In this study,an automated multimodal system for detecting,classifying,and dating fruit was developed using a two-stage YOLOv11 pipeline.In the first stage,the YOLOv11 detection model locates individual date fruits in...In this study,an automated multimodal system for detecting,classifying,and dating fruit was developed using a two-stage YOLOv11 pipeline.In the first stage,the YOLOv11 detection model locates individual date fruits in real time by drawing bounding boxes around them.These bounding boxes are subsequently passed to a YOLOv11 classification model,which analyzes cropped images and assigns class labels.An additional counting module automatically tallies the detected fruits,offering a near-instantaneous estimation of quantity.The experimental results suggest high precision and recall for detection,high classification accuracy(across 15 classes),and near-perfect counting in real time.This paper presents a multi-stage pipeline for date fruit detection,classification,and automated counting,employing YOLOv11-based models to achieve high accuracy while maintaining real-time throughput.The results demonstrated that the detection precision exceeded 90%,the classification accuracy approached 92%,and the counting module correlated closely with the manual tallies.These findings confirm the potential of reducing manual labour and enhancing operational efficiency in post-harvesting processes.Future studies will include dataset expansion,user-centric interfaces,and integration with harvesting robotics.展开更多
Accurately counting dense objects in complex and diverse backgrounds is a significant challenge in computer vision,with applications ranging from crowd counting to various other object counting tasks.To address this,w...Accurately counting dense objects in complex and diverse backgrounds is a significant challenge in computer vision,with applications ranging from crowd counting to various other object counting tasks.To address this,we propose HUANNet(High-Resolution Unified Attention Network),a convolutional neural network designed to capture both local features and rich semantic information through a high-resolution representation learning framework,while optimizing computational distribution across parallel branches.HUANNet introduces three core modules:the High-Resolution Attention Module(HRAM),which enhances feature extraction by optimizing multiresolution feature fusion;the Unified Multi-Scale Attention Module(UMAM),which integrates spatial,channel,and convolutional kernel information through an attention mechanism applied across multiple levels of the network;and the Grid-Assisted Point Matching Module(GPMM),which stabilizes and improves point-to-point matching by leveraging grid-based mechanisms.Extensive experiments show that HUANNet achieves competitive results on the ShanghaiTech Part A/B crowd counting datasets and sets new state-of-the-art performance on dense object counting datasets such as CARPK and XRAY-IECCD,demonstrating the effectiveness and versatility of HUANNet.展开更多
Environmental DNA(e DNA)methods have emerged as a promising tool for studying a broad spectrum of biological taxa.However,metabarcoding studies of avian biodiversity using e DNA have received little attention.In this ...Environmental DNA(e DNA)methods have emerged as a promising tool for studying a broad spectrum of biological taxa.However,metabarcoding studies of avian biodiversity using e DNA have received little attention.In this study,we compared waterbird biodiversity derived from e DNA metabarcoding with that obtained from traditional point counting surveys at 23 sites in Tai Lake of eastern China and evaluated the accuracy of e DNA metabarcoding for waterbird community studies.The point counting method recorded a higher total number of waterbird species(22)compared to the e DNA technique(16).While e DNA achieved a 74.5%detection rate for waterbird species and was able to identify a significantly greater number of species(12.48±1.97)at each sampling site than point counting method(6.13±2.69),particularly highlighting several rare and elusive species,it failed to detect some species commonly observed by the point counting method.The alpha diversity analysis revealed no significant differences in waterbird diversity between the e DNA method and the point counting method,except that the e DNA method exhibited lower Pielou evenness.Waterbird e DNA sequencing abundance correlated significantly with species occurrence,whereas Spearman's analysis indicated no significant difference between e DNA sequence abundance and species abundance from the point counting method.e DNA method detected no significant difference in waterbird composition between sampling sites,while the point counting method revealed significant differences.Consequently,e DNA is an effective complementary tool for assessing the diversity of wintering waterbirds in lakes,though it is unable to capture the full diversity of waterbird communities.It is crucial to develop sampling strategies that comprehensively monitor species composition and integrate e DNA with traditional survey methods for accurate evaluation of community structure.展开更多
