Face liveness detection is essential for securing biometric authentication systems against spoofing attacks,including printed photos,replay videos,and 3D masks.This study systematically evaluates pre-trained CNN model...Face liveness detection is essential for securing biometric authentication systems against spoofing attacks,including printed photos,replay videos,and 3D masks.This study systematically evaluates pre-trained CNN models—DenseNet201,VGG16,InceptionV3,ResNet50,VGG19,MobileNetV2,Xception,and InceptionResNetV2—leveraging transfer learning and fine-tuning to enhance liveness detection performance.The models were trained and tested on NUAA and Replay-Attack datasets,with cross-dataset generalization validated on SiW-MV2 to assess real-world adaptability.Performance was evaluated using accuracy,precision,recall,FAR,FRR,HTER,and specialized spoof detection metrics(APCER,NPCER,ACER).Fine-tuning significantly improved detection accuracy,with DenseNet201 achieving the highest performance(98.5%on NUAA,97.71%on Replay-Attack),while MobileNetV2 proved the most efficient model for real-time applications(latency:15 ms,memory usage:45 MB,energy consumption:30 mJ).A statistical significance analysis(paired t-tests,confidence intervals)validated these improvements.Cross-dataset experiments identified DenseNet201 and MobileNetV2 as the most generalizable architectures,with DenseNet201 achieving 86.4%accuracy on Replay-Attack when trained on NUAA,demonstrating robust feature extraction and adaptability.In contrast,ResNet50 showed lower generalization capabilities,struggling with dataset variability and complex spoofing attacks.These findings suggest that MobileNetV2 is well-suited for low-power applications,while DenseNet201 is ideal for high-security environments requiring superior accuracy.This research provides a framework for improving real-time face liveness detection,enhancing biometric security,and guiding future advancements in AI-driven anti-spoofing techniques.展开更多
In this paper, we study the supervisory control problem of discrete event systems assuming that cyber-attacks might occur. In particular, we focus on the problem of liveness enforcement and consider a sensor-reading m...In this paper, we study the supervisory control problem of discrete event systems assuming that cyber-attacks might occur. In particular, we focus on the problem of liveness enforcement and consider a sensor-reading modification attack(SM-attack) that may disguise the occurrence of an event as that of another event by intruding sensor communication channels. To solve the problem, we introduce non-deterministic supervisors in the paper, which associate to every observed sequence a set of possible control actions offline and choose a control action from the set randomly online to control the system. Specifically, given a bounded Petri net(PN) as the reference formalism and an SMattack, an algorithm that synthesizes a liveness-enforcing nondeterministic supervisor tolerant to the SM-attack is proposed for the first time.展开更多
Fingerprint-spoofing attack often occurs when imposters gain access illegally by using artificial fingerprints,which are made of common fingerprint materials,such as silicon,latex,etc.Thus,to protect our privacy,many ...Fingerprint-spoofing attack often occurs when imposters gain access illegally by using artificial fingerprints,which are made of common fingerprint materials,such as silicon,latex,etc.Thus,to protect our privacy,many fingerprint liveness detection methods are put forward to discriminate fake or true fingerprint.Current work on liveness detection for fingerprint images is focused on the construction of complex handcrafted features,but these methods normally destroy or lose spatial information between pixels.Different from existing methods,convolutional neural network(CNN)can generate high-level semantic representations by learning and concatenating low-level edge and shape features from a large amount of labeled data.Thus,CNN is explored to solve the above problem and discriminate true fingerprints from fake ones in this paper.To reduce the redundant information and extract the most distinct features,ROI and PCA operations are performed for learned features of convolutional layer or pooling layer.After that,the extracted features are fed into SVM classifier.Experimental results based on the LivDet(2013)and the LivDet(2011)datasets,which are captured by using different fingerprint materials,indicate that the classification performance of our proposed method is both efficient and convenient compared with the other previous methods.展开更多
