essential for sustaining waterbird diversity and guiding wetland restoration.展开更多
AIM:To investigate the clinical features and prognosis of patients with orbital inflammatory myofibroblastic tumor(IMT).METHODS:This retrospective study collected clinical data from 22 patients diagnosed with orbital ...AIM:To investigate the clinical features and prognosis of patients with orbital inflammatory myofibroblastic tumor(IMT).METHODS:This retrospective study collected clinical data from 22 patients diagnosed with orbital IMT based on histopathological examination.The patients were followed up to assess their prognosis.Clinical data from patients,including age,gender,course of disease,past medical history,primary symptoms,ophthalmologic examination findings,general condition,as well as imaging,laboratory,histopathological,and immunohistochemical results from digital records were collected.Orbital magnetic resonance imaging(MRI)and(or)computed tomography(CT)scans were performed to assess bone destruction of the mass,invasion of surrounding tissues,and any inflammatory changes in periorbital areas.RESULTS:The mean age of patients with orbital IMT was 28.24±3.30y,with a male-to-female ratio of 1.2:1.Main clinical manifestations were proptosis,blurred vision,palpable mass,and pain.Bone destruction and surrounding tissue invasion occurred in 72.73%and 54.55%of cases,respectively.Inflammatory changes in the periorbital site were observed in 77.27%of the patients.Hematoxylin and eosin staining showed proliferation of fibroblasts and myofibroblasts,accompanied by infiltration of lymphocytes and plasma cells.Immunohistochemical staining revealed that smooth muscle actin(SMA)and vimentin were positive in 100%of cases,while anaplastic lymphoma kinase(ALK)showed positivity in 47.37%.The recurrence rate of orbital IMT was 27.27%,and sarcomatous degeneration could occur.There were no significant correlations between recurrence and factors such as age,gender,laterality,duration of the disease,periorbital tissue invasion,bone destruction,periorbital inflammation,tumor size,fever,leukocytosis,or treatment(P>0.05).However,lymphadenopathy and a Ki-67 index of 10%or higher may be risk factors for recurrence(P=0.046;P=0.023).CONCLUSION:Orbital IMT is a locally invasive disease that may recur or lead to sarcomatoid degeneration,primarily affecting young and middle-aged patients.The presence of lymphadenopathy and a Ki-67 index of 10%or higher may signify a poor prognosis.展开更多
BACKGROUND SMARCB1/INI1-deficient pancreatic undifferentiated rhabdoid carcinoma is a highly aggressive tumor,and spontaneous splenic rupture(SSR)as its presenting manifestation is rarely reported among pancreatic mal...BACKGROUND SMARCB1/INI1-deficient pancreatic undifferentiated rhabdoid carcinoma is a highly aggressive tumor,and spontaneous splenic rupture(SSR)as its presenting manifestation is rarely reported among pancreatic malignancies.CASE SUMMARY We herein report a rare case of a 59-year-old female who presented with acute left upper quadrant abdominal pain without any history of trauma.Abdominal imaging demonstrated a heterogeneous splenic lesion with hemoperitoneum,raising clinical suspicion of SSR.Emergency laparotomy revealed a pancreatic tumor invading the spleen and left kidney,with associated splenic rupture and dense adhesions,necessitating en bloc resection of the distal pancreas,spleen,and left kidney.Histopathology revealed a biphasic malignancy composed of moderately differentiated pancreatic ductal adenocarcinoma and an undifferentiated carcinoma with rhabdoid morphology and loss of SMARCB1 expression.Immunohistochemical analysis confirmed complete loss of SMARCB1/INI1 in the undifferentiated component,along with a high Ki-67 index(approximately 80%)and CD10 positivity.The ductal adenocarcinoma component retained SMARCB1/INI1 expression and was positive for CK7 and CK-pan.Transitional zones between the two tumor components suggested progressive dedifferentiation and underlying genomic instability.The patient received adjuvant chemotherapy with gemcitabine and nab-paclitaxel and maintained a satisfactory quality of life at the 6-month follow-up.CONCLUSION This study reports a rare case of SMARCB1/INI1-deficient undifferentiated rhabdoid carcinoma of the pancreas combined with ductal adenocarcinoma,presenting as SSR-an exceptionally uncommon initial manifestation of pancreatic malignancy.展开更多
The primary task of top-down assembly design is to define a product抯 detailed physical description satisfying its functional requirements identified during the functional design phase. The implementation of this desi...The primary task of top-down assembly design is to define a product抯 detailed physical description satisfying its functional requirements identified during the functional design phase. The implementation of this design process requires two things, that is, product functional representation and a general assembly model. Product functions are not only the formulation of a customer抯 needs, but also the input data of assembly design. A general assembly model is to support the evolving process of the elaboration of a product structure. The assembly feature of extended concept is taken as a functional carrier, which is a generic relation among assembly-modeled entities. The model of assembly features describes the link between product functions and form features of parts. On the basis of this link, the propagation of design modifications is discussed so as to preserve the functionality and the coherence of the assembly model. The formal model of assembly design process describes the top-down process of creating an assembly model. This formal model is represented by the combination of assembly feature operations, the assembly model and the evaluation process. A design case study is conducted to verify the applicability of the presented approaches.展开更多
In the article“A Lightweight Approach for Skin Lesion Detection through Optimal Features Fusion”by Khadija Manzoor,Fiaz Majeed,Ansar Siddique,Talha Meraj,Hafiz Tayyab Rauf,Mohammed A.El-Meligy,Mohamed Sharaf,Abd Ela...In the article“A Lightweight Approach for Skin Lesion Detection through Optimal Features Fusion”by Khadija Manzoor,Fiaz Majeed,Ansar Siddique,Talha Meraj,Hafiz Tayyab Rauf,Mohammed A.El-Meligy,Mohamed Sharaf,Abd Elatty E.Abd Elgawad Computers,Materials&Continua,2022,Vol.70,No.1,pp.1617–1630.DOI:10.32604/cmc.2022.018621,URL:https://www.techscience.com/cmc/v70n1/44361,there was an error regarding the affiliation for the author Hafiz Tayyab Rauf.Instead of“Centre for Smart Systems,AI and Cybersecurity,Staffordshire University,Stoke-on-Trent,UK”,the affiliation should be“Independent Researcher,Bradford,BD80HS,UK”.展开更多
Juglans sigillata is an economically valuable nut crop renowned for its nutritional richness,including essential nutrients,antioxidants,and healthy fats,which boost human cardial,brain and gut health.Despite its impor...Juglans sigillata is an economically valuable nut crop renowned for its nutritional richness,including essential nutrients,antioxidants,and healthy fats,which boost human cardial,brain and gut health.Despite its importance,the lack of a complete genome assembly has been a stumbling block in its biological breeding process.Therefore,we generated deep coverage ultralong Oxford Nanopore Technology(ONT)and PacBio HiFi reads to construct a telomere-to-telomere(T2T)genome assembly.The final assembly spans 537.27 Mb with no gaps,demonstrating a remarkable completeness of 98.1%.We utilized a combination of transcriptome data and homologous proteins to annotate the genome,identifying 36018 protein-coding genes.Furthermore,we profiled global cytosine DNA methylations using ONT sequencing data.Global methylome analysis revealed high methylation levels in transposable element(TE)-rich chromosomal regions juxtaposed with comparatively lower methylation in gene-rich areas.By integrating a detailed multi-omics data analysis,we obtained valuable insights into the mechanism underlying endopleura coloration.This investigation led to the identification of eight candidate genes(e.g.ANR)involved in anthocyanin biosynthesis pathways,which are crucial for the development of color in plants.The comprehensive genome assembly and the understanding of the genetic basis of important traits like endopleura coloration will open avenues for more efficient breeding programs and improved crop quality.展开更多
