Automated grading of dandruff severity is a clinically significant but challenging task due to the inherent ordinal nature of severity levels and the high prevalence of label noise from subjective expert annotations.S...Automated grading of dandruff severity is a clinically significant but challenging task due to the inherent ordinal nature of severity levels and the high prevalence of label noise from subjective expert annotations.Standard classification methods fail to address these dual challenges,limiting their real-world performance.In this paper,a novel,three-phase training framework is proposed that learns a robust ordinal classifier directly from noisy labels.The approach synergistically combines a rank-based ordinal regression backbone with a cooperative,semi-supervised learning strategy to dynamically partition the data into clean and noisy subsets.A hybrid training objective is then employed,applying a supervised ordinal loss to the clean set.The noisy set is simultaneously trained using a dualobjective that combines a semi-supervised ordinal loss with a parallel,label-agnostic contrastive loss.This design allows themodel to learn fromthe entire noisy subset while using contrastive learning to mitigate the risk of error propagation frompotentially corrupt supervision.Extensive experiments on a new,large-scale,multi-site clinical dataset validate our approach.Themethod achieves state-of-the-art performance with 80.71%accuracy and a 76.86%F1-score,significantly outperforming existing approaches,including a 2.26%improvement over the strongest baseline method.This work provides not only a robust solution for a practical medical imaging problem but also a generalizable framework for other tasks plagued by noisy ordinal labels.展开更多
BACKGROUND Esophageal squamous cell carcinoma is a major histological subtype of esophageal cancer.Many molecular genetic changes are associated with its occurrence.Raman spectroscopy has become a new method for the e...BACKGROUND Esophageal squamous cell carcinoma is a major histological subtype of esophageal cancer.Many molecular genetic changes are associated with its occurrence.Raman spectroscopy has become a new method for the early diagnosis of tumors because it can reflect the structures of substances and their changes at the molecular level.AIM To detect alterations in Raman spectral information across different stages of esophageal neoplasia.METHODS Different grades of esophageal lesions were collected,and a total of 360 groups of Raman spectrum data were collected.A 1D-transformer network model was proposed to handle the task of classifying the spectral data of esophageal squamous cell carcinoma.In addition,a deep learning model was applied to visualize the Raman spectral data and interpret their molecular characteristics.RESULTS A comparison among Raman spectral data with different pathological grades and a visual analysis revealed that the Raman peaks with significant differences were concentrated mainly at 1095 cm^(-1)(DNA,symmetric PO,and stretching vibration),1132 cm^(-1)(cytochrome c),1171 cm^(-1)(acetoacetate),1216 cm^(-1)(amide III),and 1315 cm^(-1)(glycerol).A comparison among the training results of different models revealed that the 1Dtransformer network performed best.A 93.30%accuracy value,a 96.65%specificity value,a 93.30%sensitivity value,and a 93.17%F1 score were achieved.CONCLUSION Raman spectroscopy revealed significantly different waveforms for the different stages of esophageal neoplasia.The combination of Raman spectroscopy and deep learning methods could significantly improve the accuracy of classification.展开更多
Dear Editor,This letter proposes an end-to-end feature disentangled Transformer(FDTs)for entanglement-free and semantic feature representation to enable accurate and trustworthy pathology grading of squamous cell carc...Dear Editor,This letter proposes an end-to-end feature disentangled Transformer(FDTs)for entanglement-free and semantic feature representation to enable accurate and trustworthy pathology grading of squamous cell carcinoma(SCC).Existing vision transformers(ViTs)can implement representation learning for SCC grading,however,they all adopt the class-patch token fuzzy mapping for pattern prediction probability or window down-sampling to enhance the representation to contextual information.展开更多
This study aims to explore the correlation between plasma homocysteine (Hcy) levels and the clinical grading of varicocele (VC) when analyzing the potential pathogenesis of endothelial cells injury by Hcy. A total of ...This study aims to explore the correlation between plasma homocysteine (Hcy) levels and the clinical grading of varicocele (VC) when analyzing the potential pathogenesis of endothelial cells injury by Hcy. A total of 184 VC patients, aged 18–46 years, were included in this study. These patients visited The Second Hospital of Dalian Medical University (Dalian, China), between January 2022 and September 2024. Patients were divided into three groups based on clinical grading: Group A (59 cases, Grade I), Group B (28 cases, Grade II), and Group C (97 cases, Grade III). Additionally, 120 individuals with normal fertility test results during the same period were selected as the control group. Routine blood and biochemical indices were collected from the patients. Differences in clinical indices between groups were compared, and univariate and multivariate linear regression analyses were performed to identify factors associated with clinical grading. The results showed that the median Hcy levels in the control group and in patients with Grade I, II, and III VC were 9.56 (interquartile range [IQR]: 8.66, 14.02) µmol l−1, 11.28 (IQR: 9.71, 14.55) µmol l−1, 11.84 (IQR: 10.14, 15.60) µmol l−1, and 12.27 (IQR: 9.52, 15.40) µmol l−1, respectively. The differences between the four groups were statistically significant (χ2 = 12.41, P = 0.006). Multivariate regression analysis indicated that Hcy is a factor associated with the clinical grading of VC (t = 2.53, P = 0.013). Hcy is associated with the clinical grading and may have clinical value in assessing severity of VC.展开更多
