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
This paper reports the application of multi-component hydrocracking catalyst grading technology in diesel hydrocracking system to increase naphtha,and studies the influence of catalyst systems with different number of...This paper reports the application of multi-component hydrocracking catalyst grading technology in diesel hydrocracking system to increase naphtha,and studies the influence of catalyst systems with different number of graded beds on the reaction process of diesel hydrocracking.Three hydrocracking catalysts with different physicochemical properties as gradation components,the diesel hydrocracking reaction on catalyst systems of one-component,two-component and three-component graded beds with different loading sequences are carried out and evaluated,respectively.The catalytic mechanism of the multi-component grading system is analyzed.The results show that,with the increase of the number of grading beds,the space velocity of reaction on each catalyst increases,which can effectively control the overreaction process;along the flow direction of feedstock,the loading sequences of catalysts with acidity decreasing and pore properties increasing can satisfy the demand of different catalytic activity for the conversion of reactant with changing composition to naphtha,which has a guiding role in the conversion of feedstock to target products.Therefore,the conversion of diesel,the selectivity and yield of naphtha all increase significantly on the multi-component catalyst system.The research on the grading technology of multi-component catalysts is of great significance to the promotion and application of catalyst systems in various catalytic fields.展开更多
Diabetes problems can lead to an eye disease called Diabetic Retinopathy(DR),which permanently damages the blood vessels in the retina.If not treated early,DR becomes a significant reason for blindness.To identify the...Diabetes problems can lead to an eye disease called Diabetic Retinopathy(DR),which permanently damages the blood vessels in the retina.If not treated early,DR becomes a significant reason for blindness.To identify the DR and determine the stages,medical tests are very labor-intensive,expensive,and timeconsuming.To address the issue,a hybrid deep and machine learning techniquebased autonomous diagnostic system is provided in this paper.Our proposal is based on lesion segmentation of the fundus images based on the LuNet network.Then a Refined Attention Pyramid Network(RAPNet)is used for extracting global and local features.To increase the performance of the classifier,the unique features are selected from the extracted feature set using Aquila Optimizer(AO)algorithm.Finally,the LightGBM model is applied to classify the input image based on the severity.Several investigations have been done to analyze the performance of the proposed framework on three publically available datasets(MESSIDOR,APTOS,and IDRiD)using several performance metrics such as accuracy,precision,recall,and f1-score.The proposed classifier achieves 99.29%,99.35%,and 99.31%accuracy for these three datasets respectively.The outcomes of the experiments demonstrate that the suggested technique is effective for disease identification and reliable DR grading.展开更多
Cataract is the leading cause of visual impairment globally.The scarcity and uneven distribution of ophthalmologists seriously hinder early visual impairment grading for cataract patients in the clin-ic.In this study,...Cataract is the leading cause of visual impairment globally.The scarcity and uneven distribution of ophthalmologists seriously hinder early visual impairment grading for cataract patients in the clin-ic.In this study,a deep learning-based automated grading system of visual impairment in cataract patients is proposed using a multi-scale efficient channel attention convolutional neural network(MECA_CNN).First,the efficient channel attention mechanism is applied in the MECA_CNN to extract multi-scale features of fundus images,which can effectively focus on lesion-related regions.Then,the asymmetric convolutional modules are embedded in the residual unit to reduce the infor-mation loss of fine-grained features in fundus images.In addition,the asymmetric loss function is applied to address the problem of a higher false-negative rate and weak generalization ability caused by the imbalanced dataset.A total of 7299 fundus images derived from two clinical centers are em-ployed to develop and evaluate the MECA_CNN for identifying mild visual impairment caused by cataract(MVICC),moderate to severe visual impairment caused by cataract(MSVICC),and nor-mal sample.The experimental results demonstrate that the MECA_CNN provides clinically meaning-ful performance for visual impairment grading in the internal test dataset:MVICC(accuracy,sensi-tivity,and specificity;91.3%,89.9%,and 92%),MSVICC(93.2%,78.5%,and 96.7%),and normal sample(98.1%,98.0%,and 98.1%).The comparable performance in the external test dataset is achieved,further verifying the effectiveness and generalizability of the MECA_CNN model.This study provides a deep learning-based practical system for the automated grading of visu-al impairment in cataract patients,facilitating the formulation of treatment strategies in a timely man-ner and improving patients’vision prognosis.展开更多
The increasing trend towards independent fruit packaging demands a high appearance quality of individually packed fruits.In this paper,we propose an improved YOLOv5-based model,YOLO-Banana,to effectively grade banana ...The increasing trend towards independent fruit packaging demands a high appearance quality of individually packed fruits.In this paper,we propose an improved YOLOv5-based model,YOLO-Banana,to effectively grade banana appearance quality based on the number of banana defect points.Due to the minor and dense defects on the surface of bananas,existing detection algorithms have poor detection results and high missing rates.To address this,we propose a densitybased spatial clustering of applications with noise(DBSCAN)and K-means fusion clustering method that utilizes refined anchor points to obtain better initial anchor values,thereby enhancing the network’s recognition accuracy.Moreover,the optimized progressive aggregated network(PANet)enables better multi-level feature fusion.Additionally,the non-maximum suppression function is replaced with a weighted non-maximum suppression(weighted NMS)function based on distance intersection over union(DIoU).Experimental results show that the model’s accuracy is improved by 2.3%compared to the original YOLOv5 network model,thereby effectively grading the banana appearance quality.展开更多
