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
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
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
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
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
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
As-forged WSTi6421 titanium alloy billet afterβannealing was investigated.Abnormally coarse grains larger than adjacent grains could be observed in the microstructures,forming abnormal grain structures with uneven si...As-forged WSTi6421 titanium alloy billet afterβannealing was investigated.Abnormally coarse grains larger than adjacent grains could be observed in the microstructures,forming abnormal grain structures with uneven size distribution.Through electron backscattered diffraction(EBSD),the forged microstructure at various locations of as-forged WSTi6421 titanium alloy billet was analyzed,revealing that the strength of theβphase cubic texture generated by forging significantly influences the grain size afterβannealing.Heat treatment experiments were conducted within the temperature range from T_(β)−50°C to T_(β)+10°C to observe the macro-and micro-morphologies.Results show that the cubic texture ofβphase caused by forging impacts the texture of the secondaryαphase,which subsequently influences theβphase formed during the post-βannealing process.Moreover,the pinning effect of the residual primaryαphase plays a crucial role in the growth ofβgrains during theβannealing process.EBSD analysis results suggest that the strength ofβphase with cubic texture formed during forging process impacts the orientation distribution differences ofβgrains afterβannealing.Additionally,the development of grains with large orientations within the cubic texture shows a certain degree of selectivity duringβannealing,which is affected by various factors,including the pinning effect of the primaryαphase,the strength of the matrix cubic texture,and the orientation relationship betweenβgrain and matrix.Comprehensively,the stronger the texture in a certain region,the less likely the large misoriented grains suffering secondary growth,thereby aggregating the difference in microstructure and grain orientation distribution across different regions afterβannealing.展开更多
Objective Rheumatoid arthritis(RA)is a systemic autoimmune disease that affects the small joints of the whole body and degrades the patients’quality of life.Zhengqing Fengtongning(ZF)is a traditional Chinese medicine...Objective Rheumatoid arthritis(RA)is a systemic autoimmune disease that affects the small joints of the whole body and degrades the patients’quality of life.Zhengqing Fengtongning(ZF)is a traditional Chinese medicine preparation used to treat RA.ZF may cause liver injury.In this study,we aimed to develop a prediction model for abnormal liver function caused by ZF.Methods This retrospective study collected data from multiple centers from January 2018 to April 2023.Abnormal liver function was set as the target variable according to the alanine transaminase(ALT)level.Features were screened through univariate analysis and sequential forward selection for modeling.Ten machine learning and deep learning models were compared to find the model that most effectively predicted liver function from the available data.Results This study included 1,913 eligible patients.The LightGBM model exhibited the best performance(accuracy=0.96)out of the 10 learning models.The predictive metrics of the LightGBM model were as follows:precision=0.99,recall rate=0.97,F1_score=0.98,area under the curve(AUC)=0.98,sensitivity=0.97 and specificity=0.85 for predicting ALT<40 U/L;precision=0.60,recall rate=0.83,F1_score=0.70,AUC=0.98,sensitivity=0.83 and specificity=0.97 for predicting 40≤ALT<80 U/L;and precision=0.83,recall rate=0.63,F1_score=0.71,AUC=0.97,sensitivity=0.63 and specificity=1.00 for predicting ALT≥80 U/L.ZF-induced abnormal liver function was found to be associated with high total cholesterol and triglyceride levels,the combination of TNF-αinhibitors,JAK inhibitors,methotrexate+nonsteroidal anti-inflammatory drugs,leflunomide,smoking,older age,and females in middle-age(45-65 years old).Conclusion This study developed a model for predicting ZF-induced abnormal liver function,which may help improve the safety of integrated administration of ZF and Western medicine.展开更多
Male infertility can result from impaired sperm motility caused by multiple morphological abnormalities of the flagella(MMAF).Distinct projections encircling the central microtubules of the spermatozoal axoneme play p...Male infertility can result from impaired sperm motility caused by multiple morphological abnormalities of the flagella(MMAF).Distinct projections encircling the central microtubules of the spermatozoal axoneme play pivotal roles in flagellar bending and spermatozoal movement.Mammalian sperm-associated antigen 17(SPAG17)encodes a conserved axonemal protein of cilia and flagella,forming part of the C1a projection of the central apparatus,with functions related to ciliary/flagellar motility,skeletal growth,and male fertility.This study investigated two novel homozygous SPAG17 mutations(M1:NM_206996.2,c.829+1G>T,p.Asp212_Glu276del;and M2:c.2120del,p.Leu707*)identified in four infertile patients from two consanguineous Pakistani families.These patients displayed the MMAF phenotype confirmed by Papanicolaou staining and scanning electron microscopy assays of spermatozoa.Quantitative real-time polymerase chain reaction(PCR)of patients’spermatozoa also revealed a significant decrease in SPAG17 mRNA