The rapid integration of Internet of Things(IoT)technologies is reshaping the global energy landscape by deploying smart meters that enable high-resolution consumption monitoring,two-way communication,and advanced met...The rapid integration of Internet of Things(IoT)technologies is reshaping the global energy landscape by deploying smart meters that enable high-resolution consumption monitoring,two-way communication,and advanced metering infrastructure services.However,this digital transformation also exposes power system to evolving threats,ranging from cyber intrusions and electricity theft to device malfunctions,and the unpredictable nature of these anomalies,coupled with the scarcity of labeled fault data,makes realtime detection exceptionally challenging.To address these difficulties,a real-time decision support framework is presented for smart meter anomality detection that leverages rolling time windows and two self-supervised contrastive learning modules.The first module synthesizes diverse negative samples to overcome the lack of labeled anomalies,while the second captures intrinsic temporal patterns for enhanced contextual discrimination.The end-to-end framework continuously updates its model with rolling updated meter data to deliver timely identification of emerging abnormal behaviors in evolving grids.Extensive evaluations on eight publicly available smart meter datasets over seven diverse abnormal patterns testing demonstrate the effectiveness of the proposed full framework,achieving average recall and F1 score of more than 0.85.展开更多
The integration of cloud computing into traditional industrial control systems is accelerating the evolution of Industrial Cyber-Physical System(ICPS),enhancing intelligence and autonomy.However,this transition also e...The integration of cloud computing into traditional industrial control systems is accelerating the evolution of Industrial Cyber-Physical System(ICPS),enhancing intelligence and autonomy.However,this transition also expands the attack surface,introducing critical security vulnerabilities.To address these challenges,this article proposes a hybrid intrusion detection scheme for securing ICPSs that combines system state anomaly and network traffic anomaly detection.Specifically,an improved variation-Bayesian-based noise covariance-adaptive nonlinear Kalman filtering(IVB-NCA-NLKF)method is developed to model nonlinear system dynamics,enabling optimal state estimation in multi-sensor ICPS environments.Intrusions within the physical sensing system are identified by analyzing residual discrepancies between predicted and observed system states.Simultaneously,an adaptive network traffic anomaly detection mechanism is introduced,leveraging learned traffic patterns to detect node-and network-level anomalies through pattern matching.Extensive experiments on a simulated network control system demonstrate that the proposed framework achieves higher detection accuracy(92.14%)with a reduced false alarm rate(0.81%).Moreover,it not only detects known attacks and vulnerabilities but also uncovers stealthy attacks that induce system state deviations,providing a robust and comprehensive security solution for the safety protection of ICPS.展开更多
BACKGROUND An echocardiogram is an essential tool in the evaluation of potential kidney transplant recipients(KTRs).Despite cardiac clearance,potential KTRs still have structural and functional abnormalities.Identifyi...BACKGROUND An echocardiogram is an essential tool in the evaluation of potential kidney transplant recipients(KTRs).Despite cardiac clearance,potential KTRs still have structural and functional abnormalities.Identifying the prevalence of these abnormalities and understanding their predictors is vital for optimizing pretransplant risk stratification and improving post-transplant outcomes.AIM To determine the prevalence of left ventricular hypertrophy(LVH),left ventricular systolic dysfunction(LVSD),diastolic dysfunction(DD),pulmonary hypertension(PH),and their predictors,and to assess their impact on graft function in pre-transplant candidates.METHODS The study included all successful transplant candidates older than 14 who had a baseline echocardiogram.Binary logistic regression models were constructed to identify factors associated with LVH,LVSD,DD,and PH.RESULTS Out of 259 patients,LVH was present in 64%(166),12%(31)had LVSD,27.5%(71)had DD,and 66(25.5%)had PH.Independent predictors of LVH included male gender[odds ratio(OR):2.51;95%CI:1.17-5.41 P=0.02],PH(OR=2.07;95%CI:1.11-3.86;P=0.02),DD(OR:2.47;95%CI:1.29-4.73;P=0.006),and dyslipidemia(OR=1.94;95%CI:1.07-3.53;P=0.03).Predictors for LVSD included patients with DD(OR=3.3,95%CI:1.41-7.81;P=0.006)and a family history of coronary artery disease(OR=4.50,95%CI:1.33-15.20;P=0.015).Peritoneal dialysis was an independent predictor for DD(OR=10.03;95%CI:1.71-58.94,P=0.011).The presence of LVH(OR=3.32,95%CI:1.05-10.55,P=0.04)and mild to moderate or moderate to severe mitral regurgitation(OR=4.63,95%CI:1.45-14.78,P=0.01)were significant factors associated with PH.These abnormalities had no significant impact on estimated glomerular filtration at discharge,6 months,1 year,or 2 years post-transplant.CONCLUSION Significant echocardiographic abnormalities persist in a potential transplant candidate despite cardiac clearance,although they don’t affect future graft function.Understanding the risk factors associated with these abnormalities may help clinicians address these factors pre-and post-transplant to achieve better outcomes.展开更多
AIM:To define the prevalence and anatomical patterns of paranasal sinus abnormalities(PSA)in thyroid-associated ophthalmopathy(TAO)and to test the hypothesis that TAO is partially driven by contiguous orbital inflamma...AIM:To define the prevalence and anatomical patterns of paranasal sinus abnormalities(PSA)in thyroid-associated ophthalmopathy(TAO)and to test the hypothesis that TAO is partially driven by contiguous orbital inflammation rather than systemic autoimmunity or generalized orbital pressure.METHODS:Data included ophthalmic assessments and a panel of thyroid function and autoimmune biomarkers.Blinded radiological analysis of orbital computed tomography(CT)scans was performed to quantify sinus abnormalities and extraocular muscles(EOMs)involvement.Patients were categorized into two groups based on CT findings,those with no radiological evidence of sinus abnormalities(non-PSA control group)and those with identifiable PSA.Furthermore,ethmoid sinus mucosal biopsies from a subset of TAO patients and noninflammatory controls were subjected to histopathological analysis.RESULTS:Totally 121 TAO patients(mean age 42.4±12.8y,range 10-78y),male:female=42:79,were included.PSA was identified in 44.6%(n=54)of patients,with a distribution anatomically restricted to the maxillary(50.0%isolated)and ethmoid sinuses(18.5%isolated;29.6%combined).Compared to the non-PSA group(n=67),patients with PSA were significantly older(45.1±11.8 vs 40.3±13.2y;P=0.040)and were more likely to be male(55.6%vs 17.9%;P<0.001).They also had significantly higher proptosis(22.1±3.2 vs 20.7±2.9 mm;P<0.001).Medial/inferior rectus involvement was most frequent(88.4%vs 89.3%).Histopathological analysis of sinus mucosa from PSA patients provided direct evidence of pathology,revealing a dense,chronic lymphoplasmacytic infiltrate and submucosal edema,validating the radiological findings as a true inflammatory process.No significant correlation was found with systemic autoimmune markers,including thyroid-stimulating hormone(TSH)receptor antibodies(TRAb,median 4.86 vs 2.71 IU/L,P=0.104).CONCLUSION:TAO is associated with a high prevalence of PSA in a pattern consistent with the orbital anatomy.The correlation with ipsilateral muscle thickening combined with the lack of association with proptosis laterality or systemic biomarkers lend strong support to a model of contiguous inflammation over systemic autoimmunity,a hypothesis that warrants further validation through longitudinal and mechanistic studies.展开更多
