941 resultados para Multivariate Statistics


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Concentrations of Fe, Mn, Co, Cr, Zn and Cu were determinated using flame atomic absorption spectrometry in nine lichen species of the Sul-Mato-Grossense cerrado. The average metal ion concentrations varied in the following ranges: Fe, 248.41-1568.01; Mn, 98.50-397.33; Co, 10.08-24.81; Cr, 18.24-44.26; Zn, 14.62-34.79 and Cu, 3.23-7.57 mg kg-1. Statistical analysis (Pearson and Cluster) applied to the metal ion concentrations indicated that the accumulation of these ions can be due to several anthropogenic sources including agricultural activities, mineral exploration, biomass burning, soil mineral composition and leather tanning processes by chromium.

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The spread of Brasília isn't accompanied by correct support of land occupation, situation that is reflected in water quality. Under the optics of land use and occupation, working with multivariate statistics as main tool, water physical and chemical quality of Gama Catchment were assessed. During two years samples were collected and analyzed for 24 parameters. The statistical analysis showed the influence of civil buildings, agricultural activities and the best statistical parameters to a quickly assessment: nitrate, ammonia, suspended solids and aluminium.

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This study examines the efficiency of search engine advertising strategies employed by firms. The research setting is the online retailing industry, which is characterized by extensive use of Web technologies and high competition for market share and profitability. For Internet retailers, search engines are increasingly serving as an information gateway for many decision-making tasks. In particular, Search engine advertising (SEA) has opened a new marketing channel for retailers to attract new customers and improve their performance. In addition to natural (organic) search marketing strategies, search engine advertisers compete for top advertisement slots provided by search brokers such as Google and Yahoo! through keyword auctions. The rationale being that greater visibility on a search engine during a keyword search will capture customers' interest in a business and its product or service offerings. Search engines account for most online activities today. Compared with the slow growth of traditional marketing channels, online search volumes continue to grow at a steady rate. According to the Search Engine Marketing Professional Organization, spending on search engine marketing by North American firms in 2008 was estimated at $13.5 billion. Despite the significant role SEA plays in Web retailing, scholarly research on the topic is limited. Prior studies in SEA have focused on search engine auction mechanism design. In contrast, research on the business value of SEA has been limited by the lack of empirical data on search advertising practices. Recent advances in search and retail technologies have created datarich environments that enable new research opportunities at the interface of marketing and information technology. This research uses extensive data from Web retailing and Google-based search advertising and evaluates Web retailers' use of resources, search advertising techniques, and other relevant factors that contribute to business performance across different metrics. The methods used include Data Envelopment Analysis (DEA), data mining, and multivariate statistics. This research contributes to empirical research by analyzing several Web retail firms in different industry sectors and product categories. One of the key findings is that the dynamics of sponsored search advertising vary between multi-channel and Web-only retailers. While the key performance metrics for multi-channel retailers include measures such as online sales, conversion rate (CR), c1ick-through-rate (CTR), and impressions, the key performance metrics for Web-only retailers focus on organic and sponsored ad ranks. These results provide a useful contribution to our organizational level understanding of search engine advertising strategies, both for multi-channel and Web-only retailers. These results also contribute to current knowledge in technology-driven marketing strategies and provide managers with a better understanding of sponsored search advertising and its impact on various performance metrics in Web retailing.

