Pre-stack seismic inversion is used to calculate elastic parameters,including P-wave and S-wave velocities,as well as densities.These parameters play an integral role in the characterization of reservoirs,thereby enha...Pre-stack seismic inversion is used to calculate elastic parameters,including P-wave and S-wave velocities,as well as densities.These parameters play an integral role in the characterization of reservoirs,thereby enhancing the exploration and production process.Deep learning-based seismic inversion does not need a known physical system and can give satisfactory results with sufficient training data.The acquisition of such datasets for seismic inversion poses a significant challenge due to the exorbitant costs associated with drilling activities.Integrating domain knowledge,physical systems,and well log data into a deep learning-based seismic inversion framework is crucial for improving its efficiency and effectiveness.Nevertheless,existing data-driven approaches do not adequately exploit such information,thereby constraining their overall performance and applicability.Therefore,we develop a double dual neural network structure built upon the closed-loop neural network framework,which incorporates both physics and model information to mitigate the dependency on extensive labeled datasets.The information from the different domains is linked through a loss function,where one dual network is responsible for constraining the inversion results using physics information to ensure the physics consistency of the predictions,and the other dual network is responsible for constraining the inversion results using a priori model information to enhance the reliability of the predictions.The method makes full use of well-log data for network training when wells are available,as well as providing unsupervised learning and inversion under well-free conditions.The integration of qualitative and quantitative analyses proves instrumental in demonstrating the effectiveness of the proposed methodology through the use of synthetic and field pre-stack examples.展开更多
For unmanned surface vehicles(USVs),how to find an effective,feasible path that substantially improves mission success rates and time efficiency in dynamic marine environments is a critical issue.To address the path p...For unmanned surface vehicles(USVs),how to find an effective,feasible path that substantially improves mission success rates and time efficiency in dynamic marine environments is a critical issue.To address the path planning problem for USVs using deep reinforcement learning(DRL)in dynamic ocean environments,an improved algorithm based on Deep Q-Networks(DQN)is proposed,which is called Fast Guided Deep Q-Network Algorithm(FG-DQN).This algorithm combines DQN with the artificial potential field(APF)method and uses the A*algorithm to initialize a guiding path in a global static environment and to provide prior knowledge for the USVs.Additionally,the configuration of the reward function using APF and the guiding path effectively reduces the frequency of random movements during the early exploration phase of the DQN algorithm,which accelerates convergence,improves the computational efficiency of path planning,and increases path safety.Finally,the performance of the presented algorithm is validated through experiments in a 2D environment.Compared with traditional reinforcement learning methods such as Q-learning and Sarsa,as well as the original DQN algorithm,FG-DQN is more effective for USV path planning.展开更多
The depth of coal mining is expected to increase continuously owing to the exhaustion of shallow coal resources.However,with the continuous increase in mining depth,transportation and lifting difficulties in deep mine...The depth of coal mining is expected to increase continuously owing to the exhaustion of shallow coal resources.However,with the continuous increase in mining depth,transportation and lifting difficulties in deep mines have significantly increased,and traditional wire rope lifting methods can no longer meet the needs of deep transportation.Based on the principle of pipeline hydraulic lifting,a deep coal fluidization pipeline lifting system has been proposed.To address the problem of particle settlement in the horizontal connection section of large particles,a scheme involving the installation of guide vane-type swirlers in the conveying pipeline is proposed.First,the impact of the guide vane parameters on the liquid flow field and solid particles within the pipeline was studied,and a mathematical model of the characteristic parameters of the swirler was established.Suitable guide vane parameters for the swirler were determined by considering factors such as the alleviation of particle settling,energy utilization efficiency,and the structural strength of the swirler.On this basis,the movement patterns of particles of different sizes in pipelines with and without swirlers were investigated.The study found that under conditions of high velocity and large particle size,the swirler was more effective in improving the slurry flow state within the pipeline.Subsequently,a quantitative method for determining the slurry flow state in the spiral flow pipeline was established,using the particle proportion within the pipeline section as an evaluation index,while considering flow velocity and particle size.Finally,the bench test results show that adding a swirler can reduce the critical nonsilting velocity and resistance loss of the slurry conveying pipeline by 9.0%and 42.9%,respectively,and we elucidate the internal mechanisms behind these reductions.展开更多
