In this paper we make use of a special procedure on the repro ducing kernel space to give an expansion theorem for the function with two unkno wns and a surface approximation formula. The error of the surface posses...In this paper we make use of a special procedure on the repro ducing kernel space to give an expansion theorem for the function with two unkno wns and a surface approximation formula. The error of the surface possesses mono tonically decreasing and uniformly convergent characteristics in the sense of t he norm on the space.展开更多
This paper proposes linear and nonlinear filters for a non-Gaussian dynamic system with an unknown nominal covariance of the output noise.The challenge of designing a suitable filter in the presence of an unknown cova...This paper proposes linear and nonlinear filters for a non-Gaussian dynamic system with an unknown nominal covariance of the output noise.The challenge of designing a suitable filter in the presence of an unknown covariance matrix is addressed by focusing on the output data set of the system.Considering that data generated from a Gaussian distribution exhibit ellipsoidal scattering,we first propose the weighted sum of norms(SON)clustering method that prioritizes nearby points,reduces distant point influence,and lowers computational cost.Then,by introducing the weighted maximum likelihood,we propose a semi-definite program(SDP)to detect outliers and reduce their impacts on each cluster.Detecting these weights paves the way to obtain an appropriate covariance of the output noise.Next,two filtering approaches are presented:a cluster-based robust linear filter using the maximum a posterior(MAP)estimation and a clusterbased robust nonlinear filter assuming that output noise distribution stems from some Gaussian noise resources according to the ellipsoidal clusters.At last,simulation results demonstrate the effectiveness of our proposed filtering approaches.展开更多
The present study addresses the problem of fault estimation for a specific class of nonlinear time-varying complex networks,utilizing an unknown-input-observer approach within the framework of dynamic event-triggered ...The present study addresses the problem of fault estimation for a specific class of nonlinear time-varying complex networks,utilizing an unknown-input-observer approach within the framework of dynamic event-triggered mechanism(DETM).In order to optimize communication resource utilization,the DETM is employed to determine whether the current measurement data should be transmitted to the estimator or not.To guarantee a satisfactory estimation performance for the fault signal,an unknown-input-observer-based estimator is constructed to decouple the estimation error dynamics from the influence of fault signals.The aim of this paper is to find the suitable estimator parameters under the effects of DETM such that both the state estimates and fault estimates are confined within two sets of closed ellipsoid domains.The techniques of recursive matrix inequality are applied to derive sufficient conditions for the existence of the desired estimator,ensuring that the specified performance requirements are met under certain conditions.Then,the estimator gains are derived by minimizing the ellipsoid domain in the sense of trace and a recursive estimator parameter design algorithm is then provided.Finally,a numerical example is conducted to demonstrate the effectiveness of the designed estimator.展开更多
With the increasing number of connected devices in the Internet of Things(IoT)era,the number of intrusions is also increasing.An intrusion detection system(IDS)is a secondary intelligent system for monitoring,detectin...With the increasing number of connected devices in the Internet of Things(IoT)era,the number of intrusions is also increasing.An intrusion detection system(IDS)is a secondary intelligent system for monitoring,detecting and alerting against malicious activity.IDS is important in developing advanced security models.This study reviews the importance of various techniques,tools,and methods used in IoT detection and/or prevention systems.Specifically,it focuses on machine learning(ML)and deep learning(DL)techniques for IDS.This paper proposes an accurate intrusion detection model to detect traditional and new attacks on the Internet of Vehicles.To speed up the detection of recent attacks,the proposed network architecture developed at the data processing layer is incorporated with a convolutional neural network(CNN),which performs better than a support vector machine(SVM).Processing data are enhanced using the synthetic minority oversampling technique to ensure learning accuracy.The nearest class mean classifier is applied during the testing phase to identify new attacks.Experimental results using the AWID dataset,which is one of the most common open intrusion detection datasets,revealed a higher detection accuracy(94%)compared to SVM and random forest methods.展开更多
Since its inception,the Internet has been rapidly evolving.With the advancement of science and technology and the explosive growth of the population,the demand for the Internet has been on the rise.Many applications i...Since its inception,the Internet has been rapidly evolving.With the advancement of science and technology and the explosive growth of the population,the demand for the Internet has been on the rise.Many applications in education,healthcare,entertainment,science,and more are being increasingly deployed based on the internet.Concurrently,malicious threats on the internet are on the rise as well.Distributed Denial of Service(DDoS)attacks are among the most common and dangerous threats on the internet today.The scale and complexity of DDoS attacks are constantly growing.Intrusion Detection Systems(IDS)have been deployed and have demonstrated their effectiveness in defense against those threats.In