Accurate capacity and State of Charge(SOC)estimation are crucial for ensuring the safety and longevity of lithium-ion batteries in electric vehicles.This study examines ten machine learning architectures,Including Dee...Accurate capacity and State of Charge(SOC)estimation are crucial for ensuring the safety and longevity of lithium-ion batteries in electric vehicles.This study examines ten machine learning architectures,Including Deep Belief Network(DBN),Bidirectional Recurrent Neural Network(BiDirRNN),Gated Recurrent Unit(GRU),and others using the NASA B0005 dataset of 591,458 instances.Results indicate that DBN excels in capacity estimation,achieving orders-of-magnitude lower error values and explaining over 99.97%of the predicted variable’s variance.When computational efficiency is paramount,the Deep Neural Network(DNN)offers a strong alternative,delivering near-competitive accuracy with significantly reduced prediction times.The GRU achieves the best overall performance for SOC estimation,attaining an R^(2) of 0.9999,while the BiDirRNN provides a marginally lower error at a slightly higher computational speed.In contrast,Convolutional Neural Networks(CNN)and Radial Basis Function Networks(RBFN)exhibit relatively high error rates,making them less viable for real-world battery management.Analyses of error distributions reveal that the top-performing models cluster most predictions within tight bounds,limiting the risk of overcharging or deep discharging.These findings highlight the trade-off between accuracy and computational overhead,offering valuable guidance for battery management system(BMS)designers seeking optimal performance under constrained resources.Future work may further explore advanced data augmentation and domain adaptation techniques to enhance these models’robustness in diverse operating conditions.展开更多
In this paper,we establish and study a single-species logistic model with impulsive age-selective harvesting.First,we prove the ultimate boundedness of the solutions of the system.Then,we obtain conditions for the asy...In this paper,we establish and study a single-species logistic model with impulsive age-selective harvesting.First,we prove the ultimate boundedness of the solutions of the system.Then,we obtain conditions for the asymptotic stability of the trivial solution and the positive periodic solution.Finally,numerical simulations are presented to validate our results.Our results show that age-selective harvesting is more conducive to sustainable population survival than non-age-selective harvesting.展开更多
Monitoring,understanding and predicting Origin-destination(OD)flows in a city is an important problem for city planning and human activity.Taxi-GPS traces,acted as one kind of typical crowd sensed data,it can be used ...Monitoring,understanding and predicting Origin-destination(OD)flows in a city is an important problem for city planning and human activity.Taxi-GPS traces,acted as one kind of typical crowd sensed data,it can be used to mine the semantics of OD flows.In this paper,we firstly construct and analyze a complex network of OD flows based on large-scale GPS taxi traces of a city in China.The spatiotemporal analysis for the OD flows complex network showed that there were distinctive patterns in OD flows.Then based on a novel complex network model,a semantics mining method of OD flows is proposed through compounding Points of Interests(POI)network and public transport network to the OD flows network.The propose method would offer a novel way to predict the location characteristic and future traffic conditions accurately.展开更多
Power quality is a crucial area of research in contemporary power systems,particularly given the rapid proliferation of intermittent renewable energy sources such as wind power.This study investigated the relationship...Power quality is a crucial area of research in contemporary power systems,particularly given the rapid proliferation of intermittent renewable energy sources such as wind power.This study investigated the relationships between power quality indices of system output and PSD by utilizing theories related to spectra,PSD,and random signal power spectra.The relationship was derived,validated through experiments and simulations,and subsequently applied to multi-objective optimization.Various optimization algorithms were compared to achieve optimal system power quality.The findings revealed that the relationships between power quality indices and PSD were influenced by variations in the order of the power spectral estimation model.An increase in the order of the AR model resulted in a 36%improvement in the number of optimal solutions.Regarding optimal solution distribution,NSGA-II demonstrated superior diversity,while MOEA/D exhibited better convergence.However,practical applications showed that while MOEA/D had higher convergence,NSGA-II produced superior optimal solutions,achieving the best power quality indices(THDi at 4.62%,d%at 3.51%,and cosφat 96%).These results suggest that the proposed method holds significant potential for optimizing power quality in practical applications.展开更多
This study tracked the characteristics of atmospheric wet deposition of the toxic element arsenic(As)at both urban(Guangzhou(GZ))and forested(Dinghushan Natural Reserve(DHS))sites within the Pearl River Delta(PRD)regi...This study tracked the characteristics of atmospheric wet deposition of the toxic element arsenic(As)at both urban(Guangzhou(GZ))and forested(Dinghushan Natural Reserve(DHS))sites within the Pearl River Delta(PRD)region between 2016 and 2019,examining its correlation with rainfall patterns.Additionally,by employing backward trajectory analysis and the potential source contribution function(PSCF)in conjunction with pertinent emission inventories,we pinpointed the main pathways of atmospheric arsenic transport and evaluated the emission contributions from priority source areas.The study revealed that the atmospheric arsenic wet deposition fluxes at the GZ and DHS sites exhibited a trend of increase followed by a decrease over the four-year period.Wet season deposition fluxes were more than triple those of the dry season,with urban site showing a difference of over four times.Notably,wet season As deposition at both sites was predominantly affected by heavy rainfall from marine air masses,constituting 31%of the total deposition.The predominant trajectory directions contributing to arsenic deposition at GZ and DHS were northeast(55%)and south(53%),respectively.The primary source areas for both sites were largely outside the PRD region,with the GZ site having 80%to 95%of its source area in the non-PRD region,compared to 69%to 88%at the DHS site.Furthermore,non-PRD areas contributed approximately 65%to arsenic emissions for both sites,with the industrial sector being the dominant emission source,exceeding 97%of the total emissions.展开更多
In this paper,a two-dimensional(2 D)direction-of-arrival(DOA)estimation algorithm with increased degrees of freedom for two parallel linear arrays is presented.Being different from the conventional two-parallel linear...In this paper,a two-dimensional(2 D)direction-of-arrival(DOA)estimation algorithm with increased degrees of freedom for two parallel linear arrays is presented.Being different from the conventional two-parallel linear array,the proposed two-parallel linear array consists of two uniform linear arrays with non-equal inter-element spacing.Propagator method(PM)is used to obtain a special matrix which can be utilized to increase the virtual elements of one of uniform linear arrays.Then,the PM algorithm is used again to obtain automatically paired elevation and azimuth angles.The simulation results and complexity analysis show that the proposed method can increase the number of distinguishable signals and improve the estimation precision without increasing the computational complexity.展开更多
