350 keV He^(+) ions were injected into laser powder bed fusion(LPBF)-processed 304L stainless steel and traditional rolled 304L stainless steel with a flux of 1×10^(17) ions/cm^(2) at room temperature,followed by...350 keV He^(+) ions were injected into laser powder bed fusion(LPBF)-processed 304L stainless steel and traditional rolled 304L stainless steel with a flux of 1×10^(17) ions/cm^(2) at room temperature,followed by annealing at 750℃ for 10,100,and 300 h,respectively.The results showed that material swelling due to helium bubble coarsening was almost not observed in either the LPBF or rolled samples after 10 h of annealing duration.Rapid coarsening and swelling of bubbles occurred in the rolled samples,but only moderate bubble growth occurred in the LPBF sample after annealing for 100 h.After annealing for 300 h,the helium bubbles in both samples tended to grow steadily.For 10 h of annealing,the irradiated samples were in a disequilibrium state,and the apparent activation energy(E^(act))calculated by the Arrhenius model determined that helium atoms tended to diffuse through the displacement mechanism,and helium bubbles grew under the migration and coalescence(MC)mechanism.With annealing times over 100 h,the high-density dislocations and nano-oxide particles in the LPBF sample still had a strong trapping effect on the movement and growth of helium bubbles.After annealing for 300 h,the cellular subgrains in the LPBF sample decomposed,and the nano-oxide particles had no trapping effect on the helium bubbles.At this time,the dislocation structure played a primary role in suppressing the growth of helium bubbles,and the radiation resistance of the LPBF sample remained superior to that of the rolled samples.展开更多
Acute lung injury(ALl)is characterized by a sudden decline in pulmonary gas exchange function due to various pathological factors,with severe cases progressing to acute respiratory distress syndrome(ARDS).ARDS affects...Acute lung injury(ALl)is characterized by a sudden decline in pulmonary gas exchange function due to various pathological factors,with severe cases progressing to acute respiratory distress syndrome(ARDS).ARDS affects approximately 3million patients annually,accounting for 10% of intensive care unit admissions[1].展开更多
Background:Parkinson’s disease(PD)is one of the most common movement disorders worldwide.Ziyin Xifeng Decoction(ZYXFD),a traditional Chinese medicine compound formula,has shown therapeutic efficacy in treating PD,but...Background:Parkinson’s disease(PD)is one of the most common movement disorders worldwide.Ziyin Xifeng Decoction(ZYXFD),a traditional Chinese medicine compound formula,has shown therapeutic efficacy in treating PD,but its specific mechanisms of action have not been fully elucidated.Methods:Firstly,we employed network pharmacology and untargeted metabolomics analysis to identify the core targets,pathways,and key metabolites of ZYXFD in the treatment of PD.Subsequently,we evaluated the protective effects of ZYXFD and further investigated its anti-PD mechanisms by validating the analytical results.Results:Combined analyses of network pharmacology and metabolomics identify the core targets including EGFR,SRC,PTGS2,and CDK2,while the effects of ZYXFD against PD are likely mediated primarily through the PI3K/AKT/mTOR signaling pathway.Pharmacodynamic evaluation demonstrated that a high dose of ZYXFD significantly improved behavioral deficits in chronic PD mice,downregulatedα-synuclein protein expression,and protected dopaminergic neurons.It also regulated the expression of core targets,inhibited the PI3K/AKT/mTOR signaling pathway,promoted autophagy,and reduced apoptosis.In vitro experiments further verified that the therapeutic effect of ZYXFD on PD is dependent on autophagy regulation.Conclusion:The findings demonstrated that ZYXFD alleviates PD by modulating related proteins and metabolites,inhibiting the PI3K/AKT/mTOR signaling pathway,and enhancing autophagy.This provides a theoretical basis for its broader application in PD treatment.展开更多
Traditional Chinese medicine(TCM)has garnered increasing attention globally,with its modernization becoming a prominent research focus both within China and internationally.However,the lack of a precise definition for...Traditional Chinese medicine(TCM)has garnered increasing attention globally,with its modernization becoming a prominent research focus both within China and internationally.However,the lack of a precise definition for TCM modernization has hindered clear guidance for its development.Additionally,cancer remains a significant global public health challenge,largely untreatable with current methods.Therefore,a comprehensive understanding of TCM modernization is crucial for its evolution,revolution,drug discovery,and cancer therapy.This study provides an overview of the history,theory,characteristics,and evolution of TCM,highlighting its potential in cancer prevention and treatment.We propose a definition for TCM modernization,innovative Chinese medicine(ICM),and elucidate strategies to elevate TCM from a supporting role to a leading one.Electronic databases such as PubMed,Web of Science,ScienceDirect,and Clinical Trials were utilized to retrieve relevant literature spanning from 1979 to 2024,with most publications being from the last five years,using keywords like“Traditional Chinese medicine”,“Cancer”,“Mechanism”,and“Clinical trial”.In this study,we introduce the theory of TCM modernization following target identification and initial compound screening:ICM,defined by“3 D”elements:definite active ingredient composition and content,determined functional mechanism,and detection through evidence-based medicine.Overall,the“3 D”definition of ICM will establish a standard for ICM,accelerate TCM modernization,enhance drug discovery targeting cancer and various human diseases,and benefit patients worldwide.展开更多