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This thesis entitled “Studies on Nitrifying Microorganisms in Cochin Estuary and Adjacent Coastal Waters” reports for the first time the spatial andtemporal variations in the abundance and activity of nitrifiers (Ammonia oxidizingbacteria-AOB; Nitrite oxidizing bacteria- NOB and Ammonia oxidizing archaea-AOA) from the Cochin Estuary (CE), a monsoon driven, nutrient rich tropicalestuary along the southwest coast of India. To fulfil the above objectives, field observations were carried out for aperiod of one year (2011) in the CE. Surface (1 m below surface) and near-bottomwater samples were collected from four locations (stations 1 to 3 in estuary and 4 in coastal region), covering pre-monsoon, monsoon and post-monsoon seasons. Station 1 is a low saline station (salinity range 0-10) with high freshwater influx While stations 2 and 3 are intermediately saline stations (salinity ranges 10-25). Station 4 is located ~20 km away from station 3 with least influence of fresh water and is considered as high saline (salinity range 25- 35) station. Ambient physicochemical parameters like temperature, pH, salinity, dissolved oxygen (DO), Ammonium, nitrite, nitrate, phosphate and silicate of surface and bottom waters were measured using standard techniques. Abundance of Eubacteria, total Archaea and ammonia and nitrite oxidizing bacteria (AOB and NOB) were quantified using Fluorescent in situ Hybridization (FISH) with oligonucleotide probes labeled withCy3. Community structure of AOB and AOA was studied using PCR Denaturing Gradient Gel Electrophoresis (DGGE) technique. PCR products were cloned and sequenced to determine approximate phylogenetic affiliations. Nitrification rate in the water samples were analyzed using chemical NaClO3 (inhibitor of nitrite oxidation), and ATU (inhibitor of ammonium oxidation). Contribution of AOA and AOB in ammonia oxidation process was measured based on the recovered ammonia oxidation rate. The contribution of AOB and AOA were analyzed after inhibiting the activities of AOB and AOA separately using specific protein inhibitors. To understand the factors influencing or controlling nitrification, various statistical tools were used viz. Karl Pearson’s correlation (to find out the relationship between environmental parameters, bacterial abundance and activity), three-way ANOVA (to find out the significant variation between observations), Canonical Discriminant Analysis (CDA) (for the discrimination of stations based on observations), Multivariate statistics, Principal components analysis (PCA) and Step up multiple regression model (SMRM) (First order interaction effects were applied to determine the significantly contributing biological and environmental parameters to the numerical abundance of nitrifiers). In the CE, nitrification is modulated by the complex interplay between different nitrifiers and environmental variables which in turn is dictated by various hydrodynamic characteristics like fresh water discharge and seawater influx brought in by river water discharge and flushing. AOB in the CE are more adapted to varying environmental conditions compared to AOA though the diversity of AOA is higher than AOB. The abundance and seasonality of AOB and NOB is influenced by the concentration of ammonia in the water column. AOB are the major players in modulating ammonia oxidation process in the water column of CE. The distribution pattern and seasonality of AOB and NOB in the CE suggest that these organisms coexist, and are responsible for modulating the entire nitrification process in the estuary. This process is fuelled by the cross feeding among different nitrifiers, which in turn is dictated by nutrient levels especially ammonia. Though nitrification modulates the increasing anthropogenic ammonia concentration the anthropogenic inputs have to be controlled to prevent eutrophication and associated environmental changes.

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Planners in public and private institutions would like coherent forecasts of the components of age-specic mortality, such as causes of death. This has been di cult to achieve because the relative values of the forecast components often fail to behave in a way that is coherent with historical experience. In addition, when the group forecasts are combined the result is often incompatible with an all-groups forecast. It has been shown that cause-specic mortality forecasts are pessimistic when compared with all-cause forecasts (Wilmoth, 1995). This paper abandons the conventional approach of using log mortality rates and forecasts the density of deaths in the life table. Since these values obey a unit sum constraint for both conventional single-decrement life tables (only one absorbing state) and multiple-decrement tables (more than one absorbing state), they are intrinsically relative rather than absolute values across decrements as well as ages. Using the methods of Compositional Data Analysis pioneered by Aitchison (1986), death densities are transformed into the real space so that the full range of multivariate statistics can be applied, then back-transformed to positive values so that the unit sum constraint is honoured. The structure of the best-known, single-decrement mortality-rate forecasting model, devised by Lee and Carter (1992), is expressed in compositional form and the results from the two models are compared. The compositional model is extended to a multiple-decrement form and used to forecast mortality by cause of death for Japan

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Theory of compositional data analysis is often focused on the composition only. However in practical applications we often treat a composition together with covariables with some other scale. This contribution systematically gathers and develop statistical tools for this situation. For instance, for the graphical display of the dependence of a composition with a categorical variable, a colored set of ternary diagrams might be a good idea for a first look at the data, but it will fast hide important aspects if the composition has many parts, or it takes extreme values. On the other hand colored scatterplots of ilr components could not be very instructive for the analyst, if the conventional, black-box ilr is used. Thinking on terms of the Euclidean structure of the simplex, we suggest to set up appropriate projections, which on one side show the compositional geometry and on the other side are still comprehensible by a non-expert analyst, readable for all locations and scales of the data. This is e.g. done by defining special balance displays with carefully- selected axes. Following this idea, we need to systematically ask how to display, explore, describe, and test the relation to complementary or explanatory data of categorical, real, ratio or again compositional scales. This contribution shows that it is sufficient to use some basic concepts and very few advanced tools from multivariate statistics (principal covariances, multivariate linear models, trellis or parallel plots, etc.) to build appropriate procedures for all these combinations of scales. This has some fundamental implications in their software implementation, and how might they be taught to analysts not already experts in multivariate analysis

