In recent years,skeleton-based action recognition has made great achievements in Computer Vision.A graph convolutional network(GCN)is effective for action recognition,modelling the human skeleton as a spatio-temporal ...In recent years,skeleton-based action recognition has made great achievements in Computer Vision.A graph convolutional network(GCN)is effective for action recognition,modelling the human skeleton as a spatio-temporal graph.Most GCNs define the graph topology by physical relations of the human joints.However,this predefined graph ignores the spatial relationship between non-adjacent joint pairs in special actions and the behavior dependence between joint pairs,resulting in a low recognition rate for specific actions with implicit correlation between joint pairs.In addition,existing methods ignore the trend correlation between adjacent frames within an action and context clues,leading to erroneous action recognition with similar poses.Therefore,this study proposes a learnable GCN based on behavior dependence,which considers implicit joint correlation by constructing a dynamic learnable graph with extraction of specific behavior dependence of joint pairs.By using the weight relationship between the joint pairs,an adaptive model is constructed.It also designs a self-attention module to obtain their inter-frame topological relationship for exploring the context of actions.Combining the shared topology and the multi-head self-attention map,the module obtains the context-based clue topology to update the dynamic graph convolution,achieving accurate recognition of different actions with similar poses.Detailed experiments on public datasets demonstrate that the proposed method achieves better results and realizes higher quality representation of actions under various evaluation protocols compared to state-of-the-art methods.展开更多
We are writing in response to the article titled“Addressing the needs and rights of sex workers for HIV healthcare services in the Philippines”[1].The article calls for attention on the significant challenges faced ...We are writing in response to the article titled“Addressing the needs and rights of sex workers for HIV healthcare services in the Philippines”[1].The article calls for attention on the significant challenges faced by sex workers in the Philippines in accessing HIV healthcare.We appreciate the article’s effort to examine these issues in depth.We would like to present a constant flow of thoughts in this letter while highlighting the positive aspects,potential obstacles,and additional points that contribute to this ongoing discussion.展开更多
This study presents a general optimal trajectory planning(GOTP)framework for autonomous vehicles(AVs)that can effectively avoid obstacles and guide AVs to complete driving tasks safely and efficiently.Firstly,we emplo...This study presents a general optimal trajectory planning(GOTP)framework for autonomous vehicles(AVs)that can effectively avoid obstacles and guide AVs to complete driving tasks safely and efficiently.Firstly,we employ the fifth-order Bezier curve to generate and smooth the reference path along the road centerline.Cartesian coordinates are then transformed to achieve the curvature continuity of the generated curve.Considering the road constraints and vehicle dynamics,limited polynomial candidate trajectories are generated and smoothed in a curvilinear coordinate system.Furthermore,in selecting the optimal trajectory,we develop a unified and auto-tune objective function based on the principle of least action by employing AVs to simulate drivers’behavior and summarizing their manipulation characteristics of“seeking benefits and avoiding losses.”Finally,by integrating the idea of receding-horizon optimization,the proposed framework is achieved by considering dynamic multi-performance objectives and selecting trajectories that satisfy feasibility,optimality,and adaptability.Extensive simulations and experiments are performed,and the results demonstrate the framework’s feasibility and effectiveness,which avoids both dynamic and static obstacles and applies to various scenarios with multi-source interactive traffic participants.Moreover,we prove that the proposed method can guarantee real-time planning and safety requirements compared to drivers’manipulation.展开更多
Lithium-sulfur battery(LSB)has brought much attention and concern because of high theoretical specific capacity and energy density as one of main competitors for next-generation energy storage systems.The widely comme...Lithium-sulfur battery(LSB)has brought much attention and concern because of high theoretical specific capacity and energy density as one of main competitors for next-generation energy storage systems.The widely commercial application and development of LSB is mainly hindered by serious“shuttle effect”of lithium polysulfides(Li PSs),slow reaction kinetics,notorious lithium dendrites,etc.In various structures of LSB materials,array structured materials,possessing the composition of ordered micro units with the same or similar characteristics of each unit,present excellent application potential for various secondary cells due to some merits such as immobilization of active substances,high specific surface area,appropriate pore sizes,easy modification of functional material surface,accommodated huge volume change,enough facilitated transportation for electrons/lithium ions,and special functional groups strongly adsorbing Li PSs.Thus many novel array structured materials are applied to battery for tackling thorny problems mentioned above.In this review,recent progresses and developments on array structured materials applied in LSBs including preparation ways,collaborative structural designs based on array structures,and action mechanism analyses in improving electrochemical performance and safety are summarized.Meanwhile,we also have detailed discussion for array structured materials in LSBs and constructed the structure-function relationships between array structured materials and battery performances.Lastly,some directions and prospects about preparation ways,functional modifications,and practical applications of array structured materials in LSBs are generalized.We hope the review can attract more researchers'attention and bring more studying on array structured materials for other secondary batteries including LSB.展开更多