Dear Editor,Automated fish grading and packaging,critical in the seafood industry,have not been simultaneously addressed by prior works using machine vision and robotics.This letter presents a novel proofof-concept ro...Dear Editor,Automated fish grading and packaging,critical in the seafood industry,have not been simultaneously addressed by prior works using machine vision and robotics.This letter presents a novel proofof-concept robotic vision system for automatic,size-based fish grading and packaging.Our system classifies frozen fish steaks into two size grades and localizes them on a conveyor belt for robotic pickand-place via a specialized end-effector.Experiments achieved a grading accuracy of 87.6%and a robotic packaging rate of 87%,demonstrating the potential of vision-guided robotics for automated food quality inspection and handling.展开更多
The key challenge in the preparation of perovskite solar cells is to enhance the reproducibility of PSC manufacturing,particularly by better controlling multiple high-dimensional process parameters.This study proposes...The key challenge in the preparation of perovskite solar cells is to enhance the reproducibility of PSC manufacturing,particularly by better controlling multiple high-dimensional process parameters.This study proposes a machine learning(ML)approach to efficiently predict and analyze perovskite film fabrication processes.By evaluating five classic ML algorithms on 130 experimental data sets from blade-coating parameters,the Random Forest(RF)model was identified as the most effective,enabling rapid prediction of over 100,000 parameter sets in just 10 min-equivalent to 3 years of manual experimentation.The RF model demonstrated strong predictive accuracy,with an R2 close to 0.8.This approach led to the identification of optimal process parameter combinations,significantly improving the reproducibility of PSCs and reducing performance variance by approximately threefold,thereby advancing the development of scalable manufacturing processes.展开更多
Scar-related ventricular tachycardia(VT)is a malignant arrhythmia with high mortality rates in patients with cardiomyopathies such as ischemic and dilated cardiomyopathy.[1]While implantable cardioverter defibrillator...Scar-related ventricular tachycardia(VT)is a malignant arrhythmia with high mortality rates in patients with cardiomyopathies such as ischemic and dilated cardiomyopathy.[1]While implantable cardioverter defibrillators(ICD)effectively terminate VT episodes and prevent sudden cardiac death,recurrent ICD discharges may precipitate electrical storms and severely impair quality of life.Radiofrequency catheter ablation is another available treatment for VT but faces challenges in rapidly mapping the critical isthmus during hemodynamically unstable VT.Stereotactic arrhythmia radioablation(STAR)has emerged as a novel,non-invasive,and effective approach for refractory VT over the past decade.展开更多
Structural health monitoring(SHM)of ship piping systems is a core component of predictive maintenance strategies for complex marine engineering systems.During the detection of ship T-shaped pipes using ultrasonic guid...Structural health monitoring(SHM)of ship piping systems is a core component of predictive maintenance strategies for complex marine engineering systems.During the detection of ship T-shaped pipes using ultrasonic guided waves,signal overlap arises from the diffusion of guided wave branches.To address this issue,an intelligent waveguidance mechanism based on acoustic metamaterials is proposed for dynamic propagation control of ultrasonic guided waves.First,a metamaterial unit composed of a stainless steel substrate and a copper column is designed.The control of bandgap characteristics by lattice constant,column diameter,and column height is systematically investigated,and a design range of structural parameters with optimal bandgap is obtained.The particle swarm optimization algorithm is used to design and optimize two metamaterials,Acoustic-metamaterials-1(AMs-1)and Acoustic-metamaterials-2(AMs-2),which further improve the bandgap performance and achieve a transmission loss of over 30 dB for guided waves at 100 and 150 kHz,respectively.Simulation and experimental verification show that when AMs-1 and AMs-2 are deployed in the left and right branches of the T-shaped pipe,respectively,wave propagation can be achieved according to the excitation frequency.At 1oo kHz excitation,the guided wave preferentially propagates along the right branch,while at 150 kHz excitation,it preferentially propagates along the left branch.This method actively regulates the guided wave propagation trajectory at the structural level,thereby preventing signal overlap at the T-shaped pipe and offering a novel technical solution for the efficient damage detection and predictive maintenance in ship pipe systems.展开更多
Pancreatic neuroendocrine tumors(pNETs)are a heterogeneous group of pancreatic neoplasms that originate from the endocrine cells of the pancreas,whose prevalence and incidence are constantly increasing worldwide.Based...Pancreatic neuroendocrine tumors(pNETs)are a heterogeneous group of pancreatic neoplasms that originate from the endocrine cells of the pancreas,whose prevalence and incidence are constantly increasing worldwide.Based on current knowledge of their natural history,pNETs can be divided into functioning pNET and nonfunctioning pNET tumors,characterized by hormone hypersecretion,which results distinct clinical presentations.Treatment options include observation,medical or surgical therapy,and the choice depends on various factors such as staging and grading of the pancreatic lesion and the presence of a specific hormonal syndrome.Surgical resection has long been considered the gold standard for treatment,with related risks of morbidity and mortality.Endoscopic ultrasound(EUS)-guided radiofrequency ablation(RFA)plays a crucial role as minimally invasive procedure for loco-regional treatment of pNETs in selected patients,showing promising results in terms of clinical outcome.EUS-RFA causes a coagulative necrosis with minimal damage to surrounding tissue,allowing for local ablation.This review summarizes the most recent evidences on the use of EUS-RFA as local ablation therapy describing the main endoscopic steps and providing a critical overview of patient selection criteria,side effects,and longterm outcomes.展开更多
