针对自动驾驶场景下,近处干扰点云误检率高、远处稀疏点云漏检率高的问题,提出了一种基于改进PointPillars的自动驾驶障碍物点云检测算法.首先,通过聚合模块和共享多层感知机(shared multi-layer perceptron,MLP)对柱体内点云进行特征编...针对自动驾驶场景下,近处干扰点云误检率高、远处稀疏点云漏检率高的问题,提出了一种基于改进PointPillars的自动驾驶障碍物点云检测算法.首先,通过聚合模块和共享多层感知机(shared multi-layer perceptron,MLP)对柱体内点云进行特征编码,采用最大池化与平均池化叠加的方法将点云的显著特征与细节特征映射为柱体特征;其次,针对算法对伪图特征关注与利用不充分的问题,引入坐标注意力(coordinate attention,CA)机制和残差连接的伪图特征提取模块(attention and residual second block,ARSB),将深层与浅层特征图进行融合,优化算法梯度,增强算法对有效目标的关注度.试验结果表明:改进算法对全局点云检测精度较高,平均精度优于PointPillars、稀疏到稠密3D目标检测器(STD)等点云目标检测算法,在汽车类别上的检测精度优势明显,检测速度较快,符合实时性要求.展开更多
The strong connection between braids and knots provides valuable insights into studying the topological state and phase classification of various physical systems.The phenomenon of non-Hermitian(NH)two-and three-band ...The strong connection between braids and knots provides valuable insights into studying the topological state and phase classification of various physical systems.The phenomenon of non-Hermitian(NH)two-and three-band braiding has received widespread attention.However,a systematic exploration and visualization of non-Abelian braiding and the associated knot transformations in four-band systems remains unexplored.Here,we propose a theoretical model of NH four-band braiding,provide its phase diagram,and establish its trivial,Abelian,and non-Abelian braiding rules.Additionally,we report on special knots,such as the Hopf and Solomon links in braided knots,and reveal that their transformations are accompanied by and mediated through exceptional points.Our work provides a detailed case for studying NH multiband braiding and knot structures in four-band systems,which could offer insights for topological photonics and analog information processing applications.展开更多
Background:The medicinal material known as Os Draconis(Longgu)originates from fossilized remains of ancient mammals and is widely used in treating emotional and mental conditions.However,fossil resources are nonrenewa...Background:The medicinal material known as Os Draconis(Longgu)originates from fossilized remains of ancient mammals and is widely used in treating emotional and mental conditions.However,fossil resources are nonrenewable,and clinical demand is increasingly difficult to meet,leading to a proliferation of counterfeit products.During prolonged geological burial,static pressure from the surrounding strata severely compromises the microstructural integrity of osteons in Os Draconis,but Os Draconis still largely retains the structural features of mammalian bone.Methods:Using verified authentic Os Draconis samples over 10,000 years old as a baseline,this study summarizes the ultrastructural characteristics of genuine Os Draconis.Employing electron probe microanalysis and optical polarized light microscopy,we examined 28 batches of authentic Os Draconis and 31 batches of counterfeits to identify their ultrastructural differences.Key points for ultrastructural identification of Os Draconis were compiled,and a new identification approach was proposed based on these differences.Results:Authentic Os Draconis exhibited distinct ultrastructural markers:irregularly shaped osteons with traversing fissures,deformed/displaced Haversian canals,and secondary mineral infill(predominantly calcium carbonate).Counterfeits showed regular osteon arrangements,absent traversal fissures,and homogeneous hydroxyapatite composition.Lab-simulated samples lacked structural degradation features.EPMA confirmed calcium carbonate infill in fossilized Haversian canals,while elemental profiles differentiated lacunae types(void vs.mineral-packed).Conclusion:The study established ultrastructural criteria for authentic Os Draconis identification:osteon deformation,geological fissures penetrating bone units,and heterogenous mineral deposition.These features,unattainable in counterfeits or modern processed bones,provide a cost-effective,accurate identification method.This approach bridges gaps in TCM material standardization and supports quality control for clinical applications.展开更多
