With the popularity of deep learning tools in image decomposition and natural language processing,how to support and store a large number of parameters required by deep learning algorithms has become an urgent problem...With the popularity of deep learning tools in image decomposition and natural language processing,how to support and store a large number of parameters required by deep learning algorithms has become an urgent problem to be solved.These parameters are huge and can be as many as millions.At present,a feasible direction is to use the sparse representation technique to compress the parameter matrix to achieve the purpose of reducing parameters and reducing the storage pressure.These methods include matrix decomposition and tensor decomposition.To let vector take advance of the compressing performance of matrix decomposition and tensor decomposition,we use reshaping and unfolding to let vector be the input and output of Tensor-Factorized Neural Networks.We analyze how reshaping can get the best compress ratio.According to the relationship between the shape of tensor and the number of parameters,we get a lower bound of the number of parameters.We take some data sets to verify the lower bound.展开更多
Objective:To evaluate the effect of the ethyl acetate fraction derived from Sargassum pallidum extract against particulate matter(PM)-induced oxidative stress and inflammation in HaCaT cells and zebrafish.Methods:HaCa...Objective:To evaluate the effect of the ethyl acetate fraction derived from Sargassum pallidum extract against particulate matter(PM)-induced oxidative stress and inflammation in HaCaT cells and zebrafish.Methods:HaCaT cells and zebrafish were used to evaluate the protective effects of the ethyl acetate fraction of Sargassum pallidum extract against PM-induced oxidative stress and inflammation.The production of nitric oxide(NO),intracellular ROS,prostaglandin E_(2)(PGE_(2)),and pro-inflammatory cytokines,and the expression levels of COX-2,iNOS,and NF-κB were evaluated in PM-induced HaCaT cells.Furthermore,the levels of ROS,NO,and lipid peroxidation were assessed in the PM-exposed zebrafish model.Results:The ethyl acetate fraction of Sargassum pallidum extract significantly decreased the production of NO,intracellular ROS,and PGE_(2) in PM-induced HaCaT cells.In addition,the fraction markedly suppressed the levels of pro-inflammatory cytokines and inhibited the expression levels of COX-2,iNOS,and NF-κB.Furthermore,it displayed remarkable protective effects against PM-induced inflammatory response and oxidative stress,represented by the reduction of NO,ROS,and lipid peroxidation in zebrafish.Conclusions:The ethyl acetate fraction of Sargassum pallidum extract exhibits a protective effect against PM-induced oxidative stress and inflammation both in vitro and in vivo and has the potential as a candidate for the development of pharmaceutical and cosmeceutical products.展开更多
Understanding the connection between brain and behavior in animals requires precise monitoring of their behaviors in three-dimensional(3-D)space.However,there is no available three-dimensional behavior capture system ...Understanding the connection between brain and behavior in animals requires precise monitoring of their behaviors in three-dimensional(3-D)space.However,there is no available three-dimensional behavior capture system that focuses on rodents.Here,we present MouseVenue3D,an automated and low-cost system for the efficient capture of 3-D skeleton trajectories in markerless rodents.We improved the most time-consuming step in 3-D behavior capturing by developing an automatic calibration module.Then,we validated this process in behavior recognition tasks,and showed that 3-D behavioral data achieved higher accuracy than 2-D data.Subsequently,MouseVenue3D was combined with fast high-resolution miniature two-photon microscopy for synchronous neural recording and behavioral tracking in the freely-moving mouse.Finally,we successfully decoded spontaneous neuronal activity from the 3-D behavior of mice.Our findings reveal that subtle,spontaneous behavior modules are strongly correlated with spontaneous neuronal activity patterns.展开更多
Objective:To evaluate the effects of Catalpa bignonioides fruit extract on the promotion of muscle growth and muscular capacity in vitro and in vivo.Methods:Cell viability was measured using the 3-(4,5-dimethylthiazol...Objective:To evaluate the effects of Catalpa bignonioides fruit extract on the promotion of muscle growth and muscular capacity in vitro and in vivo.Methods:Cell viability was measured using the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide assay.Cell proliferation was assessed using a 5-bromo-2’-deoxyuridine(BrdU)assay kit.Western blot analysis was performed to determine the protein expressions of related factors.The effects of Catalpa bignonioides extract were investigated in mice using the treadmill exhaustion test and whole-limb grip strength assay.Chemical composition analysis was performed using high-performance liquid chromatography(HPLC).Results:Catalpa bignonioides extract increased the proliferation of C2C12 mouse myoblasts by activating the Akt/mTOR signaling pathway.It also induced metabolic changes,increasing the number of mitochondria and glucose metabolism by phosphorylating adenosine monophosphate-activated protein kinase.In an in vivo study,the extract-treated mice showed improved motor abilities,such as muscular endurance and grip strength.Additionally,HPLC analysis showed that vanillic acid may be the main component of the Catalpa bignonioides extract that enhanced muscle strength.Conclusions:Catalpa bignonioides improves exercise performance through regulation of growth and metabolism in skeletal muscles,suggesting its potential as an effective natural agent for improving muscular strength.展开更多
