BACKGROUND Certain subgroups are at an increased risk of false fecal immunochemical test(FIT)results;however,related studies are limited,and the available evidence is conflicting.AIM To evaluate factors associated wit...BACKGROUND Certain subgroups are at an increased risk of false fecal immunochemical test(FIT)results;however,related studies are limited,and the available evidence is conflicting.AIM To evaluate factors associated with false-positive and false-negative FIT results.METHODS This retrospective study was based on the database of the Tianjin Colorectal Cancer Screening Program from 2012 to 2020.A total of 4129947 residents aged 40-74 years completed at least one FIT.Of these,24890 asymptomatic participants who underwent colonoscopy examinations and completed lifestyle questionnaires were included in the analysis.Multivariable logistic regression was performed to identify the factors associated with false FIT results.RESULTS Among the overall screening population,88687(2.15%)participants tested positive for FIT.The sensitivity,specificity,positive predictive value,and negative predictive value of FIT for advanced neoplasms were 58.2%,44.8%,9.7%,and 91.3%,respectively.Older age,female sex,smoking,alcohol consumption,higher body mass index,and hemorrhoids were significantly associated with increased odds of false-positive and lower odds of falsenegative FIT results.Moreover,features of high-grade dysplasia or villous for advanced adenoma and the presence of cancer were also associated with lower odds of false-negative results,while irregular exercise and diverticulum were associated with higher odds of false-positive results.CONCLUSION FIT results may be inaccurate in certain subgroups.Our results provide important evidence for further individualization of screening strategies.展开更多
Despite advancements in neuroimaging,false positive diagnoses of intracranial aneurysms remain a significant concern.This article examines the causes,prevalence,and implications of such false-positive diagnoses.We dis...Despite advancements in neuroimaging,false positive diagnoses of intracranial aneurysms remain a significant concern.This article examines the causes,prevalence,and implications of such false-positive diagnoses.We discuss how conditions like arterial occlusion with vascular stump formation and infundibular widening can mimic aneurysms,particularly in the anterior circulation.The article compares various imaging modalities,including computer tomography angiogram,magnetic resonance imaging/angiography,and digital subtraction angiogram,highlighting their strengths and limitations.We emphasize the im-portance of accurate differentiation to avoid unnecessary surgical interventions.The potential of emerging technologies,such as high-resolution vessel wall ima-ging and deep neural networks for automated detection,is explored as promising avenues for improving diagnostic accuracy.This manuscript underscores the need for continued research and clinical vigilance in the diagnosis of intracranial aneurysms.展开更多
Pedestrian detection has been a hot spot in computer vision over the past decades due to the wide spectrum of promising applications,and the major challenge is false positives that occur during pedestrian detection.Th...Pedestrian detection has been a hot spot in computer vision over the past decades due to the wide spectrum of promising applications,and the major challenge is false positives that occur during pedestrian detection.The emergence of various Convolutional Neural Network-based detection strategies substantially enhances pedestrian detection accuracy but still does not solve this problem well.This paper deeply analyzes the detection framework of the two-stage CNN detection methods and finds out false positives in detection results are due to its training strategy misclassifying some false proposals,thus weakening the classification capability of the following subnetwork and hardly suppressing false ones.To solve this problem,this paper proposes a pedestrian-sensitive training algorithm to help two-stage CNN detection methods effectively learn to distinguish the pedestrian and non-pedestrian samples and suppress the false positives in the final detection results.The core of the proposed algorithm is to redesign the training proposal generating scheme for the two-stage CNN detection methods,which can avoid a certain number of false ones that mislead its training process.With the help of the proposed algorithm,the detection accuracy of the MetroNext,a smaller and more accurate metro passenger detector,is further improved,which further decreases false ones in its metro passenger detection results.Based on various challenging benchmark datasets,experiment results have demonstrated that the feasibility of the proposed algorithm is effective in improving pedestrian detection accuracy by removing false positives.Compared with the existing state-of-the-art detection networks,PSTNet demonstrates better overall prediction performance in accuracy,total number of parameters,and inference time;thus,it can become a practical solution for hunting pedestrians on various hardware platforms,especially for mobile and edge devices.展开更多
The earthquake early warning system is an effective means of disaster reduction to reduce losses caused by earthquakes,it can release earthquake warning information to the public before destructive seismic waves reach...The earthquake early warning system is an effective means of disaster reduction to reduce losses caused by earthquakes,it can release earthquake warning information to the public before destructive seismic waves reach the warning target area,and carry out automatic disposal of lifeline engineering facilities.Through the construction of the National Earthquake Intensity Rapid Reporting and Early Warning Project,an earthquake early warning network consisting of over 1900 monitoring stations has been established in the Beijing-Tianjin-Hebei Urban Agglomeration.The early warning system has achieved second level earthquake warning and minute level intensity rapid reporting.The implementation of these functions relies on the system's ability to timely,accurately,and reliably identify seismic waves.But with the development of social economy,the background noise of earthquake observation environment is becoming increasingly complex,which brings certain challenges to earthquake wave recognition,some interference events have the risk of triggering the earthquake warning system incorrectly.Therefore,this article focuses on seismic wave recognition in complex noise environments and proposes a seismic wave detection method based on triangulation to enhance the antiinterference ability and recognition accuracy of early warning systems.展开更多