The application of photocatalytic technology in algae killing is limited by the non-floatability and difficulty in recycling of the photocatalysts.Loading photocatalyst on magnetic or floatable carriers is the most po...The application of photocatalytic technology in algae killing is limited by the non-floatability and difficulty in recycling of the photocatalysts.Loading photocatalyst on magnetic or floatable carriers is the most popular method for overcoming the above inadequacies.In this work,a CdZnS/TiO_(2) membrane photocatalyst with adjustable suspended depth(include floating)and flexible assembly is designed,which is less prone to dislodgement due to in situ synthesis and has a wider range of applicability than previously reported photocatalysts.The photocatalytic removal of Microcystis aeruginosa revealed that the suspended depth and distribution format of the CdZnS/TiO_(2) membrane photocatalysts have striking effects on the photocatalytic removal performance of Microcystis aeruginosa,the photocatalytic removal efficiency of CdZnS/TiO_(2)-2 membrane photocatalysts for Microcystis aeruginosa could reach to 98.6%in 60 min when the photocatalysts assembled in the form of 3×3 arrays suspended at a depth of 2 cm from the liquid surface.A tiny amount of TiO_(2) loading allows the formation of Z-Scheme heterojunction,resulting in accelerating the separation efficiency of photogenerated carriers,preserving the photogenerated electrons and holes with stronger reduction and oxidation ability and inhabiting the photo-corrosion of CdZnS.展开更多
Membrane electrode assembly(MEA)is widely considered to be the most promising type of electrolyzer for the practical application of electrochemical CO_(2) reduction reaction(CO_(2)RR).In MEAs,a square-shaped cross-sec...Membrane electrode assembly(MEA)is widely considered to be the most promising type of electrolyzer for the practical application of electrochemical CO_(2) reduction reaction(CO_(2)RR).In MEAs,a square-shaped cross-section in the flow channel is normally adopted,the configuration optimization of which could potentially enhance the performance of the electrolyzer.This paper describes the numerical simulation study on the impact of the flow-channel cross-section shapes in the MEA electrolyzer for CO_(2)RR.The results show that wide flow channels with low heights are beneficial to the CO_(2)RR by providing a uniform flow field of CO_(2),especially at high current densities.Moreover,the larger the electrolyzer,the more significant the effect is.This study provides a theoretical basis for the design of high-performance MEA electrolyzers for CO_(2)RR.展开更多
BACKGROUND Pancreatic cancer remains one of the most lethal malignancies worldwide,with a poor prognosis often attributed to late diagnosis.Understanding the correlation between pathological type and imaging features ...BACKGROUND Pancreatic cancer remains one of the most lethal malignancies worldwide,with a poor prognosis often attributed to late diagnosis.Understanding the correlation between pathological type and imaging features is crucial for early detection and appropriate treatment planning.AIM To retrospectively analyze the relationship between different pathological types of pancreatic cancer and their corresponding imaging features.METHODS We retrospectively analyzed the data of 500 patients diagnosed with pancreatic cancer between January 2010 and December 2020 at our institution.Pathological types were determined by histopathological examination of the surgical spe-cimens or biopsy samples.The imaging features were assessed using computed tomography,magnetic resonance imaging,and endoscopic ultrasound.Statistical analyses were performed to identify significant associations between pathological types and specific imaging characteristics.RESULTS There were 320(64%)cases of pancreatic ductal adenocarcinoma,75(15%)of intraductal papillary mucinous neoplasms,50(10%)of neuroendocrine tumors,and 55(11%)of other rare types.Distinct imaging features were identified in each pathological type.Pancreatic ductal adenocarcinoma typically presents as a hypodense mass with poorly defined borders on computed tomography,whereas intraductal papillary mucinous neoplasms present as characteristic cystic lesions with mural nodules.Neuroendocrine tumors often appear as hypervascular lesions in contrast-enhanced imaging.Statistical analysis revealed significant correlations between specific imaging features and pathological types(P<0.001).CONCLUSION This study demonstrated a strong association between the pathological types of pancreatic cancer and imaging features.These findings can enhance the accuracy of noninvasive diagnosis and guide personalized treatment approaches.展开更多
Despite the gradual transformation of traditional manufacturing by the Human-Robot Collaboration Assembly(HRCA),challenges remain in the robot’s ability to understand and predict human assembly intentions.This study ...Despite the gradual transformation of traditional manufacturing by the Human-Robot Collaboration Assembly(HRCA),challenges remain in the robot’s ability to understand and predict human assembly intentions.This study aims to enhance the robot’s comprehension and prediction capabilities of operator assembly intentions by capturing and analyzing operator behavior and movements.We propose a video feature extraction method based on the Temporal Shift Module Network(TSM-ResNet50)to extract spatiotemporal features from assembly videos and differentiate various assembly actions using feature differences between video frames.Furthermore,we construct an action recognition and segmentation model based on the Refined-Multi-Scale Temporal Convolutional Network(Refined-MS-TCN)to identify assembly action intervals and accurately acquire action categories.Experiments on our self-built reducer assembly action dataset demonstrate that our network can classify assembly actions frame by frame,achieving an accuracy rate of 83%.Additionally,we develop a HiddenMarkovModel(HMM)integrated with assembly task constraints to predict operator assembly intentions based on the probability transition matrix and assembly task constraints.The experimental results show that our method for predicting operator assembly intentions can achieve an accuracy of 90.6%,which is a 13.3%improvement over the HMM without task constraints.展开更多
During Donald Trump’s first term,the“Trump Shock”brought world politics into an era of uncertainties and pulled the transatlantic alliance down to its lowest point in history.The Trump 2.0 tsunami brewed by the 202...During Donald Trump’s first term,the“Trump Shock”brought world politics into an era of uncertainties and pulled the transatlantic alliance down to its lowest point in history.The Trump 2.0 tsunami brewed by the 2024 presidential election of the United States has plunged the U.S.-Europe relations into more gloomy waters,ushering in a more complex and turbulent period of adjustment.展开更多