In order to clarify the preparation process parameters of manufactured sand,optimize its quality,and analyze the effect of its grading on the microstructure of concrete,the three-dimensional models of jaw crusher,vibr...In order to clarify the preparation process parameters of manufactured sand,optimize its quality,and analyze the effect of its grading on the microstructure of concrete,the three-dimensional models of jaw crusher,vibrating screen and conveyor belt were established by using SolidWorks 2016 software.Rocky DEM4.5 software was used to simulate the initial crushing,screening,and transportation stages of the manufactured sand preparation process,with Linear Spring Dashpot as the normal contact model and Coulomb as the tangential contact model;furthermore,the key process parameters were defined.The manufactured sand grading model was then proposed,thereby,the influence of the grading of manufactured sand on the distribution of pore structure in concrete and the interfacial transition zone(ITZ)was studied.The experimetal results show that the particle size of granite,after being crushed in the jaw crusher,is primarily concentrated between 80 and 130 mm,with a crushing energy consumption typically below 100000 J.However,certain instances of granite exhibit higher energy consumption due to undergoing multiple crushings within the chamber.At the same time,the granite causes significant wear on the jaw crusher plate.Furthermore,the tilt angle of the vibrating screen should be adjusted to between 10 and 15 degrees,while the layout angle of the conveyor belt needs to be set at 16 degrees.The proposed manufactured sand grading model is feasible,and the pore diameter distribution inside concrete increases with an increase in the fineness modulus of manufactured sand.展开更多
Innovation in learning algorithms has made retinal vessel segmentation and automatic grading tech-niques crucial for clinical diagnosis and prevention of diabetic retinopathy.The traditional methods struggle with accu...Innovation in learning algorithms has made retinal vessel segmentation and automatic grading tech-niques crucial for clinical diagnosis and prevention of diabetic retinopathy.The traditional methods struggle with accuracy and reliability due to multi-scale variations in retinal blood vessels and the complex pathological relationship in fundus images associated with diabetic retinopathy.While the single-modal diabetic retinopathy grading network addresses class imbalance challenges and lesion representation in fundus image data,dual-modal diabetic retinopathy grading methods offer superior performance.However,the scarcity of dual-modal data and the lack of effective feature fusion methods limit their potential due to multi-scale variations.This paper addresses these issues by focusing on multi-scale retinal vessel segmentation,dual feature fusion,data augmentation,and attention-based grading.The proposed model aims to improve comprehensive segmentation for retinal images with varying vessel thicknesses.It employs a dual-branch parallel architecture that integrates a transformer encoder with a convolutional neural network encoder to extract local and global information for synergistic saliency learning.Besides that,the model uses residual structures and attention modules to extract critical lesions,enhancing the accuracy and reliability of diabetic retinopathy grading.To evaluate the efficacy of the proposed approach,this study compared it with other pre-trained publicly open models,ResNet152V2,ConvNext,Efficient Net,DenseNet,and Swin Transform,with the same developmental parameters.All models achieved approximately 85%accuracy with the same image preparation method.However,the proposed approach outperforms and optimizes existing models by achieving an accuracy of 99.17%,99.04%,and 99.24%,on Kaggle APTOS19,IDRiD,and EyePACS datasets,respectively.These results support the model’s utility in helping ophthalmologists diagnose diabetic retinopathy more rapidly and accurately.展开更多
Addressing challenges in accurately detecting persimmon fruit quality in orchards—such as reliance on manual grading,low efficiency,severe foliage obstruction,and subtle differences between quality grades—this paper...Addressing challenges in accurately detecting persimmon fruit quality in orchards—such as reliance on manual grading,low efficiency,severe foliage obstruction,and subtle differences between quality grades—this paper proposes a lightweight persimmon detection model based on an improved YOLOv8s architecture.First,the Conv layer in the backbone network is replaced with an ADown module to reduce model complexity.Second,MSFAN is introduced in the Neck layer to fully extract texture features from persimmon images,highlighting differences between quality grades.Finally,the Wise-IoU loss function mitigates the impact of low-quality sample data on grading accuracy.The improved model accurately identifies and separates persimmons of varying quality,effectively addressing quality grading detection in complex backgrounds.This provides a viable technical approach for achieving persimmon quality grading detection.展开更多