Recently,large-scale deep learning models have been increasingly adopted for point cloud classification.However,thesemethods typically require collecting extensive datasets frommultiple clients,which may lead to priva...Recently,large-scale deep learning models have been increasingly adopted for point cloud classification.However,thesemethods typically require collecting extensive datasets frommultiple clients,which may lead to privacy leaks.Federated learning provides an effective solution to data leakage by eliminating the need for data transmission,relying instead on the exchange of model parameters.However,the uneven distribution of client data can still affect the model’s ability to generalize effectively.To address these challenges,we propose a new framework for point cloud classification called Federated Dynamic Aggregation Selection Strategy-based Multi-Receptive Field Fusion Classification Framework(FDASS-MRFCF).Specifically,we tackle these challenges with two key innovations:(1)During the client local training phase,we propose a Multi-Receptive Field Fusion Classification Model(MRFCM),which captures local and global structures in point cloud data through dynamic convolution and multi-scale feature fusion,enhancing the robustness of point cloud classification.(2)In the server aggregation phase,we introduce a Federated Dynamic Aggregation Selection Strategy(FDASS),which employs a hybrid strategy to average client model parameters,skip aggregation,or reallocate local models to different clients,thereby balancing global consistency and local diversity.We evaluate our framework using the ModelNet40 and ShapeNetPart benchmarks,demonstrating its effectiveness.The proposed method is expected to significantly advance the field of point cloud classification in a secure environment.展开更多
Objective To investigate whether Tuina alleviates fibrotic symptoms in myofascial trigger points(MTrPs)by regulating transforming growth factor(TGF)-β1/Smad3 signaling pathway,thereby deactivating these points.Method...Objective To investigate whether Tuina alleviates fibrotic symptoms in myofascial trigger points(MTrPs)by regulating transforming growth factor(TGF)-β1/Smad3 signaling pathway,thereby deactivating these points.Methods This study comprised two experimental phases.In phase 1,27 specific pathogenfree(SPF)grade female Sprague-Dawley(SD)rats were randomized into three groups:control 1,model 1,and Tuina 1 groups.Model 1 and Tuina 1 groups underwent an 8-week MTrPs modeling protocol involving blunt impact and eccentric exercise.After successful modeling,rats in Tuina 1 group received manual pressing on nodules or cord-like taut bands on the medial aspect of the left hindlimb.Pain sensitivity and tissue stiffness were evaluated via pressure pain threshold(PPT)and soft tissue tension(STT).Muscle histopathology and fibrosis were observed using hematoxylin and eosin(HE)and Masson staining.Inflammatory factors in muscle were measured by enzyme-linked immunosorbent assay(ELISA),while immunofluorescence(IF)and Western blot(WB)were used to detect the expression levels ofα-smooth muscle actin(α-SMA),collagenⅢ,and TGF-β1.In phase 2,45 SPF female SD rats were randomized into five groups:control 2,model 2,Tuina 2,TGF-β1 inhibitor(TI),and Tuina+TGF-β1 agonist(Tuina+TA)groups.All groups except control 2 underwent standardized MTrPs modeling.Rats in Tuina 2 group received consistent pressing manipulation.TI group received intraperitoneal injections of oxymatrine,while Tuina+TA group received intraperitoneal injections of SRI-011381 hydrochloride followed by the same pressing protocol as Tuina 2 group.WB was used to detect the expression of collagen I,collagen III,TGF-β1,and phosphorylated-Smad3(p-Smad3)/Smad3.Results In phase 1,Tuina significantly improved PPT and STT in MTrPs of rats(P<0.01),reversed pathological damages including disorganized muscle fiber arrangement,abnormal myocyte morphology,and exacerbated fibrosis.In addition,in MTrPs of rats in model 1 group,expression levels of nuclear factor kappa-light-chain-enhancer of activated B cells(NF-κB),interleukin(IL)-1β,IL-6,tumor necrosis factor(TNF)-α,and fibrosis markers(α-SMA,collagen I,and collagen III)were upregulated,and all exhibited a significant downward trend after Tuina intervention(P<0.05 or P<0.01).This indicates that the therapeutic effects of Tuina are directly associated with reduced local inflammation and fibrosis in MTrPs.In phase 2,compared with model 2 group,rats in TI and Tuina 2 groups had decreased expression levels of TGF-β1 and p-Smad3/Smad3 in MTrPs,alongside reduced levels of inflammatory factors(IL-1β,IL-6,NF-κB,and TNF-α)and fibrosis markers(α-SMA,collagen I,and collagen III)(P<0.05 or P<0.01).When co-administered with TGF-β1 agonist,the therapeutic effects of Tuina were significantly attenuated,with rebounded TGF-β1 expression and p-Smad3/Smad3 in local MTrPs,and fibrosis and inflammatory responses were re-exacerbated(P<0.05 or P<0.01).Conclusion Tuina can effectively reduce inflammatory responses and fibrosis in MTrPs tissue,and its mechanism is closely related to the inhibition of the TGF-β1/Smad3 signaling pathway,which plays a critical role in Tuina-mediated regulation of MTrPs fibrosis.展开更多