According to the World Health Organization(WHO)manual,sperm concentration should be measured using an improved Neubauer hemocytometer,while sperm motility should be measured by manual assessment.However,in China,thous...According to the World Health Organization(WHO)manual,sperm concentration should be measured using an improved Neubauer hemocytometer,while sperm motility should be measured by manual assessment.However,in China,thousands of laboratories do not use the improved Neubauer hemocytometer or method;instead,the Makler counting chamber is one of the most widely used chambers.To study sources of error that could impact the measurement of the apparent concentration and motility of sperm using the Makler counting chamber and to verify its accuracy for clinical application,67 semen samples from patients attending the Department of Andrology,West China Second University Hospital,Sichuan University(Chengdu,China)between 13 September 2023 and 27 September 2023,were included.Compared with applying the cover glass immediately,delaying the application of the cover glass for 5 s,10 s,and 30 s resulted in average increases in the sperm concentration of 30.3%,74.1%,and 107.5%,respectively(all P<0.0001)and in the progressive motility(PR)of 17.7%,30.8%,and 39.6%,respectively(all P<0.0001).However,when the semen specimens were fixed with formaldehyde,a delay in the application of the cover glass for 5 s,10 s,and 30 s resulted in an average increase in the sperm concentration of 6.7%,10.8%,and 14.6%,respectively,compared with immediate application of the cover glass.The accumulation of motile sperm due to delays in the application of the cover glass is a significant source of error with the Makler counting chamber and should be avoided.展开更多
The analysis of the ejaculate,better known as spermiogram,represents the first and main step to identify whether a series of sperm quality parameters are within the norm and therefore are consistent with normal sperm ...The analysis of the ejaculate,better known as spermiogram,represents the first and main step to identify whether a series of sperm quality parameters are within the norm and therefore are consistent with normal sperm fertilizing capacity.Among these,sperm concentration and motility are the first parameters to be evaluated through an estimation carried out by expert examiners.展开更多
Characterization of the distribution and accurate counting of RNA molecules in the context of tissues is necessary to understand their complexity and heterogeneity.Single-molecule fluorescence in situ hybridization re...Characterization of the distribution and accurate counting of RNA molecules in the context of tissues is necessary to understand their complexity and heterogeneity.Single-molecule fluorescence in situ hybridization reveals the abundance and distribution of RNA and resolves different cell types in complex tissues.Especially,off-target binding and nonspecific adsorption of probes are prone to producing nonspecific amplification.Herein,we present highly de-noising amplified imaging,which leverages a sitespecific cleavage-amplifying design to achieve accurate counting of RNA in tissues.Our method avoids adding probe as primer,decreases nonspecific spots of single cells from 7 to nearly zero,and enables RNA imaging in uncleared tissue sections with nearly zero noise.We demonstrate the efficacy of this method on various thickness of mouse tissue sections.We envision this approach will serve as a tool to revealing the information content from patient samples for biomedical purpose.展开更多
Aiming at problems such as large errors and low efficiency in manual counting of drill pipes during drilling depth measurement,an intelligent detection and counting method for the small targets at the end of drill pip...Aiming at problems such as large errors and low efficiency in manual counting of drill pipes during drilling depth measurement,an intelligent detection and counting method for the small targets at the end of drill pipes based on the improved YOLO11n is proposed.This method realizes the high-precision detection of targets at drill pipe ends in the image by optimizing the target detection model,and combines a post-processing correction mechanism to improve the drill pipe counting accuracy.In order to alleviate the low-precision problem of YOLO11n algorithm for small target recognition in the complex underground background,the YOLO11n algorithm is improved.First,the key module C3k2 in the backbone network was improved,and Poly Kernel Inception(PKI)Block was introduced to replace Bottleneck in it to fully integrate the target context information and the model’s capability of feature extraction;Second,within the model’s neck network,a new feature fusion pyramid ISOP(Improved Small Object Pyramid)is proposed,SPDConv is introduced to strengthen the P2 feature,and CSP and OmniKernel are combined to integrate multi-scale features;Finally,the default loss function is substituted with Powerful-IoU(PIoU)to solve the anchor box expansion problem.On the self-built dataset,experimental verification was conducted.The findings showed that the Recall rose by 6.4%,mAP@0.5 increased by 4.5%,and mAP@0.5:0.95 improved by 6%compared with the baseline model,effectively solving the issues of false detection and missed detection problems in small target detection task.Meanwhile,we conducted counting tests on drilling videos from 5 different scenarios,achieving an average accuracy of 97.3%,which meets the accuracy needs for drill pipe recognition and counting in coal mine drilling sites.The research findings offer theoretical basis and technical backing for promoting the intelligent development of coal mine gas extraction drilling sites.展开更多