Fingerprint authentication system is used to verify users' identification according to the characteristics of their fingerprints.However,this system has some security and privacy problems.For example,some artifici...Fingerprint authentication system is used to verify users' identification according to the characteristics of their fingerprints.However,this system has some security and privacy problems.For example,some artificial fingerprints can trick the fingerprint authentication system and access information using real users' identification.Therefore,a fingerprint liveness detection algorithm needs to be designed to prevent illegal users from accessing privacy information.In this paper,a new software-based liveness detection approach using multi-scale local phase quantity(LPQ) and principal component analysis(PCA) is proposed.The feature vectors of a fingerprint are constructed through multi-scale LPQ.PCA technology is also introduced to reduce the dimensionality of the feature vectors and gain more effective features.Finally,a training model is gained using support vector machine classifier,and the liveness of a fingerprint is detected on the basis of the training model.Experimental results demonstrate that our proposed method can detect the liveness of users' fingerprints and achieve high recognition accuracy.This study also confirms that multi-resolution analysis is a useful method for texture feature extraction during fingerprint liveness detection.展开更多
Aim to countermeasure the presentation attack for iris recognition system,an iris liveness detection scheme based on batch normalized convolutional neural network(BNCNN)is proposed to improve the reliability of the ir...Aim to countermeasure the presentation attack for iris recognition system,an iris liveness detection scheme based on batch normalized convolutional neural network(BNCNN)is proposed to improve the reliability of the iris authentication system.The BNCNN architecture with eighteen layers is constructed to detect the genuine iris and fake iris,including convolutional layer,batch-normalized(BN)layer,Relu layer,pooling layer and full connected layer.The iris image is first preprocessed by iris segmentation and is normalized to 256×256 pixels,and then the iris features are extracted by BNCNN.With these features,the genuine iris and fake iris are determined by the decision-making layer.Batch normalization technique is used in BNCNN to avoid the problem of over fitting and gradient disappearing during training.Extensive experiments are conducted on three classical databases:the CASIA Iris Lamp database,the CASIA Iris Syn database and Ndcontact database.The results show that the proposed method can effectively extract micro texture features of the iris,and achieve higher detection accuracy compared with some typical iris liveness detection methods.展开更多
Contactless verification is possible with iris biometric identification,which helps prevent infections like COVID-19 from spreading.Biometric systems have grown unsteady and dangerous as a result of spoofing assaults ...Contactless verification is possible with iris biometric identification,which helps prevent infections like COVID-19 from spreading.Biometric systems have grown unsteady and dangerous as a result of spoofing assaults employing contact lenses,replayed the video,and print attacks.The work demonstrates an iris liveness detection approach by utilizing fragmental coefficients of Haar transformed Iris images as signatures to prevent spoofing attacks for the very first time in the identification of iris liveness.Seven assorted feature creation ways are studied in the presented solutions,and these created features are explored for the training of eight distinct machine learning classifiers and ensembles.The predicted iris liveness identification variants are evaluated using recall,F-measure,precision,accuracy,APCER,BPCER,and ACER.Three standard datasets were used in the investigation.The main contribution of our study is achieving a good accuracy of 99.18%with a smaller feature vector.The fragmental coefficients of Haar transformed iris image of size 8∗8 utilizing random forest algorithm showed superior iris liveness detection with reduced featured vector size(64 features).Random forest gave 99.18%accuracy.Additionally,conduct an extensive experiment on cross datasets for detailed analysis.The results of our experiments showthat the iris biometric template is decreased in size tomake the proposed framework suitable for algorithmic verification in real-time environments and settings.展开更多