3D laser scanning technology is widely used in underground openings for high-precision,rapid,and nondestructive structural evaluations.Segmenting large 3D point cloud datasets,particularly in coal mine roadways with m...3D laser scanning technology is widely used in underground openings for high-precision,rapid,and nondestructive structural evaluations.Segmenting large 3D point cloud datasets,particularly in coal mine roadways with multi-scale targets,remains challenging.This paper proposes an enhanced segmentation method integrating improved PointNet++with a coverage-voted strategy.The coverage-voted strategy reduces data while preserving multi-scale target topology.The segmentation is achieved using an enhanced PointNet++algorithm with a normalization preprocessing head,resulting in a 94%accuracy for common supporting components.Ablation experiments show that the preprocessing head and coverage strategies increase segmentation accuracy by 20%and 2%,respectively,and improve Intersection over Union(IoU)for bearing plate segmentation by 58%and 20%.The accuracy of the current pretraining segmentation model may be affected by variations in surface support components,but it can be readily enhanced through re-optimization with additional labeled point cloud data.This proposed method,combined with a previously developed machine learning model that links rock bolt load and the deformation field of its bearing plate,provides a robust technique for simultaneously measuring the load of multiple rock bolts in a single laser scan.展开更多
Carbon Capture,Utilization,and Storage(CCUS)technology has gained widespread attention in recent years as a critical strategy to combat global climate change,particularly in achieving carbon neutrality goals.The Guang...Carbon Capture,Utilization,and Storage(CCUS)technology has gained widespread attention in recent years as a critical strategy to combat global climate change,particularly in achieving carbon neutrality goals.The Guangdong-Hong Kong-Macao Greater Bay Area(GBA),as one of China's most economically active regions,serves as a key engine for economic growth while also facing considerable carbon emission challenges.This study analyzes the industrial emission volume and geographical distribution of key emitting enterprises in the GBA,summarizes their technological processes and main carbonemitting equipment,and provides scientific support for precise mitigation policies and low-carbon development.Based on data from 176 key emitting enterprises,the study reveals that Guangzhou and Dongguan host the largest number of such enterprises.Carbon emissions are primarily concentrated in the power sector,dominated by coal-and gas-fired power units,characterized by significant spatial dispersion and uneven distribution.Beyond the power sector,the paper industry has a high number of enterprises but lower emissions.Key facilities such as boilers,cogeneration systems,and production lines are predominantly located near tributaries rivers in Dongguan and Jiangmen.The building materials sector,primarily cement production,ranks as the second-largest emitter,with hightemperature kilns and grinding equipment,particularly rotary kilns and glass furnaces,as the main sources.The petrochemical and chemical sectors have fewer enterprises and lower emissions in the GBA,mainly located in suburban industrial clusters.Carbon emissions in the GBA exhibit distinct industry concentration and geographical distribution disparities.This study provides crucial data and theoretical insights for the development of targeted emission reduction strategies,optimization of source-sink matching,and the advancement of CCUS technologies in the region,particularly from the GBA to the northern South China Sea.展开更多
For India to achieve elimination by 2030,the challenges posed by Plasmodium(P.)vivax cannot be overlooked owing to its burden and unique biology.In 2023,in India,about 224000 malaria cases were reported,and a signific...For India to achieve elimination by 2030,the challenges posed by Plasmodium(P.)vivax cannot be overlooked owing to its burden and unique biology.In 2023,in India,about 224000 malaria cases were reported,and a significant proportion(40%)were P.vivax cases.In P.vivax infection,the persistence of dormant liver stage of parasite,i.e.,hypnozoites,leading to relapses weeks or months later poses challenge in its elimination.展开更多
