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
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
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
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
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
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 R^(2) 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
Multi-layer riveted structures are widely applied to aircraft.During the service,cracks may appear within these structures due to stress concentration of the riveted holes.The guided wave monitoring has been proved to...Multi-layer riveted structures are widely applied to aircraft.During the service,cracks may appear within these structures due to stress concentration of the riveted holes.The guided wave monitoring has been proved to be an effective tool to deal with this problem.However,there is a lack of understanding of the wave propagation process across such kinds of structures.This study proposes a piezoelectric guided wave simulation method to reveal the propagation of guided waves in multi-layer riveted structures.Effects of pretension force,friction coefficient,and cracks that might influence wave characteristics are studied.The guided wave simulation data is compared with the experimental results and the results verify the simulation model.Then the guided wave propagation in a more complex long-beam butt joint structure is further simulated.展开更多
To tackle the issue of notch frequency and center frequency drift of the L(0,1)mode guided wave in ultra⁃sonic guided wave⁃based stress monitoring of prestressed steel strands,a method using higher⁃order mode plateau ...To tackle the issue of notch frequency and center frequency drift of the L(0,1)mode guided wave in ultra⁃sonic guided wave⁃based stress monitoring of prestressed steel strands,a method using higher⁃order mode plateau fre⁃quencies is adopted.First,the correlation between group velocity peaks and phase velocities at these plateau frequen⁃cies is analyzed.This analysis establishes a quantitative rela⁃tionship between phase velocity and stress in the steel strand,providing a theoretical foundation for stress monitor⁃ing.Then the two⁃dimensional Fourier transform is em⁃ployed to separate wave modes.Dynamic programming techniques are applied in the frequency⁃velocity domain to extract higher⁃order modes.By identifying the group veloc⁃ity peaks of these separated higher⁃order modes,the plateau frequencies of guided waves are determined,enabling indi⁃rect measurement of stress in the steel strand.To validate this method,finite element simulations are conducted under three scenarios.Results show that the higher⁃order modes of transient signals from three different positions can be ac⁃curately extracted,leading to successful cable stress moni⁃toring.This approach effectively circumvents the issue of guided wave frequency drift and improves stress monitoring accuracy.Consequently,it significantly improves the appli⁃cation of ultrasonic guided wave technology in structural health monitoring.展开更多
Fatigue damage is a primary contributor to the failure of composite structures,underscoring the critical importance of monitoring its progression to ensure structural safety.This paper introduces an innovative approac...Fatigue damage is a primary contributor to the failure of composite structures,underscoring the critical importance of monitoring its progression to ensure structural safety.This paper introduces an innovative approach to fatigue damage monitoring in composite structures,leveraging a hybrid methodology that integrates the Whale Optimization Algorithm(WOA)-Backpropagation(BP)neural network with an ultrasonic guided wave feature selection algorithm.Initially,a network of piezoelectric ceramic sensors is employed to transmit and capture ultrasonic-guided waves,thereby establishing a signal space that correlates with the structural condition.Subsequently,the Relief-F algorithm is applied for signal feature extraction,culminating in the formation of a feature matrix.This matrix is then utilized to train the WOA-BP neural network,which optimizes the fatigue damage identification model globally.The proposed model’s efficacy in quantifying fatigue damage is tested against fatigue test datasets,with its performance benchmarked against the traditional BP neural network algorithm.The findings demonstrate that the WOA-BP neural network model not only surpasses the BP model in predictive accuracy but also exhibits enhanced global search capabilities.The effect of different sensor-receiver path signals on the model damage recognition results is also discussed.The results of the discussion found that the path directly through the damaged area is more accurate in modeling damage recognition compared to the path signals away from the damaged area.Consequently,the proposed monitoring method in the fatigue test dataset is adept at accurately tracking and recognizing the progression of fatigue damage.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
