Benefiting from the development of Federated Learning(FL)and distributed communication systems,large-scale intelligent applications become possible.Distributed devices not only provide adequate training data,but also ...Benefiting from the development of Federated Learning(FL)and distributed communication systems,large-scale intelligent applications become possible.Distributed devices not only provide adequate training data,but also cause privacy leakage and energy consumption.How to optimize the energy consumption in distributed communication systems,while ensuring the privacy of users and model accuracy,has become an urgent challenge.In this paper,we define the FL as a 3-layer architecture including users,agents and server.In order to find a balance among model training accuracy,privacy-preserving effect,and energy consumption,we design the training process of FL as game models.We use an extensive game tree to analyze the key elements that influence the players’decisions in the single game,and then find the incentive mechanism that meet the social norms through the repeated game.The experimental results show that the Nash equilibrium we obtained satisfies the laws of reality,and the proposed incentive mechanism can also promote users to submit high-quality data in FL.Following the multiple rounds of play,the incentive mechanism can help all players find the optimal strategies for energy,privacy,and accuracy of FL in distributed communication systems.展开更多
Tissue regeneration maintains homeostasis and preserves the functional features of each tissue.However,not all tissues show a strong repairing capacity.This is the case of the central nervous system.It is now well est...Tissue regeneration maintains homeostasis and preserves the functional features of each tissue.However,not all tissues show a strong repairing capacity.This is the case of the central nervous system.It is now well established that the generation of new functional neurons from stem cells in the adult brain occurs in specific regions of the brain of different species such as rodents,birds,primates,and humans(Eriksson et al.,1998).展开更多
BACKGROUND Microwave endometrial ablation(MEA)is a minimally invasive treatment method for heavy menstrual bleeding.However,additional treatment is often required after recurrence of uterine myomas treated with MEA.Ad...BACKGROUND Microwave endometrial ablation(MEA)is a minimally invasive treatment method for heavy menstrual bleeding.However,additional treatment is often required after recurrence of uterine myomas treated with MEA.Additionally,because this treatment ablates the endometrium,it is not indicated for patients planning to become pregnant.To overcome these issues,we devised a method for ultrasound-guided microwave ablation of uterine myoma feeder vessels.We report three patients successfully treated for heavy menstrual bleeding,secondary to uterine myoma,using our novel method.CASE SUMMARY All patients had a favorable postoperative course,were discharged within 4 h,and experienced no complications.Further,no postoperative recurrence of heavy menstrual bleeding was noted.Our method also reduced the myoma’s maximum diameter.CONCLUSION This method does not ablate the endometrium,suggesting its potential appli-cation in patients planning to become pregnant.展开更多
Type 1 diabetes(T1D)is a chronic autoimmune condition that destroys insulinproducing beta cells in the pancreas,leading to insulin deficiency and hyperglycemia.The management of T1D primarily focuses on exogenous insu...Type 1 diabetes(T1D)is a chronic autoimmune condition that destroys insulinproducing beta cells in the pancreas,leading to insulin deficiency and hyperglycemia.The management of T1D primarily focuses on exogenous insulin replacement to control blood glucose levels.However,this approach does not address the underlying autoimmune process or prevent the progressive loss of beta cells.Recent research has explored the potential of glucagon-like peptide-1 receptor agonists(GLP-1RAs)as a novel intervention to modify the disease course and delay the onset of T1D.GLP-1RAs are medications initially developed for treating type 2 diabetes.They exert their effects by enhancing glucose-dependent insulin secretion,suppressing glucagon secretion,and slowing gastric emptying.Emerging evidence suggests that GLP-1RAs may also benefit the treatment of newly diagnosed patients with T1D.This article aims to highlight the potential of GLP-1RAs as an intervention to delay the onset of T1D,possibly through their potential immunomodulatory and anti-inflammatory effects and preservation of beta-cells.This article aims to explore the potential of shifting the paradigm of T1D management from reactive insulin replacement to proactive disease modification,which should open new avenues for preventing and treating T1D,improving the quality of life and long-term outcomes for individuals at risk of T1D.展开更多
Suppose R is an idempotence-diagonalizable ring. Let n and m be two arbitrary positive integers with n ≥ 3. We denote by Mn（R） the ring of all n x n matrices over R. Let （Jn（R）） be the additive subgroup of Mn（...Suppose R is an idempotence-diagonalizable ring. Let n and m be two arbitrary positive integers with n ≥ 3. We denote by Mn（R） the ring of all n x n matrices over R. Let （Jn（R）） be the additive subgroup of Mn（R） generated additively by all idempotent matrices. Let JJ = （Jn（R）） or Mn（R）. We describe the additive preservers of idempotence from JJ to Mm（R） when 2 is a unit of R. Thereby, we also characterize the Jordan （respectively, ring and ring anti-） homomorphisms from Mn （R） to Mm （R） when 2 is a unit of R.展开更多
Let B（X） be the algebra of all bounded linear operators on an infinite-dimensional complex or real Banach space X. Given an integer n 〉 1, we show that an additive surjective map Ф on B（X） preserves Drazin inver...Let B（X） be the algebra of all bounded linear operators on an infinite-dimensional complex or real Banach space X. Given an integer n 〉 1, we show that an additive surjective map Ф on B（X） preserves Drazin invertible operators of index non-greater than n in both directions if and only if Ф is either of the form Ф（T） = aATA-1 or of the form Ф（T） = aBT＊B-1 where a is a non-zero scalar, A ： X → X and B ： X＊ → X are two bounded invertible linear or conjugate linear operators.展开更多