AIM:To construct an intelligent segmentation scheme for precise localization of central serous chorioretinopathy(CSC)leakage points,thereby enabling ophthalmologists to deliver accurate laser treatment without navigat...AIM:To construct an intelligent segmentation scheme for precise localization of central serous chorioretinopathy(CSC)leakage points,thereby enabling ophthalmologists to deliver accurate laser treatment without navigational laser equipment.METHODS:A dataset with dual labels(point-level and pixel-level)was first established based on fundus fluorescein angiography(FFA)images of CSC and subsequently divided into training(102 images),validation(40 images),and test(40 images)datasets.An intelligent segmentation method was then developed,based on the You Only Look Once version 8 Pose Estimation(YOLOv8-Pose)model and segment anything model(SAM),to segment CSC leakage points.Next,the YOLOv8-Pose model was trained for 200 epochs,and the best-performing model was selected to form the optimal combination with SAM.Additionally,the classic five types of U-Net series models[i.e.,U-Net,recurrent residual U-Net(R2U-Net),attention U-Net(AttU-Net),recurrent residual attention U-Net(R2AttUNet),and nested U-Net(UNet^(++))]were initialized with three random seeds and trained for 200 epochs,resulting in a total of 15 baseline models for comparison.Finally,based on the metrics including Dice similarity coefficient(DICE),intersection over union(IoU),precision,recall,precisionrecall(PR)curve,and receiver operating characteristic(ROC)curve,the proposed method was compared with baseline models through quantitative and qualitative experiments for leakage point segmentation,thereby demonstrating its effectiveness.RESULTS:With the increase of training epochs,the mAP50-95,Recall,and precision of the YOLOv8-Pose model showed a significant increase and tended to stabilize,and it achieved a preliminary localization success rate of 90%(i.e.,36 images)for CSC leakage points in 40 test images.Using manually expert-annotated pixel-level labels as the ground truth,the proposed method achieved outcomes with a DICE of 57.13%,an IoU of 45.31%,a precision of 45.91%,a recall of 93.57%,an area under the PR curve(AUC-PR)of 0.78 and an area under the ROC curve(AUC-ROC)of 0.97,which enables more accurate segmentation of CSC leakage points.CONCLUSION:By combining the precise localization capability of the YOLOv8-Pose model with the robust and flexible segmentation ability of SAM,the proposed method not only demonstrates the effectiveness of the YOLOv8-Pose model in detecting keypoint coordinates of CSC leakage points from the perspective of application innovation but also establishes a novel approach for accurate segmentation of CSC leakage points through the“detect-then-segment”strategy,thereby providing a potential auxiliary means for the automatic and precise realtime localization of leakage points during traditional laser photocoagulation for CSC.展开更多
Highlights By conjugating the same anti-N monoclonal antibody(mAb4-mAb1)with colloidal gold or fluorescent microspheres,this study developed two rapid point-of-care antigen immunochromatographic strips for the detecti...Highlights By conjugating the same anti-N monoclonal antibody(mAb4-mAb1)with colloidal gold or fluorescent microspheres,this study developed two rapid point-of-care antigen immunochromatographic strips for the detection of porcine deltacoronavirus.The fluorescent microsphere-based lateral flow test strip demonstrated a sensitivity of 10^(1.7)TCID_(50)/0.1 mL,which is fourfold higher than that of the colloidal gold-based assay.Porcine deltacoronavirus(PDCoV)is a recently identified enteric coronavirus that causes an acute infectious disease in piglets,leading to diarrhea,vomiting,dehydration,and mortality(Hu et al.2015).展开更多
针对菇房内杏鲍菇表型参数测量任务中,由于扫描设备视角受限,扫描的杏鲍菇点云出现残缺问题,基于AdaPoinTr(Adaptive geometry-aware point transformers)提出了改进的SwinPoinTr模型,实现了对残缺杏鲍菇点云的准确补全和杏鲍菇表型参...针对菇房内杏鲍菇表型参数测量任务中,由于扫描设备视角受限,扫描的杏鲍菇点云出现残缺问题,基于AdaPoinTr(Adaptive geometry-aware point transformers)提出了改进的SwinPoinTr模型,实现了对残缺杏鲍菇点云的准确补全和杏鲍菇表型参数的测量。该方法在使用提出的特征重塑模块的基础上,构建具有几何感知能力的层次化Transformer编码模块,提高了模型对输入点云的利用率和模型捕捉点云细节特征的能力。然后基于泊松重建方法完成了补全点云表面重建,并测量到杏鲍菇表型参数。实验结果表明,本文所提算法在残缺杏鲍菇点云补全任务中,模型倒角距离为1.316×10^(-4),地球移动距离为21.3282,F1分数为87.87%。在表型参数估测任务中,模型对杏鲍菇菌高、体积、表面积估测结果的决定系数分别为0.9582、0.9596、0.9605,均方根误差分别为4.4213 mm、10.8185 cm^(3)、7.5778 cm^(2)。结果证实了该研究方法可以有效地补全残缺的杏鲍菇点云,可以为菇房内杏鲍菇表型参数测量提供基础。展开更多
文摘针对自动驾驶场景下,近处干扰点云误检率高、远处稀疏点云漏检率高的问题,提出了一种基于改进PointPillars的自动驾驶障碍物点云检测算法.首先,通过聚合模块和共享多层感知机(shared multi-layer perceptron,MLP)对柱体内点云进行特征编码,采用最大池化与平均池化叠加的方法将点云的显著特征与细节特征映射为柱体特征;其次,针对算法对伪图特征关注与利用不充分的问题,引入坐标注意力(coordinate attention,CA)机制和残差连接的伪图特征提取模块(attention and residual second block,ARSB),将深层与浅层特征图进行融合,优化算法梯度,增强算法对有效目标的关注度.试验结果表明:改进算法对全局点云检测精度较高,平均精度优于PointPillars、稀疏到稠密3D目标检测器(STD)等点云目标检测算法,在汽车类别上的检测精度优势明显,检测速度较快,符合实时性要求.
