921 resultados para two-dimensional principal component analysis (2DPCA)


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PURPOSE: In view of reports in the literature on the benefits achieved with the use of platform switching, described as the use of an implant with a larger diameter than the abutment diameter, the goal being to prevent the (previously) normal bone loss down to the first thread that occurs around most implants, thus enhancing soft tissue aesthetics and stability and the need for implant inclination due to bone anatomy in some cases, the aim of this study was to evaluate bone stress distribution on peri-implant bone, by using three-dimensional finite element analysis to simulate the influence of implants with different abutment angulations (0 and 15 degrees) in platform switching. METHODS: Four mathematical models of an implant-supported central incisor were created with varying abutment angulations: straight abutment (S1 and S2) and angulated abutment at 15 degrees (A1 and A2), submitted to 2 loading conditions (100 N): S1 and A1-oblique loading (45 degrees) and S2 and A2-axial loading, parallel to the long axis of the implant. Maximum (σmax) and minimum (σmin) principal stress values were obtained for cortical and trabecular bone. RESULTS: Models S1 and A1 showed higher σmax in cortical and trabecular bone when compared with S2 and A2. The highest σmax values (in MPa) in the cortical bone were found in S1 (28.5), followed by A1 (25.7), S2 (11.6), and A2 (5.15). For the trabecular bone, the highest σmax values were found in S1 (7.53), followed by A1 (2.87), S2 (2.85), and A2 (1.47). CONCLUSIONS: Implants with straight abutments generated the highest stress values in bone. In addition, this effect was potentiated when the load was applied obliquely.

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Melipona scutellaris Latreille has great economic and ecological importance, especially because it is a pollinator of native plant species. Despite the importance of this species, there is little information about the conservation status of their populations. The objective of this study was to assess the diversity in populations of M. scutellaris coming from a Semideciduous Forest Fragment and an Atlantic Forest Fragment in the Northeast Brazil, through geometric morphometric analysis of wings in worker bees. In each area, worker bees were collected from 10 colonies, 10 workers per colony. To assess the diversity on the right wings of worker bees, 15 landmarks were plotted and the measures were used in analysis of variance and multivariate analysis, principal component analysis, discriminant analysis and clustering analysis. There were significant differences in the shape of the wing venation patterns between colonies of two sites (Wilk's lambda = 0.000006; p < 0.000001), which is probably due to the geographical distance between places of origin which impedes the gene flow between them. It indicates that inter and intrapopulation morphometric variability exists (p < 0.000001) in M. scutellaris coming from two different biomes, revealing the existence of diversity in these populations, which is necessary for the conservation of this bee species.

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The combination of solid-phase microextraction (SPME) with comprehensive two-dimensional gas chromatography is evaluated here for fatty acid (FA) profiling of the glycerophospholipid fraction from human buccal mucosal cells. A base-catalyzed derivatization reaction selective for polar lipids such as glycerophospholipid was adopted. SPME is compared to a miniaturized liquidliquid extraction procedure for the isolation of FA methyl esters produced in the derivatization step. The limits of detection and limits of quantitation were calculated for each sample preparation method. Because of its lower values of limits of detection and quantitation, SPME was adopted. The extracted analytes were separated, detected, and quantified by comprehensive two-dimensional gas chromatography with flame ionization detection (FID). The combination of SPME and comprehensive two-dimensional gas chromatography with FID, using a selective derivatization reaction in the preliminary steps, proved to be a simple and fast procedure for FA profiling, and was successfully applied to the analysis of adult human buccal mucosal cells.

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We report a morphology-based approach for the automatic identification of outlier neurons, as well as its application to the NeuroMorpho.org database, with more than 5,000 neurons. Each neuron in a given analysis is represented by a feature vector composed of 20 measurements, which are then projected into a two-dimensional space by applying principal component analysis. Bivariate kernel density estimation is then used to obtain the probability distribution for the group of cells, so that the cells with highest probabilities are understood as archetypes while those with the smallest probabilities are classified as outliers. The potential of the methodology is illustrated in several cases involving uniform cell types as well as cell types for specific animal species. The results provide insights regarding the distribution of cells, yielding single and multi-variate clusters, and they suggest that outlier cells tend to be more planar and tortuous. The proposed methodology can be used in several situations involving one or more categories of cells, as well as for detection of new categories and possible artifacts.