In an era characterized by digital pervasiveness and rapidly expanding datasets,ensuring the integrity and reliability of information is paramount.As cyber threats evolve in complexity,traditional cryptographic method...In an era characterized by digital pervasiveness and rapidly expanding datasets,ensuring the integrity and reliability of information is paramount.As cyber threats evolve in complexity,traditional cryptographic methods face increasingly sophisticated challenges.This article initiates an exploration into these challenges,focusing on key exchanges(encompassing their variety and subtleties),scalability,and the time metrics associated with various cryptographic processes.We propose a novel cryptographic approach underpinned by theoretical frameworks and practical engineering.Central to this approach is a thorough analysis of the interplay between Confidentiality and Integrity,foundational pillars of information security.Our method employs a phased strategy,beginning with a detailed examination of traditional cryptographic processes,including Elliptic Curve Diffie-Hellman(ECDH)key exchanges.We also delve into encrypt/decrypt paradigms,signature generation modes,and the hashes used for Message Authentication Codes(MACs).Each process is rigorously evaluated for performance and reliability.To gain a comprehensive understanding,a meticulously designed simulation was conducted,revealing the strengths and potential improvement areas of various techniques.Notably,our cryptographic protocol achieved a confidentiality metric of 9.13 in comprehensive simulation runs,marking a significant advancement over existing methods.Furthermore,with integrity metrics at 9.35,the protocol’s resilience is further affirmed.These metrics,derived from stringent testing,underscore the protocol’s efficacy in enhancing data security.展开更多
Loss of plasma membrane integrity can compromise cell functioning and viability.To countera ct this eminent threat,euka ryotic cells have developed efficient repair mechanisms,which seem to have co-evolved with the em...Loss of plasma membrane integrity can compromise cell functioning and viability.To countera ct this eminent threat,euka ryotic cells have developed efficient repair mechanisms,which seem to have co-evolved with the emergence of vital membrane processes(Cooper and McNeil,2015).This relationship between basic cellular functioning and membrane repair highlights the fundamental significance of preserving membrane integrity for cellular life.展开更多
Microneurovascular units(mNVUs),comprising neurons,micro-glia,and blood-brain barrier(BBB)endothelial cells,are pivotal to the central nervous system and are associated with cerebral hypoxia and brain injuries.Cerebra...Microneurovascular units(mNVUs),comprising neurons,micro-glia,and blood-brain barrier(BBB)endothelial cells,are pivotal to the central nervous system and are associated with cerebral hypoxia and brain injuries.Cerebral hypoxia triggers microglial overactivity,causing inflammation,neuronal injury,and disruption of the BBB[1].Salidroside(Sal),a key compound in Tibetan medicine Rhodiola crenulata,mitigates hypoxia-induced metabolic disorders and neuronal damage by preserving mitochondrial function[2].展开更多
With the growth of requirements for data sharing,a novel business model of digital assets trading has emerged that allows data owners to sell their data for monetary gain.In the distributed ledger of blockchain,howeve...With the growth of requirements for data sharing,a novel business model of digital assets trading has emerged that allows data owners to sell their data for monetary gain.In the distributed ledger of blockchain,however,the privacy of stakeholder's identity and the confidentiality of data content are threatened.Therefore,we proposed a blockchainenabled privacy-preserving and access control scheme to address the above problems.First,the multi-channel mechanism is introduced to provide the privacy protection of distributed ledger inside the channel and achieve coarse-grained access control to digital assets.Then,we use multi-authority attribute-based encryption(MAABE)algorithm to build a fine-grained access control model for data trading in a single channel and describe its instantiation in detail.Security analysis shows that the scheme has IND-CPA secure and can provide privacy protection and collusion resistance.Compared with other schemes,our solution has better performance in privacy protection and access control.The evaluation results demonstrate its effectiveness and practicability.展开更多
Dear Editor,This letter proposes a symmetry-preserving dual-stream graph neural network(SDGNN) for precise representation learning to an undirected weighted graph(UWG). Although existing graph neural networks(GNNs) ar...Dear Editor,This letter proposes a symmetry-preserving dual-stream graph neural network(SDGNN) for precise representation learning to an undirected weighted graph(UWG). Although existing graph neural networks(GNNs) are influential instruments for representation learning to a UWG, they invariably adopt a unique node feature matrix for illustrating the sole node set of a UWG.展开更多
The increasing data pool in finance sectors forces machine learning(ML)to step into new complications.Banking data has significant financial implications and is confidential.Combining users data from several organizat...The increasing data pool in finance sectors forces machine learning(ML)to step into new complications.Banking data has significant financial implications and is confidential.Combining users data from several organizations for various banking services may result in various intrusions and privacy leakages.As a result,this study employs federated learning(FL)using a flower paradigm to preserve each organization’s privacy while collaborating to build a robust shared global model.However,diverse data distributions in the collaborative training process might result in inadequate model learning and a lack of privacy.To address this issue,the present paper proposes the imple-mentation of Federated Averaging(FedAvg)and Federated Proximal(FedProx)methods in the flower framework,which take advantage of the data locality while training and guaranteeing global convergence.Resultantly improves the privacy of the local models.This analysis used the credit card and Canadian Institute for Cybersecurity Intrusion Detection Evaluation(CICIDS)datasets.Precision,recall,and accuracy as performance indicators to show the efficacy of the proposed strategy using FedAvg and FedProx.The experimental findings suggest that the proposed approach helps to safely use banking data from diverse sources to enhance customer banking services by obtaining accuracy of 99.55%and 83.72%for FedAvg and 99.57%,and 84.63%for FedProx.展开更多