expression,and immunofluorescence staining showed the absence of SPAG17 protein signals along the flagella.However,no apparent ciliary-related symptoms or skeletal malformations were observed in the chest X-rays of any of the patients.Transmission electron microscopy of axoneme cross-sections from the patients showed incomplete C1a projection and a higher frequency of missing microtubule doublets 1 and 9 compared with those from fertile controls.Immunofluorescence staining and Western blot analyses of spermatogenesis-associated protein 17(SPATA17),a component of the C1a projection,and sperm-associated antigen 6(SPAG6),a marker of the spring layer,revealed disrupted expression of both proteins in the patients’spermatozoa.Altogether,these findings demonstrated that SPAG17 maintains the integrity of spermatozoal flagellar axoneme,expanding the phenotypic spectrum of SPAG17 mutations in humans.展开更多
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
BACKGROUND Tumor necrosis factor-α(TNF-α)has been implicated in the development of diabetes following chronic pancreatitis.However,its role in abnormal glucose metabolism(AGM)after acute pancreatitis(AP)and post-pan...BACKGROUND Tumor necrosis factor-α(TNF-α)has been implicated in the development of diabetes following chronic pancreatitis.However,its role in abnormal glucose metabolism(AGM)after acute pancreatitis(AP)and post-pancreatitis diabetes mellitus remains unclear.AIM To investigate the role of TNF-αin AP-associated AGM and its effects on isletβ-cell apoptosis,focusing on the underlying molecular mechanisms.METHODS Clinical data were collected to assess AGM’s incidence and identify the characteristics in 369 AP patients.In vitro,AP models were established using lipopolysaccharide in 266-6 acinar cells and MIN-6β-cells.Cell proliferation,apoptosis,and protein expression were analyzed using the Cell Counting Kit-8 assay,terminal deoxynucleotidyl transferase dUTP nick-end labeling assay,and western blotting.The TNF-αand insulin concentration in co-culture medium was measured by enzyme-linked immunosorbent assay.In vivo,an AP mouse model was induced using sodium taurocholate,and pancreatic tissues were analyzed through hematoxylin and eosin staining,terminal deoxynucleotidyl transferase dUTP nick-end labeling,and western blotting.TNF-αlevels were assessed by enzyme-linked immunosorbent assay.A TNF-αinhibitor was applied to the AP cell model to reassess apoptosis and protein expression.RESULTS AGM occurred in 40.38%of AP patients.Body mass index,severity grade,recurrence frequency,and lung injury were significantly associated with AGM.AP models in 266-6 and MIN-6 cells showed reducedβ-cell proliferation,insulin secretion,and increased apoptosis,which correlated with inflammation severity.Similar findings ofβ-cell apoptosis were confirmed in the mouse model.TNF-αlevels were significantly elevated in AP models,with higher levels in severe inflammation.Increased Bax and caspase-3 expression and decreased Bcl-2 expression were observed in both in vitro and in vivo models.These changes intensified with increasing inflammation.TNF-αinhibition reduced apoptosis and altered protein expression patterns,decreasing Bax and caspase-3,while increasing Bcl-2 in MIN-6 cells.CONCLUSION TNF-αcontributes toβ-cell apoptosis and AGM in AP through the Bax/Bcl-2/caspase-3 signaling pathway,suggesting TNF-αas a potential therapeutic target for preventing AP-associated AGM.展开更多
Abnormal grain growth(AGG),a prevalent phenomenon in dilute magnesium(Mg)alloys during elevated-temperature processing,significantly compromises mechanical performance through microstructural degradation.This study in...Abnormal grain growth(AGG),a prevalent phenomenon in dilute magnesium(Mg)alloys during elevated-temperature processing,significantly compromises mechanical performance through microstructural degradation.This study investigates AGG evolution in a heat-treatable Mg-1Al-0.3Ca-0.5Mn(wt.%)alloy,revealing its fundamental mechanism through phase interaction analysis.The AGG initiation is predominantly driven by Zener pinning force attenuation around abnormally coarsened Al_(8)Mn_(5) precipitates.Mechanistically,this heterogeneous coarsening stems from preferential Al_(8)Mn_(5) phase growth kinetics adjacent to Al_(2)Ca phase during homogenization treatment,creating localized pinning force discontinuities.However,addition of 0.2 wt.%Gd facilitates phase transformation from Al_(8)Mn_(5) to thermally stable Al_(8)Mn_(4)Gd with lower Gibbs free energy,thereby promoting a more uniform and refined precipitate distribution.Consequently,the Gd-containing alloy exhibits enhanced grain thermal stability,maintaining a refined microstructure with average grain size of∼7.7μm even after T4 treatment at 500℃ for 1 h,which simultaneously improves strength and ductility compared to the Gd-free alloy.展开更多
The deformation behavior of hot-rolled AZ31 magnesium(Mg)alloy sheet was analyzed when subjected to uniaxial tension along its normal direction at temperatures ranging from 100 to 400℃and strain rates ranging from 0....The deformation behavior of hot-rolled AZ31 magnesium(Mg)alloy sheet was analyzed when subjected to uniaxial tension along its normal direction at temperatures ranging from 100 to 400℃and strain rates ranging from 0.5 to 100 mm/min.Based on the stress−strain curves and the dynamic material model,the hot processing map was established,which demonstrates that the power dissipation factor(η)is the most sensitive to strain rate at 400℃via absorption of dislocations.At 400℃,sample at 0.5 mm/min possessesηof 0.89 because of its lower kernel average misorientation(KAM)value of 0.51,while sample at 100 mm/min possessesηof 0.46 with a higher KAM value of 1.147.In addition,the flow stress presents a slight decrease of 25.94 MPa at 10 mm/min compared to that at 100 mm/min and 100℃.The reasons are twofold:a special~34°texture component during 100℃-100 mm/min favoring the activation of basal slip,and dynamic recrystallization(DRX)also providing softening effect to some extent by absorbing dislocations.Difference in activation of basal slip among twin laminas during 100℃-100 mm/min results in deformation inhomogeneity within the grains,which generates stress that helps matrix grains tilt to a direction favorable to basal slip,forming the special~34°texture component.展开更多