addition,the research of Machine Learning(ML)and Deep Learning(DL)in IDS has gained effective results and significant attention.However,one of the challenges when applying ML and DL techniques in intrusion detection is the identification of unknown attacks.These attacks,which are not encountered during the system’s training,can lead to misclassification with significant errors.In this research,we focused on addressing the issue of Unknown Attack Detection,combining two methods:Spatial Location Constraint Prototype Loss(SLCPL)and Fuzzy C-Means(FCM).With the proposed method,we achieved promising results compared to traditional methods.The proposed method demonstrates a very high accuracy of up to 99.8%with a low false positive rate for known attacks on the Intrusion Detection Evaluation Dataset(CICIDS2017)dataset.Particularly,the accuracy is also very high,reaching 99.7%,and the precision goes up to 99.9%for unknown DDoS attacks on the DDoS Evaluation Dataset(CICDDoS2019)dataset.The success of the proposed method is due to the combination of SLCPL,an advanced Open-Set Recognition(OSR)technique,and FCM,a traditional yet highly applicable clustering technique.This has yielded a novel method in the field of unknown attack detection.This further expands the trend of applying DL and ML techniques in the development of intrusion detection systems and cybersecurity.Finally,implementing the proposed method in real-world systems can enhance the security capabilities against increasingly complex threats on computer networks.展开更多
Based on the finite difference discretization of partial differential equations, we propose a kind of semi-implicit θ-schemes of incremental unknowns type for the heat equation with time-dependent coefficients. The s...Based on the finite difference discretization of partial differential equations, we propose a kind of semi-implicit θ-schemes of incremental unknowns type for the heat equation with time-dependent coefficients. The stability of the new schemes is carefully studied. Some new types of conditions give better stability when θ is closed to 1/2 even if we have variable coefficients.展开更多
The novel coronavirus disease(COVID-19)outbreak is a major public health crisis unseen in about 100 years.There is also a possibility that the disease may continue to exist for a long time to come.One of the most effe...The novel coronavirus disease(COVID-19)outbreak is a major public health crisis unseen in about 100 years.There is also a possibility that the disease may continue to exist for a long time to come.One of the most effective approaches to tackling the spread of the virus is to adopt widespread lockdowns.展开更多
Component failures can cause multi-agent system(MAS)performance degradation and even disasters,which provokes the demand of the fault diagnosis method.A distributed sliding mode observer-based fault diagnosis method f...Component failures can cause multi-agent system(MAS)performance degradation and even disasters,which provokes the demand of the fault diagnosis method.A distributed sliding mode observer-based fault diagnosis method for MAS is developed in presence of actuator and sensor faults.Firstly,the actuator and sensor faults are extended to the system state,and the system is transformed into a descriptor system form.Then,a sliding mode-based distributed unknown input observer is proposed to estimate the extended state.Furthermore,adaptive laws are introduced to adjust the observer parameters.Finally,the effectiveness of the proposed method is demonstrated with numerical simulations.展开更多
This paper proposes an adaptive unscented Kalman filter algorithm(ARUKF)to implement fault estimation for the dynamics of high⁃speed train(HST)with measurement uncertainty and time⁃varying noise with unknown statistic...This paper proposes an adaptive unscented Kalman filter algorithm(ARUKF)to implement fault estimation for the dynamics of high⁃speed train(HST)with measurement uncertainty and time⁃varying noise with unknown statistics.Firstly,regarding the actuator and sensor fault as the auxiliary variables of the dynamics of HST,an augmented system is established,and the fault estimation problem for dynamics of HST is formulated as the state estimation of the augmented system.Then,considering the measurement uncertainties,a robust lower bound is proposed to modify the update of the UKF to decrease the influence of measurement uncertainty on the filtering accuracy.Further,considering the unknown time⁃varying noise of the dynamics of HST,an adaptive UKF algorithm based on moving window is proposed to estimate the time⁃varying noise so that accurate concurrent actuator and sensor fault estimations of dynamics of HST is implemented.Finally,a five-car model of HST is given to show the effectiveness of this method.展开更多
In this paper,we consider the practical prescribed-time performance guaranteed tracking control problem for a class of uncertain strict-feedback systems subject to unknown control direction.Due to the existence of unk...In this paper,we consider the practical prescribed-time performance guaranteed tracking control problem for a class of uncertain strict-feedback systems subject to unknown control direction.Due to the existence of unknown nonlinearities and uncertainties,it is challenging to design a controller that can ensure the stability of closed-loop system within a predetermined finite time while maintaining the specified transient performance.The underlying problem becomes further complex as the control directions are unknown.To deal with the above problems,a special translation function as well as Nussbaum type function are introduced in the prescribed performance control(PPC)framework.Finally,a PPC as well as preset finite time tracking control scheme is designed,and its effectiveness is confirmed by both theoretical analysis and numerical simulation.展开更多
