Objective:This study aimed to investigate the prevalence,causes,and influencing factors of vision impairment in the elderly population aged 60 years and above in Mangxin Town,Kashgar region,Xinjiang,China.Located in a...Objective:This study aimed to investigate the prevalence,causes,and influencing factors of vision impairment in the elderly population aged 60 years and above in Mangxin Town,Kashgar region,Xinjiang,China.Located in a region characterized by intense ultraviolet radiation and arid climatic conditions,Mangxin Town presents unique environmental challenges that may exacerbate ocular health issues.Despite the global emphasis on addressing vision impairment among aging populations,there remains a paucity of updated and region-specific data in Xinjiang,necessitating this comprehensive assessment to inform targeted interventions.Methods:A cross-sectional study was conducted from May to June 2024,involving 1,311 elderly participants(76.76%participation rate)out of a total eligible population of 1,708 individuals aged≥60 years.Participants underwent detailed ocular examinations,including assessments of uncorrected visual acuity(UVA)and best-corrected visual acuity(BCVA)using standard logarithmic charts,slit-lamp biomicroscopy,optical coherence tomography(OCT,Topcon DRI OCT Triton),fundus photography,and intraocular pressure measurement(Canon TX-20 Tonometer).A multidisciplinary team of 10 ophthalmologists and 2 local village doctors,trained rigorously in standardized protocols,ensured consistent data collection.Demographic,lifestyle,and medical history data were collected via questionnaires.Statistical analyses,performed using STATA 16,included multivariate logistic regression to identify risk factors,with significance defined as P<0.05.Results:The overall prevalence of vision impairment was 13.21%(95%CI:11.37%-15.04%),with low vision at 11.76%(95%CI:10.01%-13.50%)and blindness at 1.45%(95%CI:0.80%-2.10%).Cataract emerged as the leading cause,responsible for 68.20%of cases,followed by glaucoma(5.80%),optic atrophy(5.20%),and age-related macular degeneration(2.90%).Vision impairment prevalence escalated significantly with age:7.74%in the 60–69 age group,17.79%in 70–79,and 33.72%in those≥80.Males exhibited higher prevalence than females(15.84%vs.10.45%,P=0.004).Multivariate analysis revealed age≥80 years(OR=6.43,95%CI:3.79%-10.90%),male sex(OR=0.53,95%CI:0.34%-0.83%),and daily exercise(OR=0.44,95%CI:0.20%-0.95%)as significant factors.History of eye disease showed a non-significant trend toward increased risk(OR=1.49,P=0.107).Education level,income,and smoking status showed no significant associations.Conclusions:This study underscores cataract as the predominant cause of vision impairment in Mangxin Town’s elderly population,with age and sex as critical determinants.The findings align with global patterns but highlight region-specific challenges,such as environmental factors contributing to cataract prevalence.Public health strategies should prioritize improving access to cataract surgery,enhancing grassroots ophthalmic infrastructure,and integrating portable screening technologies for early detection of fundus diseases.Additionally,promoting health education on UV protection and lifestyle modifications,such as regular exercise,may mitigate risks.Future research should expand to broader regions in Xinjiang,employ advanced diagnostic tools for complex conditions like glaucoma,and explore longitudinal trends to refine intervention strategies.These efforts are vital to reducing preventable blindness and improving quality of life for aging populations in underserved areas.展开更多
AIM:To investigate the underlying causes of surgical failure and reoperation management in patients with rhegmatogenous retinal detachment(RRD)who underwent scleral buckle surgery at our institution.METHODS:This was a...AIM:To investigate the underlying causes of surgical failure and reoperation management in patients with rhegmatogenous retinal detachment(RRD)who underwent scleral buckle surgery at our institution.METHODS:This was a single-center,retrospective,descriptive study.The clinical data of 368 patients(387 eyes)with RRD who underwent scleral buckling(SB)surgery between August 2013 and July 2023 at our institution were collected.The aim was to analyze the causes of recurrence and the rationale for selecting reoperation methods.RESULTS:Totally 368 patients(387 eyes)were included in the analysis,comprising 222 males and 146 females.The average age was 30.26±14.18 years,and the mean follow-up duration was(48.33±20.39)mo.The success rate of SB surgery was 90.2%.Recurrent retinal detachment occurred in 38 eyes.Based on surgical records,the causes of SB failure were analyzed.The recurrence causes included abnormal compression ridge position(position,height,or width)in 14 eyes(36.8%,14/38),hole omission in 11 eyes(29.0%,11/38),proliferative vitreoretinopathy(PVR)in 10 eyes(26.3%,10/38),and new holes in 3 eyes(7.9%,3/38).Among these,8 eyes(21.1%,8/38)underwent repeat SB surgery,while the remaining 30 eyes(78.9%,30/38)underwent pars plana vitrectomy(PPV).Regarding tamponade agents,silicone oil was used in 11 eyes(36.7%,11/30),C 3F 8 gas in 12 eyes(40.0%,12/30),and sterile air in 7 eyes(23.3%,7/30).CONCLUSION:SB surgery demonstrates a high success rate in the treatment of RRD.However,abnormal compression ridge position,missed holes during surgery,and PVR are the primary causes of SB failure.After addressing the reasons for failure,re-SB surgery or PPV can be effective alternatives.展开更多