Prenatal exposure to bisphenols and metals has raised significant concerns regarding their potential impact on fetal development,particularly the risk of fetal chromosome numerical abnormalities(CNA).In this case-cont...Prenatal exposure to bisphenols and metals has raised significant concerns regarding their potential impact on fetal development,particularly the risk of fetal chromosome numerical abnormalities(CNA).In this case-control study,we analyzed bisphenol and metal concentrations in amniotic fluid of high-risk pregnant women undergoing amniocentesis.Concentrations of bisphenols and metals were measured using ultra-performance liquid chromatography-tandem mass spectrometry and inductively coupled plasma-mass spectrometry,respectively.Logistic regression and quantile-based g-computation were applied to evaluate individual and combined effects,while dose-response relationships were assessed using restricted cubic splines.Our findings indicated that bisphenol S(BPS),bisphenol Z(BPZ),bisphenol AF(BPAF),antimony(Sb),and vanadium(V)were significantly associated with an increased risk of CNA when analyzed individually,whereas manganese,iron,copper(Cu),nickel(Ni),and zinc(Zn)were significantly and inversely associated with CNA risk.Combined exposure to bisphenol and metal mixtures was associated with an increased risk of CNA in multi-pollutant models.Cu and Ni exhibited a positive additive interaction.Furthermore,BPS,BPZ,and BPAF were individually associated with an increased risk of Down syndrome,while Zn was associated with a decreased risk of Down syndrome.BPS,Sb,V,and Zn were individually associated with an increased risk of Klinefelter syndrome.These findings underscore the potential role of prenatal bisphenol and metal exposure in the pathogenesis of fetal CNA,highlighting both additive and synergistic effects.展开更多
Aiming at the problem of imbalance between detection accuracy and algorithm model lightweight in UAV aerial image target detection algorithm,a lightweight multi-category abnormal behavior detection algorithm based on ...Aiming at the problem of imbalance between detection accuracy and algorithm model lightweight in UAV aerial image target detection algorithm,a lightweight multi-category abnormal behavior detection algorithm based on improved YOLOv11n is designed.By integrating multi-head grouped self-attention mechanism and Partial-Conv,a two-way feature grouping fusion module(DFPF)was designed,which carried out effective channel segmentation and fusion strategies to reduce redundant calculations andmemory access.C3K2 module was improved,and then unstructured pruning and feature distillation technologywere used.The algorithmmodel is lightweight,and the feature extraction ability for airborne visual abnormal behavior targets is strengthened,and the computational efficiency of the model is improved.Finally,we test the generalization of the baseline model and the improved model on the VisDrone2019 dataset.The results show that com-pared with the baseline model,the detection accuracy of the final improved model on the airborne visual abnormal behavior dataset is improved from 90.2% to 94.8%,and the model parameters are reduced by 50.9% to meet the detection requirements of high efficiency and high precision.The detection accuracy of the improved model on the Vis-Drone2019 public dataset is 1.3% higher than that of the baseline model,indicating the effectiveness of the improved method in this paper.展开更多
Nail changes following upper extremity transplantation(UET)cannot be overlooked as they possess diagnostic and prognostic relevance in allotransplantation of upper limbs.This comprehensive review explores nail and nai...Nail changes following upper extremity transplantation(UET)cannot be overlooked as they possess diagnostic and prognostic relevance in allotransplantation of upper limbs.This comprehensive review explores nail and nail bed related changes encountered in UET recipients in the literature.The differential diagnosis of nail abnormalities in UET includes a wide range of systemic,local and iatrogenic conditions other than immune responses to the allograft.It requires interdisciplinary evaluation by primary transplant surgeons,pathologists,dermatologists and immunologists.The possible underlying mechanisms of nail pathology in UET and the management are discussed.It also underscores the importance of onychodystrophy and need for timely intervention and to improve outcomes in UET recipients.展开更多
Advances in optical coherence tomography(OCT)technology allow a clear view of the vitreoretinal interface(VRI).The abnormality of the VRI is one of the common symptoms of high myopia,mainly including posterior vitreou...Advances in optical coherence tomography(OCT)technology allow a clear view of the vitreoretinal interface(VRI).The abnormality of the VRI is one of the common symptoms of high myopia,mainly including posterior vitreous detachment(PVD)and epiretinal membrane(ERM).They can cause severe damage to the structure and function of the retina,leading to permanent vision loss.Therefore,fully automated detection of abnormalities at the VRI is crucial for the management of high myopia.This paper presents a DS-YOLOv7 network aimed at accurately identifying abnormalities,including partial PVD,complete PVD,and ERM from retinal OCT images.Built upon the YOLOv7 network,the proposed model integrates the advanced dynamic snake convolution(DSConv)module to capture the curvilinear characteristics of lesions,and the mixture of attention and convolution(ACMix)module to improve the precision and robustness of feature extraction through effective fusion of self-attention mechanisms and convolution.Moreover,the introduction of the efficient complete intersection-over-union(ECIoU)loss function further enhances the coordinate regression capability of the model.Threefold cross-validation on a dataset with 1973 OCT B-scans from 46 patients shows that the DS-YOLOv7 achieved superior performance in vitreoretinal interface abnormality detection,with mAP@0.5 of 0.714,mAP@0.75 of 0.438,and mAP@0.5:0.95 of 0.424.The proposed model can provide an accurate and efficient diagnostic tool for patients with high myopia.展开更多
To address the issue of abnormal energy consumption fluctuations in the converter steelmaking process,an integrated diagnostic method combining the gray wolf optimization(GWO)algorithm,support vector machine(SVM),and ...To address the issue of abnormal energy consumption fluctuations in the converter steelmaking process,an integrated diagnostic method combining the gray wolf optimization(GWO)algorithm,support vector machine(SVM),and K-means clustering was proposed.Eight input parameters—derived from molten iron conditions and external factors—were selected as feature variables.A GWO-SVM model was developed to accurately predict the energy consumption of individual heats.Based on the prediction results,the mean absolute percentage error and maximum relative error of the test set were employed as criteria to identify heats with abnormal energy usage.For these heats,the K-means clustering algorithm was used to determine benchmark values of influencing factors from similar steel grades,enabling root-cause diagnosis of excessive energy consumption.The proposed method was applied to real production data from a converter in a steel plant.The analysis reveals that heat sample No.44 exhibits abnormal energy consumption,due to gas recovery being 1430.28 kg of standard coal below the benchmark level.A secondary contributing factor is a steam recovery shortfall of 237.99 kg of standard coal.This integrated approach offers a scientifically grounded tool for energy management in converter operations and provides valuable guidance for optimizing process parameters and enhancing energy efficiency.展开更多
