975 resultados para multivariate methods


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The aim of this paper is to describe the patterns of associations between fish species and their distribution in lotic habitats at basin level. Samples were accomplished in 27 localities of Iguatemi river basin, distributed in four environments (Iguatemi river, Jogui river, Puitã river and streams). The presence/absence data of those species which occurred in 2 or more sites were submitted at multivariate methods with the aim to describe the major species associations. The species distribution was considered determinative in these communities (C-score = 17,33; P = 0,000), with significant difference among the studied environments (ANOSIM r = 0,082; P = 0,012), with verified difference between Iguatemi river and streams (P = 0,001) and also streams and Jogui river (P = 0,014). We verified a strong segregation among species from headstreams and more discharge river stretches or even larger streams.

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The correlation between vegetation patterns (species distribution and richness) and altitudinal variation has been widely reported for tropical forests, thereby providing theoretical basis for biodiversity conservation. However, this relationship may have been oversimplified, as many other factors may influence vegetation patterns, such as disturbances, topography and geographic distance. Considering these other factors, our primary question was: is there a vegetation pattern associated with substantial altitudinal variation (10-1,093 m a.s.l.) in the Atlantic Rainforest-a top hotspot for biodiversity conservation-and, if so, what are the main factors driving this pattern? We addressed this question by sampling 11 1-ha plots, applying multivariate methods, correlations and variance partitioning. The Restinga (forest on sandbanks along the coastal plains of Brazil) and a lowland area that was selectively logged 40 years ago were floristically isolated from the other plots. The maximum species richness (>200 spp. per hectare) occurred at approximately 350 m a.s.l. (submontane forest). Gaps, multiple stemmed trees, average elevation and the standard deviation of the slope significantly affected the vegetation pattern. Spatial proximity also influenced the vegetation pattern as a structuring environmental variable or via dispersal constraints. Our results clarify, for the first time, the key variables that drive species distribution and richness across a large altitudinal range within the Atlantic Rainforest. © 2013 Springer Science+Business Media Dordrecht.