This paper studies the privacy-preserving distributed economic dispatch(DED)problem of smart grids.An autonomous consensus-based algorithm is developed via local data exchange with neighboring nodes,which covers both ...This paper studies the privacy-preserving distributed economic dispatch(DED)problem of smart grids.An autonomous consensus-based algorithm is developed via local data exchange with neighboring nodes,which covers both the islanded mode and the grid-connected mode of smart grids.To prevent power-sensitive information from being disclosed,a privacy-preserving mechanism is integrated into the proposed DED algorithm by randomly decomposing the state into two parts,where only partial data is transmitted.Our objective is to develop a privacy-preserving DED algorithm to achieve optimal power dispatch with the lowest generation cost under physical constraints while preventing sensitive information from being eavesdropped.To this end,a comprehensive analysis framework is established to ensure that the proposed algorithm can converge to the optimal solution of the concerned optimization problem by means of the consensus theory and the eigenvalue perturbation approach.In particular,the proposed autonomous algorithm can achieve a smooth transition between the islanded mode and the grid-connected mode.Furthermore,rigorous analysis is given to show privacy-preserving performance against internal and external eavesdroppers.Finally,case studies illustrate the feasibility and validity of the developed algorithm.展开更多
Dear Editor,This letter presents a novel process monitoring model based on ensemble structure analysis(ESA).The ESA model takes advantage of principal component analysis(PCA),locality preserving projections(LPP),and m...Dear Editor,This letter presents a novel process monitoring model based on ensemble structure analysis(ESA).The ESA model takes advantage of principal component analysis(PCA),locality preserving projections(LPP),and multi-manifold projections(MMP)models,and then combines the multiple solutions within an ensemble result through Bayesian inference.In the developed ESA model,different structure features of the given dataset are taken into account simultaneously,the suitability and reliability of the ESA-based monitoring model are then illustrated through comparison.Introduction:The requirement for ensuring safe operation and improving process efficiency has led to increased research activity in the field of process monitoring.展开更多
The umbrella term"neurodege ne rative disorders"(NDDs) refers to several conditions characterized by a progressive loss of structure and function of cells belonging to the nervous system.Such diseases affect...The umbrella term"neurodege ne rative disorders"(NDDs) refers to several conditions characterized by a progressive loss of structure and function of cells belonging to the nervous system.Such diseases affect more than 50million people worldwide.Neurodegenerative disorders are characterized by sundry factors and pathophysiological mechanisms that a re challenging to be fully profiled.Many of these rely on cell signaling pathways to preserve homeostasis,involving second messengers such as cyclic adenosine monophosphate (cAMP)and cyclic guanosine 3',5'-monophosphate(cGMP).Their ability to control the duration and amplitude of the signaling cascade is given by the presence of several common and uncommon effectors.Protein kinases A and G (PKA and PKG),phosphodiesterases (PDEs),and scaffold proteins are among them.展开更多
Feature matching plays a key role in computer vision. However, due to the limitations of the descriptors, the putative matches are inevitably contaminated by massive outliers.This paper attempts to tackle the outlier ...Feature matching plays a key role in computer vision. However, due to the limitations of the descriptors, the putative matches are inevitably contaminated by massive outliers.This paper attempts to tackle the outlier filtering problem from two aspects. First, a robust and efficient graph interaction model,is proposed, with the assumption that matches are correlated with each other rather than independently distributed. To this end, we construct a graph based on the local relationships of matches and formulate the outlier filtering task as a binary labeling energy minimization problem, where the pairwise term encodes the interaction between matches. We further show that this formulation can be solved globally by graph cut algorithm. Our new formulation always improves the performance of previous localitybased method without noticeable deterioration in processing time,adding a few milliseconds. Second, to construct a better graph structure, a robust and geometrically meaningful topology-aware relationship is developed to capture the topology relationship between matches. The two components in sum lead to topology interaction matching(TIM), an effective and efficient method for outlier filtering. Extensive experiments on several large and diverse datasets for multiple vision tasks including general feature matching, as well as relative pose estimation, homography and fundamental matrix estimation, loop-closure detection, and multi-modal image matching, demonstrate that our TIM is more competitive than current state-of-the-art methods, in terms of generality, efficiency, and effectiveness. The source code is publicly available at http://github.com/YifanLu2000/TIM.展开更多
Xiazhuang uranium ore field,located in the southern part of the Nanling Metallogenic Belt,is considered one of the largest granite-related U regions in South China.In this paper,we contribute new apatite fission track...Xiazhuang uranium ore field,located in the southern part of the Nanling Metallogenic Belt,is considered one of the largest granite-related U regions in South China.In this paper,we contribute new apatite fission track data and thermal history modeling to constrain the exhumation history and evaluate preservation potential of the Xiazhuang Uranium ore field.Nine Triassic outcrop granite samples collected from different locations of Xiazhuang Uranium ore field yield AFT ages ranging from 43 to 24 Ma with similar mean confined fission track lengths ranging from 11.8±2.0 to 12.9±1.9μm and Dpar values between 1.01 and 1.51μm.The robustness time-temperature reconstructions of samples from the hanging wall of Huangpi fault show that the Xiazhuang Uranium ore field experienced a time of monotonous and slow cooling starting from middle Paleocene to middle Miocene(~60-10 Ma),followed by relatively rapid exhumation in the late Miocene(~10-5 Ma)and nearly thermal stability in the Pliocene-Quaternary(~5-0 Ma).The amount of exhumation after U mineralization since the Middle Paleogene was estimated as~4.3±1.8 km according to the integrated thermal history model.Previous studies indicate that the ore-forming ages of U deposits in the Xiazhuang ore field are mainly before Middle Paleocene and the mineralization depths are more than 4.4±1.2 km.Therefore,the exhumation history since middle Paleocene plays important roles in the preservation of the Xiazhuang Uranium ore field.展开更多