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The spatial and temporal dynamics in the stream water NO3-N concentrations in a major European river-system, the Garonne (62,700 km(2)), are described and related to variations in climate, land management, and effluent point-sources using multivariate statistics. Building on this, the Hydrologiska Byrans Vattenbalansavdelning (HBV) rainfall-runoff model and the Integrated Catchment Model of Nitrogen (INCA-N) are applied to simulate the observed flow and N dynamics. This is done to help us to understand which factors and processes control the flow and N dynamics in different climate zones and to assess the relative inputs from diffuse and point sources across the catchment. This is the first application of the linked HBV and INCA-N models to a major European river system commensurate with the largest basins to be managed tinder the Water Framework Directive. The simulations suggest that in the lowlands, seasonal patterns in the stream water NO3-N concentrations emerge and are dominated by diffuse agricultural inputs, with an estimated 75% of the river load in the lowlands derived from arable farming. The results confirm earlier European catchment studies. Namely, current semi-distrubuted catchment-scale dynamic models, which integrate variations in land cover, climate, and a simple representation of the terrestrial and in-stream N cycle, are able to simulate seasonal NO3-N patterns at large spatial (> 300 km(2)) and temporal (>= monthly) scales using available national datasets.

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The spatial and temporal dynamics in the stream water NO3-N concentrations in a major European river-system, the Garonne (62,700 km(2)), are described and related to variations in climate, land management, and effluent point-sources using multivariate statistics. Building on this, the Hydrologiska Byrans Vattenbalansavdelning (HBV) rainfall-runoff model and the Integrated Catchment Model of Nitrogen (INCA-N) are applied to simulate the observed flow and N dynamics. This is done to help us to understand which factors and processes control the flow and N dynamics in different climate zones and to assess the relative inputs from diffuse and point sources across the catchment. This is the first application of the linked HBV and INCA-N models to a major European river system commensurate with the largest basins to be managed tinder the Water Framework Directive. The simulations suggest that in the lowlands, seasonal patterns in the stream water NO3-N concentrations emerge and are dominated by diffuse agricultural inputs, with an estimated 75% of the river load in the lowlands derived from arable farming. The results confirm earlier European catchment studies. Namely, current semi-distrubuted catchment-scale dynamic models, which integrate variations in land cover, climate, and a simple representation of the terrestrial and in-stream N cycle, are able to simulate seasonal NO3-N patterns at large spatial (> 300 km(2)) and temporal (>= monthly) scales using available national datasets.

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The rheological properties of fresh gluten in small amplitude oscillation in shear (SAOS) and creep recovery after short application of stress was related to the hearth breadbaking performance of wheat flours using the multivariate statistics partial least squares (PLS) regression. The picture was completed by dough mixing and extensional properties, flour protein size distribution determined by SE-HPLC, and high molecular weight glutenin subunit (HMW-GS) composition. The sample set comprised 20 wheat cultivars grown at two different levels of nitrogen fertilizer in one location. Flours yielding stiffer and more elastic glutens, with higher elastic and viscous moduli (G' and G") and lower tan 8 values in SAOS, gave doughs that were better able to retain their shape during proving and baking, resulting in breads of high form ratios. Creep recovery measurements after short application of stress showed that glutens from flours of good breadmaking quality had high relative elastic recovery. The nitrogen fertilizer level affected the protein size distribution by an increase in monomeric proteins (gliadins), which gave glutens of higher tan delta and flatter bread loaves (lower form ratio).

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The time-course of metabolic events following response to a model hepatotoxin ethionine (800 mg/kg) was investigated over a 7 day period in rats using high-resolution (1)H NMR spectroscopic analysis of urine and multivariate statistics. Complementary information was obtained by multivariate analysis of (1)H MAS NMR spectra of intact liver and by conventional histopathology and clinical chemistry of blood plasma. (1)H MAS NMR spectra of liver showed toxin-induced lipidosis 24 h postdose consistent with the steatosis observed by histopathology, while hypertaurinuria was suggestive of liver injury. Early biochemical changes in urine included elevation of guanidinoacetate, suggesting impaired methylation reactions. Urinary increases in 5-oxoproline and glycine suggested disruption of the gamma-glutamyl cycle. Signs of ATP depletion together with impairment of the energy metabolism were given from the decreased levels in tricarboxylic acid cycle intermediates, the appearance of ketone bodies in urine, the depletion of hepatic glucose and glycogen, and also hypoglycemia. The observed increase in nicotinuric acid in urine could be an indication of an increase in NAD catabolism, a possible consequence of ATP depletion. Effects on the gut microbiota were suggested by the observed urinary reductions in the microbial metabolites 3-/4-hydroxyphenyl propionic acid, dimethylamine, and tryptamine. At later stages of toxicity, there was evidence of kidney damage, as indicated by the tubular damage observed by histopathology, supported by increased urinary excretion of lactic acid, amino acids, and glucose. These studies have given new insights into mechanisms of ethionine-induced toxicity and show the value of multisystem level data integration in the understanding of experimental models of toxicity or disease.

