After spinal cord injury,impairment of the sensorimotor circuit can lead to dysfunction in the motor,sensory,proprioceptive,and autonomic nervous systems.Functional recovery is often hindered by constraints on the tim...After spinal cord injury,impairment of the sensorimotor circuit can lead to dysfunction in the motor,sensory,proprioceptive,and autonomic nervous systems.Functional recovery is often hindered by constraints on the timing of interventions,combined with the limitations of current methods.To address these challenges,various techniques have been developed to aid in the repair and reconstruction of neural circuits at different stages of injury.Notably,neuromodulation has garnered considerable attention for its potential to enhance nerve regeneration,provide neuroprotection,restore neurons,and regulate the neural reorganization of circuits within the cerebral cortex and corticospinal tract.To improve the effectiveness of these interventions,the implementation of multitarget early interventional neuromodulation strategies,such as electrical and magnetic stimulation,is recommended to enhance functional recovery across different phases of nerve injury.This review concisely outlines the challenges encountered following spinal cord injury,synthesizes existing neurostimulation techniques while emphasizing neuroprotection,repair,and regeneration of impaired connections,and advocates for multi-targeted,task-oriented,and timely interventions.展开更多
The combination of Daphnes Cortex(DC)and Liquorice Root(LR),two traditional Chinese medicinal herbs,has shown significant therapeutic effects on rheumatoid arthritis(RA),but its synergistic mechanism of action remains...The combination of Daphnes Cortex(DC)and Liquorice Root(LR),two traditional Chinese medicinal herbs,has shown significant therapeutic effects on rheumatoid arthritis(RA),but its synergistic mechanism of action remains to be elucidated.Employing a network pharmacology and molecular docking approach,this study systematically investigated the synergistic mechanism of the herb pair DC and LR in RA treatment.Active components and their corresponding targets were retrieved from the TCMSP database and relevant literature,and RA-related targets were collected from established disease databases.A total of 73 overlapping targets between DC-LR and RA were identified,among which core targets such as AKT1,TNF,and CASP3 were highlighted.GO and KEGG enrichment analyses revealed that these targets are involved in biological processes such as oxidative stress response and cell migration,and are significantly enriched in key pathways including HIF-1,TNF,and PI3K-Akt signaling pathways.Compatibility analysis further revealed that the combination of DC and LR may enhance therapeutic effects through synergistic regulation of shared targets and complementary modulation of upstream and downstream pathway components.Molecular docking confirmed strong binding affinities between core active components and key targets.This study provides a multi-dimensional“component-target-pathway”perspective on the potential synergistic anti-RA mechanism of the DC-LR herb pair,offering a theoretical basis for further experimental validation and clinical application.展开更多
End-to-end Temporal Action Detection(TAD)has achieved remarkable progress in recent years,driven by innovations in model architectures and the emergence of Video Foundation Models(VFMs).However,existing TAD methods th...End-to-end Temporal Action Detection(TAD)has achieved remarkable progress in recent years,driven by innovations in model architectures and the emergence of Video Foundation Models(VFMs).However,existing TAD methods that perform full fine-tuning of pretrained video models often incur substantial computational costs,which become particularly pronounced when processing long video sequences.Moreover,the need for precise temporal boundary annotations makes data labeling extremely expensive.In low-resource settings where annotated samples are scarce,direct fine-tuning tends to cause overfitting.To address these challenges,we introduce Dynamic LowRank Adapter(DyLoRA),a lightweight fine-tuning framework tailored specifically for the TAD task.Built upon the Low-Rank Adaptation(LoRA)architecture,DyLoRA adapts only the key layers of the pretrained model via low-rank decomposition,reducing the number of trainable parameters to less than 5%of full fine-tuning methods.This significantly lowers memory consumption and mitigates overfitting in low-resource settings.Notably,DyLoRA enhances the temporal modeling capability of pretrained models by optimizing temporal dimension weights,thereby alleviating the representation misalignment of temporal features.Experimental results demonstrate that DyLoRA-TAD achieves impressive performance,with 73.9%mAP on THUMOS14,39.52%on ActivityNet-1.3,and 28.2%on Charades,substantially surpassing the best traditional feature-based methods.展开更多
Ulcerative colitis (UC) is a chronic inflammatory bowel disease characterized byclinical symptoms of diarrhea and mucopurulent bloody stools, and its incidenceis increasing globally. The etiology and pathogenesis of U...Ulcerative colitis (UC) is a chronic inflammatory bowel disease characterized byclinical symptoms of diarrhea and mucopurulent bloody stools, and its incidenceis increasing globally. The etiology and pathogenesis of UC remain elusive. Currenttherapeutic approaches, including anti-inflammatory, immunosuppressiveand immunomodulating agents, are often limited in efficacy and frequently associatedwith adverse drug reactions. Therefore, there is an urgent need to developsafer and more effective treatment strategies to address the limitations of existingtherapies. Scutellaria baicalensis Georgi (HQ), a traditional Chinese medicinal herb,has been employed in the treatment of UC for over 2000 years. Recent studieshave demonstrated that HQ contains multiple active components capable oftreating UC through anti-inflammation, immune modulation, intestinal barrierprotection, antioxidant activity, and regulation of the gut microbiota. This paperreviews recent studies on the mechanism of action and clinical trials of HQ intreating UC based on relevant literature, with the aim of providing valuable insightsinto future treatment approaches.展开更多