Tectonism is one of the dominant factors affecting the shale pore structure.However,the control of shale pore structure by tectonic movements is still controversial,which limits the research progress of shale gas accu...Tectonism is one of the dominant factors affecting the shale pore structure.However,the control of shale pore structure by tectonic movements is still controversial,which limits the research progress of shale gas accumulation mechanism in the complex tectonic region of southern China.In this study,34 samples were collected from two exploratory wells located in different tectonic locations.Diverse experiments,e.g.,organic geochemistry,XRD analysis,FE-SEM,low-pressure gas adsorption,and high-pressure mercury intrusion,were conducted to fully characterize the shale reservoir.The TOC,Ro,and mineral composition of the shale samples between the two wells are similar,which reflects that the shale samples of the two wells have proximate pores-generating capacity and pores-supporting capacity.However,the pore characteristics of shale samples from two wells are significantly different.Compared with the stabilized zone shale,the porosity,pore volume,and specific surface area of the deformed zone shale were reduced by 60.61%,64.85%,and 27.81%,respectively.Moreover,the macroscopic and fine pores were reduced by 54.01%and 84.95%,respectively.Fault activity and uplift denudation are not conducive to pore preservation,and the rigid basement of Huangling uplift can promote pore preservation.These three factors are important reasons for controlling the difference in pore structure between two wells shales.We established a conceptual model of shale pores evolution under different tectonic preservation conditions.This study is significant to clarify the scale of shale gas formation and enrichment in complex tectonic regions,and helps in the selection of shale sweet spots.展开更多
With the prevalence of the Internet of Things(IoT)systems,smart cities comprise complex networks,including sensors,actuators,appliances,and cyber services.The complexity and heterogeneity of smart cities have become v...With the prevalence of the Internet of Things(IoT)systems,smart cities comprise complex networks,including sensors,actuators,appliances,and cyber services.The complexity and heterogeneity of smart cities have become vulnerable to sophisticated cyber-attacks,especially privacy-related attacks such as inference and data poisoning ones.Federated Learning(FL)has been regarded as a hopeful method to enable distributed learning with privacypreserved intelligence in IoT applications.Even though the significance of developing privacy-preserving FL has drawn as a great research interest,the current research only concentrates on FL with independent identically distributed(i.i.d)data and few studies have addressed the non-i.i.d setting.FL is known to be vulnerable to Generative Adversarial Network(GAN)attacks,where an adversary can presume to act as a contributor participating in the training process to acquire the private data of other contributors.This paper proposes an innovative Privacy Protection-based Federated Deep Learning(PP-FDL)framework,which accomplishes data protection against privacy-related GAN attacks,along with high classification rates from non-i.i.d data.PP-FDL is designed to enable fog nodes to cooperate to train the FDL model in a way that ensures contributors have no access to the data of each other,where class probabilities are protected utilizing a private identifier generated for each class.The PP-FDL framework is evaluated for image classification using simple convolutional networks which are trained using MNIST and CIFAR-10 datasets.The empirical results have revealed that PF-DFL can achieve data protection and the framework outperforms the other three state-of-the-art models with 3%–8%as accuracy improvements.展开更多
With the recent technological developments,massive vehicular ad hoc networks(VANETs)have been established,enabling numerous vehicles and their respective Road Side Unit(RSU)components to communicate with oneanother.Th...With the recent technological developments,massive vehicular ad hoc networks(VANETs)have been established,enabling numerous vehicles and their respective Road Side Unit(RSU)components to communicate with oneanother.The best way to enhance traffic flow for vehicles and traffic management departments is to share thedata they receive.There needs to be more protection for the VANET systems.An effective and safe methodof outsourcing is suggested,which reduces computation costs by achieving data security using a homomorphicmapping based on the conjugate operation of matrices.This research proposes a VANET-based data outsourcingsystem to fix the issues.To keep data outsourcing secure,the suggested model takes cryptography models intoaccount.Fog will keep the generated keys for the purpose of vehicle authentication.For controlling and overseeingthe outsourced data while preserving privacy,the suggested approach considers the Trusted Certified Auditor(TCA).Using the secret key,TCA can identify the genuine identity of VANETs when harmful messages aredetected.The proposed model develops a TCA-based unique static vehicle labeling system using cryptography(TCA-USVLC)for secure data outsourcing and privacy preservation in VANETs.The proposed model calculatesthe trust of vehicles in 16 ms for an average of 180 vehicles and achieves 98.6%accuracy for data encryption toprovide security.The proposedmodel achieved 98.5%accuracy in data outsourcing and 98.6%accuracy in privacypreservation in fog-enabled VANETs.Elliptical curve cryptography models can be applied in the future for betterencryption and decryption rates with lightweight cryptography operations.展开更多
基金sponsored by the National Key R&D Program of China(No.2018YFB2100400)the National Natural Science Foundation of China(No.62002077,61872100)+4 种基金the Major Research Plan of the National Natural Science Foundation of China(92167203)the Guangdong Basic and Applied Basic Research Foundation(No.2020A1515110385)the China Postdoctoral Science Foundation(No.2022M710860)the Zhejiang Lab(No.2020NF0AB01)Guangzhou Science and Technology Plan Project(202102010440).