This paper presents a subspace identification method for closed-loop systems with unknown deterministic disturbances.To deal with the unknown deterministic disturbances,two strategies are implemented to construct the ...This paper presents a subspace identification method for closed-loop systems with unknown deterministic disturbances.To deal with the unknown deterministic disturbances,two strategies are implemented to construct the row space that can be used to approximately represent the unknown deterministic disturbances using the trigonometric functions or Bernstein polynomials depending on whether the disturbance frequencies are known.For closed-loop identification,CCF-N4SID is extended to the case with unknown deterministic disturbances using the oblique projection.In addition,a proper Bernstein polynomial order can be determined using the Akaike information criterion(AIC)or the Bayesian information criterion(BIC).Numerical simulation results demonstrate the effectiveness of the proposed identification method for both periodic and aperiodic deterministic disturbances.展开更多
In recent times,wireless sensor network(WSN)finds their suitability in several application areas,ranging from military to commercial ones.Since nodes in WSN are placed arbitrarily in the target field,node localization...In recent times,wireless sensor network(WSN)finds their suitability in several application areas,ranging from military to commercial ones.Since nodes in WSN are placed arbitrarily in the target field,node localization(NL)becomes essential where the positioning of the nodes can be determined by the aid of anchor nodes.The goal of any NL scheme is to improve the localization accuracy and reduce the localization error rate.With this motivation,this study focuses on the design of Intelligent Aquila Optimization Algorithm Based Node Localization Scheme(IAOAB-NLS)for WSN.The presented IAOAB-NLS model makes use of anchor nodes to determine proper positioning of the nodes.In addition,the IAOAB-NLS model is stimulated by the behaviour of Aquila.The IAOAB-NLS model has the ability to accomplish proper coordinate points of the nodes in the network.For guaranteeing the proficient NL process of the IAOAB-NLS model,widespread experimentation takes place to assure the betterment of the IAOAB-NLS model.The resultant values reported the effectual outcome of the IAOAB-NLS model irrespective of changing parameters in the network.展开更多
There has been an increasing number of reported cases of acute hepatitis of unknown origin in previously healthy children since first reported on March 31,2022.This clinical syndrome is identified by jaundice and mark...There has been an increasing number of reported cases of acute hepatitis of unknown origin in previously healthy children since first reported on March 31,2022.This clinical syndrome is identified by jaundice and markedly elevated liver enzymes with increased aspartate transaminase and/or alanine aminotransa-minase(greater than 500 IU/L).We conducted an inclusive literature review with respect to acute hepatitis outbreaks in children using the search terms acute hepatitis,outbreak,children,severe acute respiratory syndrome coronavirus 2(SARS-CoV-2),coronavirus disease 2019(COVID-19),and adenovirus.According to the cumulative data presented in four main studies,the median age is 4 years,with a male predominance(1.3:1).Jaundice was the most common clinical manifestation(69%),followed by vomiting(63%),anorexia(52.9%),diarrhea(47.2%),abdominal pain(39%),pyrexia(33.3%),pale stool(30%),and dark urine(30%).Coryza and lethargy were reported in 16.6%,while pruritus was reported in 2%of cases.Acute liver failure was observed in 25%of cases.The exact mechanism of this acute hepatitis outbreak is still not entirely clear.Adenoviruses and SARS-CoV-2 were detected in a significant number of patients.Coinfection with adenovirus and SARS-CoV-2 could be a possible underlying mechanism.However,other possible infections and mechanisms must be considered in the pathogenesis of this condition.Acute hepatitis of unknown origin in children has been a serious problem since the start of the COVID-19 pandemic but has not yet been sufficiently addressed.Many questions remain regarding the underlying mechanisms leading to acute liver failure in children,and it is likely that extensive future research is needed.展开更多
BACKGROUND Acute liver injury(ALI)refers to inflammation of the hepatic parenchyma without hepatic encephalopathy that lasts less than 6 mo.When the etiology is unknown,Acute Hepatitis of Unknown Origin(AHUO)can prese...BACKGROUND Acute liver injury(ALI)refers to inflammation of the hepatic parenchyma without hepatic encephalopathy that lasts less than 6 mo.When the etiology is unknown,Acute Hepatitis of Unknown Origin(AHUO)can present as a diagnostic and treatment challenge.AHUO in the adult population is unusual and poorly documented.It has an incidence between 11%and 75%.Currently,no treatment guidelines exist.With no identified cause,treatment is often blind,and the wrong treatment plan may have unintended consequences.CASE SUMMARY We present the case of a 58-year-old woman who presented to the emergency room for elevated liver function tests(LFTs).Her symptoms started 10 d prior to admission and included nausea,vomiting,jaundice,decreased appetite,weight loss of 10 lbs,and dark urine.She denied drinking alcohol or taking any hepatotoxic agents,including acetaminophen,statins,vitamins,or supplements.She was admitted to the hospital,and an etiologic work-up was carried out.Her initial bloodwork revealed elevated liver enzymes(alanine aminotransferase 2500 U/L,aspartate aminotransferase 3159 U/L,and alkaline phosphatase 714 U/L)and elevated total bilirubin of 6.4 mg/dL.She tested negative for common infectious etiologies such as hepatotropic viruses A,B,C,and E.Further infective work-up revealed negative serology for cytomegalovirus,Epstein-Barr virus,herpes simplex virus 1&2,and human immunodeficiency virus.Her autoanti-body test results were negative,including anti-smooth muscle antibody,anti-mitochondrial antibody,and anti-liver kidney microsome 1 antibody.Magnetic resonance cholangiopancreatography ruled out biliary causes of elevated LFTs,and her core liver biopsy proved inconclusive.Over the course of her hospital stay,the patient's LFTs improved with supportive care and without steroids.CONCLUSION Idiopathic hepatitis makes treatment challenging.It can leave patients feeling confused and unfulfilled.Thus,educating the patient thoroughly for shared decision-making and management becomes essential.展开更多