This paper deals with the supervisory control problem of discrete event systems modeled by labeled Petri nets. The system is originally unbounded. First, the solvability of the problem is confirmed. A necessary condit...This paper deals with the supervisory control problem of discrete event systems modeled by labeled Petri nets. The system is originally unbounded. First, the solvability of the problem is confirmed. A necessary condition is given and proven for the existence of a feasible priority-based controller based on the notions of liveness and transition invariants. Next, a cyclic behavior graph is constructed, which shows the reachable markings that guarantee the maximum liveness of the system within a given bound vector. Finally, an on-line control strategy is proposed to enforce boundedness and liveness to the given system by appending priority relations to transitions. The dynamic priority relation changes flexibly according to the current state of the system and enforces the system evolving in a bounded and live manner. In addition, numerical examples are studied to verify the validity of the proposed approach that remains the structure of the plant net and is efficient for on-line control.展开更多
The probabilities for the technology to be spoofed are widely acknowledged in biometric verification system. Important efforts have been conducted to study such threats and to develop countermeasures to direct attacks...The probabilities for the technology to be spoofed are widely acknowledged in biometric verification system. Important efforts have been conducted to study such threats and to develop countermeasures to direct attacks to the biometric verification system to ensure the security of these systems against spoof attacks and reduce this risk, by using another module that is added to the biometric verification system called the “liveness detection” which uses different anatomical properties to distinguish between real and fake traits. Thus, the robustness of the system against direct attacks can be improved through increasing the security level offered to the final user. This paper is an attempt to construct support biometric security system to protect the iris biometric verification system from spoof attacks, through integrating the iris verification system with addition module called liveness detection which composed of two sub-modules (static and dynamic). A test has been performed, for iris verification phase performed on two types of database (MMU DB) for 180 samples and (CASIA DB) for 90 samples, and gave accuracy (99.44%) with FAR of (0.0277) and FRR (0.0055) for MMU DB, and accuracy (97.77%) with FAR of (0.0333) and FRR (0.0222) for CASIA DB.展开更多
Multi-living agent system （MLAS） is a new concept in the field of complex system research, which is peculiarly suitable for the design and analysis of a complex information system in a serious confrontation and tigh...Multi-living agent system （MLAS） is a new concept in the field of complex system research, which is peculiarly suitable for the design and analysis of a complex information system in a serious confrontation and tight constraint environment. However, the universal method to quantitatively measure the living degree of an MLAS remains uncertain, which is critical to the self-organizing process. Therefore, a novel analytic hierarchy process （AHP） based method with dependent pairwise comparison matrix （PCM） for the evaluation of living degree of the MLAS is proposed, which eliminates the shortcoming of fixed PCM in traditional process. Furthermore, to avoid the annoying procedure of the consistency validation, the PCMs are appropriately reconstructed. Through an illustration of the netted radar system, the calculation detail is explicitly presented. Altogether, the advanced evaluation method successfully accomplishes the preset objective and promotes the development of the MLAS theory and AHP as well.展开更多
BACKGROUND Transplant teams often hesitate to use the right kidney(RK)in living donor(LD)transplants due to the complexities of anastomosing the short,thin-walled right renal veins,which can potentially lead to graft ...BACKGROUND Transplant teams often hesitate to use the right kidney(RK)in living donor(LD)transplants due to the complexities of anastomosing the short,thin-walled right renal veins,which can potentially lead to graft loss or graft dysfunction.Nevertheless,circumstances may arise where selecting the RK over the left kidney(LK)is unavoidable.Consequently,it is crucial to thoroughly examine the implications of such a choice on the overall transplant outcome.AIM To compare transplant outcomes between recipients of RK and LK while examining the factors that influence these outcomes.METHODS We retrospectively analyzed data from adult patients who received LD kidney transplants involving meticulous patient selection and surgical techniques at our center from January 2020 to December 2023.We included all kidney donors who were over 18,fit to donate,and had undergone diethylenetriamine pentaacetic acid split function