Understanding the unstable evolution of railway slopes is the premise for preventing slope failure and ensuring the safe operation of trains.However,as two major factors affecting the stability of railway slopes,few s...Understanding the unstable evolution of railway slopes is the premise for preventing slope failure and ensuring the safe operation of trains.However,as two major factors affecting the stability of railway slopes,few scholars have explored the unstable evolution of railway slopes under the joint action of rainfall-vibration.Based on the model test of sandy soil slope,the unstable evolution process of slope under locomotive vibration,rainfall,and rainfall-vibration joint action conditions was simulated in this paper.By comparing and analyzing the variation trends of soil pressure and water content of slope under these conditions,the change laws of pore pressure under the influence of vibration and rainfall were explored.The main control factors affecting the stability of slope structure under the joint action conditions were further defined.Combined with the slope failure phenomena under these three conditions,the causes of slope instability resulting from each leading factor were clarified.Finally,according to the above conclusions,the unstable evolution of the slope under the rainfall-vibration joint action was determined.The test results show that the unstable evolution process of sandy soil slope,under the rainfall-vibration joint action,can be divided into:rainfall erosion cracking,vibration promotion penetrating,and slope instability sliding three stages.In the process of slope unstable evolution,rainfall and vibration play the roles of inducing and promoting slide respectively.In addition,the deep cracks,which are the premise for the formation of the sliding surface,and the violent irregular fluctuation of soil pressure,which reflects the near penetration of the sliding surface,constitute the instability characteristics of the railway slope together.This paper reveals the unstable evolution of sandy soil slopes under the joint action of rainfall-vibration,hoping to provide the theoretical basis for the early warning and prevention technology of railway slopes.展开更多
Atractylodis Rhizoma comes from the dry rhizome of Atractylis lancea or Atractylodes chinensis in the Compositae family,and it is suitable for preventing and treating diseases such as cold,edema,night blindness and rh...Atractylodis Rhizoma comes from the dry rhizome of Atractylis lancea or Atractylodes chinensis in the Compositae family,and it is suitable for preventing and treating diseases such as cold,edema,night blindness and rheumatic arthralgia.Atractylodin is the main active component extracted and isolated from Atractylodis Rhizoma.A large number of studies have found that atractylodin has excellent drug activity in improving gastrointestinal emptying,anti-inflammation,inhibiting malignant tumor and reducing blood lipid.In this paper,the purification process and pharmacological activity of Atractylodin were summarized to provide a theoretical basis for basic research,clinical application and further development and utilization of atractylodin.展开更多
Alzheimer’s disease (AD) is a neurodegenerative disorder characterized by cognitive impairments in the initial stage, which lead to severe cognitive dysfunction in the later stage. Action observation therapy (AOT) is...Alzheimer’s disease (AD) is a neurodegenerative disorder characterized by cognitive impairments in the initial stage, which lead to severe cognitive dysfunction in the later stage. Action observation therapy (AOT) is a multisensory cognitive rehabilitation technique where the patient initially observes the actions and then tries to perform. The study aimed to examine the impact of AOT along with usual physiotherapy interventions to reduce depression, improve cognition and balance of a patient with AD. A 67 years old patient with AD was selected for this study because the patient has been suffering from depression, dementia, and physical dysfunction along with some other health conditions like diabetes and hypertension. Before starting intervention, a baseline assessment was done through the Beck Depression Inventory (BDI) tool, the Mini-Cog Scale, and the Berg Balance Scale (BBS). The patient received 12 sessions of AOT along with usual physiotherapy interventions thrice a week for four weeks, which included 45 minutes of each session. After four weeks of intervention, the patient demonstrated significant improvement in depression, cognition, and balance, whereas the BDI score declined from moderate 21/63 to mild 15/63 level of depression. The Mini-Cog score improved from 2/5 to 4/5, and the BBS score increased from 18/56 to 37/56. It is concluded that AOT along with usual physiotherapy intervention helps to reduce depression, improve cognition and balance of people with AD.展开更多