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The Agroindustrial System coffee after decades of state regulation has become a decentralized economic activity. This situation compelled most of the actors in the production chain to resort to self r egulatory systems offered by certification agencies, which have specific criteria and procedures. However the diversity criteria of the agencies do not offer resources able to ensure efficient management of the governance structure. There is a need to reduce the asymmetry of information, which is possible through the sharing of data compatible with the production tracking feature. This work is supported in this contextualized problem, based on Transaction Cost Theory and the use of qualitative and quantitative research methodologies. The first part of the work seeks to know the procedures required by leading regulatory agencies in Brazil, with perspective to emphasize the similarities and compatibilities between them, which was reached after analysis of standards and comparison of similarities. Next is registered the operation and the coffee traceability of the structure, in order to identify, through observation, documental and bibliographical analysis, the systems in place and traceable information in line with the recommendations of the coffee certification. Finally, he sought to create a labeling model that allows to generate and share information about the product from the field to the sale for consumption. The information obtained in the previous steps were the basis for data collection with the production chain agents through a structured questionnaire administered to 618 agents of the production chain, whose answers were treated by multivariate methods of statistical analysis. The results showed that actors in the chain are in favor of inclusion and sharing information related to rural production and economic and environmental data. This knowledge enabled develop a labeling model where the information sharing agents is an efficient mechanism to mitigate the governance problems identified.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Two experiments with 25 maize commercial hybrids were carried out in a direct sowing system in Southern Brazil in the harvests of 2009/2010 and 2010/2011. Quantitative descriptors were used with the objective of determining the genetic divergence and the relative contributions of traits among hybrids for extraction of inbred lines. This study was carried out in Oxisol soil using a randomized block design with four replicates. Data were subjected to combined analysis of variance, and based on the multivariate analyses, Tocher and average linkage (UPGMA) cluster analyses, based on generalized distance of Mahalanobis, to quantify divergence in addition to Singh criterion to validate trait with the most contribution. The multivariate methods were consistent with each other, and the weight of 100 grains was the trait that contributed most to the divergence and had similar behavior in grain yield between hybrids in both years. Furthermore, this descriptor representing significant genetic variability for crossings and lines extraction to hybridization between BM 3061, ATL 200 and P 30B39 Y.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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This thesis is focused on the metabolomic study of human cancer tissues by ex vivo High Resolution-Magic Angle Spinning (HR-MAS) nuclear magnetic resonance (NMR) spectroscopy. This new technique allows for the acquisition of spectra directly on intact tissues (biopsy or surgery), and it has become very important for integrated metabonomics studies. The objective is to identify metabolites that can be used as markers for the discrimination of the different types of cancer, for the grading, and for the assessment of the evolution of the tumour. Furthermore, an attempt to recognize metabolites, that although involved in the metabolism of tumoral tissues in low concentration, can be important modulators of neoplastic proliferation, was performed. In addition, NMR data was integrated with statistical techniques in order to obtain semi-quantitative information about the metabolite markers. In the case of gliomas, the NMR study was correlated with gene expression of neoplastic tissues. Chapter 1 begins with a general description of a new “omics” study, the metabolomics. The study of metabolism can contribute significantly to biomedical research and, ultimately, to clinical medical practice. This rapidly developing discipline involves the study of the metabolome: the total repertoire of small molecules present in cells, tissues, organs, and biological fluids. Metabolomic approaches are becoming increasingly popular in disease diagnosis and will play an important role on improving our understanding of cancer mechanism. Chapter 2 addresses in more detail the basis of NMR Spectroscopy, presenting the new HR-MAS NMR tool, that is gaining importance in the examination of tumour tissues, and in the assessment of tumour grade. Some advanced chemometric methods were used in an attempt to enhance the interpretation and quantitative information of the HR-MAS NMR data are and presented in chapter 3. Chemometric methods seem to have a high potential in the study of human diseases, as it permits the extraction of new and relevant information from spectroscopic data, allowing a better interpretation of the results. Chapter 4 reports results obtained from HR-MAS NMR analyses performed on different brain tumours: medulloblastoma, meningioms and gliomas. The medulloblastoma study is a case report of primitive neuroectodermal tumor (PNET) localised in the cerebellar region by Magnetic Resonance Imaging (MRI) in a 3-year-old child. In vivo single voxel 1H MRS shows high specificity in detecting the main metabolic alterations in the primitive cerebellar lesion; which consist of very high amounts of the choline-containing compounds and of very low levels of creatine derivatives and N-acetylaspartate. Ex vivo HR-MAS NMR, performed at 9.4 Tesla on the neoplastic specimen collected during surgery, allows the unambiguous identification of several metabolites giving a more in-depth evaluation of the metabolic pattern of the lesion. The ex vivo HR-MAS NMR spectra show higher detail than that obtained in vivo. In addition, the spectroscopic data appear to correlate with some morphological features of the medulloblastoma. The present study shows that ex vivo HR-MAS 1H NMR is able to strongly improve the clinical possibility of in vivo MRS and can be used in conjunction with in vivo spectroscopy for clinical purposes. Three histological subtypes of meningiomas (meningothelial, fibrous and oncocytic) were analysed both by in vivo and ex vivo MRS experiments. The ex vivo HR-MAS investigations are very helpful for the assignment of the in vivo resonances of human meningiomas and for the validation of the quantification procedure of in vivo MR spectra. By using one- and two dimensional experiments, several metabolites in different histological subtypes of meningiomas, were identified. The spectroscopic data confirmed the presence of the typical metabolites of these benign neoplasms and, at the same time, that meningomas with different morphological characteristics have different metabolic profiles, particularly regarding macromolecules and lipids. The profile of total choline metabolites (tCho) and the expression of the Kennedy pathway genes in biopsies of human gliomas were also investigated using HR-MAS NMR, and microfluidic genomic cards. 1H HR-MAS spectra, allowed the resolution and relative quantification by LCModel of the resonances from choline (Cho), phosphorylcholine (PC) and glycerolphorylcholine (GPC), the three main components of the combined tCho peak observed in gliomas by in vivo 1H MRS spectroscopy. All glioma biopsies depicted an increase in tCho as calculated from the addition of Cho, PC and GPC HR-MAS resonances. However, the increase was constantly derived from augmented GPC in low grade NMR gliomas or increased PC content in the high grade gliomas, respectively. This circumstance allowed the unambiguous discrimination of high and low grade gliomas by 1H HR-MAS, which could not be achieved by calculating the tCho/Cr ratio commonly used by in vivo 1H MR spectroscopy. The expression of the genes involved in choline metabolism was investigated in the same biopsies. The present findings offer a convenient procedure to classify accurately glioma grade using 1H HR-MAS, providing in addition the genetic background for the alterations of choline metabolism observed in high and low gliomas grade. Chapter 5 reports the study on human gastrointestinal tract (stomach and colon) neoplasms. The human healthy gastric mucosa, and the characteristics of the biochemical profile of human gastric adenocarcinoma in comparison with that of healthy gastric mucosa were analyzed using ex vivo HR-MAS NMR. Healthy human mucosa is mainly characterized by the presence of small metabolites (more than 50 identified) and macromolecules. The adenocarcinoma spectra were dominated by the presence of signals due to triglycerides, that are usually very low in healthy gastric mucosa. The use of spin-echo experiments enable us to detect some metabolites in the unhealthy tissues and to determine their variation with respect to the healthy ones. Then, the ex vivo HR-MAS NMR analysis was applied to human gastric tissue, to obtain information on the molecular steps involved in the gastric carcinogenesis. A microscopic investigation was also carried out in order to identify and locate the lipids in the cellular and extra-cellular environments. Correlation of the morphological changes detected by transmission (TEM) and scanning (SEM) electron microscopy, with the metabolic profile of gastric mucosa in healthy, gastric atrophy autoimmune diseases (AAG), Helicobacter pylori-related gastritis and adenocarcinoma subjects, were obtained. These ultrastructural studies of AAG and gastric adenocarcinoma revealed lipid intra- and extra-cellularly accumulation associated with a severe prenecrotic hypoxia and mitochondrial degeneration. A deep insight into the metabolic profile of human healthy and neoplastic colon tissues was gained using ex vivo HR-MAS NMR spectroscopy in combination with multivariate methods: Principal Component Analysis (PCA) and Partial Least Squares Discriminant Analysis (PLS-DA). The NMR spectra of healthy tissues highlight different metabolic profiles with respect to those of neoplastic and microscopically normal colon specimens (these last obtained at least 15 cm far from the adenocarcinoma). Furthermore, metabolic variations are detected not only for neoplastic tissues with different histological diagnosis, but also for those classified identical by histological analysis. These findings suggest that the same subclass of colon carcinoma is characterized, at a certain degree, by metabolic heterogeneity. The statistical multivariate approach applied to the NMR data is crucial in order to find metabolic markers of the neoplastic state of colon tissues, and to correctly classify the samples. Significant different levels of choline containing compounds, taurine and myoinositol, were observed. Chapter 6 deals with the metabolic profile of normal and tumoral renal human tissues obtained by ex vivo HR-MAS NMR. The spectra of human normal cortex and medulla show the presence of differently distributed osmolytes as markers of physiological renal condition. The marked decrease or disappearance of these metabolites and the high lipid content (triglycerides and cholesteryl esters) is typical of clear cell renal carcinoma (RCC), while papillary RCC is characterized by the absence of lipids and very high amounts of taurine. This research is a contribution to the biochemical classification of renal neoplastic pathologies, especially for RCCs, which can be evaluated by in vivo MRS for clinical purposes. Moreover, these data help to gain a better knowledge of the molecular processes envolved in the onset of renal carcinogenesis.