BACKGROUND Adrenocortical oncocytoma is a rare,mostly benign,nonfunctional tumor that is typically detected incidentally.Its diagnosis is challenging because of the absence of distinctive imaging characteristics,neces...BACKGROUND Adrenocortical oncocytoma is a rare,mostly benign,nonfunctional tumor that is typically detected incidentally.Its diagnosis is challenging because of the absence of distinctive imaging characteristics,necessitating pathological validation.CASE SUMMARY We present a case report of a 35-year-old woman with an adrenal mass located on the left side,where endoscopic ultrasound-guided fine-needle aspiration(EUSFNA)was performed after comprehensive diagnostic assessment.Our results are consistent with those of previously documented cases regarding tumor demographics and anatomical location.Given the limited number of reports on this condition,long-term follow-up is crucial to enhance our understanding of its prognosis.CONCLUSION For patients with adrenocortical oncocytoma,EUS-FNA can enables collection of preoperative tissue specimens leading to suitable treatment strategies.展开更多
Objective:The use of technology is growing rapidly.It can also be used in nursing interventions.A technology pack can support nursing interventions.An application called guided imagery in Indonesian(GIANESIA)has been ...Objective:The use of technology is growing rapidly.It can also be used in nursing interventions.A technology pack can support nursing interventions.An application called guided imagery in Indonesian(GIANESIA)has been developed to reduce anxiety in preoperative patients.Methods:A total of 42 participants joined this research.The respondents were those who would undergo surgery.We used the numeric visual analog anxiety scale(NVAAS)as the instrument to measure their anxiety levels.The participants were first given informed consent.Then,they open the application that has been installed.The process begins with participants choosing their initial anxiety score.Later,they start the therapy session,and immediately after finishing it,a pop-up bar prompts them to enter their final,posttherapy anxiety score.Results:This study shows the effectiveness of therapy given by GIANESIA in reducing anxiety in preoperative patients with p-value=0.000(a<0.05).Also,61.9%of the participants had decreased anxiety levels after therapy with GIANESIA.Conclusions:This study proves that providing therapy via a mobile application is effective in easing uncomfortable feelings,especially anxiety,in preoperative patients.Moving forward,the app can and should be expanded with new features and further developmental goals.展开更多
BACKGROUND Femur fractures are one of the most serious injuries that occur in the older population and are associated with severe pain and increased mortality.The primary objective of this study was to find if there w...BACKGROUND Femur fractures are one of the most serious injuries that occur in the older population and are associated with severe pain and increased mortality.The primary objective of this study was to find if there was a significant difference in pain scores in patients treated with femoral nerve blocks(FNB)compared with patients treated with the standard analgesia protocol.The secondary objective was to find if there was a significant difference in morbidity between the two groups.AIM To evaluate the effectiveness of ultrasound(US)-guided FNB in managing preoperative pain and reducing morbidity in patients with neck femur fractures compared to the standard analgesia protocol.The study seeks to determine whether FNB offers superior outcomes in terms of pain control,rehospitalization rates,and mortality.METHODS This retrospective cohort study included 1577 patients suffering from neck femur fractures.387 patients were treated with a FNB for pain management upon arrival at the emergency department,the rest were treated with standard analgesia.Pain was assessed from electronic medical records using the visual analogue scale(VAS)pre surgery,12-and 24-hour post-surgery.To determine morbidity and mortality during hospitalizations and 6 months after,it was collected from electronic medical records.RESULTS In a cohort of 1577 patients,those receiving US-guided FNB had significantly lower preoperative VAS pain scores(1.46±2.49 vs 1.82±2.59,P=0.001),reduced rehospitalization rates(0.99±1.96 vs 1.46±2.34,P<0.001),and lower mortality(16%vs 32%,P<0.001)compared to standard analgesia.CONCLUSION US guided FNB is more effective for pain management compared with standard analgesia.This method was also found to significantly reduce the risk of morbidity in those patients.展开更多