文摘Benefiting from the development of Federated Learning(FL)and distributed communication systems,large-scale intelligent applications become possible.Distributed devices not only provide adequate training data,but also cause privacy leakage and energy consumption.How to optimize the energy consumption in distributed communication systems,while ensuring the privacy of users and model accuracy,has become an urgent challenge.In this paper,we define the FL as a 3-layer architecture including users,agents and server.In order to find a balance among model training accuracy,privacy-preserving effect,and energy consumption,we design the training process of FL as game models.We use an extensive game tree to analyze the key elements that influence the players’decisions in the single game,and then find the incentive mechanism that meet the social norms through the repeated game.The experimental results show that the Nash equilibrium we obtained satisfies the laws of reality,and the proposed incentive mechanism can also promote users to submit high-quality data in FL.Following the multiple rounds of play,the incentive mechanism can help all players find the optimal strategies for energy,privacy,and accuracy of FL in distributed communication systems.
基金supported by the Spanish Ministerio de Ciencio,Innovoción y Universidades(grant number RTI-2018-099908-B-C21 and RTI-2018-099908-B-C22 granted to CC)by the Consejería de Economia,Conocimiento,Empresas y Universidades(grant number FEDERUCA18-106647 granted to CC)by the Consejería de Salud y Familias 80%co-financed by EDRFITI regional funds(ITI-Cadiz-0042-2019 to CC)。
文摘Tissue regeneration maintains homeostasis and preserves the functional features of each tissue.However,not all tissues show a strong repairing capacity.This is the case of the central nervous system.It is now well established that the generation of new functional neurons from stem cells in the adult brain occurs in specific regions of the brain of different species such as rodents,birds,primates,and humans(Eriksson et al.,1998).
文摘BACKGROUND Microwave endometrial ablation(MEA)is a minimally invasive treatment method for heavy menstrual bleeding.However,additional treatment is often required after recurrence of uterine myomas treated with MEA.Additionally,because this treatment ablates the endometrium,it is not indicated for patients planning to become pregnant.To overcome these issues,we devised a method for ultrasound-guided microwave ablation of uterine myoma feeder vessels.We report three patients successfully treated for heavy menstrual bleeding,secondary to uterine myoma,using our novel method.CASE SUMMARY All patients had a favorable postoperative course,were discharged within 4 h,and experienced no complications.Further,no postoperative recurrence of heavy menstrual bleeding was noted.Our method also reduced the myoma’s maximum diameter.CONCLUSION This method does not ablate the endometrium,suggesting its potential appli-cation in patients planning to become pregnant.
文摘Type 1 diabetes(T1D)is a chronic autoimmune condition that destroys insulinproducing beta cells in the pancreas,leading to insulin deficiency and hyperglycemia.The management of T1D primarily focuses on exogenous insulin replacement to control blood glucose levels.However,this approach does not address the underlying autoimmune process or prevent the progressive loss of beta cells.Recent research has explored the potential of glucagon-like peptide-1 receptor agonists(GLP-1RAs)as a novel intervention to modify the disease course and delay the onset of T1D.GLP-1RAs are medications initially developed for treating type 2 diabetes.They exert their effects by enhancing glucose-dependent insulin secretion,suppressing glucagon secretion,and slowing gastric emptying.Emerging evidence suggests that GLP-1RAs may also benefit the treatment of newly diagnosed patients with T1D.This article aims to highlight the potential of GLP-1RAs as an intervention to delay the onset of T1D,possibly through their potential immunomodulatory and anti-inflammatory effects and preservation of beta-cells.This article aims to explore the potential of shifting the paradigm of T1D management from reactive insulin replacement to proactive disease modification,which should open new avenues for preventing and treating T1D,improving the quality of life and long-term outcomes for individuals at risk of T1D.
基金This work is supported in part by the Chinese Natural Science Foundation under Grant No. 10671026 and the Postdoctoral Fund of Heilongjiang Province
文摘Suppose R is an idempotence-diagonalizable ring. Let n and m be two arbitrary positive integers with n ≥ 3. We denote by Mn（R） the ring of all n x n matrices over R. Let （Jn（R）） be the additive subgroup of Mn（R） generated additively by all idempotent matrices. Let JJ = （Jn（R）） or Mn（R）. We describe the additive preservers of idempotence from JJ to Mm（R） when 2 is a unit of R. Thereby, we also characterize the Jordan （respectively, ring and ring anti-） homomorphisms from Mn （R） to Mm （R） when 2 is a unit of R.
文摘Let B（X） be the algebra of all bounded linear operators on an infinite-dimensional complex or real Banach space X. Given an integer n 〉 1, we show that an additive surjective map Ф on B（X） preserves Drazin invertible operators of index non-greater than n in both directions if and only if Ф is either of the form Ф（T） = aATA-1 or of the form Ф（T） = aBT＊B-1 where a is a non-zero scalar, A ： X → X and B ： X＊ → X are two bounded invertible linear or conjugate linear operators.