Percutaneous coronary intervention(PCI)via the transradial route is now standard practice,particularly in elderly patients,owing to its lower bleeding risk and early ambulation.However,agerelated vascular changes such...Percutaneous coronary intervention(PCI)via the transradial route is now standard practice,particularly in elderly patients,owing to its lower bleeding risk and early ambulation.However,agerelated vascular changes such as radial and subclavian tortuosity,elongation,and reduced arterial compliance can pose unique procedural challenges.One such challenge is catheter kinking,which can impede the smooth delivery of stents.展开更多
Materials from natural sources have been studied to replace the conventional synthetic or animal-derived products as a safer alternative to be used in the healthcare field.In dentistry,guided bone regeneration(GBR)rel...Materials from natural sources have been studied to replace the conventional synthetic or animal-derived products as a safer alternative to be used in the healthcare field.In dentistry,guided bone regeneration(GBR)relies on barrier membranes,predominantly from animals or synthetic materials,to improve osteogenesis by avoiding undesired soft tissue cells from defect sites.In this study,membranes were prepared from zein,a corn-derived protein,using a simple extraction and casting method,followed by optional formaldehyde cross-linking to evaluate their behavior for application in GBR.The membranes were characterised by FTIR,DSC,TGA,tensile strength analysis,and in vitro biological assays.Cross-linked membranes exhibited improved mechanical strength(~5 MPa)and slower degradation(~43%mass loss over 30 days),while non-cross-linked membranes disintegrated more rapidly.Cytotoxicity assays using GM07492 fibroblasts confirmed biocompatibility,and cell migration studies demonstrated effective barrier function.These results indicated that zein membranes,particularly in their cross-linked form,combine biodegradability,mechanical integrity,and cellular safety,suggesting significant potential as sustainable GBR materials.This work introduces,for the first time,zein membranes prepared from corn crude extract for GBR in dentistry,paving the way for eco-friendly alternatives to animal-derived products.展开更多
The present study puts forth a proposal that combines a linear motion guide with tension springs to establish a base isolation system for carrying out laboratory experiments.The methodology involves experimental analy...The present study puts forth a proposal that combines a linear motion guide with tension springs to establish a base isolation system for carrying out laboratory experiments.The methodology involves experimental analysis using a small-scale model of a single-story structure with both fixed base and base isolated configurations.The isolation systems compared include a linear motion guide with tension springs(BI-LMG)and a conventional laminated rubber bearing(BILRB).Free vibration tests showed the time-period shift and enhanced damping in the new isolation method proposed.In addition,the performance of the base isolation system was evaluated through sinusoidal and seismic time-history analyses employing a variety of earthquake data to determine its ability to withstand seismic excitations.展开更多
With the growing demand formore comprehensive and nuanced sentiment understanding,Multimodal Sentiment Analysis(MSA)has gained significant traction in recent years and continues to attract widespread attention in the ...With the growing demand formore comprehensive and nuanced sentiment understanding,Multimodal Sentiment Analysis(MSA)has gained significant traction in recent years and continues to attract widespread attention in the academic community.Despite notable advances,existing approaches still face critical challenges in both information modeling and modality fusion.On one hand,many current methods rely heavily on encoders to extract global features from each modality,which limits their ability to capture latent fine-grained emotional cues within modalities.On the other hand,prevailing fusion strategies often lack mechanisms to model semantic discrepancies across modalities and to adaptively regulate modality interactions.To address these limitations,we propose a novel framework for MSA,termed Multi-Granularity Guided Fusion(MGGF).The proposed framework consists of three core components:(i)Multi-Granularity Feature Extraction Module,which simultaneously captures both global and local emotional features within each modality,and integrates them to construct richer intra-modal representations;(ii)Cross-ModalGuidance Learning Module(CMGL),which introduces a cross-modal scoring mechanism to quantify the divergence and complementarity betweenmodalities.These scores are then used as guiding signals to enable the fusion strategy to adaptively respond to scenarios of modality agreement or conflict;(iii)Cross-Modal Fusion Module(CMF),which learns the semantic dependencies among modalities and facilitates deep-level emotional feature interaction,thereby enhancing sentiment prediction with complementary information.We evaluate MGGF on two benchmark datasets:MVSA-Single and MVSA-Multiple.Experimental results demonstrate that MGGF outperforms the current state-of-the-art model CLMLF on MVSA-Single by achieving a 2.32% improvement in F1 score.On MVSA-Multiple,it surpasses MGNNS with a 0.26% increase in accuracy.These results substantiate the effectiveness ofMGGFin addressing two major limitations of existing methods—insufficient intra-modal fine-grained sentiment modeling and inadequate cross-modal semantic fusion.展开更多