As a paddy—upland rotation system, tobacco—rice rotation hastypical characteristics in the formation and evolution of soil fertility duringthe tobacco season with dry farming and rice season with water cultivation.T...As a paddy—upland rotation system, tobacco—rice rotation hastypical characteristics in the formation and evolution of soil fertility duringthe tobacco season with dry farming and rice season with water cultivation.To scientifically unveil the soil fertility formation process and grade thesoil fertility in tobacco—rice rotation areas, we collected 372 soil samplesfrom 11 tobacco stations (Haotang, Aoquan, Chengjiao, Renyi, Fangyuan,Anping, Huangsha, Taiping, Tushi, Dashiqiao, and Baimangying) in thetypical tobacco—rice rotation areas of Chenzhou and Yongzhou in SouthernHunan. The physical, chemical, and biological indicators of the soil sampleswere measured, and the tobacco and rice yields of each tobacco stationwere investigated. Machine learning was employed to screen the keyindicators influencing the tobacco yield, and a comprehensive numericalanalysis method combining principal component analysis and discriminantanalysis were adopted to cluster the sampling points, analyze their fertilityformation processes, and grade the soil fertility. The results showed thatclay content, available phosphorus, plow layer depth, slit-to-clay ratio, totalnitrogen, basal respiration, and organic carbon were identified as seven keyindicators influencing the tobacco yield. The results of the comprehensivenumerical analysis predicted two main processes involved in the formationof soil fertility in tobacco—rice rotation areas. One was the soil maturationprocess related to soil carbon and nitrogen cycling, and the other was theprocess of changes in soil physical properties such as clay content and slitto-clay ratio. According to the established soil fertility grading methodfor tobacco—rice rotation areas, the soil fertility of 11 tobacco stationswas graded. The results showed that the soil fertility was high in Haotang,Aoquan, Renyi, and Dashiqiao, medium in Huangsha and Tushi, and low inAnping, Baimangying, and Taiping. The tobacco and rice yields confirmedthat this grading standard can be effectively applied to the grading of soilfertility in the tobacco—rice rotation areas in Southern Hunan and canprovide a scientific basis for soil management in tobacco—rice rotation.展开更多
One in every eight men in the US is diagnosed with prostate cancer,making it the most common cancer in men.Gleason grading is one of the most essential diagnostic and prognostic factors for planning the treatment of p...One in every eight men in the US is diagnosed with prostate cancer,making it the most common cancer in men.Gleason grading is one of the most essential diagnostic and prognostic factors for planning the treatment of prostate cancer patients.Traditionally,urological pathologists perform the grading by scoring the morphological pattern,known as the Gleason pattern,in histopathology images.However,thismanual grading is highly subjective,suffers intra-and inter-pathologist variability and lacks reproducibility.An automated grading system could be more efficient,with no subjectivity and higher accuracy and reproducibility.Automated methods presented previously failed to achieve sufficient accuracy,lacked reproducibility and depended on high-resolution images such as 40×.This paper proposes an automated Gleason grading method,ProGENET,to accurately predict the grade using low-resolution images such as 10×.This method first divides the patient’s histopathology whole slide image(WSI)into patches.Then,it detects artifacts and tissue-less regions and predicts the patch-wise grade using an ensemble network of CNN and transformer models.The proposed method adapted the International Society of Urological Pathology(ISUP)grading system and achieved 90.8%accuracy in classifying the patches into healthy and Gleason grades 1 through 5 using 10×WSI,outperforming the state-of-the-art accuracy by 27%.Finally,the patient’s grade was determined by combining the patch-wise results.The method was also demonstrated for 4−class grading and binary classification of prostate cancer,achieving 93.0%and 99.6%accuracy,respectively.The reproducibility was over 90%.Since the proposedmethod determined the grades with higher accuracy and reproducibility using low-resolution images,it is more reliable and effective than existing methods and can potentially improve subsequent therapy decisions.展开更多
The wear of work rolls significantly affects the production efficiency and product quality.However,existing methods for wear assessment fail to effectively quantify work roll surface wear conditions,thereby affecting ...The wear of work rolls significantly affects the production efficiency and product quality.However,existing methods for wear assessment fail to effectively quantify work roll surface wear conditions,thereby affecting the quality control of steel strips and maintenance strategies for rolls.To accurately assess the wear conditions of hot-rolling work rolls,this study initially established an apparatus for capturing high-precision roll surfaces images.Subsequently,a quantitative assessment of common surface wear morphologies was conducted,and a hot-rolling work roll surface wear dataset was constructed.The MobileNetV2 convolutional neural network(CNN),augmented by transfer learning,was employed to develop a MobileNetV2-wear detection and classification(WDC)surface wear grading model.A comparison with mainstream CNN models revealed that the MobileNetV2-WDC model achieved high-speed(21.92 ms)and accurate(96.86%)grading with minimal model parameters(2.27 M)and size(27 M),meeting the industrial efficiency and practicality requirements.A visual analysis of the model classification errors was conducted,outlining paths for further optimization.This study provides an efficient and accurate solution for detecting and grading surface wear on hot-rolling work rolls,enhancing product quality and extending the lifespan of rolls.展开更多