BACKGROUND Brucellosis is endemic in India with seropositivity rates as high as 10%in children in the eastern states,yet the disease is not on the radar when a differential diagnosis of pyrexia of unknown origin(PUO)i...BACKGROUND Brucellosis is endemic in India with seropositivity rates as high as 10%in children in the eastern states,yet the disease is not on the radar when a differential diagnosis of pyrexia of unknown origin(PUO)is being considered,especially in children in urban set-up.This may be because of the non-specific multitude of systemic symptoms seen in this disease and the lack of awareness among clinicians.CASE SUMMARY We present a case of a 13-year-old boy,who came with a history of undulating fever for the past three and a half months,loss of appetite,and abdominal pain.The child had visited several pediatricians and was even admitted to a tertiary care hospital for PUO evaluation,but to no avail.He presented to us after three and half months of suffering and weight loss of more than 10%of body weight.His ultrasonography revealed thickening of the terminal ileum.His blood culture grew Brucella melitensis.A diagnosis of Brucellosis with terminal ileitis was made.Brucella serology by enzyme-linked immunoassay(ELISA)was positive for both IgG and IgM.He was treated with doxycycline and Rifampicin along with syrup multivitamin and zinc,for 6 wk.There was remarkable improvement with gain in 4 kg body weight within 2 mo of completing treatment.History revealed consumption of unpasteurized milk and contact with cattle.CONCLUSION Clinical suspicion,detailed history,appropriate laboratory investigations are the three pillars for diagnosing Brucellosis in patients presenting with vague symptoms.展开更多
Fabry Disease (FD) is a rare lysosomal storage disorder characterized by α-galactosidase A (α-Gal A) enzyme deficiency, resulting in glycosphingolipid accumulation. Its clinical spectrum ranges from severe classical...Fabry Disease (FD) is a rare lysosomal storage disorder characterized by α-galactosidase A (α-Gal A) enzyme deficiency, resulting in glycosphingolipid accumulation. Its clinical spectrum ranges from severe classical to milder nonclassical or late-onset phenotypes. Renal involvement, termed Fabry Nephropathy (FN), can vary from mild proteinuria to kidney failure. FN diagnosis, especially in nonclassical cases with a genetic Variant of Unknown Significance (VUS) in the GLA gene, poses challenges. Measurement of plasma lyso-Gb3 levels is gaining importance in FN diagnosis, while renal biopsy with electron microscopy remains the gold standard in equivocal cases. Treatment options include Enzyme Replacement Therapy (ERT) and chaperone therapy, demanding careful candidate selection due to high treatment costs. Research has predominantly focused on classical FD, revealing modest treatment benefits. However, evidence for treating patients, especially females, with milder nonclassical or late-onset phenotypes is scarce, emphasizing the necessity for placebo-controlled clinical trials in these subgroups. Meanwhile, participation in global FD registries can improve our understanding of disease management. Case Presentation: A woman in her late sixties presented with moderate chronic kidney disease, mild proteinuria, and microscopic hematuria. Her family history included a prevalence of renal, cardiac and cerebrovascular diseases. Kidney biopsy revealed characteristic myelin figures and zebra bodies in podocytes, strongly suggestive of FN. Genetic analysis identified a VUS in the GLA gene (c.655A > C, p.Ile219Leu), introducing diagnostic uncertainty. Further investigations revealed severe cardiac involvement. Considering the recurring difficulty presented by the finding of a VUS in the GLA gene during FN assessments, along with the uncertainty regarding the need for treatment in nonclassical or late-onset FD phenotypes, especially in women, this case becomes a central focus for a thorough review of the literature. This review aims to propose a practical algorithm that integrates clinical, biochemical, and genetic markers for FN screening and diagnosis. Additionally, it explores treatment benefits in nonclassical or late-onset FD phenotypes, with a focus on female patients.展开更多
While reading plays a very important role in English study, many English language learners find it very difficult to fully comprehend some reading materials on account of many unknown words in them. This essay mainly ...While reading plays a very important role in English study, many English language learners find it very difficult to fully comprehend some reading materials on account of many unknown words in them. This essay mainly discusses one technique of guessing meanings of new words according to context clues, thus emphasizing the importance of context.展开更多
文摘In this paper we make use of a special procedure on the repro ducing kernel space to give an expansion theorem for the function with two unkno wns and a surface approximation formula. The error of the surface possesses mono tonically decreasing and uniformly convergent characteristics in the sense of t he norm on the space.