基金supported by the National Natural Science Foundation of China(Grant Nos.62575099,62075059,61405058)Guangdong Basic and Applied Basic Research Foundation(Grant No.2024A1515011353)+2 种基金Open Project of the State Key Laboratory of Advanced Optical Communication Systems and Networks of China(Grant No.2024GZKF20)the Natural Science Foundation of Hunan Province(Grant Nos.2020JJ4161 and 2017JJ2048)Scientific Research Foundation of Hunan Provincial Education Department(Grant No.21A0013)。
文摘The strong connection between braids and knots provides valuable insights into studying the topological state and phase classification of various physical systems.The phenomenon of non-Hermitian(NH)two-and three-band braiding has received widespread attention.However,a systematic exploration and visualization of non-Abelian braiding and the associated knot transformations in four-band systems remains unexplored.Here,we propose a theoretical model of NH four-band braiding,provide its phase diagram,and establish its trivial,Abelian,and non-Abelian braiding rules.Additionally,we report on special knots,such as the Hopf and Solomon links in braided knots,and reveal that their transformations are accompanied by and mediated through exceptional points.Our work provides a detailed case for studying NH multiband braiding and knot structures in four-band systems,which could offer insights for topological photonics and analog information processing applications.
基金supported by the Scientific and Technological Innovation Project of the China Academy of Chinese Medical Sciences(CI2021A04013)the National Natural Science Foundation of China(82204610)+1 种基金the Qihang Talent Program(L2022046)the Fundamental Research Funds for the Central Public Welfare Research Institutes(ZZ15-YQ-041 and L2021029).
文摘Background:The medicinal material known as Os Draconis(Longgu)originates from fossilized remains of ancient mammals and is widely used in treating emotional and mental conditions.However,fossil resources are nonrenewable,and clinical demand is increasingly difficult to meet,leading to a proliferation of counterfeit products.During prolonged geological burial,static pressure from the surrounding strata severely compromises the microstructural integrity of osteons in Os Draconis,but Os Draconis still largely retains the structural features of mammalian bone.Methods:Using verified authentic Os Draconis samples over 10,000 years old as a baseline,this study summarizes the ultrastructural characteristics of genuine Os Draconis.Employing electron probe microanalysis and optical polarized light microscopy,we examined 28 batches of authentic Os Draconis and 31 batches of counterfeits to identify their ultrastructural differences.Key points for ultrastructural identification of Os Draconis were compiled,and a new identification approach was proposed based on these differences.Results:Authentic Os Draconis exhibited distinct ultrastructural markers:irregularly shaped osteons with traversing fissures,deformed/displaced Haversian canals,and secondary mineral infill(predominantly calcium carbonate).Counterfeits showed regular osteon arrangements,absent traversal fissures,and homogeneous hydroxyapatite composition.Lab-simulated samples lacked structural degradation features.EPMA confirmed calcium carbonate infill in fossilized Haversian canals,while elemental profiles differentiated lacunae types(void vs.mineral-packed).Conclusion:The study established ultrastructural criteria for authentic Os Draconis identification:osteon deformation,geological fissures penetrating bone units,and heterogenous mineral deposition.These features,unattainable in counterfeits or modern processed bones,provide a cost-effective,accurate identification method.This approach bridges gaps in TCM material standardization and supports quality control for clinical applications.