To solve inefficient water stress classification of spinach seedlings under complex background,this study proposed an automatic classification method for the water stress level of spinach seedlings based on the N-Mobi...To solve inefficient water stress classification of spinach seedlings under complex background,this study proposed an automatic classification method for the water stress level of spinach seedlings based on the N-MobileNetXt(NCAM+MobileNetXt)network.Firstly,this study recon-structed the Sandglass Block to effectively increase the model accuracy;secondly,this study introduced the group convolution module and a two-dimensional adaptive average pool,which can significantly compress the model parameters and enhance the model robustness separately;finally,this study innovatively proposed the Normalization-based Channel Attention Module(NCAM)to enhance the image features obviously.The experimental results showed that the classification accuracy of N-MobileNetXt model for spinach seedlings under the natural environment reached 90.35%,and the number of parameters was decreased by 66%compared with the original MobileNetXt model.The N-MobileNetXt model was superior to other net-work models such as ShuffleNet and GhostNet in terms of parameters and accuracy of identification.It can provide a theoretical basis and technical support for automatic irrigation.展开更多
For the existing support vector machine, when recognizing more questions, the shortcomings of high computational complexity and low recognition rate under the low SNR are emerged. The characteristic parameter of the s...For the existing support vector machine, when recognizing more questions, the shortcomings of high computational complexity and low recognition rate under the low SNR are emerged. The characteristic parameter of the signal is extracted and optimized by using a clustering algorithm, support vector machine is trained by grading algorithm so as to enhance the rate of convergence, improve the performance of recognition under the low SNR and realize modulation recognition of the signal based on the modulation system of the constellation diagram in this paper. Simulation results show that the average recognition rate based on this algorithm is enhanced over 30% compared with methods that adopting clustering algorithm or support vector machine respectively under the low SNR. The average recognition rate can reach 90% when the SNR is 5 dB, and the method is easy to be achieved so that it has broad application prospect in the modulating recognition.展开更多
Liver biopsy evaluation plays a critical role in management of patients with viral hepatitis C. In patients with acute viral hepatitis, a liver biopsy, though uncommonly performed, helps to rule out other nonviral cau...Liver biopsy evaluation plays a critical role in management of patients with viral hepatitis C. In patients with acute viral hepatitis, a liver biopsy, though uncommonly performed, helps to rule out other nonviral causes of deranged liver function. In chronic viral hepatitis C, it is considered the gold standard in assessment of the degree of necroinflammation and the stage of fibrosis, to help guide treatment and determine prognosis. It also helps rule out any concomitant diseases such as steatohepatitis, hemochromatosis or others. In patients with chronic progressive liver disease with cirrhosis and dominant nodules, a targeted liver biopsy is helpful in differentiating a regenerative nodule from dysplastic nodule or hepatocellular carcinoma. In the setting of transplantation, the liver biopsy helps distinguish recurrent hepatitis C from acute rejection and also is invaluable in the diagnosis of fibrosing cholestatic hepatitis, a rare variant of recurrent hepatitis C. This comprehensive review discusses the entire spectrum of pathologic findings in the course of hepatitis C infection.展开更多
Objective: To investigate histo-pathological distribution and clinico-pathological significance in a large Chinese triple-negative breast cancer(TNBC) patients serials based on the latest understanding of its clinico-...Objective: To investigate histo-pathological distribution and clinico-pathological significance in a large Chinese triple-negative breast cancer(TNBC) patients serials based on the latest understanding of its clinico-pathological diversity, and to provide more information to clinicians to improve precision of individualized treatment of TNBC.Methods: A retrospective analysis was performed on patients with TNBC at Breast Disease Center, Peking University First Hospital between January 2010 and December 2019. Histo-and clinico-pathological characteristics were analyzed by Chi-square test and Student's t-test, and prognoses were calculated using KaplanMeier method and a Cox proportionate hazards model. Bonferroni correction was used to correct for multiple comparison.Results: Conventional type of TNBC(c TNBC) were identified in 73.7% of 582 TNBC, while special type of TNBC(s TNBC) were 26.3%, including 71 apocrine carcinoma, 20 medullary carcinoma, 31 metaplastic carcinoma, 18 invasive lobular carcinoma, 7 invasive micropapillary carcinoma, 5 adenoid cystic carcinoma and 1 acinic cell carcinoma. Compared to s TNBC, c TNBC was associated with high histologic grade(P<0.001) and lower androgen receptor(AR) expression(P<0.001). TNM stage of low-grade c TNBC was significantly lower than that of high-grade c TNBC(P=0.002). Although no significant difference, there was a trend that the rate of 5-year disease-free survival(DFS) and 5-year overall survival(OS) were longer in high-grade c TNBC than in high-grade s TNBC(P=0.091 and 0.518), and were longer in low-grade s TNBC than in high-grade s TNBC(P=0.051 and0.350). Metaplastic carcinomas showed larger tumor size(P=0.008) and higher proliferative Ki67 index(P=0.004)than c TNBCs.Conclusions: Results from our cohort imply that sub-categorization or subtyping and histological grading could be meaningful in pathological evaluation of TNBC, and need to be clarified in more large collections of TNBC.展开更多
Although quality assessment is gaining increasing attention, there is still no consensus on how to define and grade postoperative complications. The absence of a definition and a widely accepted ranking system to clas...Although quality assessment is gaining increasing attention, there is still no consensus on how to define and grade postoperative complications. The absence of a definition and a widely accepted ranking system to classify surgical complications has hampered proper interpretation of the surgical outcome. This study aimed to define and search the simple and reproducible classification of complications following hepatectomy based on two therapy-oriented severity grading system: Clavien-Dindo classification of surgical complications and Accordion severity grading of postoperative complications. Two classifications were tested in a cohort of 2008 patients who underwent elective liver surgery at our institution between January 1986 and December 2005. Univariate and multivariate analyses were performed to link respective complications with perioperative parameters, length of hospital stay and the quality of life. A total of 1716(85.46%) patients did not develop any complication, while 292(14.54%) patients had at least one complication. According to Clavien-Dindo classification of surgical complications system, grade Ⅰ complications occurred in 150 patients(7.47%), grade Ⅱ in 47 patients(2.34%), grade Ⅲa in 59 patients(2.94%), grade Ⅲb in 13 patients(0.65%), grade Ⅳa in 7 patients(0.35%), grade Ⅳb in 1 patient(0.05%), and grade Ⅴ in 15 patients(0.75%). According to Accordion severity grading of postoperative complications system, mild complications occurred in 160 patients(7.97%), moderate complications in 48 patients(2.39%), severe complications(invasive procedure/no general anesthesia) in 48 patients(2.39%), severe complications(invasive procedure under general anesthesia or single organ system failure) in 20 patients(1.00%), severe complications(organ system failure and invasive procedure under general anesthesia or multisystem organ failure) in 1 patient(0.05%), and mortality was 0.75%(n=15). Complication severity of Clavien-Dindo system and Accordion system were all correlated with the length of hospital stay, the number of hepatic segments resected, the blood transfusion and the Hospital Anxiety and Depression Scale-Anxiety(HADS-A). The Clavien-Dindo classification system and Accordion classification system are the simple ways of reporting all complications following the liver surgery.展开更多