Nanotechnology has substantially advanced imaging,therapy,and clinical techniques,playing a crucial role in the development of sustainable functional materials in biomedical engineering.Nanoparticles,used as contrast ...Nanotechnology has substantially advanced imaging,therapy,and clinical techniques,playing a crucial role in the development of sustainable functional materials in biomedical engineering.Nanoparticles,used as contrast agents in multimodal imaging,offer notable advantages due to their high surface areato-volume ratio,enabling functionalization with targeting ligands for improved specificity and sensitivity.They can also carry multiple imaging agents or therapeutic drugs,promoting theranostics,an approach combining diagnosis and treatment.However,the need for high-dose contrast agents raises concerns about nanoparticle toxicity.Green nanotechnology addresses this by developing sustainable nanoparticles through eco-friendly synthesis methods,reducing environmental and health risks.Moreover,by using this method,safer imaging agents that align with current health standards can be generated.In parallel,recent advancements in artificial intelligence(AI)are transforming imaging applications.Beyond simple automation of image interpretation,AI is enhancing image acquisition,management,and interpretation,signaling a future where intelligent systems play a key role in healthcare.This review explores the diverse nanomaterials utilized as contrast agents in multimodal imaging,highlights the importance of green nanotechnology in minimizing toxicity,and emphasizes on the important role of AI in imaging and imageguided therapy.Together,these innovations are advancing precision healthcare,promising a future where diagnostics and treatment are not only more effective but also sustainable.展开更多
Correction to:Neuroscience Bulletin https://doi.org/10.1007/s12264-025-01371-x In this article the affiliation"Department of Circuit Theory,Faculty of Electrical Engineering,Czech Technical University in Prague,M...Correction to:Neuroscience Bulletin https://doi.org/10.1007/s12264-025-01371-x In this article the affiliation"Department of Circuit Theory,Faculty of Electrical Engineering,Czech Technical University in Prague,Member of the Epilepsy Research Centre Prague-EpiReC Consortium,Prague,Czechia"should only be assigned to Radek Janca and Petr Jezdik.It is removed from the authors:Jiri Hammer,Michaela Kajsova,Adam Kalina,Petr Marusic,and Kamil Vlcek.展开更多
Dear Editor,This letter addresses the enhancement of autonomous vehicles’(AVs)behavior control systems through the application of reinforcement learning(RL)techniques.It presents a novel approach to efficient knowled...Dear Editor,This letter addresses the enhancement of autonomous vehicles’(AVs)behavior control systems through the application of reinforcement learning(RL)techniques.It presents a novel approach to efficient knowledge-guided self-evolutionary intelligent decision-making by integrating human intervention as prior knowledge into the RL’s exploratory learning process.Specifically,we propose an innovative intervention-based reward shaping mechanism and develop a novel experience replay mechanism to augment the efficiency of leveraging guided knowledge within the framework of off-policy RL.The proposed methodology significantly enhances the performance of RL-based behavior control strategies in complex scenarios for AVs.Illustrative results indicate that,relative to existing state-of-theart methods,our approach yields superior learning efficiency and improved autonomous driving performance.展开更多
Genome rearrangement is an important process that leads to genetic diversity,including mutation-related insertions,deletions,or inversions in the genome[1,2].
In complex environments such as high dynamics and weak signals,a satellite signal compensation method based on prefabricated trajectory assistance and an improved adaptive Kalman filter is proposed for a 155 mm differ...In complex environments such as high dynamics and weak signals,a satellite signal compensation method based on prefabricated trajectory assistance and an improved adaptive Kalman filter is proposed for a 155 mm differential rotating rear-body control-guided projectile to address the situation of satellite signal flickering and loss in projectile navigation systems due to environmental limitations.First,establish the system state and measurement equation when receiving satellite signals normally.Second,a seven-degree-of-freedom external ballistic model is constructed,and the ideal trajectory output from the ballistic model is used to provide the virtual motion state of the projectile,which is input into a filter as a substitute observation when satellite signals are lost.Finally,an adaptive Kalman filter(AKF)is designed,the proposed adaptive Kalman filter can accurately adjust the estimation error covariance matrix and Kalman gain in real-time based on information covariance mismatch.The simulation results show that compared to the classical Kalman filter,it can reduce the average positioning error by more than 38.21%in the case of short-term and full-range loss of satellite signals,providing a new idea for the integrated navigation of projectiles with incomplete information under the condition of satellite signal loss.展开更多
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.