The particle identification(PID)of hadrons plays a crucial role in particle physics experiments,especially in flavor physics and jet tagging.The cluster counting method,which measures the number of primary ionizations...The particle identification(PID)of hadrons plays a crucial role in particle physics experiments,especially in flavor physics and jet tagging.The cluster counting method,which measures the number of primary ionizations in gaseous detectors,is a promising breakthrough in PID.However,developing an effective reconstruction algorithm for cluster counting remains challenging.To address this challenge,we propose a cluster counting algorithm based on long short-term memory and dynamic graph convolutional neural networks for the CEPC drift chamber.Experiments on Monte Carlo simulated samples demonstrate that our machine learning-based algorithm surpasses traditional methods.It improves the K/πseparation of PID by 10%,meeting the PID requirements of CEPC.展开更多
In this paper,we study composition operators on weighted Bergman spaces of Dirichlet series.We first establish some Littlewood-type inequalities for generalized mean counting functions.Then we give sufficient conditio...In this paper,we study composition operators on weighted Bergman spaces of Dirichlet series.We first establish some Littlewood-type inequalities for generalized mean counting functions.Then we give sufficient conditions for a composition operator with zero characteristic to be bounded or compact on weighted Bergman spaces of Dirichlet series.The corresponding sufficient condition for compactness in the case of positive characteristics is also obtained.展开更多
Aiming at the problem of inaccurate crowd counting and location in dense scenes,a dynamic region-sensing crowd counting and location method based on high-resolution fusion was proposed.Firstly,U-HRNet was used as the ...Aiming at the problem of inaccurate crowd counting and location in dense scenes,a dynamic region-sensing crowd counting and location method based on high-resolution fusion was proposed.Firstly,U-HRNet was used as the main backbone to extract highresolution features of the population and enhance the ability of feature extraction with different resolutions.Then,the dynamic regional awareness attention module was designed to make full use of the global and local feature information,refine the differentiated learning of target feature and background feature,reduce the interference of background feature,and improve the positioning performance of the model.Finally,the predicted threshold map and confidence map were input into the binarization module to output the prediction and counting results of the crowd independent individual target.Experimental results showed that the proposed method achieved good performance of counting and positioning in different scenarios.展开更多
A novel nano crystalline Ag2O2-PbO2 film chemically modified electrode (CME) was prepared and the CME was characterized by X-ray diffractometer (XRD) and atomic force microscope (AFM). By chronoamperometry, the nano A...A novel nano crystalline Ag2O2-PbO2 film chemically modified electrode (CME) was prepared and the CME was characterized by X-ray diffractometer (XRD) and atomic force microscope (AFM). By chronoamperometry, the nano Ag2O2-PbO2 CME was used as bioelectro- chemical sensor to determine the population of Escherichia coli (E. coli) in water. Compared with conventional methods, it is found that the technique we used is fast and convenient in counting E. coli.展开更多
Regular detection of pavement cracks is essential for infrastructure maintenance.However,existing methods often ignore the challenges such as the continuous evolution of crack features between video frames and the dif...Regular detection of pavement cracks is essential for infrastructure maintenance.However,existing methods often ignore the challenges such as the continuous evolution of crack features between video frames and the difficulty of defect quantification.To this end,this paper proposes an integrated framework for pavement crack detection,segmentation,tracking and counting based on Transformer.Firstly,we design theVitSeg-Det network,which is an integrated detection and segmentation network that can accurately locate and segment tiny cracks in complex scenes.Second,the TransTra-Count system is developed to automatically count the number of defects by combining defect tracking with width estimation.Finally,we conduct experimental verification on three datasets.The results show that the proposed method is superior to the existing deep learning methods in detection accuracy.In addition,the actual scene video test shows that the framework can accurately label the defect location and output the number of defects in real time.展开更多
Oligospermia,characterized by a low sperm count in semen,is a major cause of male infertility and may result from various factors including infections,lifestyle choices,retrograde ejaculation,tumors,hormonal imbalance...Oligospermia,characterized by a low sperm count in semen,is a major cause of male infertility and may result from various factors including infections,lifestyle choices,retrograde ejaculation,tumors,hormonal imbalances,drug treatments,and environmental exposures.Animal models play a crucial role in understanding its pathophysiology,identifying therapeutic targets,and evaluating potential treatments.The current review highlights experimental models used to induce oligospermia in laboratory animals,focusing on chemical,surgical,and radiation-based approaches.We review the reversible and irreversible methods commonly employed to study impaired spermatogenesis,along with the key endpoints used to assess testicular function and sperm quality.Standard housing and feeding conditions relevant to oligospermia research are also summarized to support reproducibility and methodological consistency in experimental designs.展开更多
