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
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
BACKGROUND The optimal approach for managing hepatic hemangioma is controversial.AIM To evaluate a clinical grading system for management of hepatic hemangioma based on our 17-year of single institution experience.MET...BACKGROUND The optimal approach for managing hepatic hemangioma is controversial.AIM To evaluate a clinical grading system for management of hepatic hemangioma based on our 17-year of single institution experience.METHODS A clinical grading system was retrospectively applied to 1171 patients with hepatic hemangioma from January 2002 to December 2018.Patients were classified into four groups based on the clinical grading system and treatment:(1)Observation group with score<4(Obs score<4);(2)Surgical group with score<4(Sur score<4);(3)Observation group with score≥4(Obs score≥4);and(4)Surgical group with score≥4(Sur score≥4).The clinico-pathological index and outcomes were evaluated.RESULTS There were significantly fewer symptomatic patients in surgical groups(Sur score≥4 vs Obs score≥4,P<0.001;Sur score<4 vs Obs score<4,χ^(2)=8.60,P=0.004;Sur score≥4 vs Obs score<4,P<0.001).The patients in Sur score≥4 had a lower rate of in need for intervention and total patients with adverse event than in Obs score≥4(P<0.001;P<0.001).Nevertheless,there was no significant difference in need for intervention and total patients with adverse event between the Sur score<4 and Obs score<4(P>0.05;χ^(2)=1.68,P>0.05).CONCLUSION This clinical grading system appeared as a practical tool for hepatic hemangioma.Surgery can be suggested for patients with a score≥4.For those with<4,follow-up should be proposed.展开更多
A crucial aspect of prostate cancer grading, especially in low- and intermediate-risk cancer, is the accurate identification of Gleason pattern 4 glands, which includes ill-formed or fused glands. However, there is no...A crucial aspect of prostate cancer grading, especially in low- and intermediate-risk cancer, is the accurate identification of Gleason pattern 4 glands, which includes ill-formed or fused glands. However, there is notable inconsistency among pathologists in recognizing these glands, especially when mixed with pattern 3 glands. This inconsistency has significant implications for patient management and treatment decisions. Conversely, the recognition of glomeruloid and cribriform architecture has shown higher reproducibility. Cribriform architecture, in particular, has been linked to the worst prognosis among pattern 4 subtypes. Intraductal carcinoma of the prostate (IDC-P) is also associated with high-grade cancer and poor prognosis. Accurate identification, classification, and tumor size evaluation by pathologists are vital for determining patient treatment. This review emphasizes the importance of prostate cancer grading, highlighting challenges like distinguishing between pattern 3 and pattern 4 and the prognostic implications of cribriform architecture and intraductal proliferations. It also addresses the inherent grading limitations due to interobserver variability and explores the potential of computational pathology to enhance pathologist accuracy and consistency.展开更多
BACKGROUND Accurate condition assessment is critical for improving the prognosis of neonatal respiratory distress syndrome(RDS),but current assessment methods for RDS pose a cumulative risk of harm to neonates.Thus,a ...BACKGROUND Accurate condition assessment is critical for improving the prognosis of neonatal respiratory distress syndrome(RDS),but current assessment methods for RDS pose a cumulative risk of harm to neonates.Thus,a less harmful method for assessing the health of neonates with RDS is needed.AIM To analyze the relationships between pulmonary ultrasonography and respiratory distress scores,oxygenation index,and chest X-ray grade of neonatal RDS to identify predictors of neonatal RDS severity.METHODS This retrospective study analyzed the medical information of 73 neonates with RDS admitted to the neonatal intensive care unit of Liupanshui Maternal and Child Care Service Center between April and December 2022.The pulmonary ultrasonography score,respiratory distress score,oxygenation index,and chest Xray grade of each newborn before and after treatment were collected.Spearman correlation analysis was