and/or computed tomography based volumetry.The variables examined comprised donor and recipient demographics,and outcome measures included technical graft loss(TGL),delayed or slow graft function(SGF),and post-transplant serum creatinine(SC)trends.We used a logistic regression model to assess the likelihood of adverse outcomes considering the donor kidney side.RESULTS Of the 250 transplants performed during the period,56(22%)were RKs.The recipient demographics and transplant factors were comparable for the right and LKs,except that the donor warm and cold ischemia time were shorter for RKs.TGL and SGF each occurred in 2%(n=1)of RKs and 0.5%(n=1)of LKs,the difference being insignificant.These complications,however,were not related to the venous anastomosis.One RK(2%)developed delayed graft function after 48 hours,which was attributable to postoperative hypoxia rather than the surgical technique.The post-transplant SC trend and mean SC at the last follow-up were similar across both kidney sides.CONCLUSION The donor kidney side has little impact on post-transplant adverse events and graft function in LD transplants,provided that careful patient selection and precise surgical techniques are employed.展开更多
With the advances in transplant oncology in recent years, the role of liver transplantation has expanded to make curative treatment a possibility for a wider patient population. We highlight strategies in Hong Kong, C...With the advances in transplant oncology in recent years, the role of liver transplantation has expanded to make curative treatment a possibility for a wider patient population. We highlight strategies in Hong Kong, China that have enabled preoperative prognostication for judicious patient selection, downstaging therapy to definitive treatment, and postoperative therapies that have provided a growing role for liver transplantation in patients with more advanced hepatocellular carcinoma.展开更多
Main cable displacement-controlled devices(DCDs)are key components for coordinating the vertical deformation of the main cable and main girder in the side span of continuous suspension bridges.To reveal the mechanical...Main cable displacement-controlled devices(DCDs)are key components for coordinating the vertical deformation of the main cable and main girder in the side span of continuous suspension bridges.To reveal the mechanical action mechanisms of DCD on bridge structures,a three-span continuous suspension bridge was taken as the engineering background in this study.The influence of different forms of DCD on the internal force and displacement of the components in the side span of the bridge and the structural dynamic characteristics were explored through numerical simulations.The results showed that the lack of DCD caused the main cable and main girder to have large vertical displacements.The stresses of other components were redistributed,and the safety factor of the suspenders at the side span was greatly reduced.The setting of DCD improved the vertical stiffness of the structure.The rigid DCD had larger internal forces,but its control effect on the internal forces at the side span was slightly better than that of the flexible DCD.Both forms of DCD effectively coordinated the deformation of the main cable and main girder and the stress distribution of components in the side span area.The choice of DCD form depends on the topographic factors of bridge sites and the design requirements of related components at the side span.展开更多
Liver transplantation(LT)has made significant progress in the treatment of end stage liver disease(ESLD).However,many patients still die from disease progression while awaiting transplantation.As the number of patient...Liver transplantation(LT)has made significant progress in the treatment of end stage liver disease(ESLD).However,many patients still die from disease progression while awaiting transplantation.As the number of patients on LT waiting lists is increasing,and the organ shortage crisis is obvious,various efforts have been made to increase the pool of available liver grafts[1].In addition to living donor liver transplantation(LDLT),improving the utilization rate of extended criteria donor(ECD)livers is an important way.However,under traditional cold storage,ECD livers are usually associated with a higher risk of ischemic biliary disease,early allograft dysfunction(EAD)or even primary nonfunction(PNF).The frequently described definition in the literature for ECD grafts generally includes elderly,steatotic,long cold ischemia time(CIT),grafts obtained from donation after circulatory death(DCD),split liver grafts,donors with increased risk of infectious disease transmission and prolonged donor intensive care unit stay[2].展开更多