文摘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.
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。
文摘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.
文摘目的: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。
文摘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 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.
文摘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。
文摘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 R^(2) 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.
文摘Multi-layer riveted structures are widely applied to aircraft.During the service,cracks may appear within these structures due to stress concentration of the riveted holes.The guided wave monitoring has been proved to be an effective tool to deal with this problem.However,there is a lack of understanding of the wave propagation process across such kinds of structures.This study proposes a piezoelectric guided wave simulation method to reveal the propagation of guided waves in multi-layer riveted structures.Effects of pretension force,friction coefficient,and cracks that might influence wave characteristics are studied.The guided wave simulation data is compared with the experimental results and the results verify the simulation model.Then the guided wave propagation in a more complex long-beam butt joint structure is further simulated.
基金The National Natural Science Foundation of China(No.52278303).
文摘To tackle the issue of notch frequency and center frequency drift of the L(0,1)mode guided wave in ultra⁃sonic guided wave⁃based stress monitoring of prestressed steel strands,a method using higher⁃order mode plateau fre⁃quencies is adopted.First,the correlation between group velocity peaks and phase velocities at these plateau frequen⁃cies is analyzed.This analysis establishes a quantitative rela⁃tionship between phase velocity and stress in the steel strand,providing a theoretical foundation for stress monitor⁃ing.Then the two⁃dimensional Fourier transform is em⁃ployed to separate wave modes.Dynamic programming techniques are applied in the frequency⁃velocity domain to extract higher⁃order modes.By identifying the group veloc⁃ity peaks of these separated higher⁃order modes,the plateau frequencies of guided waves are determined,enabling indi⁃rect measurement of stress in the steel strand.To validate this method,finite element simulations are conducted under three scenarios.Results show that the higher⁃order modes of transient signals from three different positions can be ac⁃curately extracted,leading to successful cable stress moni⁃toring.This approach effectively circumvents the issue of guided wave frequency drift and improves stress monitoring accuracy.Consequently,it significantly improves the appli⁃cation of ultrasonic guided wave technology in structural health monitoring.
基金funded by the Key Program of the National Natural Science Foundation of China(U2341235)Youth Fund for Basic Research Program of Jiangnan University(JUSRP123003)+2 种基金Postgraduate Research&Practice Innovation Program of Jiangsu Province(SJCX23_1237)the National Key R&D Program of China(2018YFA0702800)Key Technologies R&D Program of CNBM(2023SJYL01).
文摘Fatigue damage is a primary contributor to the failure of composite structures,underscoring the critical importance of monitoring its progression to ensure structural safety.This paper introduces an innovative approach to fatigue damage monitoring in composite structures,leveraging a hybrid methodology that integrates the Whale Optimization Algorithm(WOA)-Backpropagation(BP)neural network with an ultrasonic guided wave feature selection algorithm.Initially,a network of piezoelectric ceramic sensors is employed to transmit and capture ultrasonic-guided waves,thereby establishing a signal space that correlates with the structural condition.Subsequently,the Relief-F algorithm is applied for signal feature extraction,culminating in the formation of a feature matrix.This matrix is then utilized to train the WOA-BP neural network,which optimizes the fatigue damage identification model globally.The proposed model’s efficacy in quantifying fatigue damage is tested against fatigue test datasets,with its performance benchmarked against the traditional BP neural network algorithm.The findings demonstrate that the WOA-BP neural network model not only surpasses the BP model in predictive accuracy but also exhibits enhanced global search capabilities.The effect of different sensor-receiver path signals on the model damage recognition results is also discussed.The results of the discussion found that the path directly through the damaged area is more accurate in modeling damage recognition compared to the path signals away from the damaged area.Consequently,the proposed monitoring method in the fatigue test dataset is adept at accurately tracking and recognizing the progression of fatigue damage.
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)。
文摘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.
