A powerful parent-of-origin effects test for qualitative traits incorporating unaffected children in nuclear familes

InvitedGenomic imprinting is an important epigenetic phenomenon in studying complex traits and has generally been examined by detecting parent-of-origin effects of alleles. The parental-asymmetry test based on nuclear families with both parents and its extensions to deal with missing parental genotypes are simple and powerful for such a task. However, these methods only use case (affected) children in nuclear families and thus do not make full use of information on control (unaffected) children, if available, in these families. In this talk, we propose a novel parent-of-origin effects test C-PATu by using both the control and case children in nuclear families with one or both parents. C-PATu is essentially constructed under a weighted framework, in which the test based on all the unaffected children …postprin

The Development of a smart metering scheme

Paper no. O-036Collaboration is a term to characterize contemporary relationship between a supplier and a consumer. In the old days, an energy meter is the interface service-counter that prompts the double-coincidence of wants between the parties. Nowadays a meter can have smartness beyond registration of consumption units by the supplier. It can carry intelligence to serve demand side management. When the electrical-load-signature technology has been efficiently developed, then a user has to accept that the barrier to load monitoring and surveillance by other parties is no longer a technical issue, but primarily an ethical issue only. On the other hand, it is anticipated that experience curves shall drag down the cost of intelligent home management system to an extent that most of the homes can equip one system to enhance installation operation efficiency and human comfort. It is perceived that when a platform can be developed to permit the intelligence of two sides to share information, then each of them may support the other as a neighboring aide. This paper discusses on philosophies and models that shall develop the concepts.postprintThe International Conference on Electrical Engineering (ICEE) 2008, Okinawa, Japan, 6-10 July 2008

Variable selection in robust joint mean and covariance model for longitudinal data analysis

In longitudinal data analysis, a correct specification of the within-subject covariance matrix cultivates an efficient estimation for mean regression coefficients. In this article, we consider robust variable selection method in a joint mean and covariance model. We propose a set of penalized robust generalized estimating equations to simultaneously estimate the mean regression coefficients, the generalized autoregressive coefficients, and innovation variances introduced by the modified Cholesky decomposition. The set of estimating equations select important covariate variables in both mean and covariance models together with the estimating procedure. Under some regularity conditions, we develop the oracle property of the proposed robust variable selection method. Finally, a simulation study and a detailed data analysis are carried out to assess and illustrate the small sample performance; they show that the proposed method performs favorably by combining the robustifying and penalized estimating techniques together in the joint mean and covariance model.published_or_final_versio

Interpreting DNA mixtures with relatives of a missing suspect

Recent advances in DNA profiling have been proven extremely useful for forensic human identification. DNA mixtures are commonly found in serious crimes such as rape as well as voluminous crimes like theft. In this paper, one general formula is obtained for the evaluation of DNA mixtures when the suspect is unavailable for typing, but one maternal and one paternal relatives of the suspect are typed instead. In principle, closer relatives of the suspect will provide more genetic information on the genotype of the unavailable suspect. The effect of the relatives' DNA profiles on the interpretation of DNA mixtures is illustrated with case example. © 2011 IEEE.published_or_final_versionThe 1st International Conference on Remote Sensing, Environment and Transportation Engineering (RSETE 2011), Nanjing, China, 24-26 June 2011. In Proceedings of the 1st RSETE, 2011, p. 7649-765

A novel method to construct taxonomy electrical appliances based on load signatures

A load signature is an electrical expression that a load device or appliance distinctly possesses. Load signatures can be applied to produce many useful services and products, such as, determining the energy usage of individual appliances, monitoring the health of critical equipment, monitoring power quality, and developing facility management tools. Load signatures of typical yet extensive loads are needed to be collected before applying them to different services and products. As there are an enormous number of electrical appliances, it is beneficial to classify the appliances for building a well-organized load signature database. The objective of this study is to develop an effective method to classify the loads. A 2-dimensional form of load signatures, voltage-current (V-I) trajectory, is suggested for characterizing the typical household appliances. Hierarchical clustering method was employed to classify the appliances and construct the taxonomy of the appliances. The taxonomy based on V-I trajectory was compared to the taxonomies based on traditional power metrics and eigenvectors in the previous studies. It was found that the groups of appliances in the taxonomy based on V-I trajectory were well-separated and had engineering meanings. © 2007 IEEE.published_or_final_versio