Title Page The title page(page 1,do not number)should contain these elements:(a)full title;(b)Each authors'names,academic degrees,and affiliations(if Chinese,give standard English version);(c)the designated corres...Title Page The title page(page 1,do not number)should contain these elements:(a)full title;(b)Each authors'names,academic degrees,and affiliations(if Chinese,give standard English version);(c)the designated corresponding author's name,mailing address,telephone and fax numbers,and e-mail address;(d)source(s)of financial support of the study;(e)the total word count of the manuscript,including the title page,abstract,text,references,tables,and figures legends.展开更多
Objective:To evaluate and compare coagulation and hematological parameters in hypertensive and normotensive pregnant women.Methods:This present cross-sectional study was carried out in the Departments of Pathology and...Objective:To evaluate and compare coagulation and hematological parameters in hypertensive and normotensive pregnant women.Methods:This present cross-sectional study was carried out in the Departments of Pathology and Obstetrics&Gynaecology at Dr.D.Y.Patil Medical College,Hospital&Research Centre,Pimpri,Pune,India from September 2023 to March 2025.Hematological parameters[platelet count,mean platelet volume(MPV),platelet distribution width(PDW)]were analyzed using an automated hematology analyzer,while coagulation parameters[prothrombin time(PT)/international normalised ratio,activated partial thromboplastin time(aPTT),and D-dimer]were assessed by standard automated assays.Results were compared between normotensive and hypertensive groups and correlated with disease severity.Results:The study included 212 antenatal females,with 106 normotensive pregnant women and 106 hypertensive women.Hypertensive women include cases of gestational hypertension(n=55);mild preeclampsia(n=39),and severe preeclampsia(n=12).A significant progressive decrease in platelet count and significant increases in MPV,PDW,PT,aPTT,and D-dimer levels were associated with increasing severity of pregnancy-induced hypertension(P<0.001).Women with severe preeclampsia had the lowest mean platelet counts and the highest coagulation parameter values compared to women with gestational hypertension,mild preeclampsia,and normotensive pregnancies.These findings indicate enhanced platelet activation,endothelial dysfunction,and activation of the coagulation–fibrinolytic system with worsening disease severity.Conclusions:Significant hematologic and coagulation abnormalities were present in women with pregnancy-induced hypertension.For better maternal-fetal outcomes and early management,routine monitoring is essential.展开更多
A high-sensitivity,low-noise single photon avalanche diode(SPAD)detector was presented based on a 180 nm BCD process.The proposed device utilizes a p-implant layer/high-voltage n-well(HVNW)junction to form a deep aval...A high-sensitivity,low-noise single photon avalanche diode(SPAD)detector was presented based on a 180 nm BCD process.The proposed device utilizes a p-implant layer/high-voltage n-well(HVNW)junction to form a deep avalanche multiplication region for near-infrared(NIR)sensitivity enhancement.By optimizing the device size and electric field of the guard ring,the fill factor(FF)is significantly improved,further increasing photon detection efficiency(PDE).To solve the dark noise caused by the increasing active diameter,a field polysilicon gate structure connected to the p+anode was investigated,effectively suppressing dark count noise by 76.6%.It is experimentally shown that when the active diameter increases from 5 to 10μm,the FF is significantly improved from 20.7%to 39.1%,and thus the peak PDE also rises from 13.3%to 25.8%.At an excess bias voltage of 5 V,a NIR photon detection probability(PDP)of 6.8%at 905 nm,a dark count rate(DCR)of 2.12 cps/μm^(2),an afterpulsing probability(AP)of 1.2%,and a timing jitter of 216 ps are achieved,demonstrating excellent single photon detection performance.展开更多
A quantitative survey of rice planthoppers in paddy fields is important to assess the population density and make forecasting decisions. Manual rice planthopper survey methods in paddy fields are time-consuming, fatig...A quantitative survey of rice planthoppers in paddy fields is important to assess the population density and make forecasting decisions. Manual rice planthopper survey methods in paddy fields are time-consuming, fatiguing and tedious. This paper describes a handheld device for easily capturing planthopper images on rice stems and an automatic method for counting rice planthoppers based on image processing. The handheld device consists of a digital camera with WiFi, a smartphone and an extrendable pole. The surveyor can use the smartphone to control the camera, which is fixed on the front of the pole by WiFi, and to photograph planthoppers on rice stems. For the counting of planthoppers on rice stems, we adopt three layers of detection that involve the following：（a） the first layer of detection is an AdaBoost classifier based on Haar features;（b） the second layer of detection is a support vector machine（SVM） classifier based on histogram of oriented gradient（HOG） features;（c） the third layer of detection is the threshold judgment of the three features. We use this method to detect and count whiteback planthoppers（Sogatella furcifera） on rice plant images and achieve an 85.2% detection rate and a 9.6% false detection rate. The method is easy, rapid and accurate for the assessment of the population density of rice planthoppers in paddy fields.展开更多
基金supported by the Deanship of Scientific Research,Vice Presidency for Graduate Studies and Scientific Research,King Faisal University,Saudi Arabia,Grant No.KFU250098.