Flower-infecting fungi have caused many economically important diseases in crop production.The fungal pathogen Ustilaginoidea virens infects developing rice florets,causing false smut disease,which leads to reduced gr...Flower-infecting fungi have caused many economically important diseases in crop production.The fungal pathogen Ustilaginoidea virens infects developing rice florets,causing false smut disease,which leads to reduced grain yield and quality,as well as contamination with mycotoxins that pose hazards to human health and food security.To ensure rice production,substantial efforts have been made to understand the interaction between rice and U.virens.In this review,we summarize the current understanding of rice resistance mechanisms to U.virens.We discuss the evaluation of false smut resistance,quantitative resistance loci,potential defense strategies of rice panicles,pathogen effector-driven identification of resistance-related genes,and engineering of false smut resistance.We conclude by proposing an integrated defense system that includes disease avoidance,immune response,metabolic adaptation,and the inhibition of susceptibility factors.Furthermore,we outline four critical stages of interaction between rice and U.virens that are essential for understanding and enhancing organ-specific rice resistance to false smut disease.展开更多
False Data Injection Attacks(FDIAs)pose a critical security threat to modern power grids,corrupting state estimation and enabling malicious control actions that can lead to severe consequences,including cascading fail...False Data Injection Attacks(FDIAs)pose a critical security threat to modern power grids,corrupting state estimation and enabling malicious control actions that can lead to severe consequences,including cascading failures,large-scale blackouts,and significant economic losses.While detecting attacks is important,accurately localizing compromised nodes or measurements is even more critical,as it enables timely mitigation,targeted response,and enhanced system resilience beyond what detection alone can offer.Existing research typically models topological features using fixed structures,which can introduce irrelevant information and affect the effectiveness of feature extraction.To address this limitation,this paper proposes an FDIA localization model with adaptive neighborhood selection,which dynamically captures spatial dependencies of the power grid by adjusting node relationships based on data-driven similarities.The improved Transformer is employed to pre-fuse global spatial features of the graph,enriching the feature representation.To improve spatio-temporal correlation extraction for FDIA localization,the proposed model employs dilated causal convolution with a gating mechanism combined with graph convolution to capture and fuse long-range temporal features and adaptive topological features.This fully exploits the temporal dynamics and spatial dependencies inherent in the power grid.Finally,multi-source information is integrated to generate highly robust node embeddings,enhancing FDIA detection and localization.Experiments are conducted on IEEE 14,57,and 118-bus systems,and the results demonstrate that the proposed model substantially improves the accuracy of FDIA localization.Additional experiments are conducted to verify the effectiveness and robustness of the proposed model.展开更多
Automatic Dependent Surveillance-Broadcast(ADS-B)technology,with its open signal sharing,faces substantial security risks from false signals and spoofing attacks when broadcasting Unmanned Aerial Vehicle(UAV)informati...Automatic Dependent Surveillance-Broadcast(ADS-B)technology,with its open signal sharing,faces substantial security risks from false signals and spoofing attacks when broadcasting Unmanned Aerial Vehicle(UAV)information.This paper proposes a security position verification technique based on Multilateration(MLAT)to detect false signals,ensuring UAV safety and reliable airspace operations.First,the proposed method estimates the current position of the UAV by calculating the Time Difference of Arrival(TDOA),Time Sum of Arrival(TSOA),and Angle of Arrival(AOA)information.Then,this estimated position is compared with the ADS-B message to eliminate false UAV signals.Furthermore,a localization model based on TDOA/TSOA/AOA is established by utilizing reliable reference sources for base station time synchronization.Additionally,an improved Chan-Taylor algorithm is developed,incorporating the Constrained Weighted Least Squares(CWLS)method to initialize UAV position calculations.Finally,a false signal detection method is proposed to distinguish between true and false positioning targets.Numerical simulation results indicate that,at a positioning error threshold of 150 m,the improved Chan-Taylor algorithm based on TDOA/TSOA/AOA achieves 100%accuracy coverage,significantly enhancing localization precision.And the proposed false signal detection method achieves a detection accuracy rate of at least 90%within a 50-meter error range.展开更多
Although digital changes in power systems have added more ways to monitor and control them,these changes have also led to new cyber-attack risks,mainly from False Data Injection(FDI)attacks.If this happens,the sensors...Although digital changes in power systems have added more ways to monitor and control them,these changes have also led to new cyber-attack risks,mainly from False Data Injection(FDI)attacks.If this happens,the sensors and operations are compromised,which can lead to big problems,disruptions,failures and blackouts.In response to this challenge,this paper presents a reliable and innovative detection framework that leverages Bidirectional Long Short-Term Memory(Bi-LSTM)networks and employs explanatory methods from Artificial Intelligence(AI).Not only does the suggested architecture detect potential fraud with high accuracy,but it also makes its decisions transparent,enabling operators to take appropriate action.Themethod developed here utilizesmodel-free,interpretable tools to identify essential input elements,thereby making predictions more understandable and usable.Enhancing detection performance is made possible by correcting class imbalance using Synthetic Minority Over-sampling Technique(SMOTE)-based data balancing.Benchmark power system data confirms that the model functions correctly through detailed experiments.Experimental results showed that Bi-LSTM+Explainable AI(XAI)achieved an average accuracy of 94%,surpassing XGBoost(89%)and Bagging(84%),while ensuring explainability and a high level of robustness across various operating scenarios.By conducting an ablation study,we find that bidirectional recursive modeling and ReLU activation help improve generalization and model predictability.Additionally,examining model decisions through LIME enables us to identify which features are crucial for making smart grid operational decisions in real time.The research offers a practical and flexible approach for detecting FDI attacks,improving the security of cyber-physical systems,and facilitating the deployment of AI in energy infrastructure.展开更多