Early and accurate detection of bone cancer and marrow cell abnormalities is critical for timely intervention and improved patient outcomes.This paper proposes a novel hybrid deep learning framework that integrates a ...Early and accurate detection of bone cancer and marrow cell abnormalities is critical for timely intervention and improved patient outcomes.This paper proposes a novel hybrid deep learning framework that integrates a Convolutional Neural Network(CNN)with a Bidirectional Long Short-Term Memory(BiLSTM)architecture,optimized using the Firefly Optimization algorithm(FO).The proposed CNN-BiLSTM-FO model is tailored for structured biomedical data,capturing both local patterns and sequential dependencies in diagnostic features,while the Firefly Algorithm fine-tunes key hyperparameters to maximize predictive performance.The approach is evaluated on two benchmark biomedical datasets:one comprising diagnostic data for bone cancer detection and another for identifying marrow cell abnormalities.Experimental results demonstrate that the proposed method outperforms standard deep learning models,including CNN,LSTM,BiLSTM,and CNN-LSTM hybrids,significantly.The CNNBiLSTM-FO model achieves an accuracy of 98.55%for bone cancer detection and 96.04%for marrow abnormality classification.The paper also presents a detailed complexity analysis of the proposed algorithm and compares its performance across multiple evaluation metrics such as precision,recall,F1-score,and AUC.The results confirm the effectiveness of the firefly-based optimization strategy in improving classification accuracy and model robustness.This work introduces a scalable and accurate diagnostic solution that holds strong potential for integration into intelligent clinical decision-support systems.展开更多
By measuring M-T curves, ρ-T curves and MR-T curves of the samples under different temperatures, the influence of Dy doping （0.00 ≤ x ≤0.30） on the magnetic and electric properties of La0.7-xDyxSr0.3MnO3 has been...By measuring M-T curves, ρ-T curves and MR-T curves of the samples under different temperatures, the influence of Dy doping （0.00 ≤ x ≤0.30） on the magnetic and electric properties of La0.7-xDyxSr0.3MnO3 has been studied. The experimental results show that, with the increase of the Dy content, the system undergoes a transition from long range ferromagnetic order to the cluster-spin glass state and further to antiferromagnetic order. For the samples with x=0.20 and 0.30, their magnetic behaviors are abnormal at low temperature, and their resistivities at low temperature have a minimum value. These peculiar phenomena not only come from the lattice effect induced by doping, but also from extra magnetic coupling induced by doping.展开更多
Tooth number abnormality is one of the most common dental developmental diseases,which includes both tooth agenesis and supernumerary teeth.Tooth development is regulated by numerous developmental signals,such as the ...Tooth number abnormality is one of the most common dental developmental diseases,which includes both tooth agenesis and supernumerary teeth.Tooth development is regulated by numerous developmental signals,such as the well-known Wnt,BMP,FGF,Shh and Eda pathways,which mediate the ongoing complex interactions between epithelium and mesenchyme.Abnormal expression of these crutial signalling during this process may eventually lead to the development of anomalies in tooth number;however,the underlying mechanisms remain elusive.In this review,we summarized the major process of tooth development,the latest progress of mechanism studies and newly reported clinical investigations of tooth number abnormality.In addition,potential treatment approaches for tooth number abnormality based on developmental biology are also discussed.This review not only provides a reference for the diagnosis and treatment of tooth number abnormality in clinical practice but also facilitates the translation of basic research to the clinical application.展开更多
By use of the filter analysis technique, the Complex Empirical Othogonal Function (CEOF) method and the ECMWF/WMO 2.5°×2.5°grid data of the geopotential heights during the summer months in 1988, an inte...By use of the filter analysis technique, the Complex Empirical Othogonal Function (CEOF) method and the ECMWF/WMO 2.5°×2.5°grid data of the geopotential heights during the summer months in 1988, an interseasonal process that the western Pacific subtropical high (WPSH) was anomalously far to the north in the first and second ten days of July is studied. It has been found that in the western Pacific subtropical region in the first and second ten days of July,it is the continuous assembly of low frequency geopotential waves (LFGWs) that leads to the abnormality of WPSH. This abnormality emerges with the enhancement of wave assembling and ceases while the wave assembling situation disappears. The structure of the low frequency assembling waves corresponds to the structure of subtropical high in its abnormal period. The effect of the assembling waves on the abnormality of subtropical high can be considered as the accumulation of disturbance energy carried by the low frequency waves from different directions in the western Pacific region.展开更多
Objective This study aimed to investigate the expression pattern and function of Nuclear receptor subfamily 2 group E member 1 （Nr2e1） in retinoic acid （RA）-induced brain abnormality. Methods The mouse model of br...Objective This study aimed to investigate the expression pattern and function of Nuclear receptor subfamily 2 group E member 1 （Nr2e1） in retinoic acid （RA）-induced brain abnormality. Methods The mouse model of brain abnormality was established by administering 28 mg/kg RA, and neural stem cells （NSCs） were isolated from the mouse embryo and cultured in vitro. Nr2e1 expression was detected by whole mount in situ hybridization, RT-PCR, and Western blotting. Nr2e1 function was determined by transducing Nr2e1 sh RNA into NSCs, and the effect on the sonic hedgehog （Shh） signaling pathway was assessed in the cells. In addition, the regulation of Nr2e1 expression by RA was also determined in vitro. Results Nr2e1 expression was significantly downregulated in the brain and NSCs of RA-treated mouse embryos, and knockdown of Nr2e1 affected the proliferation of NSCs in vitro. In addition, a similar expression pattern of Nr2e1 and RA receptor （RAR） α was observed after treatment of NSCs with different concentrations of RA. Conclusion Our study demonstrated that Nr2e1 could be regulated by RA, which would aid a better understanding of the mechanism underlying RA-induced brain abnormality.展开更多
Depression and cardiovascular disease （CVD） are both highly prevalent disorders, and some evidence shows that there is a ＇vicious cy- cle＇ linking major depression and CVD. There is also growing evidence that immu...Depression and cardiovascular disease （CVD） are both highly prevalent disorders, and some evidence shows that there is a ＇vicious cy- cle＇ linking major depression and CVD. There is also growing evidence that immune abnormalities underpin the common pathophysiology of both CVD and major depression. The abnormalities include the following： abnormal levels of inflammatory markers, such as interleukin-6 （IL-6）, interleukin-1β （IL-1β）, minor necrosis factor α （TNF-α） and interleukin-12 （IL-12）; increased acute phase proteins, such as C-reactive protein, fibrinogen and haptoglobin; and abnormal complement factors. The findings show that major depression and CVD patients have greater immune abnormalities, which may increase depressive symptoms and cardiovascular pathological changes, and that there may be a bidirectional relationship, therefore more prospective studies are needed to draw conclusions.展开更多