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We have performed multicanonical simulations to study the critical behavior of the two-dimensional Ising model with dipole interactions. This study concerns the thermodynamic phase transitions in the range of the interaction delta where the phase characterized by striped configurations of width h = 1 is observed. Controversial results obtained from local update algorithms have been reported for this region, including the claimed existence of a second-order phase transition line that becomes first order above a tricritical point located somewhere between delta = 0.85 and 1. Our analysis relies on the complex partition function zeros obtained with high statistics from multicanonical simulations. Finite size scaling relations for the leading partition function zeros yield critical exponents. that are clearly consistent with a single second-order phase transition line, thus excluding such a tricritical point in that region of the phase diagram. This conclusion is further supported by analysis of the specific heat and susceptibility of the orientational order parameter.

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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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Coastal sand dunes represent a richness first of all in terms of defense from the sea storms waves and the saltwater ingression; moreover these morphological elements constitute an unique ecosystem of transition between the sea and the land environment. The research about dune system is a strong part of the coastal sciences, since the last century. Nowadays this branch have assumed even more importance for two reasons: on one side the born of brand new technologies, especially related to the Remote Sensing, have increased the researcher possibilities; on the other side the intense urbanization of these days have strongly limited the dune possibilities of development and fragmented what was remaining from the last century. This is particularly true in the Ravenna area, where the industrialization united to the touristic economy and an intense subsidence, have left only few dune ridges residual still active. In this work three different foredune ridges, along the Ravenna coast, have been studied with Laser Scanner technology. This research didn’t limit to analyze volume or spatial difference, but try also to find new ways and new features to monitor this environment. Moreover the author planned a series of test to validate data from Terrestrial Laser Scanner (TLS), with the additional aim of finalize a methodology to test 3D survey accuracy. Data acquired by TLS were then applied on one hand to test some brand new applications, such as Digital Shore Line Analysis System (DSAS) and Computational Fluid Dynamics (CFD), to prove their efficacy in this field; on the other hand the author used TLS data to find any correlation with meteorological indexes (Forcing Factors), linked to sea and wind (Fryberger's method) applying statistical tools, such as the Principal Component Analysis (PCA).

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The Default Mode Network (DMN) is a higher order functional neural network that displays activation during passive rest and deactivation during many types of cognitive tasks. Accordingly, the DMN is viewed to represent the neural correlate of internally-generated self-referential cognition. This hypothesis implies that the DMN requires the involvement of cognitive processes, like declarative memory. The present study thus examines the spatial and functional convergence of the DMN and the semantic memory system. Using an active block-design functional Magnetic Resonance Imaging (fMRI) paradigm and Independent Component Analysis (ICA), we trace the DMN and fMRI signal changes evoked by semantic, phonological and perceptual decision tasks upon visually-presented words. Our findings show less deactivation during semantic compared to the two non-semantic tasks for the entire DMN unit and within left-hemispheric DMN regions, i.e., the dorsal medial prefrontal cortex, the anterior cingulate cortex, the retrosplenial cortex, the angular gyrus, the middle temporal gyrus and the anterior temporal region, as well as the right cerebellum. These results demonstrate that well-known semantic regions are spatially and functionally involved in the DMN. The present study further supports the hypothesis of the DMN as an internal mentation system that involves declarative memory functions.