BACKGROUND The undifferentiated-type(UDT)component profoundly affects the clinical course of early gastric cancers(EGCs).However,an accurate preoperative diagnosis of the histological types is unsatisfactory.To date,f...BACKGROUND The undifferentiated-type(UDT)component profoundly affects the clinical course of early gastric cancers(EGCs).However,an accurate preoperative diagnosis of the histological types is unsatisfactory.To date,few studies have investigated whether the UDT component within mixed-histological-type(MT)EGCs can be recognized preoperatively.AIM To clarify the histopathological characteristics of the endoscopically-resected MT EGCs for investigating whether the UDT component could be recognized preoperatively.METHODS This was a single-center retrospective study.First,we attempted to clarify the histopathological characteristics of the endoscopically-resected MT EGCs with emphasis on the UDT component.Histopathological examination investigated each lesion’s UDT component:(1)Whole mucosal layer occupation of the UDT component;(2)UDT component exposure to the surface of the mucosa;and(3)existence of a clear border between the differentiated-type and UDT components.Then,preoperative endoscopic images with magnifying endoscopy with narrowband imaging(ME-NBI)were examined to identify whether the endoscopic UDT component finding was recognizable within the area where it was present in the histopathological examination.The preoperative biopsy results and comparative relationships between endoscopic and histopathological findings were also examined.RESULTS In the histopathological examination,the whole mucosal layer occupation of the UDT component and exposure of the UDT component to the mucosal surface were observed in 67.3%(33/49)and 79.6%(39/49)of samples,respectively.A clear distinction of the border between the differentiated-type and UDT components could not be drawn in 65.3%(32/49)of MT lesions.In the endoscopic examination,the preoperative endoscopic images showed that only 24.5%(12/49)of MT EGCs revealed the UDT component within the area where it was present histopathologically.Histopathological UDT predominance was the single significant factor associated with the presence of the endoscopic UDT component finding(61.5%vs 11.1%,P=0.0009).Only 26.5%(13/49)of the lesions were diagnosed from the pretreatment biopsy as having a UDT component.Combined results of the pretreatment biopsy and ME-NBI showed the preoperative presence of the UDT component in 40.8%(20/49)of MT EGCs.CONCLUSION Recognition of a UDT component within MT EGCs is difficult even when pretreatment biopsy and ME-NBI are combined.Endoscopic resection plays a significant role in both treatment and diagnosis.展开更多
In order to synthesize high-quality type-Ⅱa large diamond, the selection of catalyst is very important, in addition to the nitrogen getter. In this paper, type-IIa large diamonds are grown under high pressure and hig...In order to synthesize high-quality type-Ⅱa large diamond, the selection of catalyst is very important, in addition to the nitrogen getter. In this paper, type-IIa large diamonds are grown under high pressure and high temperature（HPHT） by using the temperature gradient method（TGM）, with adopting Ti/Cu as the nitrogen getter in Ni70Mn25Co5（abbreviated as NiMnCo） or Fe（55）Ni（29）Co（16）（abbreviated FeNiCo） catalyst. The values of nitrogen concentration（Nc） in both synthesized high-quality diamonds are less than 1 ppm, when Ti/Cu（1.6 wt%） is added in the FeNiCo or Ti/Cu（1.8 wt%） is added in the NiMnCo. The difference in solubility of nitrogen between both catalysts at HPHT is the basic reason for the different effect of Ti/Cu on eliminating nitrogen. The nitrogen-removal efficiency of Ti/Cu in the NiMnCo catalyst is less than in the FeNiCo catalyst. Additionally, a high-quality type-Ⅱa large diamond size of 5.0 mm is obtained by reducing the growth rate and keeping the nitrogen concentration of the diamond to be less than 1 ppm, when Ti/Cu（1.6 wt%） is added in the FeNiCo catalyst.展开更多
Since the atmospheric correction is a necessary preprocessing step of remote sensing image before detecting green tide, the introduced error directly affects the detection precision. Therefore, the detection method of...Since the atmospheric correction is a necessary preprocessing step of remote sensing image before detecting green tide, the introduced error directly affects the detection precision. Therefore, the detection method of green tide is presented from Landsat TM/ETM plus image which needs not the atmospheric correction. In order to achieve an automatic detection of green tide, a linear relationship（y =0.723 x＋0.504） between detection threshold y and subtraction x（x=λnir–λred） is found from the comparing Landsat TM/ETM plus image with the field surveys.Using this relationship, green tide patches can be detected automatically from Landsat TM/ETM plus image.Considering there is brightness difference between different regions in an image, the image will be divided into a plurality of windows（sub-images） with a same size firstly, and then each window will be detected using an adaptive detection threshold determined according to the discovered linear relationship. It is found that big errors will appear in some windows, such as those covered by clouds seriously. To solve this problem, the moving step k of windows is proposed to be less than the window width n. Using this mechanism, most pixels will be detected[n/k]×[n/k] times except the boundary pixels, then every pixel will be assigned the final class（green tide or sea water） according to majority rule voting strategy. It can be seen from the experiments, the proposed detection method using multi-windows and their adaptive thresholds can detect green tide from Landsat TM/ETM plus image automatically. Meanwhile, it avoids the reliance on the accurate atmospheric correction.展开更多
To efficiently complete a complex computation task,the complex task should be decomposed into subcomputation tasks that run parallel in edge computing.Wireless Sensor Network(WSN)is a typical application of parallel c...To efficiently complete a complex computation task,the complex task should be decomposed into subcomputation tasks that run parallel in edge computing.Wireless Sensor Network(WSN)is a typical application of parallel computation.To achieve highly reliable parallel computation for wireless sensor network,the network's lifetime needs to be extended.Therefore,a proper task allocation strategy is needed to reduce the energy consumption and balance the load of the network.This paper proposes a task model and a cluster-based WSN model in edge computing.In our model,different tasks require different types of resources and different sensors provide different types of resources,so our model is heterogeneous,which makes the model more practical.Then we propose a task allocation algorithm that combines the Genetic Algorithm(GA)and the Ant Colony Optimization(ACO)algorithm.The algorithm concentrates on energy conservation and load balancing so that the lifetime of the network can be extended.The experimental result shows the algorithm's effectiveness and advantages in energy conservation and load balancing.展开更多