A security issue with multi-sensor unmanned aerial vehicle(UAV)cyber physical systems(CPS)from the viewpoint of a false data injection(FDI)attacker is investigated in this paper.The FDI attacker can employ attacks on ...A security issue with multi-sensor unmanned aerial vehicle(UAV)cyber physical systems(CPS)from the viewpoint of a false data injection(FDI)attacker is investigated in this paper.The FDI attacker can employ attacks on feedback and feed-forward channels simultaneously with limited resource.The attacker aims at degrading the UAV CPS's estimation performance to the max while keeping stealthiness characterized by the Kullback-Leibler(K-L)divergence.The attacker is resource limited which can only attack part of sensors,and the attacked sensor as well as specific forms of attack signals at each instant should be considered by the attacker.Also,the sensor selection principle is investigated with respect to time invariant attack covariances.Additionally,the optimal switching attack strategies in regard to time variant attack covariances are modeled as a multi-agent Markov decision process(MDP)with hybrid discrete-continuous action space.Then,the multi-agent MDP is solved by utilizing the deep Multi-agent parameterized Q-networks(MAPQN)method.Ultimately,a quadrotor near hover system is used to validate the effectiveness of the results in the simulation section.展开更多
With the explosive growth of false information on social media platforms, the automatic detection of multimodalfalse information has received increasing attention. Recent research has significantly contributed to mult...With the explosive growth of false information on social media platforms, the automatic detection of multimodalfalse information has received increasing attention. Recent research has significantly contributed to multimodalinformation exchange and fusion, with many methods attempting to integrate unimodal features to generatemultimodal news representations. However, they still need to fully explore the hierarchical and complex semanticcorrelations between different modal contents, severely limiting their performance detecting multimodal falseinformation. This work proposes a two-stage detection framework for multimodal false information detection,called ASMFD, which is based on image aesthetic similarity to segment and explores the consistency andinconsistency features of images and texts. Specifically, we first use the Contrastive Language-Image Pre-training(CLIP) model to learn the relationship between text and images through label awareness and train an imageaesthetic attribute scorer using an aesthetic attribute dataset. Then, we calculate the aesthetic similarity betweenthe image and related images and use this similarity as a threshold to divide the multimodal correlation matrixinto consistency and inconsistencymatrices. Finally, the fusionmodule is designed to identify essential features fordetectingmultimodal false information. In extensive experiments on four datasets, the performance of the ASMFDis superior to state-of-the-art baseline methods.展开更多
Rice false smut,caused by Ustilaginoidea virens,is a devastating disease that greatly reduces rice yield and quality.However,controlling rice false smut disease is challenging due to the unique infection mode of U.vir...Rice false smut,caused by Ustilaginoidea virens,is a devastating disease that greatly reduces rice yield and quality.However,controlling rice false smut disease is challenging due to the unique infection mode of U.virens.Therefore,there is a need for early diagnosis and monitoring techniques to prevent the spread of this disease.Lateral flow strip-based recombinase polymerase amplification(LF-RPA)overcomes the limitations of current U.virens detection technologies,which are time-consuming,require delicate equipment,and have a high false-positive rate.In this study,we used a comparative genomics approach to identify Uv_3611,a specific gene of U.virens,as the target for the LF-RPA assay.The designed primers and probe efffectively detected the genomic DNA(gDNA)of U.virens and demonstrated no cross-reactivity with related pathogens.Under optimal conditions,the LF-RPA assay demonstrated a sensitivity of 10 pg of U.virens gDNA.Additionally,by incorporating a simplified PEG-NaOH method for plant DNA extraction,the LF-RPA assay enabled the detection of U.virens in rice spikelets within 30 min,without the need for specialized equipment.Furthermore,the LF-RPA assay successfully detected U.virens in naturally infected rice and seed samples in the field.Therefore,the LF-RPA assay is sensitive,efficient,and convenient,and could be developed as a kit for monitoring rice false smut disease in the field.展开更多
Overlooking the issue of false alarm suppression in heterogeneous change detection leads to inferior detection per-formance.This paper proposes a method to handle false alarms in heterogeneous change detection.A light...Overlooking the issue of false alarm suppression in heterogeneous change detection leads to inferior detection per-formance.This paper proposes a method to handle false alarms in heterogeneous change detection.A lightweight network of two channels is bulit based on the combination of convolutional neural network(CNN)and graph convolutional network(GCN).CNNs learn feature difference maps of multitemporal images,and attention modules adaptively fuse CNN-based and graph-based features for different scales.GCNs with a new kernel filter adaptively distinguish between nodes with the same and those with different labels,generating change maps.Experimental evaluation on two datasets validates the efficacy of the pro-posed method in addressing false alarms.展开更多
