Synaptic plasticity is essential for maintaining neuronal function in the central nervous system and serves as a critical indicator of the effects of neurodegenerative disease.Glaucoma directly impairs retinal ganglio...Synaptic plasticity is essential for maintaining neuronal function in the central nervous system and serves as a critical indicator of the effects of neurodegenerative disease.Glaucoma directly impairs retinal ganglion cells and their axons,leading to axonal transport dysfuntion,subsequently causing secondary damage to anterior or posterior ends of the visual system.Accordingly,recent evidence indicates that glaucoma is a degenerative disease of the central nervous system that causes damage throughout the visual pathway.However,the effects of glaucoma on synaptic plasticity in the primary visual cortex remain unclear.In this study,we established a mouse model of unilateral chronic ocular hypertension by injecting magnetic microbeads into the anterior chamber of one eye.We found that,after 4 weeks of chronic ocular hypertension,the neuronal somas were smaller in the superior colliculus and lateral geniculate body regions of the brain contralateral to the affected eye.This was accompanied by glial cell activation and increased expression of inflammatory factors.After 8 weeks of ocular hypertension,we observed a reduction in the number of excitatory and inhibitory synapses,dendritic spines,and activation of glial cells in the primary visual cortex contralateral to the affected eye.These findings suggest that glaucoma not only directly damages the retina but also induces alterations in synapses and dendritic spines in the primary visual cortex,providing new insights into the pathogenesis of glaucoma.展开更多
AIM:To identify early biomarkers associated with glaucomatous visual field(VF)progression in patients with normal-tension glaucoma(NTG).METHODS:This study included patients were divided into two groups based on diseas...AIM:To identify early biomarkers associated with glaucomatous visual field(VF)progression in patients with normal-tension glaucoma(NTG).METHODS:This study included patients were divided into two groups based on disease progression status.Tear samples were collected for proteomic analysis.Dataindependent acquisition(DIA)mass spectrometry combined with bioinformatic analyses was performed to identify and validate potential protein biomarkers for NTG progression.Additionally,differentially expressed proteins(DEPs)were evaluated using mediating effect models and receiver operating characteristic(ROC)curve analysis.RESULTS:A total of 19 patients(20 eyes)with NTG participated in this study,including 10 patients(4 males and 6 females;10 eyes)in the progression group with mean age of 67.70±9.03y and 10 patients(4 males and 6 females;10 eyes)in the non-progression group with mean age of 68.60±7.58y.A total of 158 significantly differentially expressed proteins were detected.UniProt database annotation identified 3 upregulated proteins and 12 downregulated proteins.Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway analysis showed that these DEPs were mainly enriched in pathways such as oocyte meiosis.Gene Ontology(GO)enrichment analysis revealed functional clusters related to cellular processes.Weighted gene coexpression network analysis(WGCNA)indicated that the core proteins were primarily involved in the neurodegenerationmultiple diseases pathway and cellular processes.Mediating effect analysis identified PRDX4(L)as a potential protein biomarker.ROC curve analysis showed that GNAI1 had the largest area under the curve(AUC=0.889).CONCLUSION:This study identifies 15 differentially expressed proteins in the tear fluid of NTG patients,including PRDX4(L).PRDX4(L)plays a key role in oxidative stress.展开更多
The intersection of visual impairment and mental health has profound effects on quality of life and warrants attention from healthcare providers,educators,and policymakers.With 20 million children under the age of 14 ...The intersection of visual impairment and mental health has profound effects on quality of life and warrants attention from healthcare providers,educators,and policymakers.With 20 million children under the age of 14 affected globally,older adults also experience significant psychological impact including depression,anxiety,and cognitive impairment.The implications of vision-related challenges extend far beyond mere sight.Depression and anxiety,exacerbated by social isolation and reduced physical activity,underscore the need for comprehensive interventions that address both medical and psychosocial dimensions.By recognizing the profound impact of ocular morbidities like strabismus,myopia,glaucoma,and age-related macular degeneration on mental health and investing in effective treatments and inclusive practices,society can pave the way for a healthier,more equitable future for affected individuals.There is evidence that myopic children experience a higher prevalence of depressive symptoms compared to their normal peers,and interventions like the correction of strabismus can enhance psychological outcome-demonstrating the value of an integrated management approach.展开更多
AIM:To evaluate long-term visual field(VF)prediction using K-means clustering in patients with primary open angle glaucoma(POAG).METHODS:Patients who underwent 24-2 VF tests≥10 were included in this study.Using 52 to...AIM:To evaluate long-term visual field(VF)prediction using K-means clustering in patients with primary open angle glaucoma(POAG).METHODS:Patients who underwent 24-2 VF tests≥10 were included in this study.Using 52 total deviation values(TDVs)from the first 10 VF tests of the training dataset,VF points were clustered into several regions using the hierarchical ordered partitioning and collapsing hybrid(HOPACH)and K-means clustering.Based on the clustering results,a linear regression analysis was applied to each clustered region of the testing dataset to predict the TDVs of the 10th VF test.Three to nine VF tests were used to predict the 10th VF test,and the prediction errors(root mean square error,RMSE)of each clustering method and pointwise linear regression(PLR)were compared.RESULTS:The training group consisted of 228 patients(mean age,54.20±14.38y;123 males and 105 females),and the testing group included 81 patients(mean age,54.88±15.22y;43 males and 38 females).All subjects were diagnosed with POAG.Fifty-two VF points were clustered into 11 and nine regions using HOPACH and K-means clustering,respectively.K-means clustering had a lower prediction error than PLR when n=1:3 and 1:4(both P≤0.003).The prediction errors of K-means clustering were lower than those of HOPACH in all sections(n=1:4 to 1:9;all P≤0.011),except for n=1:3(P=0.680).PLR outperformed K-means clustering only when n=1:8 and 1:9(both P≤0.020).CONCLUSION:K-means clustering can predict longterm VF test results more accurately in patients with POAG with limited VF data.展开更多