BACKGROUND In high-intensity sports like golf,knee joints are prone to injury,leading to pain,limited mobility,and decreased quality of life.Traditional treatment methods typically involve rehabilitation exercises,but...BACKGROUND In high-intensity sports like golf,knee joints are prone to injury,leading to pain,limited mobility,and decreased quality of life.Traditional treatment methods typically involve rehabilitation exercises,but their effectiveness may be limited.In recent years,sodium hyaluronate has emerged as a widely used biomedical material in the treatment of joint diseases.AIM To explore the effect of sodium hyaluronate combined with rehabilitation training on pain degree,flexion range of motion and motor function of knee joint injured by golf.METHODS Eighty patients with knee joint injury caused by golf were randomly divided into control(group B)and observation group(group A).The group B was treated with rehabilitation training,and the group A was treated with sodium hyaluronate combined with rehabilitation training.The clinical efficacy,range of motion and function of knee joint,quality of life and inflammatory factors were compared.RESULTS The excellent and good rate of rehabilitation in the group A was raised than group B.At 6 weeks and 3 months after treatment,the range of motion of the two groups was raised than that before treatment,and that of the group A was raised than group B.After treatment,the scores of Lysholm and International Knee Documentation Committee(IKDC)in the group A were raised,and those in the group A were raised than group B.The VAS score of the two groups was reduced than that of the group B,and the SF-36 score of the group A was reduced than group B.The interleukin(IL)-1β,IL-8 and tumor necrosis factor-αin the two groups were reduced,and those in the group A were reduced than group B.CONCLUSION Sodium hyaluronate combined with rehabilitation training has a good clinical effect in the treatment of patients with knee joint injury caused by golf,which relieve pain,maintain knee joint function and improve patients'life quality.展开更多
Currently,there are many limitations to classify images of small objects.In addition,there are limitations such as error detection due to external factors,and there is also a disadvantage that it is difficult to accur...Currently,there are many limitations to classify images of small objects.In addition,there are limitations such as error detection due to external factors,and there is also a disadvantage that it is difficult to accurately distinguish between various objects.This paper uses a convolutional neural network(CNN)algorithm to recognize and classify object images of very small moths and obtain precise data images.A convolution neural network algorithm is used for image data classification,and the classified image is transformed into image data to learn the topological structure of the image.To improve the accuracy of the image classification and reduce the loss rate,a parameter for finding a fast-optimal point of image classification is set by a convolutional neural network and a pixel image as a preprocessor.As a result of this study,we applied a convolution neural network algorithm to classify the images of very small moths by capturing precise images of the moths.Experimental results showed that the accuracy of classification of very small moths was more than 90%.展开更多
Endemic plants are important for understanding phylogenetic relationships,biogeographical history,and genetic variation because of their restricted distribution and their role in conserving biodiversity.Here,we invest...Endemic plants are important for understanding phylogenetic relationships,biogeographical history,and genetic variation because of their restricted distribution and their role in conserving biodiversity.Here,we investigated the phylogenetic relationships of the Korean endemic Fraxinus chiisanensis by reconstructing the molecular phylogeny of Fraxinus based on two nuclear DNA(nrITS and phantastica)and two chloroplast DNA(psbA-trnH and rp132-trnL)regions.Within our fossil-calibrated phylogenetic framework,we also inferred the biogeographical history of F.chiisanensis.To provide a scientific basis for the conservation of F.chiisanensis,we determined the levels of genetic diversity and genetic differentiation in this species.Combining information from nuclear and chloroplast DNA sequence data,our molecular phylogenetic analyses identified F.chiisanensis as a genetically distinct unit from its sister group,Fraxinus platypoda from Japan.Our molecular dating analyses using nuclear and chloroplast DNA data sets show F.chiisanensis diverged from its sister F.platypoda in the Early or Middle Miocene and differentiated in the Late Miocene on the Korean Peninsula.Our results suggest that the divergence of F.chiisanensis was associated with the submergence of the East China Sea land bridge and enhanced monsoons in East Asia.When compared to F.platypoda,F.chiisanensis exhibits low genetic diversity within populations and high genetic differentiation among populations.These results help us to understand the evolutionary history of F.chiisanensis and to develop a conservation strategy for this species.展开更多
The purpose of the present study was to evaluate the effects of a trunk exercise program on the gait and muscle activity in stroke patients. The participants of this pilot study included six hemiplegic stroke patients...The purpose of the present study was to evaluate the effects of a trunk exercise program on the gait and muscle activity in stroke patients. The participants of this pilot study included six hemiplegic stroke patients. The outcomes were surface electromyography (sEMG) and spatiotemporal gait parameters. In analysis of sEMG, no statistically difference was found between pre- and post-training of Maximal Voluntary Isometric Contraction (MVIC) in rectus abdominis and external abdominal oblique muscle, but it tended to increase. However, the gait parameter significantly increased in walking speed, walking cycle, and affected stride length in stroke patients. These results suggest that the trunk exercise program may in part improve the gait of chronic stroke patients.展开更多
Neural Machine Translation(NMT)is an end-to-end learning approach for automated translation,overcoming the weaknesses of conventional phrase-based translation systems.Although NMT based systems have gained their popul...Neural Machine Translation(NMT)is an end-to-end learning approach for automated translation,overcoming the weaknesses of conventional phrase-based translation systems.Although NMT based systems have gained their popularity in commercial translation applications,there is still plenty of room for improvement.Being the most popular search algorithm in NMT,beam search is vital to the translation result.However,traditional beam search can produce duplicate or missing translation due to its target sequence selection strategy.Aiming to alleviate this problem,this paper proposed neural machine translation improvements based on a novel beam search evaluation function.And we use reinforcement learning to train a translation evaluation system to select better candidate words for generating translations.In the experiments,we conducted extensive experiments to evaluate our methods.CASIA corpus and the 1,000,000 pairs of bilingual corpora of NiuTrans are used in our experiments.The experiment results prove that the proposed methods can effectively improve the English to Chinese translation quality.展开更多