The Dirac equation γ<sub>μ</sub>(δ<sub>μ</sub>-eA<sub>μ</sub>)Ψ=mc<sup>2</sup>Ψ describes the bound states of the electron under the action of external potentials...The Dirac equation γ<sub>μ</sub>(δ<sub>μ</sub>-eA<sub>μ</sub>)Ψ=mc<sup>2</sup>Ψ describes the bound states of the electron under the action of external potentials, A<sub>μ</sub>. We assumed that the fundamental form of the Dirac equation γ<sub>μ</sub>(δ<sub>μ</sub>-S<sub>μ</sub>)Ψ=0 should describe the stable particles (the electron, the proton and the dark-matter-particle (dmp)) bound to themselves under the action of their own potentials S<sub>μ</sub>. The new equation reveals that self energy is consequence of self action, it also reveals that the spin angular momentum is consequence of the dynamic structure of the stable particles. The quantitative results are the determination of their relative masses as well as the determination of the electromagnetic coupling constant.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.Methods:We assessed the prevalence of coding and splice variants in genes on the ACMG Secondary Findings,version 3.0(ACMG SF v3.0),list in the genomes of 57,933 Icelanders.We assigned pathogenicity to all reviewed variants using reported evidence in the ClinVar database,the frequency of variants,and their associations with disease to create a manually curated set of actionable genotypes(variants).We assessed the relationship between these genotypes and life span and further examined the specific causes of death among carriers.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
In South Africa,there is a saying,“I am because we are!”This ancient philosophy called ubuntu explains that our humanity is enriched through shared experiences,compassion and a sense of responsibility to others.Simi...In South Africa,there is a saying,“I am because we are!”This ancient philosophy called ubuntu explains that our humanity is enriched through shared experiences,compassion and a sense of responsibility to others.Similarly,the concepts of harmony,interconnectedness and mutual respect are deeply ingrained in the philosophy,values and culture of the Chinese people.展开更多
This article deals with the investigation of the effects of seismic impacts on the design and dimensioning of structures in South Kivu. The starting point is the observation of an ambivalence that can be observed in t...This article deals with the investigation of the effects of seismic impacts on the design and dimensioning of structures in South Kivu. The starting point is the observation of an ambivalence that can be observed in the province, namely the non-consideration of seismic action in the study of structures by both professionals and researchers. The main objective of the study is to show the importance of dynamic analysis of structures in South Kivu. It adopts a meta-analytical approach referring to previous researches on South Kivu and proposes an efficient and optimal method. To arrive at the results, we use Eurocode 7 and 8. In addition, we conducted static analysis using the Coulomb method and dynamic analysis using the Mononobe-Okabe method and compared the results. At Nyabibwe, the results showed that we have a deviation of 24.47% for slip stability, 12.038% for overturning stability and 9.677% for stability against punching through a weight wall.展开更多
In 2021,the 74th World Health Assembly endorsed updates to the WHO's Comprehensive Mental Health Action Plan extending to 2030,including revised indicators to measure progress towards reaching defined targets and ...In 2021,the 74th World Health Assembly endorsed updates to the WHO's Comprehensive Mental Health Action Plan extending to 2030,including revised indicators to measure progress towards reaching defined targets and expanded implementation options for variousfacetsoftheplan.展开更多
Under the combined influence of climate change and human activities,vegetation ecosystem has undergone profound changes.It can be seen that there are obvious differences in the evolution patterns and driving mechanism...Under the combined influence of climate change and human activities,vegetation ecosystem has undergone profound changes.It can be seen that there are obvious differences in the evolution patterns and driving mechanisms of vegetation ecosystem in different historical periods.Therefore,it is urgent to identify and reveal the dominant factors and their contribution rates in the vegetation change cycle.Based on the data of climate elements(sunshine hours,precipitation and temperature),human activities(population intensity and GDP intensity)and other natural factors(altitude,slope and aspect),this study explored the spatial and temporal evolution patterns of vegetation NDVI in the Yellow River Basin of China from 1989 to 2019 through a residual method,a trend analysis,and a gravity center model,and quantitatively distinguished the relative actions of climate change and human activities on vegetation evolution based on Geodetector model.The results showed that the spatial distribution of vegetation NDVI in the Yellow River Basin showed a decreasing trend from southeast to northwest.During 1981-2019,the temporal variation of vegetation NDVI showed an overall increasing trend.The gravity centers of average vegetation NDVI during the study period was distributed in Zhenyuan County,Gansu Province,and the center moved northeastwards from 1981 to 2019.During 1981-2000 and 2001-2019,the proportion of vegetation restoration areas promoted by the combined action of climate change and human activities was the largest.During the study period(1981-2019),the dominant factors influencing vegetation NDVI shifted from natural factors to human activities.These results could provide decision support for the protection and restoration of vegetation ecosystem in the Yellow River Basin.展开更多