文摘In an era characterized by digital pervasiveness and rapidly expanding datasets,ensuring the integrity and reliability of information is paramount.As cyber threats evolve in complexity,traditional cryptographic methods face increasingly sophisticated challenges.This article initiates an exploration into these challenges,focusing on key exchanges(encompassing their variety and subtleties),scalability,and the time metrics associated with various cryptographic processes.We propose a novel cryptographic approach underpinned by theoretical frameworks and practical engineering.Central to this approach is a thorough analysis of the interplay between Confidentiality and Integrity,foundational pillars of information security.Our method employs a phased strategy,beginning with a detailed examination of traditional cryptographic processes,including Elliptic Curve Diffie-Hellman(ECDH)key exchanges.We also delve into encrypt/decrypt paradigms,signature generation modes,and the hashes used for Message Authentication Codes(MACs).Each process is rigorously evaluated for performance and reliability.To gain a comprehensive understanding,a meticulously designed simulation was conducted,revealing the strengths and potential improvement areas of various techniques.Notably,our cryptographic protocol achieved a confidentiality metric of 9.13 in comprehensive simulation runs,marking a significant advancement over existing methods.Furthermore,with integrity metrics at 9.35,the protocol’s resilience is further affirmed.These metrics,derived from stringent testing,underscore the protocol’s efficacy in enhancing data security.
基金supported by the Novo Nordisk Foundation(NNF180C0034936)the Lundbeck Foundation(R380-2021-1262)(to CD and JN)。
文摘Loss of plasma membrane integrity can compromise cell functioning and viability.To countera ct this eminent threat,euka ryotic cells have developed efficient repair mechanisms,which seem to have co-evolved with the emergence of vital membrane processes(Cooper and McNeil,2015).This relationship between basic cellular functioning and membrane repair highlights the fundamental significance of preserving membrane integrity for cellular life.
基金supported by the National Natural Science Foundation of China(Grant Nos.:82274207,81973569,22034005)the Xinglin Scholar Research Promotion Project of Chengdu University of Traditional Chinese Medicine,China(Grant No.:XKTD2022013)the Sichuan Provincial Natural Science Foundation,China(Grant No.:24NSFSC1748).
文摘Microneurovascular units(mNVUs),comprising neurons,micro-glia,and blood-brain barrier(BBB)endothelial cells,are pivotal to the central nervous system and are associated with cerebral hypoxia and brain injuries.Cerebral hypoxia triggers microglial overactivity,causing inflammation,neuronal injury,and disruption of the BBB[1].Salidroside(Sal),a key compound in Tibetan medicine Rhodiola crenulata,mitigates hypoxia-induced metabolic disorders and neuronal damage by preserving mitochondrial function[2].
基金supported by National Key Research and Development Plan in China(Grant No.2020YFB1005500)Beijing Natural Science Foundation(Grant No.M21034)BUPT Excellent Ph.D Students Foundation(Grant No.CX2023218)。
文摘With the growth of requirements for data sharing,a novel business model of digital assets trading has emerged that allows data owners to sell their data for monetary gain.In the distributed ledger of blockchain,however,the privacy of stakeholder's identity and the confidentiality of data content are threatened.Therefore,we proposed a blockchainenabled privacy-preserving and access control scheme to address the above problems.First,the multi-channel mechanism is introduced to provide the privacy protection of distributed ledger inside the channel and achieve coarse-grained access control to digital assets.Then,we use multi-authority attribute-based encryption(MAABE)algorithm to build a fine-grained access control model for data trading in a single channel and describe its instantiation in detail.Security analysis shows that the scheme has IND-CPA secure and can provide privacy protection and collusion resistance.Compared with other schemes,our solution has better performance in privacy protection and access control.The evaluation results demonstrate its effectiveness and practicability.
基金supported in part by the National Natural Science Foundation of China (62372385,62002337)the Chongqing Natural Science Foundation (CSTB2022NSCQMSX1486,CSTB2023NSCQ-LZX0069)。
文摘Dear Editor,This letter proposes a symmetry-preserving dual-stream graph neural network(SDGNN) for precise representation learning to an undirected weighted graph(UWG). Although existing graph neural networks(GNNs) are influential instruments for representation learning to a UWG, they invariably adopt a unique node feature matrix for illustrating the sole node set of a UWG.
文摘The increasing data pool in finance sectors forces machine learning(ML)to step into new complications.Banking data has significant financial implications and is confidential.Combining users data from several organizations for various banking services may result in various intrusions and privacy leakages.As a result,this study employs federated learning(FL)using a flower paradigm to preserve each organization’s privacy while collaborating to build a robust shared global model.However,diverse data distributions in the collaborative training process might result in inadequate model learning and a lack of privacy.To address this issue,the present paper proposes the imple-mentation of Federated Averaging(FedAvg)and Federated Proximal(FedProx)methods in the flower framework,which take advantage of the data locality while training and guaranteeing global convergence.Resultantly improves the privacy of the local models.This analysis used the credit card and Canadian Institute for Cybersecurity Intrusion Detection Evaluation(CICIDS)datasets.Precision,recall,and accuracy as performance indicators to show the efficacy of the proposed strategy using FedAvg and FedProx.The experimental findings suggest that the proposed approach helps to safely use banking data from diverse sources to enhance customer banking services by obtaining accuracy of 99.55%and 83.72%for FedAvg and 99.57%,and 84.63%for FedProx.