[Objective] The aim of the research was to identify and assess the genetic characteristics of grading breeding sheep populations in Ba Yan Nur City. [Method] Genetic polymorphism and aggregation of seven sheep populat...[Objective] The aim of the research was to identify and assess the genetic characteristics of grading breeding sheep populations in Ba Yan Nur City. [Method] Genetic polymorphism and aggregation of seven sheep populations, including three breeding sheep populations (breeding F1, F2 and Bamei mutton sheep), three introduced mutton sheep breeds (Texel, Dorset and German Merino sheep) and one local female parent population (Mongolia sheep), were assessed using 10 microsatellite markers. [Result] By cluster analysis, the seven sheep populations can be divided into two groups. The F1 and German Merino sheep were closely related, which were clustered with F2, Bamei mutton sheep and Mongolia sheep to form one group while Texel and Dorset to form another group. The genetic aggregation of the seven breeds was assessed by Bayesian discrimination. And the results show that the genetic aggregation of F1 and F2 were lower while that of Bamei mutton sheep, Texel, Dorset and German Merino sheep were higher. [Conclusion] Better genetic stability has been formed in Bamei mutton sheep.展开更多
Objective The aim was to provide basis for further studies on fruit firmness in peach fruits and the standardization and standardization of peach germplasm resource. [ Method] The analysis of fruit firmness of peach g...Objective The aim was to provide basis for further studies on fruit firmness in peach fruits and the standardization and standardization of peach germplasm resource. [ Method] The analysis of fruit firmness of peach germplasm resource was based on the improved firmness measurement, and the probability grading of characteristics was carried out on peach fruit firmness. [Result] The coefficient of variation of peach fruit firmness with skin was less than that of fruit firmness without skin; the fruit firmness with skin and fruit firmness without skin were both fitted the normal distribution; the probability grading of characteristics were divided into five series based on four points of （X-1. 281 8s）, （X-0. 524 6s）, （X＋0. 524 6s） and （X＋1.281 8s）, so that the probability of 1 -5 were 10%, 20%, 40%, 20% and 10%. [Conclusion] There was more abundant genetic basis in fruit firmness, which held a potential for greater choice.展开更多
Aimed at the remanufacturing system, the effect of the uncertainty of returns＇ quality on bottleneck shifting is investigated. A novel definition of bottleneck station is presented and the probability of a station be...Aimed at the remanufacturing system, the effect of the uncertainty of returns＇ quality on bottleneck shifting is investigated. A novel definition of bottleneck station is presented and the probability of a station becoming a bottleneck is also given. By calculating the effective output, the effective operation time （EOT） and the ratio of EOT of each station, the system＇s current bottleneck of effective output time is determined. By calculating the probability coefficient of variation and index of bottleneck shifting, the quantitative performance of bottleneck shifting is obtained. Discrete event simulation and the experiment design method are adopted to simulate the system, in which the proportion of quality grading, repair rates and process routes are considered. The case study shows that the uncertainty of returns＇ quality greatly increases the probability of bottleneck shifting, and with the increase of the discrete degree of the returns＇ repair rate, the bottleneck shifting phenomenon is more obvious. Furthermore, bottleneck shifting is closely related to the process route of the dominating returns＇ quality grade.展开更多
目的对中医药治疗冠状动脉临界病变的随机对照研究进行系统评价与Meta分析,评价中医药疗效与安全性,并评估现有研究的证据等级。方法计算机检索PubMed、Embase、Cochrane Library、Web of Science、中国知网、中国生物医学文献数据库、...目的对中医药治疗冠状动脉临界病变的随机对照研究进行系统评价与Meta分析,评价中医药疗效与安全性,并评估现有研究的证据等级。方法计算机检索PubMed、Embase、Cochrane Library、Web of Science、中国知网、中国生物医学文献数据库、维普和万方数据库中医药治疗冠状动脉临界病变的随机对照研究,采用Cochrane 5.1.0偏倚风险评估工具进行方法学质量评价,运用RevMan 5.3软件进行Meta分析,运用GRADE(grading of recommendations,assessment,development and evaluation)系统对有统计学意义结局指标的证据质量进行评价。结果最终纳入文献18篇,涉及样本量1799例。结果显示,相较于单纯西医治疗,中西医结合治疗可显著改善中医证候有效率、心绞痛有效率、心电图有效率、西雅图心绞痛量表的各项评分,降低超敏C反应蛋白、白细胞介素-6等炎症因子水平,降低总胆固醇、甘油三酯、低密度脂蛋白胆固醇水平,提升高密度脂蛋白胆固醇水平,降低冠状动脉直径平均狭窄程度,减少平板运动阳性人数,提高左室射血分数,降低主要不良心脏事件发生率。GRADE证据等级评价提示,中医药改善冠状动脉临界病变患者心绞痛症状总有效率、中医证候总有效率、主要不良心脏事件、低密度脂蛋白胆固醇、西雅图心绞痛量表-躯体活动、左室射血分数为高质量证据,其余指标为极低质量、低质量或中等质量证据。结论中医药治疗冠状动脉临界病变具有一定优势,但在证据产出方面还存在较多局限,未来应尽快构建适合中医药临床试验的冠状动脉临界病变核心指标集,开展大样本随机对照研究,为该领域提供更多高质量循证医学证据。展开更多
In order to improve the survival rate of planting seedlings of Phoebe zhen-nan, the grading standard for one-year-old container seedlings of Phoebe zhennan was developed by using cluster analysis. The results showed t...In order to improve the survival rate of planting seedlings of Phoebe zhen-nan, the grading standard for one-year-old container seedlings of Phoebe zhennan was developed by using cluster analysis. The results showed that the quality of Phoebe zhennan container seedlings could be estimated from seedling height and ground diameter. The Phoebe zhennan container seedlings were divided into 3 grades： Grade 1 （seedling height ≥ 38 cm; ground diameter ≥ 0.65 cm）, Grade 2 （31.7 cm ≤ seedling height 〈 38 cm; 0.56 cm ≤ ground diameter 〈 0.65 cm） and Grade 3 （seedling height 〈 31.7 cm; ground diameter 〈 0.56 cm）.展开更多