Deep neural networks have achieved excellent classification results on several computer vision benchmarks.This has led to the popularity of machine learning as a service,where trained algorithms are hosted on the clou...Deep neural networks have achieved excellent classification results on several computer vision benchmarks.This has led to the popularity of machine learning as a service,where trained algorithms are hosted on the cloud and inference can be obtained on real-world data.In most applications,it is important to compress the vision data due to the enormous bandwidth and memory requirements.Video codecs exploit spatial and temporal correlations to achieve high compression ratios,but they are computationally expensive.This work computes the motion fields between consecutive frames to facilitate the efficient classification of videos.However,contrary to the normal practice of reconstructing the full-resolution frames through motion compensation,this work proposes to infer the class label from the block-based computed motion fields directly.Motion fields are a richer and more complex representation of motion vectors,where each motion vector carries the magnitude and direction information.This approach has two advantages:the cost of motion compensation and video decoding is avoided,and the dimensions of the input signal are highly reduced.This results in a shallower network for classification.The neural network can be trained using motion vectors in two ways:complex representations and magnitude-direction pairs.The proposed work trains a convolutional neural network on the direction and magnitude tensors of the motion fields.Our experimental results show 20×faster convergence during training,reduced overfitting,and accelerated inference on a hand gesture recognition dataset compared to full-resolution and downsampled frames.We validate the proposed methodology on the HGds dataset,achieving a testing accuracy of 99.21%,on the HMDB51 dataset,achieving 82.54%accuracy,and on the UCF101 dataset,achieving 97.13%accuracy,outperforming state-of-the-art methods in computational efficiency.展开更多
Background:In 2021,the American College of Medical Genetics and Genomics(ACMG)recommended reporting actionable genotypes in 73 genes associated with diseases for which preventive or therapeutic measures are available....Background:In 2021,the American College of Medical Genetics and Genomics(ACMG)recommended reporting actionable genotypes in 73 genes associated with diseases for which preventive or therapeutic measures are available.Evaluations of the association of actionable genotypes in these genes with life span are currently lacking.展开更多
Offshore structures are constantly subjected to the complex forces of the marine environment,including wind,sea waves,currents,and seismic loadings.Among these,wind and sea wave forces persist throughout the structure...Offshore structures are constantly subjected to the complex forces of the marine environment,including wind,sea waves,currents,and seismic loadings.Among these,wind and sea wave forces persist throughout the structure’s lifetime.This study proposes a dynamic analysis approach that incorporates both time and frequency domain methods to investigate the structural responses of offshore structures under the combined effects of wind and wave forces.A wind wave-pier coupling dynamic model is first developed using a small-scale single pier,with corresponding dynamic equilibrium equations established.Fluctuating wind and sea waves are simulated using the weighted amplitude wave superposition(WAWS)method and linear superposition,respectively.Wind and wave load histories are then derived via Fourier transforms.The structural dynamic responses under different loading scenarios(wind only,wave only,and combined wind and wave)are analyzed using the Newmarkβmethod.Additionally,the effects of varying wind and wave parameters on structural responses are evaluated.The simulation results demonstrate that the structural responses to wind-wave coupling are smaller than the superimposed effects of wind and wave forces acting independently.When wind speeds are relatively low,wave forces dominate structural displacement and serve as the primary source of vibration.展开更多
Grifola frondosa(Maitake)is traditionally valued for its health benefits,with polysaccharides being key bioactive components.This paper investigates a specific subfraction,Fraction D(GFP-D),evaluating its clinical eff...Grifola frondosa(Maitake)is traditionally valued for its health benefits,with polysaccharides being key bioactive components.This paper investigates a specific subfraction,Fraction D(GFP-D),evaluating its clinical effects and mechanisms in immune enhancement,adjunctive anti-tumor activity,and regulation of glucose/lipid metabolism.Three clinical trials were conducted.In an immune study,120 healthy volunteers(CD4+T cell count 500–1000 cells/μL)received 150 mg/day GFP-D for 8 weeks,resulting in significant increases in CD4+T cells(from 632±95 to 812±108 cells/μL,28.5%increase,within the physiological activation range),CD4+/CD8+ratio,NK cell activity,IL-2,and IFN-γ(all P<0.001 vs.placebo).An anti-tumor study with 80 advanced cancer patients(stratified by age,tumor stage,and histotype)showed that adding 1000 mg/day GFP-D to chemotherapy improved objective response rate(52.5%vs.30.0%,P=0.036,95%CI:1.02–3.87),one-year progression-free survival(55.8%vs.33.3%,P=0.022),and preserved immune parameters versus chemotherapy alone.A metabolic study in 90 type 2 diabetes patients found that 400 mg/day GFP-D for 12 weeks significantly lowered fasting glucose,HbA1c,total cholesterol,triglycerides,and LDL-C,while raising HDL-C(from 1.0±0.2 to 1.2±0.2 mmol/L,20%increase,supported by increased AMPK phosphorylation).Mechanistically,immune enhancement involves macrophage/dendritic cell activation via Dectin-1/TLR4 receptors(confirmed by increased receptor expression and downstream signaling molecules),promoting cytokine-driven T/NK cell responses.Anti-tumor effects stem from immunomodulation,direct induction of cancer cell apoptosis(via mitochondrial/caspase pathways,verified by increased Bax/Bcl-2 ratio and caspase-3 activation),and angiogenesis inhibition by downregulating VEGF.Metabolic benefits are linked to AMPK pathway activation in liver/muscle(confirmed by increased p-AMPK/AMPK ratio),enhancing glucose uptake and inhibiting gluconeogenesis/lipogenesis,alongside modulation of gut microbiota(increased Bifidobacterium and Lactobacillus abundance).All trials reported no severe adverse events related to GFP-D;liver/kidney function parameters(ALT,AST,creatinine,urea nitrogen)remained within normal ranges throughout the intervention.Collectively,GFP-D emerges as a multi-functional bioactive agent with substantial therapeutic potential.展开更多
Branded Matchmaking Services Integrated with Rural Revitalization Hunan Women's Federation and Hunan Provincial Department of Agriculture and Rural Affairs conducted a rural-matchmaking-demonstration activity rece...Branded Matchmaking Services Integrated with Rural Revitalization Hunan Women's Federation and Hunan Provincial Department of Agriculture and Rural Affairs conducted a rural-matchmaking-demonstration activity recently in Shibadong,a village in Xiangxi,a region in Central China's Hunan Province.More than 120 young,single people attended.展开更多
