The global surge in electric vehicle(EV)adoption is proportionally expanding the EV charging station(EVCS)infrastructure,thereby increasing the attack surface and potential impact of security breaches within this crit...The global surge in electric vehicle(EV)adoption is proportionally expanding the EV charging station(EVCS)infrastructure,thereby increasing the attack surface and potential impact of security breaches within this critical ecosystem.While ISO 15118 standardizes EV-EVCS communication,its underspecified security guidelines and the variability in manufacturers’implementations frequently result in vulnerabilities that can disrupt charging services,compromise user data,or affect power grid stability.This research introduces a systematic black-box fuzzing methodology,accompanied by an open-source tool,to proactively identify and mitigate such security flaws in EVCS firmware operating under ISO 15118.The proposed approach systematically evaluates EVCS behavior by leveraging the state machine defined in the ISO 15118 standard for test case generation and execution,enabling platform-agnostic testing at the application layer.Message sequences,corresponding to valid andmutated traversals of the protocol’s state machine,are generated to uncover logical errors and improper input handling.Themethodology comprises state-aware initial sequence generation,simulated V2G session establishment,targeted message mutation correlated with defined protocol states,and rigorous response analysis to detect anomalies and system crashes.Experimental validation on an open-source EVCS implementation identified five vulnerabilities.These included session integrity weaknesses allowing unauthorized interruptions,billing manipulation through invalid metering data acceptance,and resource exhaustion vulnerabilities from specific parameter malformations leading to denial-of-service.The findings confirm the proposed method’s capability in pinpointing vulnerabilities often overlooked by standard conformance tests,thus offering a robust and practical solution for enhancing the security and resilience of the rapidly growing EV charging infrastructure.展开更多
The accelerated global adoption of electric vehicles(EVs)is driving significant expansion and increasing complexity within the EV charging infrastructure,consequently presenting novel and pressing cybersecurity challe...The accelerated global adoption of electric vehicles(EVs)is driving significant expansion and increasing complexity within the EV charging infrastructure,consequently presenting novel and pressing cybersecurity challenges.While considerable effort has focused on preventative cybersecurity measures,a critical deficiency persists in structured methodologies for digital forensic analysis following security incidents,a gap exacerbated by system heterogeneity,distributed digital evidence,and inconsistent logging practices which hinder effective incident reconstruction and attribution.This paper addresses this critical need by proposing a novel,data-driven forensic framework tailored to the EV charging infrastructure,focusing on the systematic identification,classification,and correlation of diverse digital evidence across its physical,network,and application layers.Our methodology integrates open-source intelligence(OSINT)with advanced system modeling based on a three-layer cyber-physical system architecture to comprehensively map potential evidentiary sources.Key contributions include a comprehensive taxonomy of cybersecurity threats pertinent to EV charging ecosystems,detailed mappings between these threats and the resultant digital evidence to guide targeted investigations,the formulation of adaptable forensic investigation workflows for various incident scenarios,and a critical analysis of significant gaps in digital evidence availability within current EV charging systems,highlighting limitations in forensic readiness.The practical application and utility of this method are demonstrated through illustrative case studies involving both empirically-derived and virtual incident scenarios.The proposed datadriven approach is designed to significantly enhance digital forensic capabilities,support more effective incident response,strengthen compliance with emerging cybersecurity regulations,and ultimately contribute to bolstering the overall security,resilience,and trustworthiness of this increasingly vital critical infrastructure.展开更多
Delaying skin-aging through diet is a hot research topic in recent years,but the anti-aging effects of fish gelatin and related mechanisms are not well understood.In this study,we prepared edible fish gelatin from the...Delaying skin-aging through diet is a hot research topic in recent years,but the anti-aging effects of fish gelatin and related mechanisms are not well understood.In this study,we prepared edible fish gelatin from the swim bladder of Cynoscion acoupa using three different processing methods,namely dried(DCM),soaked(SCM)and instanted(ICM),to investigate its anti-aging effects and mechanisms on D-galactose induced skin aging in mice,as well as its effects on the gut microbiota.The results demonstrated that fish gelatin significantly increased water content,collagen,hyaluronic acid(HA)and hydroxyproline(Hyp)content,and skin integrity of mice skin,as well as enhanced the antioxidative ability and anti-inflammatory capacity of the skin.In terms of protein and mRNA expression levels in skin tissue,CMs treated with different treatments can up-regulate the expression of epidermal growth factor receptor(EGFR)and tissue inhibitor of metal protease 1(TIMP1),down-regulating the expression of matrix metalloproteinase 1(MMP1)and matrix metalloproteinase 3(MMP3),and increase the expression of collagen type III alpha 1 chain(COL3A1)and collagen type I alpha 2 chain(COL1A2).CMs attenuated the D-galactose-mediated inhibition collagen expression by stimulating the transforming growth factor beta(TGF-β)/Smad signaling pathway,thereby maintaining collagen matrix homeostasis.In addition,we revealed that CMs reversed gut microbiota by increase the abundance of intestinal flora.In conclusion,we demonstrated that CMs,especially for ICM,as an effective dietary supplement,have potential anti-aging and skin health benefits.展开更多