The rapid advancements in computer vision(CV)technology have transformed the traditional approaches to material microstructure analysis.This review outlines the history of CV and explores the applications of deep-lear...The rapid advancements in computer vision(CV)technology have transformed the traditional approaches to material microstructure analysis.This review outlines the history of CV and explores the applications of deep-learning(DL)-driven CV in four key areas of materials science:microstructure-based performance prediction,microstructure information generation,microstructure defect detection,and crystal structure-based property prediction.The CV has significantly reduced the cost of traditional experimental methods used in material performance prediction.Moreover,recent progress made in generating microstructure images and detecting microstructural defects using CV has led to increased efficiency and reliability in material performance assessments.The DL-driven CV models can accelerate the design of new materials with optimized performance by integrating predictions based on both crystal and microstructural data,thereby allowing for the discovery and innovation of next-generation materials.Finally,the review provides insights into the rapid interdisciplinary developments in the field of materials science and future prospects.展开更多
In the competitive retail industry of the digital era,data-driven insights into gender-specific customer behavior are essential.They support the optimization of store performance,layout design,product placement,and ta...In the competitive retail industry of the digital era,data-driven insights into gender-specific customer behavior are essential.They support the optimization of store performance,layout design,product placement,and targeted marketing.However,existing computer vision solutions often rely on facial recognition to gather such insights,raising significant privacy and ethical concerns.To address these issues,this paper presents a privacypreserving customer analytics system through two key strategies.First,we deploy a deep learning framework using YOLOv9s,trained on the RCA-TVGender dataset.Cameras are positioned perpendicular to observation areas to reduce facial visibility while maintaining accurate gender classification.Second,we apply AES-128 encryption to customer position data,ensuring secure access and regulatory compliance.Our system achieved overall performance,with 81.5%mAP@50,77.7%precision,and 75.7%recall.Moreover,a 90-min observational study confirmed the system’s ability to generate privacy-protected heatmaps revealing distinct behavioral patterns between male and female customers.For instance,women spent more time in certain areas and showed interest in different products.These results confirm the system’s effectiveness in enabling personalized layout and marketing strategies without compromising privacy.展开更多
AIM：To survey the prevalence and causes of visual impairment/blindness among elderly Chinese from different socioeconomic status in community-based design.METHODS：Cluster-sampling randomly selected residents from Bi...AIM：To survey the prevalence and causes of visual impairment/blindness among elderly Chinese from different socioeconomic status in community-based design.METHODS：Cluster-sampling randomly selected residents from Binhu and Funing District,two areas representing different socioeconomic levels in China with Binhu in an advanced status and Funing in lessdeveloped area.The participants subjected to ophthalmic examination.The presenting visual acuity（PVA） and best-corrected visual acuity（BCVA） were recorded.Visual impairment and blindness were defined according to World Health Organization criteria.The causes of visual impairment/blindness were identified by ophthalmic examination and/or questionnaire.The socioeconomic status included the per capita gross domestic product,numbers of hospital with ophthalmic service and the number of ophthalmologists per 1 million residents.RESULTS：We successfully included 12 867 participants form 2 areas in this study.The prevalence of PVA impairment（〈20/63 to ≥20/400） in the better eye was 5.4% in Binhu and 23.6% in Funing,while the prevalence of blindness（〈20/400） was 0.9% in Binhu and 2.3% in Funing.With BCVA,the prevalence of visual impairment was 2.4% in Binhu and 6.4% in Funing,while the prevalence of blindness was 0.8% in Binhu and 1.6% in Funing.The participants with older age and female gender had higher prevalence in visual impairment and blindness.The highest prevalences of vision impairment and blindness evaluated by BCVA at 〉80y age group reached 20.4% and 6.3% respectively.The prevalences of vision impairment and blindness evaluated by BCVA were 3.5% and 1.0% in male and 5.0% and 1.3% in female.The above differences were statistically significant（P〈0.05）.The predominant causes of visual impairment and blindness were cataract,retinal disorders and uncorrected refractive error in both areas.The socioeconomic status was associated with visual impairment and blindness.CONCLUSION：This community-based study build a sufficient sample size for an ophthalmic survey.Our data show the disparities on socioeconomic development and genders in visual impairment and blindness in China.Special emphasis of ophthalmic service should be placed on females and less-developed area.展开更多