Dear Editor,This letter introduces the counterfactual-guided implicit correspondence prompting(CICP)framework,designed for visible-infrared person re-identification(VI-ReID)within Industry 5.0 intelligent control syst...Dear Editor,This letter introduces the counterfactual-guided implicit correspondence prompting(CICP)framework,designed for visible-infrared person re-identification(VI-ReID)within Industry 5.0 intelligent control systems.CICP advances recognition accuracy in complex industrial environments through its innovative approach to handling modality-specific features and their implicit relationships.展开更多
Guided bone regeneration(GBR)is a widely used clinical technique for bone reconstruction.The core of GBR technology is the GBR barrier membranes,which not only possess good barrier performance to effectively block the...Guided bone regeneration(GBR)is a widely used clinical technique for bone reconstruction.The core of GBR technology is the GBR barrier membranes,which not only possess good barrier performance to effectively block the invasion of rapidly growing fibroblasts into osteoblasts,but also provide a favorable microenvironment for osteoblasts.Collagen-based GBR barrier membrane as one of the most important absorbable membranes has gained widespread clinical application due to its good biocompatibility,low immunogenicity and biodegradability.However,pure collagen has application defects such as low mechanical strength,rapid biodegradation,and susceptibility to microbial contamination,which require physical,chemical and biological crosslinking modification methods to expand its applications.In addition,antibacterial and antioxidant drugs,metal ions and growth factors are often introduced into collagen matrix to fabricate collagen-based barrier membranes by electrospinning,porogenic leaching,emulsion template method,and lyophilisation technologies.In terms of structural innovation of collagen-based barrier membranes,the monolayer,bilayer and multilayer barrier membranes have been developed to prevent fibroblast infiltration and create a favorable space for osteoblast growth.This review provided an overview of the crosslinking methods,molding techniques,and functional enhancement strategies of collagen-based GBR barrier membrane,with the aim of providing references for the future development and clinical application of novel collagen-based GBR barrier membrane.展开更多
Cholecystectomy is one of the most commonly performed procedures in hepatobiliary surgery,with ongoing clinical attention focused on its safety and minimizing complications.Bile duct injury(BDI)remains a serious conce...Cholecystectomy is one of the most commonly performed procedures in hepatobiliary surgery,with ongoing clinical attention focused on its safety and minimizing complications.Bile duct injury(BDI)remains a serious concern,with an incidence of approximately 0.3%-0.6%[1],primarily associated with anatomical variations[2].While standard preoperative imaging like magnetic resonance cholangiopancreatography(MRCP)offers high sensitivity,it may fail to detect rare,dynamic,or functionally significant biliary anomalies[3].展开更多
目的:探讨Guided Care护理模式在不孕症体外受精-胚胎移植(In vitro fertilization and embryo transfer,IVFET)助孕患者中的应用效果。方法:选取2022年12月至2024年12月于本院接受IVF-ET助孕治疗的92例不孕症患者作为研究对象,采用随...目的:探讨Guided Care护理模式在不孕症体外受精-胚胎移植(In vitro fertilization and embryo transfer,IVFET)助孕患者中的应用效果。方法:选取2022年12月至2024年12月于本院接受IVF-ET助孕治疗的92例不孕症患者作为研究对象,采用随机数字表法分为对照组和观察组,各46例。对照组患者接受常规护理,观察组患者接受Guided Care护理模式,两组均持续护理2 m。比较两组心理状态、治疗依从性、生活质量以及护理满意度。结果:护理后,观察组抑郁-焦虑-压力量表(Depression Anxiety Stress Scales,DASS)各项评分均较对照组低,Morisky改良版服药依从性量表(Morisky Medication Adherence Scale,MMAS-8)评分、(The Mos 36-item Short Form Health Survey,SF-36)评分及护理满意度均高于对照组(P<0.05)。结论:Guided Care护理模式能够有效改善不孕症患者接受IVF-ET治疗期间的焦虑、抑郁情绪,增强其治疗依从性,对于顺利妊娠具有积极意义,从而获得更高的护理满意度。展开更多
The visual noise of each light intensity area is different when the image is drawn by Monte Carlo method.However,the existing denoising algorithms have limited denoising performance under complex lighting conditions a...The visual noise of each light intensity area is different when the image is drawn by Monte Carlo method.However,the existing denoising algorithms have limited denoising performance under complex lighting conditions and are easy to lose detailed information.So we propose a rendered image denoising method with filtering guided by lighting information.First,we design an image segmentation algorithm based on lighting information to segment the image into different illumination areas.Then,we establish the parameter prediction model guided by lighting information for filtering(PGLF)to predict the filtering parameters of different illumination areas.For different illumination areas,we use these filtering parameters to construct area filters,and the filters are guided by the lighting information to perform sub-area filtering.Finally,the filtering results are fused with auxiliary features to output denoised images for improving the overall denoising effect of the image.Under the physically based rendering tool(PBRT)scene and Tungsten dataset,the experimental results show that compared with other guided filtering denoising methods,our method improves the peak signal-to-noise ratio(PSNR)metrics by 4.2164 dB on average and the structural similarity index(SSIM)metrics by 7.8%on average.This shows that our method can better reduce the noise in complex lighting scenesand improvethe imagequality.展开更多
