Browsing by Author "Wang, Xia"

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    An Uncertainty- and Collusion-Proof Voting Consensus Mechanism in Blockchain
    (IEEE, 2023-10) Wang, Shengling; Qu, Xidi; Hu, Qin; Wang, Xia; Cheng, Xiuzhen; Computer Science, Luddy School of Informatics, Computing, and Engineering
    Though voting-based consensus algorithms in blockchain outperform proof-based ones in energy- and transaction-efficiency, they are prone to incur wrong elections and bribery elections. The former originates from the uncertainties of candidates’ capability and availability, and the latter comes from the egoism of voters and candidates. Hence, in this paper, we propose an uncertainty- and collusion-proof voting consensus mechanism, including the selection pressure-based voting algorithm and the trustworthiness evaluation algorithm. The first algorithm can decrease the side effects of candidates’ uncertainties, lowering wrong elections while trading off the balance between efficiency and fairness in voting miners. The second algorithm adopts an incentive-compatible scoring rule to evaluate the trustworthiness of voting, motivating voters to report true beliefs on candidates by making egoism consistent with altruism so as to avoid bribery elections. A salient feature of our work is theoretically analyzing the proposed voting consensus mechanism by the large deviation theory. Our analysis provides not only the voting failure rate of a candidate but also its decay speed. The voting failure rate measures the incompetence of any candidate from a personal perspective by voting, based on which the concepts of the effective selection valve and the effective expectation of merit are introduced to help the system designer determine the optimal voting standard and guide a candidate to behave in an optimal way for lowering the voting failure rate.
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    Phenotypic expansion in DDX3X - a common cause of intellectual disability in females
    (Wiley, 2018-09-15) Wang, Xia; Posey, Jennifer E.; Rosenfeld, Jill A.; Bacino, Carlos A.; Scaglia, Fernando; Immken, LaDonna; Harris, Jill M.; Hickey, Scott E.; Mosher, Theresa M.; Slavotinek, Anne; Zhang, Jing; Beuten, Joke; Leduc, Magalie S.; He, Weimin; Vetrini, Francesco; Walkiewicz, Magdalena A.; Bi, Weimin; Xiao, Rui; Liu, Pengfei; Shao, Yunru; Gezdirici, Alper; Gulec, Elif Y.; Jiang, Yunyun; Darilek, Sandra A.; Hansen, Adam W.; Khayat, Michael M.; Pehlivan, Davut; Piard, Juliette; Muzny, Donna M.; Hanchard, Neil; Belmont, John W.; Van Maldergem, Lionel; Gibbs, Richard A.; Eldomery, Mohammad K.; Akdemir, Zeynep C.; Adesina, Adekunle M.; Chen, Shan; Lee, Yi-Chien; Lee, Brendan; Lupski, James R.; Eng, Christine M.; Xia, Fan; Yang, Yaping; Graham, Brett H.; Moretti, Paolo; Medical and Molecular Genetics, School of Medicine
    De novo variants in DDX3X account for 1-3% of unexplained intellectual disability (ID) cases and are amongst the most common causes of ID especially in females. Forty-seven patients (44 females, 3 males) have been described. We identified 31 additional individuals carrying 29 unique DDX3X variants, including 30 postnatal individuals with complex clinical presentations of developmental delay or ID, and one fetus with abnormal ultrasound findings. Rare or novel phenotypes observed include respiratory problems, congenital heart disease, skeletal muscle mitochondrial DNA depletion, and late-onset neurologic decline. Our findings expand the spectrum of DNA variants and phenotypes associated with DDX3X disorders.