The multi-target assignment(MTA)problem,a crucial challenge in command control,mission planning,and a fundamental research focus in military operations,has garnered significant attention over the years.Extensively stu...The multi-target assignment(MTA)problem,a crucial challenge in command control,mission planning,and a fundamental research focus in military operations,has garnered significant attention over the years.Extensively studied across various domains such as land,sea,air,space,and electronics,the MTA problem has led to the emergence of numerous models and algorithms.To delve deeper into this field,this paper starts by conducting a bibliometric analysis on 463 Scopus database papers using CiteSpace software.The analysis includes examining keyword clustering,co-occurrence,and burst,with visual representations of the results.Following this,the paper provides an overview of current classification and modeling techniques for addressing the MTA problem,distinguishing between static multi-target assignment(SMTA)and dynamic multi-target assignment(DMTA).Subsequently,existing solution algorithms for the MTA problem are reviewed,generally falling into three categories:exact algorithms,heuristic algorithms,and machine learning algorithms.Finally,a development framework is proposed based on the"HIGH"model(high-speed,integrated,great,harmonious)to guide future research and intelligent weapon system development concerning the MTA problem.This framework emphasizes application scenarios,modeling mechanisms,solution algorithms,and system efficiency to offer a roadmap for future exploration in this area.展开更多
Coal direct liquefaction technology is a crucial contemporary coal chemical technology for efficient and clean use of coal resources. The development of direct coal liquefaction technology and the promotion of alterna...Coal direct liquefaction technology is a crucial contemporary coal chemical technology for efficient and clean use of coal resources. The development of direct coal liquefaction technology and the promotion of alternative energy sources are important measures to guarantee energy security and economic security. However, several challenges need to be addressed, including low conversion rate, inadequate oil yield, significant coking, demanding reaction conditions, and high energy consumption. Extensive research has been conducted on these issues, but further exploration is required in certain aspects such as pyrolysis of macromolecules during the liquefaction process, hydrogen activation, catalysts' performance and stability, solvent hydrogenation, as well as interactions between free radicals to understand their mechanisms better. This paper presents a comprehensive analysis of the design strategy for efficient catalysts in coal liquefaction, encompassing the mechanism of coal liquefaction, catalyst construction,and enhancement of catalytic conversion efficiency. It serves as a comprehensive guide for further research endeavors. Firstly, it systematically summarizes the conversion mechanism of direct coal liquefaction, provides detailed descriptions of various catalyst design strategies, and especially outlines the catalytic mechanism. Furthermore, it addresses the challenges and prospects associated with constructing efficient catalysts for direct coal liquefaction based on an understanding of their action mechanisms.展开更多
This article focuses on the clinical efficacy and mechanism of action of heatclearing and detoxifying traditional Chinese medicines(TCMs)in the treatment of erosive gastritis,providing a reference for the treatment of...This article focuses on the clinical efficacy and mechanism of action of heatclearing and detoxifying traditional Chinese medicines(TCMs)in the treatment of erosive gastritis,providing a reference for the treatment of this disease.In the clinical treatment of erosive gastritis,TCM combinations such as Qing Gastric San,Semixia Diarrheal Heart Soup,and single-flavored heat-clearing and detoxifying drugs such as dandelion and Huanglian have specific efficacies and effectively improve the patient's symptoms,including killing or inhibiting Helicobacter pylori,reducing inflammatory reactions,protecting the gastric mucosa,inhibiting gastric acid secretion,regulating gastrointestinal hormones,and regulating immune function,playing therapeutic roles through multi-level and multi-target mechanisms.Thus,heat-clearing and detoxifying TCMs have broad application prospects in clinical practice for erosive gastritis.展开更多
It is shown that time asymmetry is essential for deriving thermodynamic law and arises from the turnover of energy while reducing its information content and driving entropy increase. A dynamically interpreted princip...It is shown that time asymmetry is essential for deriving thermodynamic law and arises from the turnover of energy while reducing its information content and driving entropy increase. A dynamically interpreted principle of least action enables time asymmetry and time flow as a generation of action and redefines useful energy as an information system which implements a form of acting information. This is demonstrated using a basic formula, originally applied for time symmetry/energy conservation considerations, relating time asymmetry (which is conventionally denied but here expressly allowed), to energy behaviour. The results derived then explained that a dynamic energy is driving time asymmetry. It is doing it by decreasing the information content of useful energy, thus generating action and entropy increase, explaining action-time as an information phenomenon. Thermodynamic laws follow directly. The formalism derived readily explains what energy is, why it is conserved (1st law of thermodynamics), why entropy increases (2nd law) and that maximum entropy production within the restraints of the system controls self-organized processes of non-linear irreversible thermodynamics. The general significance of the principle of least action arises from its role of controlling the action generating oriented time of nature. These results contrast with present understanding of time neutrality and clock-time, which are here considered a source of paradoxes, intellectual contradictions and dead-end roads in models explaining nature and the universe.展开更多