Large-scale point cloud datasets form the basis for training various deep learning networks and achieving high-quality network processing tasks.Due to the diversity and robustness constraints of the data,data augmenta...Large-scale point cloud datasets form the basis for training various deep learning networks and achieving high-quality network processing tasks.Due to the diversity and robustness constraints of the data,data augmentation(DA)methods are utilised to expand dataset diversity and scale.However,due to the complex and distinct characteristics of LiDAR point cloud data from different platforms(such as missile-borne and vehicular LiDAR data),directly applying traditional 2D visual domain DA methods to 3D data can lead to networks trained using this approach not robustly achieving the corresponding tasks.To address this issue,the present study explores DA for missile-borne LiDAR point cloud using a Monte Carlo(MC)simulation method that closely resembles practical application.Firstly,the model of multi-sensor imaging system is established,taking into account the joint errors arising from the platform itself and the relative motion during the imaging process.A distortion simulation method based on MC simulation for augmenting missile-borne LiDAR point cloud data is proposed,underpinned by an analysis of combined errors between different modal sensors,achieving high-quality augmentation of point cloud data.The effectiveness of the proposed method in addressing imaging system errors and distortion simulation is validated using the imaging scene dataset constructed in this paper.Comparative experiments between the proposed point cloud DA algorithm and the current state-of-the-art algorithms in point cloud detection and single object tracking tasks demonstrate that the proposed method can improve the network performance obtained from unaugmented datasets by over 17.3%and 17.9%,surpassing SOTA performance of current point cloud DA algorithms.展开更多
As mobile networks become high speed and attain an all-IP structure, more services are possible. This brings about many new security requirements that traditional security programs cannot handle. This paper analyzes s...As mobile networks become high speed and attain an all-IP structure, more services are possible. This brings about many new security requirements that traditional security programs cannot handle. This paper analyzes security threats and the needs of 3G/4G mobile networks, and then proposes a novel protection scheme for them based on their whole structure. In this scheme, a trusted computing environment is constructed on the mobile terminal side by combining software validity verification with access control. At the security management center, security services such as validity verification and integrity check are provided to mobile terminals. In this way, terminals and the network as a whole are secured to a much greater extent. This paper also highlights problems to be addressed in future research and development.展开更多
Centralized storage and identity identification methods pose many risks,including hacker attacks,data misuse,and single points of failure.Additionally,existing centralized identity management methods face interoperabi...Centralized storage and identity identification methods pose many risks,including hacker attacks,data misuse,and single points of failure.Additionally,existing centralized identity management methods face interoperability issues and rely on a single identity provider,leaving users without control over their identities.Therefore,this paper proposes a mechanism for identity identification and data sharing based on decentralized identifiers.The scheme utilizes blockchain technology to store the identifiers and data hashed on the chain to ensure permanent identity recognition and data integrity.Data is stored on InterPlanetary File System(IPFS)to avoid the risk of single points of failure and to enhance data persistence and availability.At the same time,compliance with World Wide Web Consortium(W3C)standards for decentralized identifiers and verifiable credentials increases the mechanism’s scalability and interoperability.展开更多
The rapid proliferation of Internet of Things(IoT)technology has facilitated automation across various sectors.Nevertheless,this advancement has also resulted in a notable surge in cyberattacks,notably botnets.As a re...The rapid proliferation of Internet of Things(IoT)technology has facilitated automation across various sectors.Nevertheless,this advancement has also resulted in a notable surge in cyberattacks,notably botnets.As a result,research on network analysis has become vital.Machine learning-based techniques for network analysis provide a more extensive and adaptable approach in comparison to traditional rule-based methods.In this paper,we propose a framework for analyzing communications between IoT devices using supervised learning and ensemble techniques and present experimental results that validate the efficacy of the proposed framework.The results indicate that using the proposed ensemble techniques improves accuracy by up to 1.7%compared to single-algorithm approaches.These results also suggest that the proposed framework can flexibly adapt to general IoT network analysis scenarios.Unlike existing frameworks,which only exhibit high performance in specific situations,the proposed framework can serve as a fundamental approach for addressing a wide range of issues.展开更多
2023 will be the inaugural year of a new artificial intelligence(AI) development round. The rapid advancement and proliferation of AI technologies and applications send shock waves worldwide. However, the risks hidden...2023 will be the inaugural year of a new artificial intelligence(AI) development round. The rapid advancement and proliferation of AI technologies and applications send shock waves worldwide. However, the risks hidden behind AI's immense energy have sparked heated debate and controversy. Powered by AI technologies and applications, the intelligent era seems to have begun.展开更多
Ice krill is the keystone species in the neritic ecosystem in the Southern Ocean, where it replaces the more oceanic Antarctic krill. It is essential to understand the variation of target strength （TS in dB re l m^2...Ice krill is the keystone species in the neritic ecosystem in the Southern Ocean, where it replaces the more oceanic Antarctic krill. It is essential to understand the variation of target strength （TS in dB re l m^2） with the different body size to accurately estimate ice krill stocks. However, there is comparatively little knowledge of the acoustic backscatter of ice krill. The TS of individual, formalin-preserved, tethered ice krill was measured in a freshwater test tank at 38, 120, and 200 kHz with a calibrated split-beam echo sounder system. Mean TS was obtained from 21 individual ice krill with a broad range of body lengths （L： 13-36 iron）. The length （L, mm） to wet weight （W; mg） relationship for ice krill was 11/=0.001 21g^103~L35s （R2=0.96）. The mean TS-to-length relationship were TS38kHz=-177.4＋57log10（L）, （R^2=0.86）; TS120kHz= -129.9＋31.561ogf0（L）, （R2=0.87）; and TS200kHz=-117.6＋24.661ogre（L）, （R2=0.84）. Empirical estimates of the relationship between the TS and body length of ice krill were established at 38, 120, and 200 kHz and compared with predictions obtained from both the linear regression model of Greene et al. （1991） and the Stochastic Distorted Wave Born Approximation （SDWBA） model. This result might be applied to improve acoustic detection and density estimation of ice krill in the Southern Ocean. Further comparative studies are needed with in situ target strength including various body lengths of ice krill.展开更多