文摘This paper proposes linear and nonlinear filters for a non-Gaussian dynamic system with an unknown nominal covariance of the output noise.The challenge of designing a suitable filter in the presence of an unknown covariance matrix is addressed by focusing on the output data set of the system.Considering that data generated from a Gaussian distribution exhibit ellipsoidal scattering,we first propose the weighted sum of norms(SON)clustering method that prioritizes nearby points,reduces distant point influence,and lowers computational cost.Then,by introducing the weighted maximum likelihood,we propose a semi-definite program(SDP)to detect outliers and reduce their impacts on each cluster.Detecting these weights paves the way to obtain an appropriate covariance of the output noise.Next,two filtering approaches are presented:a cluster-based robust linear filter using the maximum a posterior(MAP)estimation and a clusterbased robust nonlinear filter assuming that output noise distribution stems from some Gaussian noise resources according to the ellipsoidal clusters.At last,simulation results demonstrate the effectiveness of our proposed filtering approaches.
基金supported in part by the National Natural Science Foundation of China (62233012,62273087)the Research Fund for the Taishan Scholar Project of Shandong Province of Chinathe Shanghai Pujiang Program of China (22PJ1400400)。
文摘The present study addresses the problem of fault estimation for a specific class of nonlinear time-varying complex networks,utilizing an unknown-input-observer approach within the framework of dynamic event-triggered mechanism(DETM).In order to optimize communication resource utilization,the DETM is employed to determine whether the current measurement data should be transmitted to the estimator or not.To guarantee a satisfactory estimation performance for the fault signal,an unknown-input-observer-based estimator is constructed to decouple the estimation error dynamics from the influence of fault signals.The aim of this paper is to find the suitable estimator parameters under the effects of DETM such that both the state estimates and fault estimates are confined within two sets of closed ellipsoid domains.The techniques of recursive matrix inequality are applied to derive sufficient conditions for the existence of the desired estimator,ensuring that the specified performance requirements are met under certain conditions.Then,the estimator gains are derived by minimizing the ellipsoid domain in the sense of trace and a recursive estimator parameter design algorithm is then provided.Finally,a numerical example is conducted to demonstrate the effectiveness of the designed estimator.
基金The author extends the appreciation to the Deanship of Postgraduate Studies and Scientific Research atMajmaah University for funding this research work through the project number(R-2024-920).
文摘With the increasing number of connected devices in the Internet of Things(IoT)era,the number of intrusions is also increasing.An intrusion detection system(IDS)is a secondary intelligent system for monitoring,detecting and alerting against malicious activity.IDS is important in developing advanced security models.This study reviews the importance of various techniques,tools,and methods used in IoT detection and/or prevention systems.Specifically,it focuses on machine learning(ML)and deep learning(DL)techniques for IDS.This paper proposes an accurate intrusion detection model to detect traditional and new attacks on the Internet of Vehicles.To speed up the detection of recent attacks,the proposed network architecture developed at the data processing layer is incorporated with a convolutional neural network(CNN),which performs better than a support vector machine(SVM).Processing data are enhanced using the synthetic minority oversampling technique to ensure learning accuracy.The nearest class mean classifier is applied during the testing phase to identify new attacks.Experimental results using the AWID dataset,which is one of the most common open intrusion detection datasets,revealed a higher detection accuracy(94%)compared to SVM and random forest methods.
基金This research was partly supported by the National Science and Technology Council,Taiwan with Grant Numbers 112-2221-E-992-045,112-2221-E-992-057-MY3 and 112-2622-8-992-009-TD1.