Objective: To explore the effect of Health Action Process Approach (HAPA) theory in patients with type D personality psoriasis. Methods: A total of 66 patients with type D personality psoriasis admitted to the dermato...Objective: To explore the effect of Health Action Process Approach (HAPA) theory in patients with type D personality psoriasis. Methods: A total of 66 patients with type D personality psoriasis admitted to the dermatology department of a top-three hospital in Jingzhou City from November 2022 to July 2023 were selected and divided into control group and test group with 33 cases in each group by random number table method. The control group received routine health education, and the experimental group received health education based on the HAPA theory. Chronic disease self-efficacy scale, hospital anxiety and depression scale and skin disease quality of life scale were used to evaluate the effect of intervention. Results: After 3 months of intervention, the scores of self-efficacy in experimental group were higher than those in control group (P P Conclusion: Health education based on the theory of HAPA can enhance the self-efficacy of patients with type D personality psoriasis, relieve negative emotions and improve their quality of life.展开更多
The task of student action recognition in the classroom is to precisely capture and analyze the actions of students in classroom videos,providing a foundation for realizing intelligent and accurate teaching.However,th...The task of student action recognition in the classroom is to precisely capture and analyze the actions of students in classroom videos,providing a foundation for realizing intelligent and accurate teaching.However,the complex nature of the classroom environment has added challenges and difficulties in the process of student action recognition.In this research article,with regard to the circumstances where students are prone to be occluded and classroom computing resources are restricted in real classroom scenarios,a lightweight multi-modal fusion action recognition approach is put forward.This proposed method is capable of enhancing the accuracy of student action recognition while concurrently diminishing the number of parameters of the model and the Computation Amount,thereby achieving a more efficient and accurate recognition performance.In the feature extraction stage,this method fuses the keypoint heatmap with the RGB(Red-Green-Blue color model)image.In order to fully utilize the unique information of different modalities for feature complementarity,a Feature Fusion Module(FFE)is introduced.The FFE encodes and fuses the unique features of the two modalities during the feature extraction process.This fusion strategy not only achieves fusion and complementarity between modalities,but also improves the overall model performance.Furthermore,to reduce the computational load and parameter scale of the model,we use keypoint information to crop RGB images.At the same time,the first three networks of the lightweight feature extraction network X3D are used to extract dual-branch features.These methods significantly reduce the computational load and parameter scale.The number of parameters of the model is 1.40 million,and the computation amount is 5.04 billion floating-point operations per second(GFLOPs),achieving an efficient lightweight design.In the Student Classroom Action Dataset(SCAD),the accuracy of the model is 88.36%.In NTU 60(Nanyang Technological University Red-Green-Blue-Depth RGB+Ddataset with 60 categories),the accuracies on X-Sub(The people in the training set are different from those in the test set)and X-View(The perspectives of the training set and the test set are different)are 95.76%and 98.82%,respectively.On the NTU 120 dataset(Nanyang Technological University Red-Green-Blue-Depth dataset with 120 categories),RGB+Dthe accuracies on X-Sub and X-Set(the perspectives of the training set and the test set are different)are 91.97%and 93.45%,respectively.The model has achieved a balance in terms of accuracy,computation amount,and the number of parameters.展开更多
On the morning of May 31st,the parallel forum"Ecological Actions to Carry Forward the Shared Values of Mankind,"as part of the 4th Dialogue on Exchanges and Mutual Learning among Civilisations,was held in Du...On the morning of May 31st,the parallel forum"Ecological Actions to Carry Forward the Shared Values of Mankind,"as part of the 4th Dialogue on Exchanges and Mutual Learning among Civilisations,was held in Dunhuang.More than 50 experts and scholars from different countries,including China,Kenya and Japan,engaged in indepth discussions on the theme.展开更多
ln order to improve the level of investment promotion and redouble effortsto enhance services,on February l9th,the 2025 Action Plan for StabilizingForeign lnvestment was released,proposing 20 measures in four aspects....ln order to improve the level of investment promotion and redouble effortsto enhance services,on February l9th,the 2025 Action Plan for StabilizingForeign lnvestment was released,proposing 20 measures in four aspects.Cur-rently,with increasing uncertainties in the external environment,China facesmultple difficulties and challenges in attracting foreign investment.展开更多
Response prediction is a fundamental yet challenging task in aeronautical engineering,requiring an accurate selection of sensor positions correlated with the target responses to achieve precise predictions. Unfortunat...Response prediction is a fundamental yet challenging task in aeronautical engineering,requiring an accurate selection of sensor positions correlated with the target responses to achieve precise predictions. Unfortunately, in large-scale structures, the rigorous selection of reliable sensor candidates for multi-target responses remains largely unexplored. In this paper, we propose a flexible and generalized framework for selecting the most relevant sensors to the multi-target response and predicting the target response, referred to as the Fast-aware Multi-Target Response Prediction(FMTRP) approach in the spirit of divide-and-conquer. Specifically, first, a multi-task learning module is designed to predict multi-point response tasks at the same time. Simultaneously, we meticulously devise adaptive mechanisms to facilitate loss-term reweighting and encourage prioritization of challenging tasks in multiple prediction tasks. Second, to ensure ease of interpretation,we introduce a hybrid penalty to select sensors at the group-sparsity, individual-sparsity and element-sparsity levels. Finally, due to the substantial number of candidate sensors posing a significant computational burden, we develop a more efficient search strategy and support computation to make the proposed approach applicable in practice, leading to substantial runtime improvements. Extensive experiments on aircraft standard model response datasets and large airliner test flight datasets validate the effectiveness of the proposed approach in identifying sensor locations and simultaneously predicting responses at multiple points. Compared to state-of-the-art methods,the proposed approach achieves an accuracy of over 99% in sinusoidal excitation and exhibits the shortest runtime(3.514 s).展开更多
基金supported by the National Key Research and Development Program of China,No.2023YFC3603705(to DX)the National Natural Science Foundation of China,No.82302866(to YZ).