BACKGROUND Unicompartmental knee arthroplasty(UKA)has great advantages in the treatment of unicompartmental knee osteoarthritis,but its revision rate is higher than that of total knee arthroplasty.AIM To summarize and...BACKGROUND Unicompartmental knee arthroplasty(UKA)has great advantages in the treatment of unicompartmental knee osteoarthritis,but its revision rate is higher than that of total knee arthroplasty.AIM To summarize and analyse the causes of revision after UKA.METHODS This is a retrospective case series study in which the reasons for the first revision after UKA are summarized.We analysed the clinical symptoms,medical histories,laboratory test results,imaging examination results and treatment processes of the patients who underwent revision and summarized the reasons for primary revision after UKA.RESULTS A total of 13 patients,including 3 males and 10 females,underwent revision surgery after UKA.The average age of the included patients was 67.62 years.The prosthesis was used for 3 d to 72 months.The main reasons for revision after UKA were improper suturing of the surgical opening(1 patient),osteophytes(2 patients),intra-articular loose bodies(2 patients),tibial prosthesis loosening(2 patients),rheumatoid arthritis(1 patient),gasket dislocation(3 patients),anterior cruciate ligament injury(1 patient),and medial collateral ligament injury with residual bone cement(1 patient).CONCLUSION The causes of primary revision after UKA were gasket dislocation,osteophytes,intra-articular loose bodies and tibial prosthesis loosening.Avoidance of these factors may greatly reduce the rate of revision after UKA,improve patient satisfaction and reduce medical burden.展开更多
<strong>Introduction: </strong>Stress and burnout are a reality which nurses encounter and try to cope with especially in the Emergency Department (ED) so that they can provide optimal patient care. Nurses...<strong>Introduction: </strong>Stress and burnout are a reality which nurses encounter and try to cope with especially in the Emergency Department (ED) so that they can provide optimal patient care. Nurses who work in ED are front line providers of immediate medical care needed to stabilize patients. With the known critical shortage of health workforce in Cameroon, nurses are overloaded with work and often experience stress and burnout. <strong>Aim: </strong>This study aimed at determining the causes, effects and management strategies of stress and burnout among nurses working in the ED in hospitals in the Fako Division, Cameroon. <strong>Methods:</strong> This study was a descriptive cross-sectional study. The sample consisted of seventy nurses from five different hospitals. A purposive sampling technique was used and data was analyzed using SPSS version 16.0. Data was collected using a structured questionnaire developed from the International Stress Management Scale. <strong>Results: </strong>The highest reported cause of stress in this study was heavy workload (12.88%) and the least was no experience in handling the challenges of the department. The leading reported effect of stress was the development of musculoskeletal disorders such as joint and back pain (16.48%) and the least effect was contemplating quitting the profession (5.99%). The major management strategy used was humour (8.27%), while the least was crying out stress to feel relieved (2.18%).<strong> Conclusion: </strong>The major cause of stress and burnout among nurses in our study setting was heavy workload, which mostly results in joint and back pain. Moreover, humour was the prime management strategy for stress and burnout among nurses in the emergency department in the study setting. Thus more nurses should be employed and the working conditions of nurses improved to reduce the workload in the study hospitals.展开更多
Detecting pavement cracks is critical for road safety and infrastructure management.Traditional methods,relying on manual inspection and basic image processing,are time-consuming and prone to errors.Recent deep-learni...Detecting pavement cracks is critical for road safety and infrastructure management.Traditional methods,relying on manual inspection and basic image processing,are time-consuming and prone to errors.Recent deep-learning(DL)methods automate crack detection,but many still struggle with variable crack patterns and environmental conditions.This study aims to address these limitations by introducing the Masker Transformer,a novel hybrid deep learning model that integrates the precise localization capabilities of Mask Region-based Convolutional Neural Network(Mask R-CNN)with the global contextual awareness of Vision Transformer(ViT).The research focuses on leveraging the strengths of both architectures to enhance segmentation accuracy and adaptability across different pavement conditions.We evaluated the performance of theMaskerTransformer against other state-of-theartmodels such asU-Net,TransformerU-Net(TransUNet),U-NetTransformer(UNETr),SwinU-NetTransformer(Swin-UNETr),You Only Look Once version 8(YoloV8),and Mask R-CNN using two benchmark datasets:Crack500 and DeepCrack.The findings reveal that the MaskerTransformer significantly outperforms the existing models,achieving the highest Dice SimilarityCoefficient(DSC),precision,recall,and F1-Score across both datasets.Specifically,the model attained a DSC of 80.04%on Crack500 and 91.37%on DeepCrack,demonstrating superior segmentation accuracy and reliability.The high precision and recall rates further substantiate its effectiveness in real-world applications,suggesting that the Masker Transformer can serve as a robust tool for automated pavement crack detection,potentially replacing more traditional methods.展开更多