目的:系统评价培土生金中药联合西医常规疗法治疗支气管哮喘缓解期肺脾两虚证的疗效以及证据质量,为临床决策及疾病指南制订提供循证依据。方法:检索中国知网(CNKI)、万方数据库(Wangfang)、Pubmed、Web of Science等8大中英文数据库,由...目的:系统评价培土生金中药联合西医常规疗法治疗支气管哮喘缓解期肺脾两虚证的疗效以及证据质量,为临床决策及疾病指南制订提供循证依据。方法:检索中国知网(CNKI)、万方数据库(Wangfang)、Pubmed、Web of Science等8大中英文数据库,由2名研究者独立进行文献筛选、信息提取、偏倚风险评估及方法学质量评价,并对纳入研究的总有效率、中医证候积分、第一秒用力呼气容积(FEV1)、第一秒用力呼气容积/用力肺活量(FEV1/FVC)、哮喘控制测试(ACT)评分等结局指标进行Meta分析,最终依照GRADE评估证据质量。结果:共纳入14项研究,合计1263例患者。结果显示:(1)培土生金中药联合常规西医疗法可有效改善患者总有效率,降低患者中医证候积分,改善患者FEV1水平、FEV1/FVC及ACT评分。(2)总有效率证据质量较优,可信度高,其余指标证据质量较低,尚待更多高质量的研究支持以提升证据级别。结论:培土生金中药联合西医常规疗法治疗支气管哮喘缓解期肺脾两虚证优于单用西医常规治疗,且在总有效率上证据质量较高,具有一定的循证学意义。展开更多
文摘Automated grading of dandruff severity is a clinically significant but challenging task due to the inherent ordinal nature of severity levels and the high prevalence of label noise from subjective expert annotations.Standard classification methods fail to address these dual challenges,limiting their real-world performance.In this paper,a novel,three-phase training framework is proposed that learns a robust ordinal classifier directly from noisy labels.The approach synergistically combines a rank-based ordinal regression backbone with a cooperative,semi-supervised learning strategy to dynamically partition the data into clean and noisy subsets.A hybrid training objective is then employed,applying a supervised ordinal loss to the clean set.The noisy set is simultaneously trained using a dualobjective that combines a semi-supervised ordinal loss with a parallel,label-agnostic contrastive loss.This design allows themodel to learn fromthe entire noisy subset while using contrastive learning to mitigate the risk of error propagation frompotentially corrupt supervision.Extensive experiments on a new,large-scale,multi-site clinical dataset validate our approach.Themethod achieves state-of-the-art performance with 80.71%accuracy and a 76.86%F1-score,significantly outperforming existing approaches,including a 2.26%improvement over the strongest baseline method.This work provides not only a robust solution for a practical medical imaging problem but also a generalizable framework for other tasks plagued by noisy ordinal labels.
基金Supported by Beijing Hospitals Authority Youth Programme,No.QML20200505.
文摘BACKGROUND Esophageal squamous cell carcinoma is a major histological subtype of esophageal cancer.Many molecular genetic changes are associated with its occurrence.Raman spectroscopy has become a new method for the early diagnosis of tumors because it can reflect the structures of substances and their changes at the molecular level.AIM To detect alterations in Raman spectral information across different stages of esophageal neoplasia.METHODS Different grades of esophageal lesions were collected,and a total of 360 groups of Raman spectrum data were collected.A 1D-transformer network model was proposed to handle the task of classifying the spectral data of esophageal squamous cell carcinoma.In addition,a deep learning model was applied to visualize the Raman spectral data and interpret their molecular characteristics.RESULTS A comparison among Raman spectral data with different pathological grades and a visual analysis revealed that the Raman peaks with significant differences were concentrated mainly at 1095 cm^(-1)(DNA,symmetric PO,and stretching vibration),1132 cm^(-1)(cytochrome c),1171 cm^(-1)(acetoacetate),1216 cm^(-1)(amide III),and 1315 cm^(-1)(glycerol).A comparison among the training results of different models revealed that the 1Dtransformer network performed best.A 93.30%accuracy value,a 96.65%specificity value,a 93.30%sensitivity value,and a 93.17%F1 score were achieved.CONCLUSION Raman spectroscopy revealed significantly different waveforms for the different stages of esophageal neoplasia.The combination of Raman spectroscopy and deep learning methods could significantly improve the accuracy of classification.
基金supported by the National Natural Science Foundation of China(62272078)the Chongqing Natural Science Foundation(CSTB2023NSCQ-LZX0069).
文摘Dear Editor,This letter proposes an end-to-end feature disentangled Transformer(FDTs)for entanglement-free and semantic feature representation to enable accurate and trustworthy pathology grading of squamous cell carcinoma(SCC).Existing vision transformers(ViTs)can implement representation learning for SCC grading,however,they all adopt the class-patch token fuzzy mapping for pattern prediction probability or window down-sampling to enhance the representation to contextual information.
文摘This study aims to explore the correlation between plasma homocysteine (Hcy) levels and the clinical grading of varicocele (VC) when analyzing the potential pathogenesis of endothelial cells injury by Hcy. A total of 184 VC patients, aged 18–46 years, were included in this study. These patients visited The Second Hospital of Dalian Medical University (Dalian, China), between January 2022 and September 2024. Patients were divided into three groups based on clinical grading: Group A (59 cases, Grade I), Group B (28 cases, Grade II), and Group C (97 cases, Grade III). Additionally, 120 individuals with normal fertility test results during the same period were selected as the control group. Routine blood and biochemical indices were collected from the patients. Differences in clinical indices between groups were compared, and univariate and multivariate linear regression analyses were performed to identify factors associated with clinical grading. The results showed that the median Hcy levels in the control group and in patients with Grade I, II, and III VC were 9.56 (interquartile range [IQR]: 8.66, 14.02) µmol l−1, 11.28 (IQR: 9.71, 14.55) µmol l−1, 11.84 (IQR: 10.14, 15.60) µmol l−1, and 12.27 (IQR: 9.52, 15.40) µmol l−1, respectively. The differences between the four groups were statistically significant (χ2 = 12.41, P = 0.006). Multivariate regression analysis indicated that Hcy is a factor associated with the clinical grading of VC (t = 2.53, P = 0.013). Hcy is associated with the clinical grading and may have clinical value in assessing severity of VC.
