Search results for "component"
showing 10 items of 1682 documents
Social-ecological trends: managing the vulnerability of coastal fishing communities
2019
The loss of biodiversity, including the collapse of fish stocks, affects the vulnerability of social-ecological systems (SESs) and threatens local livelihoods. Incorporating community-centered indicators and SES drivers and exposures of change into coastal management can help anticipate and mitigate human and/or coastal vulnerability. We have proposed a new index to measure the social-ecological vulnerability of coastal fishing communities (Index of Coastal Vulnerability [ICV]) based on species, ecosystem, and social indicators. The ICV varies from 0 (no vulnerability) to 1 (very high vulnerability) and is composed of 3 components: species vulnerability, i.e., fish biological traits; ecosys…
A method for fitting multi-component decay curves
1982
Abstract A generalization of a non-iterative method recently proposed by Mukoyama for the fitting of two-component decay curve is presented. Two modifications of the procedure are also suggested, by which the influence of the statistical fluctuations of the data may be reduced. Results of fairly good quality are obtained also for three- and, to a lesser extent, for four-component decay curves.
Effects of Plant Density on the Number of Glandular Trichomes and on Yield and Quality of Essential Oils from Oregano.
2016
Plants yields are influenced by agronomic techniques. Plant density is a complex issue and extremely important when maximizing both crop quality, and biomass and essential oil yields. Plants belonging to the Origanum vulgare subspecies hirtum (Link) Ietswaart were grown adopting four types of plant density and were characterized in biometric and chemical terms. The samples were analyzed using the ANOVA (Principal Component Analysis) statistical method regarding biometric aspects, EO yield and peltate hair density. Essential oil (EO) was extracted by hydrodistillation and analyzed using GC-FID and GC-MS. GC-FID and GC-MS analysis led to the identification of 45 compounds from the EO. Plant …
A 21st century technique for food control: electronic noses.
2008
This work examines the main features of modern electronic noses (e-noses) and their most important applications in food control in this new century. The three components of an electronic nose (sample handling system, detection system, and data processing system) are described. Special attention is devoted to the promising mass spectrometry based e-noses, due to their advantages over the more classical gas sensors. Applications described include process monitoring, shelf-life investigation, freshness evaluation, authenticity assessment, as well as other general aspects of the utilization of electronic noses in food control. Finally, some interesting remarks concerning the strengths and weakn…
Monitoring of chicken meat freshness by means of a colorimetric sensor array
2012
A new optoelectronic nose to monitor chicken meat ageing has been developed. It is based on 16 pigments prepared by the incorporation of different dyes (pH indicators, Lewis acids, hydrogenbonding derivatives, selective probes and natural dyes) into inorganic materials (UVM-7, silica and alumina). The colour changes of the sensor array were characteristic of chicken ageing in a modi¿ed packaging atmosphere (30% CO2¿70% N2). The chromogenic array data were processed with qualitative (PCA) and quantitative (PLS) tools. The PCA statistical analysis showed a high degree of dispersion, with nine dimensions required to explain 95% of variance. Despite this high dimensionality, a tridimensional re…
Multivariate data analysis of quality parameters in drinking water.
2001
The quality of water destined for human consumption has been treated as a multivariate property. Since most of the quality parameters are obtained by applying analytical methods, the routine analytical laboratory (responsible for the accuracy of analytical data) has been treated as a process system for water quality estimation. Multivariate tools, based on principal component analysis (PCA) and partial least squares (PLS) regression, are used in the present paper to: (i) study the main factors of the latent data structure and (ii) characterize the water samples and the analytical methods in terms of multivariate quality control (MQC). Such tools could warn of both possible health risks rela…
Feature selection strategies for quality screening of diesel samples by infrared spectrometry and linear discriminant analysis.
2012
Abstract A rapid approach has been developed for the characterization of diesel quality, based on attenuated total reflectance – Fourier transform infrared (ATR-FTIR) spectrometry, which could be useful for diagnosing the sample quality condition. As a supervised technique, linear discriminant analysis (LDA) was employed to process the spectrometric data. The role of variable selection methods was also evaluated. Successive projection algorithm (SPA) and genetic algorithm (GA) feature selection techniques were applied prior to the discriminative procedure. It was aimed to compare the effect of feature selection procedures on classification capability of IR spectrometry for the diesel sample…
Detection of batch effects in liquid chromatography-mass spectrometry metabolomic data using guided principal component analysis.
2014
Metabolomics based on liquid chromatography-mass spectrometry (LC-MS) is a powerful tool for studying dynamic responses of biological systems to different physiological or pathological conditions. Differences in the instrumental response within and between batches introduce unwanted and uncontrolled data variation that should be removed to extract useful information. This work exploits a recently developed method for the identification of batch effects in high throughput genomic data based on the calculation of a delta statistic through principal component analysis (PCA) and guided PCA. Its applicability to LC-MS metabolomic data was tested on two real examples. The first example involved t…
Automated quality control protocol for MR spectra of brain tumors.
2008
Item does not contain fulltext eTUMOUR (http://www.etumour.net/) is acquiring a large database of brain tumor (1)H MR spectra to develop automated pattern recognition methods and decision support system (DSS) for tumor diagnosis. Development of accurate pattern-recognition algorithms requires spectra undistorted by artifacts, low signal-to-noise, or broad lines. eTUMOUR currently uses panels of expert spectroscopists to subjectively grade spectra as being acceptable or unacceptable. Automated quality control (QC) would be more satisfactory for several reasons: 1) to provide a reproducible objective classification of spectrum quality; 2) for use within the future DSS to prevent misdiagnosis …
Classification of Congeneric and QSAR of Homologous Antileukemic S–Alkylcysteine Ketones
2021
Based on a set of six vector properties, the partial correlation diagram is calculated for a set of 28 S-alkylcysteine diazomethyl- and chloromethyl-ketone derivatives. Those with the greatest antileukemic activity in the same class correspond to high partial correlations. A periodic classification is performed based on information entropy. The first four characteristics denote the group, and the last two indicate the period. Compounds in the same period and, especially, group present similar properties. The most active substances are situated at the bottom right. Nine classes are distinguished. The principal component analysis of the homologous compounds shows five subclasses included in t…