文摘BACKGROUND Adrenocortical oncocytoma is a rare,mostly benign,nonfunctional tumor that is typically detected incidentally.Its diagnosis is challenging because of the absence of distinctive imaging characteristics,necessitating pathological validation.CASE SUMMARY We present a case report of a 35-year-old woman with an adrenal mass located on the left side,where endoscopic ultrasound-guided fine-needle aspiration(EUSFNA)was performed after comprehensive diagnostic assessment.Our results are consistent with those of previously documented cases regarding tumor demographics and anatomical location.Given the limited number of reports on this condition,long-term follow-up is crucial to enhance our understanding of its prognosis.CONCLUSION For patients with adrenocortical oncocytoma,EUS-FNA can enables collection of preoperative tissue specimens leading to suitable treatment strategies.
基金supported by Ministry of Research and Technology/National Research and Innovation Agency Program scheme PDP(Research for Beginner Lecturers)2021(No.B/112/E3/RA.00/2021).
文摘Objective:The use of technology is growing rapidly.It can also be used in nursing interventions.A technology pack can support nursing interventions.An application called guided imagery in Indonesian(GIANESIA)has been developed to reduce anxiety in preoperative patients.Methods:A total of 42 participants joined this research.The respondents were those who would undergo surgery.We used the numeric visual analog anxiety scale(NVAAS)as the instrument to measure their anxiety levels.The participants were first given informed consent.Then,they open the application that has been installed.The process begins with participants choosing their initial anxiety score.Later,they start the therapy session,and immediately after finishing it,a pop-up bar prompts them to enter their final,posttherapy anxiety score.Results:This study shows the effectiveness of therapy given by GIANESIA in reducing anxiety in preoperative patients with p-value=0.000(a<0.05).Also,61.9%of the participants had decreased anxiety levels after therapy with GIANESIA.Conclusions:This study proves that providing therapy via a mobile application is effective in easing uncomfortable feelings,especially anxiety,in preoperative patients.Moving forward,the app can and should be expanded with new features and further developmental goals.
文摘BACKGROUND Femur fractures are one of the most serious injuries that occur in the older population and are associated with severe pain and increased mortality.The primary objective of this study was to find if there was a significant difference in pain scores in patients treated with femoral nerve blocks(FNB)compared with patients treated with the standard analgesia protocol.The secondary objective was to find if there was a significant difference in morbidity between the two groups.AIM To evaluate the effectiveness of ultrasound(US)-guided FNB in managing preoperative pain and reducing morbidity in patients with neck femur fractures compared to the standard analgesia protocol.The study seeks to determine whether FNB offers superior outcomes in terms of pain control,rehospitalization rates,and mortality.METHODS This retrospective cohort study included 1577 patients suffering from neck femur fractures.387 patients were treated with a FNB for pain management upon arrival at the emergency department,the rest were treated with standard analgesia.Pain was assessed from electronic medical records using the visual analogue scale(VAS)pre surgery,12-and 24-hour post-surgery.To determine morbidity and mortality during hospitalizations and 6 months after,it was collected from electronic medical records.RESULTS In a cohort of 1577 patients,those receiving US-guided FNB had significantly lower preoperative VAS pain scores(1.46±2.49 vs 1.82±2.59,P=0.001),reduced rehospitalization rates(0.99±1.96 vs 1.46±2.34,P<0.001),and lower mortality(16%vs 32%,P<0.001)compared to standard analgesia.CONCLUSION US guided FNB is more effective for pain management compared with standard analgesia.This method was also found to significantly reduce the risk of morbidity in those patients.
基金the Department of Biotechnology(DBT),New Delhi[grant number BT/PR52345/BSA/33/37/2024(CN19592)]Indian Council of Medical Research(ICMR),New Delhi(grant number NIMR/Proj/Intra/HMM/134/24)D.P.and R.P.R.would like to acknowledge DBT Fellowships(DBT/2021-22/NIAB/1706&DBT/2022-23/NIAB/2051)provided by the Department of Biotechnology(DBT),New Delhi.