This paper proposes an approach to making livehess model checking problems under fairness feasible.The proposed method divides such a problem into smaller ones that can be conquered.It is not superior to existing tool...This paper proposes an approach to making livehess model checking problems under fairness feasible.The proposed method divides such a problem into smaller ones that can be conquered.It is not superior to existing tools dedicated to model checking liveness properties under fairness assumptions in terms of model checking performance but has the following positive aspects:1)the approach can be used to model check liveness properties under anti-fairness assumptions as well as fairness assumptions,2)the approach can help humans better understand the reason why they need to use fairness and/or anti-fairness assumptions,and 3)the approach makes it possible to use existing linear temporal logic model checkers to model check liveness properties under fairness and/or anti-fairness assumptions.展开更多
Several liveness theorems for GFC (the generalized free choice) systems in a reductive approach are presented.What is interesting is that the characterization is just based on deadlocks,rather than on both deadlocks a...Several liveness theorems for GFC (the generalized free choice) systems in a reductive approach are presented.What is interesting is that the characterization is just based on deadlocks,rather than on both deadlocks and traps as Commoner characterizes the liveness of ordinary free-choice systems.Several proof techniques which may be useful for proving liveness of other types of net systems are also introduced.展开更多
基金funded by Centre for Advanced Modelling and Geospatial Information Systems(CAMGIS),Faculty of Engineering and IT,University of Technology Sydney.Moreover,Ongoing Research Funding Program(ORF-2025-14)King Saud University,Riyadh,Saudi Arabia,under Project ORF-2025-。
文摘Face liveness detection is essential for securing biometric authentication systems against spoofing attacks,including printed photos,replay videos,and 3D masks.This study systematically evaluates pre-trained CNN models—DenseNet201,VGG16,InceptionV3,ResNet50,VGG19,MobileNetV2,Xception,and InceptionResNetV2—leveraging transfer learning and fine-tuning to enhance liveness detection performance.The models were trained and tested on NUAA and Replay-Attack datasets,with cross-dataset generalization validated on SiW-MV2 to assess real-world adaptability.Performance was evaluated using accuracy,precision,recall,FAR,FRR,HTER,and specialized spoof detection metrics(APCER,NPCER,ACER).Fine-tuning significantly improved detection accuracy,with DenseNet201 achieving the highest performance(98.5%on NUAA,97.71%on Replay-Attack),while MobileNetV2 proved the most efficient model for real-time applications(latency:15 ms,memory usage:45 MB,energy consumption:30 mJ).A statistical significance analysis(paired t-tests,confidence intervals)validated these improvements.Cross-dataset experiments identified DenseNet201 and MobileNetV2 as the most generalizable architectures,with DenseNet201 achieving 86.4%accuracy on Replay-Attack when trained on NUAA,demonstrating robust feature extraction and adaptability.In contrast,ResNet50 showed lower generalization capabilities,struggling with dataset variability and complex spoofing attacks.These findings suggest that MobileNetV2 is well-suited for low-power applications,while DenseNet201 is ideal for high-security environments requiring superior accuracy.This research provides a framework for improving real-time face liveness detection,enhancing biometric security,and guiding future advancements in AI-driven anti-spoofing techniques.
基金supported in part by the Public Technology Research Plan of Zhejiang Province (LGJ21F030001)the National Natural Science Foundation of China (62302448)the Zhejiang Provincial Key Laboratory of New Network Standards and Technologies (2013E10012)。
文摘In this paper, we study the supervisory control problem of discrete event systems assuming that cyber-attacks might occur. In particular, we focus on the problem of liveness enforcement and consider a sensor-reading modification attack(SM-attack) that may disguise the occurrence of an event as that of another event by intruding sensor communication channels. To solve the problem, we introduce non-deterministic supervisors in the paper, which associate to every observed sequence a set of possible control actions offline and choose a control action from the set randomly online to control the system. Specifically, given a bounded Petri net(PN) as the reference formalism and an SMattack, an algorithm that synthesizes a liveness-enforcing nondeterministic supervisor tolerant to the SM-attack is proposed for the first time.