Understanding the levels,causes,and sources of fluoride in groundwater is critical for public health,effective water resource management,and sustainable utilization.This study employs multivariate statistical methods,...Understanding the levels,causes,and sources of fluoride in groundwater is critical for public health,effective water resource management,and sustainable utilization.This study employs multivariate statistical methods,hazard quotient assessment,and geochemical analyses,such as mineral saturation index,ionic activities,and Gibbs diagrams,to investigate the hydrochemical characteristics,causes,and noncarcinogenic risks of fluoride in Red bed groundwater and geothermal water in the Guang'an area and neighboring regions.Approximately 9%of the Red bed groundwater samples contain fluoride concentrations exceeding 1 mg·L^(-1).The predominant water types identified are Cl-Na and HCO_(3)-Na,primarily influenced by evapotranspiration.Low-fluoride groundwater and high-fluoride geothermal water exhibit distinct hydrochemical types HCO_(3)-Ca and SO_(4)-Ca,respectively,which are mainly related to the weathering of carbonate,sulfate,and fluorite-containing rocks.Correlation analysis reveals that fluoride content in Red bed groundwater is positively associated with Na^(+),Cl^(-),SO_(4)^(2-),and TDS(r^(2)=0.45-0.64,p<0.01),while in geothermal water,it correlates strongly with pH,K^(+),Ca^(2+),and Mg^(2+)(r^(2)=0.52-0.80,p<0.05).Mineral saturation indices and ionic activities indicate that ion exchange processes and the dissolution of minerals such as carbonatite and fluorite are important sources of fluoride in groundwater.The enrichment of fluorine in the Red bed groundwater is linked to evaporation,cation exchange and dissolution of fluorite,caused by the lithologic characteristics of the red bed in this area.However,it exhibits minimal correlation with the geothermal water in the adjacent area.The noncarcinogenic health risk assessment indicates that 7%(n=5)of Red bed groundwater points exceed the fluoride safety limit for adults,while 12%(n=8)exceed the limit for children.These findings underscore the importance of avoiding highly fluoridated red bed groundwater as a direct drinking source and enhancing groundwater monitoring to mitigate health risks associated with elevated fluoride levels.展开更多
To overcome the limitations of low efficiency and reliance on manual processes in the measurement of geometric parameters for bridge prefabricated components,a method based on deep learning and computer vision is deve...To overcome the limitations of low efficiency and reliance on manual processes in the measurement of geometric parameters for bridge prefabricated components,a method based on deep learning and computer vision is developed to identify the geometric parameters.The study utilizes a common precast element for highway bridges as the research subject.First,edge feature points of the bridge component section are extracted from images of the precast component cross-sections by combining the Canny operator with mathematical morphology.Subsequently,a deep learning model is developed to identify the geometric parameters of the precast components using the extracted edge coordinates from the images as input and the predefined control parameters of the bridge section as output.A dataset is generated by varying the control parameters and noise levels for model training.Finally,field measurements are conducted to validate the accuracy of the developed method.The results indicate that the developed method effectively identifies the geometric parameters of bridge precast components,with an error rate maintained within 5%.展开更多
Recently,for developing neuromorphic visual systems,adaptive optoelectronic devices become one of the main research directions and attract extensive focus to achieve optoelectronic transistors with high performances a...Recently,for developing neuromorphic visual systems,adaptive optoelectronic devices become one of the main research directions and attract extensive focus to achieve optoelectronic transistors with high performances and flexible func-tionalities.In this review,based on a description of the biological adaptive functions that are favorable for dynamically perceiv-ing,filtering,and processing information in the varying environment,we summarize the representative strategies for achiev-ing these adaptabilities in optoelectronic transistors,including the adaptation for detecting information,adaptive synaptic weight change,and history-dependent plasticity.Moreover,the key points of the corresponding strategies are comprehen-sively discussed.And the applications of these adaptive optoelectronic transistors,including the adaptive color detection,sig-nal filtering,extending the response range of light intensity,and improve learning efficiency,are also illustrated separately.Lastly,the challenges faced in developing adaptive optoelectronic transistor for artificial vision system are discussed.The descrip-tion of biological adaptive functions and the corresponding inspired neuromorphic devices are expected to provide insights for the design and application of next-generation artificial visual systems.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
基金supported by Science and Technology Planning Project of Guangzhou City(2024A04J4474).
