Generalized -means in GLMs with applications to the outbreak of COVID-19 in the United States.

Generalized -means can be combined with any similarity or dissimilarity measure for clustering. Using the well known likelihood ratio or -statistic as the dissimilarity measure, a generalized -means method is proposed to group generalized linear models (GLMs) for exponential family distributions. Given the number of clusters , the proposed method is established by the uniform most powerful unbiased (UMPU) test statistic for the comparison between GLMs.

Distance metrics optimized for clustering temporal dietary patterning among U.S. adults.

Objective: Few attempts to determine dietary patterns have incorporated concepts of time, specifically time and proportion of energy intake consumed throughout a day. A type of modified dynamic time warping (MDTW) was previously developed using an appropriate distance metric for patterning these aspects to determine temporal dietary patterns (TDP). This study further explores dynamic time warping (DTW) distance metrics including unconstrained DTW (UDTW), constrained DTW (CDTW), and MDTW with modern spectral clustering methods to optimize TDP related to dietary quality.

Green Tea Increases the Concentration of Total Mercury in the Blood of Rats following an Oral Fish Tissue Bolus.

Fish has many health benefits but is also the most common source of methylmercury. The bioavailability of methylmercury in fish may be affected by other meal components. In this study, the effect of green tea on the bioavailability of methylmercury from an oral bolus of fish muscle tissue was studied in rats and compared to a water treated control group and a group treated with meso-2,3-dimercaptosuccinic acid (DMSA), a compound used medically to chelate mercury.

Postharvest correlation between swordfish (Xiphius gladius) size and mercury concentration in edible tissues.

Total mercury was measured via thermal decomposition amalgamation atomic absorption spectroscopy in the muscle tissue of 82 swordfish originating in the Pacific Ocean and was found to range from 228 to 2,090 ppb. The relationships between total mercury concentration and the size of the fish (i.e.

Statistical analysis and modeling of mass spectrometry-based metabolomics data.

Multivariate statistical techniques are used extensively in metabolomics studies, ranging from biomarker selection to model building and validation. Two model independent variable selection techniques, principal component analysis and two sample t-tests are discussed in this chapter, as well as classification and regression models and model related variable selection techniques, including partial least squares, logistic regression, support vector machine, and random forest. Model evaluation and validation methods, such as leave-one-out cross-validation, Monte Carlo cross-validation, and receiver operating characteristic analysis, are introduced with an emphasis to avoid over-fitting the data.

Bayesian reconstruction of () directly from two-dimensional detector images a Markov chain Monte Carlo method.

The interatomic distance distribution, (), is a valuable tool for evaluating the structure of a molecule in solution and represents the maximum structural information that can be derived from solution scattering data without further assumptions. Most current instrumentation for scattering experiments (typically CCD detectors) generates a finely pixelated two-dimensional image. In contin-uation of the standard practice with earlier one-dimensional detectors, these images are typically reduced to a one-dimensional profile of scattering inten-sities, (), by circular averaging of the two-dimensional image.

Spatial scan statistics with overdispersion.

The spatial scan statistic has been widely used in spatial disease surveillance and spatial cluster detection for more than a decade. However, overdispersion often presents in real-world data, causing not only violation of the Poisson assumption but also excessive type I errors or false alarms. In order to account for overdispersion, we extend the Poisson-based spatial scan test to a quasi-Poisson-based test.