performed to determine the relationships among these values and neonatal RDS severity.RESULTS The pulmonary ultrasonography score,respiratory distress score,oxygenation index,and chest X-ray RDS grade of the neonates were significantly lower after treatment than before treatment(P<0.05).Spearman correlation analysis showed that before and after treatment,the pulmonary ultrasonography score of neonates with RDS was positively correlated with the respiratory distress score,oxygenation index,and chest X-ray grade(ρ=0.429–0.859,P<0.05).Receiver operating characteristic curve analysis indicated that pulmonary ultrasonography screening effectively predicted the severity of neonatal RDS(area under the curve=0.805–1.000,P<0.05).CONCLUSION The pulmonary ultrasonography score was significantly associated with the neonatal RDS score,oxygenation index,and chest X-ray grade.The pulmonary ultrasonography score was an effective predictor of neonatal RDS severity.展开更多
Peak load and wind energy emission pressure rise more as wind energy penetration keeps growing,which affects the stabilization of the PS(power system).This paper suggests integrated optimal dispatching of thermal powe...Peak load and wind energy emission pressure rise more as wind energy penetration keeps growing,which affects the stabilization of the PS(power system).This paper suggests integrated optimal dispatching of thermal power generators and BESS(battery energy storage system)taking wind energy emission grading punishment and deep peak clipping into consideration.Firstly,in order to minimize wind abandonment,a hierarchical wind abandonment penalty strategy based on fuzzy control is designed and introduced,and the optimal grid-connected power of wind energy is determined as a result of minimizing the peak cutting cost of the system.Secondly,considering BESS and thermal power,the management approach of BESS-assisted virtual peak clipping of thermal power generators is aimed at reducing the degree of deep peak clipping of thermal power generators and optimizing the output of thermal power generators and the charging and discharging power of BESS.Finally,Give an example of how this strategy has been effective in reducing abandonment rates by 0.66% and 7.46% individually for different wind penetration programs,and the daily average can reduce the peak clipping power output of thermal power generators by 42.97 and 72.31 MWh and enhances the effect and economy of system peak clipping.展开更多
Aiming at the industry cyber-physical system(ICPS)where Denial-of-Service(DoS)attacks and actuator failure coexist,the integrated security control problem of ICPS under multi-objective constraints was studied.First,fr...Aiming at the industry cyber-physical system(ICPS)where Denial-of-Service(DoS)attacks and actuator failure coexist,the integrated security control problem of ICPS under multi-objective constraints was studied.First,from the perspective of the defender,according to the differential impact of the system under DoS attacks of different energies,the DoS attacks energy grading detection standard was formulated,and the ICPS comprehensive security control framework was constructed.Secondly,a security transmission strategy based on event triggering was designed.Under the DoS attack energy classification detection mechanism,for large-energy attacks,the method based on time series analysis was considered to predict and compensate for lost data.Therefore,on the basis of passive and elastic response to small energy attacks,the active defense capability against DoS attacks was increased.Then by introducing the conecomplement linearization algorithm,the calculation methods of the state and fault estimation observer and the integrated safety controller were deduced,the goal of DoS attack active and passive hybrid intrusion tolerance and actuator failure active fault tolerance were realized.Finally,a simulation example of a four-capacity water tank system was given to verify the validity of the obtained conclusions.展开更多