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Dahl salt-sensitive (DS) and salt-resistant (DR) inbred rat strains represent a well established animal model for cardiovascular research. Upon prolonged administration of high-salt-containing diet, DS rats develop systemic hypertension, and as a consequence they develop left ventricular hypertrophy, followed by heart failure. The aim of this work was to explore whether this animal model is suitable to identify biomarkers that characterize defined stages of cardiac pathophysiological conditions. The work had to be performed in two stages: in the first part proteomic differences that are attributable to the two separate rat lines (DS and DR) had to be established, and in the second part the process of development of heart failure due to feeding the rats with high-salt-containing diet has to be monitored. This work describes the results of the first stage, with the outcome of protein expression profiles of left ventricular tissues of DS and DR rats kept under low salt diet. Substantial extent of quantitative and qualitative expression differences between both strains of Dahl rats in heart tissue was detected. Using Principal Component Analysis, Linear Discriminant Analysis and other statistical means we have established sets of differentially expressed proteins, candidates for further molecular analysis of the heart failure mechanisms.

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Sonography is an important diagnostic tool to examine the gastrointestinal tract of dogs with chronic diarrhea. Two-dimensional grayscale ultrasound parameters to assess for various enteropathies primarily focus on wall thickness and layering. Mild, generalized thickening of the intestinal wall with maintenance of the wall layering is common in inflammatory bowel disease. Quantitative and semi-quantitative spectral Doppler arterial waveform analysis can be utilized for various enteropathies, including inflammatory bowel disease and food allergies. Dogs with inflammatory bowel disease have inadequate hemodynamic responses during digestion of food. Dogs with food allergies have prolonged vasodilation and lower resistive and pulsatility indices after eating allergen-inducing foods.

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Magnetic iron garnets as well as magnetic photonic crystals are of great interests in magneto-optic applications such as isolators, current captors, circulators, TE-TM mode conversion, wavelength accordable filters, optical sensors and switches, all of which provide a promising platform for future integrated optical circuits. In the present work, two topics are studied based on magnetic iron garnet films. In the first part, the characteristics of the magnetization are investigated for ridge waveguides fabricated on (100) oriented iron garnet thin films. The magnetic response in magneto-optic waveguides patterned on epitaxial magnetic garnet films depends on the crystallographic orientation of the waveguides and the magnetic anisotropy of the material. These can be studied by polarization rotation hysteresis loops, which are related to the component of magnetization parallel to the light propagation direction and the linear birefringence. Polarization rotation hysteresis loops for low birefringence waveguides with different orientations are experimentally investigated. Asymmetric stepped curves are obtained from waveguides along, due to the large magnetocrystalline anisotropy in the plane. A model based on the free energy density is developed to demonstrate the motion of the magnetization and can be used in the design of magneto-optic devices. The second part of this thesis focuses on the design and fabrication of high-Q cavities in two-dimensional magneto-photonic crystal slabs. The device consists of a layer of silicon and a layer of iron garnet thin film. Triangular lattice elliptical air holes are patterned in the slab. The fundamental TM band gap overlaps with the first-order TE band gap from 0374~0.431(a/λ) showing that both TE and TM polarization light can be confined in the photonic crystals. A nanocavity is designed to obtain both TE and TM defect modes in the band gaps. Additional work is needed to overlap the TE and TM defect modes and obtain a high-Q cavity so as to develop miniaturized Faraday rotators.