In this paper,weak optimal inverse problems of interval linear programming(IvLP)are studied based on KKT conditions.Firstly,the problem is precisely defined.Specifically,by adjusting the minimum change of the current ...In this paper,weak optimal inverse problems of interval linear programming(IvLP)are studied based on KKT conditions.Firstly,the problem is precisely defined.Specifically,by adjusting the minimum change of the current cost coefficient,a given weak solution can become optimal.Then,an equivalent characterization of weak optimal inverse IvLP problems is obtained.Finally,the problem is simplified without adjusting the cost coefficient of null variable.展开更多
As a mainstream research direction in the field of image segmentation,medical image segmentation plays a key role in the quantification of lesions,three-dimensional reconstruction,region of interest extraction and so ...As a mainstream research direction in the field of image segmentation,medical image segmentation plays a key role in the quantification of lesions,three-dimensional reconstruction,region of interest extraction and so on.Compared with natural images,medical images have a variety of modes.Besides,the emphasis of information which is conveyed by images of different modes is quite different.Because it is time-consuming and inefficient to manually segment medical images only by professional and experienced doctors.Therefore,large quantities of automated medical image segmentation methods have been developed.However,until now,researchers have not developed a universal method for all types of medical image segmentation.This paper reviews the literature on segmentation techniques that have produced major breakthroughs in recent years.Among the large quantities of medical image segmentation methods,this paper mainly discusses two categories of medical image segmentation methods.One is the improved strategies based on traditional clustering method.The other is the research progress of the improved image segmentation network structure model based on U-Net.The power of technology proves that the performance of the deep learning-based method is significantly better than that of the traditional method.This paper discussed both advantages and disadvantages of different algorithms and detailed how these methods can be used for the segmentation of lesions or other organs and tissues,as well as possible technical trends for future work.展开更多
Developing precise and fast methods for short circuit detection is crucial for preventing or mitigating the risk of safety issues of lithium-ion batteries(LIBs).In this paper,we developed a Convolutional Neural Networ...Developing precise and fast methods for short circuit detection is crucial for preventing or mitigating the risk of safety issues of lithium-ion batteries(LIBs).In this paper,we developed a Convolutional Neural Networks(CNN)based model that can quickly and precisely predict the short circuit resistance of LIB cells during various working conditions.Cycling tests of cells with an external short circuit(ESC)are produced to obtain the database and generate the training/testing samples.The samples are sequences of voltage,current,charging capacity,charging energy,total charging capacity,total charging energy with a length of 120 s and frequency of 1 Hz,and their corresponding short circuit resistances.A big database with~6×10^(5)samples are generated,covering various short circuit resistances(47~470Ω),current loading modes(Constant current-constant voltage(CC-CV)and drive cycle),and electrochemical states(cycle numbers from 1 to 300).Results show that the average relative absolute error of five random sample splits is 6.75%±2.8%.Further parametric analysis indicates the accuracy estimation benefits from the appropriate model setups:the optimized input sequence length(~120 s),feature selection(at least one total capacity-related variable),and rational model design,using multiple layers with different kernel sizes.This work highlights the capabilities of machine learning algorithms and data-driven methodologies in real-time safety risk prediction for batteries.展开更多
Dear Editor, This letter deals with the problem of algorithm recommendation for online fault detection of spacecraft. By transforming the time series data into distributions and introducing a distribution-aware measur...Dear Editor, This letter deals with the problem of algorithm recommendation for online fault detection of spacecraft. By transforming the time series data into distributions and introducing a distribution-aware measure, a principal method is designed for quantifying the detectabilities of fault detection algorithms over special datasets.展开更多
BACKGROUND In hepatocellular carcinoma(HCC),detection and treatment prior to growth beyond 2 cm are relevant as a larger tumor size is more frequently associated with microvascular invasion and/or satellites.AIM To ex...BACKGROUND In hepatocellular carcinoma(HCC),detection and treatment prior to growth beyond 2 cm are relevant as a larger tumor size is more frequently associated with microvascular invasion and/or satellites.AIM To examine the impact of the tumor marker alpha-fetoprotein(AFP)or PIVKA-II in detecting very small HCC nodules(≤2 cm in maximum diameter,Barcelona stage 0)in the large number of very small HCC.The difference in the behavior of these tumor markers in HCC development was also examined.METHODS A total of 933 patients with single-nodule HCC were examined.They were subdivided into 394 patients with HCC nodules≤2 cm in maximum diameter and 539 patients whose nodules were>2 cm.The rates of patients whose AFP and PIVKA-II showed normal values were examined.RESULTS The positive ratio of the marker PIVKA-II was significantly different(P<0.0001)between patients with nodules≤2 cm in diameter and those with nodules>2 cm,but there was no significant difference in AFP(P=0.4254).In the patients whose tumor was≤2 cm,50.5%showed normal levels in AFP and 68.8%showed normal levels in PIVKA-II.In 36.4%of those patients,both AFP and PIVKA-II showed normal levels.The PIVKA-II-positive ratio was markedly increased with an increase in the tumor size.In contrast,the positivity in AFP was increased gradually and slowly.CONCLUSION In the surveillance of very small HCC nodules(≤2 cm in diameter,Barcelona clinical stage 0)the tumor markers AFP and PIVKA-II are not so useful.展开更多
A series of diamonds with boron and sulfur co-doping were synthesized in the Fe Ni Mn Co-C system by temperature gradient growth（TGG） under high pressure and high temperature（HPHT）. Because of differences in addit...A series of diamonds with boron and sulfur co-doping were synthesized in the Fe Ni Mn Co-C system by temperature gradient growth（TGG） under high pressure and high temperature（HPHT）. Because of differences in additives, the resulting diamond crystals were colorless, blue-black, or yellow. Their morphologies were slab, tower, or minaret-like. Analysis of the x-ray photoelectron spectra（XPS） of these diamonds shows the presence of B, S, and N in samples from which N was not eliminated. But only the B dopant was assuredly incorporated in the samples from which N was eliminated. Resistivity and Hall mobility were 8.510 Ω·cm and 760.870 cm^2/V·s, respectively, for a P-type diamond sample from which nitrogen was eliminated. Correspondingly, resistivity and Hall mobility were 4.211×10^5 Ω·cm and 76.300 cmΩ2/V·s for an N-type diamond sample from which nitrogen was not eliminated. Large N-type diamonds of type Ib with B–S doping were acquired.展开更多