The widespread adoption of tunnel boring machines(TBMs)has led to an increased focus on disc cutter wear,including both normal and abnormal types,for efficient and safe TBM excavation.However,abnormal wear has yet to ...The widespread adoption of tunnel boring machines(TBMs)has led to an increased focus on disc cutter wear,including both normal and abnormal types,for efficient and safe TBM excavation.However,abnormal wear has yet to be thoroughly investigated,primarily due to the complexity of considering mixed ground conditions and the imbalance in the number of instances between the two types of wear.This study developed a prediction model for abnormal TBM disc cutter wear,considering mixed ground conditions,by employing interpretable machine learning with data augmentation.An equivalent elastic modulus was used to consider the characteristics of mixed ground conditions,and wear data was obtained from 65 cutterhead intervention(CHI)reports covering both mixed ground and hard rock sections.With a balanced training dataset obtained by data augmentation,an extreme gradient boosting(XGB)model delivered acceptable results with an accuracy of 0.94,an F1-score of 0.808,and a recall of 0.8.In addition,the accuracy for each individual disc cutter exhibited low variability.When employing data augmentation,a significant improvement in recall was observed compared to when it was not used,although the difference in accuracy and F1-score was marginal.The subsequent model interpretation revealed the chamber pressure,cutter installation radius,and torque as significant contributors.Specifically,a threshold in chamber pressure was observed,which could induce abnormal wear.The study also explored how elevated values of these influential contributors correlate with abnormal wear.The proposed model offers a valuable tool for planning the replacement of abnormally worn disc cutters,enhancing the safety and efficiency of TBM operations.展开更多
Owing to the extreme rainfall and evaporation events under the changing climate,coastal zones are experiencing salinity fluctuations that stress aquatic organisms.However,the biological consequences of ongoing alterat...Owing to the extreme rainfall and evaporation events under the changing climate,coastal zones are experiencing salinity fluctuations that stress aquatic organisms.However,the biological consequences of ongoing alteration in salinity levels on euryhaline organisms remain inconclusive.Herein,we sought to uncover how variation in salinity level adversely alters the bacterioplankton community,the gut microbiota of euryhaline shrimp Penaeus monodon,and subsequent shrimp disease risk.To mimic the extreme weather that induces abrupt changes in coastal water salinity,three salinity levels(10,20,and 30)were selected to investigate the differences in shrimp gut microbiota using bacterial 16S rRNA gene sequencing.Results shows that salinity level and days post experiment(dpe)respectively constrained 45.9%and 13.0%of the variance in the gut bacterial communities.Particularly,abnormal salinity levels accelerated temporal turnover rate,disrupted gut network stability,augmented average variation degree,and increased pathogenic potential in the gut microbiota of shrimp reared at 10 and 30 salinities compared with 20 salinity controls.These changes were accompanied with the shifts in the gut microbiota-mediated functions,especially the compromised immunity and elevated infectious diseases potentials,thereby increasing shrimp disease risk.In addition,abnormal salinity levels increased the role of homogeneous selection governing the gut microbiota.After excluding the dpe-effect,we screened 35 gut salinity-discriminatory taxa that quantitatively discriminated the salinity levels where shrimp were reared,with overall accuracy of 91.1%.Collectively,abnormal salinity levels profoundly disrupt the structure,stability,assembly,and functions of the gut microbiota,which in turn increased disease risk in shrimp.In addition,gut symbionts sensitively responded to the changes in external salinity level.These findings deepened our understanding on the biological consequence of abnormal salinity levels on shrimp health.展开更多