Embodied visual exploration is critical for building intelligent visual agents. This paper presents the neural exploration with feature-based visual odometry and tracking-failure-reduction policy(Ne OR), a framework f...Embodied visual exploration is critical for building intelligent visual agents. This paper presents the neural exploration with feature-based visual odometry and tracking-failure-reduction policy(Ne OR), a framework for embodied visual exploration that possesses the efficient exploration capabilities of deep reinforcement learning(DRL)-based exploration policies and leverages feature-based visual odometry(VO) for more accurate mapping and positioning results. An improved local policy is also proposed to reduce tracking failures of feature-based VO in weakly textured scenes through a refined multi-discrete action space, keyframe fusion, and an auxiliary task. The experimental results demonstrate that Ne OR has better mapping and positioning accuracy compared to other entirely learning-based exploration frameworks and improves the robustness of feature-based VO by significantly reducing tracking failures in weakly textured scenes.展开更多
The visual cortex is an essential part of the brain for processing visual information.It exhibits structural and functional plasticity,which is crucial for adapting to complex visual environments.The quintessential ma...The visual cortex is an essential part of the brain for processing visual information.It exhibits structural and functional plasticity,which is crucial for adapting to complex visual environments.The quintessential manifestation of visual cortical plasticity is ocular dominance plasticity during the critical period,which involves numerous cellular and molecular events.While previous studies have emphasized the role of visual cortical neurons and their associated functional molecules in visual plasticity,recent findings have revealed that structural factors such as the extracellular matrix and glia are also involved.Investigating how these molecules interact to form a complex network that facilitates plasticity in the visual cortex is crucial to our understanding of the development of the visual system and the advancement of therapeutic strategies for visual disorders like amblyopia.展开更多
Despite the global attention towards pollution,it remains a significant global threat and challenge for both developed and developing countries.Urbanization and economic development influence different types of pollut...Despite the global attention towards pollution,it remains a significant global threat and challenge for both developed and developing countries.Urbanization and economic development influence different types of pollution.Visual pollution is considered a new phenomenon referring to the impact of existing and growing mainstream pollution which impairs an individual’s ability to enjoy visits or views.Recently,Jordanian cities have expanded in response to urbanization and ongoing development.Irbid City has the second largest population in Jordan after the capital Amman City highest population density in Jordan.In the modern era,Irbid City dramatically increased in population and dimension.The growth of the demographic population has been significant and has led to overpopulation,rapid urbanization,and unresolved problems associated with spatial planning and infrastructures leading to different types of pollution including visual pollution.The study area focuses on the city center with the most crowded population through field visits and actual observations.The study technique is descriptive and analytical,with a focus on meticulous monitoring and a follow-up-based questionnaire which is a tool for the study,involving data collection,classification,presentation,analysis,interpretation,and exploration to identify new facts and generalizations that can help solve current issues of visual pollution.The study provides recommendations for Irbid Municipal to eliminate visual pollution,in parallel with stricter supervision from the municipality during the building process to ensure proper implementation of the new rules,adopting an integrated policy for the city with the rest of the social,political,sensory,cultural,economic,and functional aspects,so that this policy is in the short and long term.展开更多
Throughout the lifespan,an animal can encounter predators frequently,thus the ability to avoid attacks from predators is crucial for its survival.The chances of evading danger can be greatly improved if the animal can...Throughout the lifespan,an animal can encounter predators frequently,thus the ability to avoid attacks from predators is crucial for its survival.The chances of evading danger can be greatly improved if the animal can respond immediately to the threat.Therefore,when an animal detects a threat through its visual system,it must quickly direct its gaze and attention toward the source of danger,assess the threat level,and take appropriate action.展开更多
In recent years,the rapid development of artificial intelligence has driven the widespread deployment of visual systems in complex environments such as autonomous driving,security surveillance,and medical diagnosis.Ho...In recent years,the rapid development of artificial intelligence has driven the widespread deployment of visual systems in complex environments such as autonomous driving,security surveillance,and medical diagnosis.However,existing image sensors—such as CMOS and CCD devices—intrinsically suffer from the limitation of fixed spectral response.Especially in environments with strong glare,haze,or dust,external spectral conditions often severely mismatch the device's design range,leading to significant degradation in image quality and a sharp drop in target recognition accuracy.While algorithmic post-processing(such as color bias correction or background suppression)can mitigate these issues,algorithm approaches typically introduce computational latency and increased energy consumption,making them unsuitable for edge computing or high-speed scenarios.展开更多