As urban landscapes evolve and vehicular volumes soar,traditional traffic monitoring systems struggle to scale,often failing under the complexities of dense,dynamic,and occluded environments.This paper introduces a no...As urban landscapes evolve and vehicular volumes soar,traditional traffic monitoring systems struggle to scale,often failing under the complexities of dense,dynamic,and occluded environments.This paper introduces a novel,unified deep learning framework for vehicle detection,tracking,counting,and classification in aerial imagery designed explicitly for modern smart city infrastructure demands.Our approach begins with adaptive histogram equalization to optimize aerial image clarity,followed by a cutting-edge scene parsing technique using Mask2Former,enabling robust segmentation even in visually congested settings.Vehicle detection leverages the latest YOLOv11 architecture,delivering superior accuracy in aerial contexts by addressing occlusion,scale variance,and fine-grained object differentiation.We incorporate the highly efficient ByteTrack algorithm for tracking,enabling seamless identity preservation across frames.Vehicle counting is achieved through an unsupervised DBSCAN-based method,ensuring adaptability to varying traffic densities.We further introduce a hybrid feature extraction module combining Convolutional Neural Networks(CNNs)with Zernike Moments,capturing both deep semantic and geometric signatures of vehicles.The final classification is powered by NASNet,a neural architecture search-optimized model,ensuring high accuracy across diverse vehicle types and orientations.Extensive evaluations of the VAID benchmark dataset demonstrate the system’s outstanding performance,achieving 96%detection,94%tracking,and 96.4%classification accuracy.On the UAVDT dataset,the system attains 95%detection,93%tracking,and 95%classification accuracy,confirming its robustness across diverse aerial traffic scenarios.These results establish new benchmarks in aerial traffic analysis and validate the framework’s scalability,making it a powerful and adaptable solution for next-generation intelligent transportation systems and urban surveillance.展开更多
Successful ex situ conservation of plant populations requires a high degree of genetic representativeness.However,spatially biased sampling in ex situ conservation efforts may fail to capture all wild genetic clusters...Successful ex situ conservation of plant populations requires a high degree of genetic representativeness.However,spatially biased sampling in ex situ conservation efforts may fail to capture all wild genetic clusters for species with range-wide genetic structure.To investigate the extent of spatially biased sampling in living collections and the coverage of wild genetic clusters in plant populations under ex situ conservation worldwide,we combined a global synthesis of ex situ conservation efforts with a case study of an endangered riparian plant species,Myricaria laxiflora.Our analysis of ex situ conservation worldwide revealed that the majority(82.6%)of ex situ populations fail to cover all wild genetic clusters,largely due to spatially biased sampling with low geographic coverage.Our case study of M.laxiflora showed that genetic diversity differed between the ex situ and upstream populations,while it was comparable between ex situ populations and other wild populations.However,current ex situ populations did not cover all wild genetic clusters,as the upstream genetic cluster was previously uncollected.Our study suggests that the failure to cover all wild genetic clusters in ex situ populations is a widespread issue,and ex situ populations with high genetic diversity can also fail to cover all wild genetic clusters.In future ex situ conservation programs,both the importance of high genetic diversity and the high coverage of wild genetic clusters should be prioritized.展开更多