基金supported in part by the National Key Research and Development Program of Chinaunder(Grant 2021YFB3101100)in part by the National Natural Science Foundation of Chinaunder(Grant 42461057),(Grant 62272123),and(Grant 42371470)+1 种基金in part by the Fundamental Research Program of Shanxi Province under(Grant 202303021212164)in part by the Postgraduate Education Innovation Program of Shanxi Province under(Grant 2024KY474).
文摘Recently,large-scale deep learning models have been increasingly adopted for point cloud classification.However,thesemethods typically require collecting extensive datasets frommultiple clients,which may lead to privacy leaks.Federated learning provides an effective solution to data leakage by eliminating the need for data transmission,relying instead on the exchange of model parameters.However,the uneven distribution of client data can still affect the model’s ability to generalize effectively.To address these challenges,we propose a new framework for point cloud classification called Federated Dynamic Aggregation Selection Strategy-based Multi-Receptive Field Fusion Classification Framework(FDASS-MRFCF).Specifically,we tackle these challenges with two key innovations:(1)During the client local training phase,we propose a Multi-Receptive Field Fusion Classification Model(MRFCM),which captures local and global structures in point cloud data through dynamic convolution and multi-scale feature fusion,enhancing the robustness of point cloud classification.(2)In the server aggregation phase,we introduce a Federated Dynamic Aggregation Selection Strategy(FDASS),which employs a hybrid strategy to average client model parameters,skip aggregation,or reallocate local models to different clients,thereby balancing global consistency and local diversity.We evaluate our framework using the ModelNet40 and ShapeNetPart benchmarks,demonstrating its effectiveness.The proposed method is expected to significantly advance the field of point cloud classification in a secure environment.
基金Natural Science Foundation of China(82274676 and 82374613)Program of Hunan Provincial Natural Science(2023JJ30458).
文摘Objective To investigate whether Tuina alleviates fibrotic symptoms in myofascial trigger points(MTrPs)by regulating transforming growth factor(TGF)-β1/Smad3 signaling pathway,thereby deactivating these points.Methods This study comprised two experimental phases.In phase 1,27 specific pathogenfree(SPF)grade female Sprague-Dawley(SD)rats were randomized into three groups:control 1,model 1,and Tuina 1 groups.Model 1 and Tuina 1 groups underwent an 8-week MTrPs modeling protocol involving blunt impact and eccentric exercise.After successful modeling,rats in Tuina 1 group received manual pressing on nodules or cord-like taut bands on the medial aspect of the left hindlimb.Pain sensitivity and tissue stiffness were evaluated via pressure pain threshold(PPT)and soft tissue tension(STT).Muscle histopathology and fibrosis were observed using hematoxylin and eosin(HE)and Masson staining.Inflammatory factors in muscle were measured by enzyme-linked immunosorbent assay(ELISA),while immunofluorescence(IF)and Western blot(WB)were used to detect the expression levels ofα-smooth muscle actin(α-SMA),collagenⅢ,and TGF-β1.In phase 2,45 SPF female SD rats were randomized into five groups:control 2,model 2,Tuina 2,TGF-β1 inhibitor(TI),and Tuina+TGF-β1 agonist(Tuina+TA)groups.All groups except control 2 underwent standardized MTrPs modeling.Rats in Tuina 2 group received consistent pressing manipulation.TI group received intraperitoneal injections of oxymatrine,while Tuina+TA group received intraperitoneal injections of SRI-011381 hydrochloride followed by the same pressing protocol as Tuina 2 group.WB was used to detect the expression of collagen I,collagen III,TGF-β1,and phosphorylated-Smad3(p-Smad3)/Smad3.Results In phase 1,Tuina significantly improved PPT and STT in MTrPs of rats(P<0.01),reversed pathological damages including disorganized muscle fiber arrangement,abnormal myocyte morphology,and exacerbated fibrosis.In addition,in MTrPs of rats in model 1 group,expression levels of nuclear factor kappa-light-chain-enhancer of activated B cells(NF-κB),interleukin(IL)-1β,IL-6,tumor necrosis factor(TNF)-α,and fibrosis markers(α-SMA,collagen I,and collagen III)were upregulated,and all exhibited a significant downward trend after Tuina intervention(P<0.05 or P<0.01).This indicates that the therapeutic effects of Tuina are directly associated with reduced local inflammation and fibrosis in MTrPs.In phase 2,compared with model 2 group,rats in TI and Tuina 2 groups had decreased expression levels of TGF-β1 and p-Smad3/Smad3 in MTrPs,alongside reduced levels of inflammatory factors(IL-1β,IL-6,NF-κB,and TNF-α)and fibrosis markers(α-SMA,collagen I,and collagen III)(P<0.05 or P<0.01).When co-administered with TGF-β1 agonist,the therapeutic effects of Tuina were significantly attenuated,with rebounded TGF-β1 expression and p-Smad3/Smad3 in local MTrPs,and fibrosis and inflammatory responses were re-exacerbated(P<0.05 or P<0.01).Conclusion Tuina can effectively reduce inflammatory responses and fibrosis in MTrPs tissue,and its mechanism is closely related to the inhibition of the TGF-β1/Smad3 signaling pathway,which plays a critical role in Tuina-mediated regulation of MTrPs fibrosis.