文摘In this study,an automated multimodal system for detecting,classifying,and dating fruit was developed using a two-stage YOLOv11 pipeline.In the first stage,the YOLOv11 detection model locates individual date fruits in real time by drawing bounding boxes around them.These bounding boxes are subsequently passed to a YOLOv11 classification model,which analyzes cropped images and assigns class labels.An additional counting module automatically tallies the detected fruits,offering a near-instantaneous estimation of quantity.The experimental results suggest high precision and recall for detection,high classification accuracy(across 15 classes),and near-perfect counting in real time.This paper presents a multi-stage pipeline for date fruit detection,classification,and automated counting,employing YOLOv11-based models to achieve high accuracy while maintaining real-time throughput.The results demonstrated that the detection precision exceeded 90%,the classification accuracy approached 92%,and the counting module correlated closely with the manual tallies.These findings confirm the potential of reducing manual labour and enhancing operational efficiency in post-harvesting processes.Future studies will include dataset expansion,user-centric interfaces,and integration with harvesting robotics.
基金funded by the National Natural Science Foundation of China(62273213,62472262,62572287)Natural Science Foundation of Shandong Province(ZR2024MF144)+1 种基金Natural Science Foundation of Shandong Province for Innovation and Development Joint Funds(ZR2022LZH001)Taishan Scholarship Construction Engineering.
文摘Accurately counting dense objects in complex and diverse backgrounds is a significant challenge in computer vision,with applications ranging from crowd counting to various other object counting tasks.To address this,we propose HUANNet(High-Resolution Unified Attention Network),a convolutional neural network designed to capture both local features and rich semantic information through a high-resolution representation learning framework,while optimizing computational distribution across parallel branches.HUANNet introduces three core modules:the High-Resolution Attention Module(HRAM),which enhances feature extraction by optimizing multiresolution feature fusion;the Unified Multi-Scale Attention Module(UMAM),which integrates spatial,channel,and convolutional kernel information through an attention mechanism applied across multiple levels of the network;and the Grid-Assisted Point Matching Module(GPMM),which stabilizes and improves point-to-point matching by leveraging grid-based mechanisms.Extensive experiments show that HUANNet achieves competitive results on the ShanghaiTech Part A/B crowd counting datasets and sets new state-of-the-art performance on dense object counting datasets such as CARPK and XRAY-IECCD,demonstrating the effectiveness and versatility of HUANNet.
基金funded by the National Key Research and Development Program of China(Award Number:2022YFC3202104)。
文摘Environmental DNA(e DNA)methods have emerged as a promising tool for studying a broad spectrum of biological taxa.However,metabarcoding studies of avian biodiversity using e DNA have received little attention.In this study,we compared waterbird biodiversity derived from e DNA metabarcoding with that obtained from traditional point counting surveys at 23 sites in Tai Lake of eastern China and evaluated the accuracy of e DNA metabarcoding for waterbird community studies.The point counting method recorded a higher total number of waterbird species(22)compared to the e DNA technique(16).While e DNA achieved a 74.5%detection rate for waterbird species and was able to identify a significantly greater number of species(12.48±1.97)at each sampling site than point counting method(6.13±2.69),particularly highlighting several rare and elusive species,it failed to detect some species commonly observed by the point counting method.The alpha diversity analysis revealed no significant differences in waterbird diversity between the e DNA method and the point counting method,except that the e DNA method exhibited lower Pielou evenness.Waterbird e DNA sequencing abundance correlated significantly with species occurrence,whereas Spearman's analysis indicated no significant difference between e DNA sequence abundance and species abundance from the point counting method.e DNA method detected no significant difference in waterbird composition between sampling sites,while the point counting method revealed significant differences.Consequently,e DNA is an effective complementary tool for assessing the diversity of wintering waterbirds in lakes,though it is unable to capture the full diversity of waterbird communities.It is crucial to develop sampling strategies that comprehensively monitor species composition and integrate e DNA with traditional survey methods for accurate evaluation of community structure.