The fusion of infrared and visible images should emphasize the salient targets in the infrared image while preserving the textural details of the visible images.To meet these requirements,an autoencoder-based method f...The fusion of infrared and visible images should emphasize the salient targets in the infrared image while preserving the textural details of the visible images.To meet these requirements,an autoencoder-based method for infrared and visible image fusion is proposed.The encoder designed according to the optimization objective consists of a base encoder and a detail encoder,which is used to extract low-frequency and high-frequency information from the image.This extraction may lead to some information not being captured,so a compensation encoder is proposed to supplement the missing information.Multi-scale decomposition is also employed to extract image features more comprehensively.The decoder combines low-frequency,high-frequency and supplementary information to obtain multi-scale features.Subsequently,the attention strategy and fusion module are introduced to perform multi-scale fusion for image reconstruction.Experimental results on three datasets show that the fused images generated by this network effectively retain salient targets while being more consistent with human visual perception.展开更多
A unitized regenerative fuel cell(URFC)is a device that may function reversibly as either a fuel cell(FC)or water elec-trolysis(WE).An important component of this device is the Membrane electrode assembly(MEA).Therefo...A unitized regenerative fuel cell(URFC)is a device that may function reversibly as either a fuel cell(FC)or water elec-trolysis(WE).An important component of this device is the Membrane electrode assembly(MEA).Therefore,this study aimed to compare the performance outcomes of MEA using electrodes with single and three catalyst layers.This study measured Electrochemical Surface Area(ECSA),Electrochemical Impedance Spectroscopy(EIS),X-ray Diffraction analysis(XRD),and X-ray Fluorescence(XRF).Furthermore,the round-trip efficiency(RTE)of the MEA,as w ell as the performance in FC and WE mode,was measured.In comparison,The ECSA values of Pt-Ru/C and Pt/C with three catalyst layers were higher than the single catalyst layer.This result was supported by electrode characterization data for XRD and XRF.The respective electrical conductivity values of Pt-Ru/C and Pt/C with three catalyst layers are also higher than the single cata-lyst layer,and the performance of URFC using MEA with three catalyst layers has the highest value of RTE among the MEA performances of URFC,which is 100%at a current density of 4 mA·cm-2.展开更多
Assembly precision greatly influences the performance of complex high-end equipment.The traditional industrial assembly process and deviation transfer are implicit and uncertain,causing problems like poor component fi...Assembly precision greatly influences the performance of complex high-end equipment.The traditional industrial assembly process and deviation transfer are implicit and uncertain,causing problems like poor component fit and hard-to-trace assembly stress concentration.Assemblers can only check whether the dimensional tolerance of the component design is exceeded step by step in combination with prior knowledge.Inversion in industrial assembly optimizes assembly and design by comparing real and theoretical results and doing inversion analysis to reduce assembly deviation.The digital twin(DT)technology visualizes and predicts the assembly process by mapping real and virtual model parameters and states simultaneously,expanding parameter range for inversion analysis and improving inversion result accuracy.Problems in improving industrial assembly precision and the significance and research status of DT-driven parametric inversion of assembly tools,processes and object precision are summarized.It analyzes vital technologies for assembly precision inversion such as multi-attribute assembly process parameter sensing,virtual modeling of high-fidelity assembly systems,twin synchronization of assembly process data models,multi-physical field simulation,and performance twin model construction of the assembly process.Combined with human-cyber-physical system,augmented reality,and generative intelligence,the outlook of DT-driven assembly precision inversion is proposed,providing support for DT's use in industrial assembly and precision improvement.展开更多
As the demands for assembly quality and efficiency increase,robot-assisted assembly applications are becoming more widespread.Peg-in-hole assembly,as a typical form of assembly,has been widely researched by scholars.C...As the demands for assembly quality and efficiency increase,robot-assisted assembly applications are becoming more widespread.Peg-in-hole assembly,as a typical form of assembly,has been widely researched by scholars.Currently,robotic peg-in-hole assembly faces challenges such as complex analysis of part contact forces,difficulties in task modeling,and the failure of traditional strategies.Simply controlling the position of the robot's end effector cannot achieve high precision,high efficiency peg-in-hole assembly.Flexible assembly,especially intelligent flexible assembly,is becoming the future development trend.So there is a lack of comprehensive reviews on robotic flexible peg-in-hole assembly.This paper first outlines the basic components of peg-in-hole assembly and summarizes the two basic operational processes of peg-in-hole assembly,along with their related theoretical foundations.We then review and analyze the research on passive compliant assembly,active compliant assembly,and intelligent flexible assembly.Finally,it presents an outlook on the future development directions of robotic peg-in-hole assembly.展开更多
To address the challenges of insufficient visualization in the industrial robot assembly operation system and the limitation of visualizing only geometric attributes of physical properties,a method is proposed for con...To address the challenges of insufficient visualization in the industrial robot assembly operation system and the limitation of visualizing only geometric attributes of physical properties,a method is proposed for constructing an industrial robot assembly system based on virtual reality technology.Focusing on the shaft hole assembly,the mechanical characteristics of the industrial robot shaft hole assembly process are analyzed and a dynamic model is established for shaft hole assembly operations.The key elements of virtual assembly operations for industrial robots are summarized and a five-dimensional model is proposed for industrial robot virtual operations.Utilizing the Unity3D engine based on the 5-D model for industrial robot virtual operations,an industrial robot shaft hole assembly system is developed.This system enables virtual assembly operations,displays physical attributes,and provides valuable references for the research of virtual systems.展开更多