Introduction: HIV screening tests are routinely conducted on dialysis patients as the constant exposure of their blood during the dialysis process makes them a reasonable risk for blood-borne infections. However, in l...Introduction: HIV screening tests are routinely conducted on dialysis patients as the constant exposure of their blood during the dialysis process makes them a reasonable risk for blood-borne infections. However, in low prevalence settings, where HIV rates are <0.1% of the population, false positive results are more likely. This results in apprehension in the dialysis unit as breaches in infectious disease protocols could be presumed. This is illustrated in the case report below. Case Summary: A 62-year-old male Saudi end-stage kidney disease patient secondary to DM nephropathy began dialysis a year before presentation in a hemodialysis center in Saudi Arabia. Routine screening tests done at the start of dialysis revealed negative Hepatitis C, HIV 1 and 2 screening but a positive Hepatitis B surface antigen screen. The patient went for holiday dialysis at another facility and had a routine fourth-generation HIV test done which was positive. A confirmatory HIV PCR test was negative. Conclusion: This case highlights the need for caution in interpreting highly sensitive and specific HIV screening tests in a low-prevalence setting. Routine screening beyond the national recommendation may not be necessary in low-prevalence areas.展开更多
A recombinant inbred line （RILs） population with 157 lines derived from an inter-subspecies cross of Daguandao （japonica）/IR28 （indica） by the single seed de-scent method was used to detect quantitative trait lo...A recombinant inbred line （RILs） population with 157 lines derived from an inter-subspecies cross of Daguandao （japonica）/IR28 （indica） by the single seed de-scent method was used to detect quantitative trait loci （QTLs） conferring resistance to rice false smut caused by Ustilaginoidea virens（Cooke） Takahashi in Nanjing and Yangzhou. The disease rate index of the two parents and 157 RILs caused by rice false smut were scored and the QTLs for rice false smut resistance were detected accordingly by QTL Cartographer software. Eight QTLs control ing false smut resis-tance were detected on chromosomes 1, 2, 4, 8, 10, 11 and 12, respectively, with the phenotypic variance of 8.6%-22.5%. There were five QTLs detected in Nanjing and Yangzhou, respectively, and only two QTLs were found in both two years, the phenotypic variation was explained by individual QTL ranged from 18.0% to 18.9% for these two QTLs, and the additive effects of these two QTLs contributed to the 8.0%-14.6% decrease of disease index and therefore the disease resistance increased. The direction of the additive effects at six loci qFsr1, qFsr2, qFsr8, qFsr10a, qFsr11 and qFsr12 coincided with that predicted by phenotypes of the parents, and the IR28 al eles at these loci had positive effect against rice false smut while the negative effects were found in Daguandao al eles at qFsr4 and qFsr10b. Both qFsr10a and qFsr11 should be useful in rice breeding for resistance to rice false smut in marker-assisted selection （MAS） program.展开更多
Rice false smut disease is an increasing concern for research and production, not only because of the increasing epidemic occurrence in rice production, but also the intriguing specific pathogenesis of the disease to ...Rice false smut disease is an increasing concern for research and production, not only because of the increasing epidemic occurrence in rice production, but also the intriguing specific pathogenesis of the disease to be a unique pathological system to enrich the molecular mechanism of plant-microbe interaction. Progresses have been achieved in the pathogen phylogenetic placement, the alternative hosts, the pathogen morphology and diversity, the toxins generated by false smut balls, the artificial inoculation method, and the pathogen transformation as well as rice resistance to the disease. However, it is still controversy on the infection process. It is not clear how the life cycle of this pathogen is coupled with the disease cycle. This review summarized our current understanding on the pathogen, the pathogenesis, and the rice resistance to the disease. Future work should pay attention to developing a more rapid and effective system to evaluate rice resistance and susceptibility to the disease, screening of rice germplasm for disease-resistance breeding, studying the resistance inheritance, and investigating the molecular mechanism of rice-false smut fungus interaction.展开更多
In order to identify the resistant gene of rice false smut in rice, a recombi- nant inbred line （RILs） population with 157 lines derived from an inter-subspecies cross of Daguandao/IR28 by the single seed descent me...In order to identify the resistant gene of rice false smut in rice, a recombi- nant inbred line （RILs） population with 157 lines derived from an inter-subspecies cross of Daguandao/IR28 by the single seed descent method was used to detect quantitative trait loci （QTLs） conferring resistance to strain Pi-1 of rice false smut caused by Usti/aginoiclea virens （Cooke） Takahashi in 2012 and 2013. The disease rate indexes of the two parents and 157 RILs caused by the strain Pi-1 of rice false smut were scored and the QTLs for rice false smut resistance were detected accordingly by QTL Cartographer software. Seven QTLs controlling false smut re- sistance were detected on chromosomes 2, 7, 8, 11 and 12, respectively, with the phenotypic variance of 8.5%-17.2%. There were four QTLs detected in 2012 and 2013, respectively, and only one QTL was found in both two years, the phenotypic variation explained by this individual QTL was 13.5% and 17.2%, and the additive effects of this QTL contributed to the 9.9% and 14.3% decrease of disease index and therefore the disease resistance increased. The direction of the additive effects at five loci qFsr2a, qFsr8a, qFsr8b, qFsr11 and qFsr12 coincided with that predicted by phenotypes of the parents, and the IR28 alleles at these loci had positive effect against rice false smut while the negative effects were found in Daguandao alleles at qFsr2b and qFsr7. The qFsr11 should be useful in rice breeding for resistance to rice false smut in marker-assisted selection （MAS） program.展开更多
[Objective] The aim was to explore the reasons of false positives in Different Display Reverse Transcription（DDRT）analysis.[Method] Soybean varieties ＂Jilin 30＂ and ＂Tongnong 13＂ were used as materials to carry ...[Objective] The aim was to explore the reasons of false positives in Different Display Reverse Transcription（DDRT）analysis.[Method] Soybean varieties ＂Jilin 30＂ and ＂Tongnong 13＂ were used as materials to carry out analysis on false positives in DDRT analysis.[Result] An important origin of false positives appeared in DDRT analysis was the non-specific amplification caused by the combination of single primer and cDNA.The parallel PCR test of single primer should be set so as to verify whether the obtained fragments were the false positives or the PCR productions combined with single primer.[Conclusion] This study had provided basis for improving the success rate of DDRT experiment.展开更多
A new modification of false position method for solving nonlinear equations is presented by applying homotopy analysis method （HAM）. Some numerical illustrations are given to show the efficiency of algorithm.