基金supported in part by the National Natural Science Foundation of China under Grant 42204108,42374166 and42374149in part by National Key Laboratory of Petroleum Resources and Engineering,China University of Petroleum,Beijing under Grant PRE/open-2305in part by Research on Fine Exploration and Surrounding Rock Classification Technology for Deep Buried Long Tunnels Driven by Horizontal Directional Drilling and Magnetotelluric Methods Based on Deep Learning under Grant E202408010。
摘要Pre-stack seismic inversion is used to calculate elastic parameters,including P-wave and S-wave velocities,as well as densities.These parameters play an integral role in the characterization of reservoirs,thereby enhancing the exploration and production process.Deep learning-based seismic inversion does not need a known physical system and can give satisfactory results with sufficient training data.The acquisition of such datasets for seismic inversion poses a significant challenge due to the exorbitant costs associated with drilling activities.Integrating domain knowledge,physical systems,and well log data into a deep learning-based seismic inversion framework is crucial for improving its efficiency and effectiveness.Nevertheless,existing data-driven approaches do not adequately exploit such information,thereby constraining their overall performance and applicability.Therefore,we develop a double dual neural network structure built upon the closed-loop neural network framework,which incorporates both physics and model information to mitigate the dependency on extensive labeled datasets.The information from the different domains is linked through a loss function,where one dual network is responsible for constraining the inversion results using physics information to ensure the physics consistency of the predictions,and the other dual network is responsible for constraining the inversion results using a priori model information to enhance the reliability of the predictions.The method makes full use of well-log data for network training when wells are available,as well as providing unsupervised learning and inversion under well-free conditions.The integration of qualitative and quantitative analyses proves instrumental in demonstrating the effectiveness of the proposed methodology through the use of synthetic and field pre-stack examples.
基金Supported by the Science Research Foundation for Introduced Talents,Fujian Province of China under Grant Nos.GY-Z21215,GY-Z21216.
摘要For unmanned surface vehicles(USVs),how to find an effective,feasible path that substantially improves mission success rates and time efficiency in dynamic marine environments is a critical issue.To address the path planning problem for USVs using deep reinforcement learning(DRL)in dynamic ocean environments,an improved algorithm based on Deep Q-Networks(DQN)is proposed,which is called Fast Guided Deep Q-Network Algorithm(FG-DQN).This algorithm combines DQN with the artificial potential field(APF)method and uses the A*algorithm to initialize a guiding path in a global static environment and to provide prior knowledge for the USVs.Additionally,the configuration of the reward function using APF and the guiding path effectively reduces the frequency of random movements during the early exploration phase of the DQN algorithm,which accelerates convergence,improves the computational efficiency of path planning,and increases path safety.Finally,the performance of the presented algorithm is validated through experiments in a 2D environment.Compared with traditional reinforcement learning methods such as Q-learning and Sarsa,as well as the original DQN algorithm,FG-DQN is more effective for USV path planning.
基金The Double-First Class Discipline Construction Project of China University of Mining and Technology,Grant/Award Number:2019XKPT03The Priority Academic Program Development of Jiangsu Higher Education Institutions,Grant/Award Number:PAPD。
摘要The depth of coal mining is expected to increase continuously owing to the exhaustion of shallow coal resources.However,with the continuous increase in mining depth,transportation and lifting difficulties in deep mines have significantly increased,and traditional wire rope lifting methods can no longer meet the needs of deep transportation.Based on the principle of pipeline hydraulic lifting,a deep coal fluidization pipeline lifting system has been proposed.To address the problem of particle settlement in the horizontal connection section of large particles,a scheme involving the installation of guide vane-type swirlers in the conveying pipeline is proposed.First,the impact of the guide vane parameters on the liquid flow field and solid particles within the pipeline was studied,and a mathematical model of the characteristic parameters of the swirler was established.Suitable guide vane parameters for the swirler were determined by considering factors such as the alleviation of particle settling,energy utilization efficiency,and the structural strength of the swirler.On this basis,the movement patterns of particles of different sizes in pipelines with and without swirlers were investigated.The study found that under conditions of high velocity and large particle size,the swirler was more effective in improving the slurry flow state within the pipeline.Subsequently,a quantitative method for determining the slurry flow state in the spiral flow pipeline was established,using the particle proportion within the pipeline section as an evaluation index,while considering flow velocity and particle size.Finally,the bench test results show that adding a swirler can reduce the critical nonsilting velocity and resistance loss of the slurry conveying pipeline by 9.0%and 42.9%,respectively,and we elucidate the internal mechanisms behind these reductions.