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To predict the response of aquatic ecosystems to future global climate change, data on the ecology and distribution of keystone groups in freshwater ecosystems are needed. In contrast to mid- and high-latitude zones, such data are scarce across tropical South America (Neotropics). We present the distribution and diversity of chironomid species using surface sediments of 59 lakes from the Andes to the Amazon (0.1–17°S and 64–78°W) within the Neotropics. We assess the spatial variation in community assemblages and identify the key variables influencing the distributional patterns. The relationships between environmental variables (pH, conductivity, depth, and sediment organic content), climatic data, and chironomid assemblages were assessed using multivariate statistics (detrended correspondence analysis and canonical correspondence analysis). Climatic parameters (temperature and precipitation) were most significant in describing the variance in chironomid assemblages. Temperature and precipitation are both predicted to change under future climate change scenarios in the tropical Andes. Our findings suggest taxa of Orthocladiinae, which show a preference to cold high-elevation oligotrophic lakes, will likely see range contraction under future anthropogenic-induced climate change. Taxa abundant in areas of high precipitation, such as Micropsectra and Phaenopsectra, will likely become restricted to the inner tropical Andes, as the outer tropical Andes become drier. The sensitivity of chironomids to climate parameters makes them important bio-indicators of regional climate change in the Neotropics. Furthermore, the distribution of chironomid taxa presented here is a vital first step toward providing urgently needed autecological data for interpreting fossil chironomid records of past ecological and climate change from the tropical Andes.

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A Análise Financeira dos Índices tem sido usada largamente, desde o fim do século passado na avaliação das demonstrações financeiras; no entanto, encontrou-se desacreditada por volta dos anos 60. Assim, por essa época, Beaver; baseando-se na literatura existente, testa empiricamente muitas crenças tidas como verdadeiras e chega a resultados diferentes. Para isso, utilizou-se de metodologia estatística univariada, isto é, analisou cada índice isoladamente. Altman refuta a metodologia usada por Beaver e cria um modelo utilizando se da estatística multivariada, isto é, vários Índices são estudados, estabelecendo um score limite. Outros autores, baseando-se nestes dois estudos, ora criticando, ora comparando, montam outros modelos. Assim temos: Deakin, Blum, Libby, Kennedy, Kanitz, Zappa, Collongues, Conan, Holder, C.E.S.A. e outros que não foram mencionados neste trabalho. Este estudo mostrou o trabalho de cada autor individualmente e, num segundo momento, apresentou críticas e comparações sofridas por esses modelos, procurando evidenciar que essas críticas e comparações serviram para estimular o desenvolvimento da Análise Financeira, a tal ponto que pode-se citar Altman que, devido a críticas e também ao seu interesse em atualizar os dados, reformula o seu modelo original (1968), criando o modelo Zeta (1977). A segunda preocupação deste trabalho foi evidenciar alguns pontos que puderam ser colhidos do material disponível. Assim, procurou-se responder quais os Índices que mais foram usados pelos modelos e, como conclusão, chegou-se a evidência de que não existem alguns poucos índices que melhor discriminem uma empresa falida e não falida. Outra indagação foi, se esses modelos serviriam para todos os tipos e tamanhos de empresas, e concluiu-se que servem, desde que o analista os adapte às suas necessidades peculiares. E, por fim, procurou-se verificar a que finalidade esses modelos podiam corresponder. E, assim, apontou-se a análise de crédito comercial, para investimento, para decisões internas, para compra e venda de ações etc. Conclui-se, pois, que os vários modelos desenvolvidos nestes últimos anos, realmente trouxeram progresso à Análise Financeira, mas que esses resultados devem ser cuidadosa mente adaptados às diversas realidades e mais, dado ao desenvolvimento de outras ciências, podem somar-se esforços com intuito de alcançar um maior desenvolvimento.

