Search results for "Component"
showing 10 items of 1682 documents
Chemical Element Levels as a Methodological Tool in Forensic Science
2014
The aim of the present study was to define a methodological strategy for understanding how post- mortem degradation in bones caused by the environment affects different skeletal parts and for selecting better preserved bone samples, employing rare earth elements (REEs) analysis and multivariate statistics. To test our methodological proposal the samples selected belong to adult and young individuals and were obtained from the Late Roman Necropolis of c/Virgen de la Misericordia located in Valencia city centre (Comunidad Valenciana, Spain). Therefore, a method for the determination of major elements, trace elements and REEs in bone remains has been developed employing Inductively-Coupled Pla…
Capillary electrophoresis–inductively coupled plasma-mass spectrometry hyphenation for the determination at the nanogram scale of metal affinities an…
2012
Abstract A screening strategy based on hyphenated capillary electrophoresis and inductively coupled plasma mass spectrometry (CE–ICP-MS) was developed to classify phosphorylated ligands according to their europium(III) binding affinity in a hydro-organic medium (sodium formate, pH 3.7, H2O/MeOH 90:10, v/v). Taking advantage of the high sensibility of ICP-MS for detecting phosphorus, this method enabled to assess the affinity of a variety of phosphorylated compounds, including phosphine oxides, thiophosphines, phosphonates, and phosphinates, in less than 1 h and using less than 5 ng of substance. By varying the total europium concentration, complexation constants could be determined accordin…
Improvement of Hall Effect Current Transducer Metrological Performances in the Presence of Harmonic Distortion
2010
The performance of Hall effect current transducers (HECTs), under distorted waveform conditions, is usually characterized by means of a frequency response test. In this paper, it was investigated if frequency response is able to correctly evaluate the ratio and the phase errors under distorted conditions. Two HECTs, with the accuracy class level of 1% and 0.5%, respectively, were experimentally characterized under two conditions: 1) sinusoidal excitation with frequencies ranging from 50 to 750 Hz, which is the well-known frequency response test, and 2) nonsinusoidal excitation using fundamental frequency and one harmonic with adjusted amplitude and phase shift. It was found that ratio and p…
Table of Periodic Properties of Fullerenes Based on Structural Parameters.
2004
The periodic table (PT) of the elements suggests that hydrogen could be the origin of everything else. The construction principle is an evolutionary process that is formally similar to those of Darwin and Oparin. The Kekulé structure count and permanence of the adjacency matrix of fullerenes are related to structural parameters involving the presence of contiguous pentagons p, q and r. Let p be the number of edges common to two pentagons, q the number of vertices common to three pentagons, and r the number of pairs of nonadjacent pentagon edges shared between two other pentagons. Principal component analysis (PCA) of the structural parameters and cluster analysis (CA) of the fullerenes perm…
Principal components for multivariate spatiotemporal functional data
2014
Multivariate spatio-temporal data consist of a three way array with two dimensions’ domains both structured, temporally and spatially; think for example to a set of different pollutant levels recorded for a month/year at different sites. In this kind of dataset we can recognize time series along one dimension, spatial series along another and multivariate data along the third dimension. Statistical techniques aiming at handling huge amounts of information are very important in this context and classical dimension reduction techniques, such as Principal Components, are relevant, allowing to compress the information without much loss. Although time series, as well as spatial series, are recor…
Assessing High-Order Interdependencies Through Static O-Information Measures Computed on Resting State fMRI Intrinsic Component Networks
2022
Resting state brain networks have reached a strong popularity in recent scientific endeavors due to their feasibility to characterize the metabolic mechanisms at the basis of neural control when the brain is not engaged in any task. The evaluation of these states, consisting in complex physiological processes employing a large amount of energy, is carried out from diagnostic images acquired through resting-state functionalmagnetic resonance (RS-fMRI) on different populations of subjects. In the present study, RS-fMRI signals from the WU-MinnHCP 1200 Subjects Data Release of the Human Connectome Project were studied with the aim of investigating the high order organizational structure of the…
Functional Data Analysis in NTCP Modeling: A New Method to Explore the Radiation Dose-Volume Effects
2014
Purpose/Objective(s) To describe a novel method to explore radiation dose-volume effects. Functional data analysis is used to investigate the information contained in differential dose-volume histograms. The method is applied to the normal tissue complication probability modeling of rectal bleeding (RB) for patients irradiated in the prostatic bed by 3-dimensional conformal radiation therapy. Methods and Materials Kernel density estimation was used to estimate the individual probability density functions from each of the 141 rectum differential dose-volume histograms. Functional principal component analysis was performed on the estimated probability density functions to explore the variatio…
Comparing Spatial and Spatio-temporal FPCA to Impute Large Continuous Gaps in Space
2018
Multivariate spatio-temporal data analysis methods usually assume fairly complete data, while a number of gaps often occur along time or in space. In air quality data long gaps may be due to instrument malfunctions; moreover, not all the pollutants of interest are measured in all the monitoring stations of a network. In literature, many statistical methods have been proposed for imputing short sequences of missing values, but most of them are not valid when the fraction of missing values is high. Furthermore, the limitation of the methods commonly used consists in exploiting temporal only, or spatial only, correlation of the data. The objective of this paper is to provide an approach based …
Functional Principal Components Analysis with Survey Data
2008
This work aims at performing Functional Principal Components Analysis (FPCA) with Horvitz-Thompson estimators when the observations are curves collected with survey sampling techniques. FPCA relies on estimations of the eigenelements of the covariance operator which can be seen as nonlinear functionals. Adapting to our functional context the linearization technique based on the influence function developed by Deville (1999), we prove that these estimators are asymptotically design unbiased and convergent. Under mild assumptions, asymptotic variances are derived for the FPCA’ estimators and convergent estimators of them are proposed. Our approach is illustrated with a simulation study and we…
A functional approach to monitor and recognize patterns of daily traffic profiles
2014
Functional Data Analysis (FDA) is a collection of statistical techniques for the analysis of information on curves or functions. This paper presents a new methodology for analyzing the daily traffic flow profiles based on the employment of FDA. A daily traffic profile corresponds to a single datum rather than a large set of traffic counts. This insight provides ideal information for strategic decision-making regarding road expansion, control, and other long-term decisions. Using Functional Principal Component Analysis the data are projected into a low dimensional space: the space of the first functional principal components. Each curve is represented by their vector of scores on this basis.…