基金supported by the National Natural Science Foundation of China(Grant Nos.52304139,52325403)the CCTEG Coal Mining Research Institute funding(Grant No.KCYJY-2024-MS-10).
文摘3D laser scanning technology is widely used in underground openings for high-precision,rapid,and nondestructive structural evaluations.Segmenting large 3D point cloud datasets,particularly in coal mine roadways with multi-scale targets,remains challenging.This paper proposes an enhanced segmentation method integrating improved PointNet++with a coverage-voted strategy.The coverage-voted strategy reduces data while preserving multi-scale target topology.The segmentation is achieved using an enhanced PointNet++algorithm with a normalization preprocessing head,resulting in a 94%accuracy for common supporting components.Ablation experiments show that the preprocessing head and coverage strategies increase segmentation accuracy by 20%and 2%,respectively,and improve Intersection over Union(IoU)for bearing plate segmentation by 58%and 20%.The accuracy of the current pretraining segmentation model may be affected by variations in surface support components,but it can be readily enhanced through re-optimization with additional labeled point cloud data.This proposed method,combined with a previously developed machine learning model that links rock bolt load and the deformation field of its bearing plate,provides a robust technique for simultaneously measuring the load of multiple rock bolts in a single laser scan.
基金supported by the National Natural Science Foundation of China(52304098,52106092,42376215,52474105)Shenzhen Science and Technology Program(JCYJ20220818095605012,JCYJ20220530113011027)+5 种基金Guangdong Basic and Applied Basic Research Foundation(2022A1515110338,2023A1515012316,2023A1515012761,2025A1515010748)Research Team Cultivation Program of Shenzhen University(2023QNT004)Shenzhen Key Laboratory of Natural Gas Hydrates(ZDSYS20200421111201738)the General Research Fund(No.12616222)Early Career Scheme(No.22611624)of Hong Kong Research Grants CouncilMajor Science and Technology Infrastructure Project of Material Genome Big–science Facilities Platform supported by the Municipal Development and Reform Commission of Shenzhen。
文摘Carbon Capture,Utilization,and Storage(CCUS)technology has gained widespread attention in recent years as a critical strategy to combat global climate change,particularly in achieving carbon neutrality goals.The Guangdong-Hong Kong-Macao Greater Bay Area(GBA),as one of China's most economically active regions,serves as a key engine for economic growth while also facing considerable carbon emission challenges.This study analyzes the industrial emission volume and geographical distribution of key emitting enterprises in the GBA,summarizes their technological processes and main carbonemitting equipment,and provides scientific support for precise mitigation policies and low-carbon development.Based on data from 176 key emitting enterprises,the study reveals that Guangzhou and Dongguan host the largest number of such enterprises.Carbon emissions are primarily concentrated in the power sector,dominated by coal-and gas-fired power units,characterized by significant spatial dispersion and uneven distribution.Beyond the power sector,the paper industry has a high number of enterprises but lower emissions.Key facilities such as boilers,cogeneration systems,and production lines are predominantly located near tributaries rivers in Dongguan and Jiangmen.The building materials sector,primarily cement production,ranks as the second-largest emitter,with hightemperature kilns and grinding equipment,particularly rotary kilns and glass furnaces,as the main sources.The petrochemical and chemical sectors have fewer enterprises and lower emissions in the GBA,mainly located in suburban industrial clusters.Carbon emissions in the GBA exhibit distinct industry concentration and geographical distribution disparities.This study provides crucial data and theoretical insights for the development of targeted emission reduction strategies,optimization of source-sink matching,and the advancement of CCUS technologies in the region,particularly from the GBA to the northern South China Sea.