Smart contracts are widely used on the blockchain to implement complex transactions,such as decentralized applications on Ethereum.Effective vulnerability detection of large-scale smart contracts is critical,as attack...Smart contracts are widely used on the blockchain to implement complex transactions,such as decentralized applications on Ethereum.Effective vulnerability detection of large-scale smart contracts is critical,as attacks on smart contracts often cause huge economic losses.Since it is difficult to repair and update smart contracts,it is necessary to find the vulnerabilities before they are deployed.However,code analysis,which requires traversal paths,and learning methods,which require many features to be trained,are too time-consuming to detect large-scale on-chain contracts.Learning-based methods will obtain detection models from a feature space compared to code analysis methods such as symbol execution.But the existing features lack the interpretability of the detection results and training model,even worse,the large-scale feature space also affects the efficiency of detection.This paper focuses on improving the detection efficiency by reducing the dimension of the features,combined with expert knowledge.In this paper,a feature extraction model Block-gram is proposed to form low-dimensional knowledge-based features from bytecode.First,the metadata is separated and the runtime code is converted into a sequence of opcodes,which are divided into segments based on some instructions(jumps,etc.).Then,scalable Block-gram features,including 4-dimensional block features and 8-dimensional attribute features,are mined for the learning-based model training.Finally,feature contributions are calculated from SHAP values to measure the relationship between our features and the results of the detection model.In addition,six types of vulnerability labels are made on a dataset containing 33,885 contracts,and these knowledge-based features are evaluated using seven state-of-the-art learning algorithms,which show that the average detection latency speeds up 25×to 650×,compared with the features extracted by N-gram,and also can enhance the interpretability of the detection model.展开更多
Molecular recognition of fullerene using various host compounds is well-known in literature.But most studies focus on host-vip complexation in solution using host compounds with a single binding cavity.Herein,we rep...Molecular recognition of fullerene using various host compounds is well-known in literature.But most studies focus on host-vip complexation in solution using host compounds with a single binding cavity.Herein,we report a series of highly preorganized janusarene derivatives with homoditopic binding sites.These novel janusarenes can bind and align various fullerenes such as C_(60),C_(70),C_(84),and Gd@C_(82)in a highly efficient manner.Robust shape complementary association and assembly are observed in solution,in the bulk solid state,in the liquid crystalline state,or on surface,and the assembled structures are characterized by nuclear magnetic resonance(NMR)titration,X-ray diffraction,polarized optical microscopy,and scanning tunneling microscopy.展开更多
Biometric characteristics are playing a vital role in security for the last few years.Human gait classification in video sequences is an important biometrics attribute and is used for security purposes.A new framework...Biometric characteristics are playing a vital role in security for the last few years.Human gait classification in video sequences is an important biometrics attribute and is used for security purposes.A new framework for human gait classification in video sequences using deep learning(DL)fusion assisted and posterior probability-based moth flames optimization(MFO)is proposed.In the first step,the video frames are resized and finetuned by two pre-trained lightweight DL models,EfficientNetB0 and MobileNetV2.Both models are selected based on the top-5 accuracy and less number of parameters.Later,both models are trained through deep transfer learning and extracted deep features fused using a voting scheme.In the last step,the authors develop a posterior probabilitybased MFO feature selection algorithm to select the best features.The selected features are classified using several supervised learning methods.The CASIA-B publicly available dataset has been employed for the experimental process.On this dataset,the authors selected six angles such as 0°,18°,90°,108°,162°,and 180°and obtained an average accuracy of 96.9%,95.7%,86.8%,90.0%,95.1%,and 99.7%.Results demonstrate comparable improvement in accuracy and significantly minimize the computational time with recent state-of-the-art techniques.展开更多
Due to the limitations of existing imaging hardware, obtaining high-resolution hyperspectral images is challenging. Hyperspectral image super-resolution(HSI SR) has been a very attractive research topic in computer vi...Due to the limitations of existing imaging hardware, obtaining high-resolution hyperspectral images is challenging. Hyperspectral image super-resolution(HSI SR) has been a very attractive research topic in computer vision, attracting the attention of many researchers. However, most HSI SR methods focus on the tradeoff between spatial resolution and spectral information, and cannot guarantee the efficient extraction of image information. In this paper, a multidimensional features network(MFNet) for HSI SR is proposed, which simultaneously learns and fuses the spatial,spectral, and frequency multidimensional features of HSI. Spatial features contain rich local details,spectral features contain the information and correlation between spectral bands, and frequency feature can reflect the global information of the image and can be used to obtain the global context of HSI. The fusion of the three features can better guide image super-resolution, to obtain higher-quality high-resolution hyperspectral images. In MFNet, we use the frequency feature extraction module(FFEM) to extract the frequency feature. On this basis, a multidimensional features extraction module(MFEM) is designed to learn and fuse multidimensional features. In addition, experimental results on two public datasets demonstrate that MFNet achieves state-of-the-art performance.展开更多
基金funded by the National Natural Science Foundation of China(Grant No.42271116)。
文摘As one of the important wintering areas along the East Asian-Australasian Flyway,wetlands in the Yangtze River floodplain face threats from land-use changes,yet its effects on wintering waterbirds at the landscape level remain understudied,impeding conservation practice.Here,using survey data collected across 14 inland lakes in Jiangsu Province in 2022,we calculated wintering waterbirds diversity(taxonomic,functional,phylogenetic)and assembly patterns(MPD/MNTD of functional and phylogenetic).Then,we interpreted satellite imagery of lake areas and buffer zones(5 km),and partitioned them into three land-use and landscape index categories(anthropogenic,ecological,and lake landscape).Finally,we employed multiple linear regression and hierarchical partitioning to explain the influence of landscape scales on wintering waterbird communities.Our results showed that the diversity and assembly of regional wintering waterbird communities tended to be consistent across taxonomic,functional,and phylogenetic dimensions.The standardized diversity indices indicated that functional assembly of communities tends to be clustered at both local and regional scale.In contrast,the phylogenetic structure showed a predominantly overdispersed pattern in most lakes at the local scale,while neutral processes dominated at the regional scale.Modeling showed that selected variables explained waterbird diversity and assembly well.Lake fragmentation increased species evenness but reduced other diversity indices,while landscape evenness was negatively associated with functional and phylogenetic assembly.Among anthropogenic factors,aquaculture ponds and impervious surfaces reduced all diversity dimensions,whereas cropland connectivity enhanced phylogenetic diversity.These factors had consistent effects on community assembly.For ecological variables,grassland area enhanced functional and phylogenetic diversity but led to more clustered functional assembly.Overall,maintaining the integrity and connectivity of lakes and their surrounding landscapes is essential for sustaining waterbird diversity and guiding wetland restoration.