This study aims to apply ResNet-18 convolutional neural network(CNN)and XGBoost to preoperative computed tomography(CT)images and clinical data for distinguishing Xp11.2 translocation renal cell carcinoma(Xp11.2 tRCC)...This study aims to apply ResNet-18 convolutional neural network(CNN)and XGBoost to preoperative computed tomography(CT)images and clinical data for distinguishing Xp11.2 translocation renal cell carcinoma(Xp11.2 tRCC)from common subtypes of renal cell carcinoma(RCC)in order to provide patients with individualized treatment plans.Data from45 patients with Xp11.2 tRCC fromJanuary 2007 to December 2021 are collected.Clear cell RCC(ccRCC),papillary RCC(pRCC),or chromophobe RCC(chRCC)can be detected from each patient.CT images are acquired in the following three phases:unenhanced,corticomedullary,and nephrographic.A unified framework is proposed for the classification of renal masses.In this framework,ResNet-18 CNN is employed to classify renal cancers with CT images,while XGBoost is adopted with clinical data.Experiments demonstrate that,if applying ResNet-18 CNN or XGBoost singly,the latter outperforms the former,while the framework integrating both technologies performs similarly or better than urologists.Especially,the possibility of misclassifying Xp11.2 tRCC,pRCC,and chRCC as ccRCC by the proposed framework is much lower than urologists.展开更多
BACKGROUND The oral nucleos(t)ide analogue,entecavir(ETV)was demonstrated to reduce the rate of hepatocellular carcinoma(HCC)in patients with hepatitis B virus(HBV)-associated liver cirrhosis.However,the reduction of ...BACKGROUND The oral nucleos(t)ide analogue,entecavir(ETV)was demonstrated to reduce the rate of hepatocellular carcinoma(HCC)in patients with hepatitis B virus(HBV)-associated liver cirrhosis.However,the reduction of HCC differs in various regions of the world.AIM To investigate the reduction of HCC development due to ETV therapy by metaanalysis.METHODS We surveyed the differences in HCC development following ETV treatment based on published articles using PubMed(2004-2019).RESULTS The regions with the most marked reduction in HCC development due to ETV therapy were Spain(1.0%/year)and Canada(Southern part,1.3%/year),and the most ineffective areas were South Korea(3.6%-3.8%/year),China(3.3%/year),Taiwan(2.4%-3.1%/year),and Hong Kong(2.8%/year).Following ETV administration,the incidence of HCC in genotype D regions(1.89%±0.28%/year,mean±SE)was significantly lower than that in genotype C regions(2.91%±0.24%/year,P<0.01).With regard to the initial HBV-DNA level,in genotype C patients(average:5.61 Log10IU/mL)this was almost the same as that in genotype D patients(average:5.46 Log10IU/mL).Moreover,there was no association between the prevalence ratio of HBV and the incidence of HCC on ETV treatment.CONCLUSION The effectiveness of ETV in preventing HCC development in HBV-associated liver cirrhosis is genotype-dependent.展开更多
With the help of surgical navigation system,doctors can operate on patients more intuitively and accurately.The positioning accuracy and real-time performance of surgical instruments are very important to the whole sy...With the help of surgical navigation system,doctors can operate on patients more intuitively and accurately.The positioning accuracy and real-time performance of surgical instruments are very important to the whole system.In this paper,we analyze and design the detection algorithm of surgical instrument location mark,and estimate the posture of surgical instrument.In addition,we optimized the pose by remapping.Finally,the algorithm of location mark detection proposed in this paper and the posture analysis data of surgical instruments are verified and analyzed through experiments.The final result shows a high accuracy.展开更多
Significant breakthroughs in medical image registration have been achieved using deep neural networks(DNNs).However,DNN-based end-to-end registration methods often require large quantities of data or adequate annotati...Significant breakthroughs in medical image registration have been achieved using deep neural networks(DNNs).However,DNN-based end-to-end registration methods often require large quantities of data or adequate annotations for training.To leverage the intensity information of abundant unlabeled images,unsupervised registration methods commonly employ intensity-based similarity measures to optimize the network parameters.However,finding a sufficiently robust measure can be challenging for specific registration applications.Weakly supervised registration methods use anatomical labels to estimate the deformation between images.High-level structural information in label images is more reliable and practical for estimating the voxel correspondence of anatomic regions of interest between images,whereas label images are extremely difficult to collect.In this paper,we propose a two-stage semi-supervised learning framework for medical image registration,which consists of unsupervised and weakly supervised registration networks.The proposed semi-supervised learning framework is trained with intensity information from available images,label information from a relatively small number of labeled images and pseudo-label information from unlabeled images.Experimental results on two datasets(cardiac and abdominal images)demonstrate the efficacy and efficiency of this method in intra-and inter-modality medical image registrations,as well as its superior performance when a vast amount of unlabeled data and a small set of annotations are available.Our code is publicly available at at https://github.com/jdq818/SeRN.展开更多
文摘Accurate capacity and State of Charge(SOC)estimation are crucial for ensuring the safety and longevity of lithium-ion batteries in electric vehicles.This study examines ten machine learning architectures,Including Deep Belief Network(DBN),Bidirectional Recurrent Neural Network(BiDirRNN),Gated Recurrent Unit(GRU),and others using the NASA B0005 dataset of 591,458 instances.Results indicate that DBN excels in capacity estimation,achieving orders-of-magnitude lower error values and explaining over 99.97%of the predicted variable’s variance.When computational efficiency is paramount,the Deep Neural Network(DNN)offers a strong alternative,delivering near-competitive accuracy with significantly reduced prediction times.The GRU achieves the best overall performance for SOC estimation,attaining an R^(2) of 0.9999,while the BiDirRNN provides a marginally lower error at a slightly higher computational speed.In contrast,Convolutional Neural Networks(CNN)and Radial Basis Function Networks(RBFN)exhibit relatively high error rates,making them less viable for real-world battery management.Analyses of error distributions reveal that the top-performing models cluster most predictions within tight bounds,limiting the risk of overcharging or deep discharging.These findings highlight the trade-off between accuracy and computational overhead,offering valuable guidance for battery management system(BMS)designers seeking optimal performance under constrained resources.Future work may further explore advanced data augmentation and domain adaptation techniques to enhance these models’robustness in diverse operating conditions.