文摘Objective:This study aimed to investigate the prevalence,causes,and influencing factors of vision impairment in the elderly population aged 60 years and above in Mangxin Town,Kashgar region,Xinjiang,China.Located in a region characterized by intense ultraviolet radiation and arid climatic conditions,Mangxin Town presents unique environmental challenges that may exacerbate ocular health issues.Despite the global emphasis on addressing vision impairment among aging populations,there remains a paucity of updated and region-specific data in Xinjiang,necessitating this comprehensive assessment to inform targeted interventions.Methods:A cross-sectional study was conducted from May to June 2024,involving 1,311 elderly participants(76.76%participation rate)out of a total eligible population of 1,708 individuals aged≥60 years.Participants underwent detailed ocular examinations,including assessments of uncorrected visual acuity(UVA)and best-corrected visual acuity(BCVA)using standard logarithmic charts,slit-lamp biomicroscopy,optical coherence tomography(OCT,Topcon DRI OCT Triton),fundus photography,and intraocular pressure measurement(Canon TX-20 Tonometer).A multidisciplinary team of 10 ophthalmologists and 2 local village doctors,trained rigorously in standardized protocols,ensured consistent data collection.Demographic,lifestyle,and medical history data were collected via questionnaires.Statistical analyses,performed using STATA 16,included multivariate logistic regression to identify risk factors,with significance defined as P<0.05.Results:The overall prevalence of vision impairment was 13.21%(95%CI:11.37%-15.04%),with low vision at 11.76%(95%CI:10.01%-13.50%)and blindness at 1.45%(95%CI:0.80%-2.10%).Cataract emerged as the leading cause,responsible for 68.20%of cases,followed by glaucoma(5.80%),optic atrophy(5.20%),and age-related macular degeneration(2.90%).Vision impairment prevalence escalated significantly with age:7.74%in the 60–69 age group,17.79%in 70–79,and 33.72%in those≥80.Males exhibited higher prevalence than females(15.84%vs.10.45%,P=0.004).Multivariate analysis revealed age≥80 years(OR=6.43,95%CI:3.79%-10.90%),male sex(OR=0.53,95%CI:0.34%-0.83%),and daily exercise(OR=0.44,95%CI:0.20%-0.95%)as significant factors.History of eye disease showed a non-significant trend toward increased risk(OR=1.49,P=0.107).Education level,income,and smoking status showed no significant associations.Conclusions:This study underscores cataract as the predominant cause of vision impairment in Mangxin Town’s elderly population,with age and sex as critical determinants.The findings align with global patterns but highlight region-specific challenges,such as environmental factors contributing to cataract prevalence.Public health strategies should prioritize improving access to cataract surgery,enhancing grassroots ophthalmic infrastructure,and integrating portable screening technologies for early detection of fundus diseases.Additionally,promoting health education on UV protection and lifestyle modifications,such as regular exercise,may mitigate risks.Future research should expand to broader regions in Xinjiang,employ advanced diagnostic tools for complex conditions like glaucoma,and explore longitudinal trends to refine intervention strategies.These efforts are vital to reducing preventable blindness and improving quality of life for aging populations in underserved areas.
文摘AIM:To investigate the underlying causes of surgical failure and reoperation management in patients with rhegmatogenous retinal detachment(RRD)who underwent scleral buckle surgery at our institution.METHODS:This was a single-center,retrospective,descriptive study.The clinical data of 368 patients(387 eyes)with RRD who underwent scleral buckling(SB)surgery between August 2013 and July 2023 at our institution were collected.The aim was to analyze the causes of recurrence and the rationale for selecting reoperation methods.RESULTS:Totally 368 patients(387 eyes)were included in the analysis,comprising 222 males and 146 females.The average age was 30.26±14.18 years,and the mean follow-up duration was(48.33±20.39)mo.The success rate of SB surgery was 90.2%.Recurrent retinal detachment occurred in 38 eyes.Based on surgical records,the causes of SB failure were analyzed.The recurrence causes included abnormal compression ridge position(position,height,or width)in 14 eyes(36.8%,14/38),hole omission in 11 eyes(29.0%,11/38),proliferative vitreoretinopathy(PVR)in 10 eyes(26.3%,10/38),and new holes in 3 eyes(7.9%,3/38).Among these,8 eyes(21.1%,8/38)underwent repeat SB surgery,while the remaining 30 eyes(78.9%,30/38)underwent pars plana vitrectomy(PPV).Regarding tamponade agents,silicone oil was used in 11 eyes(36.7%,11/30),C 3F 8 gas in 12 eyes(40.0%,12/30),and sterile air in 7 eyes(23.3%,7/30).CONCLUSION:SB surgery demonstrates a high success rate in the treatment of RRD.However,abnormal compression ridge position,missed holes during surgery,and PVR are the primary causes of SB failure.After addressing the reasons for failure,re-SB surgery or PPV can be effective alternatives.
