Visuality can be generically described as the quality of the visual,that is,as the given visual field in which a subject’s attention is concentrated.In fact,the visual is intrinsically linked to human vision,and this...Visuality can be generically described as the quality of the visual,that is,as the given visual field in which a subject’s attention is concentrated.In fact,the visual is intrinsically linked to human vision,and this presupposes the existence of a visible horizon from which(visual)images are given.However,this formulation presents something uncanny paradoxical because it forgets,on one hand,the broader status of the image(such as auditory and olfactory images)-seeing is not just a visual process(at least since Diderot we know it)and there are mental mechanisms in the visual constitution process that help to fabricate reality and that gestalt theory has explained-and on the other hand,the possibility of seeing beyond what is visible,after all,everything(or almost everything)that presents itself in a digital and virtual environment it can be quite ontologically suspect.Based on some of these premises,we will trace a path of analysis that leads us to the current blindness:unconditional faith in digital technology and the fragile hope of happiness in a way that rejects the reality of the visible.展开更多
The hierarchical and coordinated processing of visual information by the brain demonstrates its superior ability to min-imize energy consumption and maximize signal transmission efficiency.Therefore,it is crucial to d...The hierarchical and coordinated processing of visual information by the brain demonstrates its superior ability to min-imize energy consumption and maximize signal transmission efficiency.Therefore,it is crucial to develop artificial visual synapses that integrate optical sensing and synaptic functions.This study fully leverages the excellent photoresponsivity proper-ties of the PM6:Y6 system to construct a vertical photo-tunable organic memristor and conducts in-depth research on its resis-tive switching performance,photodetection capability,and simulation of photo-synaptic behavior,showcasing its excellent per-formance in processing visual information and simulating neuromorphic behaviors.The device achieves stable and gradual resis-tance change,successfully simulating voltage-controlled long-term potentiation/depression(LTP/LTD),and exhibits various photo-electric synergistic regulation of synaptic plasticity.Moreover,the device has successfully simulated the image percep-tion and recognition functions of the human visual nervous system.The non-volatile Au/PM6:Y6/ITO memristor is used as an artificial synapse and neuron modeling,building a hierarchical coordinated processing SLP-CNN cascade neural network for visual image recognition training,its linear tunable photoconductivity characteristic serves as the weight update of the net-work,achieving a recognition accuracy of up to 93.4%.Compared with the single-layer visual target recognition model,this scheme has improved the recognition accuracy by 19.2%.展开更多
The prevalence of glaucoma, the second leading cause of global blindness, is increasing due to aging populations. In glaucoma, degeneration of the optic nerve and retinal ganglion cells(RGCs) causes visual field defec...The prevalence of glaucoma, the second leading cause of global blindness, is increasing due to aging populations. In glaucoma, degeneration of the optic nerve and retinal ganglion cells(RGCs) causes visual field defects and eventual blindness.展开更多
The year 2024 marks the 60^(th)anniversary of Title IX and 25 years since the New York Times revealed bias against female faculty members at the Massachusetts Institute of Technology.We take an opportunity here to exa...The year 2024 marks the 60^(th)anniversary of Title IX and 25 years since the New York Times revealed bias against female faculty members at the Massachusetts Institute of Technology.We take an opportunity here to examine the state of gender bias in a relatively new yet already prominent field,neural regeneration in the visual system,for which there is a well-defined context useful for this purpose.The National Eye Institute(NEI)provided the first round of research funding for its Audacious Goals Initiative(AGI)on visual neural regeneration in 2013 and the last round in 2021.Therefore,we focus on this timespan.Data sources included PubMed,the National Science Foundation(NSF),the NEI,the Blue Ridge Institute for Medical Research and data from the major professional organization for eye and vision research,the Association for Research in Vision and Ophthalmology(ARVO).展开更多
This study presents an innovative approach to enhancing the security of visual medical data in the generative AI environment through the integration of blockchain technology.By combining the strengths of blockchain an...This study presents an innovative approach to enhancing the security of visual medical data in the generative AI environment through the integration of blockchain technology.By combining the strengths of blockchain and generative AI,the research team aimed to address the timely challenge of safeguarding visual medical content.The participating researchers conducted a comprehensive analysis,examining the vulnerabilities of medical AI services,personal information protection issues,and overall security weaknesses.This multi faceted exploration led to an indepth evaluation of the model’s performance and security.Notably,the correlation between accuracy,detection rate,and error rate was scrutinized.This analysis revealed insights into the model’s strengths and limitations,while the consideration of standard deviation shed light on the model’s stability and performance variability.The study proposed practical improvements,emphasizing the reduction of false negatives to enhance detection rate and leveraging blockchain technology to ensure visual data integrity in medical applications.Applying blockchain to generative AI-created medical content addresses key personal information protection issues.By utilizing the distributed ledger system of blockchain,the research team aimed to protect the privacy and integrity of medical data especially medical images.This approach not only enhances security but also enables transparent and tamperproof record-keeping.Additionally,the use of generative AI models ensures the creation of novel medical content without compromising personal information,further safeguarding patient privacy.In conclusion,this study showcases the potential of blockchain-based solutions in the medical field,particularly in securing sensitive medical data and protecting patient privacy.The proposed approach,combining blockchain and generative AI,offers a promising direction toward more robust and secure medical content management.Further research and advancements in this area will undoubtedly contribute to the development of robust and privacy-preserving healthcare systems,and visual diagnostic systems.展开更多