Objective To investigate if immunological factors associated with rheumatoid arthritis(RA) affect the result of human immunodeficiency virus(HIV) screening by electrochemiluminescence immunoassay(ECLIA) and enzyme-lin...Objective To investigate if immunological factors associated with rheumatoid arthritis(RA) affect the result of human immunodeficiency virus(HIV) screening by electrochemiluminescence immunoassay(ECLIA) and enzyme-linked immunosorbent assay(ELISA). Methods 100 RA cases were enrolled from January 2012 to February 2013 into this study. HIV screening was conducted with ECLIA detecting both HIV-1 p24 antigen, HIV-1 and HIV-2 antibodies, with ELISA and colloidal gold method detecting HIV-1 and HIV-2 antibodies. The samples producing positive results were submitted to the Center for Disease Control for confirmation using Western blotting method. The antibody titers of rheumatoid factors(RF) including RF-IgG, RF-IgM, RF-IgA, and CCP-IgG were analyzed by ELISA. Results The HIV positive-rate determined by ECLIA was significantly higher than that by ELISA and colloidal gold method(P<0.01). The false-positive rate of HIV screening was associated with antibody titers of RF-IgG, RF-IgM, RF-IgA, and CCP-IgG in RA(P<0.01). Conclusion Immunological factors, including RF and anti-CCP antibody, may influence the screening of HIV by ECLIA, producing false-positive result.展开更多
基金Supported by Natural Science Foundation of Tianjin,No.21JCZDJC00060 and No.21JCYBJC00180Tianjin Health and Medical Science and Technology Project,No.TJWJ2023QN040National Key Research and Development Program,No.2017YFC1700606 and No.2017YFC1700604.
文摘BACKGROUND Certain subgroups are at an increased risk of false fecal immunochemical test(FIT)results;however,related studies are limited,and the available evidence is conflicting.AIM To evaluate factors associated with false-positive and false-negative FIT results.METHODS This retrospective study was based on the database of the Tianjin Colorectal Cancer Screening Program from 2012 to 2020.A total of 4129947 residents aged 40-74 years completed at least one FIT.Of these,24890 asymptomatic participants who underwent colonoscopy examinations and completed lifestyle questionnaires were included in the analysis.Multivariable logistic regression was performed to identify the factors associated with false FIT results.RESULTS Among the overall screening population,88687(2.15%)participants tested positive for FIT.The sensitivity,specificity,positive predictive value,and negative predictive value of FIT for advanced neoplasms were 58.2%,44.8%,9.7%,and 91.3%,respectively.Older age,female sex,smoking,alcohol consumption,higher body mass index,and hemorrhoids were significantly associated with increased odds of false-positive and lower odds of falsenegative FIT results.Moreover,features of high-grade dysplasia or villous for advanced adenoma and the presence of cancer were also associated with lower odds of false-negative results,while irregular exercise and diverticulum were associated with higher odds of false-positive results.CONCLUSION FIT results may be inaccurate in certain subgroups.Our results provide important evidence for further individualization of screening strategies.
文摘Despite advancements in neuroimaging,false positive diagnoses of intracranial aneurysms remain a significant concern.This article examines the causes,prevalence,and implications of such false-positive diagnoses.We discuss how conditions like arterial occlusion with vascular stump formation and infundibular widening can mimic aneurysms,particularly in the anterior circulation.The article compares various imaging modalities,including computer tomography angiogram,magnetic resonance imaging/angiography,and digital subtraction angiogram,highlighting their strengths and limitations.We emphasize the im-portance of accurate differentiation to avoid unnecessary surgical interventions.The potential of emerging technologies,such as high-resolution vessel wall ima-ging and deep neural networks for automated detection,is explored as promising avenues for improving diagnostic accuracy.This manuscript underscores the need for continued research and clinical vigilance in the diagnosis of intracranial aneurysms.
文摘Pedestrian detection has been a hot spot in computer vision over the past decades due to the wide spectrum of promising applications,and the major challenge is false positives that occur during pedestrian detection.The emergence of various Convolutional Neural Network-based detection strategies substantially enhances pedestrian detection accuracy but still does not solve this problem well.This paper deeply analyzes the detection framework of the two-stage CNN detection methods and finds out false positives in detection results are due to its training strategy misclassifying some false proposals,thus weakening the classification capability of the following subnetwork and hardly suppressing false ones.To solve this problem,this paper proposes a pedestrian-sensitive training algorithm to help two-stage CNN detection methods effectively learn to distinguish the pedestrian and non-pedestrian samples and suppress the false positives in the final detection results.The core of the proposed algorithm is to redesign the training proposal generating scheme for the two-stage CNN detection methods,which can avoid a certain number of false ones that mislead its training process.With the help of the proposed algorithm,the detection accuracy of the MetroNext,a smaller and more accurate metro passenger detector,is further improved,which further decreases false ones in its metro passenger detection results.Based on various challenging benchmark datasets,experiment results have demonstrated that the feasibility of the proposed algorithm is effective in improving pedestrian detection accuracy by removing false positives.Compared with the existing state-of-the-art detection networks,PSTNet demonstrates better overall prediction performance in accuracy,total number of parameters,and inference time;thus,it can become a practical solution for hunting pedestrians on various hardware platforms,especially for mobile and edge devices.
基金supported by the Spark Program of Earthquake Science and Technology(No.XH23003C)。
文摘The earthquake early warning system is an effective means of disaster reduction to reduce losses caused by earthquakes,it can release earthquake warning information to the public before destructive seismic waves reach the warning target area,and carry out automatic disposal of lifeline engineering facilities.Through the construction of the National Earthquake Intensity Rapid Reporting and Early Warning Project,an earthquake early warning network consisting of over 1900 monitoring stations has been established in the Beijing-Tianjin-Hebei Urban Agglomeration.The early warning system has achieved second level earthquake warning and minute level intensity rapid reporting.The implementation of these functions relies on the system's ability to timely,accurately,and reliably identify seismic waves.But with the development of social economy,the background noise of earthquake observation environment is becoming increasingly complex,which brings certain challenges to earthquake wave recognition,some interference events have the risk of triggering the earthquake warning system incorrectly.Therefore,this article focuses on seismic wave recognition in complex noise environments and proposes a seismic wave detection method based on triangulation to enhance the antiinterference ability and recognition accuracy of early warning systems.