BACKGROUND Pancreatic ductal adenocarcinoma(PDA)is a malignancy with a high mortality rate and short survival time.The conventional computed tomography(CT)has been worldwide used as a modality for diagnosis of PDA,as ...BACKGROUND Pancreatic ductal adenocarcinoma(PDA)is a malignancy with a high mortality rate and short survival time.The conventional computed tomography(CT)has been worldwide used as a modality for diagnosis of PDA,as CT enhancement pattern has been thought to be related to tumor angiogenesis and pathologic grade of PDA.AIM To evaluate the relationship between the pathologic grade of pancreatic ductal adenocarcinoma and the enhancement parameters of contrast-enhanced CT.METHODS In this retrospective study,42 patients(Age,mean±SD:62.43±11.42 years)with PDA who underwent surgery after preoperative CT were selected.Two radiologists evaluated the CT images and calculated the value of attenuation at the aorta in the arterial phase and the pancreatic phase(VAarterial and VApancreatic)and of the tumor(VTarterial and VTpancreatic)by finding out four regions of interest.Ratio between the tumor and the aorta enhancement on the arterial phase and the pancreatic phase(TARarterial and TARpancreatic)was figured out through dividing VT arterial by VAarterial and VTpancreatic by VApancreatic.Tumor-to-aortic enhancement fraction(TAF)was expressed as the ratio of the difference between attenuation of the tumor on arterial and parenchymal images to that between attenuation of the aorta on arterial and pancreatic images.The Kruskal-Wallis analysis of variance and Mann-Whitney U test for statistical analysis were used.RESULTS Forty-two PDAs(23 men and 19 women)were divided into three groups:Welldifferentiated(n=13),moderately differentiated(n=21),and poorly differentiated(n=8).TAF differed significantly between the three groups(P=0.034)but TARarterial(P=0.164)and TARpancreatic(P=0.339)did not.The median value of TAF for poorly differentiated PDAs(0.1011;95%CI:0.01100-0.1796)was significantly higher than that for well-differentiated PDAs(0.1941;95%CI:0.1463-0.3194).CONCLUSION Calculation of TAF might be useful in predicting the pathologic grade of PDA.展开更多
AIM:To compare the assessment outcomes of the characteristics of mild to moderate non-proliferative diabetic retinopathy(NPDR) established by fundus photography and fundus fluorescein angiography(FFA).METHODS:The fund...AIM:To compare the assessment outcomes of the characteristics of mild to moderate non-proliferative diabetic retinopathy(NPDR) established by fundus photography and fundus fluorescein angiography(FFA).METHODS:The fundus photos and FFA results of 260 patients with diabetes mellitus were reviewed.Diabetic retinopathy(DR) severity was graded based on the international classification standard.The microaneurysms,hemorrhages,and intraretinal microvascular abnormalities(IRMA) in FFA images of patients with mild to moderate NPDR were observed.The differences between the fundus photos and the FFA results were summarized,analyzed,and compared.RESULTS:The counting of intraretinal hemorrhages identified by FFA revealed that only 9 eyes(1.9%) had more than 20 intraretinal hemorrhages in all four quadrants;15 eyes(3.1%) had more than 20 intraretinal hemorrhages in three quadrants;26 eyes(5.4%) had over 20 intraretinal hemorrhages in two quadrants;and 37 eyes(7.7%) had more than 20 intraretinal hemorrhages in only one quadrant.Furthermore,the number of IRMAs appeared ≥4 in 17 eyes,3 in 35 eyes,2 in 69 eyes,and 1 in 93 eyes.CONCLUSION:FFA has higher detection accuracy of retinal angiopathy than fundus photography.FFA grading results are helpful for timely detection and proper treatment of lesions easily missed by fundus photography.展开更多
Larch wood is structurally classifi ed in many countries as one of conifers with the highest load-bearing capacity(strength class of C30).The Spanish visual classifi cation regulation only assigns a strength class to ...Larch wood is structurally classifi ed in many countries as one of conifers with the highest load-bearing capacity(strength class of C30).The Spanish visual classifi cation regulation only assigns a strength class to 4 pine woods:Laricio pine(Pinus nigra Arn.var.Salzmannii),Silvestre pine(Pinus sylvestris L.),Radiata pine(Pinus radiata D.Don),and Pinaster pine(Pinus pinaster Ait.).This work adds to the number of structurally characterised species by creating a visual classifi cation table for Japanese larch wood(Larix kaempferi(Lamb.)Carr.)which diff erentiates between 2 visual classes,MEG-1 and MEG-2.Characteristic strength values were calculated for each class(fk,MEG-1=31.80 MPa,f k,MEG-2=24.55 MPa),mean module of elasticity(E 0,mean,MEG-1=13,082 MPA,E 0,mean,MEG-2=12,320 MPA)and density(ρk,MEG-1=456.6 kg m−3,ρk,MEG-2=469.1 kg m−3),before fi nally assigning a strength class of C30 to visual class MEG-1,and a strength class of C24 to visual class MEG-2.展开更多
Knee osteoarthritis(OA) is a progressive joint disease hallmarked by cartilage and bone breakdown and associated with changes to all of the tissues in the joint,ultimately causing pain,stiffness,deformity and disabili...Knee osteoarthritis(OA) is a progressive joint disease hallmarked by cartilage and bone breakdown and associated with changes to all of the tissues in the joint,ultimately causing pain,stiffness,deformity and disability in many people.Radiographs are commonly used for the clinical assessment of knee OA incidence and progression,and to assess for risk factors.One risk factor for the incidence and progression of knee OA is malalignment of the lower extremities(LE).The hipknee-ankle(HKA) angle,assessed from a full-length LE radiograph,is ideally used to assess LE alignment.Careful attention to LE positioning is necessary to obtain the most accurate measurement of the HKA angle.Since full-length LE radiographs are not always available,the femoral shaft-tibial shaft(FS-TS) angle may be calculated from a knee radiograph instead.However,the FS-TS angle is more variable than the HKA angle and it should be used with caution.Knee radiographs are used to assess the severity of knee OA and its progression.There are three types of ordinal grading scales for knee OA:global,composite and individual feature scales.Each grade on a global scale describes one or more features of knee OA.The entire description must be met for a specific grade to be assigned.The KellgrenLawrence scale is the most commonly-used global scale.Composite scales grade several features of knee OA individually and sum the grades to create a total score.One example is the compartmental grading scale for knee OA.Composite scales can respond to change in a variety of presentations of knee OA.Individual feature scales assess one or more OA features individually and do not calculate a total score.They are most often used to monitor change in one OA feature,commonly joint space narrowing.The most commonly-used individual feature scale is the OA Research Society International atlas.Each type of scale has its advantages;however,composite scales may offer greater content validity.Responsiveness to change is unknown for most scales and deserves further evaluation.展开更多