基金Supported by the National Natural Science Foundation of China(12261018)Universities Key Laboratory of Mathematical Modeling and Data Mining in Guizhou Province(2023013)。
文摘In this paper,we establish and study a single-species logistic model with impulsive age-selective harvesting.First,we prove the ultimate boundedness of the solutions of the system.Then,we obtain conditions for the asymptotic stability of the trivial solution and the positive periodic solution.Finally,numerical simulations are presented to validate our results.Our results show that age-selective harvesting is more conducive to sustainable population survival than non-age-selective harvesting.
基金This work is supported by Shandong Provincial Natural Science Foundation,China under Grant No.ZR2017MG011This work is also supported by Key Research and Development Program in Shandong Provincial(2017GGX90103).
文摘Monitoring,understanding and predicting Origin-destination(OD)flows in a city is an important problem for city planning and human activity.Taxi-GPS traces,acted as one kind of typical crowd sensed data,it can be used to mine the semantics of OD flows.In this paper,we firstly construct and analyze a complex network of OD flows based on large-scale GPS taxi traces of a city in China.The spatiotemporal analysis for the OD flows complex network showed that there were distinctive patterns in OD flows.Then based on a novel complex network model,a semantics mining method of OD flows is proposed through compounding Points of Interests(POI)network and public transport network to the OD flows network.The propose method would offer a novel way to predict the location characteristic and future traffic conditions accurately.
基金funded by the Inner Mongolia Nature Foundation Project,Project number:2023JQ04.
文摘Power quality is a crucial area of research in contemporary power systems,particularly given the rapid proliferation of intermittent renewable energy sources such as wind power.This study investigated the relationships between power quality indices of system output and PSD by utilizing theories related to spectra,PSD,and random signal power spectra.The relationship was derived,validated through experiments and simulations,and subsequently applied to multi-objective optimization.Various optimization algorithms were compared to achieve optimal system power quality.The findings revealed that the relationships between power quality indices and PSD were influenced by variations in the order of the power spectral estimation model.An increase in the order of the AR model resulted in a 36%improvement in the number of optimal solutions.Regarding optimal solution distribution,NSGA-II demonstrated superior diversity,while MOEA/D exhibited better convergence.However,practical applications showed that while MOEA/D had higher convergence,NSGA-II produced superior optimal solutions,achieving the best power quality indices(THDi at 4.62%,d%at 3.51%,and cosφat 96%).These results suggest that the proposed method holds significant potential for optimizing power quality in practical applications.
基金supported by the National Natural Science Foundation of China(Nos.42121004,42275107,and 42077205)the National Key Research and Development Plan(No.2023YFC3706202)+1 种基金the Foundational and Applied Basic Research in Guangzhou in 2023(No.2023A04J0251)the Special Fund Project for Science and Technology Innovation Strategy of Guangdong Province(No.2019B121205004)。
文摘This study tracked the characteristics of atmospheric wet deposition of the toxic element arsenic(As)at both urban(Guangzhou(GZ))and forested(Dinghushan Natural Reserve(DHS))sites within the Pearl River Delta(PRD)region between 2016 and 2019,examining its correlation with rainfall patterns.Additionally,by employing backward trajectory analysis and the potential source contribution function(PSCF)in conjunction with pertinent emission inventories,we pinpointed the main pathways of atmospheric arsenic transport and evaluated the emission contributions from priority source areas.The study revealed that the atmospheric arsenic wet deposition fluxes at the GZ and DHS sites exhibited a trend of increase followed by a decrease over the four-year period.Wet season deposition fluxes were more than triple those of the dry season,with urban site showing a difference of over four times.Notably,wet season As deposition at both sites was predominantly affected by heavy rainfall from marine air masses,constituting 31%of the total deposition.The predominant trajectory directions contributing to arsenic deposition at GZ and DHS were northeast(55%)and south(53%),respectively.The primary source areas for both sites were largely outside the PRD region,with the GZ site having 80%to 95%of its source area in the non-PRD region,compared to 69%to 88%at the DHS site.Furthermore,non-PRD areas contributed approximately 65%to arsenic emissions for both sites,with the industrial sector being the dominant emission source,exceeding 97%of the total emissions.