Human object detection and recognition is essential for elderly monitoring and assisted living however,models relying solely on pose or scene context often struggle in cluttered or visually ambiguous settings.To addre...Human object detection and recognition is essential for elderly monitoring and assisted living however,models relying solely on pose or scene context often struggle in cluttered or visually ambiguous settings.To address this,we present SCENET-3D,a transformer-drivenmultimodal framework that unifies human-centric skeleton features with scene-object semantics for intelligent robotic vision through a three-stage pipeline.In the first stage,scene analysis,rich geometric and texture descriptors are extracted from RGB frames,including surface-normal histograms,angles between neighboring normals,Zernike moments,directional standard deviation,and Gabor-filter responses.In the second stage,scene-object analysis,non-human objects are segmented and represented using local feature descriptors and complementary surface-normal information.In the third stage,human-pose estimation,silhouettes are processed through an enhanced MoveNet to obtain 2D anatomical keypoints,which are fused with depth information and converted into RGB-based point clouds to construct pseudo-3D skeletons.Features from all three stages are fused and fed in a transformer encoder with multi-head attention to resolve visually similar activities.Experiments on UCLA(95.8%),ETRI-Activity3D(89.4%),andCAD-120(91.2%)demonstrate that combining pseudo-3D skeletonswith rich scene-object fusion significantly improves generalizable activity recognition,enabling safer elderly care,natural human–robot interaction,and robust context-aware robotic perception in real-world environments.展开更多
Cisplatin(CDDP)-based chemotherapy is an effective strategy for the treatment of advanced nasopharyngeal carcinoma(NPC).However,serious toxic side effects of CDDP limit patient tolerance and treatment compliance,which...Cisplatin(CDDP)-based chemotherapy is an effective strategy for the treatment of advanced nasopharyngeal carcinoma(NPC).However,serious toxic side effects of CDDP limit patient tolerance and treatment compliance,which urgently needs to be addressed in clinical application.Liposomes have been considered ideal vehicles for reducing CDDP toxicity due to their high biocompatibility,low toxicity and passive targeting ability.Nevertheless,CDDP's poor water/lipid solubility usually results in a low liposome druglipid ratio,limiting tumor delivery ability.Herein,a CDDP-polyphenol complex liposome was designed to increase the drug loading capacity of CDDP to realize the reduction of toxicity and effective antitumor effect simultaneously.The complex was prepared via complexation reaction of different stoichiometric ratios of CDDP and polyphenolic substances(gallic acid,epigallocatechin gallate and tannic acid),followed by encapsulation of complex in liposomes to improve tumor targeting.Notably,the molecular interaction forces between CDDP and polyphenolic substances were intensively investigated through a binding force disruption assay.In vitro studies demonstrated that the optimal formulation of CDDP-epigallocatechin gallate complex liposome(CDDP-EGCG Lips) showed the highest CDDP encapsulation efficiency,favorable stability,pH-sensitive release,enhanced cellular uptake and apoptosis effect.In vivo studies revealed that CDDP-EGCG Lips retarded the elimination of CDDP to prolong their circulation time,inhibited the growth of tumors,and significantly reduced the toxic side effects compared to CDDP monotherapy.This delivery strategy holds great promise for improving the clinical use of platinum-based drugs.展开更多
BiMeO_(3)–PbTiO_(3)(where Me represents transition metals)perovskite-type thin films have been widely studied due to their superior ferroelectric properties,including robust ferroelectric polarization and high Curie ...BiMeO_(3)–PbTiO_(3)(where Me represents transition metals)perovskite-type thin films have been widely studied due to their superior ferroelectric properties,including robust ferroelectric polarization and high Curie temperatures.In this study,PbTiO_(3)-based perovskite thin films of xBi(Cu_(1/2)Zr_(1/2))O_(3)–(1-x)PbTiO_(3)(xBCZ–(1-x)PT)were designed and prepared on Pt(111)/Ti/SiO_2/Si substrates using the conventional sol–gel method.The x BCZ–(1-x)PT thin films demonstrate remarkable crystallinity,characterized by a perovskite structure and a dense microstructure,which contribute to their highperformance ferroelectric and fatigue properties.Notably,the thin films exhibit large remnant polarization(2P_(r0))values,reaching 98μC·cm^(-2)and 74μC·cm^(-2)for the 0.05BCZ–0.95PT and 0.1BCZ–0.9PT compositions,respectively.Furthermore,the thin films also demonstrate a high Curie temperature(T_(C)=510℃),as well as favorable fatigue properties and low leakage current,suggesting their potential applicability in ferroelectric devices.展开更多
Seawater zinc-air batteries are promising energy storage devices due to their high energy density and utilization of seawater electrolytes.However,their efficiency is hindered by the sluggish oxygen reduction reaction...Seawater zinc-air batteries are promising energy storage devices due to their high energy density and utilization of seawater electrolytes.However,their efficiency is hindered by the sluggish oxygen reduction reaction(ORR)and chlorideinduced degradation over conventional catalysts.In this study,we proposed a universal synthetic strategy to construct heteroatom axially coordinated Fe–N_(4) single-atom seawater catalyst materials(Cl–Fe–N_(4) and S–Fe–N_(4)).X-ray absorption spectroscopy confirmed their five-coordinated square pyramidal structure.Systematic evaluation of catalytic activities revealed that compared with S–Fe–N_(4),Cl–Fe–N_(4) exhibits smaller electrochemical active surface area and specific surface area,yet demonstrates higher limiting current density(5.8 mA cm^(−2)).The assembled zinc-air batteries using Cl–Fe–N_(4) showed superior power density(187.7 mW cm^(−2) at 245.1 mA cm^(−2)),indicating that Cl axial coordination more effectively enhances the intrinsic ORR activity.Moreover,Cl–Fe–N_(4) demonstrates stronger Cl−poisoning resistance in seawater environments.Chronoamperometry tests and zinc-air battery cycling performance evaluations confirmed its enhanced stability.Density functional theory calculations revealed that the introduction of heteroatoms in the axial direction regulates the electron center of Fe single atom,leading to more active reaction intermediates and increased electron density of Fe single sites,thereby enhancing the reduction in adsorbed intermediates and hence the overall ORR catalytic activity.展开更多