基金financially supported by the National Science Fund for Distinguished Young Scholars,China(No.52025041)the National Natural Science Foundation of China(Nos.52450003,U2341267,and 52174294)+1 种基金the National Postdoctoral Program for Innovative Talents,China(No.BX20240437)the Fundamental Research Funds for the Central Universities,China(Nos.FRF-IDRY-23-037 and FRF-TP-20-02C2)。
文摘The rapid advancements in computer vision(CV)technology have transformed the traditional approaches to material microstructure analysis.This review outlines the history of CV and explores the applications of deep-learning(DL)-driven CV in four key areas of materials science:microstructure-based performance prediction,microstructure information generation,microstructure defect detection,and crystal structure-based property prediction.The CV has significantly reduced the cost of traditional experimental methods used in material performance prediction.Moreover,recent progress made in generating microstructure images and detecting microstructural defects using CV has led to increased efficiency and reliability in material performance assessments.The DL-driven CV models can accelerate the design of new materials with optimized performance by integrating predictions based on both crystal and microstructural data,thereby allowing for the discovery and innovation of next-generation materials.Finally,the review provides insights into the rapid interdisciplinary developments in the field of materials science and future prospects.
文摘In the competitive retail industry of the digital era,data-driven insights into gender-specific customer behavior are essential.They support the optimization of store performance,layout design,product placement,and targeted marketing.However,existing computer vision solutions often rely on facial recognition to gather such insights,raising significant privacy and ethical concerns.To address these issues,this paper presents a privacypreserving customer analytics system through two key strategies.First,we deploy a deep learning framework using YOLOv9s,trained on the RCA-TVGender dataset.Cameras are positioned perpendicular to observation areas to reduce facial visibility while maintaining accurate gender classification.Second,we apply AES-128 encryption to customer position data,ensuring secure access and regulatory compliance.Our system achieved overall performance,with 81.5%mAP@50,77.7%precision,and 75.7%recall.Moreover,a 90-min observational study confirmed the system’s ability to generate privacy-protected heatmaps revealing distinct behavioral patterns between male and female customers.For instance,women spent more time in certain areas and showed interest in different products.These results confirm the system’s effectiveness in enabling personalized layout and marketing strategies without compromising privacy.
基金Supported by the National Natural Science Foundation of China(No.81070718)the 333 Project of Jiangsu Province,China(No.BRA2010173)
文摘AIM：To survey the prevalence and causes of visual impairment/blindness among elderly Chinese from different socioeconomic status in community-based design.METHODS：Cluster-sampling randomly selected residents from Binhu and Funing District,two areas representing different socioeconomic levels in China with Binhu in an advanced status and Funing in lessdeveloped area.The participants subjected to ophthalmic examination.The presenting visual acuity（PVA） and best-corrected visual acuity（BCVA） were recorded.Visual impairment and blindness were defined according to World Health Organization criteria.The causes of visual impairment/blindness were identified by ophthalmic examination and/or questionnaire.The socioeconomic status included the per capita gross domestic product,numbers of hospital with ophthalmic service and the number of ophthalmologists per 1 million residents.RESULTS：We successfully included 12 867 participants form 2 areas in this study.The prevalence of PVA impairment（〈20/63 to ≥20/400） in the better eye was 5.4% in Binhu and 23.6% in Funing,while the prevalence of blindness（〈20/400） was 0.9% in Binhu and 2.3% in Funing.With BCVA,the prevalence of visual impairment was 2.4% in Binhu and 6.4% in Funing,while the prevalence of blindness was 0.8% in Binhu and 1.6% in Funing.The participants with older age and female gender had higher prevalence in visual impairment and blindness.The highest prevalences of vision impairment and blindness evaluated by BCVA at 〉80y age group reached 20.4% and 6.3% respectively.The prevalences of vision impairment and blindness evaluated by BCVA were 3.5% and 1.0% in male and 5.0% and 1.3% in female.The above differences were statistically significant（P〈0.05）.The predominant causes of visual impairment and blindness were cataract,retinal disorders and uncorrected refractive error in both areas.The socioeconomic status was associated with visual impairment and blindness.CONCLUSION：This community-based study build a sufficient sample size for an ophthalmic survey.Our data show the disparities on socioeconomic development and genders in visual impairment and blindness in China.Special emphasis of ophthalmic service should be placed on females and less-developed area.