As industrial production progresses toward digitalization,massive amounts of data have been collected,transmitted,and stored,with characteristics of large-scale,high-dimensional,heterogeneous,and spatiotemporal dynami...As industrial production progresses toward digitalization,massive amounts of data have been collected,transmitted,and stored,with characteristics of large-scale,high-dimensional,heterogeneous,and spatiotemporal dynamics.The high complexity of industrial big data poses challenges for the practical decision-making of domain experts,leading to ever-increasing needs for integrating computational intelligence with human perception into traditional data analysis.Industrial big data visualization integrates theoretical methods and practical technologies from multiple disciplines,including data mining,information visualization,computer graphics,and human-computer interaction,providing a highly effective manner for understanding and exploring the complex industrial processes.This review summarizes the state-of-the-art approaches,characterizes them with six visualization methods,and categorizes them based on analytical tasks and applications.Furthermore,key research challenges and potential future directions are identified.展开更多
Image captioning,the task of generating descriptive sentences for images,has advanced significantly with the integration of semantic information.However,traditional models still rely on static visual features that do ...Image captioning,the task of generating descriptive sentences for images,has advanced significantly with the integration of semantic information.However,traditional models still rely on static visual features that do not evolve with the changing linguistic context,which can hinder the ability to form meaningful connections between the image and the generated captions.This limitation often leads to captions that are less accurate or descriptive.In this paper,we propose a novel approach to enhance image captioning by introducing dynamic interactions where visual features continuously adapt to the evolving linguistic context.Our model strengthens the alignment between visual and linguistic elements,resulting in more coherent and contextually appropriate captions.Specifically,we introduce two innovative modules:the Visual Weighting Module(VWM)and the Enhanced Features Attention Module(EFAM).The VWM adjusts visual features using partial attention,enabling dynamic reweighting of the visual inputs,while the EFAM further refines these features to improve their relevance to the generated caption.By continuously adjusting visual features in response to the linguistic context,our model bridges the gap between static visual features and dynamic language generation.We demonstrate the effectiveness of our approach through experiments on the MS-COCO dataset,where our method outperforms state-of-the-art techniques in terms of caption quality and contextual relevance.Our results show that dynamic visual-linguistic alignment significantly enhances image captioning performance.展开更多
In the visual‘teach-and-repeat’task,a mobile robot is expected to perform path following based on visual memory acquired along a route that it has traversed.Following a visually familiar route is also a critical nav...In the visual‘teach-and-repeat’task,a mobile robot is expected to perform path following based on visual memory acquired along a route that it has traversed.Following a visually familiar route is also a critical navigation skill for foraging insects,which they accomplish robustly despite tiny brains.Inspired by the mushroom body structure in the insect brain and its well-understood associative learning ability,we develop an embodied model that can accomplish visual teach-and-repeat efficiently.Critical to the performance is steering the robot body reflexively based on the relative familiarity of left and right visual fields,eliminating the need for stopping and scanning regularly for optimal directions.The model is robust against noise in visual processing and motor control and can produce performance comparable to pure pursuit or visual localisation methods that rely heavily on the estimation of positions.The model is tested on a real robot and also shown to be able to correct for significant intrinsic steering bias.展开更多
The dorsal and ventral visual streams have been considered to play distinct roles in visual processing for action:the dorsal stream is assumed to support real-time actions,while the ventral stream facilitates memory-g...The dorsal and ventral visual streams have been considered to play distinct roles in visual processing for action:the dorsal stream is assumed to support real-time actions,while the ventral stream facilitates memory-guided actions.However,recent evidence suggests a more integrated function of these streams.We investigated the neural dynamics and functional connectivity between them during memory-guided actions using intracranial EEG.We tracked neural activity in the inferior parietal lobule in the dorsal stream,and the ventral temporal cortex in the ventral stream as well as the hippocampus during a delayed action task involving object identity and location memory.We found increased alpha power in both streams during the delay,indicating their role in maintaining spatial visual information.In addition,we recorded increased alpha power in the hippocampus during the delay,but only when both object identity and location needed to be remembered.We also recorded an increase in theta band phase synchronization between the inferior parietal lobule and ventral temporal cortex and between the inferior parietal lobule and hippocampus during the encoding and delay.Granger causality analysis indicated dynamic and frequency-specific directional interactions among the inferior parietal lobule,ventral temporal cortex,and hippocampus that varied across task phases.Our study provides unique electrophysiological evidence for close interactions between dorsal and ventral streams,supporting an integrated processing model in which both streams contribute to memory-guided actions.展开更多