Certificateless public key cryptography （CL-PKC） avoids the inherent escrow of identity-based cryptography and does not require certificates to guarantee the authenticity of public keys. Based on CL-PKC, we present ...Certificateless public key cryptography （CL-PKC） avoids the inherent escrow of identity-based cryptography and does not require certificates to guarantee the authenticity of public keys. Based on CL-PKC, we present an efficient constant-round group key exchange protocol, which is provably secure under the intractability of computation Diffie-Hellman problem. Our protocol is a contributory key exchange with perfect forward secrecy and has only two communication rounds. So it is more efficient than other protocols. Moreover, our protocol provides a method to design efficient constant-round group key exchange protocols and most secret sharing schemes could be adopted to construct our protocol.展开更多
AIM To determine the predictive role of body mass index(BMI) and waist circumference(WC) for diabetes and prediabetes risk in future in total sample as well as in men and women separately. METHODS In a population base...AIM To determine the predictive role of body mass index(BMI) and waist circumference(WC) for diabetes and prediabetes risk in future in total sample as well as in men and women separately. METHODS In a population based cohort study, 1765 with mean ± SD age: 42.32 ± 6.18 healthy participants were followed up from 2003 till 2013(n = 960). Anthropometric and biochemical measures of participants were evaluated regularly during the follow up period. BMI and WC measures at baseline and diabetes and prediabetes status of participants at 2013 were determined. Multivariable logistic regression analysis was used for determining the risk of diabetes and prediabetes considering important potential confounding variables. Receiver operatingcharacteristic curve analysis was conducted to determine the best cut of values of BMI and WC for diabetes and prediabetes. RESULTS At 2013, among participants who had complete data, 45 and 307 people were diabetic and prediabetic, respectively. In final fully adjusted model, BMI value was a significant predictor of diabetes(RR = 1.39, 95%CI: 1.06-1.82 and AUC = 0.68, 95%CI: 0.59-0.75; P < 0.001) however not a significant risk factor for prediabetes. Also, WC was a significant predictor for diabetes(RR = 1.2, 95%CI: 1.05-1.38 and AUC = 0.67, 95%CI: 0.6-0.75) but not significant risk factor for prediabetes. Similar results were observed in both genders.CONCLUSION General and abdominal obesity are significant risk factors for diabetes in future.展开更多
Because the small CACHE size of computers, the scanning speed of DFA based multi-pattern string-matching algorithms slows down rapidly especially when the number of patterns is very large. For solving such problems, w...Because the small CACHE size of computers, the scanning speed of DFA based multi-pattern string-matching algorithms slows down rapidly especially when the number of patterns is very large. For solving such problems, we cut down the scanning time of those algorithms (i.e. DFA based) by rearranging the states table and shrinking the DFA alphabet size. Both the methods can decrease the probability of large-scale random memory accessing and increase the probability of continuously memory accessing. Then the hitting rate of the CACHE is increased and the searching time of on the DFA is reduced. Shrinking the alphabet size of the DFA also reduces the storage complication. The AC++algorithm, by optimizing the Aho-Corasick (i.e. AC) algorithm using such methods, proves the theoretical analysis. And the experimentation results show that the scanning time of AC++and the storage occupied is better than that of AC in most cases and the result is much attractive when the number of patterns is very large. Because DFA is a widely used base algorithm in may string matching algorithms, such as DAWG, SBOM etc., the optimizing method discussed is significant in practice.展开更多
Radio frequency identification(RFID)has been widespread used in massive items tagged domains.However,tag collision increases both time and energy consumption of RFID network.Tag collision can seriously affect the succ...Radio frequency identification(RFID)has been widespread used in massive items tagged domains.However,tag collision increases both time and energy consumption of RFID network.Tag collision can seriously affect the success of tag identification.An efficient anti-collision protocol is very crucially in RFID system.In this paper,an improved binary search anti-collision protocol namely BRTP is proposed to cope with the tag collision concern,which introduces a Bi-response mechanism.In Bi-response mechanism,two groups of tags allowed to reply to the reader in the same slot.According to Bi-response mechanism,the BRTP strengthens the tag identification of RFID network by reducing the total number of queries and exchanged messages between the reader and tags.Both theoretical analysis and numerical results verify the effectiveness of the proposed BRTP in various performance metrics including the number of total slots,system efficiency,communication complexity and total identification time.The BRTP is suitable to be applied in passive RFID systems.展开更多
In Wireless Sensor Network(WSN),because battery and energy supply are constraints,sleep scheduling is always needed to save energy while maintaining connectivity for packet delivery.Traditional schemes have to ensure ...In Wireless Sensor Network(WSN),because battery and energy supply are constraints,sleep scheduling is always needed to save energy while maintaining connectivity for packet delivery.Traditional schemes have to ensure high duty cycling to ensure enough percentage of active nodes and then derogate the energy efficiency.This paper proposes an RFID based non-preemptive random sleep scheduling scheme with stable low duty cycle.It employs delay tolerant network routing protocol to tackle the frequent disconnections.A low-power RFID based non-preemptive wakeup signal is used to confirm the availability of next-hop before sending packet.It eliminates energy consumption of repeated retransmission of the delayed packets.Moreover,the received wakeup signal is postponed to take effect until the sleep period is finished,and the waken node then responds to the sending node to start the packet delivery.The scheme can keep stable duty cycle and then ensure energy saving effect compared with other sleeping scheduling methods.展开更多