Safety evaluation of a bridge under Moving Abnormal Indivisible Loads(MAILs)directly relates to whether an oversized and/or overweight Large-Cargo Transportation(LCT)vehicle is permitted to pass the bridge.Safety eval...Safety evaluation of a bridge under Moving Abnormal Indivisible Loads(MAILs)directly relates to whether an oversized and/or overweight Large-Cargo Transportation(LCT)vehicle is permitted to pass the bridge.Safety evaluation can be updated by fusing bridge inspection data and load test data,but there are two fundamental difficulties in updating.The first difficulty is to develop an updating scheme to utilize the unstructured inspection data.The second difficulty is to develop a successive updating scheme using load test data based on the previous updating results of the inspection data.This paper proposed a framework,consisting of three modules,to tackle these two fundamental difficulties of updating.Module one is the updating of Finite Element Model(FEM)and resistance of the bridge based on fusing bridge inspection data and load test data.The first difficulty in utilizing the unstructured inspection data is tackled by introducing updating guidelines using the unstructured inspection data.The second difficulty in conducting a successively updating scheme using load test data based on previous updating results is tackled by Bayesian updating.Module two is the simulation of a bridge under a MAIL,updating the ProbabilityDensity Functions(PDFs)of Load Effects(LEs)of critical sections of critical components based on the updated FEM and the givenMAIL.Module three is the safety evaluation of the bridge based on the load-bearing capacity index and reliability index,updating indices based on the updated resistance and LE.Theillustrative examples consist of a simulated example and an engineering example,demonstrating the effectiveness of the proposed framework.The simulated example is the safety evaluation of a bridge under a MAIL,and the engineering example is the safety evaluation of the Anning River Bridge of the Yazhong-Jiangxi Ultra-High-Voltage Direct Current(UHVDC)MAIL project.The results show that it is crucial to fuse bridge inspection data and load test data for updating the safety evaluation of bridges under MAILs.展开更多
BACKGROUND Liver function of chronic hepatitis B(CHB)patients is essentially normal after treatment with antiviral drugs.In rare cases,persistently abnormally elevatedα-fetoprotein(AFP)is seen in CHB patients followi...BACKGROUND Liver function of chronic hepatitis B(CHB)patients is essentially normal after treatment with antiviral drugs.In rare cases,persistently abnormally elevatedα-fetoprotein(AFP)is seen in CHB patients following long-term antiviral treatment.However,in the absence of imaging evidence of liver cancer,a reasonable expla-nation for this phenomenon is still lacking.AIM To explore the causes of abnormal AFP in patients with CHB who were not diag-nosed with liver cancer.METHODS From November 2019 to May 2023,15 patients with CHB after antiviral treatment and elevated AFP were selected.Clinical data and quality indicators related to laboratory testing,imaging data,and pathological data were obtained through inpatient medical records.RESULTS All patients had increased AFP and significantly elevated IgG.Cancer was excluded by imaging examination.Only four patients had elevated alanine ami-notransferase,10 had elevated aspartate aminotransferase,nine had elevated total bilirubin,and two had antinuclear antibodies.The liver biopsy and histopatho-logical examination indicated that 14 patients had rosette,moderate,or higher interfacial inflammation,lymphocyte infiltration,and severe hepatic fibers(11 cases),which was consistent with the pathological features of autoimmune hepa-titis(AIH).After 8-12 week of hormone therapy,the levels of AFP and IgG,and liver function returned to normal(P<0.05).CONCLUSION For patients with CHB and elevated AFP after antiviral treatment,autoimmune hepatitis should be considered.CHB with AIH is clinically insidious and difficult to detect,and prone to progression to cirrhosis.Liver puncture pathological examination should be performed when necessary to confirm diagnosis.展开更多
BACKGROUND Research has shown that several factors can influence postoperative abnormal liver function;however,most studies on this issue have focused specifically on hepatic and cardiac surgeries,leaving limited rese...BACKGROUND Research has shown that several factors can influence postoperative abnormal liver function;however,most studies on this issue have focused specifically on hepatic and cardiac surgeries,leaving limited research on contributing factors in other types of surgeries.AIM To identify the risk factors for early postoperative abnormal liver function in multiple surgery types and construct a risk prediction model.METHODS This retrospective cohort study involved 3720 surgical patients from 5 surgical departments at Guangdong Provincial Hospital of Traditional Chinese Medicine.Patients were divided into abnormal(n=108)and normal(n=3612)groups based on liver function post-surgery.Univariate analysis and LASSO regression screened variables,followed by logistic regression to identify risk factors.A prediction model was constructed based on the variables selected via logistic re-gression.The goodness-of-fit of the model was evaluated using the Hosm-er–Lemeshow test,while discriminatory ability was measured by the area under the receiver operating characteristic curve.Calibration curves were plotted to visualize the consistency between predicted probabilities and observed outcomes.RESULTS The key factors contributing to abnormal liver function after surgery include elevated aspartate aminotransferase and alanine aminotransferase levels and reduced platelet counts pre-surgery,as well as the sevoflurane use during the procedure,among others.CONCLUSION The above factors collectively represent notable risk factors for postoperative liver function injury,and the prediction model developed based on these factors demonstrates strong predictive efficacy.展开更多
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.
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.
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.
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.