Fig.1.The GenomeSyn tool for visualizing genome synteny and characterizing structural variations.A:The first synteny visualization map showed the detailed information of two or three genomes and can display structural...Fig.1.The GenomeSyn tool for visualizing genome synteny and characterizing structural variations.A:The first synteny visualization map showed the detailed information of two or three genomes and can display structural variations and other annotation information.B:The second type of visualization map was simple and only showed the synteny relationship between the chromosomes of two or three genomes.C:Multiplatform general GenomeSyn submission page,applicable to Windows,MAC and web platforms;other analysis files can be entered in the"other"option.The publisher would like to apologise for any inconvenience caused.展开更多
BACKGROUND Anterior visual pathway lesions can cause severe visual loss.Optical coherence tomography(OCT)can detect ganglion cell complex(GCC)thinning,even with normal retinal nerve fiber layer(RNFL)thickness and subt...BACKGROUND Anterior visual pathway lesions can cause severe visual loss.Optical coherence tomography(OCT)can detect ganglion cell complex(GCC)thinning,even with normal retinal nerve fiber layer(RNFL)thickness and subtle visual field changes.AIM To determine the proportion of eyes with RNFL and GCC thinning and their association with visual parameters in patients with brain tumors undergoing surgery.METHODS A prospective study was conducted on 37 patients(69 eyes)with peri-chiasmatic and chiasmatic brain tumors undergoing surgical decompression between February 2019 and June 2020 at a tertiary care institute.A comprehensive neuroophthalmological work-up,demographic and clinical profile documentation,and six-month postoperative follow-up weredone.Statistical analysis was significant at P<0.05.RESULTS Mean age was 35.14±11.98 years.The best and worst visual outcomes were associated with the craniopharyngioma and meningioma groups,respectively(P=0.008).There was an increase in the proportion of eyes with RNFL damage in the inferior quadrant(P=0.02).Maximum GCC thickness thinning was associated with severe visual impairment.The odds of having blindness in eyes with RNFL(inferior)and GCC loss were 0.96(P=0.003)and 0.95(P=0.03),respectively.GCC thickness showed a clinically positive correlation with visual acuity(r=-0.48,P<0.001)and field defect(r=-0.27,P=0.04)at six months postoperatively.The preoperative GCC thickness and the final postoperative visual outcome were plotted in an empirical ROC curve with area under the curve=0.754.The cut-off value of RNFL(inferior)and GCC,beyond which blindness could be prevented,was 73μm and 58μm,respectively.CONCLUSION In chiasmal compression,RNFL and GCC thickness measurements using OCT can be a useful prognostic indicator for assessing visual recovery.An eye with structural damage,with significant RNFL and GCC loss,is a predictive factor of blindness.A minimum preoperative RNFL and GCC thickness of 73μm and 58μm,respectively,can preserve vision after surgery.展开更多
Accessible communication based on sign language recognition(SLR)is the key to emergency medical assistance for the hearing-impaired community.Balancing the capture of both local and global information in SLR for emerg...Accessible communication based on sign language recognition(SLR)is the key to emergency medical assistance for the hearing-impaired community.Balancing the capture of both local and global information in SLR for emergency medicine poses a significant challenge.To address this,we propose a novel approach based on the inter-learning of visual features between global and local information.Specifically,our method enhances the perception capabilities of the visual feature extractor by strategically leveraging the strengths of convolutional neural network(CNN),which are adept at capturing local features,and visual transformers which perform well at perceiving global features.Furthermore,to mitigate the issue of overfitting caused by the limited availability of sign language data for emergency medical applications,we introduce an enhanced short temporal module for data augmentation through additional subsequences.Experimental results on three publicly available sign language datasets demonstrate the efficacy of the proposed approach.展开更多
Visual entailment(VE)is a prototypical task in multimodal visual reasoning,where current methods frequently utilize large language models(LLMs)as the knowledge base to assist in answering questions.These methods heavi...Visual entailment(VE)is a prototypical task in multimodal visual reasoning,where current methods frequently utilize large language models(LLMs)as the knowledge base to assist in answering questions.These methods heavily rely on the textual modality,which inherently cannot capture the full extent of information contained within images.We propose a context-aware visual entailment(CAVE)model,which introduces a novel aggregation module designed to extract high-level semantic features from images.This module integrates lower-level semantic image features into high-level visual tokens,formatting them similarly to text tokens so that they can serve as inputs for LLMs.The CAVE model compensates for the loss of image information and integrates it more effectively with textual comprehension.Additionally,the CAVE model incorporates a new input format and training methodology,which is rooted in instruction tuning and in-context learning techniques.The objective of this research is to maximize the inherent logical reasoning capabilities of LLMs.Experimental results on the E-SNLIVE dataset show that the proposed CAVE model exhibits outstanding performance.展开更多
The methods of visual recognition,positioning and orienting with simple 3 D geometric workpieces are presented in this paper.The principle and operating process of multiple orientation run le...The methods of visual recognition,positioning and orienting with simple 3 D geometric workpieces are presented in this paper.The principle and operating process of multiple orientation run length coding based on general orientation run length coding and visual recognition method are described elaborately.The method of positioning and orientating based on the moment of inertia of the workpiece binary image is stated also.It has been applied in a research on flexible automatic coordinate measuring system formed by integrating computer aided design,computer vision and computer aided inspection planning,with a coordinate measuring machine.The results show that integrating computer vision with measurement system is a feasible and effective approach to improve their flexibility and automation.展开更多
基金supported by the National Natural Science Foundation of China,No.82271115(to MY).