基金supported by the Natural Science Foundation of China(No.32171264 and No.81974226)the Sichuan Science and Technology Program(2023NSFSC1609)。
文摘According to the World Health Organization(WHO)manual,sperm concentration should be measured using an improved Neubauer hemocytometer,while sperm motility should be measured by manual assessment.However,in China,thousands of laboratories do not use the improved Neubauer hemocytometer or method;instead,the Makler counting chamber is one of the most widely used chambers.To study sources of error that could impact the measurement of the apparent concentration and motility of sperm using the Makler counting chamber and to verify its accuracy for clinical application,67 semen samples from patients attending the Department of Andrology,West China Second University Hospital,Sichuan University(Chengdu,China)between 13 September 2023 and 27 September 2023,were included.Compared with applying the cover glass immediately,delaying the application of the cover glass for 5 s,10 s,and 30 s resulted in average increases in the sperm concentration of 30.3%,74.1%,and 107.5%,respectively(all P<0.0001)and in the progressive motility(PR)of 17.7%,30.8%,and 39.6%,respectively(all P<0.0001).However,when the semen specimens were fixed with formaldehyde,a delay in the application of the cover glass for 5 s,10 s,and 30 s resulted in an average increase in the sperm concentration of 6.7%,10.8%,and 14.6%,respectively,compared with immediate application of the cover glass.The accumulation of motile sperm due to delays in the application of the cover glass is a significant source of error with the Makler counting chamber and should be avoided.
文摘The analysis of the ejaculate,better known as spermiogram,represents the first and main step to identify whether a series of sperm quality parameters are within the norm and therefore are consistent with normal sperm fertilizing capacity.Among these,sperm concentration and motility are the first parameters to be evaluated through an estimation carried out by expert examiners.
基金supported by the National Natural Science Foundation of China(Nos.22125404,92068118,21874105)the Natural Science Basic Research Program of Shaanxi Province(Nos.2023-JCJQ-13,2020JQ-021)the Innovation Capability Support Program of Shaanxi Province(No.2023-CX-TD-62)。
文摘Characterization of the distribution and accurate counting of RNA molecules in the context of tissues is necessary to understand their complexity and heterogeneity.Single-molecule fluorescence in situ hybridization reveals the abundance and distribution of RNA and resolves different cell types in complex tissues.Especially,off-target binding and nonspecific adsorption of probes are prone to producing nonspecific amplification.Herein,we present highly de-noising amplified imaging,which leverages a sitespecific cleavage-amplifying design to achieve accurate counting of RNA in tissues.Our method avoids adding probe as primer,decreases nonspecific spots of single cells from 7 to nearly zero,and enables RNA imaging in uncleared tissue sections with nearly zero noise.We demonstrate the efficacy of this method on various thickness of mouse tissue sections.We envision this approach will serve as a tool to revealing the information content from patient samples for biomedical purpose.
基金Henan Province University Science and Technology Innovation Team Support Program Project(22IRTSTHN005)..
文摘Aiming at problems such as large errors and low efficiency in manual counting of drill pipes during drilling depth measurement,an intelligent detection and counting method for the small targets at the end of drill pipes based on the improved YOLO11n is proposed.This method realizes the high-precision detection of targets at drill pipe ends in the image by optimizing the target detection model,and combines a post-processing correction mechanism to improve the drill pipe counting accuracy.In order to alleviate the low-precision problem of YOLO11n algorithm for small target recognition in the complex underground background,the YOLO11n algorithm is improved.First,the key module C3k2 in the backbone network was improved,and Poly Kernel Inception(PKI)Block was introduced to replace Bottleneck in it to fully integrate the target context information and the model’s capability of feature extraction;Second,within the model’s neck network,a new feature fusion pyramid ISOP(Improved Small Object Pyramid)is proposed,SPDConv is introduced to strengthen the P2 feature,and CSP and OmniKernel are combined to integrate multi-scale features;Finally,the default loss function is substituted with Powerful-IoU(PIoU)to solve the anchor box expansion problem.On the self-built dataset,experimental verification was conducted.The findings showed that the Recall rose by 6.4%,mAP@0.5 increased by 4.5%,and mAP@0.5:0.95 improved by 6%compared with the baseline model,effectively solving the issues of false detection and missed detection problems in small target detection task.Meanwhile,we conducted counting tests on drilling videos from 5 different scenarios,achieving an average accuracy of 97.3%,which meets the accuracy needs for drill pipe recognition and counting in coal mine drilling sites.The research findings offer theoretical basis and technical backing for promoting the intelligent development of coal mine gas extraction drilling sites.