基金Key Research and Development Plan of Shaanxi Province(2023-YBGY-493)。
文摘As-forged WSTi6421 titanium alloy billet afterβannealing was investigated.Abnormally coarse grains larger than adjacent grains could be observed in the microstructures,forming abnormal grain structures with uneven size distribution.Through electron backscattered diffraction(EBSD),the forged microstructure at various locations of as-forged WSTi6421 titanium alloy billet was analyzed,revealing that the strength of theβphase cubic texture generated by forging significantly influences the grain size afterβannealing.Heat treatment experiments were conducted within the temperature range from T_(β)−50°C to T_(β)+10°C to observe the macro-and micro-morphologies.Results show that the cubic texture ofβphase caused by forging impacts the texture of the secondaryαphase,which subsequently influences theβphase formed during the post-βannealing process.Moreover,the pinning effect of the residual primaryαphase plays a crucial role in the growth ofβgrains during theβannealing process.EBSD analysis results suggest that the strength ofβphase with cubic texture formed during forging process impacts the orientation distribution differences ofβgrains afterβannealing.Additionally,the development of grains with large orientations within the cubic texture shows a certain degree of selectivity duringβannealing,which is affected by various factors,including the pinning effect of the primaryαphase,the strength of the matrix cubic texture,and the orientation relationship betweenβgrain and matrix.Comprehensively,the stronger the texture in a certain region,the less likely the large misoriented grains suffering secondary growth,thereby aggregating the difference in microstructure and grain orientation distribution across different regions afterβannealing.
基金supported by the Budgeted Fund of Shanghai University of Traditional Chinese Medicine(Natural Science)(No.2021LK037)the Open Project of Qinghai Province Key Laboratory of Tibetan Medicine Pharmacology and Safety Evaluation(No.2021-ZY-03).
文摘Objective Rheumatoid arthritis(RA)is a systemic autoimmune disease that affects the small joints of the whole body and degrades the patients’quality of life.Zhengqing Fengtongning(ZF)is a traditional Chinese medicine preparation used to treat RA.ZF may cause liver injury.In this study,we aimed to develop a prediction model for abnormal liver function caused by ZF.Methods This retrospective study collected data from multiple centers from January 2018 to April 2023.Abnormal liver function was set as the target variable according to the alanine transaminase(ALT)level.Features were screened through univariate analysis and sequential forward selection for modeling.Ten machine learning and deep learning models were compared to find the model that most effectively predicted liver function from the available data.Results This study included 1,913 eligible patients.The LightGBM model exhibited the best performance(accuracy=0.96)out of the 10 learning models.The predictive metrics of the LightGBM model were as follows:precision=0.99,recall rate=0.97,F1_score=0.98,area under the curve(AUC)=0.98,sensitivity=0.97 and specificity=0.85 for predicting ALT<40 U/L;precision=0.60,recall rate=0.83,F1_score=0.70,AUC=0.98,sensitivity=0.83 and specificity=0.97 for predicting 40≤ALT<80 U/L;and precision=0.83,recall rate=0.63,F1_score=0.71,AUC=0.97,sensitivity=0.63 and specificity=1.00 for predicting ALT≥80 U/L.ZF-induced abnormal liver function was found to be associated with high total cholesterol and triglyceride levels,the combination of TNF-αinhibitors,JAK inhibitors,methotrexate+nonsteroidal anti-inflammatory drugs,leflunomide,smoking,older age,and females in middle-age(45-65 years old).Conclusion This study developed a model for predicting ZF-induced abnormal liver function,which may help improve the safety of integrated administration of ZF and Western medicine.
基金supported by the National Natural Science Foundation of China(No.82171599 and No.32270901)the National Key Research and Developmental Program of China(2022YFC2702601 and 2022YFA0806303)the Global Select Project(DJKLX-2022010)of the Institute of Health and Medicine,Hefei Comprehensive National Science Center.
文摘Male infertility can result from impaired sperm motility caused by multiple morphological abnormalities of the flagella(MMAF).Distinct projections encircling the central microtubules of the spermatozoal axoneme play pivotal roles in flagellar bending and spermatozoal movement.Mammalian sperm-associated antigen 17(SPAG17)encodes a conserved axonemal protein of cilia and flagella,forming part of the C1a projection of the central apparatus,with functions related to ciliary/flagellar motility,skeletal growth,and male fertility.This study investigated two novel homozygous SPAG17 mutations(M1:NM_206996.2,c.829+1G>T,p.Asp212_Glu276del;and M2:c.2120del,p.Leu707*)identified in four infertile patients from two consanguineous Pakistani families.These patients displayed the MMAF phenotype confirmed by Papanicolaou staining and scanning electron microscopy assays of spermatozoa.Quantitative real-time polymerase chain reaction(PCR)of patients’spermatozoa also revealed a significant decrease in SPAG17 mRNA expression,and immunofluorescence staining showed the absence of SPAG17 protein signals along the flagella.However,no apparent ciliary-related symptoms or skeletal malformations were observed in the chest X-rays of any of the patients.Transmission electron microscopy of axoneme cross-sections from the patients showed incomplete C1a projection and a higher frequency of missing microtubule doublets 1 and 9 compared with those from fertile controls.Immunofluorescence staining and Western blot analyses of spermatogenesis-associated protein 17(SPATA17),a component of the C1a projection,and sperm-associated antigen 6(SPAG6),a marker of the spring layer,revealed disrupted expression of both proteins in the patients’spermatozoa.Altogether,these findings demonstrated that SPAG17 maintains the integrity of spermatozoal flagellar axoneme,expanding the phenotypic spectrum of SPAG17 mutations in humans.