文摘Nanotechnology has substantially advanced imaging,therapy,and clinical techniques,playing a crucial role in the development of sustainable functional materials in biomedical engineering.Nanoparticles,used as contrast agents in multimodal imaging,offer notable advantages due to their high surface areato-volume ratio,enabling functionalization with targeting ligands for improved specificity and sensitivity.They can also carry multiple imaging agents or therapeutic drugs,promoting theranostics,an approach combining diagnosis and treatment.However,the need for high-dose contrast agents raises concerns about nanoparticle toxicity.Green nanotechnology addresses this by developing sustainable nanoparticles through eco-friendly synthesis methods,reducing environmental and health risks.Moreover,by using this method,safer imaging agents that align with current health standards can be generated.In parallel,recent advancements in artificial intelligence(AI)are transforming imaging applications.Beyond simple automation of image interpretation,AI is enhancing image acquisition,management,and interpretation,signaling a future where intelligent systems play a key role in healthcare.This review explores the diverse nanomaterials utilized as contrast agents in multimodal imaging,highlights the importance of green nanotechnology in minimizing toxicity,and emphasizes on the important role of AI in imaging and imageguided therapy.Together,these innovations are advancing precision healthcare,promising a future where diagnostics and treatment are not only more effective but also sustainable.
文摘Correction to:Neuroscience Bulletin https://doi.org/10.1007/s12264-025-01371-x In this article the affiliation"Department of Circuit Theory,Faculty of Electrical Engineering,Czech Technical University in Prague,Member of the Epilepsy Research Centre Prague-EpiReC Consortium,Prague,Czechia"should only be assigned to Radek Janca and Petr Jezdik.It is removed from the authors:Jiri Hammer,Michaela Kajsova,Adam Kalina,Petr Marusic,and Kamil Vlcek.
基金supported by the National Natural Science Foundation of China(62373224)by the Natural Science Foundation of Shandong Province(ZR2024JQ021).
文摘Dear Editor,This letter addresses the enhancement of autonomous vehicles’(AVs)behavior control systems through the application of reinforcement learning(RL)techniques.It presents a novel approach to efficient knowledge-guided self-evolutionary intelligent decision-making by integrating human intervention as prior knowledge into the RL’s exploratory learning process.Specifically,we propose an innovative intervention-based reward shaping mechanism and develop a novel experience replay mechanism to augment the efficiency of leveraging guided knowledge within the framework of off-policy RL.The proposed methodology significantly enhances the performance of RL-based behavior control strategies in complex scenarios for AVs.Illustrative results indicate that,relative to existing state-of-theart methods,our approach yields superior learning efficiency and improved autonomous driving performance.
基金supported by grants(92168103,32171417,2019CXJQ01)from the National Nature Science Foundation of China,Shanghai Municipal GovernmentPeak Disciplines(Type IV)of Institutions of Higher Learning in Shanghai.
文摘Genome rearrangement is an important process that leads to genetic diversity,including mutation-related insertions,deletions,or inversions in the genome[1,2].
基金funded by the National Natural Science Foundation of China (Grant No. 62471048)Open Fund Project of Beijing Key Laboratory of High Dynamic Navigation TechnologyKey Laboratory Fund Project of Modern Measurement and Control Technology, Ministry of Education
文摘In complex environments such as high dynamics and weak signals,a satellite signal compensation method based on prefabricated trajectory assistance and an improved adaptive Kalman filter is proposed for a 155 mm differential rotating rear-body control-guided projectile to address the situation of satellite signal flickering and loss in projectile navigation systems due to environmental limitations.First,establish the system state and measurement equation when receiving satellite signals normally.Second,a seven-degree-of-freedom external ballistic model is constructed,and the ideal trajectory output from the ballistic model is used to provide the virtual motion state of the projectile,which is input into a filter as a substitute observation when satellite signals are lost.Finally,an adaptive Kalman filter(AKF)is designed,the proposed adaptive Kalman filter can accurately adjust the estimation error covariance matrix and Kalman gain in real-time based on information covariance mismatch.The simulation results show that compared to the classical Kalman filter,it can reduce the average positioning error by more than 38.21%in the case of short-term and full-range loss of satellite signals,providing a new idea for the integrated navigation of projectiles with incomplete information under the condition of satellite signal loss.