基金supported by the National Natural Science Foundation of China(51877015,U1831117)the Cooperation Agreement Foundation by the Department of Science and Technology of Guizhou Province of China(LH[2017]7320,LH[2017]7321,[2015]7249)+2 种基金the Innovation Group Major Research Program Funded by Guizhou Provincial Education Department(KY[2016]051)the Foundation of Top-notch Talents by Education Department of Guizhou Province of China(KY[2018]075)PhD Research Startup Foundation of Tongren University(trxy DH1710)。
文摘In this paper,a two-dimensional(2 D)direction-of-arrival(DOA)estimation algorithm with increased degrees of freedom for two parallel linear arrays is presented.Being different from the conventional two-parallel linear array,the proposed two-parallel linear array consists of two uniform linear arrays with non-equal inter-element spacing.Propagator method(PM)is used to obtain a special matrix which can be utilized to increase the virtual elements of one of uniform linear arrays.Then,the PM algorithm is used again to obtain automatically paired elevation and azimuth angles.The simulation results and complexity analysis show that the proposed method can increase the number of distinguishable signals and improve the estimation precision without increasing the computational complexity.
文摘BACKGROUND The undifferentiated-type(UDT)component profoundly affects the clinical course of early gastric cancers(EGCs).However,an accurate preoperative diagnosis of the histological types is unsatisfactory.To date,few studies have investigated whether the UDT component within mixed-histological-type(MT)EGCs can be recognized preoperatively.AIM To clarify the histopathological characteristics of the endoscopically-resected MT EGCs for investigating whether the UDT component could be recognized preoperatively.METHODS This was a single-center retrospective study.First,we attempted to clarify the histopathological characteristics of the endoscopically-resected MT EGCs with emphasis on the UDT component.Histopathological examination investigated each lesion’s UDT component:(1)Whole mucosal layer occupation of the UDT component;(2)UDT component exposure to the surface of the mucosa;and(3)existence of a clear border between the differentiated-type and UDT components.Then,preoperative endoscopic images with magnifying endoscopy with narrowband imaging(ME-NBI)were examined to identify whether the endoscopic UDT component finding was recognizable within the area where it was present in the histopathological examination.The preoperative biopsy results and comparative relationships between endoscopic and histopathological findings were also examined.RESULTS In the histopathological examination,the whole mucosal layer occupation of the UDT component and exposure of the UDT component to the mucosal surface were observed in 67.3%(33/49)and 79.6%(39/49)of samples,respectively.A clear distinction of the border between the differentiated-type and UDT components could not be drawn in 65.3%(32/49)of MT lesions.In the endoscopic examination,the preoperative endoscopic images showed that only 24.5%(12/49)of MT EGCs revealed the UDT component within the area where it was present histopathologically.Histopathological UDT predominance was the single significant factor associated with the presence of the endoscopic UDT component finding(61.5%vs 11.1%,P=0.0009).Only 26.5%(13/49)of the lesions were diagnosed from the pretreatment biopsy as having a UDT component.Combined results of the pretreatment biopsy and ME-NBI showed the preoperative presence of the UDT component in 40.8%(20/49)of MT EGCs.CONCLUSION Recognition of a UDT component within MT EGCs is difficult even when pretreatment biopsy and ME-NBI are combined.Endoscopic resection plays a significant role in both treatment and diagnosis.
基金supported by the National Natural Science Foundation of China(Grant No.11604246)the China Postdoctoral Science Foundation(Grant No.2016M592714)+2 种基金the Professional Practice Demonstration Base for Professional Degree Graduate in Material Engineering of Henan Polytechnic University,China(Grant No.2016YJD03)the Funds from the Education Department of Henan Province,China(Grant Nos.12A430010 and 17A430020)the Project for Key Science and Technology Research of Henan Province,China(Grant No.162102210275)
文摘In order to synthesize high-quality type-Ⅱa large diamond, the selection of catalyst is very important, in addition to the nitrogen getter. In this paper, type-IIa large diamonds are grown under high pressure and high temperature（HPHT） by using the temperature gradient method（TGM）, with adopting Ti/Cu as the nitrogen getter in Ni70Mn25Co5（abbreviated as NiMnCo） or Fe（55）Ni（29）Co（16）（abbreviated FeNiCo） catalyst. The values of nitrogen concentration（Nc） in both synthesized high-quality diamonds are less than 1 ppm, when Ti/Cu（1.6 wt%） is added in the FeNiCo or Ti/Cu（1.8 wt%） is added in the NiMnCo. The difference in solubility of nitrogen between both catalysts at HPHT is the basic reason for the different effect of Ti/Cu on eliminating nitrogen. The nitrogen-removal efficiency of Ti/Cu in the NiMnCo catalyst is less than in the FeNiCo catalyst. Additionally, a high-quality type-Ⅱa large diamond size of 5.0 mm is obtained by reducing the growth rate and keeping the nitrogen concentration of the diamond to be less than 1 ppm, when Ti/Cu（1.6 wt%） is added in the FeNiCo catalyst.
基金The National Natural Science Foundation of China under contract Nos 41506198 and 41476101the Natural Science Foundation Projects of Shandong Province of China under contract No.ZR2012FZ003the Science and Technology Development Plan of Qingdao City of China under contract No.13-1-4-121-jch
文摘Since the atmospheric correction is a necessary preprocessing step of remote sensing image before detecting green tide, the introduced error directly affects the detection precision. Therefore, the detection method of green tide is presented from Landsat TM/ETM plus image which needs not the atmospheric correction. In order to achieve an automatic detection of green tide, a linear relationship（y =0.723 x＋0.504） between detection threshold y and subtraction x（x=λnir–λred） is found from the comparing Landsat TM/ETM plus image with the field surveys.Using this relationship, green tide patches can be detected automatically from Landsat TM/ETM plus image.Considering there is brightness difference between different regions in an image, the image will be divided into a plurality of windows（sub-images） with a same size firstly, and then each window will be detected using an adaptive detection threshold determined according to the discovered linear relationship. It is found that big errors will appear in some windows, such as those covered by clouds seriously. To solve this problem, the moving step k of windows is proposed to be less than the window width n. Using this mechanism, most pixels will be detected[n/k]×[n/k] times except the boundary pixels, then every pixel will be assigned the final class（green tide or sea water） according to majority rule voting strategy. It can be seen from the experiments, the proposed detection method using multi-windows and their adaptive thresholds can detect green tide from Landsat TM/ETM plus image automatically. Meanwhile, it avoids the reliance on the accurate atmospheric correction.