Atractylodes macrocephala Koidz.(A.macrocephala)is a medicinal and edible plant species belonging to the Compositae family.Its rhizome serves both therapeutic and nutritional purposes in China.This investigation led t...Atractylodes macrocephala Koidz.(A.macrocephala)is a medicinal and edible plant species belonging to the Compositae family.Its rhizome serves both therapeutic and nutritional purposes in China.This investigation led to the isolation of thirteen novel rearranged 9(8→7)-abeo-eudesmane-type sesquiterpenoid dimers(SDs),atramacronins A-M(1-13),three eudesmane-type SDs,atramacronins N-P(14-16),and two previously identified meroterpenoids,atrachinenin G(17)and atrachineninΙ(18),from Atractylodes macrocephala.Structure elucidation was accomplished through comprehensive spectroscopic analysis and single-crystal X-ray diffraction.Compounds 1,4-7,9,and 10 exhibited notable cytotoxicity against Hep3B,HepG2,and Huh7 cell lines,with half maximal inhibitory concentration(IC_(50))values ranging from 3.71 to 13.99μmol·L^(-1).展开更多
Recognizing human interactions in RGB videos is a critical task in computer vision,with applications in video surveillance.Existing deep learning-based architectures have achieved strong results,but are computationall...Recognizing human interactions in RGB videos is a critical task in computer vision,with applications in video surveillance.Existing deep learning-based architectures have achieved strong results,but are computationally intensive,sensitive to video resolution changes and often fail in crowded scenes.We propose a novel hybrid system that is computationally efficient,robust to degraded video quality and able to filter out irrelevant individuals,making it suitable for real-life use.The system leverages multi-modal handcrafted features for interaction representation and a deep learning classifier for capturing complex dependencies.Using Mask R-CNN and YOLO11-Pose,we extract grayscale silhouettes and keypoint coordinates of interacting individuals,while filtering out irrelevant individuals using a proposed algorithm.From these,we extract silhouette-based features(local ternary pattern and histogram of optical flow)and keypoint-based features(distances,angles and velocities)that capture distinct spatial and temporal information.A Bidirectional Long Short-Term Memory network(BiLSTM)then classifies the interactions.Extensive experiments on the UT Interaction,SBU Kinect Interaction and the ISR-UOL 3D social activity datasets demonstrate that our system achieves competitive accuracy.They also validate the effectiveness of the chosen features and classifier,along with the proposed system’s computational efficiency and robustness to occlusion.展开更多
The abundancy of defect sinks in the microstructure of laser powder bed fusion(LPBF) processed austenitic stainless steels was found to be beneficial for helium resistance.In the current study,the influence of the nov...The abundancy of defect sinks in the microstructure of laser powder bed fusion(LPBF) processed austenitic stainless steels was found to be beneficial for helium resistance.In the current study,the influence of the novel microstructure in LPBF processed 304 L on the helium bubble growth behaviour was investigated using transmission electron microscopy in samples implanted with He^(+) ion and post-irradiation annealing treated at 600℃ for 1 h.Two variants of LPBF processed 304 L samples were used,one in as-built condition and the other solution-annealed.The comparison between the two samples indicated that the helium bubble growth was inhibited and remained stable in the as-built sample but coarsened significantly in the solution-annealed sample.The sub-grain boundaries and oxide nano-inclusions acted as defect sinks to trap helium atoms and inhibited the growth of helium bubble in the as-built sample under the post-irradiation annealing conditions used.展开更多
We have carefully read the description of the proposed mechanisms of hamstring muscle strain injury by Liu et al.1and noticed that they suggest that hamstring strain injuries may be associated with extensive muscle fo...We have carefully read the description of the proposed mechanisms of hamstring muscle strain injury by Liu et al.1and noticed that they suggest that hamstring strain injuries may be associated with extensive muscle force and occur during the early stance phase of sprinting when the hamstrings are thought to work concentrically.We did not find any evidence in our extensive literature review to support this展开更多
基金supported by the National Natural Science Foundation of China(Nos.U22B2067 and 52073176).