In dynamic scenarios,visual simultaneous localization and mapping(SLAM)algorithms often incorrectly incorporate dynamic points during camera pose computation,leading to reduced accuracy and robustness.This paper prese...In dynamic scenarios,visual simultaneous localization and mapping(SLAM)algorithms often incorrectly incorporate dynamic points during camera pose computation,leading to reduced accuracy and robustness.This paper presents a dynamic SLAM algorithm that leverages object detection and regional dynamic probability.Firstly,a parallel thread employs the YOLOX object detectionmodel to gather 2D semantic information and compensate for missed detections.Next,an improved K-means++clustering algorithm clusters bounding box regions,adaptively determining the threshold for extracting dynamic object contours as dynamic points change.This process divides the image into low dynamic,suspicious dynamic,and high dynamic regions.In the tracking thread,the dynamic point removal module assigns dynamic probability weights to the feature points in these regions.Combined with geometric methods,it detects and removes the dynamic points.The final evaluation on the public TUM RGB-D dataset shows that the proposed dynamic SLAM algorithm surpasses most existing SLAM algorithms,providing better pose estimation accuracy and robustness in dynamic environments.展开更多
With the development of anti-virus technology,malicious documents have gradually become the main pathway of Advanced Persistent Threat(APT)attacks,therefore,the development of effective malicious document classifiers ...With the development of anti-virus technology,malicious documents have gradually become the main pathway of Advanced Persistent Threat(APT)attacks,therefore,the development of effective malicious document classifiers has become particularly urgent.Currently,detection methods based on document structure and behavioral features encounter challenges in feature engineering,these methods not only have limited accuracy,but also consume large resources,and usually can only detect documents in specific formats,which lacks versatility and adaptability.To address such problems,this paper proposes a novel malicious document detection method-visualizing documents as GGE images(Grayscale,Grayscale matrix,Entropy).The GGE method visualizes the original byte sequence of the malicious document as a grayscale image,the information entropy sequence of the document as an entropy image,and at the same time,the grayscale level co-occurrence matrix and the texture and spatial information stored in it are converted into grayscale matrix image,and fuses the three types of images to get the GGE color image.The Convolutional Block Attention Module-EfficientNet-B0(CBAM-EfficientNet-B0)model is then used for classification,combining transfer learning and applying the pre-trained model on the ImageNet dataset to the feature extraction process of GGE images.As shown in the experimental results,the GGE method has superior performance compared with other methods,which is suitable for detecting malicious documents in different formats,and achieves an accuracy of 99.44%and 97.39%on Portable Document Format(PDF)and office datasets,respectively,and consumes less time during the detection process,which can be effectively applied to the task of detecting malicious documents in real-time.展开更多
Understanding the neural underpinning of human gait and balance is one of the most pertinent challenges for 21st-century translational neuroscience due to the profound impact that falls and mobility disturbances have ...Understanding the neural underpinning of human gait and balance is one of the most pertinent challenges for 21st-century translational neuroscience due to the profound impact that falls and mobility disturbances have on our aging population.Posture and gait control does not happen automatically,as previously believed,but rather requires continuous involvement of central nervous mechanisms.To effectively exert control over the body,the brain must integrate multiple streams of sensory information,including visual,vestibular,and somatosensory signals.The mechanisms which underpin the integration of these multisensory signals are the principal topic of the present work.Existing multisensory integration theories focus on how failure of cognitive processes thought to be involved in multisensory integration leads to falls in older adults.Insufficient emphasis,however,has been placed on specific contributions of individual sensory modalities to multisensory integration processes and cross-modal interactions that occur between the sensory modalities in relation to gait and balance.In the present work,we review the contributions of somatosensory,visual,and vestibular modalities,along with their multisensory intersections to gait and balance in older adults and patients with Parkinson’s disease.We also review evidence of vestibular contributions to multisensory temporal binding windows,previously shown to be highly pertinent to fall risk in older adults.Lastly,we relate multisensory vestibular mechanisms to potential neural substrates,both at the level of neurobiology(concerning positron emission tomography imaging)and at the level of electrophysiology(concerning electroencephalography).We hope that this integrative review,drawing influence across multiple subdisciplines of neuroscience,paves the way for novel research directions and therapeutic neuromodulatory approaches,to improve the lives of older adults and patients with neurodegenerative diseases.展开更多