In order to improve the performance of the automatic apple grading and sorting system,in this paper,an ensemble model of ordinal classification based on neural network with ordered partitions and Dempster–Shafer theo...In order to improve the performance of the automatic apple grading and sorting system,in this paper,an ensemble model of ordinal classification based on neural network with ordered partitions and Dempster–Shafer theory is proposed.As a non-destructive grading method,apples are graded into three grades based on the Soluble Solids Content value,with features extracted from the preprocessed near-infrared spectrum of apple serving as model inputs.Considering the uncertainty in grading labels,mass generation approach and evidential encoding scheme for ordinal label are proposed,with uncertainty handled within the framework of Dempster–Shafer theory.Constructing neural network with ordered partitions as the base learner,the learning procedure of the Bagging-based ensemble model is detailed.Experiments on Yantai Red Fuji apples demonstrate the satisfactory grading performances of proposed evidential ensemble model for ordinal classification.展开更多
Objective:Histology grade,subtypes and TNM stage of lung adenocarcinomas are useful predictors of prognosis and survival.The aim of the study was to investigate the relationship between chromosomal instability,morphol...Objective:Histology grade,subtypes and TNM stage of lung adenocarcinomas are useful predictors of prognosis and survival.The aim of the study was to investigate the relationship between chromosomal instability,morphological subtypes and the grading system used in lung non-mucinous adenocarcinoma(LNMA).Methods:We developed a whole genome copy number variation(WGCNV)scoring system and applied next generation sequencing to evaluate CNVs present in 91 LNMA tumor samples.Results:Higher histological grades,aggressive subtypes and more advanced TNM staging were associated with an increased WGCNV score,particularly in CNV regions enriched for tumor suppressor genes and oncogenes.In addition,we demonstrate that 24-chromosome CNV profiling can be performed reliably from specific cell types(<100 cells)isolated by sample laser capture microdissection.Conclusions:Our findings suggest that the WGCNV scoring system we developed may have potential value as an adjunct test for predicting the prognosis of patients diagnosed with LNMA.展开更多
In order to objectively and reasonably evaluate the actual and potential value of cultivated land, both social and ecological values are introduced into the classification and grading index system of cultivated land b...In order to objectively and reasonably evaluate the actual and potential value of cultivated land, both social and ecological values are introduced into the classification and grading index system of cultivated land based on the viewpoint of sustainable development, after considering the natural and economic values of cultivated land. Index system construction of the sustainable utilization of cultivated land should follow the principles of economic viability, social acceptability, and ecological protection. Classification of cultivated land should take into account the soil fertility of cultivated land. Then, grading of cultivated land is carried out from the practical productivity (or potential productivity) of cultivated land. According to the existing classification index system of cultivated land, the soil, natural and environmental factors in plains, mountains and hills are mainly modified in the classification index system of cultivated land. And index systems for the cultivated land classification in plains, mountains and hills are set up. The grading index system of cultivated land is established based on the economic viability (economic value), social acceptability (social value) and protection of cultivated land (ecological value). Quantitative expression of cultivated land grading index is also carried out.展开更多
Taking Fengkai County of Guangdong Province as an example of the application of GIS technology in farmland grading.The application of GIS in farmland grading is discussed in order to provide a professional and high-ef...Taking Fengkai County of Guangdong Province as an example of the application of GIS technology in farmland grading.The application of GIS in farmland grading is discussed in order to provide a professional and high-efficient method to complete the work.The function of space analysis of MAPGIS software shows advantages in speed and precision and is regarded as a new way of farmland grading.展开更多
This paper proposes a novel grading method of apples,in an automated grading device that uses convolutional neural networks to extract the size,color,texture,and roundness of an apple.The developed machine learning me...This paper proposes a novel grading method of apples,in an automated grading device that uses convolutional neural networks to extract the size,color,texture,and roundness of an apple.The developed machine learning method uses the ability of learning representative features by means of a convolutional neural network(CNN),to determine suitable features of apples for the grading process.This information is fed into a one-to-one classifier that uses a support vector machine(SVM),instead of the softmax output layer of the CNN.In this manner,Yantai apples with similar shapes and low discrimination are graded using four different approaches.The fusion model using both CNN and SVM classifiers is much more accurate than the simple k-nearest neighbor(KNN),SVM,and CNN model when used separately for grading,and the learning ability and the generalization ability of the model is correspondingly increased by the combined method.Grading tests are carried out using the automated grading device that is developed in the present work.It is verified that the actual effect of apple grading using the combined CNN-SVM model is fast and accurate,which greatly reduces the manpower and labor costs of manual grading,and has important commercial prospects.展开更多
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National Key R&D Program of China(2021YFA1501203)is acknowledged for financial support.