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 Taicang Science and Technology Program,No.TC2021JCYL21“National Tutor System”Training Program for Health Youth Key Talents in Suzhou,No.Qngg2023042Suzhou Science and Technology Bureau,No.SYW2024152.
文摘BACKGROUND Tumor necrosis factor-α(TNF-α)has been implicated in the development of diabetes following chronic pancreatitis.However,its role in abnormal glucose metabolism(AGM)after acute pancreatitis(AP)and post-pancreatitis diabetes mellitus remains unclear.AIM To investigate the role of TNF-αin AP-associated AGM and its effects on isletβ-cell apoptosis,focusing on the underlying molecular mechanisms.METHODS Clinical data were collected to assess AGM’s incidence and identify the characteristics in 369 AP patients.In vitro,AP models were established using lipopolysaccharide in 266-6 acinar cells and MIN-6β-cells.Cell proliferation,apoptosis,and protein expression were analyzed using the Cell Counting Kit-8 assay,terminal deoxynucleotidyl transferase dUTP nick-end labeling assay,and western blotting.The TNF-αand insulin concentration in co-culture medium was measured by enzyme-linked immunosorbent assay.In vivo,an AP mouse model was induced using sodium taurocholate,and pancreatic tissues were analyzed through hematoxylin and eosin staining,terminal deoxynucleotidyl transferase dUTP nick-end labeling,and western blotting.TNF-αlevels were assessed by enzyme-linked immunosorbent assay.A TNF-αinhibitor was applied to the AP cell model to reassess apoptosis and protein expression.RESULTS AGM occurred in 40.38%of AP patients.Body mass index,severity grade,recurrence frequency,and lung injury were significantly associated with AGM.AP models in 266-6 and MIN-6 cells showed reducedβ-cell proliferation,insulin secretion,and increased apoptosis,which correlated with inflammation severity.Similar findings ofβ-cell apoptosis were confirmed in the mouse model.TNF-αlevels were significantly elevated in AP models,with higher levels in severe inflammation.Increased Bax and caspase-3 expression and decreased Bcl-2 expression were observed in both in vitro and in vivo models.These changes intensified with increasing inflammation.TNF-αinhibition reduced apoptosis and altered protein expression patterns,decreasing Bax and caspase-3,while increasing Bcl-2 in MIN-6 cells.CONCLUSION TNF-αcontributes toβ-cell apoptosis and AGM in AP through the Bax/Bcl-2/caspase-3 signaling pathway,suggesting TNF-αas a potential therapeutic target for preventing AP-associated AGM.
基金supports from The National Natural Science Foundation of China (Nos. 52222409, U24A20104 and 52401049)The National Key Research and Development Program (No. 2024YFB3408900) are greatly acknowledgedPartial financial support came from the Fundamental Research Funds for the Central Universities, JLU
文摘Abnormal grain growth(AGG),a prevalent phenomenon in dilute magnesium(Mg)alloys during elevated-temperature processing,significantly compromises mechanical performance through microstructural degradation.This study investigates AGG evolution in a heat-treatable Mg-1Al-0.3Ca-0.5Mn(wt.%)alloy,revealing its fundamental mechanism through phase interaction analysis.The AGG initiation is predominantly driven by Zener pinning force attenuation around abnormally coarsened Al_(8)Mn_(5) precipitates.Mechanistically,this heterogeneous coarsening stems from preferential Al_(8)Mn_(5) phase growth kinetics adjacent to Al_(2)Ca phase during homogenization treatment,creating localized pinning force discontinuities.However,addition of 0.2 wt.%Gd facilitates phase transformation from Al_(8)Mn_(5) to thermally stable Al_(8)Mn_(4)Gd with lower Gibbs free energy,thereby promoting a more uniform and refined precipitate distribution.Consequently,the Gd-containing alloy exhibits enhanced grain thermal stability,maintaining a refined microstructure with average grain size of∼7.7μm even after T4 treatment at 500℃ for 1 h,which simultaneously improves strength and ductility compared to the Gd-free alloy.