By using ECMWF (2. 5°×2. 5°) grid data, analyzing correlation for the summer (June-August) of 1980 (the West Pacific Subtropical High (WPSH) anomalously more to the south), 1988 (the WPSH anomalously mo...By using ECMWF (2. 5°×2. 5°) grid data, analyzing correlation for the summer (June-August) of 1980 (the West Pacific Subtropical High (WPSH) anomalously more to the south), 1988 (the WPSH anomalously more to the north), 1981 (normal) in the west Pacific area, distribution characteristics of the low frequency waves are discussed. The relationship between distribution of the low frequency waves and intraseasonal abnormality of the west subtropical high is also analyzed. There is some discussions:(1)If the WPSH acts anomalously in summer, there is a distinct zonal wave series in the subtropical zone of the north Pacific.(2) One of the important characteristics of the WPSH abnormality is that there are low frequency geopotential high centres from east Pacific and northeast Asia, being combined in the west Pacific area.For different circulation, the combination areas are different, which define the WSPH anomalously more to the north or south.展开更多
By using the historical data during 1953-2009,the yearly most wind direction change in Yumen and the meteorological disasters of 4 times yearly most wind direction abnormality in recent 57 years were analyzed. The res...By using the historical data during 1953-2009,the yearly most wind direction change in Yumen and the meteorological disasters of 4 times yearly most wind direction abnormality in recent 57 years were analyzed. The results showed that there were 51 years which the yearly most wind direction was the easterlies in Yumen,and the westerly had 4 years. There were 2 years which the occurrence frequencies of westerly and easterlies were same. 4 years which the yearly wind direction abnormality was the most were in 1961,1979,1987 and 1998. When the yearly wind direction abnormality was the most,the meteorological disaster was serious. The total output of grain in Gansu Province in 1961 was the least in the history in recent 60 years. The serious drought disaster in 1961 caused that half agricultural population in Gansu seriously lacked of the grain,and the dead population sharply increased. In the end of 1961,the population in Gansu decreased nearly million than in 1958. The annual precipitation in 1979 was the most in recent 57 years. The daily precipitation on June 11,1987 was the most in June of recent 57 years in Yumen. The annual average temperature in 1998 was the highest in Yumen in recent 57 years.展开更多
Our previous study used regional homogeneity analysis and found that activity in some brain areas of patients with ischemic stroke changed significantly. In the current study, we examined structural changes in these b...Our previous study used regional homogeneity analysis and found that activity in some brain areas of patients with ischemic stroke changed significantly. In the current study, we examined structural changes in these brain regions by taking structural magnetic resonance imaging scans of 11 ischemic stroke patients and 15 healthy participants, and analyzing the data using voxel-based morphometry. Compared with healthy participants, patients exhibited higher gray matter density in the left inferior occipital gyrus and right anterior white matter tract. In contrast, gray matter density in the right cerebellum, left precentral gyrus, right middle frontal gyrus, and left middle temporal gyrus was less in ischemic stroke patients. The changes of gray matter density in the middle frontal gyrus were negatively associated with the clin- ical rating scales of the Fugl-Meyer Motor Assessment （r = -0.609, P = 0.047） and the left middle temporal gyrus was negatively correlated with the clinical rating scales of the nervous functional deficiency scale （r = -0.737, P = 0.010）. Our findings call objectively identify the functional abnormality in some brain regions of ischemic stroke patients.展开更多
Online monitoring methods have been widely used in many major devices, however the normal and abnormal states of equipment are estimated mainly based on the monitoring results whether monitored parameters exceed the s...Online monitoring methods have been widely used in many major devices, however the normal and abnormal states of equipment are estimated mainly based on the monitoring results whether monitored parameters exceed the setting thresholds. Using these monitoring methods may cause serious false positive or false negative results. In order to precisely monitor the state of equipment, the problem of abnormality degree detection without fault sample is studied with a new detection method called negative potential field group detectors（NPFG-detectors）. This method achieves the quantitative expression of abnormality degree and provides the better detection results compared with other methods. In the process of Iris data set simulation, the new algorithm obtains the successful results in abnormal detection. The detection rates for 3 types of Iris data set respectively reach 100%, 91.6%, and 95.24% with 50% training samples. The problem of Bearing abnormality degree detection via an abnormality degree curve is successfully solved.展开更多
With the development of intelligent and netw orking technology in automobile,the malicious attacks against in-vehicle CAN netw orks are increasing day by day,and the problem of information safety in automobile is aggr...With the development of intelligent and netw orking technology in automobile,the malicious attacks against in-vehicle CAN netw orks are increasing day by day,and the problem of information safety in automobile is aggravated. In this regard,this paper analyzes the security loopholes and threats w hich the CAN bus faced,put forw ard a kind of anomaly detection algorithm for vehicle CAN bus. The method uses support vector machine algorithm to distinguish betw een normal message and abnormal message,so as to realize the CAN bus anomaly detection. Theoretical and experimental studies show that this method can effectively detect abnormal packets in the CAN bus w ith a detection rate of over 90%,w hich can effectively resist malicious attacks such as tampering and cheating on the vehicle CAN bus.展开更多
文摘The rapid integration of Internet of Things(IoT)technologies is reshaping the global energy landscape by deploying smart meters that enable high-resolution consumption monitoring,two-way communication,and advanced metering infrastructure services.However,this digital transformation also exposes power system to evolving threats,ranging from cyber intrusions and electricity theft to device malfunctions,and the unpredictable nature of these anomalies,coupled with the scarcity of labeled fault data,makes realtime detection exceptionally challenging.To address these difficulties,a real-time decision support framework is presented for smart meter anomality detection that leverages rolling time windows and two self-supervised contrastive learning modules.The first module synthesizes diverse negative samples to overcome the lack of labeled anomalies,while the second captures intrinsic temporal patterns for enhanced contextual discrimination.The end-to-end framework continuously updates its model with rolling updated meter data to deliver timely identification of emerging abnormal behaviors in evolving grids.Extensive evaluations on eight publicly available smart meter datasets over seven diverse abnormal patterns testing demonstrate the effectiveness of the proposed full framework,achieving average recall and F1 score of more than 0.85.