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It has been suggested that there are several distinct phenotypes of childhood asthma or childhood wheezing. Here, we review the research relating to these phenotypes, with a focus on the methods used to define and validate them. Childhood wheezing disorders manifest themselves in a range of observable (phenotypic) features such as lung function, bronchial responsiveness, atopy and a highly variable time course (prognosis). The underlying causes are not sufficiently understood to define disease entities based on aetiology. Nevertheless, there is a need for a classification that would (i) facilitate research into aetiology and pathophysiology, (ii) allow targeted treatment and preventive measures and (iii) improve the prediction of long-term outcome. Classical attempts to define phenotypes have been one-dimensional, relying on few or single features such as triggers (exclusive viral wheeze vs. multiple trigger wheeze) or time course (early transient wheeze, persistent and late onset wheeze). These definitions are simple but essentially subjective. Recently, a multi-dimensional approach has been adopted. This approach is based on a wide range of features and relies on multivariate methods such as cluster or latent class analysis. Phenotypes identified in this manner are more complex but arguably more objective. Although phenotypes have an undisputed standing in current research on childhood asthma and wheezing, there is confusion about the meaning of the term 'phenotype' causing much circular debate. If phenotypes are meant to represent 'real' underlying disease entities rather than superficial features, there is a need for validation and harmonization of definitions. The multi-dimensional approach allows validation by replication across different populations and may contribute to a more reliable classification of childhood wheezing disorders and to improved precision of research relying on phenotype recognition, particularly in genetics. Ultimately, the underlying pathophysiology and aetiology will need to be understood to properly characterize the diseases causing recurrent wheeze in children.