Remote sensing images often need to be merged into a larger mosaic image to support analysis on large areas in many applications.However,the performance of the mosaic imagery may be severely restricted if there are ma...Remote sensing images often need to be merged into a larger mosaic image to support analysis on large areas in many applications.However,the performance of the mosaic imagery may be severely restricted if there are many areas with cloud coverage or if these images used for merging have a long-time span.Therefore,this paper proposes a method of image selection for full coverage image(i.e.a mosaic image with no cloud-contaminated pixels)generation.Specifically,a novel High-Frequency-Aware(HFA)-Net based on Swin-Transformer for region quality grading is presented to provide a data basis for image selection.Spatiotemporal constraints are presented to optimize the image selection.In the temporal dimension,the shortest-time-span constraint shortens the time span of the selected images,obviously improving the timeliness of the image selection results(i.e.with a shorter time span).In the spatial dimension,a spatial continuity constraint is proposed to select data with better quality and larger area,thus improving the radiometric continuity of the results.Experiments on the GF-1 images indicate that the proposed method reduces the averages by 76.1%and 38.7%in terms of the shortest time span compared to the Improved Coverage-oriented Retrieval algorithm(MICR)and Retrieval Method based on Grid Compensation(RMGC)methods,respectively.Moreover,the proposed method also reduces the residual cloud amount by an average of 91.2%,89.8%,and 83.4%when compared to the MICR,RMGC,and Pixel-based Time-series Synthesis Method(PTSM)methods,respectively.展开更多
干燥综合征是一种以淋巴细胞增殖及进行性外分泌腺体损伤为特征的自身免疫病,可出现多系统、多脏器受累。目前,关于中西医结合治疗的时机及具体方案尚无可遵循的临床诊疗指南。指南针对最终纳入的临床问题按照“人群(P)、干预(I)、对照...干燥综合征是一种以淋巴细胞增殖及进行性外分泌腺体损伤为特征的自身免疫病,可出现多系统、多脏器受累。目前,关于中西医结合治疗的时机及具体方案尚无可遵循的临床诊疗指南。指南针对最终纳入的临床问题按照“人群(P)、干预(I)、对照(C)、结局(O)”原则检索证据。采用推荐意见分级的评估、制订及评价(grading of recommendations assessment,development and evaluation,GRADE)方法对证据进行分级和质量评价。基于证据等级,考虑疗效、安全性、经济性、患者可接受程度综合权衡后作出推荐强度,采用GRADE网格计票法进行计票,最终形成推荐意见。展开更多
2025年5月,美国血液和生物治疗促进协会(the Association for the Advancement of Blood and Biotherapies,AABB)与国际输血医学指南协作组(the International Collaboration for Transfusion Medicine Guidelines,ICTMG)联合发布新版...2025年5月,美国血液和生物治疗促进协会(the Association for the Advancement of Blood and Biotherapies,AABB)与国际输血医学指南协作组(the International Collaboration for Transfusion Medicine Guidelines,ICTMG)联合发布新版《血小板输注指南》。该指南基于21项随机对照试验(RCT)和13项高质量观察性研究,采用推荐分级的评价、制定与评估系统(the Grading of Recommendations Assessment Development and Evaluation,GRADE)进行证据分析,将“限制性血小板输注策略”确立为核心,旨在推动全球血小板输注实践的规范化与同质化。指南适用范围广泛,涵盖成人、儿童、新生儿等不同群体,包括血液系统疾病患者、干细胞移植患者、围手术期患者、登革热患者及接受有创操作的患者等。指南设置了死亡率(2%)、2~4级出血(20%)、3~4级出血(5%)三类关键结局的最小重要差异(MIDs)阈值,用于证据确定性分级。在重要推荐方面,明确了高度/中度可信的强烈推荐(如化疗或异体干细胞移植的非出血性血小板减少症患者血小板计数<10×10^(9)/L时输注、无严重出血的新生儿消耗性血小板减少症患者计数<25×10^(9)/L时输注、登革热无大出血患者不输注等)及低度/极低度可信的有条件推荐(如自体干细胞移植成人患者有条件不推荐预防性输注、中心静脉置管成人患者计数<10×10^(9)/L时条件性输注等),同时阐述了过敏反应、发热反应、输血相关急性肺损伤(TRALI)等常见血小板输血反应及其风险。该指南通过降低输注阈值、细化风险分层,可减少不必要输注及相关不良反应,缓解血小板资源短缺;未来需进一步补充体外循环、放射介入等领域的循证证据,并探索体外诱导分化血小板、通用工程血小板等技术以优化输血实践。展开更多
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 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.
文摘BACKGROUND The optimal approach for managing hepatic hemangioma is controversial.AIM To evaluate a clinical grading system for management of hepatic hemangioma based on our 17-year of single institution experience.METHODS A clinical grading system was retrospectively applied to 1171 patients with hepatic hemangioma from January 2002 to December 2018.Patients were classified into four groups based on the clinical grading system and treatment:(1)Observation group with score<4(Obs score<4);(2)Surgical group with score<4(Sur score<4);(3)Observation group with score≥4(Obs score≥4);and(4)Surgical group with score≥4(Sur score≥4).The clinico-pathological index and outcomes were evaluated.RESULTS There were significantly fewer symptomatic patients in surgical groups(Sur score≥4 vs Obs score≥4,P<0.001;Sur score<4 vs Obs score<4,χ^(2)=8.60,P=0.004;Sur score≥4 vs Obs score<4,P<0.001).The patients in Sur score≥4 had a lower rate of in need for intervention and total patients with adverse event than in Obs score≥4(P<0.001;P<0.001).Nevertheless,there was no significant difference in need for intervention and total patients with adverse event between the Sur score<4 and Obs score<4(P>0.05;χ^(2)=1.68,P>0.05).CONCLUSION This clinical grading system appeared as a practical tool for hepatic hemangioma.Surgery can be suggested for patients with a score≥4.For those with<4,follow-up should be proposed.
