Principal Component Analysis Of Data Research Articles

Seasonal climate signals (1990–2008) in a modern Soreq Cave stalagmite as revealed by high-resolution geochemical analysis

High-resolution isotopic and geochemical analyses in a modern (1990–2008) Soreq Cave stalagmite are compared to instrumental records of rainfall and dripwater from the cave, with the aim of determining how seasonal-resolution climate information is transmitted to speleothem geochemistry. In situ, micron-scale analysis of oxygen isotope ratios (δ18O) and trace elements by ion microprobe in combination with a continuous, linear traverse of trace element concentrations by laser-ablation ICP-MS (LA-ICP-MS) allow the definition of geochemical pathways within the cave. Fluorescent banding, imaged by confocal laser fluorescent microscopy (CLFM), as well as δ18O and trace element variations is used to define 18 annual growth increments. Reduced intensity of fluorescent banding and a change in trace element variability reflect the decrease in average rainfall from 628mm/yr (1990–1998) to 433mm/yr (1999–2008). During the wetter period before 1998, Pearson (r-value) and Spearman (ρ-value) correlation coefficients are >0.5 for ion microprobe analyses of the element pairings Sr–Y, Y–P, and Mn–Si. After the transition to the drier period in 1999, a different set of geochemical pairings have r- and ρ-values >0.5, including Mg–δ18O, Mg–Sr, and Sr–Ba. Principal component analysis of data from the adjacent LA-ICP-MS traverse identifies two primary underlying modes of trace element variability. Based on the ion microprobe correlations and principal component analyses, we suggest that a greater seasonal influx of particulate material into the cave during the wetter period (1990–1998) brought about greater P, Cu, Sr, Na, and U variability in the stalagmite. The co-variability of δ18O, Mg, Sr, and Ba is characteristic of the trace element pattern from the drier period (1999–2008) of growth when particulate transport is reduced. These findings support a two-reservoir model of Soreq Cave dripwaters. One reservoir displays a well-mixed “baseline” with a decadal residence time that supplies water to the cave year-round, probably from fine pores or grain-boundary films in the vadose zone. The second reservoir is seasonal rainwater enriched in organic acids, colloids, and small particles and is rapidly transmitted to the cave. Finally, the similar patterns of fluorescence intensity, P, and Cu concentrations support the hypothesis that fluorescent bands in Soreq Cave speleothems are caused by the influx of organic colloids.

Demagnetization Analysis in Excel (DAIE). An open source workbook in Excel for viewing and analyzing demagnetization data from paleomagnetic discrete samples and u-channels

<p>The Demagnetization Analysis in Excel (DAIE) software is a single Microsoft Excel file designed for viewing and analyzing stepwise demagnetization data of both discrete and u-channel samples in paleomagnetic studies. DAIE is an Excel workbook and has an open modular structure organized in 10 worksheets. It is designed for an easy use and an interactive operability; all the commands and choices can be entered by sliding menus associated to single cells. The standard demagnetization diagrams and various parameters of common use are shown on the same worksheet including selectable parameters and user's choices. The remanence characteristic components may be computed by principal component analysis (PCA) on a selected interval of demagnetization steps. Saving of the PCA data can be done both sample by sample, or in automatic by applying the selected choices to all the samples included in the file. The whole workbook is free both for use and editing and it is available for download on a dedicated website.</p>

Endpoint Detection in Plasma Etching Using FFT and SVM

As semiconductor devices are highly integrated, etching control is much more difficult in semiconductor industry. Plasma etching has better performance than wet etching especially in small open area etching. In semiconductor manufacturing industry, the optical emission spectroscopy (OES) is widely used to collect data from plasma chamber. The enormous OES data need to be transformed for accutate endpoint detection. There are some research results regarding endpoint detection in plasma etching using various methods such as Principal Component Analysis (PCA), Partial Least Squares (PLS), etc. In this paper a new approach is proposed for endpoint detection of small open area wafers in plasma etching. The new approach utilizes a Fast Fourier Transform (FFT), which is an efficient algorithm to detect frequency changes in signal, and this property is applied to OES data to detect endpoint in etching process. By applying FFT, noise is reduced compared to PCA data. The data after FFT is used to detect endpoint using Support Vector Machine (SVM). The combination of FFT and SVM performs excellent in terms of endpoint detection, and the performance of proposed FFT/SVM algorithm is compared to the performance of PCA/SVM algorithm.