文摘Fingerprint-spoofing attack often occurs when imposters gain access illegally by using artificial fingerprints,which are made of common fingerprint materials,such as silicon,latex,etc.Thus,to protect our privacy,many fingerprint liveness detection methods are put forward to discriminate fake or true fingerprint.Current work on liveness detection for fingerprint images is focused on the construction of complex handcrafted features,but these methods normally destroy or lose spatial information between pixels.Different from existing methods,convolutional neural network(CNN)can generate high-level semantic representations by learning and concatenating low-level edge and shape features from a large amount of labeled data.Thus,CNN is explored to solve the above problem and discriminate true fingerprints from fake ones in this paper.To reduce the redundant information and extract the most distinct features,ROI and PCA operations are performed for learned features of convolutional layer or pooling layer.After that,the extracted features are fed into SVM classifier.Experimental results based on the LivDet(2013)and the LivDet(2011)datasets,which are captured by using different fingerprint materials,indicate that the classification performance of our proposed method is both efficient and convenient compared with the other previous methods.
基金supported by the NSFC (U1536206,61232016,U1405254,61373133, 61502242)BK20150925the PAPD fund
文摘Fingerprint authentication system is used to verify users' identification according to the characteristics of their fingerprints.However,this system has some security and privacy problems.For example,some artificial fingerprints can trick the fingerprint authentication system and access information using real users' identification.Therefore,a fingerprint liveness detection algorithm needs to be designed to prevent illegal users from accessing privacy information.In this paper,a new software-based liveness detection approach using multi-scale local phase quantity(LPQ) and principal component analysis(PCA) is proposed.The feature vectors of a fingerprint are constructed through multi-scale LPQ.PCA technology is also introduced to reduce the dimensionality of the feature vectors and gain more effective features.Finally,a training model is gained using support vector machine classifier,and the liveness of a fingerprint is detected on the basis of the training model.Experimental results demonstrate that our proposed method can detect the liveness of users' fingerprints and achieve high recognition accuracy.This study also confirms that multi-resolution analysis is a useful method for texture feature extraction during fingerprint liveness detection.
基金This work was supported in part by project supported by National Natural Science Foundation of China(Grant No.61572182,No.61370225)project supported by Hunan Provincial Natural Science Foundation of China(Grant No.15JJ2007).
文摘Aim to countermeasure the presentation attack for iris recognition system,an iris liveness detection scheme based on batch normalized convolutional neural network(BNCNN)is proposed to improve the reliability of the iris authentication system.The BNCNN architecture with eighteen layers is constructed to detect the genuine iris and fake iris,including convolutional layer,batch-normalized(BN)layer,Relu layer,pooling layer and full connected layer.The iris image is first preprocessed by iris segmentation and is normalized to 256×256 pixels,and then the iris features are extracted by BNCNN.With these features,the genuine iris and fake iris are determined by the decision-making layer.Batch normalization technique is used in BNCNN to avoid the problem of over fitting and gradient disappearing during training.Extensive experiments are conducted on three classical databases:the CASIA Iris Lamp database,the CASIA Iris Syn database and Ndcontact database.The results show that the proposed method can effectively extract micro texture features of the iris,and achieve higher detection accuracy compared with some typical iris liveness detection methods.
基金supported by theResearchers Supporting Project No.RSP-2021/14,King Saud University,Riyadh,Saudi Arabia.
文摘Contactless verification is possible with iris biometric identification,which helps prevent infections like COVID-19 from spreading.Biometric systems have grown unsteady and dangerous as a result of spoofing assaults employing contact lenses,replayed the video,and print attacks.The work demonstrates an iris liveness detection approach by utilizing fragmental coefficients of Haar transformed Iris images as signatures to prevent spoofing attacks for the very first time in the identification of iris liveness.Seven assorted feature creation ways are studied in the presented solutions,and these created features are explored for the training of eight distinct machine learning classifiers and ensembles.The predicted iris liveness identification variants are evaluated using recall,F-measure,precision,accuracy,APCER,BPCER,and ACER.Three standard datasets were used in the investigation.The main contribution of our study is achieving a good accuracy of 99.18%with a smaller feature vector.The fragmental coefficients of Haar transformed iris image of size 8∗8 utilizing random forest algorithm showed superior iris liveness detection with reduced featured vector size(64 features).Random forest gave 99.18%accuracy.Additionally,conduct an extensive experiment on cross datasets for detailed analysis.The results of our experiments showthat the iris biometric template is decreased in size tomake the proposed framework suitable for algorithmic verification in real-time environments and settings.