摘要Dear Editor,Automated fish grading and packaging,critical in the seafood industry,have not been simultaneously addressed by prior works using machine vision and robotics.This letter presents a novel proofof-concept robotic vision system for automatic,size-based fish grading and packaging.Our system classifies frozen fish steaks into two size grades and localizes them on a conveyor belt for robotic pickand-place via a specialized end-effector.Experiments achieved a grading accuracy of 87.6%and a robotic packaging rate of 87%,demonstrating the potential of vision-guided robotics for automated food quality inspection and handling.
基金Key Research and Development Program of Hubei Province,China(Grant No.2022BAA096)Zhejiang Provincial Natural Science Foundation of China(This material is based upon work funded by Zhejiang Provincial Natural Science Foundation of China under Grant No.LR25A020002)support of the Center for Materials Analysis and Characterization,Material Characterization Lab,and Nanofabrication Lab at Hubei University。
摘要The key challenge in the preparation of perovskite solar cells is to enhance the reproducibility of PSC manufacturing,particularly by better controlling multiple high-dimensional process parameters.This study proposes a machine learning(ML)approach to efficiently predict and analyze perovskite film fabrication processes.By evaluating five classic ML algorithms on 130 experimental data sets from blade-coating parameters,the Random Forest(RF)model was identified as the most effective,enabling rapid prediction of over 100,000 parameter sets in just 10 min-equivalent to 3 years of manual experimentation.The RF model demonstrated strong predictive accuracy,with an R2 close to 0.8.This approach led to the identification of optimal process parameter combinations,significantly improving the reproducibility of PSCs and reducing performance variance by approximately threefold,thereby advancing the development of scalable manufacturing processes.
摘要Scar-related ventricular tachycardia(VT)is a malignant arrhythmia with high mortality rates in patients with cardiomyopathies such as ischemic and dilated cardiomyopathy.[1]While implantable cardioverter defibrillators(ICD)effectively terminate VT episodes and prevent sudden cardiac death,recurrent ICD discharges may precipitate electrical storms and severely impair quality of life.Radiofrequency catheter ablation is another available treatment for VT but faces challenges in rapidly mapping the critical isthmus during hemodynamically unstable VT.Stereotactic arrhythmia radioablation(STAR)has emerged as a novel,non-invasive,and effective approach for refractory VT over the past decade.
基金supported in part by the National Natural Science Foundation of China under Grant 5237553752405105.
摘要Structural health monitoring(SHM)of ship piping systems is a core component of predictive maintenance strategies for complex marine engineering systems.During the detection of ship T-shaped pipes using ultrasonic guided waves,signal overlap arises from the diffusion of guided wave branches.To address this issue,an intelligent waveguidance mechanism based on acoustic metamaterials is proposed for dynamic propagation control of ultrasonic guided waves.First,a metamaterial unit composed of a stainless steel substrate and a copper column is designed.The control of bandgap characteristics by lattice constant,column diameter,and column height is systematically investigated,and a design range of structural parameters with optimal bandgap is obtained.The particle swarm optimization algorithm is used to design and optimize two metamaterials,Acoustic-metamaterials-1(AMs-1)and Acoustic-metamaterials-2(AMs-2),which further improve the bandgap performance and achieve a transmission loss of over 30 dB for guided waves at 100 and 150 kHz,respectively.Simulation and experimental verification show that when AMs-1 and AMs-2 are deployed in the left and right branches of the T-shaped pipe,respectively,wave propagation can be achieved according to the excitation frequency.At 1oo kHz excitation,the guided wave preferentially propagates along the right branch,while at 150 kHz excitation,it preferentially propagates along the left branch.This method actively regulates the guided wave propagation trajectory at the structural level,thereby preventing signal overlap at the T-shaped pipe and offering a novel technical solution for the efficient damage detection and predictive maintenance in ship pipe systems.
摘要Pancreatic neuroendocrine tumors(pNETs)are a heterogeneous group of pancreatic neoplasms that originate from the endocrine cells of the pancreas,whose prevalence and incidence are constantly increasing worldwide.Based on current knowledge of their natural history,pNETs can be divided into functioning pNET and nonfunctioning pNET tumors,characterized by hormone hypersecretion,which results distinct clinical presentations.Treatment options include observation,medical or surgical therapy,and the choice depends on various factors such as staging and grading of the pancreatic lesion and the presence of a specific hormonal syndrome.Surgical resection has long been considered the gold standard for treatment,with related risks of morbidity and mortality.Endoscopic ultrasound(EUS)-guided radiofrequency ablation(RFA)plays a crucial role as minimally invasive procedure for loco-regional treatment of pNETs in selected patients,showing promising results in terms of clinical outcome.EUS-RFA causes a coagulative necrosis with minimal damage to surrounding tissue,allowing for local ablation.This review summarizes the most recent evidences on the use of EUS-RFA as local ablation therapy describing the main endoscopic steps and providing a critical overview of patient selection criteria,side effects,and longterm outcomes.