BACKGROUND Epidemiological surveys indicate an increasing incidence of type 2 diabetes mellitus(T2DM)among children and adolescents worldwide.Due to rapid disease progression,severe long-term cardiorenal complications...BACKGROUND Epidemiological surveys indicate an increasing incidence of type 2 diabetes mellitus(T2DM)among children and adolescents worldwide.Due to rapid disease progression,severe long-term cardiorenal complications,a lack of effective treatment strategies,and substantial socioeconomic burdens,it has become an urgent public health issue that requires management and resolution.Adolescent T2DM differs from adult T2DM.Despite a significant increase in our understanding of youth-onset T2DM over the past two decades,the related review and evidence-based content remain limited.AIM To visualize the hotspots and trends in pediatric and adolescent T2DM research and to forecast their future research themes.METHODS This study utilized the terms“children”,“adolescents”,and“type 2 diabetes”,retrieving relevant articles published between 1983 and 2023 from three citation databases within the Web of Science Core Collection(SCI,SSCI,ESCI).Utilizing CiteSpace and VoSviewer software,we analyze and visually represent the annual output of literature,countries involved,and participating institutions.This allows us to predict trends in this research field.Our analysis encompasses co-cited authors,journal overlays,citation overlays,time-zone views,keyword analysis,and reference analysis,etc.RESULTS A total of 9210 articles were included,and the annual publication volume in this field showed a steady growth trend.The United States had the highest number of publications and the highest H-index.The United States also had the most research institutions and the strongest research capacity.The global hot journals were primarily diabetes professional journals but also included journals related to nutrition,endocrinology,and metabolism.Keyword analysis showed that research related to endothelial dysfunction,exposure risk,cardiac metabolic risk,changes in gut microbiota,the impact on comorbidities and outcomes,etc.,were emerging keywords.They have maintained their popularity in this field,suggesting that these areas have garnered significant research interest in recent years.CONCLUSION Pediatric and adolescent T2DM is increasingly drawing global attention,with genes,behaviors,environmental factors,and multisystemic interventions potentially emerging as future research hot spots.展开更多
A two-stage algorithm based on deep learning for the detection and recognition of can bottom spray codes and numbers is proposed to address the problems of small character areas and fast production line speeds in can ...A two-stage algorithm based on deep learning for the detection and recognition of can bottom spray codes and numbers is proposed to address the problems of small character areas and fast production line speeds in can bottom spray code number recognition.In the coding number detection stage,Differentiable Binarization Network is used as the backbone network,combined with the Attention and Dilation Convolutions Path Aggregation Network feature fusion structure to enhance the model detection effect.In terms of text recognition,using the Scene Visual Text Recognition coding number recognition network for end-to-end training can alleviate the problem of coding recognition errors caused by image color distortion due to variations in lighting and background noise.In addition,model pruning and quantization are used to reduce the number ofmodel parameters to meet deployment requirements in resource-constrained environments.A comparative experiment was conducted using the dataset of tank bottom spray code numbers collected on-site,and a transfer experiment was conducted using the dataset of packaging box production date.The experimental results show that the algorithm proposed in this study can effectively locate the coding of cans at different positions on the roller conveyor,and can accurately identify the coding numbers at high production line speeds.The Hmean value of the coding number detection is 97.32%,and the accuracy of the coding number recognition is 98.21%.This verifies that the algorithm proposed in this paper has high accuracy in coding number detection and recognition.展开更多
BACKGROUND Bipolar disorder(BD)is a severe mental illness characterized by significant mood swings.Effective drug treatment modalities are crucial for managing BD.AIM To analyze the current status and future trends of...BACKGROUND Bipolar disorder(BD)is a severe mental illness characterized by significant mood swings.Effective drug treatment modalities are crucial for managing BD.AIM To analyze the current status and future trends of global research on BD drug treatment over the last decade.METHODS The Web of Science Core Collection database spanning from 2015 to 2024 was utilized to retrieve literature related to BD drug treatment.A total of 2624 articles were extracted.Data visualization and analysis were conducted using CiteSpace,VOSviewer,Pajek,Scimago Graphica,and R-studio bibliometrix to identify RESULTS The United States,China,and the United Kingdom have made the most significant contributions to research on BD drug treatment and formed notable research collaboration networks.The University of Pittsburgh,Massachusetts General Hospital,and the University of Michigan have been identified as the major research institutions in this field.The Journal of Affective Disorders is the most influential journal.A keyword analysis revealed research hotspots related to clinical symptoms,drug efficacy,and genetic mechanisms.A citation analysis identified the management guidelines published by Yatham et al in 2018 as the most cited paper.CONCLUSION This study provides a detailed overview of the field of BD drug treatment,highlighting key contributors,research hotspots,and future directions.The study findings can be employed as a reference for future research and policymaking,which may enable further development and optimization of BD pharmacotherapy.展开更多
This letter provides a concise review of the pertinent literature on visual and tactile hallucinations in elderly patients.The discussion addresses differential diagnoses and potential underlying mechanisms,as well as...This letter provides a concise review of the pertinent literature on visual and tactile hallucinations in elderly patients.The discussion addresses differential diagnoses and potential underlying mechanisms,as well as the psychopathology associated with tactile hallucinations,and emphasizes the necessity for invest-igation into the possibility of coexisting delusional infestation(parasitosis).These symptoms frequently manifest in patients with primary psychotic disorders,organic mental disorders,and substance use disorders.The proposed pathophy-siological mechanisms may involve dopaminergic imbalances and dysfunction of the striatal dopamine transporter.展开更多