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This technical report discusses the application of Lattice Boltzmann Method (LBM) in the fluid flow simulation through porous filter-wall of disordered media. The diesel particulate filter (DPF) is an example of disordered media. DPF is developed as a cutting edge technology to reduce harmful particulate matter in the engine exhaust. Porous filter-wall of DPF traps these soot particles in the after-treatment of the exhaust gas. To examine the phenomena inside the DPF, researchers are looking forward to use the Lattice Boltzmann Method as a promising alternative simulation tool. The lattice Boltzmann method is comparatively a newer numerical scheme and can be used to simulate fluid flow for single-component single-phase, single-component multi-phase. It is also an excellent method for modelling flow through disordered media. The current work focuses on a single-phase fluid flow simulation inside the porous micro-structure using LBM. Firstly, the theory concerning the development of LBM is discussed. LBM evolution is always related to Lattice gas Cellular Automata (LGCA), but it is also shown that this method is a special discretized form of the continuous Boltzmann equation. Since all the simulations are conducted in two-dimensions, the equations developed are in reference with D2Q9 (two-dimensional 9-velocity) model. The artificially created porous micro-structure is used in this study. The flow simulations are conducted by considering air and CO2 gas as fluids. The numerical model used in this study is explained with a flowchart and the coding steps. The numerical code is constructed in MATLAB. Different types of boundary conditions and their importance is discussed separately. Also the equations specific to boundary conditions are derived. The pressure and velocity contours over the porous domain are studied and recorded. The results are compared with the published work. The permeability values obtained in this study can be fitted to the relation proposed by Nabovati [8], and the results are in excellent agreement within porosity range of 0.4 to 0.8.

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Reports on left-lateralized abnormalities of component P300 of event-related brain potentials (ERP) in schizophrenics typically did not vary task difficulties. We collected 16-channel ERP in 13 chronic, medicated schizophrenics (25±4.9 years) and 13 matched controls in a visual P300 paradigm with targets defined by one or two stimulus dimensions (C1: color; C2: color and tilt); subjects key-pressed to targets. The mean target-ERP map landscapes were assessed numerically by the locations of the positive and negative map-area centroids. The centroids' time-space trajectories were searched for the P300 microstate landscape defined by the positive centroid posterior of the negative centroid. At P300 microstate centre latencies in C1, patients' maps tended to a right shift of the positive centroid (p<0.10); in C2 the anterior centroid was more posterior (p<0.07) and the posterior (positive) centroid more anterior (p<0.03), but without leftright difference. Duration of P300 microstate in C2 was shorter in patients (232 vs 347 ms;p<0.03) and the latency of maximal strength of P300 microstate increased significantly in patients (C1: 459 vs 376 ms; C2: 585 vs 525 ms). In summary only the one-dimensional task C1 supported left-sided abnormalities; the two-dimensional task C2 produced abnormal P300 microstate map landscapes in schizophrenics, but no abnormal lateralization. Thus, information processing involved clearly aberrant neural populations in schizophrenics, different when processing one and two stimulus dimensions. The lack of lateralization in the two-dimensional task supported the view that left-temporal abnormality in schizophrenics is only one of several task-dependent aberrations.

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This paper studied two different regression techniques for pelvic shape prediction, i.e., the partial least square regression (PLSR) and the principal component regression (PCR). Three different predictors such as surface landmarks, morphological parameters, or surface models of neighboring structures were used in a cross-validation study to predict the pelvic shape. Results obtained from applying these two different regression techniques were compared to the population mean model. In almost all the prediction experiments, both regression techniques unanimously generated better results than the population mean model, while the difference on prediction accuracy between these two regression methods is not statistically significant (α=0.01).

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The aim of this study was to validate oxygen-sensitive 3He-MRI in noninvasive determination of the regional, two- and three-dimensional distribution of oxygen partial pressure. In a gas-filled elastic silicon ventilation bag used as a lung phantom, oxygen sensitive two- and three-dimensional 3He-MRI measurements were performed at different oxygen concentrations which had been equilibrated in a range of normal and pathologic values. The oxygen partial pressure distribution was determined from 3He-MRI using newly developed software allowing for mapping of oxygen partial pressure. The reference bulk oxygen partial pressure inside the phantom was measured by conventional respiratory gas analysis. In two-dimensional measurements, image-based and gas-analysis results correlated with r=0.98; in three-dimensional measurements the between-methods correlation coefficient was r=0.89. The signal-to-noise ratio of three-dimensional measurements was about half of that of two-dimensional measurements and became critical (below 3) in some data sets. Oxygen-sensitive 3He-MRI allows for noninvasive determination of the two- and three-dimensional distribution of oxygen partial pressure in gas-filled airspaces.