基金Supported by the National Key R&D Program of China(No.2023YFC2410203)Beijing Hospitals Authority Clinical Medicine Development of Special Funding Support(No.ZLRK202503).
文摘AIM:To investigate the clinical features and prognosis of patients with orbital inflammatory myofibroblastic tumor(IMT).METHODS:This retrospective study collected clinical data from 22 patients diagnosed with orbital IMT based on histopathological examination.The patients were followed up to assess their prognosis.Clinical data from patients,including age,gender,course of disease,past medical history,primary symptoms,ophthalmologic examination findings,general condition,as well as imaging,laboratory,histopathological,and immunohistochemical results from digital records were collected.Orbital magnetic resonance imaging(MRI)and(or)computed tomography(CT)scans were performed to assess bone destruction of the mass,invasion of surrounding tissues,and any inflammatory changes in periorbital areas.RESULTS:The mean age of patients with orbital IMT was 28.24±3.30y,with a male-to-female ratio of 1.2:1.Main clinical manifestations were proptosis,blurred vision,palpable mass,and pain.Bone destruction and surrounding tissue invasion occurred in 72.73%and 54.55%of cases,respectively.Inflammatory changes in the periorbital site were observed in 77.27%of the patients.Hematoxylin and eosin staining showed proliferation of fibroblasts and myofibroblasts,accompanied by infiltration of lymphocytes and plasma cells.Immunohistochemical staining revealed that smooth muscle actin(SMA)and vimentin were positive in 100%of cases,while anaplastic lymphoma kinase(ALK)showed positivity in 47.37%.The recurrence rate of orbital IMT was 27.27%,and sarcomatous degeneration could occur.There were no significant correlations between recurrence and factors such as age,gender,laterality,duration of the disease,periorbital tissue invasion,bone destruction,periorbital inflammation,tumor size,fever,leukocytosis,or treatment(P>0.05).However,lymphadenopathy and a Ki-67 index of 10%or higher may be risk factors for recurrence(P=0.046;P=0.023).CONCLUSION:Orbital IMT is a locally invasive disease that may recur or lead to sarcomatoid degeneration,primarily affecting young and middle-aged patients.The presence of lymphadenopathy and a Ki-67 index of 10%or higher may signify a poor prognosis.
文摘BACKGROUND SMARCB1/INI1-deficient pancreatic undifferentiated rhabdoid carcinoma is a highly aggressive tumor,and spontaneous splenic rupture(SSR)as its presenting manifestation is rarely reported among pancreatic malignancies.CASE SUMMARY We herein report a rare case of a 59-year-old female who presented with acute left upper quadrant abdominal pain without any history of trauma.Abdominal imaging demonstrated a heterogeneous splenic lesion with hemoperitoneum,raising clinical suspicion of SSR.Emergency laparotomy revealed a pancreatic tumor invading the spleen and left kidney,with associated splenic rupture and dense adhesions,necessitating en bloc resection of the distal pancreas,spleen,and left kidney.Histopathology revealed a biphasic malignancy composed of moderately differentiated pancreatic ductal adenocarcinoma and an undifferentiated carcinoma with rhabdoid morphology and loss of SMARCB1 expression.Immunohistochemical analysis confirmed complete loss of SMARCB1/INI1 in the undifferentiated component,along with a high Ki-67 index(approximately 80%)and CD10 positivity.The ductal adenocarcinoma component retained SMARCB1/INI1 expression and was positive for CK7 and CK-pan.Transitional zones between the two tumor components suggested progressive dedifferentiation and underlying genomic instability.The patient received adjuvant chemotherapy with gemcitabine and nab-paclitaxel and maintained a satisfactory quality of life at the 6-month follow-up.CONCLUSION This study reports a rare case of SMARCB1/INI1-deficient undifferentiated rhabdoid carcinoma of the pancreas combined with ductal adenocarcinoma,presenting as SSR-an exceptionally uncommon initial manifestation of pancreatic malignancy.
基金This is a Sino-France project(1998-2001)supported by French Ministry of Education.
文摘The primary task of top-down assembly design is to define a product抯 detailed physical description satisfying its functional requirements identified during the functional design phase. The implementation of this design process requires two things, that is, product functional representation and a general assembly model. Product functions are not only the formulation of a customer抯 needs, but also the input data of assembly design. A general assembly model is to support the evolving process of the elaboration of a product structure. The assembly feature of extended concept is taken as a functional carrier, which is a generic relation among assembly-modeled entities. The model of assembly features describes the link between product functions and form features of parts. On the basis of this link, the propagation of design modifications is discussed so as to preserve the functionality and the coherence of the assembly model. The formal model of assembly design process describes the top-down process of creating an assembly model. This formal model is represented by the combination of assembly feature operations, the assembly model and the evaluation process. A design case study is conducted to verify the applicability of the presented approaches.
