Functional data analytic approach of modeling ECG T-wave shape to measure cardiovascular behavior

The T-wave of an electrocardiogram (ECG) represents the ventricular repolarization that is critical in restoration of the heart muscle to a pre-contractile state prior to the next beat. Alterations in the T-wave reflect various cardiac conditions; and links between abnormal (prolonged) ventricular repolarization and malignant arrhythmias have been documented. Cardiac safety testing prior to approval of any new drug currently relies on two points of the ECG waveform: onset of the Q-wave and termination of the T-wave; and only a few beats are measured. Using functional data analysis, a statistical approach extracts a common shape for each subject (reference curve) from a sequence of beats, and then models the deviation of each curve in the sequence from that reference curve as a four-dimensional vector. The representation can be used to distinguish differences between beats or to model shape changes in a subject's T-wave over time. This model provides physically interpretable parameters characterizing T-wave shape, and is robust to the determination of the endpoint of the T-wave. Thus, this dimension reduction methodology offers the strong potential for definition of more robust and more informative biomarkers of cardiac abnormalities than the QT (or QT corrected) interval in current use.Comment: Published in at http://dx.doi.org/10.1214/09-AOAS273 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Heterogeneous Information and Appraisal Smoothing

This study examines the heterogeneous appraiser behavior and its implication on the traditional appraisal smoothing theory. We show that the partial adjustment model is consistent with the traditional appraisal smoothing argument only when all the appraisers choose the same smoothing technique. However, if appraiser behavior is heterogeneous and exhibits cross-sectional variation due to the difference in their access to, and interpretation of information, the model actually leads to a mixed outcome: The variance of the appraisal-based returns can be higher or lower than the variance of transaction-based return depending on the degree of such heterogeneity. Using data from the residential market, we find that, contrary to what the traditional appraisal smoothing theory would predict, appraisal-based indices may not suffer any “smoothing” bias. These findings suggest that the traditional appraisal smoothing theory, which fails to consider the heterogeneity of appraiser behaviors, exaggerates the effect of appraisal smoothing.

Rotation alignment in neutron-rich Cr isotopes: A probe of deformed single-particle levels across N=40

Recent experiments have reached the neutron-rich Cr isotope with N=40 and confirmed enhanced collectivity near this sub-shell. The current data focus on low-spin spectroscopy only, with little information on the states where high-j particles align their spins with the system rotation. By applying the Projected Shell Model, we show that rotation alignment occurs in neutron-rich even-even Cr nuclei as early as spin 8 and, due to shell filling, the aligning particles differ in different isotopes. It is suggested that observation of irregularities in moments of inertia is a direct probe of the deformed single-particle scheme in this exotic mass region.Comment: 6 pages, 5 figures, accepted for publication in Phys. Rev.

Statistical and Functional Analysis of Genomic and Proteomic Data

High-throughput technologies have led to an explosion in the availability of data at the genome scale. Such data provide important information about cellular processes and causes of human diseases, as well as for drug discovery. Deciphering the biologically relevant results from these data requires comprehensive analytical methods. In this dissertation, we present methods for gene and protein expression data analysis. Our major contributions include a method for differential in-gelelectrophoresis data analysis capable of removing protein-specific dye bias in the data, a method for finding unknown biological groups using expression data, and a method for identifying active and inactive signaling pathways in a gene expression signature based on the enrichment of downstream target genes of pathways

A Model-Driven Architecture based Evolution Method and Its Application in An Electronic Learning System

Software products have been racing against aging problem for most of their lifecycles, and evolution is the most effective and efficient solution to this problem. Model-Driven Architecture (MDA) is a new technique for software product for evolving development and reengineering methods. The main steps for MDA are to establish models in different levels and phases, therefore to solve the challenges of requirement and technology change. However, there is only a standard established by Object Management Group (OMG) but without a formal method and approach. Presently, MDA is widely researched in both industrial and research areas, however, there is still without a smooth approach to realise it especially in electronic learning (e-learning) system due to the following reasons: (1) models’ transformations are hard to realise because of lack of tools, (2) most of existing mature research results are working for business and government services but not education area, and (3) most of existing model-driven researches are based on Model-Driven Development (MDD) but not MDA because of OMG standard’s preciseness. Hence, it is worth to investigate an MDA-based method and approach to improve the existing software development approach for e-learning system. Due to the features of MDA actuality, a MDA-based evolution method and approach is proposed in this thesis. The fundamental theories of this research are OMG’s MDA standard and education pedagogical knowledge. Unified Modelling Language (UML) and Unified Modelling Language Profile are hired to represent the information of software system from different aspects. This study can be divided into three main parts: MDA-based evolution method and approach research, Platform-Independent Model (PIM) to Platform-Specific Model (PSM) transformation development, and MDA-based electronic learning system evolution. Top-down approach is explored to develop models for e-learning system. A transformation approach is developed to generate Computation Independent Model (CIM), Platform-Independent Model (PIM), and Platform-Specific Model (PSM); while a set of transformation rules are defined following MDA standard to support PSM’ s generation. In addition, proposed method is applied in an e-learning system as a case study with the prototype rules support. In the end, conclusions are drawn based on analysis and further research directions are discussed as well. The kernel contributions are the proposed transformation rules and its application in electronic learning system