Recurrent Neural Networks(RNNs)have been widely applied to deal with temporal problems,such as flood forecasting and financial data processing.On the one hand,traditional RNNs models amplify the gradient issue due to ...Recurrent Neural Networks(RNNs)have been widely applied to deal with temporal problems,such as flood forecasting and financial data processing.On the one hand,traditional RNNs models amplify the gradient issue due to the strict time serial dependency,making it difficult to realize a long-term memory function.On the other hand,RNNs cells are highly complex,which will signifi-cantly increase computational complexity and cause waste of computational resources during model training.In this paper,an improved Time Feedforward Connections Recurrent Neural Networks(TFC-RNNs)model was first proposed to address the gradient issue.A parallel branch was introduced for the hidden state at time t−2 to be directly transferred to time t without the nonlinear transforma-tion at time t−1.This is effective in improving the long-term dependence of RNNs.Then,a novel cell structure named Single Gate Recurrent Unit(SGRU)was presented.This cell structure can reduce the number of parameters for RNNs cell,consequently reducing the computational complexity.Next,applying SGRU to TFC-RNNs as a new TFC-SGRU model solves the above two difficulties.Finally,the performance of our proposed TFC-SGRU was verified through sev-eral experiments in terms of long-term memory and anti-interference capabilities.Experimental results demonstrated that our proposed TFC-SGRU model can cap-ture helpful information with time step 1500 and effectively filter out the noise.The TFC-SGRU model accuracy is better than the LSTM and GRU models regarding language processing ability.展开更多
There are various applied electro-optical devices, which utilize light emitting didoe(LED) chip array for applications to displays and opto-electronic sensors. In those devices, it is the one of the critical technical...There are various applied electro-optical devices, which utilize light emitting didoe(LED) chip array for applications to displays and opto-electronic sensors. In those devices, it is the one of the critical technical issues to minimize uncertain fluctuations including optical power and optical density. Due to variation in operating environment of a device, those are not corrected precisely by controlling parameters based on simple relation between parameters and resultant abovementioned outputs.Therefore, there is essential need to correct outputs in real-time based on correction function generated from the consideration on various operation condition. In this article, we introduce an output correction method through reporting real-time image noise reduction in the application to electro-photography with LED print head. In the technology of LED print head, as differences in optical characteristics between each LED cause vertical image noise, it should be corrected in order to obtain images that are comparable or better in quality compared to those produced by the conventional laser scanning method. Even though it seems that the method used to obtain uniform light power from each LED can solve this problem, it does not work well for high-resolution printing. Therefore, a scan method involving correction by a printed and scanned pattern is introduced through this work. The scan method is composed of correction patterns to minimize printing noise by its shape, the correction algorithm to calculate the optimized value and the printing algorithm to control gray levels in real-time precisely. We believe that the developed correction method upgrades the printing quality of the LPH printer better than commercial printers. The developed correction method can also be applied to various application areas that use an array-type light source such as display systems and lighting systems.展开更多
Studies have demonstrated that some cutaneous biophysical properties vary with the part of the body. The results to date of skin conditions in human skin of multiple parts of the body have not yet been well establishe...Studies have demonstrated that some cutaneous biophysical properties vary with the part of the body. The results to date of skin conditions in human skin of multiple parts of the body have not yet been well established. In this study, we assessed the differences in the skin’s sebum, moisture, pores, wrinkles, pigmentation, and elasticity of each body part in Korean men in their 20s. A total of 34 healthy men were enrolled. A Skin Diagnosis Meter was used to measure the skin’s surface sebum, moisture, pores, wrinkles, pigmentation, and elasticity of each body part. The sebum content was significantly higher on the face than at other sites. Moisture was significantly high on the feet. Pores were significantly high on the face. Wrinkles were significantly high on the face. Pigmentation was high on the face and neck, but not significantly. Elasticity was significantly high on the hands. In the correlation analysis results, sebum and pore were positively correlated, but sebum and moisture and wrinkle and elasticity were negatively correlated. For nearly the first time, this study resulted in systematic reference values for standardized biophysical measuring methods and body parts reflecting the skin physiology of healthy South Korean men. The results show that skin’s surface sebum, moisture, pores, wrinkles, pigmentation, and elasticity vary with the part of the body.展开更多
The aim of our study was to recognize different skin conditions of the face and neck using six biophysical parameters and to show the changes after the application of ultrasonic stimulation (US). We assessed the diffe...The aim of our study was to recognize different skin conditions of the face and neck using six biophysical parameters and to show the changes after the application of ultrasonic stimulation (US). We assessed the differences in the sebum, moisture, pores, wrinkles, pigmentation, and elasticity of the skin in the face and neck regions. A total of 30 healthy men in their 20s were enrolled. We used a skin diagnosis meter to assess the state of the skin. The sebum and pores of the face were more significant than in the neck. The amount of moisture in the U-zone was significantly higher than in other areas. Statistical differences were found between the pre-and post-measure-ment values in the sebum, moisture, wrinkles and pigmentation. Wrinkles and pigmentation were positively correlated. Our data showed that the changes in skin condition are associated with external stimulants. The effect of US on skin may differ depending on the part of the body, and some biophysical properties of skin vary depending on the location on the body.展开更多