文摘In the article“A Lightweight Approach for Skin Lesion Detection through Optimal Features Fusion”by Khadija Manzoor,Fiaz Majeed,Ansar Siddique,Talha Meraj,Hafiz Tayyab Rauf,Mohammed A.El-Meligy,Mohamed Sharaf,Abd Elatty E.Abd Elgawad Computers,Materials&Continua,2022,Vol.70,No.1,pp.1617–1630.DOI:10.32604/cmc.2022.018621,URL:https://www.techscience.com/cmc/v70n1/44361,there was an error regarding the affiliation for the author Hafiz Tayyab Rauf.Instead of“Centre for Smart Systems,AI and Cybersecurity,Staffordshire University,Stoke-on-Trent,UK”,the affiliation should be“Independent Researcher,Bradford,BD80HS,UK”.
基金supported by the Yunnan Seed Laboratory,China(202205AR070001-15)the National Natural Science Foundation of China,China(Grant No.32160697)。
文摘Juglans sigillata is an economically valuable nut crop renowned for its nutritional richness,including essential nutrients,antioxidants,and healthy fats,which boost human cardial,brain and gut health.Despite its importance,the lack of a complete genome assembly has been a stumbling block in its biological breeding process.Therefore,we generated deep coverage ultralong Oxford Nanopore Technology(ONT)and PacBio HiFi reads to construct a telomere-to-telomere(T2T)genome assembly.The final assembly spans 537.27 Mb with no gaps,demonstrating a remarkable completeness of 98.1%.We utilized a combination of transcriptome data and homologous proteins to annotate the genome,identifying 36018 protein-coding genes.Furthermore,we profiled global cytosine DNA methylations using ONT sequencing data.Global methylome analysis revealed high methylation levels in transposable element(TE)-rich chromosomal regions juxtaposed with comparatively lower methylation in gene-rich areas.By integrating a detailed multi-omics data analysis,we obtained valuable insights into the mechanism underlying endopleura coloration.This investigation led to the identification of eight candidate genes(e.g.ANR)involved in anthocyanin biosynthesis pathways,which are crucial for the development of color in plants.The comprehensive genome assembly and the understanding of the genetic basis of important traits like endopleura coloration will open avenues for more efficient breeding programs and improved crop quality.
基金financially supported by the Natural Science Foundation of ShanDong(Nos.ZR2023QD152 and ZR2021MD002).
文摘The application of photocatalytic technology in algae killing is limited by the non-floatability and difficulty in recycling of the photocatalysts.Loading photocatalyst on magnetic or floatable carriers is the most popular method for overcoming the above inadequacies.In this work,a CdZnS/TiO_(2) membrane photocatalyst with adjustable suspended depth(include floating)and flexible assembly is designed,which is less prone to dislodgement due to in situ synthesis and has a wider range of applicability than previously reported photocatalysts.The photocatalytic removal of Microcystis aeruginosa revealed that the suspended depth and distribution format of the CdZnS/TiO_(2) membrane photocatalysts have striking effects on the photocatalytic removal performance of Microcystis aeruginosa,the photocatalytic removal efficiency of CdZnS/TiO_(2)-2 membrane photocatalysts for Microcystis aeruginosa could reach to 98.6%in 60 min when the photocatalysts assembled in the form of 3×3 arrays suspended at a depth of 2 cm from the liquid surface.A tiny amount of TiO_(2) loading allows the formation of Z-Scheme heterojunction,resulting in accelerating the separation efficiency of photogenerated carriers,preserving the photogenerated electrons and holes with stronger reduction and oxidation ability and inhabiting the photo-corrosion of CdZnS.
基金the National Key R&D Program of China(No.2021YFA1501503)the National Natural Science Foundation of China(Nos.22250008,22121004,22108197)+3 种基金the Haihe Laboratory of Sustainable Chemical Transformations(No.CYZC202107)the Natural Science Foundation of Tianjin City(No.21JCZXJC00060)the Program of Introducing Talents of Discipline to Universities(No.BP0618007)the Xplorer Prize for financial support。
文摘Membrane electrode assembly(MEA)is widely considered to be the most promising type of electrolyzer for the practical application of electrochemical CO_(2) reduction reaction(CO_(2)RR).In MEAs,a square-shaped cross-section in the flow channel is normally adopted,the configuration optimization of which could potentially enhance the performance of the electrolyzer.This paper describes the numerical simulation study on the impact of the flow-channel cross-section shapes in the MEA electrolyzer for CO_(2)RR.The results show that wide flow channels with low heights are beneficial to the CO_(2)RR by providing a uniform flow field of CO_(2),especially at high current densities.Moreover,the larger the electrolyzer,the more significant the effect is.This study provides a theoretical basis for the design of high-performance MEA electrolyzers for CO_(2)RR.
文摘BACKGROUND Pancreatic cancer remains one of the most lethal malignancies worldwide,with a poor prognosis often attributed to late diagnosis.Understanding the correlation between pathological type and imaging features is crucial for early detection and appropriate treatment planning.AIM To retrospectively analyze the relationship between different pathological types of pancreatic cancer and their corresponding imaging features.METHODS We retrospectively analyzed the data of 500 patients diagnosed with pancreatic cancer between January 2010 and December 2020 at our institution.Pathological types were determined by histopathological examination of the surgical spe-cimens or biopsy samples.The imaging features were assessed using computed tomography,magnetic resonance imaging,and endoscopic ultrasound.Statistical analyses were performed to identify significant associations between pathological types and specific imaging characteristics.RESULTS There were 320(64%)cases of pancreatic ductal adenocarcinoma,75(15%)of intraductal papillary mucinous neoplasms,50(10%)of neuroendocrine tumors,and 55(11%)of other rare types.Distinct imaging features were identified in each pathological type.Pancreatic ductal adenocarcinoma typically presents as a hypodense mass with poorly defined borders on computed tomography,whereas intraductal papillary mucinous neoplasms present as characteristic cystic lesions with mural nodules.Neuroendocrine tumors often appear as hypervascular lesions in contrast-enhanced imaging.Statistical analysis revealed significant correlations between specific imaging features and pathological types(P<0.001).CONCLUSION This study demonstrated a strong association between the pathological types of pancreatic cancer and imaging features.These findings can enhance the accuracy of noninvasive diagnosis and guide personalized treatment approaches.