A collective user web behavior simulation is an import means for generating a large-scale user network behavior in a network testbed or cyber range.Existing studies almost focus on individual web behavior analysis and...A collective user web behavior simulation is an import means for generating a large-scale user network behavior in a network testbed or cyber range.Existing studies almost focus on individual web behavior analysis and prediction,which cannot simulate human dynamics that widely exist in large-scale users’behaviors.To address these issues,we propose a novel collective user web behavior simulation method,in which an algorithm for constructing a connected virtual social network is proposed,and then a collective user web behavior simulation algorithm is designed on the virtual social network.In the simulation method,a new epidemic information dissemination algorithm based on the SIR model is proposed to drive the user web behavior with Breadth—First Search algorithm on the connected virtual social network.We specially build an experiment environment with 12 servers by using Docker container technology and then perform a wide range of experiments with different user scales to evaluate the method.The experimental results demonstrate that not only the degrees of the social network but also the time intervals of the collective users’web behavior can be well fitted to a power-law distribution and show that our simulation method can well simulate a collective user web behavior.展开更多
Using the hydroacoustic method with a 200 kHz scientific echo sounding system, the diel vertical migration （DVM） of the sound-scatteringlayer （SSL） in the Yellow Sea Bottom Cold Water （YSBCW） of the southeastern...Using the hydroacoustic method with a 200 kHz scientific echo sounding system, the diel vertical migration （DVM） of the sound-scatteringlayer （SSL） in the Yellow Sea Bottom Cold Water （YSBCW） of the southeastern Yellow Sea was studied in April （spring） and August （summer） of 2010 and 2011. For each survey, 13-27 hours of acoustic data were continuously collected at a stationary station. The acoustic volume scattering strength （Sv） data were analyzed with temperature profile data. In the spring of both 2010 and 2011, the SSL clearly showed the vertical migration throughout the entire water column, moving from the surface layer at night to near the bottom during the day. Conductivity, temperature, and depth data indicated that the entire water column was well mixed with low temperature of about 8℃. However, the SSL showed different patterns in the summers of 2010 and 2011. In the summer of 2010 （≈28℃ at the surface）, the SSL migrated to near the bottom during the day, but there were two SSLs above and below the thermocline at depth of 10-30 m at night. In the summer of 2011 （≈20℃ at the surface）, the SSL extended throughout the entire water column at night, possibly owing to an abrupt change in sea weather conditions caused by the passage of a Typhoon Muifa over the study area. It was cancluded that the DVM patterns in summer in the YSBCW area may be greatly influenced by a strengthened or weakened thermocline.展开更多
BACKGROUND The risk of developing prediabetes based on the metabolic/obesity phenotypes has been poorly investigated. AIM To examine the association of baseline metabolic/obesity phenotypes and their changes over time...BACKGROUND The risk of developing prediabetes based on the metabolic/obesity phenotypes has been poorly investigated. AIM To examine the association of baseline metabolic/obesity phenotypes and their changes over time with the risk of prediabetes development. METHODS In a population-based cohort study, 1741 adults (aged > 19 years) with normal blood glucose were followed for 14 years. Anthropometric and biochemical measures were evaluated regularly during the follow-up period. According to body mass index and metabolic health status, participants were categorized into four groups: Metabolically healthy normal weight (MHNW), metabolically healthy obese (MHO), metabolically unhealthy normal weight (MUNW) and metabolically unhealthy obese (MUO). Multivariable Cox regression analysis was used to measure the risk of prediabetes according to the baseline metabolic/obesity phenotype and their changes during the follow-up. RESULTS In the whole population with a mean (95CCI for mean) follow up duration of 12.7 years (12.6-12.9), all three MUNW, MHO, MUO groups were at higher risk for developing prediabetes compared to the MHNW group (P = 0.022). The MUNW group had the highest risk for developing prediabetes (hazard ratio (HR): 3.84, 95%CI: 1.20, 12.27). In stratified analysis by sex, no significant association was found in men, while women in the MUNW group were at the greatest risk for prediabetes (HR: 6.74, 95%CI: 1.53, 29.66). Transforming from each phenotype to MHNW or MHO was not related to the risk of prediabetes development, whereas transforming from each phenotype to MUO was associated with an increased risk of prediabetes (HR > 1;P < 0.05). CONCLUSION Our findings indicate that MHO is not a high risk, unless it transforms into MUO over time. However, people in the MUNW group have the greatest risk for developing prediabetes, and therefore, they should be screened and treated.展开更多
With the enormous developmen t of imformation and communicat ion technology,more concerns are focused to achieve secure and reliable smart grids as the social infrastrueture,especially in the explosion era of mobile d...With the enormous developmen t of imformation and communicat ion technology,more concerns are focused to achieve secure and reliable smart grids as the social infrastrueture,especially in the explosion era of mobile devices.In this paper,we propose an efficient scheme to satis勿the outdoor electrical demand of mobile customers.Our scheme protects the privacy and integrity of users'electricity consumption data.Technically,we encrypt users'electricity consumption data by a chosen-plai nt ext-at tack(CPA)secure public key encryption(PKE)scheme and aggregate ciphertexts by the aggregator(an untrusted third party).In the scheme,internal and external adversaries cannot obtain the electricity consumption data.Additionally,we require users to provide authentication and commitment of consumption data that can track who modifies the data,which protects the integrity of users1 electricity consumption data.展开更多
基金support of the Korea Internet&Security Agency(KISA)—Information Security Specialized University Support Project(50%)supported by a grant from the Korea Electric Power Corporation(R24XO01-4,50%)for basic research and development projects starting in 2024.