文摘A crucial aspect of prostate cancer grading, especially in low- and intermediate-risk cancer, is the accurate identification of Gleason pattern 4 glands, which includes ill-formed or fused glands. However, there is notable inconsistency among pathologists in recognizing these glands, especially when mixed with pattern 3 glands. This inconsistency has significant implications for patient management and treatment decisions. Conversely, the recognition of glomeruloid and cribriform architecture has shown higher reproducibility. Cribriform architecture, in particular, has been linked to the worst prognosis among pattern 4 subtypes. Intraductal carcinoma of the prostate (IDC-P) is also associated with high-grade cancer and poor prognosis. Accurate identification, classification, and tumor size evaluation by pathologists are vital for determining patient treatment. This review emphasizes the importance of prostate cancer grading, highlighting challenges like distinguishing between pattern 3 and pattern 4 and the prognostic implications of cribriform architecture and intraductal proliferations. It also addresses the inherent grading limitations due to interobserver variability and explores the potential of computational pathology to enhance pathologist accuracy and consistency.
基金Guizhou Provincial Science and Technology Department,Technology Achievement Application and Industrialization Plan,Applied Fundamental Research,No.Qianke Synthetic Fruit[2022]004.
文摘BACKGROUND Accurate condition assessment is critical for improving the prognosis of neonatal respiratory distress syndrome(RDS),but current assessment methods for RDS pose a cumulative risk of harm to neonates.Thus,a less harmful method for assessing the health of neonates with RDS is needed.AIM To analyze the relationships between pulmonary ultrasonography and respiratory distress scores,oxygenation index,and chest X-ray grade of neonatal RDS to identify predictors of neonatal RDS severity.METHODS This retrospective study analyzed the medical information of 73 neonates with RDS admitted to the neonatal intensive care unit of Liupanshui Maternal and Child Care Service Center between April and December 2022.The pulmonary ultrasonography score,respiratory distress score,oxygenation index,and chest Xray grade of each newborn before and after treatment were collected.Spearman correlation analysis was performed to determine the relationships among these values and neonatal RDS severity.RESULTS The pulmonary ultrasonography score,respiratory distress score,oxygenation index,and chest X-ray RDS grade of the neonates were significantly lower after treatment than before treatment(P<0.05).Spearman correlation analysis showed that before and after treatment,the pulmonary ultrasonography score of neonates with RDS was positively correlated with the respiratory distress score,oxygenation index,and chest X-ray grade(ρ=0.429–0.859,P<0.05).Receiver operating characteristic curve analysis indicated that pulmonary ultrasonography screening effectively predicted the severity of neonatal RDS(area under the curve=0.805–1.000,P<0.05).CONCLUSION The pulmonary ultrasonography score was significantly associated with the neonatal RDS score,oxygenation index,and chest X-ray grade.The pulmonary ultrasonography score was an effective predictor of neonatal RDS severity.
基金supported by Jilin Province Higher Education Teaching Reform Research Project in 2021(JLJY202186163419).
文摘Peak load and wind energy emission pressure rise more as wind energy penetration keeps growing,which affects the stabilization of the PS(power system).This paper suggests integrated optimal dispatching of thermal power generators and BESS(battery energy storage system)taking wind energy emission grading punishment and deep peak clipping into consideration.Firstly,in order to minimize wind abandonment,a hierarchical wind abandonment penalty strategy based on fuzzy control is designed and introduced,and the optimal grid-connected power of wind energy is determined as a result of minimizing the peak cutting cost of the system.Secondly,considering BESS and thermal power,the management approach of BESS-assisted virtual peak clipping of thermal power generators is aimed at reducing the degree of deep peak clipping of thermal power generators and optimizing the output of thermal power generators and the charging and discharging power of BESS.Finally,Give an example of how this strategy has been effective in reducing abandonment rates by 0.66% and 7.46% individually for different wind penetration programs,and the daily average can reduce the peak clipping power output of thermal power generators by 42.97 and 72.31 MWh and enhances the effect and economy of system peak clipping.
基金supported by Gansu Higher Education Innovation Fund Project(No.2023B-439)。
文摘Aiming at the industry cyber-physical system(ICPS)where Denial-of-Service(DoS)attacks and actuator failure coexist,the integrated security control problem of ICPS under multi-objective constraints was studied.First,from the perspective of the defender,according to the differential impact of the system under DoS attacks of different energies,the DoS attacks energy grading detection standard was formulated,and the ICPS comprehensive security control framework was constructed.Secondly,a security transmission strategy based on event triggering was designed.Under the DoS attack energy classification detection mechanism,for large-energy attacks,the method based on time series analysis was considered to predict and compensate for lost data.Therefore,on the basis of passive and elastic response to small energy attacks,the active defense capability against DoS attacks was increased.Then by introducing the conecomplement linearization algorithm,the calculation methods of the state and fault estimation observer and the integrated safety controller were deduced,the goal of DoS attack active and passive hybrid intrusion tolerance and actuator failure active fault tolerance were realized.Finally,a simulation example of a four-capacity water tank system was given to verify the validity of the obtained conclusions.
