Non-Deterministic Liveness-Enforcing Supervisor Tolerant to Sensor-Reading Modification Attacks

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.

Iris Liveness Detection Using Fragmental Energy of Haar Transformed Iris Images Using Ensemble of Machine Learning Classifiers

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.

Boundedness and liveness enforcement for labeled Petri nets using transition priority

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.

Fingerprint Liveness Detection from Different Fingerprint Materials Using Convolutional Neural Network and Principal Component Analysis

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.

Fingerprint Liveness Detection Based on Multi-Scale LPQ and PCA

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.

Detecting Iris Liveness with Batch Normalized Convolutional Neural Network

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.

Integrate Liveness Detection with Iris Verification to Construct Support Biometric System

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.

Liveness evaluation of multi-living agent system

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.

Liver transplantation and resection in patients with hepatocellular cancer and portal vein tumor thrombosis: Feasible and effective?

Patients with locally advanced hepatocellular cancer(HCC)and portal vein tumor thrombosis(PVTT)have a dismal prognosis since limited treatment options are available for them.In recent years,effective systemic therapy,and advances in the understanding of technicalities and effectiveness of ablative therapies especially radiotherapy,have given some hope to prolong survival in them.This review summarized recent evidence in literature regarding the possible role of liver resection(LR)and liver transplantation(LT)in patients with locally advanced HCC and PVTT with no extrahepatic disease.Downstaging therapies have helped make curative resection or LT a reality in selected patients.This review emphasizes on the key points to focus on when considering surgery in these patients,who are usually relegated to palliative systemic therapy alone.Meticulous patient selection based on tumor biology,documented downstaging based on imaging and decrease in tumor marker levels,and an adequate waiting period to demonstrate stable disease,may help obtain satisfactory long-term outcomes post LR or LT in an intention to treat strategy in patients with HCC and PVTT.

The impact of the Rural Minimum Living Standard Guarantee(Rural Dibao)Program on child nutrition outcomes

The Rural Minimum Living Standard Guarantee(Rural Dibao)is an important unconditional cash transfer program to alleviate poverty in rural China.Despite the importance of children’s nutrition in breaking poverty cycles,little is known about the impact of Rural Dibao on child nutrition outcomes.Using China Family Panel Studies(CFPS),this paper examines the effects of Rural Dibao on child nutrition outcomes and investigates potential pathways and heterogeneous effects.We exploit propensity score matching and difference-in-differences techniques to evaluate the effects of the Rural Dibao program on child nutrition outcomes.Our results suggest that Rural Dibao significantly impacts the nutrition outcomes of children up to 15 years of age.Specifically,our results suggest that Rural Dibao improves child height-to-age z-scores by 1.05 standard deviations and lowers the probability of stunting by 11.9 percentage points.Additional analyses suggest that increased protein intake is the main pathway through which Rural Dibao participation contributes to better nutrition outcomes.We also find that the effect of the program is more pronounced among girls,children who are non-left-behind or live with highly educated mothers,and those from low-income families and poor areas.Our findings suggest that Rural Dibao participation helps improve child nutrition outcomes through improving diet quality.

Development and validation of a prediction model for early screening of people at high risk for colorectal cancer

BACKGROUND Colorectal cancer(CRC)is a serious threat worldwide.Although early screening is suggested to be the most effective method to prevent and control CRC,the current situation of early screening for CRC is still not optimistic.In China,the incidence of CRC in the Yangtze River Delta region is increasing dramatically,but few studies have been conducted.Therefore,it is necessary to develop a simple and efficient early screening model for CRC.AIM To develop and validate an early-screening nomogram model to identify individuals at high risk of CRC.METHODS Data of 64448 participants obtained from Ningbo Hospital,China between 2014 and 2017 were retrospectively analyzed.The cohort comprised 64448 individuals,of which,530 were excluded due to missing or incorrect data.Of 63918,7607(11.9%)individuals were considered to be high risk for CRC,and 56311(88.1%)were not.The participants were randomly allocated to a training set(44743)or validation set(19175).The discriminatory ability,predictive accuracy,and clinical utility of the model were evaluated by constructing and analyzing receiver operating characteristic(ROC)curves and calibration curves and by decision curve analysis.Finally,the model was validated internally using a bootstrap resampling technique.RESULTS Seven variables,including demographic,lifestyle,and family history information,were examined.Multifactorial logistic regression analysis revealed that age[odds ratio(OR):1.03,95%confidence interval(CI):1.02-1.03,P<0.001],body mass index(BMI)(OR:1.07,95%CI:1.06-1.08,P<0.001),waist circumference(WC)(OR:1.03,95%CI:1.02-1.03 P<0.001),lifestyle(OR:0.45,95%CI:0.42-0.48,P<0.001),and family history(OR:4.28,95%CI:4.04-4.54,P<0.001)were the most significant predictors of high-risk CRC.Healthy lifestyle was a protective factor,whereas family history was the most significant risk factor.The area under the curve was 0.734(95%CI:0.723-0.745)for the final validation set ROC curve and 0.735(95%CI:0.728-0.742)for the training set ROC curve.The calibration curve demonstrated a high correlation between the CRC high-risk population predicted by the nomogram model and the actual CRC high-risk population.CONCLUSION The early-screening nomogram model for CRC prediction in high-risk populations developed in this study based on age,BMI,WC,lifestyle,and family history exhibited high accuracy.