Tenofovir disoproxil fumarate for the treatment of chronic hepatitis B monoinfection

Introduction: Resistance in nucleoside/nucleotide analog (NA) therapy has always been a challenge in the management of chronic hepatitis B (CHB). Clinical studies: Initially developed for the treatment of HIV infection, early in vitro and clinical observational studies had shown tenofovir disoproxil fumarate (TDF) to be also active against CHB. Recent data from various multicenter phase 3 and 4 clinical trials have confirmed TDF being able to achieve a high viral suppression in both NA-naive and -experienced CHB patients. There are also emerging data on the efficacy of TDF in decompensated CHB. Although there are in vitro studies identifying certain mutation loci associated with a reduced susceptibility to TDF, there have so far been no reports of virologic resistance to TDF in clinical studies. TDF has a favorable safety profile, although more long-term data would be needed. Conclusions: TDF has the makings of an 'ideal' first-line drug for the treatment of CHB. © 2011 Asian Pacific Association for the Study of the Liver.postprin

Confounding, homogeneity and collapsibility for causal effects in epidemiologic studies

Detection of confounding and confounders is important for observational studies, and especially so for epidemiologic studies. Miettinen and Cook (1981) derived two criteria for detecting confounders. Using a model, Wickramaratne and Holford (1987) proved that the two criteria are necessary but not sufficient conditions for confounders. We take uniform nonconfounding to mean there is no confounding at a coarse-subpopulation-level obtained by pooling any number of subpopulations. We discuss the necessity and sufficiency of the two criteria for uniform nonconfounding. The concepts of homogeneity and collapsibility for causal effects are also defined, and the relation among confounding, homogeneity and collapsibility is discussed. We show that the common causal effect over all fine subpopulations is just the causal effect of the whole population.published_or_final_versio

Confounding, homogeneity and collapsibility for causal effects in epidemiologic studies

Detection of confounding and confounders is important for observational studies, and especially so for epidemiologic studies. Miettinen and Cook (1981) derived two criteria for detecting confounders. Using a model, Wickramaratne and Holford (1987) proved that the two criteria are necessary but not sufficient conditions for confounders. We take uniform nonconfounding to mean there is no confounding at a coarse-subpopulation-level obtained by pooling any number of subpopulations. We discuss the necessity and sufficiency of the two criteria for uniform nonconfounding. The concepts of homogeneity and collapsibility for causal effects are also defined, and the relation among confounding, homogeneity and collapsibility is discussed. We show that the common causal effect over all fine subpopulations is just the causal effect of the whole population.published_or_final_versio

Future prevention and treatment of chronic hepatitis B infection

Vaccination for hepatitis B virus (HBV) infection and treatment for chronic hepatitis B, while effective for primary prevention and control of the disease, still have their limitations. Global coverage of HBV immunization needs improvement. Several patient populations are noted to have suboptimal seroprotective rates after HBV vaccination. There are currently several potential new vaccines undergoing animal and human studies, most notably vaccines containing immunostimulatory DNA sequences. Long-term nucleoside analogue therapy is necessary in achieving permanent virologic suppression. Potential new treatments explore new mechanisms of action, including the inhibition of hepatitis B surface antigen release, targeting antifibrotic mechanism, and immunomodulation through novel interferons and therapeutic vaccines. The clinical application of potential new vaccines and therapies would enhance the prevention of HBV infection and treatment of chronic hepatitis B. © 2012 by Lippincott Williams & Wilkins.postprin

Dimension reduction based on canonical correlation

Dimension reduction is helpful and often necessary in exploring nonlinear or nonparametric regression structures with a large number of predictors. We consider using the canonical variables from the design space whose correlations with a spline basis in the response space are significant. The method can be viewed as a variant of sliced inverse regression (SIR) with simple slicing replaced by B-spline basis functions. The asymptotic distribution theory we develop extends to weakly dependent stationary sequences and enables us to consider asymptotic tests that are useful in determining the number of significant dimensions for modeling. We compare several tests for dimensionality and make specific recommendations for dimension selection based on our theoretical and empirical studies. These tests apply to any form of SIR. The methodology and some of the practical issues are illustrated through a tuition study of American colleges.published_or_final_versio