文摘Since its inception,the Internet has been rapidly evolving.With the advancement of science and technology and the explosive growth of the population,the demand for the Internet has been on the rise.Many applications in education,healthcare,entertainment,science,and more are being increasingly deployed based on the internet.Concurrently,malicious threats on the internet are on the rise as well.Distributed Denial of Service(DDoS)attacks are among the most common and dangerous threats on the internet today.The scale and complexity of DDoS attacks are constantly growing.Intrusion Detection Systems(IDS)have been deployed and have demonstrated their effectiveness in defense against those threats.In addition,the research of Machine Learning(ML)and Deep Learning(DL)in IDS has gained effective results and significant attention.However,one of the challenges when applying ML and DL techniques in intrusion detection is the identification of unknown attacks.These attacks,which are not encountered during the system’s training,can lead to misclassification with significant errors.In this research,we focused on addressing the issue of Unknown Attack Detection,combining two methods:Spatial Location Constraint Prototype Loss(SLCPL)and Fuzzy C-Means(FCM).With the proposed method,we achieved promising results compared to traditional methods.The proposed method demonstrates a very high accuracy of up to 99.8%with a low false positive rate for known attacks on the Intrusion Detection Evaluation Dataset(CICIDS2017)dataset.Particularly,the accuracy is also very high,reaching 99.7%,and the precision goes up to 99.9%for unknown DDoS attacks on the DDoS Evaluation Dataset(CICDDoS2019)dataset.The success of the proposed method is due to the combination of SLCPL,an advanced Open-Set Recognition(OSR)technique,and FCM,a traditional yet highly applicable clustering technique.This has yielded a novel method in the field of unknown attack detection.This further expands the trend of applying DL and ML techniques in the development of intrusion detection systems and cybersecurity.Finally,implementing the proposed method in real-world systems can enhance the security capabilities against increasingly complex threats on computer networks.
基金This project is partially supported by Natural Science Foundation of Gansu Province under Grant 3ZS041-A25-011 by National Natural Science Foundation under Grant 10471056.
文摘Based on the finite difference discretization of partial differential equations, we propose a kind of semi-implicit θ-schemes of incremental unknowns type for the heat equation with time-dependent coefficients. The stability of the new schemes is carefully studied. Some new types of conditions give better stability when θ is closed to 1/2 even if we have variable coefficients.
文摘The novel coronavirus disease(COVID-19)outbreak is a major public health crisis unseen in about 100 years.There is also a possibility that the disease may continue to exist for a long time to come.One of the most effective approaches to tackling the spread of the virus is to adopt widespread lockdowns.
基金supported by the National Natural Science Foundation of China(62020106003,62003162)111 project(B20007)+1 种基金the Natural Science Foundation of Jiangsu Province of China(BK20200416)the China Postdoctoral Science Foundation(2020TQ0151,2020M681590).
文摘Component failures can cause multi-agent system(MAS)performance degradation and even disasters,which provokes the demand of the fault diagnosis method.A distributed sliding mode observer-based fault diagnosis method for MAS is developed in presence of actuator and sensor faults.Firstly,the actuator and sensor faults are extended to the system state,and the system is transformed into a descriptor system form.Then,a sliding mode-based distributed unknown input observer is proposed to estimate the extended state.Furthermore,adaptive laws are introduced to adjust the observer parameters.Finally,the effectiveness of the proposed method is demonstrated with numerical simulations.
基金the Department of Education of Liaoning Province(Grant No.JDL2020020)the Changzhou Applied Basic Research Program(Grant No.CJ2020007).
文摘This paper proposes an adaptive unscented Kalman filter algorithm(ARUKF)to implement fault estimation for the dynamics of high⁃speed train(HST)with measurement uncertainty and time⁃varying noise with unknown statistics.Firstly,regarding the actuator and sensor fault as the auxiliary variables of the dynamics of HST,an augmented system is established,and the fault estimation problem for dynamics of HST is formulated as the state estimation of the augmented system.Then,considering the measurement uncertainties,a robust lower bound is proposed to modify the update of the UKF to decrease the influence of measurement uncertainty on the filtering accuracy.Further,considering the unknown time⁃varying noise of the dynamics of HST,an adaptive UKF algorithm based on moving window is proposed to estimate the time⁃varying noise so that accurate concurrent actuator and sensor fault estimations of dynamics of HST is implemented.Finally,a five-car model of HST is given to show the effectiveness of this method.
基金supported in part by the National Key Research and Development Program of China under grant(No.2022YFB4701400/4701401)by the National Natural Science Foundation of China under grant(No.61991400,No.61991403,No.62250710167,No.61860206008,No.61933012,No.62273064,No.62203078)+2 种基金in part by the National Key Research and Development Program of China under grant(No.2021ZD0201300)in part by the Innovation Support Program for International Students Returning to China under grant(No.cx2022016)in part by the Chongqing Medical Scientific Research Project under grant(No.2022DBXM001).
文摘In this paper,we consider the practical prescribed-time performance guaranteed tracking control problem for a class of uncertain strict-feedback systems subject to unknown control direction.Due to the existence of unknown nonlinearities and uncertainties,it is challenging to design a controller that can ensure the stability of closed-loop system within a predetermined finite time while maintaining the specified transient performance.The underlying problem becomes further complex as the control directions are unknown.To deal with the above problems,a special translation function as well as Nussbaum type function are introduced in the prescribed performance control(PPC)framework.Finally,a PPC as well as preset finite time tracking control scheme is designed,and its effectiveness is confirmed by both theoretical analysis and numerical simulation.
