scholarly journals VARIACIONES NICTEMERALES EN LA COMUNIDAD DE ZOOPLANCTON DE LA BAHIA DE SANTA MARTA, MAR CARIBE COLOMBIANO

Author(s):  
Alvaro Ramiro BernaI V. ◽  
Sven Zea

Day-night and between-day variation in surficial zooplankton composition and its relationship to environmental parameters were analyzed in the Santa Marta Bay, Colombian Caribbean, by Principal Components Analysis. Sampling was carried out every four hours in three different days between August and October 1989. The greatest variation in abundance (first principal component) was due to an increase over the mean in most groups at nightfall and during night hours. This variation was inversely and significantly correlated with incident light intensity, and was interpreted as consequence of the vertical migration out of the surface zone. On the other hand, the second and third principal components showed differences amog days for groups and within groups; those that existed in the first sampling day with respect to the other two were highlighted by the second component,, and were negatively correlated with temperature and positively correlated with disolved nitrates. These results were interpreted as a consequence of movements of water masses with different physical-chemical characteristics and zooplankton composition over the sampling site. However, a case of close association between these parameters and the changes in migrating movements could not be ruled out.

Author(s):  
Jihhyeon Yi ◽  
Sungryul Park ◽  
Juah Im ◽  
Seonyeong Jeon ◽  
Gyouhyung Kyung

The purpose of this study was to examine the effects of display curvature and hand length on smartphone usability, which was assessed in terms of grip comfort, immersive feeling, typing performance, and overall satisfaction. A total of 20 younger individuals with the mean (SD) age of 20.8 (2.4) yrs were divided into three hand-size groups (small: 8, medium: 6, large: 6). Two smartphones of the same size were used – one with a flat display and the other with a side-edge curved display. Three tasks (watching video, calling, and texting) were used to evaluate smartphone usability. The smartphones were used in a landscape mode for the first task, and in a portrait mode for the other two. The flat display smartphone provided higher grip comfort during calling (p = 0.008) and texting (p = 0.006) and higher overall satisfaction (p = 0.0002) than the curved display smartphone. The principal component regression (adjusted R2 = 0.49) of overall satisfaction on three principal components comprised of the remaining measures showed that the first principal component on grip comfort was more important than the other two on watching experience and texting performance. It is thus necessary to carefully consider the effect of display curvature on grip comfort when applying curved displays to hand-held devices such as smartphones.


Author(s):  
Ancuta Simona Rotaru ◽  
Ioana Pop ◽  
Anamaria Vatca ◽  
Luisa Andronie

Principal Component Analysis is a method factor - factor analysis - and is used to reduce data complexity by replacingmassive data sets by smaller sets. It is also used to highlight the way in which the variables are correlated with eachother and to determining the (less)latent variableswhich are behind the (more)measured variables. These latent variables are called factors, hence the name of the methodi.e. factor analysis. Our paper shows the applicability of Principal Components Analysis (PCA) in livestock area of study by carrying out a researchon some physiological characteristics in the case of tencow breeds.By using PCA only two factors have been preserved, concentrating over 80% of their information from the four variables in question, one factor concentrating weight and height and the other factor concentrating trunk circumference and weight at calving, respectively.


2021 ◽  
pp. 000370282098784
Author(s):  
James Renwick Beattie ◽  
Francis Esmonde-White

Spectroscopy rapidly captures a large amount of data that is not directly interpretable. Principal Components Analysis (PCA) is widely used to simplify complex spectral datasets into comprehensible information by identifying recurring patterns in the data with minimal loss of information. The linear algebra underpinning PCA is not well understood by many applied analytical scientists and spectroscopists who use PCA. The meaning of features identified through PCA are often unclear. This manuscript traces the journey of the spectra themselves through the operations behind PCA, with each step illustrated by simulated spectra. PCA relies solely on the information within the spectra, consequently the mathematical model is dependent on the nature of the data itself. The direct links between model and spectra allow concrete spectroscopic explanation of PCA, such the scores representing ‘concentration’ or ‘weights’. The principal components (loadings) are by definition hidden, repeated and uncorrelated spectral shapes that linearly combine to generate the observed spectra. They can be visualized as subtraction spectra between extreme differences within the dataset. Each PC is shown to be a successive refinement of the estimated spectra, improving the fit between PC reconstructed data and the original data. Understanding the data-led development of a PCA model shows how to interpret application specific chemical meaning of the PCA loadings and how to analyze scores. A critical benefit of PCA is its simplicity and the succinctness of its description of a dataset, making it powerful and flexible.