This study aims to detect and prevent greening disease in citrus trees using a deep neural network.The process of collecting data on citrus greening disease is very difficult because the vector pests are too small.In ...This study aims to detect and prevent greening disease in citrus trees using a deep neural network.The process of collecting data on citrus greening disease is very difficult because the vector pests are too small.In this paper,since the amount of data collected for deep learning is insufficient,we intend to use the efficient feature extraction function of the neural network based on the Transformer algorithm.We want to use the Cascade Region-based Convolutional Neural Networks(Cascade R-CNN)Swin model,which is a mixture of the transformer model and Cascade R-CNN model to detect greening disease occurring in citrus.In this paper,we try to improve model safety by establishing a linear relationship between samples using Mixup and Cutmix algorithms,which are image processing-based data augmentation techniques.In addition,by using the ImageNet dataset,transfer learning,and stochastic weight averaging(SWA)methods,more accuracy can be obtained.This study compared the Faster Region-based Convolutional Neural Networks Residual Network101(Faster R-CNN ResNet101)model,Cascade Regionbased Convolutional Neural Networks Residual Network101(Cascade RCNN-ResNet101)model,and Cascade R-CNN Swin Model.As a result,the Faster R-CNN ResNet101 model came out as Average Precision(AP)(Intersection over Union(IoU)=0.5):88.2%,AP(IoU=0.75):62.8%,Recall:68.2%,and the Cascade R-CNN ResNet101 model was AP(IoU=0.5):91.5%,AP(IoU=0.75):67.2%,Recall:73.1%.Alternatively,the Cascade R-CNN Swin Model showed AP(IoU=0.5):94.9%,AP(IoU=0.75):79.8%and Recall:76.5%.Thus,the Cascade R-CNN Swin Model showed the best results for detecting citrus greening disease.展开更多
We examined the changes in numerous skin conditions before and after the ap-plication of interferential current therapy to various regions of healthy male bodies. In this study, we assessed the differences in the skin...We examined the changes in numerous skin conditions before and after the ap-plication of interferential current therapy to various regions of healthy male bodies. In this study, we assessed the differences in the skin’s sebum, moisture levels, pores, wrinkles, pigmentation, and elasticity on the shoulders, lower back, and the knees of Korean males in their 20s. A total of 30 healthy males were in-cluded in the study. We used a skin diagnosis meter as a device for measuring the state of the skin. A statistical difference was found when comparing the pre- and post-measurement values in regards to the moisture levels, wrinkles, and pig-mentation. In the correlation analysis results, the sebum and pigmentation, moisture levels and wrinkles, moisture levels and pigmentation, and moisture levels and elasticity were all positively correlated, respectively. The results of this study partially suggest that a change in skin condition is associated with ex-ternal stimulation. The study also found that the effects of the application of in-terferential current therapy on the various skin conditions may differ depending on the region of the body that the application is conducted as well.展开更多
Sex differences in morphology provide key information for understanding a species'morphological adaptations in relation to the evolution of sexual selection.In migratory birds,morphological traits have adapted to ...Sex differences in morphology provide key information for understanding a species'morphological adaptations in relation to the evolution of sexual selection.In migratory birds,morphological traits have adapted to long-distance travel,and sexual dimorphism is typically related to sex-differential migration phenology.Little Buntings(Emberiza pusilla)have one of the longest migrations and are the least dichromatic species among the Emberiza buntings.In this study,we measured sexual size dimorphism and sexual dichromatism of Little Buntings in relation to the spring arrival dates at a stopover site in Korea.Wing length was the most important predictor for identifying sex;the wings of males were longer than those of females.Males also had a significantly stronger chestnut color of the head feathers than females,but this color difference was more prominent in the spring than in the fall.Males arrived earlier than females by four days.Arrival dates correlated with both size and color,but unlike other bunting species previously studied in the same area,there was no clear sex-differential trend in the relationship between arrival date and morphological characteristics.Seasonal differences in the degree of sexual dichromatism suggest that chestnut plumage coloration can be used as a social or sexual signal of males in the breeding season.The correlation of size and color to early arrival regardless of sex may indicate that a preference for assortative mating exists or that a sex-differential migration strategy is not clearly defined in the early stages of northward migration.Our findings on the sexual dimorphism of Little Buntings provide insight into the evolution of the sex-differential migration of buntings in the East Asian Flyway.展开更多
X-ray inspection equipment is divided into small baggage inspection equipment and large cargo inspection equipment.In the case of inspection using X-ray scanning equipment,it is possible to identify the contents of go...X-ray inspection equipment is divided into small baggage inspection equipment and large cargo inspection equipment.In the case of inspection using X-ray scanning equipment,it is possible to identify the contents of goods,unauthorized transport,or hidden goods in real-time by-passing cargo through X-rays without opening it.In this paper,we propose a system for detecting dangerous objects in X-ray images using the Cascade Region-based Convolutional Neural Network(Cascade R-CNN)model,and the data used for learning consists of dangerous goods,storage media,firearms,and knives.In addition,to minimize the overfitting problem caused by the lack of data to be used for artificial intelligence(AI)training,data samples are increased by using the CP(copy-paste)algorithm on the existing data.It also solves the data labeling problem by mixing supervised and semi-supervised learning.The four comparative models to be used in this study are Faster Regionbased Convolutional Neural Networks Residual2 Network-101(Faster R-CNN_Res2Net-101)supervised learning,Cascade R-CNN_Res2Net-101_supervised learning,Cascade Region-based Convolutional Neural Networks Composite Backbone Network V2(CBNetV2)Network-101(Cascade R-CNN_CBNetV2Net-101)_supervised learning,and Cascade RCNN_CBNetV2-101_semi-supervised learning which are then compared and evaluated.As a result of comparing the performance of the four models in this paper,in case of Cascade R-CNN_CBNetV2-101_semi-supervised learning,Average Precision(AP)(Intersection over Union(IoU)=0.5):0.7%,AP(IoU=0.75):1.0%than supervised learning,Recall:0.8%higher.展开更多
基金This work was supported by National Natural Science Foundation of China(Nos.61802030,61572184)the Science and Technology Projects of Hunan Province(No.2016JC2075)the International Cooperative Project for“Double First-Class”,CSUST(No.2018IC24).