文摘Synaptic plasticity is essential for maintaining neuronal function in the central nervous system and serves as a critical indicator of the effects of neurodegenerative disease.Glaucoma directly impairs retinal ganglion cells and their axons,leading to axonal transport dysfuntion,subsequently causing secondary damage to anterior or posterior ends of the visual system.Accordingly,recent evidence indicates that glaucoma is a degenerative disease of the central nervous system that causes damage throughout the visual pathway.However,the effects of glaucoma on synaptic plasticity in the primary visual cortex remain unclear.In this study,we established a mouse model of unilateral chronic ocular hypertension by injecting magnetic microbeads into the anterior chamber of one eye.We found that,after 4 weeks of chronic ocular hypertension,the neuronal somas were smaller in the superior colliculus and lateral geniculate body regions of the brain contralateral to the affected eye.This was accompanied by glial cell activation and increased expression of inflammatory factors.After 8 weeks of ocular hypertension,we observed a reduction in the number of excitatory and inhibitory synapses,dendritic spines,and activation of glial cells in the primary visual cortex contralateral to the affected eye.These findings suggest that glaucoma not only directly damages the retina but also induces alterations in synapses and dendritic spines in the primary visual cortex,providing new insights into the pathogenesis of glaucoma.
基金Supported by The Eye Hospital of Wenzhou Medical University(No.KYQD20220304)The Fifth Batch of Provincial Ten Thousand Personnel Program Outstanding Talents Funding(No.474092204)+1 种基金Innovative Talents and Teams(2024)-The Fifth Batch of Funding Funds for Scientific and Technological Innovation Leading Talents Under the Provincial Ten Thousand Personnel Program(No.4240924003G)The Key R&D Program of Zhejiang(No.2022C03112).
文摘AIM:To identify early biomarkers associated with glaucomatous visual field(VF)progression in patients with normal-tension glaucoma(NTG).METHODS:This study included patients were divided into two groups based on disease progression status.Tear samples were collected for proteomic analysis.Dataindependent acquisition(DIA)mass spectrometry combined with bioinformatic analyses was performed to identify and validate potential protein biomarkers for NTG progression.Additionally,differentially expressed proteins(DEPs)were evaluated using mediating effect models and receiver operating characteristic(ROC)curve analysis.RESULTS:A total of 19 patients(20 eyes)with NTG participated in this study,including 10 patients(4 males and 6 females;10 eyes)in the progression group with mean age of 67.70±9.03y and 10 patients(4 males and 6 females;10 eyes)in the non-progression group with mean age of 68.60±7.58y.A total of 158 significantly differentially expressed proteins were detected.UniProt database annotation identified 3 upregulated proteins and 12 downregulated proteins.Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway analysis showed that these DEPs were mainly enriched in pathways such as oocyte meiosis.Gene Ontology(GO)enrichment analysis revealed functional clusters related to cellular processes.Weighted gene coexpression network analysis(WGCNA)indicated that the core proteins were primarily involved in the neurodegenerationmultiple diseases pathway and cellular processes.Mediating effect analysis identified PRDX4(L)as a potential protein biomarker.ROC curve analysis showed that GNAI1 had the largest area under the curve(AUC=0.889).CONCLUSION:This study identifies 15 differentially expressed proteins in the tear fluid of NTG patients,including PRDX4(L).PRDX4(L)plays a key role in oxidative stress.
文摘The intersection of visual impairment and mental health has profound effects on quality of life and warrants attention from healthcare providers,educators,and policymakers.With 20 million children under the age of 14 affected globally,older adults also experience significant psychological impact including depression,anxiety,and cognitive impairment.The implications of vision-related challenges extend far beyond mere sight.Depression and anxiety,exacerbated by social isolation and reduced physical activity,underscore the need for comprehensive interventions that address both medical and psychosocial dimensions.By recognizing the profound impact of ocular morbidities like strabismus,myopia,glaucoma,and age-related macular degeneration on mental health and investing in effective treatments and inclusive practices,society can pave the way for a healthier,more equitable future for affected individuals.There is evidence that myopic children experience a higher prevalence of depressive symptoms compared to their normal peers,and interventions like the correction of strabismus can enhance psychological outcome-demonstrating the value of an integrated management approach.
基金Supported by the Korea Health Technology R&D Project through the Korea Health Industry Development Institute(KHIDI),the Ministry of Health&Welfare,Republic of Korea(No.RS-2020-KH088726)the Patient-Centered Clinical Research Coordinating Center(PACEN),the Ministry of Health and Welfare,Republic of Korea(No.HC19C0276)the National Research Foundation of Korea(NRF),the Korea Government(MSIT)(No.RS-2023-00247504).
文摘AIM:To evaluate long-term visual field(VF)prediction using K-means clustering in patients with primary open angle glaucoma(POAG).METHODS:Patients who underwent 24-2 VF tests≥10 were included in this study.Using 52 total deviation values(TDVs)from the first 10 VF tests of the training dataset,VF points were clustered into several regions using the hierarchical ordered partitioning and collapsing hybrid(HOPACH)and K-means clustering.Based on the clustering results,a linear regression analysis was applied to each clustered region of the testing dataset to predict the TDVs of the 10th VF test.Three to nine VF tests were used to predict the 10th VF test,and the prediction errors(root mean square error,RMSE)of each clustering method and pointwise linear regression(PLR)were compared.RESULTS:The training group consisted of 228 patients(mean age,54.20±14.38y;123 males and 105 females),and the testing group included 81 patients(mean age,54.88±15.22y;43 males and 38 females).All subjects were diagnosed with POAG.Fifty-two VF points were clustered into 11 and nine regions using HOPACH and K-means clustering,respectively.K-means clustering had a lower prediction error than PLR when n=1:3 and 1:4(both P≤0.003).The prediction errors of K-means clustering were lower than those of HOPACH in all sections(n=1:4 to 1:9;all P≤0.011),except for n=1:3(P=0.680).PLR outperformed K-means clustering only when n=1:8 and 1:9(both P≤0.020).CONCLUSION:K-means clustering can predict longterm VF test results more accurately in patients with POAG with limited VF data.