This study investigates the application of Learnable Memory Vision Transformers(LMViT)for detecting metal surface flaws,comparing their performance with traditional CNNs,specifically ResNet18 and ResNet50,as well as o...This study investigates the application of Learnable Memory Vision Transformers(LMViT)for detecting metal surface flaws,comparing their performance with traditional CNNs,specifically ResNet18 and ResNet50,as well as other transformer-based models including Token to Token ViT,ViT withoutmemory,and Parallel ViT.Leveraging awidely-used steel surface defect dataset,the research applies data augmentation and t-distributed stochastic neighbor embedding(t-SNE)to enhance feature extraction and understanding.These techniques mitigated overfitting,stabilized training,and improved generalization capabilities.The LMViT model achieved a test accuracy of 97.22%,significantly outperforming ResNet18(88.89%)and ResNet50(88.90%),aswell as the Token to TokenViT(88.46%),ViT without memory(87.18),and Parallel ViT(91.03%).Furthermore,LMViT exhibited superior training and validation performance,attaining a validation accuracy of 98.2%compared to 91.0%for ResNet 18,96.0%for ResNet50,and 89.12%,87.51%,and 91.21%for Token to Token ViT,ViT without memory,and Parallel ViT,respectively.The findings highlight the LMViT’s ability to capture long-range dependencies in images,an areawhere CNNs struggle due to their reliance on local receptive fields and hierarchical feature extraction.The additional transformer-based models also demonstrate improved performance in capturing complex features over CNNs,with LMViT excelling particularly at detecting subtle and complex defects,which is critical for maintaining product quality and operational efficiency in industrial applications.For instance,the LMViT model successfully identified fine scratches and minor surface irregularities that CNNs often misclassify.This study not only demonstrates LMViT’s potential for real-world defect detection but also underscores the promise of other transformer-based architectures like Token to Token ViT,ViT without memory,and Parallel ViT in industrial scenarios where complex spatial relationships are key.Future research may focus on enhancing LMViT’s computational efficiency for deployment in real-time quality control systems.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
Graphical abstracts(GAs)are emerging as a pivotal tool in medical literature,enhancing the dissemination and comprehension of complex clinical data through visual summaries.This editorial highlights the significant ad...Graphical abstracts(GAs)are emerging as a pivotal tool in medical literature,enhancing the dissemination and comprehension of complex clinical data through visual summaries.This editorial highlights the significant advantages of GAs,including improved clarity,increased reader engagement,and enhanced visibility of research findings.By transforming intricate scientific data into accessible visual formats,these abstracts facilitate quick and effective knowledge transfer,crucial in clinical decision-making and patient care.However,challenges such as potential data misrepresentation due to oversimplification,the skill gap in graphic design among researchers,and the lack of standardized creation guidelines pose barriers to their widespread adoption.Additionally,while software such as Adobe Illustrator,BioRender,and Canva are commonly employed to create these visuals,not all researchers may be proficient in their use.To address these issues,we recommend that academic journals establish clear guidelines and provide necessary design training to researchers.This proactive approach will ensure the creation of high-quality GAs,promote their standardization,and expand their use in clinical reporting,ultimately benefiting the medical community and improving healthcare outcomes.展开更多
AIM:To evaluate the efficacy and safety of intravitreal low-dose(1 mg)triamcinolone acetonide(TA)in Chinese acute nonarteritic anterior ischemic optic neuropathy(NAION)patients.METHODS:Twenty-eight eyes of 28 patients...AIM:To evaluate the efficacy and safety of intravitreal low-dose(1 mg)triamcinolone acetonide(TA)in Chinese acute nonarteritic anterior ischemic optic neuropathy(NAION)patients.METHODS:Twenty-eight eyes of 28 patients with acute NAION(<30d of visual acuity loss)were enrolled and given intravitreal TA(IVTA)once.Visual field(VF),best corrected visual acuity(BCVA),retinal nerve fiber layer(RNFL)thickness,ganglion cell complex(GCC)thickness,radial peripapillary capillary(RPC)density,and intraocular pressure(IOP)were evaluated at baseline and 7d,1,3,and 6mo after IVTA.RESULTS:VF and BCVA were significant improved during the follow-up according to the mean deviation(MD),visual field index(VFI),and Early Treatment Diabetic Retinopathy Study(ETDRS)scores(all P<0.001).There was no significant difference between the group that received an injection less than 14d after illness onset and the group that received an injection more than 14d after illness onset.The RNFL thickness,GCC thickness and RPC density were significantly decreased(all P<0.001).Temporary ocular hypertension was present in five eyes.CONCLUSION:Low-dose IVTA may be an alternative safe treatment option for some NAION patients in the acute stage.However,optic nerve atrophy still existed.展开更多
文摘Visuality can be generically described as the quality of the visual,that is,as the given visual field in which a subject’s attention is concentrated.In fact,the visual is intrinsically linked to human vision,and this presupposes the existence of a visible horizon from which(visual)images are given.However,this formulation presents something uncanny paradoxical because it forgets,on one hand,the broader status of the image(such as auditory and olfactory images)-seeing is not just a visual process(at least since Diderot we know it)and there are mental mechanisms in the visual constitution process that help to fabricate reality and that gestalt theory has explained-and on the other hand,the possibility of seeing beyond what is visible,after all,everything(or almost everything)that presents itself in a digital and virtual environment it can be quite ontologically suspect.Based on some of these premises,we will trace a path of analysis that leads us to the current blindness:unconditional faith in digital technology and the fragile hope of happiness in a way that rejects the reality of the visible.