基金supported by National Natural Science Foundation of China(NSFC)(Nos.12475200 and 12275296)Joint Fund of Research utilizing Large-Scale Scientific Facility of the NSFC and CAS(No.U2032114)Institute of High Energy Physics(Chinese Academy of Sciences)Innovative Project on Sciences and Technologies(Nos.E3545BU210 and E25456U210).
文摘The particle identification(PID)of hadrons plays a crucial role in particle physics experiments,especially in flavor physics and jet tagging.The cluster counting method,which measures the number of primary ionizations in gaseous detectors,is a promising breakthrough in PID.However,developing an effective reconstruction algorithm for cluster counting remains challenging.To address this challenge,we propose a cluster counting algorithm based on long short-term memory and dynamic graph convolutional neural networks for the CEPC drift chamber.Experiments on Monte Carlo simulated samples demonstrate that our machine learning-based algorithm surpasses traditional methods.It improves the K/πseparation of PID by 10%,meeting the PID requirements of CEPC.
基金supported by the National Natural Science Foundation of China(12171373)Chen's work also supported by the Fundamental Research Funds for the Central Universities of China(GK202207018).
文摘In this paper,we study composition operators on weighted Bergman spaces of Dirichlet series.We first establish some Littlewood-type inequalities for generalized mean counting functions.Then we give sufficient conditions for a composition operator with zero characteristic to be bounded or compact on weighted Bergman spaces of Dirichlet series.The corresponding sufficient condition for compactness in the case of positive characteristics is also obtained.
基金supported by MOE(Ministry of Education in China)Project of Humanities and Social Sciences(No.19YJC760012)Key Research and Development Project of Lanzhou Jiaotong University(No.ZDYF2304).
文摘Aiming at the problem of inaccurate crowd counting and location in dense scenes,a dynamic region-sensing crowd counting and location method based on high-resolution fusion was proposed.Firstly,U-HRNet was used as the main backbone to extract highresolution features of the population and enhance the ability of feature extraction with different resolutions.Then,the dynamic regional awareness attention module was designed to make full use of the global and local feature information,refine the differentiated learning of target feature and background feature,reduce the interference of background feature,and improve the positioning performance of the model.Finally,the predicted threshold map and confidence map were input into the binarization module to output the prediction and counting results of the crowd independent individual target.Experimental results showed that the proposed method achieved good performance of counting and positioning in different scenarios.
基金We are greateful to the National Narural Science Foundation of China(No.20455017)Science and Technology Committee of Shanghai Municipal(No.0452nm084).
文摘A novel nano crystalline Ag2O2-PbO2 film chemically modified electrode (CME) was prepared and the CME was characterized by X-ray diffractometer (XRD) and atomic force microscope (AFM). By chronoamperometry, the nano Ag2O2-PbO2 CME was used as bioelectro- chemical sensor to determine the population of Escherichia coli (E. coli) in water. Compared with conventional methods, it is found that the technique we used is fast and convenient in counting E. coli.
基金supported in part by the Natural Science Foundation of Shaanxi Province of China under Grant 2024JC-YBQN-0695.
文摘Regular detection of pavement cracks is essential for infrastructure maintenance.However,existing methods often ignore the challenges such as the continuous evolution of crack features between video frames and the difficulty of defect quantification.To this end,this paper proposes an integrated framework for pavement crack detection,segmentation,tracking and counting based on Transformer.Firstly,we design theVitSeg-Det network,which is an integrated detection and segmentation network that can accurately locate and segment tiny cracks in complex scenes.Second,the TransTra-Count system is developed to automatically count the number of defects by combining defect tracking with width estimation.Finally,we conduct experimental verification on three datasets.The results show that the proposed method is superior to the existing deep learning methods in detection accuracy.In addition,the actual scene video test shows that the framework can accurately label the defect location and output the number of defects in real time.
文摘Oligospermia,characterized by a low sperm count in semen,is a major cause of male infertility and may result from various factors including infections,lifestyle choices,retrograde ejaculation,tumors,hormonal imbalances,drug treatments,and environmental exposures.Animal models play a crucial role in understanding its pathophysiology,identifying therapeutic targets,and evaluating potential treatments.The current review highlights experimental models used to induce oligospermia in laboratory animals,focusing on chemical,surgical,and radiation-based approaches.We review the reversible and irreversible methods commonly employed to study impaired spermatogenesis,along with the key endpoints used to assess testicular function and sperm quality.Standard housing and feeding conditions relevant to oligospermia research are also summarized to support reproducibility and methodological consistency in experimental designs.