基金supported in part by Shenzhen Key Laboratory of Control Theory and Intelligent Systems(ZDSYS20220330161800001)the National Natural Science Foundation of China(62303210,62173255,62188101)+1 种基金the Guangdong Basic and Applied Basic Research Foundation of China(2022A1515110459)the Shenzhen Science and Technology Program of China(RCBS20221008093348109)。
文摘This paper studies the privacy-preserving distributed economic dispatch(DED)problem of smart grids.An autonomous consensus-based algorithm is developed via local data exchange with neighboring nodes,which covers both the islanded mode and the grid-connected mode of smart grids.To prevent power-sensitive information from being disclosed,a privacy-preserving mechanism is integrated into the proposed DED algorithm by randomly decomposing the state into two parts,where only partial data is transmitted.Our objective is to develop a privacy-preserving DED algorithm to achieve optimal power dispatch with the lowest generation cost under physical constraints while preventing sensitive information from being eavesdropped.To this end,a comprehensive analysis framework is established to ensure that the proposed algorithm can converge to the optimal solution of the concerned optimization problem by means of the consensus theory and the eigenvalue perturbation approach.In particular,the proposed autonomous algorithm can achieve a smooth transition between the islanded mode and the grid-connected mode.Furthermore,rigorous analysis is given to show privacy-preserving performance against internal and external eavesdroppers.Finally,case studies illustrate the feasibility and validity of the developed algorithm.
基金supported by the National Natural Science Foundation of China(61503204)the Natural Science Foundation of Zhejiang Province(Y16F030001)the Nature Science Foundation of Ningbo City(2016A610092).
文摘Dear Editor,This letter presents a novel process monitoring model based on ensemble structure analysis(ESA).The ESA model takes advantage of principal component analysis(PCA),locality preserving projections(LPP),and multi-manifold projections(MMP)models,and then combines the multiple solutions within an ensemble result through Bayesian inference.In the developed ESA model,different structure features of the given dataset are taken into account simultaneously,the suitability and reliability of the ESA-based monitoring model are then illustrated through comparison.Introduction:The requirement for ensuring safe operation and improving process efficiency has led to increased research activity in the field of process monitoring.
文摘The umbrella term"neurodege ne rative disorders"(NDDs) refers to several conditions characterized by a progressive loss of structure and function of cells belonging to the nervous system.Such diseases affect more than 50million people worldwide.Neurodegenerative disorders are characterized by sundry factors and pathophysiological mechanisms that a re challenging to be fully profiled.Many of these rely on cell signaling pathways to preserve homeostasis,involving second messengers such as cyclic adenosine monophosphate (cAMP)and cyclic guanosine 3',5'-monophosphate(cGMP).Their ability to control the duration and amplitude of the signaling cascade is given by the presence of several common and uncommon effectors.Protein kinases A and G (PKA and PKG),phosphodiesterases (PDEs),and scaffold proteins are among them.
基金supported by the National Natural Science Foundation of China (62276192)。
文摘Feature matching plays a key role in computer vision. However, due to the limitations of the descriptors, the putative matches are inevitably contaminated by massive outliers.This paper attempts to tackle the outlier filtering problem from two aspects. First, a robust and efficient graph interaction model,is proposed, with the assumption that matches are correlated with each other rather than independently distributed. To this end, we construct a graph based on the local relationships of matches and formulate the outlier filtering task as a binary labeling energy minimization problem, where the pairwise term encodes the interaction between matches. We further show that this formulation can be solved globally by graph cut algorithm. Our new formulation always improves the performance of previous localitybased method without noticeable deterioration in processing time,adding a few milliseconds. Second, to construct a better graph structure, a robust and geometrically meaningful topology-aware relationship is developed to capture the topology relationship between matches. The two components in sum lead to topology interaction matching(TIM), an effective and efficient method for outlier filtering. Extensive experiments on several large and diverse datasets for multiple vision tasks including general feature matching, as well as relative pose estimation, homography and fundamental matrix estimation, loop-closure detection, and multi-modal image matching, demonstrate that our TIM is more competitive than current state-of-the-art methods, in terms of generality, efficiency, and effectiveness. The source code is publicly available at http://github.com/YifanLu2000/TIM.
基金the Foundation of State Key Laboratory of Nuclear Resources and Environment(Grant Nos.NRE2021-01,2022NRE34)the National Natural Science Foundation of China(Grant No.42162013)+1 种基金the Third Xinjiang Scientific Expedition Program(Grant No.2022xjkk1301)the Fund of National Key Laboratory of Science and Technology on Remote Sensing Information and imagery Analysis,Beijing Research Institute of Uranium Geology(Grant No.6142A01210405).