基金the National Natural Science Foundation of China(62111540271)Natural Science Foundation of Anhui Province(2308085MF207).
文摘The hierarchical and coordinated processing of visual information by the brain demonstrates its superior ability to min-imize energy consumption and maximize signal transmission efficiency.Therefore,it is crucial to develop artificial visual synapses that integrate optical sensing and synaptic functions.This study fully leverages the excellent photoresponsivity proper-ties of the PM6:Y6 system to construct a vertical photo-tunable organic memristor and conducts in-depth research on its resis-tive switching performance,photodetection capability,and simulation of photo-synaptic behavior,showcasing its excellent per-formance in processing visual information and simulating neuromorphic behaviors.The device achieves stable and gradual resis-tance change,successfully simulating voltage-controlled long-term potentiation/depression(LTP/LTD),and exhibits various photo-electric synergistic regulation of synaptic plasticity.Moreover,the device has successfully simulated the image percep-tion and recognition functions of the human visual nervous system.The non-volatile Au/PM6:Y6/ITO memristor is used as an artificial synapse and neuron modeling,building a hierarchical coordinated processing SLP-CNN cascade neural network for visual image recognition training,its linear tunable photoconductivity characteristic serves as the weight update of the net-work,achieving a recognition accuracy of up to 93.4%.Compared with the single-layer visual target recognition model,this scheme has improved the recognition accuracy by 19.2%.
基金supported by Japan Society for the Promotion of Science (JSPS) KAKENHI Grants-in-Aid for Scientific Research (JP22K09804 to CHJP21K09688 to XG+3 种基金JP19KK0229, JP21H04786, JP21H02819 and JP21K18279 to TH)the Shiseido Female Researcher Science Grant (to XG)Mitsubishi FoundationTakeda Science Foundation (to TH)。
文摘The prevalence of glaucoma, the second leading cause of global blindness, is increasing due to aging populations. In glaucoma, degeneration of the optic nerve and retinal ganglion cells(RGCs) causes visual field defects and eventual blindness.
文摘The year 2024 marks the 60^(th)anniversary of Title IX and 25 years since the New York Times revealed bias against female faculty members at the Massachusetts Institute of Technology.We take an opportunity here to examine the state of gender bias in a relatively new yet already prominent field,neural regeneration in the visual system,for which there is a well-defined context useful for this purpose.The National Eye Institute(NEI)provided the first round of research funding for its Audacious Goals Initiative(AGI)on visual neural regeneration in 2013 and the last round in 2021.Therefore,we focus on this timespan.Data sources included PubMed,the National Science Foundation(NSF),the NEI,the Blue Ridge Institute for Medical Research and data from the major professional organization for eye and vision research,the Association for Research in Vision and Ophthalmology(ARVO).
文摘This study presents an innovative approach to enhancing the security of visual medical data in the generative AI environment through the integration of blockchain technology.By combining the strengths of blockchain and generative AI,the research team aimed to address the timely challenge of safeguarding visual medical content.The participating researchers conducted a comprehensive analysis,examining the vulnerabilities of medical AI services,personal information protection issues,and overall security weaknesses.This multi faceted exploration led to an indepth evaluation of the model’s performance and security.Notably,the correlation between accuracy,detection rate,and error rate was scrutinized.This analysis revealed insights into the model’s strengths and limitations,while the consideration of standard deviation shed light on the model’s stability and performance variability.The study proposed practical improvements,emphasizing the reduction of false negatives to enhance detection rate and leveraging blockchain technology to ensure visual data integrity in medical applications.Applying blockchain to generative AI-created medical content addresses key personal information protection issues.By utilizing the distributed ledger system of blockchain,the research team aimed to protect the privacy and integrity of medical data especially medical images.This approach not only enhances security but also enables transparent and tamperproof record-keeping.Additionally,the use of generative AI models ensures the creation of novel medical content without compromising personal information,further safeguarding patient privacy.In conclusion,this study showcases the potential of blockchain-based solutions in the medical field,particularly in securing sensitive medical data and protecting patient privacy.The proposed approach,combining blockchain and generative AI,offers a promising direction toward more robust and secure medical content management.Further research and advancements in this area will undoubtedly contribute to the development of robust and privacy-preserving healthcare systems,and visual diagnostic systems.