文摘This paper reports the application of multi-component hydrocracking catalyst grading technology in diesel hydrocracking system to increase naphtha,and studies the influence of catalyst systems with different number of graded beds on the reaction process of diesel hydrocracking.Three hydrocracking catalysts with different physicochemical properties as gradation components,the diesel hydrocracking reaction on catalyst systems of one-component,two-component and three-component graded beds with different loading sequences are carried out and evaluated,respectively.The catalytic mechanism of the multi-component grading system is analyzed.The results show that,with the increase of the number of grading beds,the space velocity of reaction on each catalyst increases,which can effectively control the overreaction process;along the flow direction of feedstock,the loading sequences of catalysts with acidity decreasing and pore properties increasing can satisfy the demand of different catalytic activity for the conversion of reactant with changing composition to naphtha,which has a guiding role in the conversion of feedstock to target products.Therefore,the conversion of diesel,the selectivity and yield of naphtha all increase significantly on the multi-component catalyst system.The research on the grading technology of multi-component catalysts is of great significance to the promotion and application of catalyst systems in various catalytic fields.
文摘Diabetes problems can lead to an eye disease called Diabetic Retinopathy(DR),which permanently damages the blood vessels in the retina.If not treated early,DR becomes a significant reason for blindness.To identify the DR and determine the stages,medical tests are very labor-intensive,expensive,and timeconsuming.To address the issue,a hybrid deep and machine learning techniquebased autonomous diagnostic system is provided in this paper.Our proposal is based on lesion segmentation of the fundus images based on the LuNet network.Then a Refined Attention Pyramid Network(RAPNet)is used for extracting global and local features.To increase the performance of the classifier,the unique features are selected from the extracted feature set using Aquila Optimizer(AO)algorithm.Finally,the LightGBM model is applied to classify the input image based on the severity.Several investigations have been done to analyze the performance of the proposed framework on three publically available datasets(MESSIDOR,APTOS,and IDRiD)using several performance metrics such as accuracy,precision,recall,and f1-score.The proposed classifier achieves 99.29%,99.35%,and 99.31%accuracy for these three datasets respectively.The outcomes of the experiments demonstrate that the suggested technique is effective for disease identification and reliable DR grading.
基金the National Natural Science Foundation of China(No.62276210,82201148,61775180)the Natural Science Basic Research Program of Shaanxi Province(No.2022JM-380)+3 种基金the Shaanxi Province College Students'Innovation and Entrepreneurship Training Program(No.S202311664128X)the Natural Science Foundation of Zhejiang Province(No.LQ22H120002)the Medical Health Science and Technology Project of Zhejiang Province(No.2022RC069,2023KY1140)the Natural Science Foundation of Ningbo(No.2023J390)。
文摘Cataract is the leading cause of visual impairment globally.The scarcity and uneven distribution of ophthalmologists seriously hinder early visual impairment grading for cataract patients in the clin-ic.In this study,a deep learning-based automated grading system of visual impairment in cataract patients is proposed using a multi-scale efficient channel attention convolutional neural network(MECA_CNN).First,the efficient channel attention mechanism is applied in the MECA_CNN to extract multi-scale features of fundus images,which can effectively focus on lesion-related regions.Then,the asymmetric convolutional modules are embedded in the residual unit to reduce the infor-mation loss of fine-grained features in fundus images.In addition,the asymmetric loss function is applied to address the problem of a higher false-negative rate and weak generalization ability caused by the imbalanced dataset.A total of 7299 fundus images derived from two clinical centers are em-ployed to develop and evaluate the MECA_CNN for identifying mild visual impairment caused by cataract(MVICC),moderate to severe visual impairment caused by cataract(MSVICC),and nor-mal sample.The experimental results demonstrate that the MECA_CNN provides clinically meaning-ful performance for visual impairment grading in the internal test dataset:MVICC(accuracy,sensi-tivity,and specificity;91.3%,89.9%,and 92%),MSVICC(93.2%,78.5%,and 96.7%),and normal sample(98.1%,98.0%,and 98.1%).The comparable performance in the external test dataset is achieved,further verifying the effectiveness and generalizability of the MECA_CNN model.This study provides a deep learning-based practical system for the automated grading of visu-al impairment in cataract patients,facilitating the formulation of treatment strategies in a timely man-ner and improving patients’vision prognosis.
基金supported by the Beijing Science Foundation(No.9232005)the Beijing Municipal Philosophy and Social Science Foundation of China(No.19GLB036)the Beijing Science and Technology Project(No.Z221100005822014)。
文摘The increasing trend towards independent fruit packaging demands a high appearance quality of individually packed fruits.In this paper,we propose an improved YOLOv5-based model,YOLO-Banana,to effectively grade banana appearance quality based on the number of banana defect points.Due to the minor and dense defects on the surface of bananas,existing detection algorithms have poor detection results and high missing rates.To address this,we propose a densitybased spatial clustering of applications with noise(DBSCAN)and K-means fusion clustering method that utilizes refined anchor points to obtain better initial anchor values,thereby enhancing the network’s recognition accuracy.Moreover,the optimized progressive aggregated network(PANet)enables better multi-level feature fusion.Additionally,the non-maximum suppression function is replaced with a weighted non-maximum suppression(weighted NMS)function based on distance intersection over union(DIoU).Experimental results show that the model’s accuracy is improved by 2.3%compared to the original YOLOv5 network model,thereby effectively grading the banana appearance quality.
基金supported in part by the Science and Technology Development Plan Project of Changchun[Grant Number 21ZGN28]the Jilin Provincial Science and Technology Development Plan Project[Grant Number 20210101157JC]the Jilin Provincial Science and Technology Development Plan Project[Grant Number 20230202035NC].