文摘After spinal cord injury,impairment of the sensorimotor circuit can lead to dysfunction in the motor,sensory,proprioceptive,and autonomic nervous systems.Functional recovery is often hindered by constraints on the timing of interventions,combined with the limitations of current methods.To address these challenges,various techniques have been developed to aid in the repair and reconstruction of neural circuits at different stages of injury.Notably,neuromodulation has garnered considerable attention for its potential to enhance nerve regeneration,provide neuroprotection,restore neurons,and regulate the neural reorganization of circuits within the cerebral cortex and corticospinal tract.To improve the effectiveness of these interventions,the implementation of multitarget early interventional neuromodulation strategies,such as electrical and magnetic stimulation,is recommended to enhance functional recovery across different phases of nerve injury.This review concisely outlines the challenges encountered following spinal cord injury,synthesizes existing neurostimulation techniques while emphasizing neuroprotection,repair,and regeneration of impaired connections,and advocates for multi-targeted,task-oriented,and timely interventions.
基金supported by National Training Program of Innovation and Entrepreneurship for Undergraduates(202510163044).
文摘The combination of Daphnes Cortex(DC)and Liquorice Root(LR),two traditional Chinese medicinal herbs,has shown significant therapeutic effects on rheumatoid arthritis(RA),but its synergistic mechanism of action remains to be elucidated.Employing a network pharmacology and molecular docking approach,this study systematically investigated the synergistic mechanism of the herb pair DC and LR in RA treatment.Active components and their corresponding targets were retrieved from the TCMSP database and relevant literature,and RA-related targets were collected from established disease databases.A total of 73 overlapping targets between DC-LR and RA were identified,among which core targets such as AKT1,TNF,and CASP3 were highlighted.GO and KEGG enrichment analyses revealed that these targets are involved in biological processes such as oxidative stress response and cell migration,and are significantly enriched in key pathways including HIF-1,TNF,and PI3K-Akt signaling pathways.Compatibility analysis further revealed that the combination of DC and LR may enhance therapeutic effects through synergistic regulation of shared targets and complementary modulation of upstream and downstream pathway components.Molecular docking confirmed strong binding affinities between core active components and key targets.This study provides a multi-dimensional“component-target-pathway”perspective on the potential synergistic anti-RA mechanism of the DC-LR herb pair,offering a theoretical basis for further experimental validation and clinical application.
基金supported by the National Natural Science Foundation of China(Grant No.62266054)the Major Science and Technology Project of Yunnan Province(Grant No.202402AD080002)the Scientific Research Fund of the Yunnan Provincial Department of Education(Grant No.2025Y0302).
文摘End-to-end Temporal Action Detection(TAD)has achieved remarkable progress in recent years,driven by innovations in model architectures and the emergence of Video Foundation Models(VFMs).However,existing TAD methods that perform full fine-tuning of pretrained video models often incur substantial computational costs,which become particularly pronounced when processing long video sequences.Moreover,the need for precise temporal boundary annotations makes data labeling extremely expensive.In low-resource settings where annotated samples are scarce,direct fine-tuning tends to cause overfitting.To address these challenges,we introduce Dynamic LowRank Adapter(DyLoRA),a lightweight fine-tuning framework tailored specifically for the TAD task.Built upon the Low-Rank Adaptation(LoRA)architecture,DyLoRA adapts only the key layers of the pretrained model via low-rank decomposition,reducing the number of trainable parameters to less than 5%of full fine-tuning methods.This significantly lowers memory consumption and mitigates overfitting in low-resource settings.Notably,DyLoRA enhances the temporal modeling capability of pretrained models by optimizing temporal dimension weights,thereby alleviating the representation misalignment of temporal features.Experimental results demonstrate that DyLoRA-TAD achieves impressive performance,with 73.9%mAP on THUMOS14,39.52%on ActivityNet-1.3,and 28.2%on Charades,substantially surpassing the best traditional feature-based methods.
基金Supported by National Natural Science Foundation of China,No.82374200Construction of Traditional Chinese Medicine Inheritance and Innovation Development Demonstration Pilot Projects in Pudong New Area-High-Level Research-Oriented Traditional Chinese Medicine Hospital Construction,No.YC-2023-0901.
文摘Ulcerative colitis (UC) is a chronic inflammatory bowel disease characterized byclinical symptoms of diarrhea and mucopurulent bloody stools, and its incidenceis increasing globally. The etiology and pathogenesis of UC remain elusive. Currenttherapeutic approaches, including anti-inflammatory, immunosuppressiveand immunomodulating agents, are often limited in efficacy and frequently associatedwith adverse drug reactions. Therefore, there is an urgent need to developsafer and more effective treatment strategies to address the limitations of existingtherapies. Scutellaria baicalensis Georgi (HQ), a traditional Chinese medicinal herb,has been employed in the treatment of UC for over 2000 years. Recent studieshave demonstrated that HQ contains multiple active components capable oftreating UC through anti-inflammation, immune modulation, intestinal barrierprotection, antioxidant activity, and regulation of the gut microbiota. This paperreviews recent studies on the mechanism of action and clinical trials of HQ intreating UC based on relevant literature, with the aim of providing valuable insightsinto future treatment approaches.