摘要Percutaneous coronary intervention(PCI)via the transradial route is now standard practice,particularly in elderly patients,owing to its lower bleeding risk and early ambulation.However,agerelated vascular changes such as radial and subclavian tortuosity,elongation,and reduced arterial compliance can pose unique procedural challenges.One such challenge is catheter kinking,which can impede the smooth delivery of stents.
基金funded by São Paulo Research Foundation,FAPESP[research project funding 2019-25318-0 and 2017-18782-6]Conselho Nacional de Desenvolvimento Científico e Tecnológico-CNPq,grant number 305518/2023-2.
摘要Materials from natural sources have been studied to replace the conventional synthetic or animal-derived products as a safer alternative to be used in the healthcare field.In dentistry,guided bone regeneration(GBR)relies on barrier membranes,predominantly from animals or synthetic materials,to improve osteogenesis by avoiding undesired soft tissue cells from defect sites.In this study,membranes were prepared from zein,a corn-derived protein,using a simple extraction and casting method,followed by optional formaldehyde cross-linking to evaluate their behavior for application in GBR.The membranes were characterised by FTIR,DSC,TGA,tensile strength analysis,and in vitro biological assays.Cross-linked membranes exhibited improved mechanical strength(~5 MPa)and slower degradation(~43%mass loss over 30 days),while non-cross-linked membranes disintegrated more rapidly.Cytotoxicity assays using GM07492 fibroblasts confirmed biocompatibility,and cell migration studies demonstrated effective barrier function.These results indicated that zein membranes,particularly in their cross-linked form,combine biodegradability,mechanical integrity,and cellular safety,suggesting significant potential as sustainable GBR materials.This work introduces,for the first time,zein membranes prepared from corn crude extract for GBR in dentistry,paving the way for eco-friendly alternatives to animal-derived products.
摘要The present study puts forth a proposal that combines a linear motion guide with tension springs to establish a base isolation system for carrying out laboratory experiments.The methodology involves experimental analysis using a small-scale model of a single-story structure with both fixed base and base isolated configurations.The isolation systems compared include a linear motion guide with tension springs(BI-LMG)and a conventional laminated rubber bearing(BILRB).Free vibration tests showed the time-period shift and enhanced damping in the new isolation method proposed.In addition,the performance of the base isolation system was evaluated through sinusoidal and seismic time-history analyses employing a variety of earthquake data to determine its ability to withstand seismic excitations.
基金supported in part by the National Key Research and Development Program of China under Grant 2022YFB3102904in part by the National Natural Science Foundation of China under Grant No.U23A20305 and No.62472440.
摘要With the growing demand formore comprehensive and nuanced sentiment understanding,Multimodal Sentiment Analysis(MSA)has gained significant traction in recent years and continues to attract widespread attention in the academic community.Despite notable advances,existing approaches still face critical challenges in both information modeling and modality fusion.On one hand,many current methods rely heavily on encoders to extract global features from each modality,which limits their ability to capture latent fine-grained emotional cues within modalities.On the other hand,prevailing fusion strategies often lack mechanisms to model semantic discrepancies across modalities and to adaptively regulate modality interactions.To address these limitations,we propose a novel framework for MSA,termed Multi-Granularity Guided Fusion(MGGF).The proposed framework consists of three core components:(i)Multi-Granularity Feature Extraction Module,which simultaneously captures both global and local emotional features within each modality,and integrates them to construct richer intra-modal representations;(ii)Cross-ModalGuidance Learning Module(CMGL),which introduces a cross-modal scoring mechanism to quantify the divergence and complementarity betweenmodalities.These scores are then used as guiding signals to enable the fusion strategy to adaptively respond to scenarios of modality agreement or conflict;(iii)Cross-Modal Fusion Module(CMF),which learns the semantic dependencies among modalities and facilitates deep-level emotional feature interaction,thereby enhancing sentiment prediction with complementary information.We evaluate MGGF on two benchmark datasets:MVSA-Single and MVSA-Multiple.Experimental results demonstrate that MGGF outperforms the current state-of-the-art model CLMLF on MVSA-Single by achieving a 2.32% improvement in F1 score.On MVSA-Multiple,it surpasses MGNNS with a 0.26% increase in accuracy.These results substantiate the effectiveness ofMGGFin addressing two major limitations of existing methods—insufficient intra-modal fine-grained sentiment modeling and inadequate cross-modal semantic fusion.