文摘Xiazhuang uranium ore field,located in the southern part of the Nanling Metallogenic Belt,is considered one of the largest granite-related U regions in South China.In this paper,we contribute new apatite fission track data and thermal history modeling to constrain the exhumation history and evaluate preservation potential of the Xiazhuang Uranium ore field.Nine Triassic outcrop granite samples collected from different locations of Xiazhuang Uranium ore field yield AFT ages ranging from 43 to 24 Ma with similar mean confined fission track lengths ranging from 11.8±2.0 to 12.9±1.9μm and Dpar values between 1.01 and 1.51μm.The robustness time-temperature reconstructions of samples from the hanging wall of Huangpi fault show that the Xiazhuang Uranium ore field experienced a time of monotonous and slow cooling starting from middle Paleocene to middle Miocene(~60-10 Ma),followed by relatively rapid exhumation in the late Miocene(~10-5 Ma)and nearly thermal stability in the Pliocene-Quaternary(~5-0 Ma).The amount of exhumation after U mineralization since the Middle Paleogene was estimated as~4.3±1.8 km according to the integrated thermal history model.Previous studies indicate that the ore-forming ages of U deposits in the Xiazhuang ore field are mainly before Middle Paleocene and the mineralization depths are more than 4.4±1.2 km.Therefore,the exhumation history since middle Paleocene plays important roles in the preservation of the Xiazhuang Uranium ore field.
基金supported by the National Natural Science Foundation of China (42122017,41821002)the Hubei Provincial Natural Science Foundation of China (2020CFB501)+1 种基金the Shandong Provincial Key Research and Development Program (2020ZLYS08)the Independent innovation research program of China University of Petroleum (East China) (21CX06001A)。
文摘Tectonism is one of the dominant factors affecting the shale pore structure.However,the control of shale pore structure by tectonic movements is still controversial,which limits the research progress of shale gas accumulation mechanism in the complex tectonic region of southern China.In this study,34 samples were collected from two exploratory wells located in different tectonic locations.Diverse experiments,e.g.,organic geochemistry,XRD analysis,FE-SEM,low-pressure gas adsorption,and high-pressure mercury intrusion,were conducted to fully characterize the shale reservoir.The TOC,Ro,and mineral composition of the shale samples between the two wells are similar,which reflects that the shale samples of the two wells have proximate pores-generating capacity and pores-supporting capacity.However,the pore characteristics of shale samples from two wells are significantly different.Compared with the stabilized zone shale,the porosity,pore volume,and specific surface area of the deformed zone shale were reduced by 60.61%,64.85%,and 27.81%,respectively.Moreover,the macroscopic and fine pores were reduced by 54.01%and 84.95%,respectively.Fault activity and uplift denudation are not conducive to pore preservation,and the rigid basement of Huangling uplift can promote pore preservation.These three factors are important reasons for controlling the difference in pore structure between two wells shales.We established a conceptual model of shale pores evolution under different tectonic preservation conditions.This study is significant to clarify the scale of shale gas formation and enrichment in complex tectonic regions,and helps in the selection of shale sweet spots.
文摘With the prevalence of the Internet of Things(IoT)systems,smart cities comprise complex networks,including sensors,actuators,appliances,and cyber services.The complexity and heterogeneity of smart cities have become vulnerable to sophisticated cyber-attacks,especially privacy-related attacks such as inference and data poisoning ones.Federated Learning(FL)has been regarded as a hopeful method to enable distributed learning with privacypreserved intelligence in IoT applications.Even though the significance of developing privacy-preserving FL has drawn as a great research interest,the current research only concentrates on FL with independent identically distributed(i.i.d)data and few studies have addressed the non-i.i.d setting.FL is known to be vulnerable to Generative Adversarial Network(GAN)attacks,where an adversary can presume to act as a contributor participating in the training process to acquire the private data of other contributors.This paper proposes an innovative Privacy Protection-based Federated Deep Learning(PP-FDL)framework,which accomplishes data protection against privacy-related GAN attacks,along with high classification rates from non-i.i.d data.PP-FDL is designed to enable fog nodes to cooperate to train the FDL model in a way that ensures contributors have no access to the data of each other,where class probabilities are protected utilizing a private identifier generated for each class.The PP-FDL framework is evaluated for image classification using simple convolutional networks which are trained using MNIST and CIFAR-10 datasets.The empirical results have revealed that PF-DFL can achieve data protection and the framework outperforms the other three state-of-the-art models with 3%–8%as accuracy improvements.
文摘With the recent technological developments,massive vehicular ad hoc networks(VANETs)have been established,enabling numerous vehicles and their respective Road Side Unit(RSU)components to communicate with oneanother.The best way to enhance traffic flow for vehicles and traffic management departments is to share thedata they receive.There needs to be more protection for the VANET systems.An effective and safe methodof outsourcing is suggested,which reduces computation costs by achieving data security using a homomorphicmapping based on the conjugate operation of matrices.This research proposes a VANET-based data outsourcingsystem to fix the issues.To keep data outsourcing secure,the suggested model takes cryptography models intoaccount.Fog will keep the generated keys for the purpose of vehicle authentication.For controlling and overseeingthe outsourced data while preserving privacy,the suggested approach considers the Trusted Certified Auditor(TCA).Using the secret key,TCA can identify the genuine identity of VANETs when harmful messages aredetected.The proposed model develops a TCA-based unique static vehicle labeling system using cryptography(TCA-USVLC)for secure data outsourcing and privacy preservation in VANETs.The proposed model calculatesthe trust of vehicles in 16 ms for an average of 180 vehicles and achieves 98.6%accuracy for data encryption toprovide security.The proposedmodel achieved 98.5%accuracy in data outsourcing and 98.6%accuracy in privacypreservation in fog-enabled VANETs.Elliptical curve cryptography models can be applied in the future for betterencryption and decryption rates with lightweight cryptography operations.