Antioxidant Capacity, Total Phenolic Content, Fatty Acids and Correlation by Principal Component Analysis of Exotic and Native Fruits from Brazil

The antioxidant capacities of seven exotic and native fruits from Brazil were evaluated using DPPH•, ABTS•+ and FRAP assays, in addition to their total phenolic content and fatty acid composition. Murici and dovialis presented the highest total phenolic contents (243.42 and 205.98 mg GAE 100 g-1, respectively), and the highest antioxidant capacities by the FRAP assay (24.97 and 23.70 µmol Fe2+ g-1, respectively). In the DPPH• and ABTS•+ assays, dovialis presented the highest antioxidant capacity, 9.59 and 10.41 TE g-1, respectively. The highest alpha-linolenic and linoleic acid contents were found in siriguela (107.86 mg FA g-1 TL) and tomatinho do mato (215.50 mg FA g-1 TL), respectively. The principal component analysis (PCA) of fatty acids yielded three significant PCs, which accounted for 99.75% of the data set total variance. The PCA data of the antioxidant analyses yielded two significant PCs, which accounted for 97.00% of the total variance.

Sensor fault diagnosis with a probabilistic decision process

In this paper a probabilistic approach to sensor fault diagnosis is presented. The proposed method is applicable to systems whose dynamic can be approximated with only few active states, especially in process control where we usually have a relatively slow dynamics. Unlike most existing probabilistic approaches to fault diagnosis, which are based on Bayesian Belief Networks, in this approach the probabilistic model is directly extracted from a parity equation. The relevant parity equation can be found using a model of the system or through principal component analysis of data measured from the system. In addition, a sensor detectability index is introduced that specifies the level of detectability of sensor faults in a set of analytically redundant sensors. This index depends only on the internal relationships of the variables of the system and noise level. The method is tested on a model of the Tennessee Eastman process and the result shows a fast and reliable prediction of fault in the detectable sensors.

A Workflow For The Metabolomic/Metabonomic Investigation of Exhaled Breath Using Thermal Desorption Gc–Ms

Confounding factors in the analysis of human breath by thermal desorption GC-MS are reviewed, with special emphasis on the high water levels encountered in human breath samples. Multilinear regression optimization of breath sampling factors, along with the selection of ubiquitous sample components used as retention-time standards, enabled data registration based on retention indexing and mass spectral alignment. This was done on a component-by-component basis. The methodology developed reconciled participant safety, artefacts from accelerated hydrolysis of the stationary phase and the destructive nature of thermal desorption. Furthermore, using ubiquitous methylated cyclic-siloxanes in the thermal desorption-GC-MS chromatograms enabled secondary retention indexing for each chromatogram. This methodology enables the creation of a 'breath matrix' that is based on a combination of retention indexing and the mass spectral registration of isolated peaks. This approach facilitated more efficient data modeling and a case study from a 22-participant (10 male, 12 female) stress-intervention experiment. Principal component analysis of data registered by retention indexing did not classify successfully stressed from unstressed states. By contrast, adoption of a breath matrix approach enabled 95% separation.

Groundwater quality in Imphal West district, Manipur, India, with multivariate statistical analysis of data

The aim of this paper was to analyze the groundwater quality of Imphal West district, Manipur, India, and assess its suitability for drinking, domestic, and agricultural use. Eighteen physico-chemical variables were analyzed in groundwater from 30 different hand-operated tube wells in urban, suburban, and rural areas in two seasons. The data were subjected to uni-, bi-, and multivariate statistical analysis, the latter comprising cluster analysis (CA), principal component analysis (PCA), and factor analysis (FA). Arsenic concentrations exceed the Indian standard in 23.3% and the WHO limit in 73.3% of the groundwater sources with only 26.7% in the acceptable range. Several variables like iron, chloride, sodium, sulfate, total dissolved solids, and turbidity are also beyond their desirable limits for drinking water in a number of sites. Sodium concentrations and sodium absorption ratio (SAR) are both high to render the water from the majority of the sources unsuitable for agricultural use. Multivariate statistical techniques, especially varimax rotation of PCA data helped to bring to focus the hidden yet important variables and understand their roles in influencing groundwater quality. Widespread arsenic contamination and high sodium concentration of groundwater pose formidable constraints towards its exploitation for drinking and other domestic and agricultural use in the study area, although urban anthropogenic impacts are not yet pronounced.