基金the National Natural Science Foundation of China(No.62063006)to the Guangxi Natural Science Foundation under Grant(Nos.2023GXNSFAA026025,AA24010001)+3 种基金to the Innovation Fund of Chinese Universities Industry-University-Research(ID:2023RY018)to the Special Guangxi Industry and Information Technology Department,Textile and Pharmaceutical Division(ID:2021 No.231)to the Special Research Project of Hechi University(ID:2021GCC028)to the Key Laboratory of AI and Information Processing,Education Department of Guangxi Zhuang Autonomous Region(Hechi University),No.2024GXZDSY009。
文摘In dynamic scenarios,visual simultaneous localization and mapping(SLAM)algorithms often incorrectly incorporate dynamic points during camera pose computation,leading to reduced accuracy and robustness.This paper presents a dynamic SLAM algorithm that leverages object detection and regional dynamic probability.Firstly,a parallel thread employs the YOLOX object detectionmodel to gather 2D semantic information and compensate for missed detections.Next,an improved K-means++clustering algorithm clusters bounding box regions,adaptively determining the threshold for extracting dynamic object contours as dynamic points change.This process divides the image into low dynamic,suspicious dynamic,and high dynamic regions.In the tracking thread,the dynamic point removal module assigns dynamic probability weights to the feature points in these regions.Combined with geometric methods,it detects and removes the dynamic points.The final evaluation on the public TUM RGB-D dataset shows that the proposed dynamic SLAM algorithm surpasses most existing SLAM algorithms,providing better pose estimation accuracy and robustness in dynamic environments.
基金supported by the Natural Science Foundation of Henan Province(Grant No.242300420297)awarded to Yi Sun.
文摘With the development of anti-virus technology,malicious documents have gradually become the main pathway of Advanced Persistent Threat(APT)attacks,therefore,the development of effective malicious document classifiers has become particularly urgent.Currently,detection methods based on document structure and behavioral features encounter challenges in feature engineering,these methods not only have limited accuracy,but also consume large resources,and usually can only detect documents in specific formats,which lacks versatility and adaptability.To address such problems,this paper proposes a novel malicious document detection method-visualizing documents as GGE images(Grayscale,Grayscale matrix,Entropy).The GGE method visualizes the original byte sequence of the malicious document as a grayscale image,the information entropy sequence of the document as an entropy image,and at the same time,the grayscale level co-occurrence matrix and the texture and spatial information stored in it are converted into grayscale matrix image,and fuses the three types of images to get the GGE color image.The Convolutional Block Attention Module-EfficientNet-B0(CBAM-EfficientNet-B0)model is then used for classification,combining transfer learning and applying the pre-trained model on the ImageNet dataset to the feature extraction process of GGE images.As shown in the experimental results,the GGE method has superior performance compared with other methods,which is suitable for detecting malicious documents in different formats,and achieves an accuracy of 99.44%and 97.39%on Portable Document Format(PDF)and office datasets,respectively,and consumes less time during the detection process,which can be effectively applied to the task of detecting malicious documents in real-time.
文摘Understanding the neural underpinning of human gait and balance is one of the most pertinent challenges for 21st-century translational neuroscience due to the profound impact that falls and mobility disturbances have on our aging population.Posture and gait control does not happen automatically,as previously believed,but rather requires continuous involvement of central nervous mechanisms.To effectively exert control over the body,the brain must integrate multiple streams of sensory information,including visual,vestibular,and somatosensory signals.The mechanisms which underpin the integration of these multisensory signals are the principal topic of the present work.Existing multisensory integration theories focus on how failure of cognitive processes thought to be involved in multisensory integration leads to falls in older adults.Insufficient emphasis,however,has been placed on specific contributions of individual sensory modalities to multisensory integration processes and cross-modal interactions that occur between the sensory modalities in relation to gait and balance.In the present work,we review the contributions of somatosensory,visual,and vestibular modalities,along with their multisensory intersections to gait and balance in older adults and patients with Parkinson’s disease.We also review evidence of vestibular contributions to multisensory temporal binding windows,previously shown to be highly pertinent to fall risk in older adults.Lastly,we relate multisensory vestibular mechanisms to potential neural substrates,both at the level of neurobiology(concerning positron emission tomography imaging)and at the level of electrophysiology(concerning electroencephalography).We hope that this integrative review,drawing influence across multiple subdisciplines of neuroscience,paves the way for novel research directions and therapeutic neuromodulatory approaches,to improve the lives of older adults and patients with neurodegenerative diseases.