文摘Despite the gradual transformation of traditional manufacturing by the Human-Robot Collaboration Assembly(HRCA),challenges remain in the robot’s ability to understand and predict human assembly intentions.This study aims to enhance the robot’s comprehension and prediction capabilities of operator assembly intentions by capturing and analyzing operator behavior and movements.We propose a video feature extraction method based on the Temporal Shift Module Network(TSM-ResNet50)to extract spatiotemporal features from assembly videos and differentiate various assembly actions using feature differences between video frames.Furthermore,we construct an action recognition and segmentation model based on the Refined-Multi-Scale Temporal Convolutional Network(Refined-MS-TCN)to identify assembly action intervals and accurately acquire action categories.Experiments on our self-built reducer assembly action dataset demonstrate that our network can classify assembly actions frame by frame,achieving an accuracy rate of 83%.Additionally,we develop a HiddenMarkovModel(HMM)integrated with assembly task constraints to predict operator assembly intentions based on the probability transition matrix and assembly task constraints.The experimental results show that our method for predicting operator assembly intentions can achieve an accuracy of 90.6%,which is a 13.3%improvement over the HMM without task constraints.
文摘During Donald Trump’s first term,the“Trump Shock”brought world politics into an era of uncertainties and pulled the transatlantic alliance down to its lowest point in history.The Trump 2.0 tsunami brewed by the 2024 presidential election of the United States has plunged the U.S.-Europe relations into more gloomy waters,ushering in a more complex and turbulent period of adjustment.
基金Supported by the Henan Province Key Research and Development Project(231111211300)the Central Government of Henan Province Guides Local Science and Technology Development Funds(Z20231811005)+2 种基金Henan Province Key Research and Development Project(231111110100)Henan Provincial Outstanding Foreign Scientist Studio(GZS2024006)Henan Provincial Joint Fund for Scientific and Technological Research and Development Plan(Application and Overcoming Technical Barriers)(242103810028)。
文摘The fusion of infrared and visible images should emphasize the salient targets in the infrared image while preserving the textural details of the visible images.To meet these requirements,an autoencoder-based method for infrared and visible image fusion is proposed.The encoder designed according to the optimization objective consists of a base encoder and a detail encoder,which is used to extract low-frequency and high-frequency information from the image.This extraction may lead to some information not being captured,so a compensation encoder is proposed to supplement the missing information.Multi-scale decomposition is also employed to extract image features more comprehensively.The decoder combines low-frequency,high-frequency and supplementary information to obtain multi-scale features.Subsequently,the attention strategy and fusion module are introduced to perform multi-scale fusion for image reconstruction.Experimental results on three datasets show that the fused images generated by this network effectively retain salient targets while being more consistent with human visual perception.
基金support from the Ministry of Higher Education Malaysia under grant HICOE-2023-005.
文摘A unitized regenerative fuel cell(URFC)is a device that may function reversibly as either a fuel cell(FC)or water elec-trolysis(WE).An important component of this device is the Membrane electrode assembly(MEA).Therefore,this study aimed to compare the performance outcomes of MEA using electrodes with single and three catalyst layers.This study measured Electrochemical Surface Area(ECSA),Electrochemical Impedance Spectroscopy(EIS),X-ray Diffraction analysis(XRD),and X-ray Fluorescence(XRF).Furthermore,the round-trip efficiency(RTE)of the MEA,as w ell as the performance in FC and WE mode,was measured.In comparison,The ECSA values of Pt-Ru/C and Pt/C with three catalyst layers were higher than the single catalyst layer.This result was supported by electrode characterization data for XRD and XRF.The respective electrical conductivity values of Pt-Ru/C and Pt/C with three catalyst layers are also higher than the single cata-lyst layer,and the performance of URFC using MEA with three catalyst layers has the highest value of RTE among the MEA performances of URFC,which is 100%at a current density of 4 mA·cm-2.
基金Supported by National Key Research and Development Program of China(Grant No.2022YFB3304200)National Natural Science Foundation of China(Grant No.52205288)+1 种基金China Postdoctoral Science Foundation(Grant Nos.2024T170795,2024M762815)Zhejiang Provincial Key Research and Development Program(Grant No.2024C01029)。
文摘Assembly precision greatly influences the performance of complex high-end equipment.The traditional industrial assembly process and deviation transfer are implicit and uncertain,causing problems like poor component fit and hard-to-trace assembly stress concentration.Assemblers can only check whether the dimensional tolerance of the component design is exceeded step by step in combination with prior knowledge.Inversion in industrial assembly optimizes assembly and design by comparing real and theoretical results and doing inversion analysis to reduce assembly deviation.The digital twin(DT)technology visualizes and predicts the assembly process by mapping real and virtual model parameters and states simultaneously,expanding parameter range for inversion analysis and improving inversion result accuracy.Problems in improving industrial assembly precision and the significance and research status of DT-driven parametric inversion of assembly tools,processes and object precision are summarized.It analyzes vital technologies for assembly precision inversion such as multi-attribute assembly process parameter sensing,virtual modeling of high-fidelity assembly systems,twin synchronization of assembly process data models,multi-physical field simulation,and performance twin model construction of the assembly process.Combined with human-cyber-physical system,augmented reality,and generative intelligence,the outlook of DT-driven assembly precision inversion is proposed,providing support for DT's use in industrial assembly and precision improvement.
基金Supported by National Natural Science Foundation of China(Grant Nos.52475509 and U22A20203)Beijing Municipal Natural Science Foundation(Grant No.L248005)Hebei Provincial Natural Science Foundation(Grant No.E2023105059)。
文摘As the demands for assembly quality and efficiency increase,robot-assisted assembly applications are becoming more widespread.Peg-in-hole assembly,as a typical form of assembly,has been widely researched by scholars.Currently,robotic peg-in-hole assembly faces challenges such as complex analysis of part contact forces,difficulties in task modeling,and the failure of traditional strategies.Simply controlling the position of the robot's end effector cannot achieve high precision,high efficiency peg-in-hole assembly.Flexible assembly,especially intelligent flexible assembly,is becoming the future development trend.So there is a lack of comprehensive reviews on robotic flexible peg-in-hole assembly.This paper first outlines the basic components of peg-in-hole assembly and summarizes the two basic operational processes of peg-in-hole assembly,along with their related theoretical foundations.We then review and analyze the research on passive compliant assembly,active compliant assembly,and intelligent flexible assembly.Finally,it presents an outlook on the future development directions of robotic peg-in-hole assembly.