文摘The global surge in electric vehicle(EV)adoption is proportionally expanding the EV charging station(EVCS)infrastructure,thereby increasing the attack surface and potential impact of security breaches within this critical ecosystem.While ISO 15118 standardizes EV-EVCS communication,its underspecified security guidelines and the variability in manufacturers’implementations frequently result in vulnerabilities that can disrupt charging services,compromise user data,or affect power grid stability.This research introduces a systematic black-box fuzzing methodology,accompanied by an open-source tool,to proactively identify and mitigate such security flaws in EVCS firmware operating under ISO 15118.The proposed approach systematically evaluates EVCS behavior by leveraging the state machine defined in the ISO 15118 standard for test case generation and execution,enabling platform-agnostic testing at the application layer.Message sequences,corresponding to valid andmutated traversals of the protocol’s state machine,are generated to uncover logical errors and improper input handling.Themethodology comprises state-aware initial sequence generation,simulated V2G session establishment,targeted message mutation correlated with defined protocol states,and rigorous response analysis to detect anomalies and system crashes.Experimental validation on an open-source EVCS implementation identified five vulnerabilities.These included session integrity weaknesses allowing unauthorized interruptions,billing manipulation through invalid metering data acceptance,and resource exhaustion vulnerabilities from specific parameter malformations leading to denial-of-service.The findings confirm the proposed method’s capability in pinpointing vulnerabilities often overlooked by standard conformance tests,thus offering a robust and practical solution for enhancing the security and resilience of the rapidly growing EV charging infrastructure.
基金supported by the National Research Foundation of Korea(NRF)grant funded by the Korea government(MSIT)(RS-2023-00242528,50%)supported by a grant from the Korea Electric Power Corporation(R24XO01-4,50%)for basic research and development projects starting in 2024.
文摘The accelerated global adoption of electric vehicles(EVs)is driving significant expansion and increasing complexity within the EV charging infrastructure,consequently presenting novel and pressing cybersecurity challenges.While considerable effort has focused on preventative cybersecurity measures,a critical deficiency persists in structured methodologies for digital forensic analysis following security incidents,a gap exacerbated by system heterogeneity,distributed digital evidence,and inconsistent logging practices which hinder effective incident reconstruction and attribution.This paper addresses this critical need by proposing a novel,data-driven forensic framework tailored to the EV charging infrastructure,focusing on the systematic identification,classification,and correlation of diverse digital evidence across its physical,network,and application layers.Our methodology integrates open-source intelligence(OSINT)with advanced system modeling based on a three-layer cyber-physical system architecture to comprehensively map potential evidentiary sources.Key contributions include a comprehensive taxonomy of cybersecurity threats pertinent to EV charging ecosystems,detailed mappings between these threats and the resultant digital evidence to guide targeted investigations,the formulation of adaptable forensic investigation workflows for various incident scenarios,and a critical analysis of significant gaps in digital evidence availability within current EV charging systems,highlighting limitations in forensic readiness.The practical application and utility of this method are demonstrated through illustrative case studies involving both empirically-derived and virtual incident scenarios.The proposed datadriven approach is designed to significantly enhance digital forensic capabilities,support more effective incident response,strengthen compliance with emerging cybersecurity regulations,and ultimately contribute to bolstering the overall security,resilience,and trustworthiness of this increasingly vital critical infrastructure.
基金supported by the China Agriculture Research System of MOF and MARA(CARS-21)Key-Area Research and Development Program of Guangdong Province(2022B0202050001).
文摘Delaying skin-aging through diet is a hot research topic in recent years,but the anti-aging effects of fish gelatin and related mechanisms are not well understood.In this study,we prepared edible fish gelatin from the swim bladder of Cynoscion acoupa using three different processing methods,namely dried(DCM),soaked(SCM)and instanted(ICM),to investigate its anti-aging effects and mechanisms on D-galactose induced skin aging in mice,as well as its effects on the gut microbiota.The results demonstrated that fish gelatin significantly increased water content,collagen,hyaluronic acid(HA)and hydroxyproline(Hyp)content,and skin integrity of mice skin,as well as enhanced the antioxidative ability and anti-inflammatory capacity of the skin.In terms of protein and mRNA expression levels in skin tissue,CMs treated with different treatments can up-regulate the expression of epidermal growth factor receptor(EGFR)and tissue inhibitor of metal protease 1(TIMP1),down-regulating the expression of matrix metalloproteinase 1(MMP1)and matrix metalloproteinase 3(MMP3),and increase the expression of collagen type III alpha 1 chain(COL3A1)and collagen type I alpha 2 chain(COL1A2).CMs attenuated the D-galactose-mediated inhibition collagen expression by stimulating the transforming growth factor beta(TGF-β)/Smad signaling pathway,thereby maintaining collagen matrix homeostasis.In addition,we revealed that CMs reversed gut microbiota by increase the abundance of intestinal flora.In conclusion,we demonstrated that CMs,especially for ICM,as an effective dietary supplement,have potential anti-aging and skin health benefits.