文摘With the popularity of deep learning tools in image decomposition and natural language processing,how to support and store a large number of parameters required by deep learning algorithms has become an urgent problem to be solved.These parameters are huge and can be as many as millions.At present,a feasible direction is to use the sparse representation technique to compress the parameter matrix to achieve the purpose of reducing parameters and reducing the storage pressure.These methods include matrix decomposition and tensor decomposition.To let vector take advance of the compressing performance of matrix decomposition and tensor decomposition,we use reshaping and unfolding to let vector be the input and output of Tensor-Factorized Neural Networks.We analyze how reshaping can get the best compress ratio.According to the relationship between the shape of tensor and the number of parameters,we get a lower bound of the number of parameters.We take some data sets to verify the lower bound.
基金This work was supported financially by Korea Environment Industry&Technology Institute through Project to make multi-ministerial national biological research resources more advanced program,funded by Korea Ministry of Environment(grant number RS-2023-00230403).
文摘Objective:To evaluate the effect of the ethyl acetate fraction derived from Sargassum pallidum extract against particulate matter(PM)-induced oxidative stress and inflammation in HaCaT cells and zebrafish.Methods:HaCaT cells and zebrafish were used to evaluate the protective effects of the ethyl acetate fraction of Sargassum pallidum extract against PM-induced oxidative stress and inflammation.The production of nitric oxide(NO),intracellular ROS,prostaglandin E_(2)(PGE_(2)),and pro-inflammatory cytokines,and the expression levels of COX-2,iNOS,and NF-κB were evaluated in PM-induced HaCaT cells.Furthermore,the levels of ROS,NO,and lipid peroxidation were assessed in the PM-exposed zebrafish model.Results:The ethyl acetate fraction of Sargassum pallidum extract significantly decreased the production of NO,intracellular ROS,and PGE_(2) in PM-induced HaCaT cells.In addition,the fraction markedly suppressed the levels of pro-inflammatory cytokines and inhibited the expression levels of COX-2,iNOS,and NF-κB.Furthermore,it displayed remarkable protective effects against PM-induced inflammatory response and oxidative stress,represented by the reduction of NO,ROS,and lipid peroxidation in zebrafish.Conclusions:The ethyl acetate fraction of Sargassum pallidum extract exhibits a protective effect against PM-induced oxidative stress and inflammation both in vitro and in vivo and has the potential as a candidate for the development of pharmaceutical and cosmeceutical products.
基金the Key Area R&D Program of Guangdong Province,China(2018B030338001 and 2018B030331001)the National Key R&D Program of China(2018YFA0701403)+11 种基金the National Natural Science Foundation of China(31500861,31630031,91732304,and 31930047)Chang Jiang Scholars Program,the International Big Science Program Cultivating Project of the Chinese Academy of Science(CAS172644KYS820170004)the Strategic Priority Research Program of the CAS(XDB32030100)the Youth Innovation Promotion Association of the CAS(2017413)the CAS Key Laboratory of Brain Connectome and Manipulation(2019DP173024)Shenzhen Government Basic Research Grants(JCYJ20170411140807570,JCYJ20170413164535041)the Science,Technology and Innovation Commission of Shenzhen Municipality(JCYJ20160429185235132)a Helmholtz-CAS Joint Research grant(GJHZ1508)Guangdong Provincial Key Laboratory of Brain Connectome and Behavior(2017B030301017)the Ten Thousand Talent Program,the Guangdong Special Support Program,Key Laboratory of Shenzhen Institute of Advanced Technology(2019DP173024)the Shenzhen Key Science and Technology Infrastructure Planning Project(ZDKJ20190204002).
文摘Understanding the connection between brain and behavior in animals requires precise monitoring of their behaviors in three-dimensional(3-D)space.However,there is no available three-dimensional behavior capture system that focuses on rodents.Here,we present MouseVenue3D,an automated and low-cost system for the efficient capture of 3-D skeleton trajectories in markerless rodents.We improved the most time-consuming step in 3-D behavior capturing by developing an automatic calibration module.Then,we validated this process in behavior recognition tasks,and showed that 3-D behavioral data achieved higher accuracy than 2-D data.Subsequently,MouseVenue3D was combined with fast high-resolution miniature two-photon microscopy for synchronous neural recording and behavioral tracking in the freely-moving mouse.Finally,we successfully decoded spontaneous neuronal activity from the 3-D behavior of mice.Our findings reveal that subtle,spontaneous behavior modules are strongly correlated with spontaneous neuronal activity patterns.
基金supported by Korea Environment Industry&Technology Institute through Project to make multi-ministerial national biological research resources more advanced Project,funded by Korea Ministry of Environment(grant number RS-2023-00230403).
文摘Objective:To evaluate the effects of Catalpa bignonioides fruit extract on the promotion of muscle growth and muscular capacity in vitro and in vivo.Methods:Cell viability was measured using the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide assay.Cell proliferation was assessed using a 5-bromo-2’-deoxyuridine(BrdU)assay kit.Western blot analysis was performed to determine the protein expressions of related factors.The effects of Catalpa bignonioides extract were investigated in mice using the treadmill exhaustion test and whole-limb grip strength assay.Chemical composition analysis was performed using high-performance liquid chromatography(HPLC).Results:Catalpa bignonioides extract increased the proliferation of C2C12 mouse myoblasts by activating the Akt/mTOR signaling pathway.It also induced metabolic changes,increasing the number of mitochondria and glucose metabolism by phosphorylating adenosine monophosphate-activated protein kinase.In an in vivo study,the extract-treated mice showed improved motor abilities,such as muscular endurance and grip strength.Additionally,HPLC analysis showed that vanillic acid may be the main component of the Catalpa bignonioides extract that enhanced muscle strength.Conclusions:Catalpa bignonioides improves exercise performance through regulation of growth and metabolism in skeletal muscles,suggesting its potential as an effective natural agent for improving muscular strength.