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A sensitive assay to identify volatile organic metabolites (VOMs) as biomarkers that can accurately diagnose the onset of breast cancer using non-invasively collected clinical specimens is ideal for early detection. Therefore the aim of this study was to establish the urinary metabolomic profile of breast cancer patients and healthy individuals (control group) and to explore the VOMs as potential biomarkers in breast cancer diagnosis at early stage. Solid-phase microextraction (SPME) using CAR/PDMS sorbent combined with gas chromatography–mass spectrometry was applied to obtain metabolomic information patterns of 26 breast cancer patients and 21 healthy individuals (controls). A total of seventy-nine VOMs, belonging to distinct chemical classes, were detected and identified in control and breast cancer groups. Ketones and sulfur compounds were the chemical classes with highest contribution for both groups. Results showed that excretion values of 6 VOMs among the total of 79 detected were found to be statistically different (p < 0.05). A significant increase in the peak area of (−)-4-carene, 3-heptanone, 1,2,4-trimethylbenzene, 2-methoxythiophene and phenol, in VOMs of cancer patients relatively to controls was observed. Statiscally significant lower abundances of dimethyl disulfide were found in cancer patients. Bioanalytical data were submitted to multivariate statistics [principal component analysis (PCA)], in order to visualize clusters of cases and to detect the VOMs that are able to differentiate cancer patients from healthy individuals. Very good discrimination within breast cancer and control groups was achieved. Nevertheless, a deep study using a larger number of patients must be carried out to confirm the results.

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The current study presents the characteristics of self-efficacy of students of Administration course, who work and do not work. The study was conducted through a field research, descriptive, addressed quantitatively using statistical procedures. Was studied a population composed of 394 students distributed in three Higher Education Institutions, in the metropolitan region of Belém, in the State of Pará. The sampling was not probabilistic by accessibility, with a sample of 254 subjects. The instrument for data collection was a questionnaire composed of a set of questions divided into three sections: the first related to sociodemographic data, the second section was built to identify the work situation of the respondent and the third section was built with issues related to General Perceived Self-Efficacy Scale proposed by Schwarzer and Jerusalem (1999). Sociodemographic data were processed using methods of descriptive statistics. This procedure allowed characterizing the subjects of the sample. To identify the work situation, the analysis of frequency and percentage was used, which allowed to classify in percentage, the respondents who worked and those that did not work, and the data related to the scale of self-efficacy were processed quantitatively by the method of multivariate statistics using the software of program Statistical Package for Social Sciences for Windows - SPSS, version 17 from the process of Exploratory Factor Analysis. This procedure allowed characterizing the students who worked and the students who did not worked. The results were discussed based on Social Cognitive Theory from the construct of self-efficacy of Albert Bandura (1977). The study results showed a young sample, composed the majority of single women with work experience, and indicated that the characteristics of self-efficacy of students who work and students who do not work are different. The self-efficacy beliefs of students who do not work are based on psychological expectations, whereas the students who work demonstrated that their efficacy beliefs are sustained by previous experiences. A student who does not work proved to be reliant in their abilities to achieve a successful performance in their activities, believing it to be easy to achieve your goals and to face difficult situations at work, simply by invest a necessary effort and trust in their abilities. One who has experience working proved to be reliant in their abilities to conduct courses of action, although know that it is not easy to achieve your goals, and in unexpected situations showed its ability to solve difficult problems

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O objetivo deste estudo foi avaliar a possibilidade de agrupar talhões de cana-de-açúcar colhida mecanicamente e sem queima prévia da palha na região de Ribeirão Preto-SP, de acordo com o potencial de infestação de plantas daninhas, por meio de análise de agrupamento por método hierárquico e outras técnicas de análise multivariada, utilizando como variável o índice de infestação relativa atribuído por avaliações visuais, em duas etapas. A primeira contemplou 20 talhões de cana-planta com ciclo de 18 meses; essas áreas foram utilizadas para comparação de dois métodos de estimativa da composição específica da flora daninha: análise fitossociológica e por meio da porcentagem visual de cobertura geral (CG) e específica (CE). A segunda etapa consistiu no levantamento da composição específica da comunidade de plantas daninhas em 189 talhões, em áreas de cana-soca colhidas durante a safra de 2008, incluindo nesses talhões apenas CG e CE. Com as informações sobre os levantamentos da comunidade infestante foi construído um banco de dados, posteriormente submetido a análises exploratórias por técnicas de estatística multivariada. Para as principais espécies dentro dos talhões, que foram DIGNU, ARACH, IPOHF, MRRCI e IPOQU, seguidas de CYPRO, ELEIN e EPHHS, foram verificados 75% de coincidências de resultados entre os dois métodos de avaliação. Também notou-se que as avaliações visuais de porcentagem de cobertura das espécies podem substituir, para fins de praticidade, agilidade e aplicabilidade, as avaliações fitossociológicas, uma vez que proporcionaram boa capacidade de detecção das principais plantas daninhas dentro de cada talhão. As técnicas de estatística multivariada demonstraram que os talhões podem ser agrupados de acordo com semelhanças na intensidade da infestação e na composição específica.