基金partially supported by National Key Research and Development Program of China(2019YFC1510902)National Natural Science Foundation of China(62073104)+1 种基金Natural Science Foundation of Heilongjiang Province(LH2022F024)China Postdoctoral Science Foundation(2022M710965)。
文摘This paper presents a subspace identification method for closed-loop systems with unknown deterministic disturbances.To deal with the unknown deterministic disturbances,two strategies are implemented to construct the row space that can be used to approximately represent the unknown deterministic disturbances using the trigonometric functions or Bernstein polynomials depending on whether the disturbance frequencies are known.For closed-loop identification,CCF-N4SID is extended to the case with unknown deterministic disturbances using the oblique projection.In addition,a proper Bernstein polynomial order can be determined using the Akaike information criterion(AIC)or the Bayesian information criterion(BIC).Numerical simulation results demonstrate the effectiveness of the proposed identification method for both periodic and aperiodic deterministic disturbances.
基金The authors extend their appreciation to the Deanship of Scientific Research at King Khalid University for funding this work underGrant Number(RGP 1/322/42)PrincessNourah bint Abdulrahman UniversityResearchers Supporting Project number(PNURSP2022R303)Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘In recent times,wireless sensor network(WSN)finds their suitability in several application areas,ranging from military to commercial ones.Since nodes in WSN are placed arbitrarily in the target field,node localization(NL)becomes essential where the positioning of the nodes can be determined by the aid of anchor nodes.The goal of any NL scheme is to improve the localization accuracy and reduce the localization error rate.With this motivation,this study focuses on the design of Intelligent Aquila Optimization Algorithm Based Node Localization Scheme(IAOAB-NLS)for WSN.The presented IAOAB-NLS model makes use of anchor nodes to determine proper positioning of the nodes.In addition,the IAOAB-NLS model is stimulated by the behaviour of Aquila.The IAOAB-NLS model has the ability to accomplish proper coordinate points of the nodes in the network.For guaranteeing the proficient NL process of the IAOAB-NLS model,widespread experimentation takes place to assure the betterment of the IAOAB-NLS model.The resultant values reported the effectual outcome of the IAOAB-NLS model irrespective of changing parameters in the network.
文摘There has been an increasing number of reported cases of acute hepatitis of unknown origin in previously healthy children since first reported on March 31,2022.This clinical syndrome is identified by jaundice and markedly elevated liver enzymes with increased aspartate transaminase and/or alanine aminotransa-minase(greater than 500 IU/L).We conducted an inclusive literature review with respect to acute hepatitis outbreaks in children using the search terms acute hepatitis,outbreak,children,severe acute respiratory syndrome coronavirus 2(SARS-CoV-2),coronavirus disease 2019(COVID-19),and adenovirus.According to the cumulative data presented in four main studies,the median age is 4 years,with a male predominance(1.3:1).Jaundice was the most common clinical manifestation(69%),followed by vomiting(63%),anorexia(52.9%),diarrhea(47.2%),abdominal pain(39%),pyrexia(33.3%),pale stool(30%),and dark urine(30%).Coryza and lethargy were reported in 16.6%,while pruritus was reported in 2%of cases.Acute liver failure was observed in 25%of cases.The exact mechanism of this acute hepatitis outbreak is still not entirely clear.Adenoviruses and SARS-CoV-2 were detected in a significant number of patients.Coinfection with adenovirus and SARS-CoV-2 could be a possible underlying mechanism.However,other possible infections and mechanisms must be considered in the pathogenesis of this condition.Acute hepatitis of unknown origin in children has been a serious problem since the start of the COVID-19 pandemic but has not yet been sufficiently addressed.Many questions remain regarding the underlying mechanisms leading to acute liver failure in children,and it is likely that extensive future research is needed.