Effect of solvent on the initiation mechanism of living anionic polymerization of styrene:A computational study

For living anionic polymerization(LAP),solvent has a great influence on both reaction mechanism and kinetics.In this work,by using the classical butyl lithium-styrene polymerization as a model system,the effect of solvent on the mechanism and kinetics of LAP was revealed through a strategy combining density functional theory(DFT)calculations and kinetic modeling.In terms of mechanism,it is found that the stronger the solvent polarity,the more electrons transfer from initiator to solvent through detailed energy decomposition analysis of electrostatic interactions between initiator and solvent molecules.Furthermore,we also found that the stronger the solvent polarity,the higher the monomer initiation energy barrier and the smaller the initiation rate coefficient.Counterintuitively,initiation is more favorable at lower temperatures based on the calculated results ofΔG_(TS).Finally,the kinetic characteristics in different solvents were further examined by kinetic modeling.It is found that in benzene and n-pentane,the polymerization rate exhibits first-order kinetics.While,slow initiation and fast propagation were observed in tetrahydrofuran(THF)due to the slow free ion formation rate,leading to a deviation from first-order kinetics.

Relationship Between Individuals’Epidemic Risk Perception Within Living Space and Subjective Well-Being:Empirical Evidence from China after the First Wave of COVID-19

It is common to observe the epidemic risk perception(ERP)and a decline in subjective well-being(SWB)in the context of public health events,such as Corona Virus Disease 2019(COVID-19).However,there have been few studies exploring the impact of individuals’ERP within living space on their SWB,especially from a geographical and daily activity perspective after the resumption of work and other activities following a wave of the pandemic.In this paper,we conducted a study with 789 participants in urban China,measuring their ERP within living space and examining its influence on their SWB using path analysis.The results indicated that individuals’ERP within their living space had a significant negative effect on their SWB.The density of certain types of facilities within their living space,such as bus stops,subway stations,restaurants,fast food shops,convenience shops,hospitals,and public toilets,had a significantly negative impact on their SWB,mediated by their ERP within living space.Additionally,participation in out-of-home work and other activities not only increased individuals’ERP within living space,but also strengthened its negative effect on their SWB.

Multiplexed stimulated emission depletion nanoscopy(mSTED)for 5-color live-cell long-term imaging of organelle interactome

Stimulated emission depletion microscopy(STED)holds great potential in biological science applications,especially in studying nanoscale subcellular structures.However,multi-color STED imaging in live-cell remains challenging due to the limited excitation wavelengths and large amount of laser radiation.Here,we develop a multiplexed live-cell STED method to observe more structures simultaneously with limited photo-bleaching and photo-cytotoxicity.By separating live-cell fluorescent probes with similar spectral properties using phasor analysis,our method enables five-color live-cell STED imaging and reveals long-term interactions between different subcellular structures.The results here provide an avenue for understanding the complex and delicate interactome of subcellular structures in live-cell.

Individual alcohol consumption by the population of Russia versus regional living conditions