文摘To solve inefficient water stress classification of spinach seedlings under complex background,this study proposed an automatic classification method for the water stress level of spinach seedlings based on the N-MobileNetXt(NCAM+MobileNetXt)network.Firstly,this study recon-structed the Sandglass Block to effectively increase the model accuracy;secondly,this study introduced the group convolution module and a two-dimensional adaptive average pool,which can significantly compress the model parameters and enhance the model robustness separately;finally,this study innovatively proposed the Normalization-based Channel Attention Module(NCAM)to enhance the image features obviously.The experimental results showed that the classification accuracy of N-MobileNetXt model for spinach seedlings under the natural environment reached 90.35%,and the number of parameters was decreased by 66%compared with the original MobileNetXt model.The N-MobileNetXt model was superior to other net-work models such as ShuffleNet and GhostNet in terms of parameters and accuracy of identification.It can provide a theoretical basis and technical support for automatic irrigation.
基金supported in part by the National Natural Science Foundation of China under Grand No.61871129 and No.61301179Projects of Science and Technology Plan Guangdong Province under Grand No.2014A010101284
文摘For the existing support vector machine, when recognizing more questions, the shortcomings of high computational complexity and low recognition rate under the low SNR are emerged. The characteristic parameter of the signal is extracted and optimized by using a clustering algorithm, support vector machine is trained by grading algorithm so as to enhance the rate of convergence, improve the performance of recognition under the low SNR and realize modulation recognition of the signal based on the modulation system of the constellation diagram in this paper. Simulation results show that the average recognition rate based on this algorithm is enhanced over 30% compared with methods that adopting clustering algorithm or support vector machine respectively under the low SNR. The average recognition rate can reach 90% when the SNR is 5 dB, and the method is easy to be achieved so that it has broad application prospect in the modulating recognition.
文摘Liver biopsy evaluation plays a critical role in management of patients with viral hepatitis C. In patients with acute viral hepatitis, a liver biopsy, though uncommonly performed, helps to rule out other nonviral causes of deranged liver function. In chronic viral hepatitis C, it is considered the gold standard in assessment of the degree of necroinflammation and the stage of fibrosis, to help guide treatment and determine prognosis. It also helps rule out any concomitant diseases such as steatohepatitis, hemochromatosis or others. In patients with chronic progressive liver disease with cirrhosis and dominant nodules, a targeted liver biopsy is helpful in differentiating a regenerative nodule from dysplastic nodule or hepatocellular carcinoma. In the setting of transplantation, the liver biopsy helps distinguish recurrent hepatitis C from acute rejection and also is invaluable in the diagnosis of fibrosing cholestatic hepatitis, a rare variant of recurrent hepatitis C. This comprehensive review discusses the entire spectrum of pathologic findings in the course of hepatitis C infection.
基金supported by the National Key R&D Program of China (No.2016YFC0901302)。
文摘Objective: To investigate histo-pathological distribution and clinico-pathological significance in a large Chinese triple-negative breast cancer(TNBC) patients serials based on the latest understanding of its clinico-pathological diversity, and to provide more information to clinicians to improve precision of individualized treatment of TNBC.Methods: A retrospective analysis was performed on patients with TNBC at Breast Disease Center, Peking University First Hospital between January 2010 and December 2019. Histo-and clinico-pathological characteristics were analyzed by Chi-square test and Student's t-test, and prognoses were calculated using KaplanMeier method and a Cox proportionate hazards model. Bonferroni correction was used to correct for multiple comparison.Results: Conventional type of TNBC(c TNBC) were identified in 73.7% of 582 TNBC, while special type of TNBC(s TNBC) were 26.3%, including 71 apocrine carcinoma, 20 medullary carcinoma, 31 metaplastic carcinoma, 18 invasive lobular carcinoma, 7 invasive micropapillary carcinoma, 5 adenoid cystic carcinoma and 1 acinic cell carcinoma. Compared to s TNBC, c TNBC was associated with high histologic grade(P<0.001) and lower androgen receptor(AR) expression(P<0.001). TNM stage of low-grade c TNBC was significantly lower than that of high-grade c TNBC(P=0.002). Although no significant difference, there was a trend that the rate of 5-year disease-free survival(DFS) and 5-year overall survival(OS) were longer in high-grade c TNBC than in high-grade s TNBC(P=0.091 and 0.518), and were longer in low-grade s TNBC than in high-grade s TNBC(P=0.051 and0.350). Metaplastic carcinomas showed larger tumor size(P=0.008) and higher proliferative Ki67 index(P=0.004)than c TNBCs.Conclusions: Results from our cohort imply that sub-categorization or subtyping and histological grading could be meaningful in pathological evaluation of TNBC, and need to be clarified in more large collections of TNBC.
文摘Although quality assessment is gaining increasing attention, there is still no consensus on how to define and grade postoperative complications. The absence of a definition and a widely accepted ranking system to classify surgical complications has hampered proper interpretation of the surgical outcome. This study aimed to define and search the simple and reproducible classification of complications following hepatectomy based on two therapy-oriented severity grading system: Clavien-Dindo classification of surgical complications and Accordion severity grading of postoperative complications. Two classifications were tested in a cohort of 2008 patients who underwent elective liver surgery at our institution between January 1986 and December 2005. Univariate and multivariate analyses were performed to link respective complications with perioperative parameters, length of hospital stay and the quality of life. A total of 1716(85.46%) patients did not develop any complication, while 292(14.54%) patients had at least one complication. According to Clavien-Dindo classification of surgical complications system, grade Ⅰ complications occurred in 150 patients(7.47%), grade Ⅱ in 47 patients(2.34%), grade Ⅲa in 59 patients(2.94%), grade Ⅲb in 13 patients(0.65%), grade Ⅳa in 7 patients(0.35%), grade Ⅳb in 1 patient(0.05%), and grade Ⅴ in 15 patients(0.75%). According to Accordion severity grading of postoperative complications system, mild complications occurred in 160 patients(7.97%), moderate complications in 48 patients(2.39%), severe complications(invasive procedure/no general anesthesia) in 48 patients(2.39%), severe complications(invasive procedure under general anesthesia or single organ system failure) in 20 patients(1.00%), severe complications(organ system failure and invasive procedure under general anesthesia or multisystem organ failure) in 1 patient(0.05%), and mortality was 0.75%(n=15). Complication severity of Clavien-Dindo system and Accordion system were all correlated with the length of hospital stay, the number of hepatic segments resected, the blood transfusion and the Hospital Anxiety and Depression Scale-Anxiety(HADS-A). The Clavien-Dindo classification system and Accordion classification system are the simple ways of reporting all complications following the liver surgery.