基金the Project of Industrial Internet and Integration of Industrialization and Industrialization of Guangxi,China under Grant No.Guigong2021-37.
文摘This paper deals with the supervisory control problem of discrete event systems modeled by labeled Petri nets. The system is originally unbounded. First, the solvability of the problem is confirmed. A necessary condition is given and proven for the existence of a feasible priority-based controller based on the notions of liveness and transition invariants. Next, a cyclic behavior graph is constructed, which shows the reachable markings that guarantee the maximum liveness of the system within a given bound vector. Finally, an on-line control strategy is proposed to enforce boundedness and liveness to the given system by appending priority relations to transitions. The dynamic priority relation changes flexibly according to the current state of the system and enforces the system evolving in a bounded and live manner. In addition, numerical examples are studied to verify the validity of the proposed approach that remains the structure of the plant net and is efficient for on-line control.
文摘The probabilities for the technology to be spoofed are widely acknowledged in biometric verification system. Important efforts have been conducted to study such threats and to develop countermeasures to direct attacks to the biometric verification system to ensure the security of these systems against spoof attacks and reduce this risk, by using another module that is added to the biometric verification system called the “liveness detection” which uses different anatomical properties to distinguish between real and fake traits. Thus, the robustness of the system against direct attacks can be improved through increasing the security level offered to the final user. This paper is an attempt to construct support biometric security system to protect the iris biometric verification system from spoof attacks, through integrating the iris verification system with addition module called liveness detection which composed of two sub-modules (static and dynamic). A test has been performed, for iris verification phase performed on two types of database (MMU DB) for 180 samples and (CASIA DB) for 90 samples, and gave accuracy (99.44%) with FAR of (0.0277) and FRR (0.0055) for MMU DB, and accuracy (97.77%) with FAR of (0.0333) and FRR (0.0222) for CASIA DB.
基金supported by the National Natural Science Foundation of China(61172176)
文摘Multi-living agent system （MLAS） is a new concept in the field of complex system research, which is peculiarly suitable for the design and analysis of a complex information system in a serious confrontation and tight constraint environment. However, the universal method to quantitatively measure the living degree of an MLAS remains uncertain, which is critical to the self-organizing process. Therefore, a novel analytic hierarchy process （AHP） based method with dependent pairwise comparison matrix （PCM） for the evaluation of living degree of the MLAS is proposed, which eliminates the shortcoming of fixed PCM in traditional process. Furthermore, to avoid the annoying procedure of the consistency validation, the PCMs are appropriately reconstructed. Through an illustration of the netted radar system, the calculation detail is explicitly presented. Altogether, the advanced evaluation method successfully accomplishes the preset objective and promotes the development of the MLAS theory and AHP as well.
文摘BACKGROUND Transplant teams often hesitate to use the right kidney(RK)in living donor(LD)transplants due to the complexities of anastomosing the short,thin-walled right renal veins,which can potentially lead to graft loss or graft dysfunction.Nevertheless,circumstances may arise where selecting the RK over the left kidney(LK)is unavoidable.Consequently,it is crucial to thoroughly examine the implications of such a choice on the overall transplant outcome.AIM To compare transplant outcomes between recipients of RK and LK while examining the factors that influence these outcomes.METHODS We retrospectively analyzed data from adult patients who received LD kidney transplants involving meticulous patient selection and surgical techniques at our center from January 2020 to December 2023.We included all kidney donors who were over 18,fit to donate,and had undergone diethylenetriamine pentaacetic acid split function and/or computed tomography based volumetry.The variables examined comprised donor and recipient demographics,and outcome measures included technical graft loss(TGL),delayed or slow graft function(SGF),and post-transplant serum creatinine(SC)trends.We used a logistic regression model to assess the likelihood of adverse outcomes considering the donor kidney side.RESULTS Of the 250 transplants performed during the period,56(22%)were RKs.The recipient demographics and transplant factors were comparable for the right and LKs,except that the donor warm and cold ischemia time were shorter for RKs.TGL and SGF each occurred in 2%(n=1)of RKs and 0.5%(n=1)of LKs,the difference being insignificant.These complications,however,were not related to the venous anastomosis.One RK(2%)developed delayed graft function after 48 hours,which was attributable to postoperative hypoxia rather than the surgical technique.The post-transplant SC trend and mean SC at the last follow-up were similar across both kidney sides.CONCLUSION The donor kidney side has little impact on post-transplant adverse events and graft function in LD transplants,provided that careful patient selection and precise surgical techniques are employed.