In this paper the interaction of tripositive terbium ions (Tb3+) with bovine serum albumin(BSA) has bed investigated in the persence of alkaline earth metals and citric acid (Cil)by using fluorescence spectroscopy.Th...In this paper the interaction of tripositive terbium ions (Tb3+) with bovine serum albumin(BSA) has bed investigated in the persence of alkaline earth metals and citric acid (Cil)by using fluorescence spectroscopy.The results show. that Tb3+, BSA and Cit can form ternary.complex BSA.Tb2.Cit4 in in μ=0.1mol.l NaCl. pH6.3 hexamethylentetramine buffer.Other rareearths are able to compete for the same binding site in HSA with Tb3+. The sequence of competition is can not replace Tb bound to BSA.展开更多
Deep learning-based action classification technology has been applied to various fields,such as social safety,medical services,and sports.Analyzing an action on a practical level requires tracking multiple human bodie...Deep learning-based action classification technology has been applied to various fields,such as social safety,medical services,and sports.Analyzing an action on a practical level requires tracking multiple human bodies in an image in real-time and simultaneously classifying their actions.There are various related studies on the real-time classification of actions in an image.However,existing deep learning-based action classification models have prolonged response speeds,so there is a limit to real-time analysis.In addition,it has low accuracy of action of each object ifmultiple objects appear in the image.Also,it needs to be improved since it has a memory overhead in processing image data.Deep learning-based action classification using one-shot object detection is proposed to overcome the limitations of multiframe-based analysis technology.The proposed method uses a one-shot object detection model and a multi-object tracking algorithm to detect and track multiple objects in the image.Then,a deep learning-based pattern classification model is used to classify the body action of the object in the image by reducing the data for each object to an action vector.Compared to the existing studies,the constructed model shows higher accuracy of 74.95%,and in terms of speed,it offered better performance than the current studies at 0.234 s per frame.The proposed model makes it possible to classify some actions only through action vector learning without additional image learning because of the vector learning feature of the posterior neural network.Therefore,it is expected to contribute significantly to commercializing realistic streaming data analysis technologies,such as CCTV.展开更多
Human Action Recognition(HAR)in uncontrolled environments targets to recognition of different actions froma video.An effective HAR model can be employed for an application like human-computer interaction,health care,p...Human Action Recognition(HAR)in uncontrolled environments targets to recognition of different actions froma video.An effective HAR model can be employed for an application like human-computer interaction,health care,person tracking,and video surveillance.Machine Learning(ML)approaches,specifically,Convolutional Neural Network(CNN)models had beenwidely used and achieved impressive results through feature fusion.The accuracy and effectiveness of these models continue to be the biggest challenge in this field.In this article,a novel feature optimization algorithm,called improved Shark Smell Optimization(iSSO)is proposed to reduce the redundancy of extracted features.This proposed technique is inspired by the behavior ofwhite sharks,and howthey find the best prey in thewhole search space.The proposed iSSOalgorithmdivides the FeatureVector(FV)into subparts,where a search is conducted to find optimal local features fromeach subpart of FV.Once local optimal features are selected,a global search is conducted to further optimize these features.The proposed iSSO algorithm is employed on nine(9)selected CNN models.These CNN models are selected based on their top-1 and top-5 accuracy in ImageNet competition.To evaluate the model,two publicly available datasets UCF-Sports and Hollywood2 are selected.展开更多
Action recognition and detection is an important research topic in computer vision,which can be divided into action recognition and action detection.At present,the distinction between action recognition and action det...Action recognition and detection is an important research topic in computer vision,which can be divided into action recognition and action detection.At present,the distinction between action recognition and action detection is not clear,and the relevant reviews are not comprehensive.Thus,this paper summarized the action recognition and detection methods and datasets based on deep learning to accurately present the research status in this field.Firstly,according to the way that temporal and spatial features are extracted from the model,the commonly used models of action recognition are divided into the two stream models,the temporal models,the spatiotemporal models and the transformer models according to the architecture.And this paper briefly analyzes the characteristics of the four models and introduces the accuracy of various algorithms in common data sets.Then,from the perspective of tasks to be completed,action detection is further divided into temporal action detection and spatiotemporal action detection,and commonly used datasets are introduced.From the perspectives of the twostage method and one-stage method,various algorithms of temporal action detection are reviewed,and the various algorithms of spatiotemporal action detection are summarized in detail.Finally,the relationship between different parts of action recognition and detection is discussed,the difficulties faced by the current research are summarized in detail,and future development was prospected。展开更多
基金supported in part by the 2023 Key Supported Project of the 14th Five Year Plan for Education and Science in Hunan Province with No.ND230795.