基金2022 project of the Training and Research Center for Ideological and Political Workers in Colleges and Universities of the Ministry of Education(Southwest Jiaotong University)titled"Research on the Sociocultural and Psychological Mechanism of Casting the Consciousness of the Chinese Nation Community",No.SWJTUKF22-06.
文摘BACKGROUND In high-intensity sports like golf,knee joints are prone to injury,leading to pain,limited mobility,and decreased quality of life.Traditional treatment methods typically involve rehabilitation exercises,but their effectiveness may be limited.In recent years,sodium hyaluronate has emerged as a widely used biomedical material in the treatment of joint diseases.AIM To explore the effect of sodium hyaluronate combined with rehabilitation training on pain degree,flexion range of motion and motor function of knee joint injured by golf.METHODS Eighty patients with knee joint injury caused by golf were randomly divided into control(group B)and observation group(group A).The group B was treated with rehabilitation training,and the group A was treated with sodium hyaluronate combined with rehabilitation training.The clinical efficacy,range of motion and function of knee joint,quality of life and inflammatory factors were compared.RESULTS The excellent and good rate of rehabilitation in the group A was raised than group B.At 6 weeks and 3 months after treatment,the range of motion of the two groups was raised than that before treatment,and that of the group A was raised than group B.After treatment,the scores of Lysholm and International Knee Documentation Committee(IKDC)in the group A were raised,and those in the group A were raised than group B.The VAS score of the two groups was reduced than that of the group B,and the SF-36 score of the group A was reduced than group B.The interleukin(IL)-1β,IL-8 and tumor necrosis factor-αin the two groups were reduced,and those in the group A were reduced than group B.CONCLUSION Sodium hyaluronate combined with rehabilitation training has a good clinical effect in the treatment of patients with knee joint injury caused by golf,which relieve pain,maintain knee joint function and improve patients'life quality.
文摘Currently,there are many limitations to classify images of small objects.In addition,there are limitations such as error detection due to external factors,and there is also a disadvantage that it is difficult to accurately distinguish between various objects.This paper uses a convolutional neural network(CNN)algorithm to recognize and classify object images of very small moths and obtain precise data images.A convolution neural network algorithm is used for image data classification,and the classified image is transformed into image data to learn the topological structure of the image.To improve the accuracy of the image classification and reduce the loss rate,a parameter for finding a fast-optimal point of image classification is set by a convolutional neural network and a pixel image as a preprocessor.As a result of this study,we applied a convolution neural network algorithm to classify the images of very small moths by capturing precise images of the moths.Experimental results showed that the accuracy of classification of very small moths was more than 90%.
基金grants from the Korea National Arboretum(Grant no.KNA1-1-13,14-1)Gachon University(Grant no.2018-0320)to J-H Kim。
文摘Endemic plants are important for understanding phylogenetic relationships,biogeographical history,and genetic variation because of their restricted distribution and their role in conserving biodiversity.Here,we investigated the phylogenetic relationships of the Korean endemic Fraxinus chiisanensis by reconstructing the molecular phylogeny of Fraxinus based on two nuclear DNA(nrITS and phantastica)and two chloroplast DNA(psbA-trnH and rp132-trnL)regions.Within our fossil-calibrated phylogenetic framework,we also inferred the biogeographical history of F.chiisanensis.To provide a scientific basis for the conservation of F.chiisanensis,we determined the levels of genetic diversity and genetic differentiation in this species.Combining information from nuclear and chloroplast DNA sequence data,our molecular phylogenetic analyses identified F.chiisanensis as a genetically distinct unit from its sister group,Fraxinus platypoda from Japan.Our molecular dating analyses using nuclear and chloroplast DNA data sets show F.chiisanensis diverged from its sister F.platypoda in the Early or Middle Miocene and differentiated in the Late Miocene on the Korean Peninsula.Our results suggest that the divergence of F.chiisanensis was associated with the submergence of the East China Sea land bridge and enhanced monsoons in East Asia.When compared to F.platypoda,F.chiisanensis exhibits low genetic diversity within populations and high genetic differentiation among populations.These results help us to understand the evolutionary history of F.chiisanensis and to develop a conservation strategy for this species.
文摘The purpose of the present study was to evaluate the effects of a trunk exercise program on the gait and muscle activity in stroke patients. The participants of this pilot study included six hemiplegic stroke patients. The outcomes were surface electromyography (sEMG) and spatiotemporal gait parameters. In analysis of sEMG, no statistically difference was found between pre- and post-training of Maximal Voluntary Isometric Contraction (MVIC) in rectus abdominis and external abdominal oblique muscle, but it tended to increase. However, the gait parameter significantly increased in walking speed, walking cycle, and affected stride length in stroke patients. These results suggest that the trunk exercise program may in part improve the gait of chronic stroke patients.
基金This work is supported by the National Natural Science Foundation of China(61872231,61701297).