文摘With the advances in transplant oncology in recent years, the role of liver transplantation has expanded to make curative treatment a possibility for a wider patient population. We highlight strategies in Hong Kong, China that have enabled preoperative prognostication for judicious patient selection, downstaging therapy to definitive treatment, and postoperative therapies that have provided a growing role for liver transplantation in patients with more advanced hepatocellular carcinoma.
基金The National Natural Science Foundation of China(No.52338011)the Postgraduate Research&Practice Innovation Program of Jiangsu Province(No.SJCX23_0067).
文摘Main cable displacement-controlled devices(DCDs)are key components for coordinating the vertical deformation of the main cable and main girder in the side span of continuous suspension bridges.To reveal the mechanical action mechanisms of DCD on bridge structures,a three-span continuous suspension bridge was taken as the engineering background in this study.The influence of different forms of DCD on the internal force and displacement of the components in the side span of the bridge and the structural dynamic characteristics were explored through numerical simulations.The results showed that the lack of DCD caused the main cable and main girder to have large vertical displacements.The stresses of other components were redistributed,and the safety factor of the suspenders at the side span was greatly reduced.The setting of DCD improved the vertical stiffness of the structure.The rigid DCD had larger internal forces,but its control effect on the internal forces at the side span was slightly better than that of the flexible DCD.Both forms of DCD effectively coordinated the deformation of the main cable and main girder and the stress distribution of components in the side span area.The choice of DCD form depends on the topographic factors of bridge sites and the design requirements of related components at the side span.
文摘Liver transplantation(LT)has made significant progress in the treatment of end stage liver disease(ESLD).However,many patients still die from disease progression while awaiting transplantation.As the number of patients on LT waiting lists is increasing,and the organ shortage crisis is obvious,various efforts have been made to increase the pool of available liver grafts[1].In addition to living donor liver transplantation(LDLT),improving the utilization rate of extended criteria donor(ECD)livers is an important way.However,under traditional cold storage,ECD livers are usually associated with a higher risk of ischemic biliary disease,early allograft dysfunction(EAD)or even primary nonfunction(PNF).The frequently described definition in the literature for ECD grafts generally includes elderly,steatotic,long cold ischemia time(CIT),grafts obtained from donation after circulatory death(DCD),split liver grafts,donors with increased risk of infectious disease transmission and prolonged donor intensive care unit stay[2].
文摘This paper proposes an approach to making livehess model checking problems under fairness feasible.The proposed method divides such a problem into smaller ones that can be conquered.It is not superior to existing tools dedicated to model checking liveness properties under fairness assumptions in terms of model checking performance but has the following positive aspects:1)the approach can be used to model check liveness properties under anti-fairness assumptions as well as fairness assumptions,2)the approach can help humans better understand the reason why they need to use fairness and/or anti-fairness assumptions,and 3)the approach makes it possible to use existing linear temporal logic model checkers to model check liveness properties under fairness and/or anti-fairness assumptions.
文摘Several liveness theorems for GFC (the generalized free choice) systems in a reductive approach are presented.What is interesting is that the characterization is just based on deadlocks,rather than on both deadlocks and traps as Commoner characterizes the liveness of ordinary free-choice systems.Several proof techniques which may be useful for proving liveness of other types of net systems are also introduced.