文摘BACKGROUND Pancreatic ductal adenocarcinoma(PDA)is a malignancy with a high mortality rate and short survival time.The conventional computed tomography(CT)has been worldwide used as a modality for diagnosis of PDA,as CT enhancement pattern has been thought to be related to tumor angiogenesis and pathologic grade of PDA.AIM To evaluate the relationship between the pathologic grade of pancreatic ductal adenocarcinoma and the enhancement parameters of contrast-enhanced CT.METHODS In this retrospective study,42 patients(Age,mean±SD:62.43±11.42 years)with PDA who underwent surgery after preoperative CT were selected.Two radiologists evaluated the CT images and calculated the value of attenuation at the aorta in the arterial phase and the pancreatic phase(VAarterial and VApancreatic)and of the tumor(VTarterial and VTpancreatic)by finding out four regions of interest.Ratio between the tumor and the aorta enhancement on the arterial phase and the pancreatic phase(TARarterial and TARpancreatic)was figured out through dividing VT arterial by VAarterial and VTpancreatic by VApancreatic.Tumor-to-aortic enhancement fraction(TAF)was expressed as the ratio of the difference between attenuation of the tumor on arterial and parenchymal images to that between attenuation of the aorta on arterial and pancreatic images.The Kruskal-Wallis analysis of variance and Mann-Whitney U test for statistical analysis were used.RESULTS Forty-two PDAs(23 men and 19 women)were divided into three groups:Welldifferentiated(n=13),moderately differentiated(n=21),and poorly differentiated(n=8).TAF differed significantly between the three groups(P=0.034)but TARarterial(P=0.164)and TARpancreatic(P=0.339)did not.The median value of TAF for poorly differentiated PDAs(0.1011;95%CI:0.01100-0.1796)was significantly higher than that for well-differentiated PDAs(0.1941;95%CI:0.1463-0.3194).CONCLUSION Calculation of TAF might be useful in predicting the pathologic grade of PDA.
基金Supported by National Natural Science Foundation of China (No.U20A20363,No.81970776,No.81671844)Special Fund of the Academy of Medical Sciences of Heilongjiang Province for Scientific Research (No.CR201809)+2 种基金Natural Science Foundation of Heilongjiang Province,China (No.LH2020H039)Higher Education Reform Project of Heilongjiang Province,China (No.SJGY20180332)Heilongjiang Provincial Postdoctoral Research Fund (No.LBH-Z18221)。
文摘AIM:To compare the assessment outcomes of the characteristics of mild to moderate non-proliferative diabetic retinopathy(NPDR) established by fundus photography and fundus fluorescein angiography(FFA).METHODS:The fundus photos and FFA results of 260 patients with diabetes mellitus were reviewed.Diabetic retinopathy(DR) severity was graded based on the international classification standard.The microaneurysms,hemorrhages,and intraretinal microvascular abnormalities(IRMA) in FFA images of patients with mild to moderate NPDR were observed.The differences between the fundus photos and the FFA results were summarized,analyzed,and compared.RESULTS:The counting of intraretinal hemorrhages identified by FFA revealed that only 9 eyes(1.9%) had more than 20 intraretinal hemorrhages in all four quadrants;15 eyes(3.1%) had more than 20 intraretinal hemorrhages in three quadrants;26 eyes(5.4%) had over 20 intraretinal hemorrhages in two quadrants;and 37 eyes(7.7%) had more than 20 intraretinal hemorrhages in only one quadrant.Furthermore,the number of IRMAs appeared ≥4 in 17 eyes,3 in 35 eyes,2 in 69 eyes,and 1 in 93 eyes.CONCLUSION:FFA has higher detection accuracy of retinal angiopathy than fundus photography.FFA grading results are helpful for timely detection and proper treatment of lesions easily missed by fundus photography.
基金We thanks to Basque centre of research and applied innovation in vet(TKNIKA),Centre for services and promotion of Castilla y León forestry and its industry(CESEFOR),D.Bixente Dorronsoro,Gipuzkoa provincial council,and Commercial services of the wood of Guipuzkoa(SECOMA).Larranaga sawmill(Azpeitia).
文摘Larch wood is structurally classifi ed in many countries as one of conifers with the highest load-bearing capacity(strength class of C30).The Spanish visual classifi cation regulation only assigns a strength class to 4 pine woods:Laricio pine(Pinus nigra Arn.var.Salzmannii),Silvestre pine(Pinus sylvestris L.),Radiata pine(Pinus radiata D.Don),and Pinaster pine(Pinus pinaster Ait.).This work adds to the number of structurally characterised species by creating a visual classifi cation table for Japanese larch wood(Larix kaempferi(Lamb.)Carr.)which diff erentiates between 2 visual classes,MEG-1 and MEG-2.Characteristic strength values were calculated for each class(fk,MEG-1=31.80 MPa,f k,MEG-2=24.55 MPa),mean module of elasticity(E 0,mean,MEG-1=13,082 MPA,E 0,mean,MEG-2=12,320 MPA)and density(ρk,MEG-1=456.6 kg m−3,ρk,MEG-2=469.1 kg m−3),before fi nally assigning a strength class of C30 to visual class MEG-1,and a strength class of C24 to visual class MEG-2.