基金Project(52005362) supported by the National Natural Science Foundation of ChinaProjects(202303021221005,202303021211045) supported by the Natural Science Foundation of Shanxi Province,China+1 种基金Project(202402003) supported by the Patent Commercialization Program of Shanxi Province,ChinaProject supported by the Key Research and Development Plan of Xinzhou City,China。
文摘The deformation behavior of hot-rolled AZ31 magnesium(Mg)alloy sheet was analyzed when subjected to uniaxial tension along its normal direction at temperatures ranging from 100 to 400℃and strain rates ranging from 0.5 to 100 mm/min.Based on the stress−strain curves and the dynamic material model,the hot processing map was established,which demonstrates that the power dissipation factor(η)is the most sensitive to strain rate at 400℃via absorption of dislocations.At 400℃,sample at 0.5 mm/min possessesηof 0.89 because of its lower kernel average misorientation(KAM)value of 0.51,while sample at 100 mm/min possessesηof 0.46 with a higher KAM value of 1.147.In addition,the flow stress presents a slight decrease of 25.94 MPa at 10 mm/min compared to that at 100 mm/min and 100℃.The reasons are twofold:a special~34°texture component during 100℃-100 mm/min favoring the activation of basal slip,and dynamic recrystallization(DRX)also providing softening effect to some extent by absorbing dislocations.Difference in activation of basal slip among twin laminas during 100℃-100 mm/min results in deformation inhomogeneity within the grains,which generates stress that helps matrix grains tilt to a direction favorable to basal slip,forming the special~34°texture component.
基金support of the“National R&D Project for Smart Construction Technology (Grant No.RS-2020-KA157074)”funded by the Korea Agency for Infrastructure Technology Advancement under the Ministry of Land,Infrastructure and Transport,and managed by the Korea Expressway Corporation.
文摘The widespread adoption of tunnel boring machines(TBMs)has led to an increased focus on disc cutter wear,including both normal and abnormal types,for efficient and safe TBM excavation.However,abnormal wear has yet to be thoroughly investigated,primarily due to the complexity of considering mixed ground conditions and the imbalance in the number of instances between the two types of wear.This study developed a prediction model for abnormal TBM disc cutter wear,considering mixed ground conditions,by employing interpretable machine learning with data augmentation.An equivalent elastic modulus was used to consider the characteristics of mixed ground conditions,and wear data was obtained from 65 cutterhead intervention(CHI)reports covering both mixed ground and hard rock sections.With a balanced training dataset obtained by data augmentation,an extreme gradient boosting(XGB)model delivered acceptable results with an accuracy of 0.94,an F1-score of 0.808,and a recall of 0.8.In addition,the accuracy for each individual disc cutter exhibited low variability.When employing data augmentation,a significant improvement in recall was observed compared to when it was not used,although the difference in accuracy and F1-score was marginal.The subsequent model interpretation revealed the chamber pressure,cutter installation radius,and torque as significant contributors.Specifically,a threshold in chamber pressure was observed,which could induce abnormal wear.The study also explored how elevated values of these influential contributors correlate with abnormal wear.The proposed model offers a valuable tool for planning the replacement of abnormally worn disc cutters,enhancing the safety and efficiency of TBM operations.
基金Supported by the National Natural Science Foundation of China(Nos.32371596,32071549)the Zhejiang Provincial Key Natural Science Foundation of China(No.Z25C030002)+2 种基金the Science and Technology Innovation Yongjiang 2035 Key Research and Development Project of Ningbo(No.2024Z279)the One Health Interdisciplinary Research Project(No.HZ202404)the K.C.Wong Magna Fund in Ningbo University。
文摘Owing to the extreme rainfall and evaporation events under the changing climate,coastal zones are experiencing salinity fluctuations that stress aquatic organisms.However,the biological consequences of ongoing alteration in salinity levels on euryhaline organisms remain inconclusive.Herein,we sought to uncover how variation in salinity level adversely alters the bacterioplankton community,the gut microbiota of euryhaline shrimp Penaeus monodon,and subsequent shrimp disease risk.To mimic the extreme weather that induces abrupt changes in coastal water salinity,three salinity levels(10,20,and 30)were selected to investigate the differences in shrimp gut microbiota using bacterial 16S rRNA gene sequencing.Results shows that salinity level and days post experiment(dpe)respectively constrained 45.9%and 13.0%of the variance in the gut bacterial communities.Particularly,abnormal salinity levels accelerated temporal turnover rate,disrupted gut network stability,augmented average variation degree,and increased pathogenic potential in the gut microbiota of shrimp reared at 10 and 30 salinities compared with 20 salinity controls.These changes were accompanied with the shifts in the gut microbiota-mediated functions,especially the compromised immunity and elevated infectious diseases potentials,thereby increasing shrimp disease risk.In addition,abnormal salinity levels increased the role of homogeneous selection governing the gut microbiota.After excluding the dpe-effect,we screened 35 gut salinity-discriminatory taxa that quantitatively discriminated the salinity levels where shrimp were reared,with overall accuracy of 91.1%.Collectively,abnormal salinity levels profoundly disrupt the structure,stability,assembly,and functions of the gut microbiota,which in turn increased disease risk in shrimp.In addition,gut symbionts sensitively responded to the changes in external salinity level.These findings deepened our understanding on the biological consequence of abnormal salinity levels on shrimp health.