Changes on colour parameters caused by high‐pressure processing of apple juice made from six different varieties

SummaryThe colour changes caused by high‐pressure processing at different temperatures of apple juice were investigated. Six apple varieties were used (Braeburn, Fuji, Gala, Golden Delicious, Granny Smith and Red Delicious), searching for the influence of the variety from two different approaches: a kinetic study, finding the best model for each one of them, and a multivariate study consisting of a principal component analysis of data. Although it had lower initial values, redness (a*) was more influenced by high pressure than yellowness (b*). The pattern followed by colour changes was found to be definitively dependent on the variety. High‐pressure processing affects in a stronger way the absorbances located near 400 nm (i.e. 400.5 nm in Fuji and 434.0 nm in Braeburn).

Kinetic and Multivariate Analysis of Polyphenol Oxidase Inactivation by High Pressure and Temperature Processing in Apple Juices made from Six Different Varieties

The effectiveness of high pressure processing on the inactivation of apple polyphenol oxidase has been widely investigated. However, from an industrial point of view, there is a need for assessing this effectiveness on each one of the different apple varieties that each company uses for their products. This piece of work fills in this gap, studying the effect of the variety on apple juice polyphenol oxidase inactivation. Six varieties were assayed (Braeburn, Fuji, Gala, Golden Delicious, Granny Smith, and Red Delicious), searching for this influence from two different approaches: a kinetic study, finding the best model for each one of them, and a multivariate part consisting of a principal component analysis of data.

Distribution of heavy elements in urban and rural surface soils: the Novi Sad city and the surrounding settlements, Serbia

Concentrations of ten heavy elements (Cd, Co, Cr, Cu, Fe, Hg, Mn, Ni, Pb, and Zn), as well as the pH values, organic matter contents, and electrical conductivities were measured in the surface soil samples collected from 21 sites of urban areas in the city of Novi Sad, the second largest city in Serbia, its suburban settlement and the nearby villages. Range of the heavy element concentrations was from 0.16 mg/kg (for Hg) to 18,994 mg/kg (for Fe). Significantly higher Hg and Mn concentrations were observed in subgroups with rural and market garden samples in comparison to the subgroups with urban and grassland samples, respectively, while the contents of Pb found in the grasslands subgroup were significantly higher than in the subgroup with market garden soils. Only one sample of urban soil exceeded the maximum permissible value for Zn set by the relevant Serbian legislation. According to the Dutch soil quality standard, the Cd and Co concentrations in majority of the examined soils were higher than the target values for unpolluted soil. The content of Hg was above the target value in 52% of the samples, most of them belonging to the subgroup of market garden soils. The results for the Novi Sad city area were compared to the relevant data available for other cities in the Western Balkan Countries. Principal component analysis of data revealed seven outlying samples, while the rest of the analyzed samples were grouped together indicating similar heavy element patterns most probably due to mixed emission sources.

Application of Differential Scanning Calorimetry-Chemometric Coupled Procedure to the Evaluation of Thermo-Oxidation on Extra Virgin Olive Oil

In this work, the opportunity of adopting a differential scanning calorimetry (DSC)-principal component analysis (PCA) coupled procedure to measure the degree of thermal stress for extra virgin olive oil (EVOO) was presented. Oil was subjected to thermal stress under convectional or microwave heating treatments at different heating times up to 1,440 and 15 min, respectively, and p-anisidine values (PAV) were obtained on all samples to measure their oxidative degradation. The entire DSC profiles obtained on the oil upon cooling in the range from 30 °C to –80 °C and subsequent re-heating to 30 °C at different times and under cooking procedures have been subjected to PCA data analysis. PCA discriminated samples by means of profile changes in DSC transition both upon cooling and heating not only according to treatment times (which accounted for the degree of thermo-oxidation) but also considering different heating process. The proposed procedure may be useful to measure oil thermal stress and to select appropriate heating condition to be applied for EVOO both in industrial and/or in food-catering sectors.