基金supported by the National Natural Science Foundation of China(NSFC)under grant No.62371187the Hunan Provincial Natural Science Foundation of China under Grant Nos.2024JJ8309 and 2023JJ50495.
文摘The integration of cloud computing into traditional industrial control systems is accelerating the evolution of Industrial Cyber-Physical System(ICPS),enhancing intelligence and autonomy.However,this transition also expands the attack surface,introducing critical security vulnerabilities.To address these challenges,this article proposes a hybrid intrusion detection scheme for securing ICPSs that combines system state anomaly and network traffic anomaly detection.Specifically,an improved variation-Bayesian-based noise covariance-adaptive nonlinear Kalman filtering(IVB-NCA-NLKF)method is developed to model nonlinear system dynamics,enabling optimal state estimation in multi-sensor ICPS environments.Intrusions within the physical sensing system are identified by analyzing residual discrepancies between predicted and observed system states.Simultaneously,an adaptive network traffic anomaly detection mechanism is introduced,leveraging learned traffic patterns to detect node-and network-level anomalies through pattern matching.Extensive experiments on a simulated network control system demonstrate that the proposed framework achieves higher detection accuracy(92.14%)with a reduced false alarm rate(0.81%).Moreover,it not only detects known attacks and vulnerabilities but also uncovers stealthy attacks that induce system state deviations,providing a robust and comprehensive security solution for the safety protection of ICPS.
文摘BACKGROUND An echocardiogram is an essential tool in the evaluation of potential kidney transplant recipients(KTRs).Despite cardiac clearance,potential KTRs still have structural and functional abnormalities.Identifying the prevalence of these abnormalities and understanding their predictors is vital for optimizing pretransplant risk stratification and improving post-transplant outcomes.AIM To determine the prevalence of left ventricular hypertrophy(LVH),left ventricular systolic dysfunction(LVSD),diastolic dysfunction(DD),pulmonary hypertension(PH),and their predictors,and to assess their impact on graft function in pre-transplant candidates.METHODS The study included all successful transplant candidates older than 14 who had a baseline echocardiogram.Binary logistic regression models were constructed to identify factors associated with LVH,LVSD,DD,and PH.RESULTS Out of 259 patients,LVH was present in 64%(166),12%(31)had LVSD,27.5%(71)had DD,and 66(25.5%)had PH.Independent predictors of LVH included male gender[odds ratio(OR):2.51;95%CI:1.17-5.41 P=0.02],PH(OR=2.07;95%CI:1.11-3.86;P=0.02),DD(OR:2.47;95%CI:1.29-4.73;P=0.006),and dyslipidemia(OR=1.94;95%CI:1.07-3.53;P=0.03).Predictors for LVSD included patients with DD(OR=3.3,95%CI:1.41-7.81;P=0.006)and a family history of coronary artery disease(OR=4.50,95%CI:1.33-15.20;P=0.015).Peritoneal dialysis was an independent predictor for DD(OR=10.03;95%CI:1.71-58.94,P=0.011).The presence of LVH(OR=3.32,95%CI:1.05-10.55,P=0.04)and mild to moderate or moderate to severe mitral regurgitation(OR=4.63,95%CI:1.45-14.78,P=0.01)were significant factors associated with PH.These abnormalities had no significant impact on estimated glomerular filtration at discharge,6 months,1 year,or 2 years post-transplant.CONCLUSION Significant echocardiographic abnormalities persist in a potential transplant candidate despite cardiac clearance,although they don’t affect future graft function.Understanding the risk factors associated with these abnormalities may help clinicians address these factors pre-and post-transplant to achieve better outcomes.
基金Supported by The National Natural Science Foundation of China(No.82101180)the Fund for Beijing Science&Technology Development of TCM(No.BJZYYB-2023-17)the Beijing Municipal Natural Science Foundation grant(No.7252093).