基金supported by Postdoctoral Science Foundation of China(No.2021M702441)National Natural Science Foundation of China(No.61871283)。
文摘To efficiently complete a complex computation task,the complex task should be decomposed into subcomputation tasks that run parallel in edge computing.Wireless Sensor Network(WSN)is a typical application of parallel computation.To achieve highly reliable parallel computation for wireless sensor network,the network's lifetime needs to be extended.Therefore,a proper task allocation strategy is needed to reduce the energy consumption and balance the load of the network.This paper proposes a task model and a cluster-based WSN model in edge computing.In our model,different tasks require different types of resources and different sensors provide different types of resources,so our model is heterogeneous,which makes the model more practical.Then we propose a task allocation algorithm that combines the Genetic Algorithm(GA)and the Ant Colony Optimization(ACO)algorithm.The algorithm concentrates on energy conservation and load balancing so that the lifetime of the network can be extended.The experimental result shows the algorithm's effectiveness and advantages in energy conservation and load balancing.
基金Supported by the National Natural Science Foundation of China(11971433)First Class Discipline of Zhe-jiang-A(Zhejiang Gongshang University-Statistics,1020JYN4120004G-091),Graduate Scientic Research and Innovation Foundation of Zhejiang Gongshang University.
文摘In this paper,weak optimal inverse problems of interval linear programming(IvLP)are studied based on KKT conditions.Firstly,the problem is precisely defined.Specifically,by adjusting the minimum change of the current cost coefficient,a given weak solution can become optimal.Then,an equivalent characterization of weak optimal inverse IvLP problems is obtained.Finally,the problem is simplified without adjusting the cost coefficient of null variable.
基金supported partly by the Open Project of State Key Laboratory of Millimeter Wave under Grant K202218partly by Innovation and Entrepreneurship Training Program of College Students under Grants 202210700006Y and 202210700005Z.
文摘As a mainstream research direction in the field of image segmentation,medical image segmentation plays a key role in the quantification of lesions,three-dimensional reconstruction,region of interest extraction and so on.Compared with natural images,medical images have a variety of modes.Besides,the emphasis of information which is conveyed by images of different modes is quite different.Because it is time-consuming and inefficient to manually segment medical images only by professional and experienced doctors.Therefore,large quantities of automated medical image segmentation methods have been developed.However,until now,researchers have not developed a universal method for all types of medical image segmentation.This paper reviews the literature on segmentation techniques that have produced major breakthroughs in recent years.Among the large quantities of medical image segmentation methods,this paper mainly discusses two categories of medical image segmentation methods.One is the improved strategies based on traditional clustering method.The other is the research progress of the improved image segmentation network structure model based on U-Net.The power of technology proves that the performance of the deep learning-based method is significantly better than that of the traditional method.This paper discussed both advantages and disadvantages of different algorithms and detailed how these methods can be used for the segmentation of lesions or other organs and tissues,as well as possible technical trends for future work.
基金supported by the U.S.Department of Energy’s Office on Energy Efficiency and Renewable Energy(EERE)under the Advanced Manufacturing Office,award number DE-EE0009111。
文摘Developing precise and fast methods for short circuit detection is crucial for preventing or mitigating the risk of safety issues of lithium-ion batteries(LIBs).In this paper,we developed a Convolutional Neural Networks(CNN)based model that can quickly and precisely predict the short circuit resistance of LIB cells during various working conditions.Cycling tests of cells with an external short circuit(ESC)are produced to obtain the database and generate the training/testing samples.The samples are sequences of voltage,current,charging capacity,charging energy,total charging capacity,total charging energy with a length of 120 s and frequency of 1 Hz,and their corresponding short circuit resistances.A big database with~6×10^(5)samples are generated,covering various short circuit resistances(47~470Ω),current loading modes(Constant current-constant voltage(CC-CV)and drive cycle),and electrochemical states(cycle numbers from 1 to 300).Results show that the average relative absolute error of five random sample splits is 6.75%±2.8%.Further parametric analysis indicates the accuracy estimation benefits from the appropriate model setups:the optimized input sequence length(~120 s),feature selection(at least one total capacity-related variable),and rational model design,using multiple layers with different kernel sizes.This work highlights the capabilities of machine learning algorithms and data-driven methodologies in real-time safety risk prediction for batteries.
基金supported by the National Key R&D Program of China (2021YFB1715000)the National Natural Science Foundation of China (U1811461, 62022013, 12150007, 62103450, 61832003, 62272137)。
文摘Dear Editor, This letter deals with the problem of algorithm recommendation for online fault detection of spacecraft. By transforming the time series data into distributions and introducing a distribution-aware measure, a principal method is designed for quantifying the detectabilities of fault detection algorithms over special datasets.
文摘BACKGROUND In hepatocellular carcinoma(HCC),detection and treatment prior to growth beyond 2 cm are relevant as a larger tumor size is more frequently associated with microvascular invasion and/or satellites.AIM To examine the impact of the tumor marker alpha-fetoprotein(AFP)or PIVKA-II in detecting very small HCC nodules(≤2 cm in maximum diameter,Barcelona stage 0)in the large number of very small HCC.The difference in the behavior of these tumor markers in HCC development was also examined.METHODS A total of 933 patients with single-nodule HCC were examined.They were subdivided into 394 patients with HCC nodules≤2 cm in maximum diameter and 539 patients whose nodules were>2 cm.The rates of patients whose AFP and PIVKA-II showed normal values were examined.RESULTS The positive ratio of the marker PIVKA-II was significantly different(P<0.0001)between patients with nodules≤2 cm in diameter and those with nodules>2 cm,but there was no significant difference in AFP(P=0.4254).In the patients whose tumor was≤2 cm,50.5%showed normal levels in AFP and 68.8%showed normal levels in PIVKA-II.In 36.4%of those patients,both AFP and PIVKA-II showed normal levels.The PIVKA-II-positive ratio was markedly increased with an increase in the tumor size.In contrast,the positivity in AFP was increased gradually and slowly.CONCLUSION In the surveillance of very small HCC nodules(≤2 cm in diameter,Barcelona clinical stage 0)the tumor markers AFP and PIVKA-II are not so useful.