Potential of Dust and Soot from Air-Filters of Motor Vehicle Engines as a Forensic Tool: First Experimental Palynological Approach in India

Dust and soot samples collected from air filters of motor cars and motor boats from three localities, namely Darjeeling, Murshidabad and the Sundarbans, West Bengal, India, each with its own characteristic vegetation type, were analysed for pollen and spore content to investigate their potentials as palynological traps. Pollen grains from high altitude vegetation (Alnus nepalensis, Ilex sp., Pinus sp., Primula sp., Rhododendron sp., Pteris sp., Asplenium sp., Duabanga sp.) were recovered from cars driven through Darjeeling to Kalimpong while pollen grains of mesophytic plants (Mangifera indica, Cocos nucifera, Borassus flabellifer, Parthenium hysterophorus, Azadirachta indica, Lantana camara) and mangroves (Sonneratia apetala, Avicennia sp., Acanthus ilicifolius, Bruguiera sp., Rhizophora mucronata, Heritiera fomes, Phoenix paludosa, Nypa fruticans) were recovered from the vehicles in the Murshidabad district and motor boats in the Indian Sundarbans respectively. Principal Components Analysis (PCA) revealed that pollen spectra from different vegetation zones form distinct groups, while dust/soot samples from areas of similar vegetation zone form a single group while Correspondence Analysis (CA) demonstrates that the dust/soot samples from a distinct vegetation zone and the recovered palynotaxa from these dust/soot samples from a single group. Palynoassemblage analysis, together with PCA and CA data, suggests that dust and soot from air filters of motor vehicle engines may be a reliable trap for palynomorphs, which may help to trace the localities through which vehicles in question have travelled.

GeoPCA: a new tool for multivariate analysis of dihedral angles based on principal component geodesics

The GeoPCA package is the first tool developed for multivariate analysis of dihedral angles based on principal component geodesics. Principal component geodesic analysis provides a natural generalization of principal component analysis for data distributed in non-Euclidean space, as in the case of angular data. GeoPCA presents projection of angular data on a sphere composed of the first two principal component geodesics, allowing clustering based on dihedral angles as opposed to Cartesian coordinates. It also provides a measure of the similarity between input structures based on only dihedral angles, in analogy to the root-mean-square deviation of atoms based on Cartesian coordinates. The principal component geodesic approach is shown herein to reproduce clusters of nucleotides observed in an η–θ plot. GeoPCA can be accessed via http://pca.limlab.ibms.sinica.edu.tw.

Texture analysis in an apple progeny through instrumental, sensory and histological phenotyping

Phenotypic analysis of texture traits was performed in an apple progeny by three complementary approaches: two classical instrumental measurements (compression and penetrometry), sensory assessment and histological screening. The progeny was composed of 141 individuals harvested over 2 years. Sensory and instrumental texture were assessed at harvest and after 2 and 4 months of cold storage. Histological screening was performed by combining macro-vision of outer parenchyma sections and image analysis on fruits after 2 months storage. Harvest year was observed to have a major impact on texture phenotypes followed by storage and genetic factors. Principal component analysis of data from the instrumental texture evaluations showed that the two methods complemented each other in characterizing the texture of the apple progeny. Compression parameters correlated better than penetrometry variables with sensory descriptors related to crispness, firmness, and graininess. Cell size distribution differentiated individuals in the apple progeny. It correlated with instrumental texture analyses and with juiciness perception. All measured texture related traits showed that they were all under genetic control with high heritability values. Higher values were obtained for fruits after 2 months storage. These results provide ground for future search of new apple texture QTLs.

Neighbourhood immigrant acculturation and diet among Hispanic female residents of New York City.

To identify predominant dietary patterns among Hispanic women and to determine whether adherence to dietary patterns is predicted by neighbourhood-level factors: linguistic isolation, poverty rate and the retail food environment. Cross-sectional analyses of predictors of adherence to dietary patterns identified from principal component analysis of data collected using the Study of Women's Health Across the Nation FFQ. Census data were used to measure poverty rates and the percentage of Spanish-speaking families in the neighbourhood in which no person aged ≥14 years spoke English very well (linguistic isolation) and the retail food environment was measured using business listings data. New York City. A total of 345 Hispanic women. Two major dietary patterns were identified: a healthy dietary pattern loading high for vegetables, legumes, potatoes, fish and other seafood, which explained 17 % of the variance in the FFQ data and an energy-dense dietary pattern loading high for red meat, poultry, pizza, french fries and high-energy drinks, which explained 9 % of the variance in the FFQ data. Adherence to the healthy dietary pattern was positively associated with neighbourhood linguistic isolation and negatively associated with neighbourhood poverty. Presence of more fast-food restaurants per square kilometre in the neighbourhood was significantly associated with lower adherence to the healthy diet. Adherence to the energy-dense dietary pattern was inversely, but not significantly, associated with neighbourhood linguistic isolation. These results are consistent with the hypothesis that living in immigrant enclaves is associated with healthy dietary patterns among Hispanics.