基金supported by the National Natural Science Foundation of China (No.62202137)the China Postdoctoral Science Foundation (No.2023M730599)the Zhejiang Provincial Natural Science Foundation of China (No.LMS25F020009)。
文摘Embodied visual exploration is critical for building intelligent visual agents. This paper presents the neural exploration with feature-based visual odometry and tracking-failure-reduction policy(Ne OR), a framework for embodied visual exploration that possesses the efficient exploration capabilities of deep reinforcement learning(DRL)-based exploration policies and leverages feature-based visual odometry(VO) for more accurate mapping and positioning results. An improved local policy is also proposed to reduce tracking failures of feature-based VO in weakly textured scenes through a refined multi-discrete action space, keyframe fusion, and an auxiliary task. The experimental results demonstrate that Ne OR has better mapping and positioning accuracy compared to other entirely learning-based exploration frameworks and improves the robustness of feature-based VO by significantly reducing tracking failures in weakly textured scenes.
基金supported by the National Natural Science Foundation of China(81770956,81371049,32471055 and 82171090)Project of Tianjin 131 Innovative Talent Team(201936)+4 种基金the Science and Technology Planning Project of Tianjin(21JCYBJC00780)the Science and Technology Fund for Health of Tianjin(TJWJ2023ZD008)Shanghai Municipal Science and Technology Major Project(2018SHZDZX01)ZJLab,Shanghai Center for Brain Science and Brain-Inspired Technology,the Lingang Laboratory(LG-QS-202203-12)Tianjin Key Medical Discipline(Specialty)Construction Project(TJYXZDXK‑016A).
文摘The visual cortex is an essential part of the brain for processing visual information.It exhibits structural and functional plasticity,which is crucial for adapting to complex visual environments.The quintessential manifestation of visual cortical plasticity is ocular dominance plasticity during the critical period,which involves numerous cellular and molecular events.While previous studies have emphasized the role of visual cortical neurons and their associated functional molecules in visual plasticity,recent findings have revealed that structural factors such as the extracellular matrix and glia are also involved.Investigating how these molecules interact to form a complex network that facilitates plasticity in the visual cortex is crucial to our understanding of the development of the visual system and the advancement of therapeutic strategies for visual disorders like amblyopia.
文摘Despite the global attention towards pollution,it remains a significant global threat and challenge for both developed and developing countries.Urbanization and economic development influence different types of pollution.Visual pollution is considered a new phenomenon referring to the impact of existing and growing mainstream pollution which impairs an individual’s ability to enjoy visits or views.Recently,Jordanian cities have expanded in response to urbanization and ongoing development.Irbid City has the second largest population in Jordan after the capital Amman City highest population density in Jordan.In the modern era,Irbid City dramatically increased in population and dimension.The growth of the demographic population has been significant and has led to overpopulation,rapid urbanization,and unresolved problems associated with spatial planning and infrastructures leading to different types of pollution including visual pollution.The study area focuses on the city center with the most crowded population through field visits and actual observations.The study technique is descriptive and analytical,with a focus on meticulous monitoring and a follow-up-based questionnaire which is a tool for the study,involving data collection,classification,presentation,analysis,interpretation,and exploration to identify new facts and generalizations that can help solve current issues of visual pollution.The study provides recommendations for Irbid Municipal to eliminate visual pollution,in parallel with stricter supervision from the municipality during the building process to ensure proper implementation of the new rules,adopting an integrated policy for the city with the rest of the social,political,sensory,cultural,economic,and functional aspects,so that this policy is in the short and long term.
基金supported by the National Natural Science Foundation of China(32471055 and 82171090)Shanghai Municipal Science and Technology Major Project(2018SHZDZX01)ZJLab,Shanghai Center for Brain Science and Brain-Inspired Technology,the Lingang Laboratory(LG-QS-202203-12).
文摘Throughout the lifespan,an animal can encounter predators frequently,thus the ability to avoid attacks from predators is crucial for its survival.The chances of evading danger can be greatly improved if the animal can respond immediately to the threat.Therefore,when an animal detects a threat through its visual system,it must quickly direct its gaze and attention toward the source of danger,assess the threat level,and take appropriate action.
基金supported in part by STI 2030-Major Projects(2022ZD0209200)in part by National Natural Science Foundation of China(62374099)+2 种基金in part by Beijing Natural Science Foundation−Xiaomi Innovation Joint Fund(L233009)Beijing Natural Science Foundation(L248104)in part by Independent Research Program of School of Integrated Circuits,Tsinghua University,in part by Tsinghua University Fuzhou Data Technology Joint Research Institute.