Background:There are substantial regional differences in drinking alcohol in Russia,both at the population and individual levels.However,the causes of these differences have not been studied yet.Objective:The goal of our study was to examine the effect of regional living conditions on individual alcohol consumption by the population of Russia.Methods:For the analysis,we used data from a cross-sectional epidemiological study conducted in 2013-2014.The final analytical sample included 18,130 people aged 25-64 years.We conducted the interviews face to face,based on which any drinking in the last year,as well as alcohol abuse,were considered as a response.Alcohol abuse was recorded when the respondent consumed 5.75 or more grams of pure ethanol per day(75th percentile of average daily alcohol consumption among alcohol drinkers).The assessment of the regional living conditions was accomplished via integral indexing,which was previously performed based on publicly available data for 2010-2014.Associations were assessed using generalized scoring equations with unchanging standard errors.The associations were expressed by odds ratios(OR)and 95%confidence intervals(C).Results:Deterioration of social conditions and increase in demographic depression in the region of residence increased the odds of any drinking(OR 1.51,95%CI:1.33 to 1.72,P<0.001 and OR 1.22,95%CI:1.05 to 1.41,P=0.oo9,respectively).The odds of alcohol abuse increased with the deterioration of social living conditions and the growth of the industrial development in the region:OR 1.35,95%CI:1.14 to 1.59,P<0.001 and OR 1.16,95%CI:1.05 to 1.28,P=0.002,respectively.Conclusion:Our analysis allowed assessing the impact of the regional living conditions on individual drinking alcohol in the population of Russia.

Establishing delivery route-dependent safety and efficacy of living biodrug mesenchymal stem cells in heart failure patients

BACKGROUND Mesenchymal stem cells(MSCs)as living biopharmaceuticals with unique properties,i.e.,stemness,viability,phenotypes,paracrine activity,etc.,need to be administered such that they reach the target site,maintaining these properties unchanged and are retained at the injury site to participate in the repair process.Route of delivery(RoD)remains one of the critical determinants of safety and efficacy.This study elucidates the safety and effectiveness of different RoDs of MSC treatment in heart failure(HF)based on phase II randomized clinical trials(RCTs).We hypothesize that the RoD modulates the safety and efficacy of MSCbased therapy and determines the outcome of the intervention.AIM To investigate the effect of RoD of MSCs on safety and efficacy in HF patients.METHODS RCTs were retrieved from six databases.Safety endpoints included mortality and serious adverse events(SAEs),while efficacy outcomes encompassed changes in left ventricular ejection fraction(LVEF),6-minute walk distance(6MWD),and pro-B-type natriuretic peptide(pro-BNP).Subgroup analyses on RoD were performed for all study endpoints.RESULTS Twelve RCTs were included.Overall,MSC therapy demonstrated a significant decrease in mortality[relative risk(RR):0.55,95%confidence interval(95%CI):0.33-0.92,P=0.02]compared to control,while SAE outcomes showed no significant difference(RR:0.84,95%CI:0.66-1.05,P=0.11).RoD subgroup analysis revealed a significant difference in SAE among the transendocardial(TESI)injection subgroup(RR=0.71,95%CI:0.54-0.95,P=0.04).The pooled weighted mean difference(WMD)demonstrated an overall significant improvement of LVEF by 2.44%(WMD:2.44%,95%CI:0.80-4.29,P value≤0.001),with only intracoronary(IC)subgroup showing significant improvement(WMD:7.26%,95%CI:5.61-8.92,P≤0.001).Furthermore,the IC delivery route significantly improved 6MWD by 115 m(WMD=114.99 m,95%CI:91.48-138.50),respectively.In biochemical efficacy outcomes,only the IC subgroup showed a significant reduction in pro-BNP by-860.64 pg/mL(WMD:-860.64 pg/Ml,95%CI:-944.02 to-777.26,P=0.001).CONCLUSION Our study concluded that all delivery methods of MSC-based therapy are safe.Despite the overall benefits in efficacy,the TESI and IC routes provided better outcomes than other methods.Larger-scale trials are warranted before implementing MSC-based therapy in routine clinical practice.

Design Method for Optimizing the Interactive Interface of Live Broadcasting Platform for the Elderly Users

In the era of network live broadcasting for everyone,the development of live broadcasting platforms is also more intelligent and diversified.However,in the face of a large group of elderly users,the interface interaction design mode used is still mainly based on the interaction mode for young groups,and is not designed for elderly users.Therefore,a design method for optimizing the interaction interface of live broadcasting platform for elderly users was proposed in this study.Firstly,the case study method and Delphi expert survey method were used to determine the design needs of elderly users and the design mode was analysed.Secondly,the orthogonal design principle was used to design a test sample of the interactive interface of live broadcasting platform applicable for the elderly users,and then a user evaluation system was established to calculate the weights of the design elements using hierarchical analysis,and then the predictive relationship between the design mode of the interactive interface of live broadcasting platform and the elderly users was established by Quantitative Theory I.Finally,Genetic Algorithm was applied to generate the optimized design scheme.The results showed that the design method based on the Genetic Algorithm and the combination of Quantitative Theory can scientifically and effectively optimize the design of the interactive interface of the live broadcasting platform for the elderly users,and improve the experience of the elderly users.