文摘350 keV He^(+) ions were injected into laser powder bed fusion(LPBF)-processed 304L stainless steel and traditional rolled 304L stainless steel with a flux of 1×10^(17) ions/cm^(2) at room temperature,followed by annealing at 750℃ for 10,100,and 300 h,respectively.The results showed that material swelling due to helium bubble coarsening was almost not observed in either the LPBF or rolled samples after 10 h of annealing duration.Rapid coarsening and swelling of bubbles occurred in the rolled samples,but only moderate bubble growth occurred in the LPBF sample after annealing for 100 h.After annealing for 300 h,the helium bubbles in both samples tended to grow steadily.For 10 h of annealing,the irradiated samples were in a disequilibrium state,and the apparent activation energy(E^(act))calculated by the Arrhenius model determined that helium atoms tended to diffuse through the displacement mechanism,and helium bubbles grew under the migration and coalescence(MC)mechanism.With annealing times over 100 h,the high-density dislocations and nano-oxide particles in the LPBF sample still had a strong trapping effect on the movement and growth of helium bubbles.After annealing for 300 h,the cellular subgrains in the LPBF sample decomposed,and the nano-oxide particles had no trapping effect on the helium bubbles.At this time,the dislocation structure played a primary role in suppressing the growth of helium bubbles,and the radiation resistance of the LPBF sample remained superior to that of the rolled samples.
基金supported by the National Natural Science Foun-dation of China(81970011,81970070,82100086,and 82270390)the Natural Science Foundation of Hubei Province(2025AFC006)+2 种基金the research fund from Medical Sci-Tech Innovation Platform of Zhongnan Hospital,Wuhan University(PTXM2025032)the Basic Medicine-Clinical Medicine Transformation Collaborative Fund of Zhongnan Hospital of Wuhan University,the Hubei Province Inno-vation Platform Construction Project(20204201117303072238)the Hubei Provincial Engineering Research Center of Model Animal.
文摘Acute lung injury(ALl)is characterized by a sudden decline in pulmonary gas exchange function due to various pathological factors,with severe cases progressing to acute respiratory distress syndrome(ARDS).ARDS affects approximately 3million patients annually,accounting for 10% of intensive care unit admissions[1].
基金funded by Zhejiang Province Traditional Chinese Medicine Science and Technology Program(No.2021ZZ012)The Changlin Qiu National Distinguished Senior Traditional Chinese Medicine Expert Heritage Workshop Project(No.GZS2021007).
文摘Background:Parkinson’s disease(PD)is one of the most common movement disorders worldwide.Ziyin Xifeng Decoction(ZYXFD),a traditional Chinese medicine compound formula,has shown therapeutic efficacy in treating PD,but its specific mechanisms of action have not been fully elucidated.Methods:Firstly,we employed network pharmacology and untargeted metabolomics analysis to identify the core targets,pathways,and key metabolites of ZYXFD in the treatment of PD.Subsequently,we evaluated the protective effects of ZYXFD and further investigated its anti-PD mechanisms by validating the analytical results.Results:Combined analyses of network pharmacology and metabolomics identify the core targets including EGFR,SRC,PTGS2,and CDK2,while the effects of ZYXFD against PD are likely mediated primarily through the PI3K/AKT/mTOR signaling pathway.Pharmacodynamic evaluation demonstrated that a high dose of ZYXFD significantly improved behavioral deficits in chronic PD mice,downregulatedα-synuclein protein expression,and protected dopaminergic neurons.It also regulated the expression of core targets,inhibited the PI3K/AKT/mTOR signaling pathway,promoted autophagy,and reduced apoptosis.In vitro experiments further verified that the therapeutic effect of ZYXFD on PD is dependent on autophagy regulation.Conclusion:The findings demonstrated that ZYXFD alleviates PD by modulating related proteins and metabolites,inhibiting the PI3K/AKT/mTOR signaling pathway,and enhancing autophagy.This provides a theoretical basis for its broader application in PD treatment.
基金supported by the National Natural Science Foundation of China(No.82203343)the National Postdoctoral Program for Innovative Talents of China(No.BX20220273)+3 种基金China Postdoctoral Science Foundation(No.2022M712874)Henan Province Key Research and Development Promotion Special Project(Science and Technology)in 2023(No.232102311007)Henan Province Key Scientific Research Project of Colleges and Universities in 2023(No.23A310007)the Outstanding Youth Project of Henan Provincial Natural Science Foundation(No.252300421123)。
文摘Traditional Chinese medicine(TCM)has garnered increasing attention globally,with its modernization becoming a prominent research focus both within China and internationally.However,the lack of a precise definition for TCM modernization has hindered clear guidance for its development.Additionally,cancer remains a significant global public health challenge,largely untreatable with current methods.Therefore,a comprehensive understanding of TCM modernization is crucial for its evolution,revolution,drug discovery,and cancer therapy.This study provides an overview of the history,theory,characteristics,and evolution of TCM,highlighting its potential in cancer prevention and treatment.We propose a definition for TCM modernization,innovative Chinese medicine(ICM),and elucidate strategies to elevate TCM from a supporting role to a leading one.Electronic databases such as PubMed,Web of Science,ScienceDirect,and Clinical Trials were utilized to retrieve relevant literature spanning from 1979 to 2024,with most publications being from the last five years,using keywords like“Traditional Chinese medicine”,“Cancer”,“Mechanism”,and“Clinical trial”.In this study,we introduce the theory of TCM modernization following target identification and initial compound screening:ICM,defined by“3 D”elements:definite active ingredient composition and content,determined functional mechanism,and detection through evidence-based medicine.Overall,the“3 D”definition of ICM will establish a standard for ICM,accelerate TCM modernization,enhance drug discovery targeting cancer and various human diseases,and benefit patients worldwide.