基金Funded by the National Natural Science Foundation of China(Nos.U21A20150,51978339,and 52178237)。
文摘In order to clarify the preparation process parameters of manufactured sand,optimize its quality,and analyze the effect of its grading on the microstructure of concrete,the three-dimensional models of jaw crusher,vibrating screen and conveyor belt were established by using SolidWorks 2016 software.Rocky DEM4.5 software was used to simulate the initial crushing,screening,and transportation stages of the manufactured sand preparation process,with Linear Spring Dashpot as the normal contact model and Coulomb as the tangential contact model;furthermore,the key process parameters were defined.The manufactured sand grading model was then proposed,thereby,the influence of the grading of manufactured sand on the distribution of pore structure in concrete and the interfacial transition zone(ITZ)was studied.The experimetal results show that the particle size of granite,after being crushed in the jaw crusher,is primarily concentrated between 80 and 130 mm,with a crushing energy consumption typically below 100000 J.However,certain instances of granite exhibit higher energy consumption due to undergoing multiple crushings within the chamber.At the same time,the granite causes significant wear on the jaw crusher plate.Furthermore,the tilt angle of the vibrating screen should be adjusted to between 10 and 15 degrees,while the layout angle of the conveyor belt needs to be set at 16 degrees.The proposed manufactured sand grading model is feasible,and the pore diameter distribution inside concrete increases with an increase in the fineness modulus of manufactured sand.
基金funded by Princess Nourah bint Abdulrahman University and Researchers Supporting Project number(PNURSP2025R346)Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘Innovation in learning algorithms has made retinal vessel segmentation and automatic grading tech-niques crucial for clinical diagnosis and prevention of diabetic retinopathy.The traditional methods struggle with accuracy and reliability due to multi-scale variations in retinal blood vessels and the complex pathological relationship in fundus images associated with diabetic retinopathy.While the single-modal diabetic retinopathy grading network addresses class imbalance challenges and lesion representation in fundus image data,dual-modal diabetic retinopathy grading methods offer superior performance.However,the scarcity of dual-modal data and the lack of effective feature fusion methods limit their potential due to multi-scale variations.This paper addresses these issues by focusing on multi-scale retinal vessel segmentation,dual feature fusion,data augmentation,and attention-based grading.The proposed model aims to improve comprehensive segmentation for retinal images with varying vessel thicknesses.It employs a dual-branch parallel architecture that integrates a transformer encoder with a convolutional neural network encoder to extract local and global information for synergistic saliency learning.Besides that,the model uses residual structures and attention modules to extract critical lesions,enhancing the accuracy and reliability of diabetic retinopathy grading.To evaluate the efficacy of the proposed approach,this study compared it with other pre-trained publicly open models,ResNet152V2,ConvNext,Efficient Net,DenseNet,and Swin Transform,with the same developmental parameters.All models achieved approximately 85%accuracy with the same image preparation method.However,the proposed approach outperforms and optimizes existing models by achieving an accuracy of 99.17%,99.04%,and 99.24%,on Kaggle APTOS19,IDRiD,and EyePACS datasets,respectively.These results support the model’s utility in helping ophthalmologists diagnose diabetic retinopathy more rapidly and accurately.
基金National Natural Science Foundation of China(61703363,62272284)Shanxi Provincial Basic Research Program(201801D121148)Yuncheng University Research and Innovation Team for Data Mining and Industrial Intelligence Applications(YCXYTD-202402)。
文摘Addressing challenges in accurately detecting persimmon fruit quality in orchards—such as reliance on manual grading,low efficiency,severe foliage obstruction,and subtle differences between quality grades—this paper proposes a lightweight persimmon detection model based on an improved YOLOv8s architecture.First,the Conv layer in the backbone network is replaced with an ADown module to reduce model complexity.Second,MSFAN is introduced in the Neck layer to fully extract texture features from persimmon images,highlighting differences between quality grades.Finally,the Wise-IoU loss function mitigates the impact of low-quality sample data on grading accuracy.The improved model accurately identifies and separates persimmons of varying quality,effectively addressing quality grading detection in complex backgrounds.This provides a viable technical approach for achieving persimmon quality grading detection.
文摘As a paddy—upland rotation system, tobacco—rice rotation hastypical characteristics in the formation and evolution of soil fertility duringthe tobacco season with dry farming and rice season with water cultivation.To scientifically unveil the soil fertility formation process and grade thesoil fertility in tobacco—rice rotation areas, we collected 372 soil samplesfrom 11 tobacco stations (Haotang, Aoquan, Chengjiao, Renyi, Fangyuan,Anping, Huangsha, Taiping, Tushi, Dashiqiao, and Baimangying) in thetypical tobacco—rice rotation areas of Chenzhou and Yongzhou in SouthernHunan. The physical, chemical, and biological indicators of the soil sampleswere measured, and the tobacco and rice yields of each tobacco stationwere investigated. Machine learning was employed to screen the keyindicators influencing the tobacco yield, and a comprehensive numericalanalysis method combining principal component analysis and discriminantanalysis were adopted to cluster the sampling points, analyze their fertilityformation processes, and grade the soil fertility. The results showed thatclay content, available phosphorus, plow layer depth, slit-to-clay ratio, totalnitrogen, basal respiration, and organic carbon were identified as seven keyindicators influencing the tobacco yield. The results of the comprehensivenumerical analysis predicted two main processes involved in the formationof soil fertility in tobacco—rice rotation areas. One was the soil maturationprocess related to soil carbon and nitrogen cycling, and the other was theprocess of changes in soil physical properties such as clay content and slitto-clay ratio. According to the established soil fertility grading methodfor tobacco—rice rotation areas, the soil fertility of 11 tobacco stationswas graded. The results showed that the soil fertility was high in Haotang,Aoquan, Renyi, and Dashiqiao, medium in Huangsha and Tushi, and low inAnping, Baimangying, and Taiping. The tobacco and rice yields confirmedthat this grading standard can be effectively applied to the grading of soilfertility in the tobacco—rice rotation areas in Southern Hunan and canprovide a scientific basis for soil management in tobacco—rice rotation.