基金Supported by National Natural Science Foundation of China,No.82004386and Guangdong Basic and Applied Basic Research Foundation,No.2022A1515011700.
文摘BACKGROUND Unicompartmental knee arthroplasty(UKA)has great advantages in the treatment of unicompartmental knee osteoarthritis,but its revision rate is higher than that of total knee arthroplasty.AIM To summarize and analyse the causes of revision after UKA.METHODS This is a retrospective case series study in which the reasons for the first revision after UKA are summarized.We analysed the clinical symptoms,medical histories,laboratory test results,imaging examination results and treatment processes of the patients who underwent revision and summarized the reasons for primary revision after UKA.RESULTS A total of 13 patients,including 3 males and 10 females,underwent revision surgery after UKA.The average age of the included patients was 67.62 years.The prosthesis was used for 3 d to 72 months.The main reasons for revision after UKA were improper suturing of the surgical opening(1 patient),osteophytes(2 patients),intra-articular loose bodies(2 patients),tibial prosthesis loosening(2 patients),rheumatoid arthritis(1 patient),gasket dislocation(3 patients),anterior cruciate ligament injury(1 patient),and medial collateral ligament injury with residual bone cement(1 patient).CONCLUSION The causes of primary revision after UKA were gasket dislocation,osteophytes,intra-articular loose bodies and tibial prosthesis loosening.Avoidance of these factors may greatly reduce the rate of revision after UKA,improve patient satisfaction and reduce medical burden.
文摘<strong>Introduction: </strong>Stress and burnout are a reality which nurses encounter and try to cope with especially in the Emergency Department (ED) so that they can provide optimal patient care. Nurses who work in ED are front line providers of immediate medical care needed to stabilize patients. With the known critical shortage of health workforce in Cameroon, nurses are overloaded with work and often experience stress and burnout. <strong>Aim: </strong>This study aimed at determining the causes, effects and management strategies of stress and burnout among nurses working in the ED in hospitals in the Fako Division, Cameroon. <strong>Methods:</strong> This study was a descriptive cross-sectional study. The sample consisted of seventy nurses from five different hospitals. A purposive sampling technique was used and data was analyzed using SPSS version 16.0. Data was collected using a structured questionnaire developed from the International Stress Management Scale. <strong>Results: </strong>The highest reported cause of stress in this study was heavy workload (12.88%) and the least was no experience in handling the challenges of the department. The leading reported effect of stress was the development of musculoskeletal disorders such as joint and back pain (16.48%) and the least effect was contemplating quitting the profession (5.99%). The major management strategy used was humour (8.27%), while the least was crying out stress to feel relieved (2.18%).<strong> Conclusion: </strong>The major cause of stress and burnout among nurses in our study setting was heavy workload, which mostly results in joint and back pain. Moreover, humour was the prime management strategy for stress and burnout among nurses in the emergency department in the study setting. Thus more nurses should be employed and the working conditions of nurses improved to reduce the workload in the study hospitals.
文摘Detecting pavement cracks is critical for road safety and infrastructure management.Traditional methods,relying on manual inspection and basic image processing,are time-consuming and prone to errors.Recent deep-learning(DL)methods automate crack detection,but many still struggle with variable crack patterns and environmental conditions.This study aims to address these limitations by introducing the Masker Transformer,a novel hybrid deep learning model that integrates the precise localization capabilities of Mask Region-based Convolutional Neural Network(Mask R-CNN)with the global contextual awareness of Vision Transformer(ViT).The research focuses on leveraging the strengths of both architectures to enhance segmentation accuracy and adaptability across different pavement conditions.We evaluated the performance of theMaskerTransformer against other state-of-theartmodels such asU-Net,TransformerU-Net(TransUNet),U-NetTransformer(UNETr),SwinU-NetTransformer(Swin-UNETr),You Only Look Once version 8(YoloV8),and Mask R-CNN using two benchmark datasets:Crack500 and DeepCrack.The findings reveal that the MaskerTransformer significantly outperforms the existing models,achieving the highest Dice SimilarityCoefficient(DSC),precision,recall,and F1-Score across both datasets.Specifically,the model attained a DSC of 80.04%on Crack500 and 91.37%on DeepCrack,demonstrating superior segmentation accuracy and reliability.The high precision and recall rates further substantiate its effectiveness in real-world applications,suggesting that the Masker Transformer can serve as a robust tool for automated pavement crack detection,potentially replacing more traditional methods.