文摘Title Page The title page(page 1,do not number)should contain these elements:(a)full title;(b)Each authors'names,academic degrees,and affiliations(if Chinese,give standard English version);(c)the designated corresponding author's name,mailing address,telephone and fax numbers,and e-mail address;(d)source(s)of financial support of the study;(e)the total word count of the manuscript,including the title page,abstract,text,references,tables,and figures legends.
文摘Objective:To evaluate and compare coagulation and hematological parameters in hypertensive and normotensive pregnant women.Methods:This present cross-sectional study was carried out in the Departments of Pathology and Obstetrics&Gynaecology at Dr.D.Y.Patil Medical College,Hospital&Research Centre,Pimpri,Pune,India from September 2023 to March 2025.Hematological parameters[platelet count,mean platelet volume(MPV),platelet distribution width(PDW)]were analyzed using an automated hematology analyzer,while coagulation parameters[prothrombin time(PT)/international normalised ratio,activated partial thromboplastin time(aPTT),and D-dimer]were assessed by standard automated assays.Results were compared between normotensive and hypertensive groups and correlated with disease severity.Results:The study included 212 antenatal females,with 106 normotensive pregnant women and 106 hypertensive women.Hypertensive women include cases of gestational hypertension(n=55);mild preeclampsia(n=39),and severe preeclampsia(n=12).A significant progressive decrease in platelet count and significant increases in MPV,PDW,PT,aPTT,and D-dimer levels were associated with increasing severity of pregnancy-induced hypertension(P<0.001).Women with severe preeclampsia had the lowest mean platelet counts and the highest coagulation parameter values compared to women with gestational hypertension,mild preeclampsia,and normotensive pregnancies.These findings indicate enhanced platelet activation,endothelial dysfunction,and activation of the coagulation–fibrinolytic system with worsening disease severity.Conclusions:Significant hematologic and coagulation abnormalities were present in women with pregnancy-induced hypertension.For better maternal-fetal outcomes and early management,routine monitoring is essential.
基金supported by the National Natural Science Foundation of China under Grant 62171233the Natural Science Foundation of China,Jiangsu Province under Grant BK20241891the Jiangsu Province Graduate Research and Practice Innovation Plan under Grants SJCX24_0313 and KYCX24_1169。
文摘A high-sensitivity,low-noise single photon avalanche diode(SPAD)detector was presented based on a 180 nm BCD process.The proposed device utilizes a p-implant layer/high-voltage n-well(HVNW)junction to form a deep avalanche multiplication region for near-infrared(NIR)sensitivity enhancement.By optimizing the device size and electric field of the guard ring,the fill factor(FF)is significantly improved,further increasing photon detection efficiency(PDE).To solve the dark noise caused by the increasing active diameter,a field polysilicon gate structure connected to the p+anode was investigated,effectively suppressing dark count noise by 76.6%.It is experimentally shown that when the active diameter increases from 5 to 10μm,the FF is significantly improved from 20.7%to 39.1%,and thus the peak PDE also rises from 13.3%to 25.8%.At an excess bias voltage of 5 V,a NIR photon detection probability(PDP)of 6.8%at 905 nm,a dark count rate(DCR)of 2.12 cps/μm^(2),an afterpulsing probability(AP)of 1.2%,and a timing jitter of 216 ps are achieved,demonstrating excellent single photon detection performance.
基金the National Natural Science Foundation of China (31071678)the National High Technology Research and Development Program of China (863 Program, 2013AA102402)Zhejiang Provincial Natural Science Foundation of China (LY13C140009)
文摘A quantitative survey of rice planthoppers in paddy fields is important to assess the population density and make forecasting decisions. Manual rice planthopper survey methods in paddy fields are time-consuming, fatiguing and tedious. This paper describes a handheld device for easily capturing planthopper images on rice stems and an automatic method for counting rice planthoppers based on image processing. The handheld device consists of a digital camera with WiFi, a smartphone and an extrendable pole. The surveyor can use the smartphone to control the camera, which is fixed on the front of the pole by WiFi, and to photograph planthoppers on rice stems. For the counting of planthoppers on rice stems, we adopt three layers of detection that involve the following：（a） the first layer of detection is an AdaBoost classifier based on Haar features;（b） the second layer of detection is a support vector machine（SVM） classifier based on histogram of oriented gradient（HOG） features;（c） the third layer of detection is the threshold judgment of the three features. We use this method to detect and count whiteback planthoppers（Sogatella furcifera） on rice plant images and achieve an 85.2% detection rate and a 9.6% false detection rate. The method is easy, rapid and accurate for the assessment of the population density of rice planthoppers in paddy fields.