基金Sponsored by the National Natural Science Foundation of China(Grant No.52005003)the Science and Technology Planning Project of Wuhu City(Grant No.2022jc41)。
文摘To address the challenges of insufficient visualization in the industrial robot assembly operation system and the limitation of visualizing only geometric attributes of physical properties,a method is proposed for constructing an industrial robot assembly system based on virtual reality technology.Focusing on the shaft hole assembly,the mechanical characteristics of the industrial robot shaft hole assembly process are analyzed and a dynamic model is established for shaft hole assembly operations.The key elements of virtual assembly operations for industrial robots are summarized and a five-dimensional model is proposed for industrial robot virtual operations.Utilizing the Unity3D engine based on the 5-D model for industrial robot virtual operations,an industrial robot shaft hole assembly system is developed.This system enables virtual assembly operations,displays physical attributes,and provides valuable references for the research of virtual systems.
基金partially supported by the National Natural Science Foundation (62272248)the Open Project Fund of State Key Laboratory of Computer Architecture,Institute of Computing Technology,Chinese Academy of Sciences (CARCHA202108,CARCH201905)+1 种基金the Natural Science Foundation of Tianjin (20JCZDJC00610)Sponsored by Zhejiang Lab (2021KF0AB04)。
文摘Smart contracts are widely used on the blockchain to implement complex transactions,such as decentralized applications on Ethereum.Effective vulnerability detection of large-scale smart contracts is critical,as attacks on smart contracts often cause huge economic losses.Since it is difficult to repair and update smart contracts,it is necessary to find the vulnerabilities before they are deployed.However,code analysis,which requires traversal paths,and learning methods,which require many features to be trained,are too time-consuming to detect large-scale on-chain contracts.Learning-based methods will obtain detection models from a feature space compared to code analysis methods such as symbol execution.But the existing features lack the interpretability of the detection results and training model,even worse,the large-scale feature space also affects the efficiency of detection.This paper focuses on improving the detection efficiency by reducing the dimension of the features,combined with expert knowledge.In this paper,a feature extraction model Block-gram is proposed to form low-dimensional knowledge-based features from bytecode.First,the metadata is separated and the runtime code is converted into a sequence of opcodes,which are divided into segments based on some instructions(jumps,etc.).Then,scalable Block-gram features,including 4-dimensional block features and 8-dimensional attribute features,are mined for the learning-based model training.Finally,feature contributions are calculated from SHAP values to measure the relationship between our features and the results of the detection model.In addition,six types of vulnerability labels are made on a dataset containing 33,885 contracts,and these knowledge-based features are evaluated using seven state-of-the-art learning algorithms,which show that the average detection latency speeds up 25×to 650×,compared with the features extracted by N-gram,and also can enhance the interpretability of the detection model.
基金supported by the National Natural Science Foundation of China(Nos.22325111,2220312,21871298,91956118)Guangdong Basic Research Center of Excellence for Functional Molecular Engineeringthe Sun Yat-sen University。
文摘Molecular recognition of fullerene using various host compounds is well-known in literature.But most studies focus on host-vip complexation in solution using host compounds with a single binding cavity.Herein,we report a series of highly preorganized janusarene derivatives with homoditopic binding sites.These novel janusarenes can bind and align various fullerenes such as C_(60),C_(70),C_(84),and Gd@C_(82)in a highly efficient manner.Robust shape complementary association and assembly are observed in solution,in the bulk solid state,in the liquid crystalline state,or on surface,and the assembled structures are characterized by nuclear magnetic resonance(NMR)titration,X-ray diffraction,polarized optical microscopy,and scanning tunneling microscopy.
基金King Saud University,Grant/Award Number:RSP2024R157。
文摘Biometric characteristics are playing a vital role in security for the last few years.Human gait classification in video sequences is an important biometrics attribute and is used for security purposes.A new framework for human gait classification in video sequences using deep learning(DL)fusion assisted and posterior probability-based moth flames optimization(MFO)is proposed.In the first step,the video frames are resized and finetuned by two pre-trained lightweight DL models,EfficientNetB0 and MobileNetV2.Both models are selected based on the top-5 accuracy and less number of parameters.Later,both models are trained through deep transfer learning and extracted deep features fused using a voting scheme.In the last step,the authors develop a posterior probabilitybased MFO feature selection algorithm to select the best features.The selected features are classified using several supervised learning methods.The CASIA-B publicly available dataset has been employed for the experimental process.On this dataset,the authors selected six angles such as 0°,18°,90°,108°,162°,and 180°and obtained an average accuracy of 96.9%,95.7%,86.8%,90.0%,95.1%,and 99.7%.Results demonstrate comparable improvement in accuracy and significantly minimize the computational time with recent state-of-the-art techniques.
基金supported by the Fundamental Research Funds for the Provincial Universities of Zhejiang (No.GK249909299001-036)National Key Research and Development Program of China (No. 2023YFB4502803)Zhejiang Provincial Natural Science Foundation of China (No.LDT23F01014F01)。
文摘Due to the limitations of existing imaging hardware, obtaining high-resolution hyperspectral images is challenging. Hyperspectral image super-resolution(HSI SR) has been a very attractive research topic in computer vision, attracting the attention of many researchers. However, most HSI SR methods focus on the tradeoff between spatial resolution and spectral information, and cannot guarantee the efficient extraction of image information. In this paper, a multidimensional features network(MFNet) for HSI SR is proposed, which simultaneously learns and fuses the spatial,spectral, and frequency multidimensional features of HSI. Spatial features contain rich local details,spectral features contain the information and correlation between spectral bands, and frequency feature can reflect the global information of the image and can be used to obtain the global context of HSI. The fusion of the three features can better guide image super-resolution, to obtain higher-quality high-resolution hyperspectral images. In MFNet, we use the frequency feature extraction module(FFEM) to extract the frequency feature. On this basis, a multidimensional features extraction module(MFEM) is designed to learn and fuse multidimensional features. In addition, experimental results on two public datasets demonstrate that MFNet achieves state-of-the-art performance.