基金supported by Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2025R104),Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘One in every eight men in the US is diagnosed with prostate cancer,making it the most common cancer in men.Gleason grading is one of the most essential diagnostic and prognostic factors for planning the treatment of prostate cancer patients.Traditionally,urological pathologists perform the grading by scoring the morphological pattern,known as the Gleason pattern,in histopathology images.However,thismanual grading is highly subjective,suffers intra-and inter-pathologist variability and lacks reproducibility.An automated grading system could be more efficient,with no subjectivity and higher accuracy and reproducibility.Automated methods presented previously failed to achieve sufficient accuracy,lacked reproducibility and depended on high-resolution images such as 40×.This paper proposes an automated Gleason grading method,ProGENET,to accurately predict the grade using low-resolution images such as 10×.This method first divides the patient’s histopathology whole slide image(WSI)into patches.Then,it detects artifacts and tissue-less regions and predicts the patch-wise grade using an ensemble network of CNN and transformer models.The proposed method adapted the International Society of Urological Pathology(ISUP)grading system and achieved 90.8%accuracy in classifying the patches into healthy and Gleason grades 1 through 5 using 10×WSI,outperforming the state-of-the-art accuracy by 27%.Finally,the patient’s grade was determined by combining the patch-wise results.The method was also demonstrated for 4−class grading and binary classification of prostate cancer,achieving 93.0%and 99.6%accuracy,respectively.The reproducibility was over 90%.Since the proposedmethod determined the grades with higher accuracy and reproducibility using low-resolution images,it is more reliable and effective than existing methods and can potentially improve subsequent therapy decisions.
基金Supported by National Key Research and Development Program of China(Grant No.2018YFA0707300)Hebei Natural Science Foundation(Grant No.E2023203260)+1 种基金Scientific and Technological Research Projects of Hebei Higher Education Institutions(Grant No.CXY2024009)Central Government Guide Local Science and Technology Development Fund Project(Grant No.216Z1602G)。
文摘The wear of work rolls significantly affects the production efficiency and product quality.However,existing methods for wear assessment fail to effectively quantify work roll surface wear conditions,thereby affecting the quality control of steel strips and maintenance strategies for rolls.To accurately assess the wear conditions of hot-rolling work rolls,this study initially established an apparatus for capturing high-precision roll surfaces images.Subsequently,a quantitative assessment of common surface wear morphologies was conducted,and a hot-rolling work roll surface wear dataset was constructed.The MobileNetV2 convolutional neural network(CNN),augmented by transfer learning,was employed to develop a MobileNetV2-wear detection and classification(WDC)surface wear grading model.A comparison with mainstream CNN models revealed that the MobileNetV2-WDC model achieved high-speed(21.92 ms)and accurate(96.86%)grading with minimal model parameters(2.27 M)and size(27 M),meeting the industrial efficiency and practicality requirements.A visual analysis of the model classification errors was conducted,outlining paths for further optimization.This study provides an efficient and accurate solution for detecting and grading surface wear on hot-rolling work rolls,enhancing product quality and extending the lifespan of rolls.
基金Supported by Lateral Joint Projects of Inner Mongolia Agricultural University(2006-12)~~
文摘[Objective] The aim of the research was to identify and assess the genetic characteristics of grading breeding sheep populations in Ba Yan Nur City. [Method] Genetic polymorphism and aggregation of seven sheep populations, including three breeding sheep populations (breeding F1, F2 and Bamei mutton sheep), three introduced mutton sheep breeds (Texel, Dorset and German Merino sheep) and one local female parent population (Mongolia sheep), were assessed using 10 microsatellite markers. [Result] By cluster analysis, the seven sheep populations can be divided into two groups. The F1 and German Merino sheep were closely related, which were clustered with F2, Bamei mutton sheep and Mongolia sheep to form one group while Texel and Dorset to form another group. The genetic aggregation of the seven breeds was assessed by Bayesian discrimination. And the results show that the genetic aggregation of F1 and F2 were lower while that of Bamei mutton sheep, Texel, Dorset and German Merino sheep were higher. [Conclusion] Better genetic stability has been formed in Bamei mutton sheep.