文摘In recent years,skeleton-based action recognition has made great achievements in Computer Vision.A graph convolutional network(GCN)is effective for action recognition,modelling the human skeleton as a spatio-temporal graph.Most GCNs define the graph topology by physical relations of the human joints.However,this predefined graph ignores the spatial relationship between non-adjacent joint pairs in special actions and the behavior dependence between joint pairs,resulting in a low recognition rate for specific actions with implicit correlation between joint pairs.In addition,existing methods ignore the trend correlation between adjacent frames within an action and context clues,leading to erroneous action recognition with similar poses.Therefore,this study proposes a learnable GCN based on behavior dependence,which considers implicit joint correlation by constructing a dynamic learnable graph with extraction of specific behavior dependence of joint pairs.By using the weight relationship between the joint pairs,an adaptive model is constructed.It also designs a self-attention module to obtain their inter-frame topological relationship for exploring the context of actions.Combining the shared topology and the multi-head self-attention map,the module obtains the context-based clue topology to update the dynamic graph convolution,achieving accurate recognition of different actions with similar poses.Detailed experiments on public datasets demonstrate that the proposed method achieves better results and realizes higher quality representation of actions under various evaluation protocols compared to state-of-the-art methods.
文摘We are writing in response to the article titled“Addressing the needs and rights of sex workers for HIV healthcare services in the Philippines”[1].The article calls for attention on the significant challenges faced by sex workers in the Philippines in accessing HIV healthcare.We appreciate the article’s effort to examine these issues in depth.We would like to present a constant flow of thoughts in this letter while highlighting the positive aspects,potential obstacles,and additional points that contribute to this ongoing discussion.
基金supported by the National Natural Science Foundation of China(the Key Project,52131201Science Fund for Creative Research Groups,52221005)+1 种基金the China Scholarship Councilthe Joint Laboratory for Internet of Vehicles,Ministry of Education–China MOBILE Communications Corporation。
文摘This study presents a general optimal trajectory planning(GOTP)framework for autonomous vehicles(AVs)that can effectively avoid obstacles and guide AVs to complete driving tasks safely and efficiently.Firstly,we employ the fifth-order Bezier curve to generate and smooth the reference path along the road centerline.Cartesian coordinates are then transformed to achieve the curvature continuity of the generated curve.Considering the road constraints and vehicle dynamics,limited polynomial candidate trajectories are generated and smoothed in a curvilinear coordinate system.Furthermore,in selecting the optimal trajectory,we develop a unified and auto-tune objective function based on the principle of least action by employing AVs to simulate drivers’behavior and summarizing their manipulation characteristics of“seeking benefits and avoiding losses.”Finally,by integrating the idea of receding-horizon optimization,the proposed framework is achieved by considering dynamic multi-performance objectives and selecting trajectories that satisfy feasibility,optimality,and adaptability.Extensive simulations and experiments are performed,and the results demonstrate the framework’s feasibility and effectiveness,which avoids both dynamic and static obstacles and applies to various scenarios with multi-source interactive traffic participants.Moreover,we prove that the proposed method can guarantee real-time planning and safety requirements compared to drivers’manipulation.
基金This work was supported by the National Natural Science Foundation of China(52203066,51973157,61904123)the Tianjin Natural Science Foundation(18JCQNJC02900)+3 种基金the National innovation and entrepreneurship training program for college students(202310058007)the Tianjin Municipal college students’innovation and entrepreneurship training program(202310058088)the Science&Technology Development Fund of Tianjin Education Commission for Higher Education(Grant No.2018KJ196)the State Key Laboratory of Membrane and Membrane Separation,Tiangong University.
文摘Lithium-sulfur battery(LSB)has brought much attention and concern because of high theoretical specific capacity and energy density as one of main competitors for next-generation energy storage systems.The widely commercial application and development of LSB is mainly hindered by serious“shuttle effect”of lithium polysulfides(Li PSs),slow reaction kinetics,notorious lithium dendrites,etc.In various structures of LSB materials,array structured materials,possessing the composition of ordered micro units with the same or similar characteristics of each unit,present excellent application potential for various secondary cells due to some merits such as immobilization of active substances,high specific surface area,appropriate pore sizes,easy modification of functional material surface,accommodated huge volume change,enough facilitated transportation for electrons/lithium ions,and special functional groups strongly adsorbing Li PSs.Thus many novel array structured materials are applied to battery for tackling thorny problems mentioned above.In this review,recent progresses and developments on array structured materials applied in LSBs including preparation ways,collaborative structural designs based on array structures,and action mechanism analyses in improving electrochemical performance and safety are summarized.Meanwhile,we also have detailed discussion for array structured materials in LSBs and constructed the structure-function relationships between array structured materials and battery performances.Lastly,some directions and prospects about preparation ways,functional modifications,and practical applications of array structured materials in LSBs are generalized.We hope the review can attract more researchers'attention and bring more studying on array structured materials for other secondary batteries including LSB.
