•We propose a unified adversary model for inference attacks on genomic privacy of unrelated individuals.•We present an inference attack strategy that employs the correlations of SNPs and the sampling ...and recombination model.•We reveal an RCNN–based inference attack and investigate the large-scale capabilities of machine learning for genomic privacy attacking.•We evaluate the inference attack capability and quantify genomic privacy in terms of mutual information.•Our results obtain with much higher accuracy, lower uncertainty on the inferred genomic data, and more loss of privacy than previous work.
In recent years, the collection of large-scale genomic data for individuals has become feasible and affordable. Concurrently, several practical attacks targeting genome re-identification and genotype inference have emerged to threaten the confidentiality of genomic data sharing, leading to security and privacy concerns regarding genomic data. The authors have shown that this problem can be even worse in this paper. Specifically, two possible large-scale genotype inference attack stretegies for nonrelatives have exposed. One is based on an improved hidden Markov model (iHMM), and the other is based on a regressive convolutional neural network (RCNN). By using a genomic privacy metric combining the attacker’s incorrectness, the attacker’s uncertainty, and the genomic privacy loss of the victims, it is shown that with these atrategies, the attack can be significantly more severe than those reported previously. It is also shown that machine learning can be applied to empower large-scale inference attacks against genomic privacy.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
The distributed training of federated machine learning, referred to as federated learning (FL), is discussed in models by multiple participants using local data without compromising data privacy and ...violating laws. In this paper, we consider the training of federated machine models with uncertain participation attitudes and uncertain benefits of each federated participant, and to encourage all participants to train the desired FL models, we design a fuzzy Shapley value incentive mechanism with supervision. In this incentive mechanism, if the supervision of the supervised mechanism detects that the payoffs of a federated participant reach a value that satisfies the Pareto optimality condition, the federated participant receives a distribution of federated payoffs. The results of numerical experiments demonstrate that the mechanism successfully achieves a fair and Pareto optimal distribution of payoffs. The contradiction between fairness and Pareto-efficient optimization is solved by introducing a supervised mechanism.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
Increasing evidence indicates Chronic Periodontitis (CP) is a comorbidity of Alzheimer's disease (AD), which is the most common form of age-related dementia, and for the later, effective diagnostic ...and treatment strategies are lacking. Although inflammation is present in both diseases, the exact mechanisms and cross-links between CP and AD are poorly understood; and a direct association between the two has not been reported. The aim of this study was to identify a direct serum proteins link between AD and CP. Two-dimensional differential in-gel electrophoresis was employed to analyze serum samples from 12 CP patients and 12 age-matched controls. Furthermore, to determine the molecular link between CP and AD, neuroblastoma SK-N-SH APPwt cells were treated with 1 μg/mL of lipopolysaccharide from Porphyromonas gingivalis (P.g-LPS). Ten differentially expressed proteins were identified in CP patients. Among them, nine proteins were up-regulated, and one protein was down-regulated. Of the 10 differentially expressed proteins, five proteins were reportedly involved in the pathology of AD: Cofilin-2, Cathepsin B, Clusterin, Triosephosphate isomerase, and inter-alpha-trypsin inhibitor heavy chain H4 (ITI-H4). Western blotting indicated a significantly higher expression of Cofilin-2, Cathepsin B, and Clusterin and lower expression of ITI-H4 in the CP group than in the control group. The serum concentration of Cathepsin B has a good correlation with MMSE scores. Moreover, the protein level of Cathepsin B (but not that of ADAM10 and BACE1) increased significantly along with a prominent increase inAβ1-40 andAβ1-42in the cell lysates of P.g-LPS-treated SK-N-SH APPwt cells. Cathepsin B inhibition resulted in a sharp decrease in Aβ1-40 and Aβ1-42 in the cell lysates. Furthermore, TNF-α was one of the most important inflammatory cytokines for the P.g-LPS-induced Cathepsin B upregulation in SK-N-SH APPwt cells. These results show that CP and AD share an association, while Cathepsin B could be a key link between the two diseases. The discovery of the identical serum proteins provides a potential mechanism underlying the increased risk of AD in CP patients, which could be critical for elucidating the pathophysiology of AD.
Warfarin is the most recommended oral anticoagulant after artificial mechanical valve replacement therapy. However, the narrow therapeutic window and varying safety and efficacy in individuals make ...dose determination difficult. It may cause adverse events such as hemorrhage or thromboembolism. Therefore, advanced algorithms are urgently required for the use of warfarin.