基金Supported by Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2025R896).
文摘Deep neural networks have achieved excellent classification results on several computer vision benchmarks.This has led to the popularity of machine learning as a service,where trained algorithms are hosted on the cloud and inference can be obtained on real-world data.In most applications,it is important to compress the vision data due to the enormous bandwidth and memory requirements.Video codecs exploit spatial and temporal correlations to achieve high compression ratios,but they are computationally expensive.This work computes the motion fields between consecutive frames to facilitate the efficient classification of videos.However,contrary to the normal practice of reconstructing the full-resolution frames through motion compensation,this work proposes to infer the class label from the block-based computed motion fields directly.Motion fields are a richer and more complex representation of motion vectors,where each motion vector carries the magnitude and direction information.This approach has two advantages:the cost of motion compensation and video decoding is avoided,and the dimensions of the input signal are highly reduced.This results in a shallower network for classification.The neural network can be trained using motion vectors in two ways:complex representations and magnitude-direction pairs.The proposed work trains a convolutional neural network on the direction and magnitude tensors of the motion fields.Our experimental results show 20×faster convergence during training,reduced overfitting,and accelerated inference on a hand gesture recognition dataset compared to full-resolution and downsampled frames.We validate the proposed methodology on the HGds dataset,achieving a testing accuracy of 99.21%,on the HMDB51 dataset,achieving 82.54%accuracy,and on the UCF101 dataset,achieving 97.13%accuracy,outperforming state-of-the-art methods in computational efficiency.
文摘Background:In 2021,the American College of Medical Genetics and Genomics(ACMG)recommended reporting actionable genotypes in 73 genes associated with diseases for which preventive or therapeutic measures are available.Evaluations of the association of actionable genotypes in these genes with life span are currently lacking.
基金Project(2022YFB2302700)supported by the National Key Research and Development Program of China。
文摘Offshore structures are constantly subjected to the complex forces of the marine environment,including wind,sea waves,currents,and seismic loadings.Among these,wind and sea wave forces persist throughout the structure’s lifetime.This study proposes a dynamic analysis approach that incorporates both time and frequency domain methods to investigate the structural responses of offshore structures under the combined effects of wind and wave forces.A wind wave-pier coupling dynamic model is first developed using a small-scale single pier,with corresponding dynamic equilibrium equations established.Fluctuating wind and sea waves are simulated using the weighted amplitude wave superposition(WAWS)method and linear superposition,respectively.Wind and wave load histories are then derived via Fourier transforms.The structural dynamic responses under different loading scenarios(wind only,wave only,and combined wind and wave)are analyzed using the Newmarkβmethod.Additionally,the effects of varying wind and wave parameters on structural responses are evaluated.The simulation results demonstrate that the structural responses to wind-wave coupling are smaller than the superimposed effects of wind and wave forces acting independently.When wind speeds are relatively low,wave forces dominate structural displacement and serve as the primary source of vibration.
文摘Grifola frondosa(Maitake)is traditionally valued for its health benefits,with polysaccharides being key bioactive components.This paper investigates a specific subfraction,Fraction D(GFP-D),evaluating its clinical effects and mechanisms in immune enhancement,adjunctive anti-tumor activity,and regulation of glucose/lipid metabolism.Three clinical trials were conducted.In an immune study,120 healthy volunteers(CD4+T cell count 500–1000 cells/μL)received 150 mg/day GFP-D for 8 weeks,resulting in significant increases in CD4+T cells(from 632±95 to 812±108 cells/μL,28.5%increase,within the physiological activation range),CD4+/CD8+ratio,NK cell activity,IL-2,and IFN-γ(all P<0.001 vs.placebo).An anti-tumor study with 80 advanced cancer patients(stratified by age,tumor stage,and histotype)showed that adding 1000 mg/day GFP-D to chemotherapy improved objective response rate(52.5%vs.30.0%,P=0.036,95%CI:1.02–3.87),one-year progression-free survival(55.8%vs.33.3%,P=0.022),and preserved immune parameters versus chemotherapy alone.A metabolic study in 90 type 2 diabetes patients found that 400 mg/day GFP-D for 12 weeks significantly lowered fasting glucose,HbA1c,total cholesterol,triglycerides,and LDL-C,while raising HDL-C(from 1.0±0.2 to 1.2±0.2 mmol/L,20%increase,supported by increased AMPK phosphorylation).Mechanistically,immune enhancement involves macrophage/dendritic cell activation via Dectin-1/TLR4 receptors(confirmed by increased receptor expression and downstream signaling molecules),promoting cytokine-driven T/NK cell responses.Anti-tumor effects stem from immunomodulation,direct induction of cancer cell apoptosis(via mitochondrial/caspase pathways,verified by increased Bax/Bcl-2 ratio and caspase-3 activation),and angiogenesis inhibition by downregulating VEGF.Metabolic benefits are linked to AMPK pathway activation in liver/muscle(confirmed by increased p-AMPK/AMPK ratio),enhancing glucose uptake and inhibiting gluconeogenesis/lipogenesis,alongside modulation of gut microbiota(increased Bifidobacterium and Lactobacillus abundance).All trials reported no severe adverse events related to GFP-D;liver/kidney function parameters(ALT,AST,creatinine,urea nitrogen)remained within normal ranges throughout the intervention.Collectively,GFP-D emerges as a multi-functional bioactive agent with substantial therapeutic potential.