文摘AIM:To define the prevalence and anatomical patterns of paranasal sinus abnormalities(PSA)in thyroid-associated ophthalmopathy(TAO)and to test the hypothesis that TAO is partially driven by contiguous orbital inflammation rather than systemic autoimmunity or generalized orbital pressure.METHODS:Data included ophthalmic assessments and a panel of thyroid function and autoimmune biomarkers.Blinded radiological analysis of orbital computed tomography(CT)scans was performed to quantify sinus abnormalities and extraocular muscles(EOMs)involvement.Patients were categorized into two groups based on CT findings,those with no radiological evidence of sinus abnormalities(non-PSA control group)and those with identifiable PSA.Furthermore,ethmoid sinus mucosal biopsies from a subset of TAO patients and noninflammatory controls were subjected to histopathological analysis.RESULTS:Totally 121 TAO patients(mean age 42.4±12.8y,range 10-78y),male:female=42:79,were included.PSA was identified in 44.6%(n=54)of patients,with a distribution anatomically restricted to the maxillary(50.0%isolated)and ethmoid sinuses(18.5%isolated;29.6%combined).Compared to the non-PSA group(n=67),patients with PSA were significantly older(45.1±11.8 vs 40.3±13.2y;P=0.040)and were more likely to be male(55.6%vs 17.9%;P<0.001).They also had significantly higher proptosis(22.1±3.2 vs 20.7±2.9 mm;P<0.001).Medial/inferior rectus involvement was most frequent(88.4%vs 89.3%).Histopathological analysis of sinus mucosa from PSA patients provided direct evidence of pathology,revealing a dense,chronic lymphoplasmacytic infiltrate and submucosal edema,validating the radiological findings as a true inflammatory process.No significant correlation was found with systemic autoimmune markers,including thyroid-stimulating hormone(TSH)receptor antibodies(TRAb,median 4.86 vs 2.71 IU/L,P=0.104).CONCLUSION:TAO is associated with a high prevalence of PSA in a pattern consistent with the orbital anatomy.The correlation with ipsilateral muscle thickening combined with the lack of association with proptosis laterality or systemic biomarkers lend strong support to a model of contiguous inflammation over systemic autoimmunity,a hypothesis that warrants further validation through longitudinal and mechanistic studies.
基金supported by the Key Project of Natural Science Foundation of Tianjin(No.23JCZDJC00330)Tianjin Municipal Education Commission Scientific Research Program(No.2022ZD056).
文摘Prenatal exposure to bisphenols and metals has raised significant concerns regarding their potential impact on fetal development,particularly the risk of fetal chromosome numerical abnormalities(CNA).In this case-control study,we analyzed bisphenol and metal concentrations in amniotic fluid of high-risk pregnant women undergoing amniocentesis.Concentrations of bisphenols and metals were measured using ultra-performance liquid chromatography-tandem mass spectrometry and inductively coupled plasma-mass spectrometry,respectively.Logistic regression and quantile-based g-computation were applied to evaluate individual and combined effects,while dose-response relationships were assessed using restricted cubic splines.Our findings indicated that bisphenol S(BPS),bisphenol Z(BPZ),bisphenol AF(BPAF),antimony(Sb),and vanadium(V)were significantly associated with an increased risk of CNA when analyzed individually,whereas manganese,iron,copper(Cu),nickel(Ni),and zinc(Zn)were significantly and inversely associated with CNA risk.Combined exposure to bisphenol and metal mixtures was associated with an increased risk of CNA in multi-pollutant models.Cu and Ni exhibited a positive additive interaction.Furthermore,BPS,BPZ,and BPAF were individually associated with an increased risk of Down syndrome,while Zn was associated with a decreased risk of Down syndrome.BPS,Sb,V,and Zn were individually associated with an increased risk of Klinefelter syndrome.These findings underscore the potential role of prenatal bisphenol and metal exposure in the pathogenesis of fetal CNA,highlighting both additive and synergistic effects.
基金supported by y the Applied Research Advancement Project in Engineering University of PAP(WYY202304)Research and Innovation Team Project in Engineering University of PAP(KYTD202306)Funding for postgraduate education and teaching.
文摘Aiming at the problem of imbalance between detection accuracy and algorithm model lightweight in UAV aerial image target detection algorithm,a lightweight multi-category abnormal behavior detection algorithm based on improved YOLOv11n is designed.By integrating multi-head grouped self-attention mechanism and Partial-Conv,a two-way feature grouping fusion module(DFPF)was designed,which carried out effective channel segmentation and fusion strategies to reduce redundant calculations andmemory access.C3K2 module was improved,and then unstructured pruning and feature distillation technologywere used.The algorithmmodel is lightweight,and the feature extraction ability for airborne visual abnormal behavior targets is strengthened,and the computational efficiency of the model is improved.Finally,we test the generalization of the baseline model and the improved model on the VisDrone2019 dataset.The results show that com-pared with the baseline model,the detection accuracy of the final improved model on the airborne visual abnormal behavior dataset is improved from 90.2% to 94.8%,and the model parameters are reduced by 50.9% to meet the detection requirements of high efficiency and high precision.The detection accuracy of the improved model on the Vis-Drone2019 public dataset is 1.3% higher than that of the baseline model,indicating the effectiveness of the improved method in this paper.
文摘Nail changes following upper extremity transplantation(UET)cannot be overlooked as they possess diagnostic and prognostic relevance in allotransplantation of upper limbs.This comprehensive review explores nail and nail bed related changes encountered in UET recipients in the literature.The differential diagnosis of nail abnormalities in UET includes a wide range of systemic,local and iatrogenic conditions other than immune responses to the allograft.It requires interdisciplinary evaluation by primary transplant surgeons,pathologists,dermatologists and immunologists.The possible underlying mechanisms of nail pathology in UET and the management are discussed.It also underscores the importance of onychodystrophy and need for timely intervention and to improve outcomes in UET recipients.
基金supported by the National Natural Science Foundation of China(62271337,62371326,and 62371328)the National Key Research and Development Program of China(2019FYC1710204)+1 种基金the National Clinical Key Specialty Construction Project(10000015Z155080000004)the Natural Science Foundation of Jiangsu Province(BK20231310).
文摘Advances in optical coherence tomography(OCT)technology allow a clear view of the vitreoretinal interface(VRI).The abnormality of the VRI is one of the common symptoms of high myopia,mainly including posterior vitreous detachment(PVD)and epiretinal membrane(ERM).They can cause severe damage to the structure and function of the retina,leading to permanent vision loss.Therefore,fully automated detection of abnormalities at the VRI is crucial for the management of high myopia.This paper presents a DS-YOLOv7 network aimed at accurately identifying abnormalities,including partial PVD,complete PVD,and ERM from retinal OCT images.Built upon the YOLOv7 network,the proposed model integrates the advanced dynamic snake convolution(DSConv)module to capture the curvilinear characteristics of lesions,and the mixture of attention and convolution(ACMix)module to improve the precision and robustness of feature extraction through effective fusion of self-attention mechanisms and convolution.Moreover,the introduction of the efficient complete intersection-over-union(ECIoU)loss function further enhances the coordinate regression capability of the model.Threefold cross-validation on a dataset with 1973 OCT B-scans from 46 patients shows that the DS-YOLOv7 achieved superior performance in vitreoretinal interface abnormality detection,with mAP@0.5 of 0.714,mAP@0.75 of 0.438,and mAP@0.5:0.95 of 0.424.The proposed model can provide an accurate and efficient diagnostic tool for patients with high myopia.