基金supported by grants from the Sichuan Natural Science Foundation(2024NSFSC0335 and SCCXTD-2024-SD-4 to D.-Q.L.)the National Natural Science Foundation of China(32372490 and 32072503 to J.F.)。
文摘Flower-infecting fungi have caused many economically important diseases in crop production.The fungal pathogen Ustilaginoidea virens infects developing rice florets,causing false smut disease,which leads to reduced grain yield and quality,as well as contamination with mycotoxins that pose hazards to human health and food security.To ensure rice production,substantial efforts have been made to understand the interaction between rice and U.virens.In this review,we summarize the current understanding of rice resistance mechanisms to U.virens.We discuss the evaluation of false smut resistance,quantitative resistance loci,potential defense strategies of rice panicles,pathogen effector-driven identification of resistance-related genes,and engineering of false smut resistance.We conclude by proposing an integrated defense system that includes disease avoidance,immune response,metabolic adaptation,and the inhibition of susceptibility factors.Furthermore,we outline four critical stages of interaction between rice and U.virens that are essential for understanding and enhancing organ-specific rice resistance to false smut disease.
基金supported by National Key Research and Development Plan of China(No.2022YFB3103304).
文摘False Data Injection Attacks(FDIAs)pose a critical security threat to modern power grids,corrupting state estimation and enabling malicious control actions that can lead to severe consequences,including cascading failures,large-scale blackouts,and significant economic losses.While detecting attacks is important,accurately localizing compromised nodes or measurements is even more critical,as it enables timely mitigation,targeted response,and enhanced system resilience beyond what detection alone can offer.Existing research typically models topological features using fixed structures,which can introduce irrelevant information and affect the effectiveness of feature extraction.To address this limitation,this paper proposes an FDIA localization model with adaptive neighborhood selection,which dynamically captures spatial dependencies of the power grid by adjusting node relationships based on data-driven similarities.The improved Transformer is employed to pre-fuse global spatial features of the graph,enriching the feature representation.To improve spatio-temporal correlation extraction for FDIA localization,the proposed model employs dilated causal convolution with a gating mechanism combined with graph convolution to capture and fuse long-range temporal features and adaptive topological features.This fully exploits the temporal dynamics and spatial dependencies inherent in the power grid.Finally,multi-source information is integrated to generate highly robust node embeddings,enhancing FDIA detection and localization.Experiments are conducted on IEEE 14,57,and 118-bus systems,and the results demonstrate that the proposed model substantially improves the accuracy of FDIA localization.Additional experiments are conducted to verify the effectiveness and robustness of the proposed model.
基金supported by the National Natural Science Foundation of China(Nos.U2441250,62301380,and 62231027)Natural Science Basic Research Program of Shaanxi,China(2024JC-JCQN-63)+3 种基金the Key Research and Development Program of Shaanxi,China(No.2023-YBGY-249)the Guangxi Key Research and Development Program,China(No.2022AB46002)the China Postdoctoral Science Foundation(No.2022M722504 and 2024T170696)the Innovation Capability Support Program of Shaanxi,China(No.2024RS-CXTD-01).
文摘Automatic Dependent Surveillance-Broadcast(ADS-B)technology,with its open signal sharing,faces substantial security risks from false signals and spoofing attacks when broadcasting Unmanned Aerial Vehicle(UAV)information.This paper proposes a security position verification technique based on Multilateration(MLAT)to detect false signals,ensuring UAV safety and reliable airspace operations.First,the proposed method estimates the current position of the UAV by calculating the Time Difference of Arrival(TDOA),Time Sum of Arrival(TSOA),and Angle of Arrival(AOA)information.Then,this estimated position is compared with the ADS-B message to eliminate false UAV signals.Furthermore,a localization model based on TDOA/TSOA/AOA is established by utilizing reliable reference sources for base station time synchronization.Additionally,an improved Chan-Taylor algorithm is developed,incorporating the Constrained Weighted Least Squares(CWLS)method to initialize UAV position calculations.Finally,a false signal detection method is proposed to distinguish between true and false positioning targets.Numerical simulation results indicate that,at a positioning error threshold of 150 m,the improved Chan-Taylor algorithm based on TDOA/TSOA/AOA achieves 100%accuracy coverage,significantly enhancing localization precision.And the proposed false signal detection method achieves a detection accuracy rate of at least 90%within a 50-meter error range.
基金the Deanship of Scientific Research and Libraries in Princess Nourah bint Abdulrahman University for funding this research work through the Research Group project,Grant No.(RG-1445-0064).
文摘Although digital changes in power systems have added more ways to monitor and control them,these changes have also led to new cyber-attack risks,mainly from False Data Injection(FDI)attacks.If this happens,the sensors and operations are compromised,which can lead to big problems,disruptions,failures and blackouts.In response to this challenge,this paper presents a reliable and innovative detection framework that leverages Bidirectional Long Short-Term Memory(Bi-LSTM)networks and employs explanatory methods from Artificial Intelligence(AI).Not only does the suggested architecture detect potential fraud with high accuracy,but it also makes its decisions transparent,enabling operators to take appropriate action.Themethod developed here utilizesmodel-free,interpretable tools to identify essential input elements,thereby making predictions more understandable and usable.Enhancing detection performance is made possible by correcting class imbalance using Synthetic Minority Over-sampling Technique(SMOTE)-based data balancing.Benchmark power system data confirms that the model functions correctly through detailed experiments.Experimental results showed that Bi-LSTM+Explainable AI(XAI)achieved an average accuracy of 94%,surpassing XGBoost(89%)and Bagging(84%),while ensuring explainability and a high level of robustness across various operating scenarios.By conducting an ablation study,we find that bidirectional recursive modeling and ReLU activation help improve generalization and model predictability.Additionally,examining model decisions through LIME enables us to identify which features are crucial for making smart grid operational decisions in real time.The research offers a practical and flexible approach for detecting FDI attacks,improving the security of cyber-physical systems,and facilitating the deployment of AI in energy infrastructure.