基金supported in part by the National Natural Science Foundation of China(62406177)the Shandong Excellent Young Scientists Fund(Oversea)(2024HWYQ-027)+1 种基金the Natural Science Foundation of Shandong Province(ZR2023QF124)the Young Scholars Program of Shandong University。
摘要Dear Editor,This letter introduces the counterfactual-guided implicit correspondence prompting(CICP)framework,designed for visible-infrared person re-identification(VI-ReID)within Industry 5.0 intelligent control systems.CICP advances recognition accuracy in complex industrial environments through its innovative approach to handling modality-specific features and their implicit relationships.
基金supported by the National Natural Science Foundation of China(22578288,22505169)Natural Science Foundation of Beijing Municipality(L244036)+2 种基金Beijing Natural Science Foundation(Z250013)Research and Develop Program,West China Hospital of Stomatology Sichuan University(RD-03-202105)the Fundamental Research Funds for the Central Universities(buctrc202319).
摘要Guided bone regeneration(GBR)is a widely used clinical technique for bone reconstruction.The core of GBR technology is the GBR barrier membranes,which not only possess good barrier performance to effectively block the invasion of rapidly growing fibroblasts into osteoblasts,but also provide a favorable microenvironment for osteoblasts.Collagen-based GBR barrier membrane as one of the most important absorbable membranes has gained widespread clinical application due to its good biocompatibility,low immunogenicity and biodegradability.However,pure collagen has application defects such as low mechanical strength,rapid biodegradation,and susceptibility to microbial contamination,which require physical,chemical and biological crosslinking modification methods to expand its applications.In addition,antibacterial and antioxidant drugs,metal ions and growth factors are often introduced into collagen matrix to fabricate collagen-based barrier membranes by electrospinning,porogenic leaching,emulsion template method,and lyophilisation technologies.In terms of structural innovation of collagen-based barrier membranes,the monolayer,bilayer and multilayer barrier membranes have been developed to prevent fibroblast infiltration and create a favorable space for osteoblast growth.This review provided an overview of the crosslinking methods,molding techniques,and functional enhancement strategies of collagen-based GBR barrier membrane,with the aim of providing references for the future development and clinical application of novel collagen-based GBR barrier membrane.
摘要Cholecystectomy is one of the most commonly performed procedures in hepatobiliary surgery,with ongoing clinical attention focused on its safety and minimizing complications.Bile duct injury(BDI)remains a serious concern,with an incidence of approximately 0.3%-0.6%[1],primarily associated with anatomical variations[2].While standard preoperative imaging like magnetic resonance cholangiopancreatography(MRCP)offers high sensitivity,it may fail to detect rare,dynamic,or functionally significant biliary anomalies[3].
摘要目的:探讨Guided Care护理模式在不孕症体外受精-胚胎移植(In vitro fertilization and embryo transfer,IVFET)助孕患者中的应用效果。方法:选取2022年12月至2024年12月于本院接受IVF-ET助孕治疗的92例不孕症患者作为研究对象,采用随机数字表法分为对照组和观察组,各46例。对照组患者接受常规护理,观察组患者接受Guided Care护理模式,两组均持续护理2 m。比较两组心理状态、治疗依从性、生活质量以及护理满意度。结果:护理后,观察组抑郁-焦虑-压力量表(Depression Anxiety Stress Scales,DASS)各项评分均较对照组低,Morisky改良版服药依从性量表(Morisky Medication Adherence Scale,MMAS-8)评分、(The Mos 36-item Short Form Health Survey,SF-36)评分及护理满意度均高于对照组(P<0.05)。结论:Guided Care护理模式能够有效改善不孕症患者接受IVF-ET治疗期间的焦虑、抑郁情绪,增强其治疗依从性,对于顺利妊娠具有积极意义,从而获得更高的护理满意度。
基金supported by the National Natural Science(No.U19A2063)the Jilin Provincial Development Program of Science and Technology (No.20230201080GX)the Jilin Province Education Department Scientific Research Project (No.JJKH20230851KJ)。
摘要The visual noise of each light intensity area is different when the image is drawn by Monte Carlo method.However,the existing denoising algorithms have limited denoising performance under complex lighting conditions and are easy to lose detailed information.So we propose a rendered image denoising method with filtering guided by lighting information.First,we design an image segmentation algorithm based on lighting information to segment the image into different illumination areas.Then,we establish the parameter prediction model guided by lighting information for filtering(PGLF)to predict the filtering parameters of different illumination areas.For different illumination areas,we use these filtering parameters to construct area filters,and the filters are guided by the lighting information to perform sub-area filtering.Finally,the filtering results are fused with auxiliary features to output denoised images for improving the overall denoising effect of the image.Under the physically based rendering tool(PBRT)scene and Tungsten dataset,the experimental results show that compared with other guided filtering denoising methods,our method improves the peak signal-to-noise ratio(PSNR)metrics by 4.2164 dB on average and the structural similarity index(SSIM)metrics by 7.8%on average.This shows that our method can better reduce the noise in complex lighting scenesand improvethe imagequality.