基金support from the National Key R&D Program of China(Grant No.2020YFB1711100).
文摘To address the issue of abnormal energy consumption fluctuations in the converter steelmaking process,an integrated diagnostic method combining the gray wolf optimization(GWO)algorithm,support vector machine(SVM),and K-means clustering was proposed.Eight input parameters—derived from molten iron conditions and external factors—were selected as feature variables.A GWO-SVM model was developed to accurately predict the energy consumption of individual heats.Based on the prediction results,the mean absolute percentage error and maximum relative error of the test set were employed as criteria to identify heats with abnormal energy usage.For these heats,the K-means clustering algorithm was used to determine benchmark values of influencing factors from similar steel grades,enabling root-cause diagnosis of excessive energy consumption.The proposed method was applied to real production data from a converter in a steel plant.The analysis reveals that heat sample No.44 exhibits abnormal energy consumption,due to gas recovery being 1430.28 kg of standard coal below the benchmark level.A secondary contributing factor is a steam recovery shortfall of 237.99 kg of standard coal.This integrated approach offers a scientifically grounded tool for energy management in converter operations and provides valuable guidance for optimizing process parameters and enhancing energy efficiency.
文摘Early and accurate detection of bone cancer and marrow cell abnormalities is critical for timely intervention and improved patient outcomes.This paper proposes a novel hybrid deep learning framework that integrates a Convolutional Neural Network(CNN)with a Bidirectional Long Short-Term Memory(BiLSTM)architecture,optimized using the Firefly Optimization algorithm(FO).The proposed CNN-BiLSTM-FO model is tailored for structured biomedical data,capturing both local patterns and sequential dependencies in diagnostic features,while the Firefly Algorithm fine-tunes key hyperparameters to maximize predictive performance.The approach is evaluated on two benchmark biomedical datasets:one comprising diagnostic data for bone cancer detection and another for identifying marrow cell abnormalities.Experimental results demonstrate that the proposed method outperforms standard deep learning models,including CNN,LSTM,BiLSTM,and CNN-LSTM hybrids,significantly.The CNNBiLSTM-FO model achieves an accuracy of 98.55%for bone cancer detection and 96.04%for marrow abnormality classification.The paper also presents a detailed complexity analysis of the proposed algorithm and compares its performance across multiple evaluation metrics such as precision,recall,F1-score,and AUC.The results confirm the effectiveness of the firefly-based optimization strategy in improving classification accuracy and model robustness.This work introduces a scalable and accurate diagnostic solution that holds strong potential for integration into intelligent clinical decision-support systems.
基金This work was supported by the National Nature Science Foundation of China （No. 19934003） the State Key Project of Fundamental Research of China （No.001CB610604） the Item of Nature Science Research of Anhui （No. 2001kj244）.
文摘By measuring M-T curves, ρ-T curves and MR-T curves of the samples under different temperatures, the influence of Dy doping （0.00 ≤ x ≤0.30） on the magnetic and electric properties of La0.7-xDyxSr0.3MnO3 has been studied. The experimental results show that, with the increase of the Dy content, the system undergoes a transition from long range ferromagnetic order to the cluster-spin glass state and further to antiferromagnetic order. For the samples with x=0.20 and 0.30, their magnetic behaviors are abnormal at low temperature, and their resistivities at low temperature have a minimum value. These peculiar phenomena not only come from the lattice effect induced by doping, but also from extra magnetic coupling induced by doping.
基金supported by grants from the National Key R&D Program of China(2022YFA1103201)Shanghai Academic Leader of Science and Technology Innovation Action Plan(20XD1424000)+2 种基金Shanghai Experimental Animal Research Project of Science and Technology Innovation Action Plan(201409006400)National Natural Science Foundation of China(82270963,82061130222)awarded to Y.S.National Natural Science Foundation Projects of China(92049201)awarded to X.W.
文摘Tooth number abnormality is one of the most common dental developmental diseases,which includes both tooth agenesis and supernumerary teeth.Tooth development is regulated by numerous developmental signals,such as the well-known Wnt,BMP,FGF,Shh and Eda pathways,which mediate the ongoing complex interactions between epithelium and mesenchyme.Abnormal expression of these crutial signalling during this process may eventually lead to the development of anomalies in tooth number;however,the underlying mechanisms remain elusive.In this review,we summarized the major process of tooth development,the latest progress of mechanism studies and newly reported clinical investigations of tooth number abnormality.In addition,potential treatment approaches for tooth number abnormality based on developmental biology are also discussed.This review not only provides a reference for the diagnosis and treatment of tooth number abnormality in clinical practice but also facilitates the translation of basic research to the clinical application.
文摘By use of the filter analysis technique, the Complex Empirical Othogonal Function (CEOF) method and the ECMWF/WMO 2.5°×2.5°grid data of the geopotential heights during the summer months in 1988, an interseasonal process that the western Pacific subtropical high (WPSH) was anomalously far to the north in the first and second ten days of July is studied. It has been found that in the western Pacific subtropical region in the first and second ten days of July,it is the continuous assembly of low frequency geopotential waves (LFGWs) that leads to the abnormality of WPSH. This abnormality emerges with the enhancement of wave assembling and ceases while the wave assembling situation disappears. The structure of the low frequency assembling waves corresponds to the structure of subtropical high in its abnormal period. The effect of the assembling waves on the abnormality of subtropical high can be considered as the accumulation of disturbance energy carried by the low frequency waves from different directions in the western Pacific region.