基金supported by the Major Research Plan of the National Natural Science Foundation of China(Grant No.42027806)the Key Programme of the Natural Science Foundation of China(Grant No.41630639)National Natural Science Foundation of China General Program(Grant No.42372324).
文摘Understanding the unstable evolution of railway slopes is the premise for preventing slope failure and ensuring the safe operation of trains.However,as two major factors affecting the stability of railway slopes,few scholars have explored the unstable evolution of railway slopes under the joint action of rainfall-vibration.Based on the model test of sandy soil slope,the unstable evolution process of slope under locomotive vibration,rainfall,and rainfall-vibration joint action conditions was simulated in this paper.By comparing and analyzing the variation trends of soil pressure and water content of slope under these conditions,the change laws of pore pressure under the influence of vibration and rainfall were explored.The main control factors affecting the stability of slope structure under the joint action conditions were further defined.Combined with the slope failure phenomena under these three conditions,the causes of slope instability resulting from each leading factor were clarified.Finally,according to the above conclusions,the unstable evolution of the slope under the rainfall-vibration joint action was determined.The test results show that the unstable evolution process of sandy soil slope,under the rainfall-vibration joint action,can be divided into:rainfall erosion cracking,vibration promotion penetrating,and slope instability sliding three stages.In the process of slope unstable evolution,rainfall and vibration play the roles of inducing and promoting slide respectively.In addition,the deep cracks,which are the premise for the formation of the sliding surface,and the violent irregular fluctuation of soil pressure,which reflects the near penetration of the sliding surface,constitute the instability characteristics of the railway slope together.This paper reveals the unstable evolution of sandy soil slopes under the joint action of rainfall-vibration,hoping to provide the theoretical basis for the early warning and prevention technology of railway slopes.
基金Supported by Innovation and Entrepreneurship Project for College Students in Heilongjiang Province(S202210223119)the Central Fund Support for the Talent Training Project of Local University Reform and Development(2020GSP16).
文摘Atractylodis Rhizoma comes from the dry rhizome of Atractylis lancea or Atractylodes chinensis in the Compositae family,and it is suitable for preventing and treating diseases such as cold,edema,night blindness and rheumatic arthralgia.Atractylodin is the main active component extracted and isolated from Atractylodis Rhizoma.A large number of studies have found that atractylodin has excellent drug activity in improving gastrointestinal emptying,anti-inflammation,inhibiting malignant tumor and reducing blood lipid.In this paper,the purification process and pharmacological activity of Atractylodin were summarized to provide a theoretical basis for basic research,clinical application and further development and utilization of atractylodin.
文摘Alzheimer’s disease (AD) is a neurodegenerative disorder characterized by cognitive impairments in the initial stage, which lead to severe cognitive dysfunction in the later stage. Action observation therapy (AOT) is a multisensory cognitive rehabilitation technique where the patient initially observes the actions and then tries to perform. The study aimed to examine the impact of AOT along with usual physiotherapy interventions to reduce depression, improve cognition and balance of a patient with AD. A 67 years old patient with AD was selected for this study because the patient has been suffering from depression, dementia, and physical dysfunction along with some other health conditions like diabetes and hypertension. Before starting intervention, a baseline assessment was done through the Beck Depression Inventory (BDI) tool, the Mini-Cog Scale, and the Berg Balance Scale (BBS). The patient received 12 sessions of AOT along with usual physiotherapy interventions thrice a week for four weeks, which included 45 minutes of each session. After four weeks of intervention, the patient demonstrated significant improvement in depression, cognition, and balance, whereas the BDI score declined from moderate 21/63 to mild 15/63 level of depression. The Mini-Cog score improved from 2/5 to 4/5, and the BBS score increased from 18/56 to 37/56. It is concluded that AOT along with usual physiotherapy intervention helps to reduce depression, improve cognition and balance of people with AD.