文摘Neural Machine Translation(NMT)is an end-to-end learning approach for automated translation,overcoming the weaknesses of conventional phrase-based translation systems.Although NMT based systems have gained their popularity in commercial translation applications,there is still plenty of room for improvement.Being the most popular search algorithm in NMT,beam search is vital to the translation result.However,traditional beam search can produce duplicate or missing translation due to its target sequence selection strategy.Aiming to alleviate this problem,this paper proposed neural machine translation improvements based on a novel beam search evaluation function.And we use reinforcement learning to train a translation evaluation system to select better candidate words for generating translations.In the experiments,we conducted extensive experiments to evaluate our methods.CASIA corpus and the 1,000,000 pairs of bilingual corpora of NiuTrans are used in our experiments.The experiment results prove that the proposed methods can effectively improve the English to Chinese translation quality.
基金This work was funded by the National Science Foundation of Hunan Province(2020JJ2029)。
文摘Recurrent Neural Networks(RNNs)have been widely applied to deal with temporal problems,such as flood forecasting and financial data processing.On the one hand,traditional RNNs models amplify the gradient issue due to the strict time serial dependency,making it difficult to realize a long-term memory function.On the other hand,RNNs cells are highly complex,which will signifi-cantly increase computational complexity and cause waste of computational resources during model training.In this paper,an improved Time Feedforward Connections Recurrent Neural Networks(TFC-RNNs)model was first proposed to address the gradient issue.A parallel branch was introduced for the hidden state at time t−2 to be directly transferred to time t without the nonlinear transforma-tion at time t−1.This is effective in improving the long-term dependence of RNNs.Then,a novel cell structure named Single Gate Recurrent Unit(SGRU)was presented.This cell structure can reduce the number of parameters for RNNs cell,consequently reducing the computational complexity.Next,applying SGRU to TFC-RNNs as a new TFC-SGRU model solves the above two difficulties.Finally,the performance of our proposed TFC-SGRU was verified through sev-eral experiments in terms of long-term memory and anti-interference capabilities.Experimental results demonstrated that our proposed TFC-SGRU model can cap-ture helpful information with time step 1500 and effectively filter out the noise.The TFC-SGRU model accuracy is better than the LSTM and GRU models regarding language processing ability.
基金supported by the National Research Foundation of Korea Grant funded by the Korean Government(Grant No.2015R1C1A1A01053888)the Yeungnam University Research Grant(Grant No.216A580022)
文摘There are various applied electro-optical devices, which utilize light emitting didoe(LED) chip array for applications to displays and opto-electronic sensors. In those devices, it is the one of the critical technical issues to minimize uncertain fluctuations including optical power and optical density. Due to variation in operating environment of a device, those are not corrected precisely by controlling parameters based on simple relation between parameters and resultant abovementioned outputs.Therefore, there is essential need to correct outputs in real-time based on correction function generated from the consideration on various operation condition. In this article, we introduce an output correction method through reporting real-time image noise reduction in the application to electro-photography with LED print head. In the technology of LED print head, as differences in optical characteristics between each LED cause vertical image noise, it should be corrected in order to obtain images that are comparable or better in quality compared to those produced by the conventional laser scanning method. Even though it seems that the method used to obtain uniform light power from each LED can solve this problem, it does not work well for high-resolution printing. Therefore, a scan method involving correction by a printed and scanned pattern is introduced through this work. The scan method is composed of correction patterns to minimize printing noise by its shape, the correction algorithm to calculate the optimized value and the printing algorithm to control gray levels in real-time precisely. We believe that the developed correction method upgrades the printing quality of the LPH printer better than commercial printers. The developed correction method can also be applied to various application areas that use an array-type light source such as display systems and lighting systems.
文摘Studies have demonstrated that some cutaneous biophysical properties vary with the part of the body. The results to date of skin conditions in human skin of multiple parts of the body have not yet been well established. In this study, we assessed the differences in the skin’s sebum, moisture, pores, wrinkles, pigmentation, and elasticity of each body part in Korean men in their 20s. A total of 34 healthy men were enrolled. A Skin Diagnosis Meter was used to measure the skin’s surface sebum, moisture, pores, wrinkles, pigmentation, and elasticity of each body part. The sebum content was significantly higher on the face than at other sites. Moisture was significantly high on the feet. Pores were significantly high on the face. Wrinkles were significantly high on the face. Pigmentation was high on the face and neck, but not significantly. Elasticity was significantly high on the hands. In the correlation analysis results, sebum and pore were positively correlated, but sebum and moisture and wrinkle and elasticity were negatively correlated. For nearly the first time, this study resulted in systematic reference values for standardized biophysical measuring methods and body parts reflecting the skin physiology of healthy South Korean men. The results show that skin’s surface sebum, moisture, pores, wrinkles, pigmentation, and elasticity vary with the part of the body.
文摘The aim of our study was to recognize different skin conditions of the face and neck using six biophysical parameters and to show the changes after the application of ultrasonic stimulation (US). We assessed the differences in the sebum, moisture, pores, wrinkles, pigmentation, and elasticity of the skin in the face and neck regions. A total of 30 healthy men in their 20s were enrolled. We used a skin diagnosis meter to assess the state of the skin. The sebum and pores of the face were more significant than in the neck. The amount of moisture in the U-zone was significantly higher than in other areas. Statistical differences were found between the pre-and post-measure-ment values in the sebum, moisture, wrinkles and pigmentation. Wrinkles and pigmentation were positively correlated. Our data showed that the changes in skin condition are associated with external stimulants. The effect of US on skin may differ depending on the part of the body, and some biophysical properties of skin vary depending on the location on the body.
基金This research was supported by the Honam University Research Fund,2021.