基金Supported by the National Natural Science Foundation of China,No.82105018 and No.81903950.
文摘BACKGROUND Epidemiological surveys indicate an increasing incidence of type 2 diabetes mellitus(T2DM)among children and adolescents worldwide.Due to rapid disease progression,severe long-term cardiorenal complications,a lack of effective treatment strategies,and substantial socioeconomic burdens,it has become an urgent public health issue that requires management and resolution.Adolescent T2DM differs from adult T2DM.Despite a significant increase in our understanding of youth-onset T2DM over the past two decades,the related review and evidence-based content remain limited.AIM To visualize the hotspots and trends in pediatric and adolescent T2DM research and to forecast their future research themes.METHODS This study utilized the terms“children”,“adolescents”,and“type 2 diabetes”,retrieving relevant articles published between 1983 and 2023 from three citation databases within the Web of Science Core Collection(SCI,SSCI,ESCI).Utilizing CiteSpace and VoSviewer software,we analyze and visually represent the annual output of literature,countries involved,and participating institutions.This allows us to predict trends in this research field.Our analysis encompasses co-cited authors,journal overlays,citation overlays,time-zone views,keyword analysis,and reference analysis,etc.RESULTS A total of 9210 articles were included,and the annual publication volume in this field showed a steady growth trend.The United States had the highest number of publications and the highest H-index.The United States also had the most research institutions and the strongest research capacity.The global hot journals were primarily diabetes professional journals but also included journals related to nutrition,endocrinology,and metabolism.Keyword analysis showed that research related to endothelial dysfunction,exposure risk,cardiac metabolic risk,changes in gut microbiota,the impact on comorbidities and outcomes,etc.,were emerging keywords.They have maintained their popularity in this field,suggesting that these areas have garnered significant research interest in recent years.CONCLUSION Pediatric and adolescent T2DM is increasingly drawing global attention,with genes,behaviors,environmental factors,and multisystemic interventions potentially emerging as future research hot spots.
文摘A two-stage algorithm based on deep learning for the detection and recognition of can bottom spray codes and numbers is proposed to address the problems of small character areas and fast production line speeds in can bottom spray code number recognition.In the coding number detection stage,Differentiable Binarization Network is used as the backbone network,combined with the Attention and Dilation Convolutions Path Aggregation Network feature fusion structure to enhance the model detection effect.In terms of text recognition,using the Scene Visual Text Recognition coding number recognition network for end-to-end training can alleviate the problem of coding recognition errors caused by image color distortion due to variations in lighting and background noise.In addition,model pruning and quantization are used to reduce the number ofmodel parameters to meet deployment requirements in resource-constrained environments.A comparative experiment was conducted using the dataset of tank bottom spray code numbers collected on-site,and a transfer experiment was conducted using the dataset of packaging box production date.The experimental results show that the algorithm proposed in this study can effectively locate the coding of cans at different positions on the roller conveyor,and can accurately identify the coding numbers at high production line speeds.The Hmean value of the coding number detection is 97.32%,and the accuracy of the coding number recognition is 98.21%.This verifies that the algorithm proposed in this paper has high accuracy in coding number detection and recognition.
基金Supported by the National College Students’Innovative Entrepreneurial Training Plan Program,No.202410403067the Innovation and Entrepreneurship Training Program for College Students in Jiangxi Province,No.S202410403035.
文摘BACKGROUND Bipolar disorder(BD)is a severe mental illness characterized by significant mood swings.Effective drug treatment modalities are crucial for managing BD.AIM To analyze the current status and future trends of global research on BD drug treatment over the last decade.METHODS The Web of Science Core Collection database spanning from 2015 to 2024 was utilized to retrieve literature related to BD drug treatment.A total of 2624 articles were extracted.Data visualization and analysis were conducted using CiteSpace,VOSviewer,Pajek,Scimago Graphica,and R-studio bibliometrix to identify RESULTS The United States,China,and the United Kingdom have made the most significant contributions to research on BD drug treatment and formed notable research collaboration networks.The University of Pittsburgh,Massachusetts General Hospital,and the University of Michigan have been identified as the major research institutions in this field.The Journal of Affective Disorders is the most influential journal.A keyword analysis revealed research hotspots related to clinical symptoms,drug efficacy,and genetic mechanisms.A citation analysis identified the management guidelines published by Yatham et al in 2018 as the most cited paper.CONCLUSION This study provides a detailed overview of the field of BD drug treatment,highlighting key contributors,research hotspots,and future directions.The study findings can be employed as a reference for future research and policymaking,which may enable further development and optimization of BD pharmacotherapy.