A Linear Correction for Principal Component Analysis of Dynamic Fluorescence Diffuse Optical Tomography Images

The analysis of dynamic fluorescence diffuse optical tomography (D-FDOT) is important both for drug delivery research and for medical diagnosis and treatment. The low spatial resolution and complex kinetics, however, limit the ability of FDOT in resolving drug distributions within small animals. Principal component analysis (PCA) provides the capability of detecting and visualizing functional structures with different kinetic patterns from D-FDOT images. A particular challenge in using PCA is to reduce the level of noise in D-FDOT images. This is particularly relevant in drug study, where the time-varying fluorophore concentration (drug concentration) will result in the reconstructed images containing more noise and, therefore, affect the performance of PCA. In this paper, a new linear corrected method is proposed for modeling these time-varying fluorescence measurements before performing PCA. To evaluate the performance of the new method in resolving drug biodistribution, the metabolic processes of indocyanine green within mouse is dynamically simulated and used as the input data of PCA. Simulation results suggest that the principal component (PC) images generated using the new method improve SNR and discrimination capability, compared to the PC images generated using the uncorrected D-FDOT images.

Effets de quelques prétraitements physico—chimiques sur la levée de l'inhibition tégumentaire des graines de Retama monosperma Boiss. et recherches des conditions thermiques optimales de germination

Seeds of Retama monosperma are affected by integumentary inhibition preventing their germination in the natural conditions. In the laboratory, the germination is triggered after chemical scarification of seeds by undiluted sulfuric acid, in a range of temperatures, between 10 °C and 30 °C. The principal component analysis of data relating to the capacity of germination, coefficients of velocity and latency time obtained after pretreatment with sulfuric acid for 4, 6 and 8 hours, tested at different temperatures, show that the optimum thermal germination is between 20 °C and 25 °C. Indeed, at these two temperatures, we recorded the best coefficients of velocity (23.25% to 31.81%), germination capacity (72% to 92%) and the shortest latency time (1 to 2 days).

Variability of Polyphenol Compounds in Myrtus Communis L. (Myrtaceae) Berries from Corsica

Polyphenol compounds were extracted from Myrtus communis L. berries (Myrtaceae) by maceration in 70% ethanol and analysed by HPLC-DAD and electrospray mass spectrometry. The Myrtus berries were collected at maturity from seven localities on the island of Corsica (France) and the sampling was carried out during three years. The polyphenol composition of Corsican Myrtus berries was characterized by two phenolic acids, four flavanols, three flavonols and five flavonol glycosides. The major compounds were myricetin-3-O-arabinoside and myricetin-3-O-galactoside. Principal components analysis (PCA) is applied to study the chemical composition and variability of myrtle berries alcoholic extracts from the seven localities. Canonical analysis and PCA data distinguishes two groups of myrtle berries characterized by different concentrations of polyphenols according to soil and years of harvest. The variations in the polyphenol concentration were due to biotic and abiotic factors.

Perceived parental support predicts enhanced late positive event-related brain potentials to parent faces

This study examined event-related brain potentials in college students viewing facial pictures of their parents, celebrities, and strangers in the context of a guessing task. A temporal principal component analysis of data obtained from midline electrode sites was used to extract a component reflecting the mid- to late-positive deflection observed between 200 and 500 ms following stimulus onset. Parent faces elicited enhanced positivity compared to celebrity and stranger faces suggesting greater attention allocation to parent faces. In addition, greater perceived parental support predicted larger factor scores to parent faces relative to non-parent faces. Greater perceived negative interaction with parent, however, attenuated this relationship.

Constructing Indices of Rural Living Standards in Northwestern Bangladesh

This study aimed to construct indices of living standards in rural Bangladesh that could be useful to study health outcomes or identify target populations for poverty-alleviation programmes. The indices were constructed using principal component analysis of data on household assets and house construction materials. Their robustness and use was tested and found to be internally consistent and correlated with maternal and infant health, nutritional and demographic indicators, and infant mortality. Indices derived from 9 or 10 household asset variables performed well; little was gained by adding more variables but problems emerged if fewer variables were used. A ranking of the most informative assets from this rural, South Asian context is provided. Living standards consistently and significantly improved over the six-year study period. It is concluded that simple household socioeconomic data, collected under field conditions, can be used for constructing reliable and useful indices of living standards in rural South Asian communities that can assist in the assessment of health, quality of life, and capabilities of households and their members.