文摘The Dirac equation γ<sub>μ</sub>(δ<sub>μ</sub>-eA<sub>μ</sub>)Ψ=mc<sup>2</sup>Ψ describes the bound states of the electron under the action of external potentials, A<sub>μ</sub>. We assumed that the fundamental form of the Dirac equation γ<sub>μ</sub>(δ<sub>μ</sub>-S<sub>μ</sub>)Ψ=0 should describe the stable particles (the electron, the proton and the dark-matter-particle (dmp)) bound to themselves under the action of their own potentials S<sub>μ</sub>. The new equation reveals that self energy is consequence of self action, it also reveals that the spin angular momentum is consequence of the dynamic structure of the stable particles. The quantitative results are the determination of their relative masses as well as the determination of the electromagnetic coupling constant.
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.Methods:We assessed the prevalence of coding and splice variants in genes on the ACMG Secondary Findings,version 3.0(ACMG SF v3.0),list in the genomes of 57,933 Icelanders.We assigned pathogenicity to all reviewed variants using reported evidence in the ClinVar database,the frequency of variants,and their associations with disease to create a manually curated set of actionable genotypes(variants).We assessed the relationship between these genotypes and life span and further examined the specific causes of death among carriers.
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.
文摘In South Africa,there is a saying,“I am because we are!”This ancient philosophy called ubuntu explains that our humanity is enriched through shared experiences,compassion and a sense of responsibility to others.Similarly,the concepts of harmony,interconnectedness and mutual respect are deeply ingrained in the philosophy,values and culture of the Chinese people.
文摘This article deals with the investigation of the effects of seismic impacts on the design and dimensioning of structures in South Kivu. The starting point is the observation of an ambivalence that can be observed in the province, namely the non-consideration of seismic action in the study of structures by both professionals and researchers. The main objective of the study is to show the importance of dynamic analysis of structures in South Kivu. It adopts a meta-analytical approach referring to previous researches on South Kivu and proposes an efficient and optimal method. To arrive at the results, we use Eurocode 7 and 8. In addition, we conducted static analysis using the Coulomb method and dynamic analysis using the Mononobe-Okabe method and compared the results. At Nyabibwe, the results showed that we have a deviation of 24.47% for slip stability, 12.038% for overturning stability and 9.677% for stability against punching through a weight wall.
文摘In 2021,the 74th World Health Assembly endorsed updates to the WHO's Comprehensive Mental Health Action Plan extending to 2030,including revised indicators to measure progress towards reaching defined targets and expanded implementation options for variousfacetsoftheplan.
基金This work was supported by grants from the National Natural Science Foundation of China(42101306,4217107)the Natural Science Foundation of Shandong Province(ZR2021MD047),the Strategic Priority Research Program of the Chinese Academy of Sciences(XDA2002040203)+2 种基金the Open Fund of the Key Laboratory of National Geographic Census and Monitoring,Ministry of Natural Resources(MNR)(2020NGCM02)the Open Fund of the Key Laboratory of Urban Land Resources Monitoring and Simulation,Ministry of Natural Resources(KF-2020-05-001)the Major Project of the High Resolution Earth Observation System of China(GFZX0404130304).
文摘Under the combined influence of climate change and human activities,vegetation ecosystem has undergone profound changes.It can be seen that there are obvious differences in the evolution patterns and driving mechanisms of vegetation ecosystem in different historical periods.Therefore,it is urgent to identify and reveal the dominant factors and their contribution rates in the vegetation change cycle.Based on the data of climate elements(sunshine hours,precipitation and temperature),human activities(population intensity and GDP intensity)and other natural factors(altitude,slope and aspect),this study explored the spatial and temporal evolution patterns of vegetation NDVI in the Yellow River Basin of China from 1989 to 2019 through a residual method,a trend analysis,and a gravity center model,and quantitatively distinguished the relative actions of climate change and human activities on vegetation evolution based on Geodetector model.The results showed that the spatial distribution of vegetation NDVI in the Yellow River Basin showed a decreasing trend from southeast to northwest.During 1981-2019,the temporal variation of vegetation NDVI showed an overall increasing trend.The gravity centers of average vegetation NDVI during the study period was distributed in Zhenyuan County,Gansu Province,and the center moved northeastwards from 1981 to 2019.During 1981-2000 and 2001-2019,the proportion of vegetation restoration areas promoted by the combined action of climate change and human activities was the largest.During the study period(1981-2019),the dominant factors influencing vegetation NDVI shifted from natural factors to human activities.These results could provide decision support for the protection and restoration of vegetation ecosystem in the Yellow River Basin.