文摘Branded Matchmaking Services Integrated with Rural Revitalization Hunan Women's Federation and Hunan Provincial Department of Agriculture and Rural Affairs conducted a rural-matchmaking-demonstration activity recently in Shibadong,a village in Xiangxi,a region in Central China's Hunan Province.More than 120 young,single people attended.
基金the financial support provided by the National Natural Science Foundation of China(NSFC)(Grant No.62173274)the National Key R&D Program of China(Grant No.2019YFA0405300)+4 种基金the Natural Science Foundation of Hunan Province of China(Grant No.2021JJ10045)the Practice and Innovation Funds for Graduate Students of Northwestern Polytechnical University(Grant No.PF2023046)the Open Research Subject of State Key Laboratory of Intelligent Game(Grant No.ZBKF-24-01)the Postdoctoral Fellowship Program of CPSF(No.GZB20240989)the China Postdoctoral Science Foundation(Grant No.2024M754304)。
文摘The multi-target assignment(MTA)problem,a crucial challenge in command control,mission planning,and a fundamental research focus in military operations,has garnered significant attention over the years.Extensively studied across various domains such as land,sea,air,space,and electronics,the MTA problem has led to the emergence of numerous models and algorithms.To delve deeper into this field,this paper starts by conducting a bibliometric analysis on 463 Scopus database papers using CiteSpace software.The analysis includes examining keyword clustering,co-occurrence,and burst,with visual representations of the results.Following this,the paper provides an overview of current classification and modeling techniques for addressing the MTA problem,distinguishing between static multi-target assignment(SMTA)and dynamic multi-target assignment(DMTA).Subsequently,existing solution algorithms for the MTA problem are reviewed,generally falling into three categories:exact algorithms,heuristic algorithms,and machine learning algorithms.Finally,a development framework is proposed based on the"HIGH"model(high-speed,integrated,great,harmonious)to guide future research and intelligent weapon system development concerning the MTA problem.This framework emphasizes application scenarios,modeling mechanisms,solution algorithms,and system efficiency to offer a roadmap for future exploration in this area.
基金National Natural Science Foundation of China (No. 22208273)Tianchi Talent Plan of Xinjiang Uygur Autonomous RegionPostdoctoral Fellowship Program of CPSF under Grant Number GZC20240428。
文摘Coal direct liquefaction technology is a crucial contemporary coal chemical technology for efficient and clean use of coal resources. The development of direct coal liquefaction technology and the promotion of alternative energy sources are important measures to guarantee energy security and economic security. However, several challenges need to be addressed, including low conversion rate, inadequate oil yield, significant coking, demanding reaction conditions, and high energy consumption. Extensive research has been conducted on these issues, but further exploration is required in certain aspects such as pyrolysis of macromolecules during the liquefaction process, hydrogen activation, catalysts' performance and stability, solvent hydrogenation, as well as interactions between free radicals to understand their mechanisms better. This paper presents a comprehensive analysis of the design strategy for efficient catalysts in coal liquefaction, encompassing the mechanism of coal liquefaction, catalyst construction,and enhancement of catalytic conversion efficiency. It serves as a comprehensive guide for further research endeavors. Firstly, it systematically summarizes the conversion mechanism of direct coal liquefaction, provides detailed descriptions of various catalyst design strategies, and especially outlines the catalytic mechanism. Furthermore, it addresses the challenges and prospects associated with constructing efficient catalysts for direct coal liquefaction based on an understanding of their action mechanisms.
基金Supported by National Science and Technology Major Project,No.2024ZD0521002The Innovation Team Project of Traditional Chinese Medicine of Liaoning Province,No.LNZYYCXTD-CCCX-003+1 种基金General Program of the National Natural Science Foundation of China,No.82074296Construction Project of Inheritance Studios of Famous Chinese Medicine Experts in China,No.[2022]No.75.
文摘This article focuses on the clinical efficacy and mechanism of action of heatclearing and detoxifying traditional Chinese medicines(TCMs)in the treatment of erosive gastritis,providing a reference for the treatment of this disease.In the clinical treatment of erosive gastritis,TCM combinations such as Qing Gastric San,Semixia Diarrheal Heart Soup,and single-flavored heat-clearing and detoxifying drugs such as dandelion and Huanglian have specific efficacies and effectively improve the patient's symptoms,including killing or inhibiting Helicobacter pylori,reducing inflammatory reactions,protecting the gastric mucosa,inhibiting gastric acid secretion,regulating gastrointestinal hormones,and regulating immune function,playing therapeutic roles through multi-level and multi-target mechanisms.Thus,heat-clearing and detoxifying TCMs have broad application prospects in clinical practice for erosive gastritis.
文摘It is shown that time asymmetry is essential for deriving thermodynamic law and arises from the turnover of energy while reducing its information content and driving entropy increase. A dynamically interpreted principle of least action enables time asymmetry and time flow as a generation of action and redefines useful energy as an information system which implements a form of acting information. This is demonstrated using a basic formula, originally applied for time symmetry/energy conservation considerations, relating time asymmetry (which is conventionally denied but here expressly allowed), to energy behaviour. The results derived then explained that a dynamic energy is driving time asymmetry. It is doing it by decreasing the information content of useful energy, thus generating action and entropy increase, explaining action-time as an information phenomenon. Thermodynamic laws follow directly. The formalism derived readily explains what energy is, why it is conserved (1st law of thermodynamics), why entropy increases (2nd law) and that maximum entropy production within the restraints of the system controls self-organized processes of non-linear irreversible thermodynamics. The general significance of the principle of least action arises from its role of controlling the action generating oriented time of nature. These results contrast with present understanding of time neutrality and clock-time, which are here considered a source of paradoxes, intellectual contradictions and dead-end roads in models explaining nature and the universe.