基金Postgraduate Innovation Top notch Talent Training Project of Hunan Province,Grant/Award Number:CX20220045Scientific Research Project of National University of Defense Technology,Grant/Award Number:22-ZZCX-07+2 种基金New Era Education Quality Project of Anhui Province,Grant/Award Number:2023cxcysj194National Natural Science Foundation of China,Grant/Award Numbers:62201597,62205372,1210456foundation of Hefei Comprehensive National Science Center,Grant/Award Number:KY23C502。
文摘Large-scale point cloud datasets form the basis for training various deep learning networks and achieving high-quality network processing tasks.Due to the diversity and robustness constraints of the data,data augmentation(DA)methods are utilised to expand dataset diversity and scale.However,due to the complex and distinct characteristics of LiDAR point cloud data from different platforms(such as missile-borne and vehicular LiDAR data),directly applying traditional 2D visual domain DA methods to 3D data can lead to networks trained using this approach not robustly achieving the corresponding tasks.To address this issue,the present study explores DA for missile-borne LiDAR point cloud using a Monte Carlo(MC)simulation method that closely resembles practical application.Firstly,the model of multi-sensor imaging system is established,taking into account the joint errors arising from the platform itself and the relative motion during the imaging process.A distortion simulation method based on MC simulation for augmenting missile-borne LiDAR point cloud data is proposed,underpinned by an analysis of combined errors between different modal sensors,achieving high-quality augmentation of point cloud data.The effectiveness of the proposed method in addressing imaging system errors and distortion simulation is validated using the imaging scene dataset constructed in this paper.Comparative experiments between the proposed point cloud DA algorithm and the current state-of-the-art algorithms in point cloud detection and single object tracking tasks demonstrate that the proposed method can improve the network performance obtained from unaugmented datasets by over 17.3%and 17.9%,surpassing SOTA performance of current point cloud DA algorithms.
基金funded by the National High-Technology Research and Development Program of China"(863"Program)under Grant No.2009AA01Z427
文摘As mobile networks become high speed and attain an all-IP structure, more services are possible. This brings about many new security requirements that traditional security programs cannot handle. This paper analyzes security threats and the needs of 3G/4G mobile networks, and then proposes a novel protection scheme for them based on their whole structure. In this scheme, a trusted computing environment is constructed on the mobile terminal side by combining software validity verification with access control. At the security management center, security services such as validity verification and integrity check are provided to mobile terminals. In this way, terminals and the network as a whole are secured to a much greater extent. This paper also highlights problems to be addressed in future research and development.
文摘Centralized storage and identity identification methods pose many risks,including hacker attacks,data misuse,and single points of failure.Additionally,existing centralized identity management methods face interoperability issues and rely on a single identity provider,leaving users without control over their identities.Therefore,this paper proposes a mechanism for identity identification and data sharing based on decentralized identifiers.The scheme utilizes blockchain technology to store the identifiers and data hashed on the chain to ensure permanent identity recognition and data integrity.Data is stored on InterPlanetary File System(IPFS)to avoid the risk of single points of failure and to enhance data persistence and availability.At the same time,compliance with World Wide Web Consortium(W3C)standards for decentralized identifiers and verifiable credentials increases the mechanism’s scalability and interoperability.
基金supported by Innovative Human Resource Development for Local Intellectualization program through the Institute of Information&Communications Technology Planning&Evaluation(IITP)grant funded by the Korea government(MSIT)(IITP2024-00156287,50%)funded by the Institute for Information&Communications Technology Planning&Evaluation(IITP)grant funded by the Korea government(MSIT)(No.2022-0-01203,Regional Strategic Industry Convergence Security Core Talent Training Business,50%).
文摘The rapid proliferation of Internet of Things(IoT)technology has facilitated automation across various sectors.Nevertheless,this advancement has also resulted in a notable surge in cyberattacks,notably botnets.As a result,research on network analysis has become vital.Machine learning-based techniques for network analysis provide a more extensive and adaptable approach in comparison to traditional rule-based methods.In this paper,we propose a framework for analyzing communications between IoT devices using supervised learning and ensemble techniques and present experimental results that validate the efficacy of the proposed framework.The results indicate that using the proposed ensemble techniques improves accuracy by up to 1.7%compared to single-algorithm approaches.These results also suggest that the proposed framework can flexibly adapt to general IoT network analysis scenarios.Unlike existing frameworks,which only exhibit high performance in specific situations,the proposed framework can serve as a fundamental approach for addressing a wide range of issues.
文摘2023 will be the inaugural year of a new artificial intelligence(AI) development round. The rapid advancement and proliferation of AI technologies and applications send shock waves worldwide. However, the risks hidden behind AI's immense energy have sparked heated debate and controversy. Powered by AI technologies and applications, the intelligent era seems to have begun.
基金Supported by the Korea Polar Research Institute(No.PP14020)the Korea Institute of Ocean Science and Technology(No.PN65250)
文摘Ice krill is the keystone species in the neritic ecosystem in the Southern Ocean, where it replaces the more oceanic Antarctic krill. It is essential to understand the variation of target strength （TS in dB re l m^2） with the different body size to accurately estimate ice krill stocks. However, there is comparatively little knowledge of the acoustic backscatter of ice krill. The TS of individual, formalin-preserved, tethered ice krill was measured in a freshwater test tank at 38, 120, and 200 kHz with a calibrated split-beam echo sounder system. Mean TS was obtained from 21 individual ice krill with a broad range of body lengths （L： 13-36 iron）. The length （L, mm） to wet weight （W; mg） relationship for ice krill was 11/=0.001 21g^103~L35s （R2=0.96）. The mean TS-to-length relationship were TS38kHz=-177.4＋57log10（L）, （R^2=0.86）; TS120kHz= -129.9＋31.561ogf0（L）, （R2=0.87）; and TS200kHz=-117.6＋24.661ogre（L）, （R2=0.84）. Empirical estimates of the relationship between the TS and body length of ice krill were established at 38, 120, and 200 kHz and compared with predictions obtained from both the linear regression model of Greene et al. （1991） and the Stochastic Distorted Wave Born Approximation （SDWBA） model. This result might be applied to improve acoustic detection and density estimation of ice krill in the Southern Ocean. Further comparative studies are needed with in situ target strength including various body lengths of ice krill.