文摘In recent years,the rapid development of artificial intelligence has driven the widespread deployment of visual systems in complex environments such as autonomous driving,security surveillance,and medical diagnosis.However,existing image sensors—such as CMOS and CCD devices—intrinsically suffer from the limitation of fixed spectral response.Especially in environments with strong glare,haze,or dust,external spectral conditions often severely mismatch the device's design range,leading to significant degradation in image quality and a sharp drop in target recognition accuracy.While algorithmic post-processing(such as color bias correction or background suppression)can mitigate these issues,algorithm approaches typically introduce computational latency and increased energy consumption,making them unsuitable for edge computing or high-speed scenarios.
基金supported in part by the National Key Research and Development Plan Project(2022YFB3304700)in part by the Xinliao Talent Program of Liaoning Province(XLYC2202002).
文摘As industrial production progresses toward digitalization,massive amounts of data have been collected,transmitted,and stored,with characteristics of large-scale,high-dimensional,heterogeneous,and spatiotemporal dynamics.The high complexity of industrial big data poses challenges for the practical decision-making of domain experts,leading to ever-increasing needs for integrating computational intelligence with human perception into traditional data analysis.Industrial big data visualization integrates theoretical methods and practical technologies from multiple disciplines,including data mining,information visualization,computer graphics,and human-computer interaction,providing a highly effective manner for understanding and exploring the complex industrial processes.This review summarizes the state-of-the-art approaches,characterizes them with six visualization methods,and categorizes them based on analytical tasks and applications.Furthermore,key research challenges and potential future directions are identified.
基金supported by the National Natural Science Foundation of China(Nos.U22A2034,62177047)High Caliber Foreign Experts Introduction Plan funded by MOST,and Central South University Research Programme of Advanced Interdisciplinary Studies(No.2023QYJC020).
文摘Image captioning,the task of generating descriptive sentences for images,has advanced significantly with the integration of semantic information.However,traditional models still rely on static visual features that do not evolve with the changing linguistic context,which can hinder the ability to form meaningful connections between the image and the generated captions.This limitation often leads to captions that are less accurate or descriptive.In this paper,we propose a novel approach to enhance image captioning by introducing dynamic interactions where visual features continuously adapt to the evolving linguistic context.Our model strengthens the alignment between visual and linguistic elements,resulting in more coherent and contextually appropriate captions.Specifically,we introduce two innovative modules:the Visual Weighting Module(VWM)and the Enhanced Features Attention Module(EFAM).The VWM adjusts visual features using partial attention,enabling dynamic reweighting of the visual inputs,while the EFAM further refines these features to improve their relevance to the generated caption.By continuously adjusting visual features in response to the linguistic context,our model bridges the gap between static visual features and dynamic language generation.We demonstrate the effectiveness of our approach through experiments on the MS-COCO dataset,where our method outperforms state-of-the-art techniques in terms of caption quality and contextual relevance.Our results show that dynamic visual-linguistic alignment significantly enhances image captioning performance.
基金support from the Huawei Technologies Co.,Ltd.[grant number YBN2020045132].
文摘In the visual‘teach-and-repeat’task,a mobile robot is expected to perform path following based on visual memory acquired along a route that it has traversed.Following a visually familiar route is also a critical navigation skill for foraging insects,which they accomplish robustly despite tiny brains.Inspired by the mushroom body structure in the insect brain and its well-understood associative learning ability,we develop an embodied model that can accomplish visual teach-and-repeat efficiently.Critical to the performance is steering the robot body reflexively based on the relative familiarity of left and right visual fields,eliminating the need for stopping and scanning regularly for optimal directions.The model is robust against noise in visual processing and motor control and can produce performance comparable to pure pursuit or visual localisation methods that rely heavily on the estimation of positions.The model is tested on a real robot and also shown to be able to correct for significant intrinsic steering bias.
基金supported by European Union–Next Generation EU(LX22NPO5107(MEYS))the Czech Science Foundation(20-21339S)+2 种基金the Grant Agency of Charles University(GAUK 248122 and 272221)ERDF-Project Brain Dynamics(CZ.02.01.01/00/22_008/0004643)the Ministry of Health of the Czech Republic Project NU21J-08-00081.
文摘The dorsal and ventral visual streams have been considered to play distinct roles in visual processing for action:the dorsal stream is assumed to support real-time actions,while the ventral stream facilitates memory-guided actions.However,recent evidence suggests a more integrated function of these streams.We investigated the neural dynamics and functional connectivity between them during memory-guided actions using intracranial EEG.We tracked neural activity in the inferior parietal lobule in the dorsal stream,and the ventral temporal cortex in the ventral stream as well as the hippocampus during a delayed action task involving object identity and location memory.We found increased alpha power in both streams during the delay,indicating their role in maintaining spatial visual information.In addition,we recorded increased alpha power in the hippocampus during the delay,but only when both object identity and location needed to be remembered.We also recorded an increase in theta band phase synchronization between the inferior parietal lobule and ventral temporal cortex and between the inferior parietal lobule and hippocampus during the encoding and delay.Granger causality analysis indicated dynamic and frequency-specific directional interactions among the inferior parietal lobule,ventral temporal cortex,and hippocampus that varied across task phases.Our study provides unique electrophysiological evidence for close interactions between dorsal and ventral streams,supporting an integrated processing model in which both streams contribute to memory-guided actions.