文摘This study aims to detect and prevent greening disease in citrus trees using a deep neural network.The process of collecting data on citrus greening disease is very difficult because the vector pests are too small.In this paper,since the amount of data collected for deep learning is insufficient,we intend to use the efficient feature extraction function of the neural network based on the Transformer algorithm.We want to use the Cascade Region-based Convolutional Neural Networks(Cascade R-CNN)Swin model,which is a mixture of the transformer model and Cascade R-CNN model to detect greening disease occurring in citrus.In this paper,we try to improve model safety by establishing a linear relationship between samples using Mixup and Cutmix algorithms,which are image processing-based data augmentation techniques.In addition,by using the ImageNet dataset,transfer learning,and stochastic weight averaging(SWA)methods,more accuracy can be obtained.This study compared the Faster Region-based Convolutional Neural Networks Residual Network101(Faster R-CNN ResNet101)model,Cascade Regionbased Convolutional Neural Networks Residual Network101(Cascade RCNN-ResNet101)model,and Cascade R-CNN Swin Model.As a result,the Faster R-CNN ResNet101 model came out as Average Precision(AP)(Intersection over Union(IoU)=0.5):88.2%,AP(IoU=0.75):62.8%,Recall:68.2%,and the Cascade R-CNN ResNet101 model was AP(IoU=0.5):91.5%,AP(IoU=0.75):67.2%,Recall:73.1%.Alternatively,the Cascade R-CNN Swin Model showed AP(IoU=0.5):94.9%,AP(IoU=0.75):79.8%and Recall:76.5%.Thus,the Cascade R-CNN Swin Model showed the best results for detecting citrus greening disease.
文摘We examined the changes in numerous skin conditions before and after the ap-plication of interferential current therapy to various regions of healthy male bodies. In this study, we assessed the differences in the skin’s sebum, moisture levels, pores, wrinkles, pigmentation, and elasticity on the shoulders, lower back, and the knees of Korean males in their 20s. A total of 30 healthy males were in-cluded in the study. We used a skin diagnosis meter as a device for measuring the state of the skin. A statistical difference was found when comparing the pre- and post-measurement values in regards to the moisture levels, wrinkles, and pig-mentation. In the correlation analysis results, the sebum and pigmentation, moisture levels and wrinkles, moisture levels and pigmentation, and moisture levels and elasticity were all positively correlated, respectively. The results of this study partially suggest that a change in skin condition is associated with ex-ternal stimulation. The study also found that the effects of the application of in-terferential current therapy on the various skin conditions may differ depending on the region of the body that the application is conducted as well.
基金supported by the New Faculty Startup Fund from Seoul National University (Grant No.500-20200268)supported by the National Research Foundation of Korea (NRF) grants funded by the Republic of Korea Government (Ministry of EducationNRF2018R1D1A1B07050135 & NRF-2019R1I1A1A01063760)
文摘Sex differences in morphology provide key information for understanding a species'morphological adaptations in relation to the evolution of sexual selection.In migratory birds,morphological traits have adapted to long-distance travel,and sexual dimorphism is typically related to sex-differential migration phenology.Little Buntings(Emberiza pusilla)have one of the longest migrations and are the least dichromatic species among the Emberiza buntings.In this study,we measured sexual size dimorphism and sexual dichromatism of Little Buntings in relation to the spring arrival dates at a stopover site in Korea.Wing length was the most important predictor for identifying sex;the wings of males were longer than those of females.Males also had a significantly stronger chestnut color of the head feathers than females,but this color difference was more prominent in the spring than in the fall.Males arrived earlier than females by four days.Arrival dates correlated with both size and color,but unlike other bunting species previously studied in the same area,there was no clear sex-differential trend in the relationship between arrival date and morphological characteristics.Seasonal differences in the degree of sexual dichromatism suggest that chestnut plumage coloration can be used as a social or sexual signal of males in the breeding season.The correlation of size and color to early arrival regardless of sex may indicate that a preference for assortative mating exists or that a sex-differential migration strategy is not clearly defined in the early stages of northward migration.Our findings on the sexual dimorphism of Little Buntings provide insight into the evolution of the sex-differential migration of buntings in the East Asian Flyway.
文摘X-ray inspection equipment is divided into small baggage inspection equipment and large cargo inspection equipment.In the case of inspection using X-ray scanning equipment,it is possible to identify the contents of goods,unauthorized transport,or hidden goods in real-time by-passing cargo through X-rays without opening it.In this paper,we propose a system for detecting dangerous objects in X-ray images using the Cascade Region-based Convolutional Neural Network(Cascade R-CNN)model,and the data used for learning consists of dangerous goods,storage media,firearms,and knives.In addition,to minimize the overfitting problem caused by the lack of data to be used for artificial intelligence(AI)training,data samples are increased by using the CP(copy-paste)algorithm on the existing data.It also solves the data labeling problem by mixing supervised and semi-supervised learning.The four comparative models to be used in this study are Faster Regionbased Convolutional Neural Networks Residual2 Network-101(Faster R-CNN_Res2Net-101)supervised learning,Cascade R-CNN_Res2Net-101_supervised learning,Cascade Region-based Convolutional Neural Networks Composite Backbone Network V2(CBNetV2)Network-101(Cascade R-CNN_CBNetV2Net-101)_supervised learning,and Cascade RCNN_CBNetV2-101_semi-supervised learning which are then compared and evaluated.As a result of comparing the performance of the four models in this paper,in case of Cascade R-CNN_CBNetV2-101_semi-supervised learning,Average Precision(AP)(Intersection over Union(IoU)=0.5):0.7%,AP(IoU=0.75):1.0%than supervised learning,Recall:0.8%higher.