基金funded by the Open Access Initiative of the University of Bremen and the DFG via SuUB BremenThe authors extend their appreciation to the Deanship of Research and Graduate Studies at King Khalid University for funding this work through Large Group Project under grant number(RGP2/367/46)+1 种基金This research is supported and funded by Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2025R410)Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘As urban landscapes evolve and vehicular volumes soar,traditional traffic monitoring systems struggle to scale,often failing under the complexities of dense,dynamic,and occluded environments.This paper introduces a novel,unified deep learning framework for vehicle detection,tracking,counting,and classification in aerial imagery designed explicitly for modern smart city infrastructure demands.Our approach begins with adaptive histogram equalization to optimize aerial image clarity,followed by a cutting-edge scene parsing technique using Mask2Former,enabling robust segmentation even in visually congested settings.Vehicle detection leverages the latest YOLOv11 architecture,delivering superior accuracy in aerial contexts by addressing occlusion,scale variance,and fine-grained object differentiation.We incorporate the highly efficient ByteTrack algorithm for tracking,enabling seamless identity preservation across frames.Vehicle counting is achieved through an unsupervised DBSCAN-based method,ensuring adaptability to varying traffic densities.We further introduce a hybrid feature extraction module combining Convolutional Neural Networks(CNNs)with Zernike Moments,capturing both deep semantic and geometric signatures of vehicles.The final classification is powered by NASNet,a neural architecture search-optimized model,ensuring high accuracy across diverse vehicle types and orientations.Extensive evaluations of the VAID benchmark dataset demonstrate the system’s outstanding performance,achieving 96%detection,94%tracking,and 96.4%classification accuracy.On the UAVDT dataset,the system attains 95%detection,93%tracking,and 95%classification accuracy,confirming its robustness across diverse aerial traffic scenarios.These results establish new benchmarks in aerial traffic analysis and validate the framework’s scalability,making it a powerful and adaptable solution for next-generation intelligent transportation systems and urban surveillance.
基金supported by National Key Research and Development Program of China(2024YFF1307400)Hubei Provincial Natural Science Foundation and Three Gorges Innovation Development Joint Fund(Grant No.2023AFD195)China Three Gorges Corporation(NBZZ202300130).
文摘Successful ex situ conservation of plant populations requires a high degree of genetic representativeness.However,spatially biased sampling in ex situ conservation efforts may fail to capture all wild genetic clusters for species with range-wide genetic structure.To investigate the extent of spatially biased sampling in living collections and the coverage of wild genetic clusters in plant populations under ex situ conservation worldwide,we combined a global synthesis of ex situ conservation efforts with a case study of an endangered riparian plant species,Myricaria laxiflora.Our analysis of ex situ conservation worldwide revealed that the majority(82.6%)of ex situ populations fail to cover all wild genetic clusters,largely due to spatially biased sampling with low geographic coverage.Our case study of M.laxiflora showed that genetic diversity differed between the ex situ and upstream populations,while it was comparable between ex situ populations and other wild populations.However,current ex situ populations did not cover all wild genetic clusters,as the upstream genetic cluster was previously uncollected.Our study suggests that the failure to cover all wild genetic clusters in ex situ populations is a widespread issue,and ex situ populations with high genetic diversity can also fail to cover all wild genetic clusters.In future ex situ conservation programs,both the importance of high genetic diversity and the high coverage of wild genetic clusters should be prioritized.