基金Project supported by the National Natural Science Foundation of China(Grant No.11604246)China Postdoctor Science Foundation(Grant No.2016M592714)+2 种基金Professional Practice Demonstration Base for Professional Degree Graduate in Material Engineering of Henan Polytechnic University,China(Grant No.2016YJD03)the Education Department of Henan Province,China(Grant Nos.12A430010 and 17A430020)the Fundamental Research Funds for the Universities of Henan Province,China(Grant No.NSFRF140110)
文摘A series of diamonds with boron and sulfur co-doping were synthesized in the Fe Ni Mn Co-C system by temperature gradient growth（TGG） under high pressure and high temperature（HPHT）. Because of differences in additives, the resulting diamond crystals were colorless, blue-black, or yellow. Their morphologies were slab, tower, or minaret-like. Analysis of the x-ray photoelectron spectra（XPS） of these diamonds shows the presence of B, S, and N in samples from which N was not eliminated. But only the B dopant was assuredly incorporated in the samples from which N was eliminated. Resistivity and Hall mobility were 8.510 Ω·cm and 760.870 cm^2/V·s, respectively, for a P-type diamond sample from which nitrogen was eliminated. Correspondingly, resistivity and Hall mobility were 4.211×10^5 Ω·cm and 76.300 cmΩ2/V·s for an N-type diamond sample from which nitrogen was not eliminated. Large N-type diamonds of type Ib with B–S doping were acquired.
基金supported by Beijing Ronghe Medical Development Foundation。
文摘This study aims to apply ResNet-18 convolutional neural network(CNN)and XGBoost to preoperative computed tomography(CT)images and clinical data for distinguishing Xp11.2 translocation renal cell carcinoma(Xp11.2 tRCC)from common subtypes of renal cell carcinoma(RCC)in order to provide patients with individualized treatment plans.Data from45 patients with Xp11.2 tRCC fromJanuary 2007 to December 2021 are collected.Clear cell RCC(ccRCC),papillary RCC(pRCC),or chromophobe RCC(chRCC)can be detected from each patient.CT images are acquired in the following three phases:unenhanced,corticomedullary,and nephrographic.A unified framework is proposed for the classification of renal masses.In this framework,ResNet-18 CNN is employed to classify renal cancers with CT images,while XGBoost is adopted with clinical data.Experiments demonstrate that,if applying ResNet-18 CNN or XGBoost singly,the latter outperforms the former,while the framework integrating both technologies performs similarly or better than urologists.Especially,the possibility of misclassifying Xp11.2 tRCC,pRCC,and chRCC as ccRCC by the proposed framework is much lower than urologists.
基金Supported by the Kanagawa Association of Medical and Dental Practitioners.
文摘BACKGROUND The oral nucleos(t)ide analogue,entecavir(ETV)was demonstrated to reduce the rate of hepatocellular carcinoma(HCC)in patients with hepatitis B virus(HBV)-associated liver cirrhosis.However,the reduction of HCC differs in various regions of the world.AIM To investigate the reduction of HCC development due to ETV therapy by metaanalysis.METHODS We surveyed the differences in HCC development following ETV treatment based on published articles using PubMed(2004-2019).RESULTS The regions with the most marked reduction in HCC development due to ETV therapy were Spain(1.0%/year)and Canada(Southern part,1.3%/year),and the most ineffective areas were South Korea(3.6%-3.8%/year),China(3.3%/year),Taiwan(2.4%-3.1%/year),and Hong Kong(2.8%/year).Following ETV administration,the incidence of HCC in genotype D regions(1.89%±0.28%/year,mean±SE)was significantly lower than that in genotype C regions(2.91%±0.24%/year,P<0.01).With regard to the initial HBV-DNA level,in genotype C patients(average:5.61 Log10IU/mL)this was almost the same as that in genotype D patients(average:5.46 Log10IU/mL).Moreover,there was no association between the prevalence ratio of HBV and the incidence of HCC on ETV treatment.CONCLUSION The effectiveness of ETV in preventing HCC development in HBV-associated liver cirrhosis is genotype-dependent.
基金supported by the Sichuan Science and Technology Program(2021YFQ0003).
文摘With the help of surgical navigation system,doctors can operate on patients more intuitively and accurately.The positioning accuracy and real-time performance of surgical instruments are very important to the whole system.In this paper,we analyze and design the detection algorithm of surgical instrument location mark,and estimate the posture of surgical instrument.In addition,we optimized the pose by remapping.Finally,the algorithm of location mark detection proposed in this paper and the posture analysis data of surgical instruments are verified and analyzed through experiments.The final result shows a high accuracy.
文摘Significant breakthroughs in medical image registration have been achieved using deep neural networks(DNNs).However,DNN-based end-to-end registration methods often require large quantities of data or adequate annotations for training.To leverage the intensity information of abundant unlabeled images,unsupervised registration methods commonly employ intensity-based similarity measures to optimize the network parameters.However,finding a sufficiently robust measure can be challenging for specific registration applications.Weakly supervised registration methods use anatomical labels to estimate the deformation between images.High-level structural information in label images is more reliable and practical for estimating the voxel correspondence of anatomic regions of interest between images,whereas label images are extremely difficult to collect.In this paper,we propose a two-stage semi-supervised learning framework for medical image registration,which consists of unsupervised and weakly supervised registration networks.The proposed semi-supervised learning framework is trained with intensity information from available images,label information from a relatively small number of labeled images and pseudo-label information from unlabeled images.Experimental results on two datasets(cardiac and abdominal images)demonstrate the efficacy and efficiency of this method in intra-and inter-modality medical image registrations,as well as its superior performance when a vast amount of unlabeled data and a small set of annotations are available.Our code is publicly available at at https://github.com/jdq818/SeRN.