文摘A security issue with multi-sensor unmanned aerial vehicle(UAV)cyber physical systems(CPS)from the viewpoint of a false data injection(FDI)attacker is investigated in this paper.The FDI attacker can employ attacks on feedback and feed-forward channels simultaneously with limited resource.The attacker aims at degrading the UAV CPS's estimation performance to the max while keeping stealthiness characterized by the Kullback-Leibler(K-L)divergence.The attacker is resource limited which can only attack part of sensors,and the attacked sensor as well as specific forms of attack signals at each instant should be considered by the attacker.Also,the sensor selection principle is investigated with respect to time invariant attack covariances.Additionally,the optimal switching attack strategies in regard to time variant attack covariances are modeled as a multi-agent Markov decision process(MDP)with hybrid discrete-continuous action space.Then,the multi-agent MDP is solved by utilizing the deep Multi-agent parameterized Q-networks(MAPQN)method.Ultimately,a quadrotor near hover system is used to validate the effectiveness of the results in the simulation section.
文摘With the explosive growth of false information on social media platforms, the automatic detection of multimodalfalse information has received increasing attention. Recent research has significantly contributed to multimodalinformation exchange and fusion, with many methods attempting to integrate unimodal features to generatemultimodal news representations. However, they still need to fully explore the hierarchical and complex semanticcorrelations between different modal contents, severely limiting their performance detecting multimodal falseinformation. This work proposes a two-stage detection framework for multimodal false information detection,called ASMFD, which is based on image aesthetic similarity to segment and explores the consistency andinconsistency features of images and texts. Specifically, we first use the Contrastive Language-Image Pre-training(CLIP) model to learn the relationship between text and images through label awareness and train an imageaesthetic attribute scorer using an aesthetic attribute dataset. Then, we calculate the aesthetic similarity betweenthe image and related images and use this similarity as a threshold to divide the multimodal correlation matrixinto consistency and inconsistencymatrices. Finally, the fusionmodule is designed to identify essential features fordetectingmultimodal false information. In extensive experiments on four datasets, the performance of the ASMFDis superior to state-of-the-art baseline methods.
基金supported by grants from the Jiangsu Agricultural Science and Technology Innovation Fund,China(JASTIF)(CX(21)3012)to Haifeng Zhang。
文摘Rice false smut,caused by Ustilaginoidea virens,is a devastating disease that greatly reduces rice yield and quality.However,controlling rice false smut disease is challenging due to the unique infection mode of U.virens.Therefore,there is a need for early diagnosis and monitoring techniques to prevent the spread of this disease.Lateral flow strip-based recombinase polymerase amplification(LF-RPA)overcomes the limitations of current U.virens detection technologies,which are time-consuming,require delicate equipment,and have a high false-positive rate.In this study,we used a comparative genomics approach to identify Uv_3611,a specific gene of U.virens,as the target for the LF-RPA assay.The designed primers and probe efffectively detected the genomic DNA(gDNA)of U.virens and demonstrated no cross-reactivity with related pathogens.Under optimal conditions,the LF-RPA assay demonstrated a sensitivity of 10 pg of U.virens gDNA.Additionally,by incorporating a simplified PEG-NaOH method for plant DNA extraction,the LF-RPA assay enabled the detection of U.virens in rice spikelets within 30 min,without the need for specialized equipment.Furthermore,the LF-RPA assay successfully detected U.virens in naturally infected rice and seed samples in the field.Therefore,the LF-RPA assay is sensitive,efficient,and convenient,and could be developed as a kit for monitoring rice false smut disease in the field.
基金This work was supported by the Natural Science Foundation of Heilongjiang Province(LH2022F049).
文摘Overlooking the issue of false alarm suppression in heterogeneous change detection leads to inferior detection per-formance.This paper proposes a method to handle false alarms in heterogeneous change detection.A lightweight network of two channels is bulit based on the combination of convolutional neural network(CNN)and graph convolutional network(GCN).CNNs learn feature difference maps of multitemporal images,and attention modules adaptively fuse CNN-based and graph-based features for different scales.GCNs with a new kernel filter adaptively distinguish between nodes with the same and those with different labels,generating change maps.Experimental evaluation on two datasets validates the efficacy of the pro-posed method in addressing false alarms.
文摘Introduction: HIV screening tests are routinely conducted on dialysis patients as the constant exposure of their blood during the dialysis process makes them a reasonable risk for blood-borne infections. However, in low prevalence settings, where HIV rates are <0.1% of the population, false positive results are more likely. This results in apprehension in the dialysis unit as breaches in infectious disease protocols could be presumed. This is illustrated in the case report below. Case Summary: A 62-year-old male Saudi end-stage kidney disease patient secondary to DM nephropathy began dialysis a year before presentation in a hemodialysis center in Saudi Arabia. Routine screening tests done at the start of dialysis revealed negative Hepatitis C, HIV 1 and 2 screening but a positive Hepatitis B surface antigen screen. The patient went for holiday dialysis at another facility and had a routine fourth-generation HIV test done which was positive. A confirmatory HIV PCR test was negative. Conclusion: This case highlights the need for caution in interpreting highly sensitive and specific HIV screening tests in a low-prevalence setting. Routine screening beyond the national recommendation may not be necessary in low-prevalence areas.