2022 ◽  
Author(s):  
Jaime González Maiz Jiménez ◽  
Adán Reyes Santiago

This research measures the systematic risk of 10 sectors in the American Stock Market, discerning the COVID-19 pandemic period. The novelty of this study is the use of the Principal Component Analysis (PCA) technique to measure the systematic risk of each sector, selecting five stocks per sector with the greatest market capitalization. The results show that the sectors that have the greatest increase in exposure to systematic risk during the pandemic are restaurants, clothing, and insurance, whereas the sectors that show the greatest decrease in terms of exposure to systematic risk are automakers and tobacco. Due to the results of this study, it seems advisable for practitioners to select stocks that belong to either the automakers or tobacco sector to get protection from health crises, such as COVID-19.


2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Pandian Suresh Kumar ◽  
Jibu Thomas

Abstract The present investigation embarks on understanding the relationship between microalgal species assemblages and their associated physico-chemical parameter dynamics of the catchment region of river Noyyal. Totally, 142 microalgae cultures belonging to 10 different families were isolated from five different sites during four seasons and relative percentage distribution showed that Scenedesmaceae (36.6%) and site S1 (26.4%) with predominant microalgae population. Diversity indices revealed that microalgae communities were characterized by high Hʹ index, lower Simpson dominance, and Margalef index value with indefinite patterns of annual variations. Results showed that variation in the physico-chemical parameters in each sampling site has its impact on the microalgae population during each season. Multivariate statistical analysis viz., Karl Pearson’s correlation coefficient, principal component analysis, and canonical correspondence analysis were applied on microalgae species data, to evaluate the seasonal relationship between microalgae and physico-chemical parameters. The findings of our study concluded that the physico- chemical parameters influenced the dominant taxa of microalgae Chlorellaceae, Scenedesmaceae and Chlorococcaceae in river Noyyal and gives a base data for the seasonal and dynamic relationship between environmental parameters and microalgae population.


1992 ◽  
Vol 74 (2) ◽  
pp. 595-598 ◽  
Author(s):  
Henry F. Kaiser

Cliff (1988) has presented a formula for the reliability of a principal component which is different from my long-known formula (Kaiser, 1957, 1991) for coefficient alpha of a principal component. Cliff claims that his approach is “correct” and mine “is the result of a misapplication of the formula for internal consistency reliability” Actually, both developments are correct but are based on different premises: Cliff considers measurement error within—but not between—attributes, while I consider measurement error between—but not within—attributes. The application of my formula to the knotty problem of the “number of factors”—the Kaiser-Guttman Rule—appears often to give the “right” result, when “right” means agreement with the subjective judgment of factor-analytic grandmasters. But when it fails it is approximately equally likely to overfactor as to underfactor. Cliff's formula, on the other hand, when used to establish the number of factors, almost invariably overfactors and, in the limit, as the within-attribute reliabilities all approach one (as with, say, physical attributes), nonsensically will declare all principal components perfectly reliable no matter how small their associated eigenvalues, yielding an absurd answer if used to establish the number of factors.


Blood ◽  
2005 ◽  
Vol 106 (11) ◽  
pp. 4249-4249
Author(s):  
Mario-Antoine Dicato ◽  
Garry Mahon

Abstract The human genome has been estimated to contain tens of thousands of genes. Of these, the promoters have been experimentally verified for almost two thousand. We have examined the DNA sequences just up-stream of the transcription start site, a region which includes the TATA box. Genetic control sites, such as promoters, often have a characteristic consensus sequence, but the variation about a given consensus sequence has received little attention. Sequence variations may be related to functional differences amongst the control sites. Principal components analysis has been chosen because of its generality and the variety of phenomena which it reveals. Promoter sequences were considered because of the large number available and their importance in gene expression. The sequences of the 1977 promoters recognised by human RNA polymerase II were obtained from the Eukaryotic Promoter Database. Many of these promoters are of interest in oncology and the database includes sequences for growth factors (e.g. GM-CSF, interleukins), oncogenes and tumour viruses among others. Sub-sequences of 25 bases centred on position −13 relative to the transcription start site were extracted. Two bits were used to encode each base (a=11, c=00, g=10 and t=01) and the covariance matrix of the resulting 50 variables was determined. The eigenvalues and eigenvectors of the covariance matrix were calculated. All calculations were carried out by computer using MS-Excel and SYSTAT 11. The eigenvalues of the covariance matrix ranged from 0.571 down to 0.133. The eigenvectors were used to calculate principal components. Thus 50 more or less correlated variables were transformed into 50 uncorrelated variables with the same total variance. The sequences were sorted according to the principal components to reveal which features were associated with the most variation amongst the sequences. When the covariances among the coded sequences were calculated many associations were found, for example, a purine at position 15 was associated with a purine at position 16, and a purine at position 19 with a G or C at position 20. Although these correlations individually were not especially strong, together they were a notable feature of the set of sequences. The consensus sequence was observed to be agggg ggggg ggc(g/c)c ggggg gcgcc. A principal components analysis enabled the promoters to be identified which differed most (in opposite directions) from the consensus sequence, taking account of the correlations. Nearly all the elements of the first eigenvector were of alternating sign; thus the first principal component separated promoters which were rich in G from those rich in T. Almost all elements of the second eigenvector were positive, so the second principal component distinguished promoters rich in A from those rich in C. There was a remarkable concentration of promoters from genes for interleukins or IL repressors with large values for the second principal component:- IL1A, IL2, IL4, IL6-2, IL2RA1, IL2RA2 and IL8RB were in positions 160, 43, 14, 158, 131, 101 and 158 (out of 1977) respectively. The variation in the sequence of promoters about their consensus sequence is seen not to be random but to display detectable patterns. Correlations were found to be frequent within the promoter sequences considered here; in the absence of correlations all the eigenvalues would have been equal. The major principal components separated promoters with markedly different sequences. It is to be expected that the other principal components would yield further separations.