文摘Fig.1.The GenomeSyn tool for visualizing genome synteny and characterizing structural variations.A:The first synteny visualization map showed the detailed information of two or three genomes and can display structural variations and other annotation information.B:The second type of visualization map was simple and only showed the synteny relationship between the chromosomes of two or three genomes.C:Multiplatform general GenomeSyn submission page,applicable to Windows,MAC and web platforms;other analysis files can be entered in the"other"option.The publisher would like to apologise for any inconvenience caused.
文摘BACKGROUND Anterior visual pathway lesions can cause severe visual loss.Optical coherence tomography(OCT)can detect ganglion cell complex(GCC)thinning,even with normal retinal nerve fiber layer(RNFL)thickness and subtle visual field changes.AIM To determine the proportion of eyes with RNFL and GCC thinning and their association with visual parameters in patients with brain tumors undergoing surgery.METHODS A prospective study was conducted on 37 patients(69 eyes)with peri-chiasmatic and chiasmatic brain tumors undergoing surgical decompression between February 2019 and June 2020 at a tertiary care institute.A comprehensive neuroophthalmological work-up,demographic and clinical profile documentation,and six-month postoperative follow-up weredone.Statistical analysis was significant at P<0.05.RESULTS Mean age was 35.14±11.98 years.The best and worst visual outcomes were associated with the craniopharyngioma and meningioma groups,respectively(P=0.008).There was an increase in the proportion of eyes with RNFL damage in the inferior quadrant(P=0.02).Maximum GCC thickness thinning was associated with severe visual impairment.The odds of having blindness in eyes with RNFL(inferior)and GCC loss were 0.96(P=0.003)and 0.95(P=0.03),respectively.GCC thickness showed a clinically positive correlation with visual acuity(r=-0.48,P<0.001)and field defect(r=-0.27,P=0.04)at six months postoperatively.The preoperative GCC thickness and the final postoperative visual outcome were plotted in an empirical ROC curve with area under the curve=0.754.The cut-off value of RNFL(inferior)and GCC,beyond which blindness could be prevented,was 73μm and 58μm,respectively.CONCLUSION In chiasmal compression,RNFL and GCC thickness measurements using OCT can be a useful prognostic indicator for assessing visual recovery.An eye with structural damage,with significant RNFL and GCC loss,is a predictive factor of blindness.A minimum preoperative RNFL and GCC thickness of 73μm and 58μm,respectively,can preserve vision after surgery.
基金supported by the National Natural Science Foundation of China(No.62376197)the Tianjin Science and Technology Program(No.23JCYBJC00360)the Tianjin Health Research Project(No.TJWJ2025MS045).
文摘Accessible communication based on sign language recognition(SLR)is the key to emergency medical assistance for the hearing-impaired community.Balancing the capture of both local and global information in SLR for emergency medicine poses a significant challenge.To address this,we propose a novel approach based on the inter-learning of visual features between global and local information.Specifically,our method enhances the perception capabilities of the visual feature extractor by strategically leveraging the strengths of convolutional neural network(CNN),which are adept at capturing local features,and visual transformers which perform well at perceiving global features.Furthermore,to mitigate the issue of overfitting caused by the limited availability of sign language data for emergency medical applications,we introduce an enhanced short temporal module for data augmentation through additional subsequences.Experimental results on three publicly available sign language datasets demonstrate the efficacy of the proposed approach.
基金Fundamental Research Funds for the Central Universities,China(No.2232021A-10)Shanghai Pujiang Program,China(No.22PJ1423400)。
文摘Visual entailment(VE)is a prototypical task in multimodal visual reasoning,where current methods frequently utilize large language models(LLMs)as the knowledge base to assist in answering questions.These methods heavily rely on the textual modality,which inherently cannot capture the full extent of information contained within images.We propose a context-aware visual entailment(CAVE)model,which introduces a novel aggregation module designed to extract high-level semantic features from images.This module integrates lower-level semantic image features into high-level visual tokens,formatting them similarly to text tokens so that they can serve as inputs for LLMs.The CAVE model compensates for the loss of image information and integrates it more effectively with textual comprehension.Additionally,the CAVE model incorporates a new input format and training methodology,which is rooted in instruction tuning and in-context learning techniques.The objective of this research is to maximize the inherent logical reasoning capabilities of LLMs.Experimental results on the E-SNLIVE dataset show that the proposed CAVE model exhibits outstanding performance.
文摘The methods of visual recognition,positioning and orienting with simple 3 D geometric workpieces are presented in this paper.The principle and operating process of multiple orientation run length coding based on general orientation run length coding and visual recognition method are described elaborately.The method of positioning and orientating based on the moment of inertia of the workpiece binary image is stated also.It has been applied in a research on flexible automatic coordinate measuring system formed by integrating computer aided design,computer vision and computer aided inspection planning,with a coordinate measuring machine.The results show that integrating computer vision with measurement system is a feasible and effective approach to improve their flexibility and automation.