基金Supported by the National Natural Science Foundation of China (90204012, 60573035, 60573036) and the University IT Research Center Project of Korea
文摘Certificateless public key cryptography （CL-PKC） avoids the inherent escrow of identity-based cryptography and does not require certificates to guarantee the authenticity of public keys. Based on CL-PKC, we present an efficient constant-round group key exchange protocol, which is provably secure under the intractability of computation Diffie-Hellman problem. Our protocol is a contributory key exchange with perfect forward secrecy and has only two communication rounds. So it is more efficient than other protocols. Moreover, our protocol provides a method to design efficient constant-round group key exchange protocols and most secret sharing schemes could be adopted to construct our protocol.
文摘AIM To determine the predictive role of body mass index(BMI) and waist circumference(WC) for diabetes and prediabetes risk in future in total sample as well as in men and women separately. METHODS In a population based cohort study, 1765 with mean ± SD age: 42.32 ± 6.18 healthy participants were followed up from 2003 till 2013(n = 960). Anthropometric and biochemical measures of participants were evaluated regularly during the follow up period. BMI and WC measures at baseline and diabetes and prediabetes status of participants at 2013 were determined. Multivariable logistic regression analysis was used for determining the risk of diabetes and prediabetes considering important potential confounding variables. Receiver operatingcharacteristic curve analysis was conducted to determine the best cut of values of BMI and WC for diabetes and prediabetes. RESULTS At 2013, among participants who had complete data, 45 and 307 people were diabetic and prediabetic, respectively. In final fully adjusted model, BMI value was a significant predictor of diabetes(RR = 1.39, 95%CI: 1.06-1.82 and AUC = 0.68, 95%CI: 0.59-0.75; P < 0.001) however not a significant risk factor for prediabetes. Also, WC was a significant predictor for diabetes(RR = 1.2, 95%CI: 1.05-1.38 and AUC = 0.67, 95%CI: 0.6-0.75) but not significant risk factor for prediabetes. Similar results were observed in both genders.CONCLUSION General and abdominal obesity are significant risk factors for diabetes in future.
文摘Because the small CACHE size of computers, the scanning speed of DFA based multi-pattern string-matching algorithms slows down rapidly especially when the number of patterns is very large. For solving such problems, we cut down the scanning time of those algorithms (i.e. DFA based) by rearranging the states table and shrinking the DFA alphabet size. Both the methods can decrease the probability of large-scale random memory accessing and increase the probability of continuously memory accessing. Then the hitting rate of the CACHE is increased and the searching time of on the DFA is reduced. Shrinking the alphabet size of the DFA also reduces the storage complication. The AC++algorithm, by optimizing the Aho-Corasick (i.e. AC) algorithm using such methods, proves the theoretical analysis. And the experimentation results show that the scanning time of AC++and the storage occupied is better than that of AC in most cases and the result is much attractive when the number of patterns is very large. Because DFA is a widely used base algorithm in may string matching algorithms, such as DAWG, SBOM etc., the optimizing method discussed is significant in practice.
基金This work was partially supported by the Key-Area Research and Development Program of Guangdong Province(2019B010136001,20190166)the Basic and Applied Basic Research Major Program for Guangdong Province(2019B030302002)the Science and Technology Planning Project of Guangdong Province LZC0023 and LZC0024.
文摘Radio frequency identification(RFID)has been widespread used in massive items tagged domains.However,tag collision increases both time and energy consumption of RFID network.Tag collision can seriously affect the success of tag identification.An efficient anti-collision protocol is very crucially in RFID system.In this paper,an improved binary search anti-collision protocol namely BRTP is proposed to cope with the tag collision concern,which introduces a Bi-response mechanism.In Bi-response mechanism,two groups of tags allowed to reply to the reader in the same slot.According to Bi-response mechanism,the BRTP strengthens the tag identification of RFID network by reducing the total number of queries and exchanged messages between the reader and tags.Both theoretical analysis and numerical results verify the effectiveness of the proposed BRTP in various performance metrics including the number of total slots,system efficiency,communication complexity and total identification time.The BRTP is suitable to be applied in passive RFID systems.
基金This work is supported in part by the National Natural Science Foundation of China(61871140,61572153,U1636215,61572492,61672020)the National Key research and Development Plan(Grant No.2018YFB0803504).
文摘In Wireless Sensor Network(WSN),because battery and energy supply are constraints,sleep scheduling is always needed to save energy while maintaining connectivity for packet delivery.Traditional schemes have to ensure high duty cycling to ensure enough percentage of active nodes and then derogate the energy efficiency.This paper proposes an RFID based non-preemptive random sleep scheduling scheme with stable low duty cycle.It employs delay tolerant network routing protocol to tackle the frequent disconnections.A low-power RFID based non-preemptive wakeup signal is used to confirm the availability of next-hop before sending packet.It eliminates energy consumption of repeated retransmission of the delayed packets.Moreover,the received wakeup signal is postponed to take effect until the sleep period is finished,and the waken node then responds to the sending node to start the packet delivery.The scheme can keep stable duty cycle and then ensure energy saving effect compared with other sleeping scheduling methods.