基金funded by Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2025R410),Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘Human object detection and recognition is essential for elderly monitoring and assisted living however,models relying solely on pose or scene context often struggle in cluttered or visually ambiguous settings.To address this,we present SCENET-3D,a transformer-drivenmultimodal framework that unifies human-centric skeleton features with scene-object semantics for intelligent robotic vision through a three-stage pipeline.In the first stage,scene analysis,rich geometric and texture descriptors are extracted from RGB frames,including surface-normal histograms,angles between neighboring normals,Zernike moments,directional standard deviation,and Gabor-filter responses.In the second stage,scene-object analysis,non-human objects are segmented and represented using local feature descriptors and complementary surface-normal information.In the third stage,human-pose estimation,silhouettes are processed through an enhanced MoveNet to obtain 2D anatomical keypoints,which are fused with depth information and converted into RGB-based point clouds to construct pseudo-3D skeletons.Features from all three stages are fused and fed in a transformer encoder with multi-head attention to resolve visually similar activities.Experiments on UCLA(95.8%),ETRI-Activity3D(89.4%),andCAD-120(91.2%)demonstrate that combining pseudo-3D skeletonswith rich scene-object fusion significantly improves generalizable activity recognition,enabling safer elderly care,natural human–robot interaction,and robust context-aware robotic perception in real-world environments.
基金supported by the National Natural Science Foundation of China (Nos.81872823,82073782,and 82241002)the Key R&D Plan of Ganjiang New District of Jiangxi (No.2023010)。
文摘Cisplatin(CDDP)-based chemotherapy is an effective strategy for the treatment of advanced nasopharyngeal carcinoma(NPC).However,serious toxic side effects of CDDP limit patient tolerance and treatment compliance,which urgently needs to be addressed in clinical application.Liposomes have been considered ideal vehicles for reducing CDDP toxicity due to their high biocompatibility,low toxicity and passive targeting ability.Nevertheless,CDDP's poor water/lipid solubility usually results in a low liposome druglipid ratio,limiting tumor delivery ability.Herein,a CDDP-polyphenol complex liposome was designed to increase the drug loading capacity of CDDP to realize the reduction of toxicity and effective antitumor effect simultaneously.The complex was prepared via complexation reaction of different stoichiometric ratios of CDDP and polyphenolic substances(gallic acid,epigallocatechin gallate and tannic acid),followed by encapsulation of complex in liposomes to improve tumor targeting.Notably,the molecular interaction forces between CDDP and polyphenolic substances were intensively investigated through a binding force disruption assay.In vitro studies demonstrated that the optimal formulation of CDDP-epigallocatechin gallate complex liposome(CDDP-EGCG Lips) showed the highest CDDP encapsulation efficiency,favorable stability,pH-sensitive release,enhanced cellular uptake and apoptosis effect.In vivo studies revealed that CDDP-EGCG Lips retarded the elimination of CDDP to prolong their circulation time,inhibited the growth of tumors,and significantly reduced the toxic side effects compared to CDDP monotherapy.This delivery strategy holds great promise for improving the clinical use of platinum-based drugs.
基金Project supported by the National Key Research and Development Program of China(Grant No.2021YFA1400300)the National Natural Science Foundation of China(Grant Nos.22271309,12304268,12261131499,and 11921004)the China Postdoctoral Science Foundation(Grant No.2023M743741)。
文摘BiMeO_(3)–PbTiO_(3)(where Me represents transition metals)perovskite-type thin films have been widely studied due to their superior ferroelectric properties,including robust ferroelectric polarization and high Curie temperatures.In this study,PbTiO_(3)-based perovskite thin films of xBi(Cu_(1/2)Zr_(1/2))O_(3)–(1-x)PbTiO_(3)(xBCZ–(1-x)PT)were designed and prepared on Pt(111)/Ti/SiO_2/Si substrates using the conventional sol–gel method.The x BCZ–(1-x)PT thin films demonstrate remarkable crystallinity,characterized by a perovskite structure and a dense microstructure,which contribute to their highperformance ferroelectric and fatigue properties.Notably,the thin films exhibit large remnant polarization(2P_(r0))values,reaching 98μC·cm^(-2)and 74μC·cm^(-2)for the 0.05BCZ–0.95PT and 0.1BCZ–0.9PT compositions,respectively.Furthermore,the thin films also demonstrate a high Curie temperature(T_(C)=510℃),as well as favorable fatigue properties and low leakage current,suggesting their potential applicability in ferroelectric devices.
基金funded by the Innovative Research Group Project of the National Natural Science Foundation of China(52121004)the Research Development Fund(No.RDF-21-02-060)by Xi’an Jiaotong-Liverpool University+1 种基金support received from the Suzhou Industrial Park High Quality Innovation Platform of Functional Molecular Materials and Devices(YZCXPT2023105)the XJTLU Advanced Materials Research Center(AMRC).