基金supported by National Natural Science Foundation Projects(No.81671462)National Natural Science Foundation for Young Scientists of China(No.81300487)+1 种基金Shanxi Province Science and Technology Creative Team(No.2013131016)Shanxi Province Overseas Returnee Scientific Research Fund(No.2013-key 5)
文摘Objective This study aimed to investigate the expression pattern and function of Nuclear receptor subfamily 2 group E member 1 （Nr2e1） in retinoic acid （RA）-induced brain abnormality. Methods The mouse model of brain abnormality was established by administering 28 mg/kg RA, and neural stem cells （NSCs） were isolated from the mouse embryo and cultured in vitro. Nr2e1 expression was detected by whole mount in situ hybridization, RT-PCR, and Western blotting. Nr2e1 function was determined by transducing Nr2e1 sh RNA into NSCs, and the effect on the sonic hedgehog （Shh） signaling pathway was assessed in the cells. In addition, the regulation of Nr2e1 expression by RA was also determined in vitro. Results Nr2e1 expression was significantly downregulated in the brain and NSCs of RA-treated mouse embryos, and knockdown of Nr2e1 affected the proliferation of NSCs in vitro. In addition, a similar expression pattern of Nr2e1 and RA receptor （RAR） α was observed after treatment of NSCs with different concentrations of RA. Conclusion Our study demonstrated that Nr2e1 could be regulated by RA, which would aid a better understanding of the mechanism underlying RA-induced brain abnormality.
文摘Depression and cardiovascular disease （CVD） are both highly prevalent disorders, and some evidence shows that there is a ＇vicious cy- cle＇ linking major depression and CVD. There is also growing evidence that immune abnormalities underpin the common pathophysiology of both CVD and major depression. The abnormalities include the following： abnormal levels of inflammatory markers, such as interleukin-6 （IL-6）, interleukin-1β （IL-1β）, minor necrosis factor α （TNF-α） and interleukin-12 （IL-12）; increased acute phase proteins, such as C-reactive protein, fibrinogen and haptoglobin; and abnormal complement factors. The findings show that major depression and CVD patients have greater immune abnormalities, which may increase depressive symptoms and cardiovascular pathological changes, and that there may be a bidirectional relationship, therefore more prospective studies are needed to draw conclusions.
文摘By using ECMWF (2. 5°×2. 5°) grid data, analyzing correlation for the summer (June-August) of 1980 (the West Pacific Subtropical High (WPSH) anomalously more to the south), 1988 (the WPSH anomalously more to the north), 1981 (normal) in the west Pacific area, distribution characteristics of the low frequency waves are discussed. The relationship between distribution of the low frequency waves and intraseasonal abnormality of the west subtropical high is also analyzed. There is some discussions:(1)If the WPSH acts anomalously in summer, there is a distinct zonal wave series in the subtropical zone of the north Pacific.(2) One of the important characteristics of the WPSH abnormality is that there are low frequency geopotential high centres from east Pacific and northeast Asia, being combined in the west Pacific area.For different circulation, the combination areas are different, which define the WSPH anomalously more to the north or south.
文摘By using the historical data during 1953-2009,the yearly most wind direction change in Yumen and the meteorological disasters of 4 times yearly most wind direction abnormality in recent 57 years were analyzed. The results showed that there were 51 years which the yearly most wind direction was the easterlies in Yumen,and the westerly had 4 years. There were 2 years which the occurrence frequencies of westerly and easterlies were same. 4 years which the yearly wind direction abnormality was the most were in 1961,1979,1987 and 1998. When the yearly wind direction abnormality was the most,the meteorological disaster was serious. The total output of grain in Gansu Province in 1961 was the least in the history in recent 60 years. The serious drought disaster in 1961 caused that half agricultural population in Gansu seriously lacked of the grain,and the dead population sharply increased. In the end of 1961,the population in Gansu decreased nearly million than in 1958. The annual precipitation in 1979 was the most in recent 57 years. The daily precipitation on June 11,1987 was the most in June of recent 57 years in Yumen. The annual average temperature in 1998 was the highest in Yumen in recent 57 years.
基金financially supported by the National Program on Key Basic Research Project of China(973 Program)No.2012CB518501the National Natural Science Foundation of China,No.81072864
文摘Our previous study used regional homogeneity analysis and found that activity in some brain areas of patients with ischemic stroke changed significantly. In the current study, we examined structural changes in these brain regions by taking structural magnetic resonance imaging scans of 11 ischemic stroke patients and 15 healthy participants, and analyzing the data using voxel-based morphometry. Compared with healthy participants, patients exhibited higher gray matter density in the left inferior occipital gyrus and right anterior white matter tract. In contrast, gray matter density in the right cerebellum, left precentral gyrus, right middle frontal gyrus, and left middle temporal gyrus was less in ischemic stroke patients. The changes of gray matter density in the middle frontal gyrus were negatively associated with the clin- ical rating scales of the Fugl-Meyer Motor Assessment （r = -0.609, P = 0.047） and the left middle temporal gyrus was negatively correlated with the clinical rating scales of the nervous functional deficiency scale （r = -0.737, P = 0.010）. Our findings call objectively identify the functional abnormality in some brain regions of ischemic stroke patients.
基金Supported by National Natural Science Foundation of China(Grant No.51175316)Specialized Research Fund for the Doctoral Program of Higher Education,China(Grant No.20103108110006)Basic Research Project of Shanghai Science and Technology Commission,China(Grant No.11JC1404100)
文摘Online monitoring methods have been widely used in many major devices, however the normal and abnormal states of equipment are estimated mainly based on the monitoring results whether monitored parameters exceed the setting thresholds. Using these monitoring methods may cause serious false positive or false negative results. In order to precisely monitor the state of equipment, the problem of abnormality degree detection without fault sample is studied with a new detection method called negative potential field group detectors（NPFG-detectors）. This method achieves the quantitative expression of abnormality degree and provides the better detection results compared with other methods. In the process of Iris data set simulation, the new algorithm obtains the successful results in abnormal detection. The detection rates for 3 types of Iris data set respectively reach 100%, 91.6%, and 95.24% with 50% training samples. The problem of Bearing abnormality degree detection via an abnormality degree curve is successfully solved.
文摘With the development of intelligent and netw orking technology in automobile,the malicious attacks against in-vehicle CAN netw orks are increasing day by day,and the problem of information safety in automobile is aggravated. In this regard,this paper analyzes the security loopholes and threats w hich the CAN bus faced,put forw ard a kind of anomaly detection algorithm for vehicle CAN bus. The method uses support vector machine algorithm to distinguish betw een normal message and abnormal message,so as to realize the CAN bus anomaly detection. Theoretical and experimental studies show that this method can effectively detect abnormal packets in the CAN bus w ith a detection rate of over 90%,w hich can effectively resist malicious attacks such as tampering and cheating on the vehicle CAN bus.