基金supported by the China Geological Survey Project(Nos.DD20220864 and DD20243077).
文摘Understanding the levels,causes,and sources of fluoride in groundwater is critical for public health,effective water resource management,and sustainable utilization.This study employs multivariate statistical methods,hazard quotient assessment,and geochemical analyses,such as mineral saturation index,ionic activities,and Gibbs diagrams,to investigate the hydrochemical characteristics,causes,and noncarcinogenic risks of fluoride in Red bed groundwater and geothermal water in the Guang'an area and neighboring regions.Approximately 9%of the Red bed groundwater samples contain fluoride concentrations exceeding 1 mg·L^(-1).The predominant water types identified are Cl-Na and HCO_(3)-Na,primarily influenced by evapotranspiration.Low-fluoride groundwater and high-fluoride geothermal water exhibit distinct hydrochemical types HCO_(3)-Ca and SO_(4)-Ca,respectively,which are mainly related to the weathering of carbonate,sulfate,and fluorite-containing rocks.Correlation analysis reveals that fluoride content in Red bed groundwater is positively associated with Na^(+),Cl^(-),SO_(4)^(2-),and TDS(r^(2)=0.45-0.64,p<0.01),while in geothermal water,it correlates strongly with pH,K^(+),Ca^(2+),and Mg^(2+)(r^(2)=0.52-0.80,p<0.05).Mineral saturation indices and ionic activities indicate that ion exchange processes and the dissolution of minerals such as carbonatite and fluorite are important sources of fluoride in groundwater.The enrichment of fluorine in the Red bed groundwater is linked to evaporation,cation exchange and dissolution of fluorite,caused by the lithologic characteristics of the red bed in this area.However,it exhibits minimal correlation with the geothermal water in the adjacent area.The noncarcinogenic health risk assessment indicates that 7%(n=5)of Red bed groundwater points exceed the fluoride safety limit for adults,while 12%(n=8)exceed the limit for children.These findings underscore the importance of avoiding highly fluoridated red bed groundwater as a direct drinking source and enhancing groundwater monitoring to mitigate health risks associated with elevated fluoride levels.
基金The National Natural Science Foundation of China(No.52338011,52378291)Young Elite Scientists Sponsorship Program by CAST(No.2022-2024QNRC0101).
文摘To overcome the limitations of low efficiency and reliance on manual processes in the measurement of geometric parameters for bridge prefabricated components,a method based on deep learning and computer vision is developed to identify the geometric parameters.The study utilizes a common precast element for highway bridges as the research subject.First,edge feature points of the bridge component section are extracted from images of the precast component cross-sections by combining the Canny operator with mathematical morphology.Subsequently,a deep learning model is developed to identify the geometric parameters of the precast components using the extracted edge coordinates from the images as input and the predefined control parameters of the bridge section as output.A dataset is generated by varying the control parameters and noise levels for model training.Finally,field measurements are conducted to validate the accuracy of the developed method.The results indicate that the developed method effectively identifies the geometric parameters of bridge precast components,with an error rate maintained within 5%.
基金the National Key Research and Development Program of China(2021YFA0717900)National Natural Science Foundation of China(62471251,62405144,62288102,22275098,and 62174089)+1 种基金Basic Research Program of Jiangsu(BK20240033,BK20243057)Jiangsu Funding Program for Excellent Postdoctoral Talent(2022ZB402).
文摘Recently,for developing neuromorphic visual systems,adaptive optoelectronic devices become one of the main research directions and attract extensive focus to achieve optoelectronic transistors with high performances and flexible func-tionalities.In this review,based on a description of the biological adaptive functions that are favorable for dynamically perceiv-ing,filtering,and processing information in the varying environment,we summarize the representative strategies for achiev-ing these adaptabilities in optoelectronic transistors,including the adaptation for detecting information,adaptive synaptic weight change,and history-dependent plasticity.Moreover,the key points of the corresponding strategies are comprehen-sively discussed.And the applications of these adaptive optoelectronic transistors,including the adaptive color detection,sig-nal filtering,extending the response range of light intensity,and improve learning efficiency,are also illustrated separately.Lastly,the challenges faced in developing adaptive optoelectronic transistor for artificial vision system are discussed.The descrip-tion of biological adaptive functions and the corresponding inspired neuromorphic devices are expected to provide insights for the design and application of next-generation artificial visual systems.
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.