基金Supported by the National Natural Science Foundation of China(31071397)the Fund for Independent Innovation of Agricultural Sciences in Jiangsu Province(CX(12)1003)~~
文摘A recombinant inbred line （RILs） population with 157 lines derived from an inter-subspecies cross of Daguandao （japonica）/IR28 （indica） by the single seed de-scent method was used to detect quantitative trait loci （QTLs） conferring resistance to rice false smut caused by Ustilaginoidea virens（Cooke） Takahashi in Nanjing and Yangzhou. The disease rate index of the two parents and 157 RILs caused by rice false smut were scored and the QTLs for rice false smut resistance were detected accordingly by QTL Cartographer software. Eight QTLs control ing false smut resis-tance were detected on chromosomes 1, 2, 4, 8, 10, 11 and 12, respectively, with the phenotypic variance of 8.6%-22.5%. There were five QTLs detected in Nanjing and Yangzhou, respectively, and only two QTLs were found in both two years, the phenotypic variation was explained by individual QTL ranged from 18.0% to 18.9% for these two QTLs, and the additive effects of these two QTLs contributed to the 8.0%-14.6% decrease of disease index and therefore the disease resistance increased. The direction of the additive effects at six loci qFsr1, qFsr2, qFsr8, qFsr10a, qFsr11 and qFsr12 coincided with that predicted by phenotypes of the parents, and the IR28 al eles at these loci had positive effect against rice false smut while the negative effects were found in Daguandao al eles at qFsr4 and qFsr10b. Both qFsr10a and qFsr11 should be useful in rice breeding for resistance to rice false smut in marker-assisted selection （MAS） program.
文摘Rice false smut disease is an increasing concern for research and production, not only because of the increasing epidemic occurrence in rice production, but also the intriguing specific pathogenesis of the disease to be a unique pathological system to enrich the molecular mechanism of plant-microbe interaction. Progresses have been achieved in the pathogen phylogenetic placement, the alternative hosts, the pathogen morphology and diversity, the toxins generated by false smut balls, the artificial inoculation method, and the pathogen transformation as well as rice resistance to the disease. However, it is still controversy on the infection process. It is not clear how the life cycle of this pathogen is coupled with the disease cycle. This review summarized our current understanding on the pathogen, the pathogenesis, and the rice resistance to the disease. Future work should pay attention to developing a more rapid and effective system to evaluate rice resistance and susceptibility to the disease, screening of rice germplasm for disease-resistance breeding, studying the resistance inheritance, and investigating the molecular mechanism of rice-false smut fungus interaction.
基金Supported by the National Natural Science Foundation of China(31071397)the Agricultural Science and Technology Innovation Fund Project of Jiangsu Province(CX(15)1054)~~
文摘In order to identify the resistant gene of rice false smut in rice, a recombi- nant inbred line （RILs） population with 157 lines derived from an inter-subspecies cross of Daguandao/IR28 by the single seed descent method was used to detect quantitative trait loci （QTLs） conferring resistance to strain Pi-1 of rice false smut caused by Usti/aginoiclea virens （Cooke） Takahashi in 2012 and 2013. The disease rate indexes of the two parents and 157 RILs caused by the strain Pi-1 of rice false smut were scored and the QTLs for rice false smut resistance were detected accordingly by QTL Cartographer software. Seven QTLs controlling false smut re- sistance were detected on chromosomes 2, 7, 8, 11 and 12, respectively, with the phenotypic variance of 8.5%-17.2%. There were four QTLs detected in 2012 and 2013, respectively, and only one QTL was found in both two years, the phenotypic variation explained by this individual QTL was 13.5% and 17.2%, and the additive effects of this QTL contributed to the 9.9% and 14.3% decrease of disease index and therefore the disease resistance increased. The direction of the additive effects at five loci qFsr2a, qFsr8a, qFsr8b, qFsr11 and qFsr12 coincided with that predicted by phenotypes of the parents, and the IR28 alleles at these loci had positive effect against rice false smut while the negative effects were found in Daguandao alleles at qFsr2b and qFsr7. The qFsr11 should be useful in rice breeding for resistance to rice false smut in marker-assisted selection （MAS） program.
文摘[Objective] The aim was to explore the reasons of false positives in Different Display Reverse Transcription（DDRT）analysis.[Method] Soybean varieties ＂Jilin 30＂ and ＂Tongnong 13＂ were used as materials to carry out analysis on false positives in DDRT analysis.[Result] An important origin of false positives appeared in DDRT analysis was the non-specific amplification caused by the combination of single primer and cDNA.The parallel PCR test of single primer should be set so as to verify whether the obtained fragments were the false positives or the PCR productions combined with single primer.[Conclusion] This study had provided basis for improving the success rate of DDRT experiment.
文摘A new modification of false position method for solving nonlinear equations is presented by applying homotopy analysis method （HAM）. Some numerical illustrations are given to show the efficiency of algorithm.
基金Supported by Shanghai Municipal Natural Science Foundation(11ZR1427000)
文摘Objective To investigate if immunological factors associated with rheumatoid arthritis(RA) affect the result of human immunodeficiency virus(HIV) screening by electrochemiluminescence immunoassay(ECLIA) and enzyme-linked immunosorbent assay(ELISA). Methods 100 RA cases were enrolled from January 2012 to February 2013 into this study. HIV screening was conducted with ECLIA detecting both HIV-1 p24 antigen, HIV-1 and HIV-2 antibodies, with ELISA and colloidal gold method detecting HIV-1 and HIV-2 antibodies. The samples producing positive results were submitted to the Center for Disease Control for confirmation using Western blotting method. The antibody titers of rheumatoid factors(RF) including RF-IgG, RF-IgM, RF-IgA, and CCP-IgG were analyzed by ELISA. Results The HIV positive-rate determined by ECLIA was significantly higher than that by ELISA and colloidal gold method(P<0.01). The false-positive rate of HIV screening was associated with antibody titers of RF-IgG, RF-IgM, RF-IgA, and CCP-IgG in RA(P<0.01). Conclusion Immunological factors, including RF and anti-CCP antibody, may influence the screening of HIV by ECLIA, producing false-positive result.