基金Supported by National Science and Technology Support Plan Project(2008BAD92B02)the Earmarked Fund for Modern Agro-industryTechnology Research System(nycytx-31-zs-4)~~
文摘Objective The aim was to provide basis for further studies on fruit firmness in peach fruits and the standardization and standardization of peach germplasm resource. [ Method] The analysis of fruit firmness of peach germplasm resource was based on the improved firmness measurement, and the probability grading of characteristics was carried out on peach fruit firmness. [Result] The coefficient of variation of peach fruit firmness with skin was less than that of fruit firmness without skin; the fruit firmness with skin and fruit firmness without skin were both fitted the normal distribution; the probability grading of characteristics were divided into five series based on four points of （X-1. 281 8s）, （X-0. 524 6s）, （X＋0. 524 6s） and （X＋1.281 8s）, so that the probability of 1 -5 were 10%, 20%, 40%, 20% and 10%. [Conclusion] There was more abundant genetic basis in fruit firmness, which held a potential for greater choice.
基金The Program for Special Talent in Six Fields of Jiangsu Province(No.2013ZBZZ-046)the Program of Lanzhou Technology Development(No.2014-1-175)
文摘Aimed at the remanufacturing system, the effect of the uncertainty of returns＇ quality on bottleneck shifting is investigated. A novel definition of bottleneck station is presented and the probability of a station becoming a bottleneck is also given. By calculating the effective output, the effective operation time （EOT） and the ratio of EOT of each station, the system＇s current bottleneck of effective output time is determined. By calculating the probability coefficient of variation and index of bottleneck shifting, the quantitative performance of bottleneck shifting is obtained. Discrete event simulation and the experiment design method are adopted to simulate the system, in which the proportion of quality grading, repair rates and process routes are considered. The case study shows that the uncertainty of returns＇ quality greatly increases the probability of bottleneck shifting, and with the increase of the discrete degree of the returns＇ repair rate, the bottleneck shifting phenomenon is more obvious. Furthermore, bottleneck shifting is closely related to the process route of the dominating returns＇ quality grade.
文摘目的对中医药治疗冠状动脉临界病变的随机对照研究进行系统评价与Meta分析,评价中医药疗效与安全性,并评估现有研究的证据等级。方法计算机检索PubMed、Embase、Cochrane Library、Web of Science、中国知网、中国生物医学文献数据库、维普和万方数据库中医药治疗冠状动脉临界病变的随机对照研究,采用Cochrane 5.1.0偏倚风险评估工具进行方法学质量评价,运用RevMan 5.3软件进行Meta分析,运用GRADE(grading of recommendations,assessment,development and evaluation)系统对有统计学意义结局指标的证据质量进行评价。结果最终纳入文献18篇,涉及样本量1799例。结果显示,相较于单纯西医治疗,中西医结合治疗可显著改善中医证候有效率、心绞痛有效率、心电图有效率、西雅图心绞痛量表的各项评分,降低超敏C反应蛋白、白细胞介素-6等炎症因子水平,降低总胆固醇、甘油三酯、低密度脂蛋白胆固醇水平,提升高密度脂蛋白胆固醇水平,降低冠状动脉直径平均狭窄程度,减少平板运动阳性人数,提高左室射血分数,降低主要不良心脏事件发生率。GRADE证据等级评价提示,中医药改善冠状动脉临界病变患者心绞痛症状总有效率、中医证候总有效率、主要不良心脏事件、低密度脂蛋白胆固醇、西雅图心绞痛量表-躯体活动、左室射血分数为高质量证据,其余指标为极低质量、低质量或中等质量证据。结论中医药治疗冠状动脉临界病变具有一定优势,但在证据产出方面还存在较多局限,未来应尽快构建适合中医药临床试验的冠状动脉临界病变核心指标集,开展大样本随机对照研究,为该领域提供更多高质量循证医学证据。
基金Supported by Forestry Science and Technology Program of Hunan Province(2010-06)~~
文摘In order to improve the survival rate of planting seedlings of Phoebe zhen-nan, the grading standard for one-year-old container seedlings of Phoebe zhennan was developed by using cluster analysis. The results showed that the quality of Phoebe zhennan container seedlings could be estimated from seedling height and ground diameter. The Phoebe zhennan container seedlings were divided into 3 grades： Grade 1 （seedling height ≥ 38 cm; ground diameter ≥ 0.65 cm）, Grade 2 （31.7 cm ≤ seedling height 〈 38 cm; 0.56 cm ≤ ground diameter 〈 0.65 cm） and Grade 3 （seedling height 〈 31.7 cm; ground diameter 〈 0.56 cm）.
文摘目的:系统评价培土生金中药联合西医常规疗法治疗支气管哮喘缓解期肺脾两虚证的疗效以及证据质量,为临床决策及疾病指南制订提供循证依据。方法:检索中国知网(CNKI)、万方数据库(Wangfang)、Pubmed、Web of Science等8大中英文数据库,由2名研究者独立进行文献筛选、信息提取、偏倚风险评估及方法学质量评价,并对纳入研究的总有效率、中医证候积分、第一秒用力呼气容积(FEV1)、第一秒用力呼气容积/用力肺活量(FEV1/FVC)、哮喘控制测试(ACT)评分等结局指标进行Meta分析,最终依照GRADE评估证据质量。结果:共纳入14项研究,合计1263例患者。结果显示:(1)培土生金中药联合常规西医疗法可有效改善患者总有效率,降低患者中医证候积分,改善患者FEV1水平、FEV1/FVC及ACT评分。(2)总有效率证据质量较优,可信度高,其余指标证据质量较低,尚待更多高质量的研究支持以提升证据级别。结论:培土生金中药联合西医常规疗法治疗支气管哮喘缓解期肺脾两虚证优于单用西医常规治疗,且在总有效率上证据质量较高,具有一定的循证学意义。