文摘Seawater zinc-air batteries are promising energy storage devices due to their high energy density and utilization of seawater electrolytes.However,their efficiency is hindered by the sluggish oxygen reduction reaction(ORR)and chlorideinduced degradation over conventional catalysts.In this study,we proposed a universal synthetic strategy to construct heteroatom axially coordinated Fe–N_(4) single-atom seawater catalyst materials(Cl–Fe–N_(4) and S–Fe–N_(4)).X-ray absorption spectroscopy confirmed their five-coordinated square pyramidal structure.Systematic evaluation of catalytic activities revealed that compared with S–Fe–N_(4),Cl–Fe–N_(4) exhibits smaller electrochemical active surface area and specific surface area,yet demonstrates higher limiting current density(5.8 mA cm^(−2)).The assembled zinc-air batteries using Cl–Fe–N_(4) showed superior power density(187.7 mW cm^(−2) at 245.1 mA cm^(−2)),indicating that Cl axial coordination more effectively enhances the intrinsic ORR activity.Moreover,Cl–Fe–N_(4) demonstrates stronger Cl−poisoning resistance in seawater environments.Chronoamperometry tests and zinc-air battery cycling performance evaluations confirmed its enhanced stability.Density functional theory calculations revealed that the introduction of heteroatoms in the axial direction regulates the electron center of Fe single atom,leading to more active reaction intermediates and increased electron density of Fe single sites,thereby enhancing the reduction in adsorbed intermediates and hence the overall ORR catalytic activity.
基金supported by the National Natural Science Foundation of China(Nos.32470414,32100319,and 82104377)the Fundamental Research Funds for the Central Universities,SWU(No.SWU-KR22052)+1 种基金the Natural Science Foundation of Chongqing,China(No.CSTB2022NSCQMSX0878)Chongqing Municipal Training Program of Innovation and Entrepreneurship for Undergraduates(No.S20241063290).
文摘Atractylodes macrocephala Koidz.(A.macrocephala)is a medicinal and edible plant species belonging to the Compositae family.Its rhizome serves both therapeutic and nutritional purposes in China.This investigation led to the isolation of thirteen novel rearranged 9(8→7)-abeo-eudesmane-type sesquiterpenoid dimers(SDs),atramacronins A-M(1-13),three eudesmane-type SDs,atramacronins N-P(14-16),and two previously identified meroterpenoids,atrachinenin G(17)and atrachineninΙ(18),from Atractylodes macrocephala.Structure elucidation was accomplished through comprehensive spectroscopic analysis and single-crystal X-ray diffraction.Compounds 1,4-7,9,and 10 exhibited notable cytotoxicity against Hep3B,HepG2,and Huh7 cell lines,with half maximal inhibitory concentration(IC_(50))values ranging from 3.71 to 13.99μmol·L^(-1).
基金supported and funded by Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2025R410),Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘Recognizing human interactions in RGB videos is a critical task in computer vision,with applications in video surveillance.Existing deep learning-based architectures have achieved strong results,but are computationally intensive,sensitive to video resolution changes and often fail in crowded scenes.We propose a novel hybrid system that is computationally efficient,robust to degraded video quality and able to filter out irrelevant individuals,making it suitable for real-life use.The system leverages multi-modal handcrafted features for interaction representation and a deep learning classifier for capturing complex dependencies.Using Mask R-CNN and YOLO11-Pose,we extract grayscale silhouettes and keypoint coordinates of interacting individuals,while filtering out irrelevant individuals using a proposed algorithm.From these,we extract silhouette-based features(local ternary pattern and histogram of optical flow)and keypoint-based features(distances,angles and velocities)that capture distinct spatial and temporal information.A Bidirectional Long Short-Term Memory network(BiLSTM)then classifies the interactions.Extensive experiments on the UT Interaction,SBU Kinect Interaction and the ISR-UOL 3D social activity datasets demonstrate that our system achieves competitive accuracy.They also validate the effectiveness of the chosen features and classifier,along with the proposed system’s computational efficiency and robustness to occlusion.
基金sponsored by the National Natural Science Foundation of China(Grant No.52073176)。
文摘The abundancy of defect sinks in the microstructure of laser powder bed fusion(LPBF) processed austenitic stainless steels was found to be beneficial for helium resistance.In the current study,the influence of the novel microstructure in LPBF processed 304 L on the helium bubble growth behaviour was investigated using transmission electron microscopy in samples implanted with He^(+) ion and post-irradiation annealing treated at 600℃ for 1 h.Two variants of LPBF processed 304 L samples were used,one in as-built condition and the other solution-annealed.The comparison between the two samples indicated that the helium bubble growth was inhibited and remained stable in the as-built sample but coarsened significantly in the solution-annealed sample.The sub-grain boundaries and oxide nano-inclusions acted as defect sinks to trap helium atoms and inhibited the growth of helium bubble in the as-built sample under the post-irradiation annealing conditions used.
文摘We have carefully read the description of the proposed mechanisms of hamstring muscle strain injury by Liu et al.1and noticed that they suggest that hamstring strain injuries may be associated with extensive muscle force and occur during the early stance phase of sprinting when the hamstrings are thought to work concentrically.We did not find any evidence in our extensive literature review to support this