基金supported by the National Natural Science Foundation of China[grant numbers 41971422 and 42090010]the Fundamental Research Funds for the Central Universities,China[grant number 2042022dx0001].
文摘Remote sensing images often need to be merged into a larger mosaic image to support analysis on large areas in many applications.However,the performance of the mosaic imagery may be severely restricted if there are many areas with cloud coverage or if these images used for merging have a long-time span.Therefore,this paper proposes a method of image selection for full coverage image(i.e.a mosaic image with no cloud-contaminated pixels)generation.Specifically,a novel High-Frequency-Aware(HFA)-Net based on Swin-Transformer for region quality grading is presented to provide a data basis for image selection.Spatiotemporal constraints are presented to optimize the image selection.In the temporal dimension,the shortest-time-span constraint shortens the time span of the selected images,obviously improving the timeliness of the image selection results(i.e.with a shorter time span).In the spatial dimension,a spatial continuity constraint is proposed to select data with better quality and larger area,thus improving the radiometric continuity of the results.Experiments on the GF-1 images indicate that the proposed method reduces the averages by 76.1%and 38.7%in terms of the shortest time span compared to the Improved Coverage-oriented Retrieval algorithm(MICR)and Retrieval Method based on Grid Compensation(RMGC)methods,respectively.Moreover,the proposed method also reduces the residual cloud amount by an average of 91.2%,89.8%,and 83.4%when compared to the MICR,RMGC,and Pixel-based Time-series Synthesis Method(PTSM)methods,respectively.
文摘干燥综合征是一种以淋巴细胞增殖及进行性外分泌腺体损伤为特征的自身免疫病,可出现多系统、多脏器受累。目前,关于中西医结合治疗的时机及具体方案尚无可遵循的临床诊疗指南。指南针对最终纳入的临床问题按照“人群(P)、干预(I)、对照(C)、结局(O)”原则检索证据。采用推荐意见分级的评估、制订及评价(grading of recommendations assessment,development and evaluation,GRADE)方法对证据进行分级和质量评价。基于证据等级,考虑疗效、安全性、经济性、患者可接受程度综合权衡后作出推荐强度,采用GRADE网格计票法进行计票,最终形成推荐意见。
文摘2025年5月,美国血液和生物治疗促进协会(the Association for the Advancement of Blood and Biotherapies,AABB)与国际输血医学指南协作组(the International Collaboration for Transfusion Medicine Guidelines,ICTMG)联合发布新版《血小板输注指南》。该指南基于21项随机对照试验(RCT)和13项高质量观察性研究,采用推荐分级的评价、制定与评估系统(the Grading of Recommendations Assessment Development and Evaluation,GRADE)进行证据分析,将“限制性血小板输注策略”确立为核心,旨在推动全球血小板输注实践的规范化与同质化。指南适用范围广泛,涵盖成人、儿童、新生儿等不同群体,包括血液系统疾病患者、干细胞移植患者、围手术期患者、登革热患者及接受有创操作的患者等。指南设置了死亡率(2%)、2~4级出血(20%)、3~4级出血(5%)三类关键结局的最小重要差异(MIDs)阈值,用于证据确定性分级。在重要推荐方面,明确了高度/中度可信的强烈推荐(如化疗或异体干细胞移植的非出血性血小板减少症患者血小板计数<10×10^(9)/L时输注、无严重出血的新生儿消耗性血小板减少症患者计数<25×10^(9)/L时输注、登革热无大出血患者不输注等)及低度/极低度可信的有条件推荐(如自体干细胞移植成人患者有条件不推荐预防性输注、中心静脉置管成人患者计数<10×10^(9)/L时条件性输注等),同时阐述了过敏反应、发热反应、输血相关急性肺损伤(TRALI)等常见血小板输血反应及其风险。该指南通过降低输注阈值、细化风险分层,可减少不必要输注及相关不良反应,缓解血小板资源短缺;未来需进一步补充体外循环、放射介入等领域的循证证据,并探索体外诱导分化血小板、通用工程血小板等技术以优化输血实践。