文摘In this paper the interaction of tripositive terbium ions (Tb3+) with bovine serum albumin(BSA) has bed investigated in the persence of alkaline earth metals and citric acid (Cil)by using fluorescence spectroscopy.The results show. that Tb3+, BSA and Cit can form ternary.complex BSA.Tb2.Cit4 in in μ=0.1mol.l NaCl. pH6.3 hexamethylentetramine buffer.Other rareearths are able to compete for the same binding site in HSA with Tb3+. The sequence of competition is can not replace Tb bound to BSA.
基金supported by Basic Science Research Program through the National Research Foundation of Korea(NRF)funded by the Ministry of Education(No.NRF-2022R1I1A1A01069526).
文摘Deep learning-based action classification technology has been applied to various fields,such as social safety,medical services,and sports.Analyzing an action on a practical level requires tracking multiple human bodies in an image in real-time and simultaneously classifying their actions.There are various related studies on the real-time classification of actions in an image.However,existing deep learning-based action classification models have prolonged response speeds,so there is a limit to real-time analysis.In addition,it has low accuracy of action of each object ifmultiple objects appear in the image.Also,it needs to be improved since it has a memory overhead in processing image data.Deep learning-based action classification using one-shot object detection is proposed to overcome the limitations of multiframe-based analysis technology.The proposed method uses a one-shot object detection model and a multi-object tracking algorithm to detect and track multiple objects in the image.Then,a deep learning-based pattern classification model is used to classify the body action of the object in the image by reducing the data for each object to an action vector.Compared to the existing studies,the constructed model shows higher accuracy of 74.95%,and in terms of speed,it offered better performance than the current studies at 0.234 s per frame.The proposed model makes it possible to classify some actions only through action vector learning without additional image learning because of the vector learning feature of the posterior neural network.Therefore,it is expected to contribute significantly to commercializing realistic streaming data analysis technologies,such as CCTV.
基金supported by the Collabo R&D between Industry,Academy,and Research Institute(S3250534)funded by the Ministry of SMEs and Startups(MSS,Korea)the National Research Foundation of Korea(NRF)grant funded by the Korea government(MSIT)(No.RS-2023-00218176)the Soonchunhyang University Research Fund.
文摘Human Action Recognition(HAR)in uncontrolled environments targets to recognition of different actions froma video.An effective HAR model can be employed for an application like human-computer interaction,health care,person tracking,and video surveillance.Machine Learning(ML)approaches,specifically,Convolutional Neural Network(CNN)models had beenwidely used and achieved impressive results through feature fusion.The accuracy and effectiveness of these models continue to be the biggest challenge in this field.In this article,a novel feature optimization algorithm,called improved Shark Smell Optimization(iSSO)is proposed to reduce the redundancy of extracted features.This proposed technique is inspired by the behavior ofwhite sharks,and howthey find the best prey in thewhole search space.The proposed iSSOalgorithmdivides the FeatureVector(FV)into subparts,where a search is conducted to find optimal local features fromeach subpart of FV.Once local optimal features are selected,a global search is conducted to further optimize these features.The proposed iSSO algorithm is employed on nine(9)selected CNN models.These CNN models are selected based on their top-1 and top-5 accuracy in ImageNet competition.To evaluate the model,two publicly available datasets UCF-Sports and Hollywood2 are selected.
基金supported by the National Educational Science 13th Five-Year Plan Project(JYKYB2019012)the Basic Research Fund for the Engineering University of PAP(WJY201907)the Basic Research Fund of the Engineering University of PAP(WJY202120).
文摘Action recognition and detection is an important research topic in computer vision,which can be divided into action recognition and action detection.At present,the distinction between action recognition and action detection is not clear,and the relevant reviews are not comprehensive.Thus,this paper summarized the action recognition and detection methods and datasets based on deep learning to accurately present the research status in this field.Firstly,according to the way that temporal and spatial features are extracted from the model,the commonly used models of action recognition are divided into the two stream models,the temporal models,the spatiotemporal models and the transformer models according to the architecture.And this paper briefly analyzes the characteristics of the four models and introduces the accuracy of various algorithms in common data sets.Then,from the perspective of tasks to be completed,action detection is further divided into temporal action detection and spatiotemporal action detection,and commonly used datasets are introduced.From the perspectives of the twostage method and one-stage method,various algorithms of temporal action detection are reviewed,and the various algorithms of spatiotemporal action detection are summarized in detail.Finally,the relationship between different parts of action recognition and detection is discussed,the difficulties faced by the current research are summarized in detail,and future development was prospected。