Genome-wide association (GWA) studies provide large amounts of high-dimensional data. GWA studies aim to identify variables, i.e., single nucleotide polymorphisms (SNP) that increase the risk for a given phenotype and have been successful in identifying susceptibility loci for several complex diseases. A remaining challenge is however to predict the individual risk based on the genetic pattern....

Hierarchical, or nested, data structures are common throughout many areas of research. However, until recently there has not been any appropriate technique for analyzing these types of data. Now, with several user-friendly software programs available, and some more readable texts and treatments on the topic, researchers need to be aware of the issue, and how it should be dealt with. The goal of...

This paper presents a new approach for objective image quality assessment using multi-metric fusion. The current research is motivated by the observation that there is no single metric that provides the best performance scores in all conditions. To attain MMF, we approve an analytical formula based approach. First, we collect a large number of test images, each of which has a score labeled by h...

We report on an extensive experiment to compare an iterative solver preconditioned by several versions of incomplete LU factorization with a sparse direct solver using LU factorization with partial pivoting. Our test suite is 24 nonsymmetric matrices drawn from benchmark sets in the literature. On a few matrices, the best iterative method is more than 5 times as fast and more than 10 times as m...

Elucidating causal relationship among variables of interests is critical to epidemiological studies. Such studies often involve mediational models, and require appropriate statistical assessment of mediational effects. However, the current statistical methodologies used to assess mediational effect are limited to linear association. Here, we propose a new definition of mediational effects for a...

Linear mappings are omnipresent in data processing analysis ranging from regression to distance metric learning. The interpretation of coefficients from under-determined mappings raises an unexpected challenge when the original modeling goal does not impose regularization. Therefore, a general posterior regularization strategy is presented for inducing unique results, and additional sensitivity...

BACKGROUND Muscle atrophy and asymmetric extremity growth is a common feature of linear scleroderma (LS). Extra-cutaneous features are also common and primary neurologic involvement, with sympathetic dysfunction, may have a pathogenic role in subcutaneous and muscle atrophy. The aim was investigate nerve conduction and muscle involvement by electromyography in pediatric patients with LS. METH...

We have developed a new algorithm based on the mathematical theory of linear programming (LP) and implemented it in our program RAPTOR. Our new approach provides an elegant formulation of the protein-threading problem, overcomes the intractability problem of protein threading, in practice, and allows us to use existing powerful linear programming software to obtain optimal protein threading sol...

abstract- the evaluation of leaf area and leaf nutritional value is important for crop growth modeling and estimations of its performance. the purpose of this study was to use image processing techniques to develop an economical method to ease the assessment of nutrient status and leaf area (la) of plants and to compare the outcomes of this method with linear models. leaf area and leaf chloroph...

background there are several studies in the literature investigating factors which can induce non-alcoholic fatty liver disease (nafld) in different populations. however, the existing literature lacks powerful studies addressing the factors which may predict the severity of nafld. objectives in the current study, we aimed to evaluate factors independently associated with liver echogenicity in a...