Assessing the role of forest resources in improving rural livelihoods in West Bengal of India

Forest resources play a vital role in supporting the livelihoods of rural communities residing in forest-rich areas.In India,a forest-rich country,a significant proportion of non-timber forest products(NTFPs)is consumed locally,supporting numerous rural communities relying on forests for essential resources,such as firewood,timber,and NTFPs.This study focuses on two forest-dominant districts in West Bengal of India,namely,Jhargram District and Paschim Medinipur District.Furthermore,this study aims to enhance the understanding of forest-dependent communities by comparing the standard of living among different village classes.Thus,we categorized villages into three classes based on the distance from home to forests,including inner villages,fringe villages,and outer villages.Through focus group discussions and household surveys,we explored the sources of local economy,income sources of household,and reasons for economic diversification in different village classes.The study findings confirm that substantial variations existed in the income sources and the standard of living in these villages.Forest income varied dramatically among the three village classes,with inner villages having greater forest income than fringe villages and outer villages.Meanwhile,households in outer villages depended on forests and engaged in diverse economic activities for their livelihoods.Compared with inner and fringe villages,households in outer villages derived a significant portion of their income from livestock.This discrepancy can be attributed to challenges,such as inadequate transportation,communication,and underdeveloped market chains in inner villages.Moreover,these findings emphasize the need to develop sustainable forest management practices,create alternative income-generation opportunities,and improve infrastructure and market access in inner villages,as well as promote economic diversification in outer villages.Through targeted policy measures,these forest-rich regions can achieve improved livelihoods,enhanced standard of living,and increased resilience for their communities.

Personalized and continuous care intervention affects rehabilitation,living quality,and negative emotions of patients with breast cancer

BACKGROUND Breast cancer is among the most common malignancies worldwide.With progress in treatment methods and levels,the overall survival period has been prolonged,and the demand for quality care has increased.AIM To investigate the effect of individualized and continuous care intervention in patients with breast cancer.METHODS Two hundred patients with breast cancer who received systemic therapy at The First Affiliated Hospital of Hebei North University(January 2021 to July 2023)were retrospectively selected as research participants.Among them,134 received routine care intervention(routing group)and 66 received personalized and continuous care(intervention group).Self-rating anxiety scale(SAS),self-rating depression scale(SDS),and Functional Assessment of Cancer Therapy-Breast(FACT-B)scores,including limb shoulder joint activity,complication rate,and care satisfaction,were compared between both groups after care.RESULTS SAS and SDS scores were lower in the intervention group than in the routing group at one and three months after care.The total FACT-B scores and five dimensions in the intervention group were higher than those in the routing group at three months of care.The range of motion of shoulder anteflexion,posterior extension,abduction,internal rotation,and external rotation in the intervention group was higher than that in the routing group one month after care.The incidence of postoperative complications was 18.18%lower in the intervention group than in the routing group(34.33%;P<0.05).Satisfaction with care was 90.91% higher in the intervention group than in the routing group(78.36%;P<0.05).CONCLUSION Personalized and continuous care can alleviate negative emotions in patients with breast cancer,quicken rehabilitation of limb function,decrease the incidence of complications,and improve living quality and care satisfaction.

Associations of PNPLA3 and LEP genetic polymorphisms with metabolic-associated fatty liver disease in Thai people living with human immunodeficiency virus

BACKGROUND The prevalence of metabolic-associated fatty liver disease(MAFLD)is a growing public health issue in people living with human immunodeficiency virus(PLWH).However,the pathophysiology of MAFLD is still unknown,and the role of genetic variables is only now becoming evident.AIM To evaluate the associations of gene-polymorphism-related MAFLD in PLWH.METHODS The study employed transient elastography with a controlled attenuation parameter≥248 dB/m to identify MAFLD in patients from a Super Tertiary Hospital in central Thailand.Candidate single-nucleotide polymorphisms(SNPs)were genotyped using TaqMan®MGB probe 5'nuclease assays for seven MAFLD-related genes.Statistical analyses included SNP frequency analysis,Fisher's Exact and Chi-square tests,odds ratio calculations,and multivariable logistic regression.RESULTS The G-allele carriers of PNPLA3(rs738409)exhibited a two-fold rise in MAFLD,increasing by 2.5 times in MAFLD with human immunodeficiency virus infection.The clinical features and genetic patterns imply that LEP rs7799039 A-allele carriers had a nine times(P=0.001)more significant chance of developing aberrant triglyceride among PLWH.CONCLUSION The current study shows an association between PNPLA3 rs738409 and LEP rs7799039 with MAFLD in PLWH.