基金funded by the Science and Technology Development Fund(SKLIOTSC(UM)-2021-2023)the State Key Laboratory of Internet of Things for Smart City(University of Macao)(SKL-IoTSC(UM)-2024-2026/ORP/GA07/2023)Guangdong Provincial Key Laboratory of Modern Civil Engineering Technology(2021B1212040003).
文摘Safety evaluation of a bridge under Moving Abnormal Indivisible Loads(MAILs)directly relates to whether an oversized and/or overweight Large-Cargo Transportation(LCT)vehicle is permitted to pass the bridge.Safety evaluation can be updated by fusing bridge inspection data and load test data,but there are two fundamental difficulties in updating.The first difficulty is to develop an updating scheme to utilize the unstructured inspection data.The second difficulty is to develop a successive updating scheme using load test data based on the previous updating results of the inspection data.This paper proposed a framework,consisting of three modules,to tackle these two fundamental difficulties of updating.Module one is the updating of Finite Element Model(FEM)and resistance of the bridge based on fusing bridge inspection data and load test data.The first difficulty in utilizing the unstructured inspection data is tackled by introducing updating guidelines using the unstructured inspection data.The second difficulty in conducting a successively updating scheme using load test data based on previous updating results is tackled by Bayesian updating.Module two is the simulation of a bridge under a MAIL,updating the ProbabilityDensity Functions(PDFs)of Load Effects(LEs)of critical sections of critical components based on the updated FEM and the givenMAIL.Module three is the safety evaluation of the bridge based on the load-bearing capacity index and reliability index,updating indices based on the updated resistance and LE.Theillustrative examples consist of a simulated example and an engineering example,demonstrating the effectiveness of the proposed framework.The simulated example is the safety evaluation of a bridge under a MAIL,and the engineering example is the safety evaluation of the Anning River Bridge of the Yazhong-Jiangxi Ultra-High-Voltage Direct Current(UHVDC)MAIL project.The results show that it is crucial to fuse bridge inspection data and load test data for updating the safety evaluation of bridges under MAILs.
文摘BACKGROUND Liver function of chronic hepatitis B(CHB)patients is essentially normal after treatment with antiviral drugs.In rare cases,persistently abnormally elevatedα-fetoprotein(AFP)is seen in CHB patients following long-term antiviral treatment.However,in the absence of imaging evidence of liver cancer,a reasonable expla-nation for this phenomenon is still lacking.AIM To explore the causes of abnormal AFP in patients with CHB who were not diag-nosed with liver cancer.METHODS From November 2019 to May 2023,15 patients with CHB after antiviral treatment and elevated AFP were selected.Clinical data and quality indicators related to laboratory testing,imaging data,and pathological data were obtained through inpatient medical records.RESULTS All patients had increased AFP and significantly elevated IgG.Cancer was excluded by imaging examination.Only four patients had elevated alanine ami-notransferase,10 had elevated aspartate aminotransferase,nine had elevated total bilirubin,and two had antinuclear antibodies.The liver biopsy and histopatho-logical examination indicated that 14 patients had rosette,moderate,or higher interfacial inflammation,lymphocyte infiltration,and severe hepatic fibers(11 cases),which was consistent with the pathological features of autoimmune hepa-titis(AIH).After 8-12 week of hormone therapy,the levels of AFP and IgG,and liver function returned to normal(P<0.05).CONCLUSION For patients with CHB and elevated AFP after antiviral treatment,autoimmune hepatitis should be considered.CHB with AIH is clinically insidious and difficult to detect,and prone to progression to cirrhosis.Liver puncture pathological examination should be performed when necessary to confirm diagnosis.
基金Supported by Guangdong Provincial Hospital of Chinese Medicine Science and Technology Research Special Project,No.YN2023WSSQ01State Key Laboratory of Traditional Chinese Medicine Syndrome.
文摘BACKGROUND Research has shown that several factors can influence postoperative abnormal liver function;however,most studies on this issue have focused specifically on hepatic and cardiac surgeries,leaving limited research on contributing factors in other types of surgeries.AIM To identify the risk factors for early postoperative abnormal liver function in multiple surgery types and construct a risk prediction model.METHODS This retrospective cohort study involved 3720 surgical patients from 5 surgical departments at Guangdong Provincial Hospital of Traditional Chinese Medicine.Patients were divided into abnormal(n=108)and normal(n=3612)groups based on liver function post-surgery.Univariate analysis and LASSO regression screened variables,followed by logistic regression to identify risk factors.A prediction model was constructed based on the variables selected via logistic re-gression.The goodness-of-fit of the model was evaluated using the Hosm-er–Lemeshow test,while discriminatory ability was measured by the area under the receiver operating characteristic curve.Calibration curves were plotted to visualize the consistency between predicted probabilities and observed outcomes.RESULTS The key factors contributing to abnormal liver function after surgery include elevated aspartate aminotransferase and alanine aminotransferase levels and reduced platelet counts pre-surgery,as well as the sevoflurane use during the procedure,among others.CONCLUSION The above factors collectively represent notable risk factors for postoperative liver function injury,and the prediction model developed based on these factors demonstrates strong predictive efficacy.