文摘For India to achieve elimination by 2030,the challenges posed by Plasmodium(P.)vivax cannot be overlooked owing to its burden and unique biology.In 2023,in India,about 224000 malaria cases were reported,and a significant proportion(40%)were P.vivax cases.In P.vivax infection,the persistence of dormant liver stage of parasite,i.e.,hypnozoites,leading to relapses weeks or months later poses challenge in its elimination.
基金Supported by the Shenzhen Science and Technology Program(No.JCYJ20240813152704006)the National Natural Science Foundation of China(No.62401259)+2 种基金the Fundamental Research Funds for the Central Universities(No.NZ2024036)the Postdoctoral Fellowship Program of CPSF(No.GZC20242228)High Performance Computing Platform of Nanjing University of Aeronautics and Astronautics。
文摘AIM:To construct an intelligent segmentation scheme for precise localization of central serous chorioretinopathy(CSC)leakage points,thereby enabling ophthalmologists to deliver accurate laser treatment without navigational laser equipment.METHODS:A dataset with dual labels(point-level and pixel-level)was first established based on fundus fluorescein angiography(FFA)images of CSC and subsequently divided into training(102 images),validation(40 images),and test(40 images)datasets.An intelligent segmentation method was then developed,based on the You Only Look Once version 8 Pose Estimation(YOLOv8-Pose)model and segment anything model(SAM),to segment CSC leakage points.Next,the YOLOv8-Pose model was trained for 200 epochs,and the best-performing model was selected to form the optimal combination with SAM.Additionally,the classic five types of U-Net series models[i.e.,U-Net,recurrent residual U-Net(R2U-Net),attention U-Net(AttU-Net),recurrent residual attention U-Net(R2AttUNet),and nested U-Net(UNet^(++))]were initialized with three random seeds and trained for 200 epochs,resulting in a total of 15 baseline models for comparison.Finally,based on the metrics including Dice similarity coefficient(DICE),intersection over union(IoU),precision,recall,precisionrecall(PR)curve,and receiver operating characteristic(ROC)curve,the proposed method was compared with baseline models through quantitative and qualitative experiments for leakage point segmentation,thereby demonstrating its effectiveness.RESULTS:With the increase of training epochs,the mAP50-95,Recall,and precision of the YOLOv8-Pose model showed a significant increase and tended to stabilize,and it achieved a preliminary localization success rate of 90%(i.e.,36 images)for CSC leakage points in 40 test images.Using manually expert-annotated pixel-level labels as the ground truth,the proposed method achieved outcomes with a DICE of 57.13%,an IoU of 45.31%,a precision of 45.91%,a recall of 93.57%,an area under the PR curve(AUC-PR)of 0.78 and an area under the ROC curve(AUC-ROC)of 0.97,which enables more accurate segmentation of CSC leakage points.CONCLUSION:By combining the precise localization capability of the YOLOv8-Pose model with the robust and flexible segmentation ability of SAM,the proposed method not only demonstrates the effectiveness of the YOLOv8-Pose model in detecting keypoint coordinates of CSC leakage points from the perspective of application innovation but also establishes a novel approach for accurate segmentation of CSC leakage points through the“detect-then-segment”strategy,thereby providing a potential auxiliary means for the automatic and precise realtime localization of leakage points during traditional laser photocoagulation for CSC.
基金financially supported by the National Key Research and Development Program of China(2021YFF0703600)。
文摘Highlights By conjugating the same anti-N monoclonal antibody(mAb4-mAb1)with colloidal gold or fluorescent microspheres,this study developed two rapid point-of-care antigen immunochromatographic strips for the detection of porcine deltacoronavirus.The fluorescent microsphere-based lateral flow test strip demonstrated a sensitivity of 10^(1.7)TCID_(50)/0.1 mL,which is fourfold higher than that of the colloidal gold-based assay.Porcine deltacoronavirus(PDCoV)is a recently identified enteric coronavirus that causes an acute infectious disease in piglets,leading to diarrhea,vomiting,dehydration,and mortality(Hu et al.2015).