文摘This letter provides a concise review of the pertinent literature on visual and tactile hallucinations in elderly patients.The discussion addresses differential diagnoses and potential underlying mechanisms,as well as the psychopathology associated with tactile hallucinations,and emphasizes the necessity for invest-igation into the possibility of coexisting delusional infestation(parasitosis).These symptoms frequently manifest in patients with primary psychotic disorders,organic mental disorders,and substance use disorders.The proposed pathophy-siological mechanisms may involve dopaminergic imbalances and dysfunction of the striatal dopamine transporter.
基金funded by Woosong University Academic Research 2024.
文摘This study investigates the application of Learnable Memory Vision Transformers(LMViT)for detecting metal surface flaws,comparing their performance with traditional CNNs,specifically ResNet18 and ResNet50,as well as other transformer-based models including Token to Token ViT,ViT withoutmemory,and Parallel ViT.Leveraging awidely-used steel surface defect dataset,the research applies data augmentation and t-distributed stochastic neighbor embedding(t-SNE)to enhance feature extraction and understanding.These techniques mitigated overfitting,stabilized training,and improved generalization capabilities.The LMViT model achieved a test accuracy of 97.22%,significantly outperforming ResNet18(88.89%)and ResNet50(88.90%),aswell as the Token to TokenViT(88.46%),ViT without memory(87.18),and Parallel ViT(91.03%).Furthermore,LMViT exhibited superior training and validation performance,attaining a validation accuracy of 98.2%compared to 91.0%for ResNet 18,96.0%for ResNet50,and 89.12%,87.51%,and 91.21%for Token to Token ViT,ViT without memory,and Parallel ViT,respectively.The findings highlight the LMViT’s ability to capture long-range dependencies in images,an areawhere CNNs struggle due to their reliance on local receptive fields and hierarchical feature extraction.The additional transformer-based models also demonstrate improved performance in capturing complex features over CNNs,with LMViT excelling particularly at detecting subtle and complex defects,which is critical for maintaining product quality and operational efficiency in industrial applications.For instance,the LMViT model successfully identified fine scratches and minor surface irregularities that CNNs often misclassify.This study not only demonstrates LMViT’s potential for real-world defect detection but also underscores the promise of other transformer-based architectures like Token to Token ViT,ViT without memory,and Parallel ViT in industrial scenarios where complex spatial relationships are key.Future research may focus on enhancing LMViT’s computational efficiency for deployment in real-time quality control systems.
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.
文摘Graphical abstracts(GAs)are emerging as a pivotal tool in medical literature,enhancing the dissemination and comprehension of complex clinical data through visual summaries.This editorial highlights the significant advantages of GAs,including improved clarity,increased reader engagement,and enhanced visibility of research findings.By transforming intricate scientific data into accessible visual formats,these abstracts facilitate quick and effective knowledge transfer,crucial in clinical decision-making and patient care.However,challenges such as potential data misrepresentation due to oversimplification,the skill gap in graphic design among researchers,and the lack of standardized creation guidelines pose barriers to their widespread adoption.Additionally,while software such as Adobe Illustrator,BioRender,and Canva are commonly employed to create these visuals,not all researchers may be proficient in their use.To address these issues,we recommend that academic journals establish clear guidelines and provide necessary design training to researchers.This proactive approach will ensure the creation of high-quality GAs,promote their standardization,and expand their use in clinical reporting,ultimately benefiting the medical community and improving healthcare outcomes.
基金Supported by the National Key R&D Program of China(No.2016YFC0904800,No.2019YFC0840607)the National Science and Technology Major Project of China(No.2017ZX09304010)the Clinical Research Innovation Plan of Shanghai General Hospital(No.CTCCR-2018BP04).
文摘AIM:To evaluate the efficacy and safety of intravitreal low-dose(1 mg)triamcinolone acetonide(TA)in Chinese acute nonarteritic anterior ischemic optic neuropathy(NAION)patients.METHODS:Twenty-eight eyes of 28 patients with acute NAION(<30d of visual acuity loss)were enrolled and given intravitreal TA(IVTA)once.Visual field(VF),best corrected visual acuity(BCVA),retinal nerve fiber layer(RNFL)thickness,ganglion cell complex(GCC)thickness,radial peripapillary capillary(RPC)density,and intraocular pressure(IOP)were evaluated at baseline and 7d,1,3,and 6mo after IVTA.RESULTS:VF and BCVA were significant improved during the follow-up according to the mean deviation(MD),visual field index(VFI),and Early Treatment Diabetic Retinopathy Study(ETDRS)scores(all P<0.001).There was no significant difference between the group that received an injection less than 14d after illness onset and the group that received an injection more than 14d after illness onset.The RNFL thickness,GCC thickness and RPC density were significantly decreased(all P<0.001).Temporary ocular hypertension was present in five eyes.CONCLUSION:Low-dose IVTA may be an alternative safe treatment option for some NAION patients in the acute stage.However,optic nerve atrophy still existed.