文摘Knee osteoarthritis(OA) is a progressive joint disease hallmarked by cartilage and bone breakdown and associated with changes to all of the tissues in the joint,ultimately causing pain,stiffness,deformity and disability in many people.Radiographs are commonly used for the clinical assessment of knee OA incidence and progression,and to assess for risk factors.One risk factor for the incidence and progression of knee OA is malalignment of the lower extremities(LE).The hipknee-ankle(HKA) angle,assessed from a full-length LE radiograph,is ideally used to assess LE alignment.Careful attention to LE positioning is necessary to obtain the most accurate measurement of the HKA angle.Since full-length LE radiographs are not always available,the femoral shaft-tibial shaft(FS-TS) angle may be calculated from a knee radiograph instead.However,the FS-TS angle is more variable than the HKA angle and it should be used with caution.Knee radiographs are used to assess the severity of knee OA and its progression.There are three types of ordinal grading scales for knee OA:global,composite and individual feature scales.Each grade on a global scale describes one or more features of knee OA.The entire description must be met for a specific grade to be assigned.The KellgrenLawrence scale is the most commonly-used global scale.Composite scales grade several features of knee OA individually and sum the grades to create a total score.One example is the compartmental grading scale for knee OA.Composite scales can respond to change in a variety of presentations of knee OA.Individual feature scales assess one or more OA features individually and do not calculate a total score.They are most often used to monitor change in one OA feature,commonly joint space narrowing.The most commonly-used individual feature scale is the OA Research Society International atlas.Each type of scale has its advantages;however,composite scales may offer greater content validity.Responsiveness to change is unknown for most scales and deserves further evaluation.
基金Natural Science Foundation of Shandong Province,Grant/Award Numbers:ZR2021MF074,ZR2020KF027,ZR2020MF067the National Key R&D Program of China,Grant/Award Number:2018AAA0101703。
文摘In order to improve the performance of the automatic apple grading and sorting system,in this paper,an ensemble model of ordinal classification based on neural network with ordered partitions and Dempster–Shafer theory is proposed.As a non-destructive grading method,apples are graded into three grades based on the Soluble Solids Content value,with features extracted from the preprocessed near-infrared spectrum of apple serving as model inputs.Considering the uncertainty in grading labels,mass generation approach and evidential encoding scheme for ordinal label are proposed,with uncertainty handled within the framework of Dempster–Shafer theory.Constructing neural network with ordered partitions as the base learner,the learning procedure of the Bagging-based ensemble model is detailed.Experiments on Yantai Red Fuji apples demonstrate the satisfactory grading performances of proposed evidential ensemble model for ordinal classification.
基金grants from Beijing Hospital Key Research Program(121 Research Program,No.BJ2019-195)。
文摘Objective:Histology grade,subtypes and TNM stage of lung adenocarcinomas are useful predictors of prognosis and survival.The aim of the study was to investigate the relationship between chromosomal instability,morphological subtypes and the grading system used in lung non-mucinous adenocarcinoma(LNMA).Methods:We developed a whole genome copy number variation(WGCNV)scoring system and applied next generation sequencing to evaluate CNVs present in 91 LNMA tumor samples.Results:Higher histological grades,aggressive subtypes and more advanced TNM staging were associated with an increased WGCNV score,particularly in CNV regions enriched for tumor suppressor genes and oncogenes.In addition,we demonstrate that 24-chromosome CNV profiling can be performed reliably from specific cell types(<100 cells)isolated by sample laser capture microdissection.Conclusions:Our findings suggest that the WGCNV scoring system we developed may have potential value as an adjunct test for predicting the prognosis of patients diagnosed with LNMA.
基金Supported by the Key Project of Chinese Ministry of Education ( 108098)the National Natural Science Foundation of China ( 40671078,40771088)the Dangui Plan of Huazhong Normal University
文摘In order to objectively and reasonably evaluate the actual and potential value of cultivated land, both social and ecological values are introduced into the classification and grading index system of cultivated land based on the viewpoint of sustainable development, after considering the natural and economic values of cultivated land. Index system construction of the sustainable utilization of cultivated land should follow the principles of economic viability, social acceptability, and ecological protection. Classification of cultivated land should take into account the soil fertility of cultivated land. Then, grading of cultivated land is carried out from the practical productivity (or potential productivity) of cultivated land. According to the existing classification index system of cultivated land, the soil, natural and environmental factors in plains, mountains and hills are mainly modified in the classification index system of cultivated land. And index systems for the cultivated land classification in plains, mountains and hills are set up. The grading index system of cultivated land is established based on the economic viability (economic value), social acceptability (social value) and protection of cultivated land (ecological value). Quantitative expression of cultivated land grading index is also carried out.
文摘Taking Fengkai County of Guangdong Province as an example of the application of GIS technology in farmland grading.The application of GIS in farmland grading is discussed in order to provide a professional and high-efficient method to complete the work.The function of space analysis of MAPGIS software shows advantages in speed and precision and is regarded as a new way of farmland grading.
文摘This paper proposes a novel grading method of apples,in an automated grading device that uses convolutional neural networks to extract the size,color,texture,and roundness of an apple.The developed machine learning method uses the ability of learning representative features by means of a convolutional neural network(CNN),to determine suitable features of apples for the grading process.This information is fed into a one-to-one classifier that uses a support vector machine(SVM),instead of the softmax output layer of the CNN.In this manner,Yantai apples with similar shapes and low discrimination are graded using four different approaches.The fusion model using both CNN and SVM classifiers is much more accurate than the simple k-nearest neighbor(KNN),SVM,and CNN model when used separately for grading,and the learning ability and the generalization ability of the model is correspondingly increased by the combined method.Grading tests are carried out using the automated grading device that is developed in the present work.It is verified that the actual effect of apple grading using the combined CNN-SVM model is fast and accurate,which greatly reduces the manpower and labor costs of manual grading,and has important commercial prospects.