To establish a warfarin dose model for patients after prosthetic mechanical valve replacement in southern China in combination with clinical and genetic variables, and to improve the accuracy and ideal prediction percentage of the model.
Clinical data of 476 patients were tracked and recorded in detail. The gene polymorphisms of VKORC1 (rs9923231, rs9934438, rs7196161, and rs7294), CYP2C9 (rs1057910), CYP1A2 (rs2069514), GGCX (rs699664), and UGT1A1 (rs887829) were determined using Sanger sequencing. Multiple linear regressions were used to analyze the gene polymorphisms and the contribution of clinical data variables; the variables that caused multicollinearity were screened stepwise and excluded to establish an algorithm model for predicting the daily maintenance dose of warfarin. The ideal predicted percentage was used to test clinical effectiveness.
A total of 395 patients were included. Univariate linear regression analysis suggested that CYP1A2 (rs2069514) and UGT1A1 (rs887829) were not associated with the daily maintenance dose of warfarin. The new algorithm model established based on multiple linear regression was as follows: Y = 1.081 - 0.011 (age) + 1.532 (body surface area)-0.807 (rs9923231 AA) + 1.788 (rs9923231 GG) + 0.530 (rs1057910 AA)-1.061 (rs1057910 AG)-0.321 (rs699664 AA). The model accounted for 61.7% of individualized medication differences, with an ideal prediction percentage of 69%.
GGCX (rs699664) may be a potential predictor of warfarin dose, and our newly established model is expected to guide the individualized use of warfarin in clinical practice in southern China.
A good classroom acoustic environment will contribute to teachers’ health and students’ learning. Comfortable acoustic environment requires suitable reverberation time, sufficient loudness, uniform ...sound field distribution, high language clarity, and no acoustic defects such as echo and acoustic focusing. In this study, the optimization strategy of acoustic environment is proposed through the investigation, field testing and numerical simulation analysis of a middle school classroom in Wenzhou under different ventilation conditions. The results show: the key factors affecting the classroom acoustic environment are outdoor activity noise, corridor noise, and classroom teacher-student activity noise. Through optimization, the quality of classroom acoustic environment is improved significantly. Classroom reverberation time (intermediate frequency) decreased from 1.5s to 0.7s; ALC decreased from 9.65% to 4.75%; STI increased from 0.534 to 0.664. The research results provided reference for acoustic design of secondary school classrooms in the future.
With the wind generation increasingly penetrating the power grids, there is a growing interest in developing new risk-based assessments for the grids security analysis. This study develops one kind ...of such risk tools to evaluate the security risks of power grids under certain amount of wind generation in a short period of time. First of all, a very short-term uncertainty model of wind generation is introduced. Then the conditional value-at-risk is used to design a safety distance (S-D), revealing the tail risks of operating states. Based on S-D, four new indices are defined to highlight the risks in a near future with considerable change of wind power output. The overall security assessment tool is compared with the conventional method both on a benchmark test system and a real power system in China. The results demonstrate the effectiveness and some advantages of this new risk-based tool.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
A repetitive pulsed high magnetic field is a useful tool for scientific research and industrial applications. In this paper, a novel repetitive pulsed power system (RPPS) adopted to generate ...repetitive pulsed high magnetic fields (RPHMF) at the Wuhan National High Magnetic Field Center (WHMFC) is designed. The capacitors serve as the energy storage elements in the pulsed power system, and the key issue of the RPHMF system is to decrease the loss and to charge the capacitors quickly, safely and efficiently. For this purpose, a new discharge topology is used to feed the energy stored in the magnet back to the capacitor by an additional choke coil and a resonant capacitor. The energy lost during each pulse will be replenished to the capacitor through a high frequency series-parallel resonant capacitor charging power supply (CCPS).
More and more security and privacy issues are arising as new technologies, such as big data and cloud computing, are widely applied in nowadays. For decreasing the privacy breaches in access control ...system under opening and cross-domain environment. In this paper, we suggest a game and risk based access model for privacy preserving by employing Shannon information and game theory. After defining the notions of Privacy Risk and Privacy Violation Access, a high-level framework of game theoretical risk based access control is proposed. Further, we present formulas for estimating the risk value of access request and user, construct and analyze the game model of the proposed access control by using a multi-stage two player game. There exists sub-game perfect Nash equilibrium each stage in the risk based access control and it's suitable to protect the privacy by limiting the privacy violation access requests.
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