Simulating Univariate and Multivariate Tukey \u3ci\u3eg\u3c/i\u3e-and-\u3ci\u3eh\u3c/i\u3e Distributions Based on the Method of Percentiles

This paper derives closed-form solutions for the -and-ℎ shape parameters associated with the Tukey family of distributions based on the method of percentiles (MOP). A proposed MOP univariate procedure is described and compared with the method of moments (MOM) in the context of distribution fitting and estimating skew and kurtosis functions. The MOP methodology is also extended from univariate to multivariate data generation. A procedure is described for simulating nonnormal distributions with specified Spearman correlations. TheMOP procedure has an advantage over theMOMbecause it does not require numerical integration to compute intermediate correlations. Simulation results demonstrate that the proposedMOP procedure is superior to the MOM in terms of distribution fitting, estimation, relative bias, and relative error

A Characterization of Power Method Transformations through The Method of Percentiles

This paper derives closed-form solutions for the fifth-ordered power method poly- nomial transformation based on the method of percentiles (MOP). A proposed MOP univariate procedure is described and compared with the method of moments (MOM) in the context of distribution fitting and estimating skew, kurtosis, fifth-and sixth- ordered functions. The MOP methodology is also extended from univariate to multi- variate data generation. The MOP procedure has an advantage over the MOM because it does not require numerical integration to compute intermediate correlations. In addition, the MOP procedure can be applied to distributions where mean and(or) variance do(does) not exist. Simulation results demonstrate that the proposed MOP procedure is superior to the MOM in terms of estimation, relative bias, and relative error

Characterization of the Power Method Transformation through the Method of Percentiles

This paper derives a standard normal based power method polynomial transformation for Monte Carlo simulation studies, approximating distributions, and fitting distributions to data based on the method of percentiles. The proposed method is used primarily when (i) conventional estimators such as skew and kurtosis are unknown or (ii) data are unavailable but percentiles are known (e.g., standardized test score reports). The proposed transformation also has the advantage that solutions to polynomial coefficients are available in simple closed form and thus obviates numerical equation solving. The Monte Carlo results presented in this study indicate that the estimators based on the method of percentiles are substantially superior to their corresponding conventional product-moment estimators in terms of relative bias

DEXON: A Highly Scalable, Decentralized DAG-Based Consensus Algorithm

A blockchain system is a replicated state machine that must be fault tolerant. When designing a blockchain system, there is usually a trade-off between decentralization, scalability, and security. In this paper, we propose a novel blockchain system, DEXON, which achieves high scalability while remaining decentralized and robust in the real-world environment. We have two main contributions. First, we present a highly scalable sharding framework for blockchain. This framework takes an arbitrary number of single chains and transforms them into the \textit{blocklattice} data structure, enabling \textit{high scalability} and \textit{low transaction confirmation latency} with asymptotically optimal communication overhead. Second, we propose a single-chain protocol based on our novel verifiable random function and a new Byzantine agreement that achieves high decentralization and low latency

Healthcare costs and utilization for Medicare beneficiaries with Alzheimer\u27s

BACKGROUND: Alzheimer\u27s disease (AD) is a neurodegenerative disorder incurring significant social and economic costs. This study uses a US administrative claims database to evaluate the effect of AD on direct healthcare costs and utilization, and to identify the most common reasons for AD patients\u27 emergency room (ER) visits and inpatient admissions. METHODS: Demographically matched cohorts age 65 and over with comprehensive medical and pharmacy claims from the 2003-2004 MEDSTAT MarketScan Medicare Supplemental and Coordination of Benefits (COB) Database were examined: 1) 25,109 individuals with an AD diagnosis or a filled prescription for an exclusively AD treatment; and 2) 75,327 matched controls. Illness burden for each person was measured using Diagnostic Cost Groups (DCGs), a comprehensive morbidity assessment system. Cost distributions and reasons for ER visits and inpatient admissions in 2004 were compared for both cohorts. Regression was used to quantify the marginal contribution of AD to health care costs and utilization, and the most common reasons for ER and inpatient admissions, using DCGs to control for overall illness burden. RESULTS: Compared with controls, the AD cohort had more co-morbid medical conditions, higher overall illness burden, and higher but less variable costs ($13,936 s.$10,369; Coefficient of variation = 181 vs. 324). Significant excess utilization was attributed to AD for inpatient services, pharmacy, ER visits, and home health care (all p \u3c 0.05). In particular, AD patients were far more likely to be hospitalized for infections, pneumonia and falls (hip fracture, syncope, collapse). CONCLUSION: Patients with AD have significantly more co-morbid medical conditions and higher healthcare costs and utilization than demographically-matched Medicare beneficiaries. Even after adjusting for differences in co-morbidity, AD patients incur excess ER visits and inpatient admissions

Viral and host proteins involved in picornavirus life cycle

Picornaviruses cause several diseases, not only in humans but also in various animal hosts. For instance, human enteroviruses can cause hand-foot-and-mouth disease, herpangina, myocarditis, acute flaccid paralysis, acute hemorrhagic conjunctivitis, severe neurological complications, including brainstem encephalitis, meningitis and poliomyelitis, and even death. The interaction between the virus and the host is important for viral replication, virulence and pathogenicity. This article reviews studies of the functions of viral and host factors that are involved in the life cycle of picornavirus. The interactions of viral capsid proteins with host cell receptors is discussed first, and the mechanisms by which the viral and host cell factors are involved in viral replication, viral translation and the switch from translation to RNA replication are then addressed. Understanding how cellular proteins interact with viral RNA or viral proteins, as well as the roles of each in viral infection, will provide insights for the design of novel antiviral agents based on these interactions