Author(s):  
Bo Zhang ◽  
Long Zhang ◽  
Zhongfu Ye

AbstractA novel sky-subtraction method based on non-negative matrix factorisation with sparsity is proposed in this paper. The proposed non-negative matrix factorisation with sparsity method is redesigned for sky-subtraction considering the characteristics of the skylights. It has two constraint terms, one for sparsity and the other for homogeneity. Different from the standard sky-subtraction techniques, such as the B-spline curve fitting methods and the Principal Components Analysis approaches, sky-subtraction based on non-negative matrix factorisation with sparsity method has higher accuracy and flexibility. The non-negative matrix factorisation with sparsity method has research value for the sky-subtraction on multi-object fibre spectroscopic telescope surveys. To demonstrate the effectiveness and superiority of the proposed algorithm, experiments are performed on Large Sky Area Multi-Object Fiber Spectroscopic Telescope data, as the mechanisms of the multi-object fibre spectroscopic telescopes are similar.


2015 ◽  
Vol 66 (2) ◽  
pp. 177 ◽  
Author(s):  
Jane Ndungu ◽  
Denie C. M. Augustijn ◽  
Suzanne J. M. H. Hulscher ◽  
Bernard Fulanda ◽  
Nzula Kitaka ◽  
...  

Water quality information in aquatic ecosystems is crucial in setting up guidelines for resource management. This study explores the water quality status and pollution sources in Lake Naivasha, Kenya. Analysis of water quality parameters at seven sampling sites was carried out from water samples collected weekly from January to June and biweekly from July to November in 2011. Principal component analysis (PCA) and cluster analysis (CA) were used to analyse the dataset. Principal component analysis showed that four principal components (PCA-1 to PCA-4) explained 94.2% of the water quality variability. PCA-1 and PCA-2 bi-plot suggested that turbidity in the lake correlated directly to nutrients and iron with close association with the sampling site close to the mouth of Malewa River. Three distinct clusters were discerned from the CA analysis: Crescent Lake, a more or less isolated crater lake, the northern region of the lake, and the main lake. The pollution threat in Lake Naivasha includes agricultural and domestic sources. This study provides a valuable dataset on the current water quality status of Lake Naivasha, which is useful for formulating effective management strategies to safeguard ecosystem services and secure the livelihoods of the riparian communities around Lake Naivasha, Kenya.


1987 ◽  
Vol 24 (12) ◽  
pp. 2396-2404 ◽  
Author(s):  
Timothy D. Browning ◽  
Suzanne J. Beske-Diehl

The close association of hematite with native copper in the flow tops of the Portage Lake Volcanics invites the opportunity to establish the relative age of copper mineralization. For this purpose, we sampled 12 paleomagnetic sites representing six mineralized flow tops and their associated massive interiors on the Keweenaw Peninsula in Michigan. Three of the four less-altered flow interiors contained two components of magnetization: one was carried by primary magnetite, and therefore the other, carried by hematite, must be secondary. The hematite component was parallel to the single hematite component in the associated flow top, indicating that both components had a common secondary origin. The low between-site dispersion of the hematite component and the similarity of the mean direction to primary directions of other rocks of the same age (1100 Ma) suggest that hematization occurred over a period of time long enough to average out secular variation but before deposition of the overlying Nonesuch Shale, extensive tectonic tilting, and significant apparent polar wander. If copper mineralization and hematization were contemporaneous, then we have also dated the relative age of copper mineralization and the associated metamorphism. In contrast, paleomagnetic results from the two extensively altered flows (from below the Greenstone flow) are consistent with the mechanism of deuteric or auto-oxidation.


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