文摘Objective: To explore the effect of Health Action Process Approach (HAPA) theory in patients with type D personality psoriasis. Methods: A total of 66 patients with type D personality psoriasis admitted to the dermatology department of a top-three hospital in Jingzhou City from November 2022 to July 2023 were selected and divided into control group and test group with 33 cases in each group by random number table method. The control group received routine health education, and the experimental group received health education based on the HAPA theory. Chronic disease self-efficacy scale, hospital anxiety and depression scale and skin disease quality of life scale were used to evaluate the effect of intervention. Results: After 3 months of intervention, the scores of self-efficacy in experimental group were higher than those in control group (P P Conclusion: Health education based on the theory of HAPA can enhance the self-efficacy of patients with type D personality psoriasis, relieve negative emotions and improve their quality of life.
基金supported by the National Natural Science Foundation of China under Grant 62107034the Major Science and Technology Project of Yunnan Province(202402AD080002)Yunnan International Joint R&D Center of China-Laos-Thailand Educational Digitalization(202203AP140006).
文摘The task of student action recognition in the classroom is to precisely capture and analyze the actions of students in classroom videos,providing a foundation for realizing intelligent and accurate teaching.However,the complex nature of the classroom environment has added challenges and difficulties in the process of student action recognition.In this research article,with regard to the circumstances where students are prone to be occluded and classroom computing resources are restricted in real classroom scenarios,a lightweight multi-modal fusion action recognition approach is put forward.This proposed method is capable of enhancing the accuracy of student action recognition while concurrently diminishing the number of parameters of the model and the Computation Amount,thereby achieving a more efficient and accurate recognition performance.In the feature extraction stage,this method fuses the keypoint heatmap with the RGB(Red-Green-Blue color model)image.In order to fully utilize the unique information of different modalities for feature complementarity,a Feature Fusion Module(FFE)is introduced.The FFE encodes and fuses the unique features of the two modalities during the feature extraction process.This fusion strategy not only achieves fusion and complementarity between modalities,but also improves the overall model performance.Furthermore,to reduce the computational load and parameter scale of the model,we use keypoint information to crop RGB images.At the same time,the first three networks of the lightweight feature extraction network X3D are used to extract dual-branch features.These methods significantly reduce the computational load and parameter scale.The number of parameters of the model is 1.40 million,and the computation amount is 5.04 billion floating-point operations per second(GFLOPs),achieving an efficient lightweight design.In the Student Classroom Action Dataset(SCAD),the accuracy of the model is 88.36%.In NTU 60(Nanyang Technological University Red-Green-Blue-Depth RGB+Ddataset with 60 categories),the accuracies on X-Sub(The people in the training set are different from those in the test set)and X-View(The perspectives of the training set and the test set are different)are 95.76%and 98.82%,respectively.On the NTU 120 dataset(Nanyang Technological University Red-Green-Blue-Depth dataset with 120 categories),RGB+Dthe accuracies on X-Sub and X-Set(the perspectives of the training set and the test set are different)are 91.97%and 93.45%,respectively.The model has achieved a balance in terms of accuracy,computation amount,and the number of parameters.
文摘On the morning of May 31st,the parallel forum"Ecological Actions to Carry Forward the Shared Values of Mankind,"as part of the 4th Dialogue on Exchanges and Mutual Learning among Civilisations,was held in Dunhuang.More than 50 experts and scholars from different countries,including China,Kenya and Japan,engaged in indepth discussions on the theme.
文摘ln order to improve the level of investment promotion and redouble effortsto enhance services,on February l9th,the 2025 Action Plan for StabilizingForeign lnvestment was released,proposing 20 measures in four aspects.Cur-rently,with increasing uncertainties in the external environment,China facesmultple difficulties and challenges in attracting foreign investment.
基金sponsored by the Innovation Foundation for National Natural Science Foundation of China(No.11872312)。
文摘Response prediction is a fundamental yet challenging task in aeronautical engineering,requiring an accurate selection of sensor positions correlated with the target responses to achieve precise predictions. Unfortunately, in large-scale structures, the rigorous selection of reliable sensor candidates for multi-target responses remains largely unexplored. In this paper, we propose a flexible and generalized framework for selecting the most relevant sensors to the multi-target response and predicting the target response, referred to as the Fast-aware Multi-Target Response Prediction(FMTRP) approach in the spirit of divide-and-conquer. Specifically, first, a multi-task learning module is designed to predict multi-point response tasks at the same time. Simultaneously, we meticulously devise adaptive mechanisms to facilitate loss-term reweighting and encourage prioritization of challenging tasks in multiple prediction tasks. Second, to ensure ease of interpretation,we introduce a hybrid penalty to select sensors at the group-sparsity, individual-sparsity and element-sparsity levels. Finally, due to the substantial number of candidate sensors posing a significant computational burden, we develop a more efficient search strategy and support computation to make the proposed approach applicable in practice, leading to substantial runtime improvements. Extensive experiments on aircraft standard model response datasets and large airliner test flight datasets validate the effectiveness of the proposed approach in identifying sensor locations and simultaneously predicting responses at multiple points. Compared to state-of-the-art methods,the proposed approach achieves an accuracy of over 99% in sinusoidal excitation and exhibits the shortest runtime(3.514 s).