基金National Key Research and Development Plan under Grant 2017YFB0801804,Key Research and Development Plan of Shandong Province under Grant 2017CXGC0706Peng Cheng Laboratory Project of Guangdong Province PCL2018KP004+1 种基金frontier science and technology innovation of China under Grant 2016QY05X1002-2national regional innovation center scientific and technological special projects Grant 2017QYCX14,University Coconstruction Project in Weihai City.
文摘A collective user web behavior simulation is an import means for generating a large-scale user network behavior in a network testbed or cyber range.Existing studies almost focus on individual web behavior analysis and prediction,which cannot simulate human dynamics that widely exist in large-scale users’behaviors.To address these issues,we propose a novel collective user web behavior simulation method,in which an algorithm for constructing a connected virtual social network is proposed,and then a collective user web behavior simulation algorithm is designed on the virtual social network.In the simulation method,a new epidemic information dissemination algorithm based on the SIR model is proposed to drive the user web behavior with Breadth—First Search algorithm on the connected virtual social network.We specially build an experiment environment with 12 servers by using Docker container technology and then perform a wide range of experiments with different user scales to evaluate the method.The experimental results demonstrate that not only the degrees of the social network but also the time intervals of the collective users’web behavior can be well fitted to a power-law distribution and show that our simulation method can well simulate a collective user web behavior.
基金The China-Korea cooperative project"The study on the impact of the Yellow Sea Cold Water Mass to the ecosystem"under contract No.PE99165promoted by the Korea Institute of Ocean Science and Technology
文摘Using the hydroacoustic method with a 200 kHz scientific echo sounding system, the diel vertical migration （DVM） of the sound-scatteringlayer （SSL） in the Yellow Sea Bottom Cold Water （YSBCW） of the southeastern Yellow Sea was studied in April （spring） and August （summer） of 2010 and 2011. For each survey, 13-27 hours of acoustic data were continuously collected at a stationary station. The acoustic volume scattering strength （Sv） data were analyzed with temperature profile data. In the spring of both 2010 and 2011, the SSL clearly showed the vertical migration throughout the entire water column, moving from the surface layer at night to near the bottom during the day. Conductivity, temperature, and depth data indicated that the entire water column was well mixed with low temperature of about 8℃. However, the SSL showed different patterns in the summers of 2010 and 2011. In the summer of 2010 （≈28℃ at the surface）, the SSL migrated to near the bottom during the day, but there were two SSLs above and below the thermocline at depth of 10-30 m at night. In the summer of 2011 （≈20℃ at the surface）, the SSL extended throughout the entire water column at night, possibly owing to an abrupt change in sea weather conditions caused by the passage of a Typhoon Muifa over the study area. It was cancluded that the DVM patterns in summer in the YSBCW area may be greatly influenced by a strengthened or weakened thermocline.
文摘BACKGROUND The risk of developing prediabetes based on the metabolic/obesity phenotypes has been poorly investigated. AIM To examine the association of baseline metabolic/obesity phenotypes and their changes over time with the risk of prediabetes development. METHODS In a population-based cohort study, 1741 adults (aged > 19 years) with normal blood glucose were followed for 14 years. Anthropometric and biochemical measures were evaluated regularly during the follow-up period. According to body mass index and metabolic health status, participants were categorized into four groups: Metabolically healthy normal weight (MHNW), metabolically healthy obese (MHO), metabolically unhealthy normal weight (MUNW) and metabolically unhealthy obese (MUO). Multivariable Cox regression analysis was used to measure the risk of prediabetes according to the baseline metabolic/obesity phenotype and their changes during the follow-up. RESULTS In the whole population with a mean (95CCI for mean) follow up duration of 12.7 years (12.6-12.9), all three MUNW, MHO, MUO groups were at higher risk for developing prediabetes compared to the MHNW group (P = 0.022). The MUNW group had the highest risk for developing prediabetes (hazard ratio (HR): 3.84, 95%CI: 1.20, 12.27). In stratified analysis by sex, no significant association was found in men, while women in the MUNW group were at the greatest risk for prediabetes (HR: 6.74, 95%CI: 1.53, 29.66). Transforming from each phenotype to MHNW or MHO was not related to the risk of prediabetes development, whereas transforming from each phenotype to MUO was associated with an increased risk of prediabetes (HR > 1;P < 0.05). CONCLUSION Our findings indicate that MHO is not a high risk, unless it transforms into MUO over time. However, people in the MUNW group have the greatest risk for developing prediabetes, and therefore, they should be screened and treated.
基金the National Natural Science Foundation of China(Nos.61632012,61672239 and 61602180)the Natural Science Foundation of Shanghai(No.16ZR1409200)the China Postdoctoral Science Foundation(No.2017M611502)。
文摘With the enormous developmen t of imformation and communicat ion technology,more concerns are focused to achieve secure and reliable smart grids as the social infrastrueture,especially in the explosion era of mobile devices.In this paper,we propose an efficient scheme to satis勿the outdoor electrical demand of mobile customers.Our scheme protects the privacy and integrity of users'electricity consumption data.Technically,we encrypt users'electricity consumption data by a chosen-plai nt ext-at tack(CPA)secure public key encryption(PKE)scheme and aggregate ciphertexts by the aggregator(an untrusted third party).In the scheme,internal and external adversaries cannot obtain the electricity consumption data.Additionally,we require users to provide authentication and commitment of consumption data that can track who modifies the data,which protects the integrity of users1 electricity consumption data.