文摘BACKGROUND Acute liver injury(ALI)refers to inflammation of the hepatic parenchyma without hepatic encephalopathy that lasts less than 6 mo.When the etiology is unknown,Acute Hepatitis of Unknown Origin(AHUO)can present as a diagnostic and treatment challenge.AHUO in the adult population is unusual and poorly documented.It has an incidence between 11%and 75%.Currently,no treatment guidelines exist.With no identified cause,treatment is often blind,and the wrong treatment plan may have unintended consequences.CASE SUMMARY We present the case of a 58-year-old woman who presented to the emergency room for elevated liver function tests(LFTs).Her symptoms started 10 d prior to admission and included nausea,vomiting,jaundice,decreased appetite,weight loss of 10 lbs,and dark urine.She denied drinking alcohol or taking any hepatotoxic agents,including acetaminophen,statins,vitamins,or supplements.She was admitted to the hospital,and an etiologic work-up was carried out.Her initial bloodwork revealed elevated liver enzymes(alanine aminotransferase 2500 U/L,aspartate aminotransferase 3159 U/L,and alkaline phosphatase 714 U/L)and elevated total bilirubin of 6.4 mg/dL.She tested negative for common infectious etiologies such as hepatotropic viruses A,B,C,and E.Further infective work-up revealed negative serology for cytomegalovirus,Epstein-Barr virus,herpes simplex virus 1&2,and human immunodeficiency virus.Her autoanti-body test results were negative,including anti-smooth muscle antibody,anti-mitochondrial antibody,and anti-liver kidney microsome 1 antibody.Magnetic resonance cholangiopancreatography ruled out biliary causes of elevated LFTs,and her core liver biopsy proved inconclusive.Over the course of her hospital stay,the patient's LFTs improved with supportive care and without steroids.CONCLUSION Idiopathic hepatitis makes treatment challenging.It can leave patients feeling confused and unfulfilled.Thus,educating the patient thoroughly for shared decision-making and management becomes essential.
文摘BACKGROUND Brucellosis is endemic in India with seropositivity rates as high as 10%in children in the eastern states,yet the disease is not on the radar when a differential diagnosis of pyrexia of unknown origin(PUO)is being considered,especially in children in urban set-up.This may be because of the non-specific multitude of systemic symptoms seen in this disease and the lack of awareness among clinicians.CASE SUMMARY We present a case of a 13-year-old boy,who came with a history of undulating fever for the past three and a half months,loss of appetite,and abdominal pain.The child had visited several pediatricians and was even admitted to a tertiary care hospital for PUO evaluation,but to no avail.He presented to us after three and half months of suffering and weight loss of more than 10%of body weight.His ultrasonography revealed thickening of the terminal ileum.His blood culture grew Brucella melitensis.A diagnosis of Brucellosis with terminal ileitis was made.Brucella serology by enzyme-linked immunoassay(ELISA)was positive for both IgG and IgM.He was treated with doxycycline and Rifampicin along with syrup multivitamin and zinc,for 6 wk.There was remarkable improvement with gain in 4 kg body weight within 2 mo of completing treatment.History revealed consumption of unpasteurized milk and contact with cattle.CONCLUSION Clinical suspicion,detailed history,appropriate laboratory investigations are the three pillars for diagnosing Brucellosis in patients presenting with vague symptoms.
文摘Fabry Disease (FD) is a rare lysosomal storage disorder characterized by α-galactosidase A (α-Gal A) enzyme deficiency, resulting in glycosphingolipid accumulation. Its clinical spectrum ranges from severe classical to milder nonclassical or late-onset phenotypes. Renal involvement, termed Fabry Nephropathy (FN), can vary from mild proteinuria to kidney failure. FN diagnosis, especially in nonclassical cases with a genetic Variant of Unknown Significance (VUS) in the GLA gene, poses challenges. Measurement of plasma lyso-Gb3 levels is gaining importance in FN diagnosis, while renal biopsy with electron microscopy remains the gold standard in equivocal cases. Treatment options include Enzyme Replacement Therapy (ERT) and chaperone therapy, demanding careful candidate selection due to high treatment costs. Research has predominantly focused on classical FD, revealing modest treatment benefits. However, evidence for treating patients, especially females, with milder nonclassical or late-onset phenotypes is scarce, emphasizing the necessity for placebo-controlled clinical trials in these subgroups. Meanwhile, participation in global FD registries can improve our understanding of disease management. Case Presentation: A woman in her late sixties presented with moderate chronic kidney disease, mild proteinuria, and microscopic hematuria. Her family history included a prevalence of renal, cardiac and cerebrovascular diseases. Kidney biopsy revealed characteristic myelin figures and zebra bodies in podocytes, strongly suggestive of FN. Genetic analysis identified a VUS in the GLA gene (c.655A > C, p.Ile219Leu), introducing diagnostic uncertainty. Further investigations revealed severe cardiac involvement. Considering the recurring difficulty presented by the finding of a VUS in the GLA gene during FN assessments, along with the uncertainty regarding the need for treatment in nonclassical or late-onset FD phenotypes, especially in women, this case becomes a central focus for a thorough review of the literature. This review aims to propose a practical algorithm that integrates clinical, biochemical, and genetic markers for FN screening and diagnosis. Additionally, it explores treatment benefits in nonclassical or late-onset FD phenotypes, with a focus on female patients.
文摘While reading plays a very important role in English study, many English language learners find it very difficult to fully comprehend some reading materials on account of many unknown words in them. This essay mainly discusses one technique of guessing meanings of new words according to context clues, thus emphasizing the importance of context.