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Multivariate Methoden stellen ein wesentliches Instrumentarium zur Datenanalyse in der Ökologie dar. Sie werden in der Ökologie häufig eingesetzt und sind seit langem Gegenstand der Lehre in der Abteilung Geobotanik der Universität Freiburg. In den letzten Jahren wurde als Werkzeug das Programm R eingeführt. R ist ein frei verfügbares, kommandozeilenorientiertes Statistikprogramm, das für eine Reihe von Betriebssystemen angeboten wird (R-Development Core-Team 2007). Das Programm befindet sich in rascher Entwicklung (derzeit Version 2.10) und wird zunehmend auch von Ökologen eingesetzt. Bislang existiert kein deutschsprachiges Lehrbuch zur Anwendung multivariater Methoden mit R. Mit MultiStaR wird versucht, diese Lücke zu schließen und den Studierenden Lernmaterialien an die Hand zu geben, die Übungen mit dem eigentlichen Analysewerkzeug mit einschließen.

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Energy efficiency has become an important research topic in intralogistics. Especially in this field the focus is placed on automated storage and retrieval systems (AS/RS) utilizing stacker cranes as these systems are widespread and consume a significant portion of the total energy demand of intralogistical systems. Numerical simulation models were developed to calculate the energy demand rather precisely for discrete single and dual command cycles. Unfortunately these simulation models are not suitable to perform fast calculations to determine a mean energy demand value of a complete storage aisle. For this purpose analytical approaches would be more convenient but until now analytical approaches only deliver results for certain configurations. In particular, for commonly used stacker cranes equipped with an intermediate circuit connection within their drive configuration there is no analytical approach available to calculate the mean energy demand. This article should address this research gap and present a calculation approach which enables planners to quickly calculate the energy demand of these systems.

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Several tests for the comparison of different groups in the randomized complete block design exist. However, there is a lack of robust estimators for the location difference between one group and all the others on the original scale. The relative marginal effects are commonly used in this situation, but they are more difficult to interpret and use by less experienced people because of the different scale. In this paper two nonparametric estimators for the comparison of one group against the others in the randomized complete block design will be presented. Theoretical results such as asymptotic normality, consistency, translation invariance, scale preservation, unbiasedness, and median unbiasedness are derived. The finite sample behavior of these estimators is derived by simulations of different scenarios. In addition, possible confidence intervals with these estimators are discussed and their behavior derived also by simulations.