Near-infrared Raman spectroscopy to detect anti-Toxoplasma gondii antibody in blood sera of domestic cats: quantitative analysis based on partial least-squares multivariate statistics

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

PRACTICAL LAND GRADING BASED ON LEAST SQUARES.

Practical methods for land grading design of a plane surface for rectangular and irregularly shaped fields based on a least squares analysis are presented. The least squares procedure leads to a system of three linear equations with three unknowns for determination of the best-fit plane. The equations can be solved by determinants (Cramer's rule) using a procedure capable of solution by many programmable calculators. The detailed computational process for determining the equation of the plane and a simple method to find the centroid location of an irregular field are also given. An illustrative example and design instructions are included to demonstrate the application of the design procedure.

Simulations of incompressible fluid flows by a least squares finite element method

In this work simulations of incompressible fluid flows have been done by a Least Squares Finite Element Method (LSFEM) using velocity-pressure-vorticity and velocity-pressure-stress formulations, named u-p-ω) and u-p-τ formulations respectively. These formulations are preferred because the resulting equations are partial differential equations of first order, which is convenient for implementation by LSFEM. The main purposes of this work are the numerical computation of laminar, transitional and turbulent fluid flows through the application of large eddy simulation (LES) methodology using the LSFEM. The Navier-Stokes equations in u-p-ω and u-p-τ formulations are filtered and the eddy viscosity model of Smagorinsky is used for modeling the sub-grid-scale stresses. Some benchmark problems are solved for validate the numerical code and the preliminary results are presented and compared with available results from the literature. Copyright © 2005 by ABCM.

Mitigating systematic errors for single frequency GPS receivers employing a penalized least squares methodology

Among the positioning systems that compose GNSS (Global Navigation Satellite System), GPS has the capability of providing low, medium and high precision positioning data. However, GPS observables may be subject to many different types of errors. These systematic errors can degrade the accuracy of the positioning provided by GPS. These errors are mainly related to GPS satellite orbits, multipath, and atmospheric effects. In order to mitigate these errors, a semiparametric model and the penalized least squares technique were employed in this study. This is similar to changing the stochastical model, in which error functions are incorporated and the results are similar to those in which the functional model is changed instead. Using this method, it was shown that ambiguities and the estimation of station coordinates were more reliable and accurate than when employing a conventional least squares methodology.

At least two indigenous species of the Bemisia tabaci complex are present in Brazil

Bemisia tabaci is one of the most important global agricultural insect pests, being a vector of emerging plant viruses such as begomoviruses and criniviruses that cause serious problems in many countries. Although knowledge of the genetic diversity of B. tabaci populations is important for controlling this pest and understanding viral epidemics, limited information is available on this pest in Brazil. A survey was conducted in different locations of São Paulo and Mato Grosso states, and the phylogenetic relationships of B. tabaci individuals from 43 populations sampled from different hosts were analysed based on partial mitochondrial cytochrome oxidase 1 gene (mtCOI) sequences. According to the recently proposed classification of the B. tabaci complex, which employs the 3.5% mtCOI sequence divergence threshold for species demarcation, most of the specimens collected were found to belong to the Middle East-Asia Minor 1 species, which includes the invasive populations of the commonly known B biotype, within the Africa/Middle East/Asia Minor high-level group. Three specimens collected from Solanun gilo and Ipomoea sp. were grouped together and could be classified in the New World species that includes the commonly known A biotype. However, six specimens collected from Euphorbia heterophylla, Xanthium cavanillesii and Glycine maxima could not be classified into any of the 28 previously proposed species, although according to the 11% mtCOI sequence divergence threshold, they belong to the New World high-level group. These specimens were classified into a new recently proposed species named New World 2 that includes populations from Argentina. Middle East-Asia Minor 1, New World and New World 2 were differentiated by RFLP analysis of the mtCOI gene using TaqI enzyme. Taq I analysis in silico also differentiates these from Mediterranean species, thus making this method a convenient tool to determine population dynamics, especially critical for monitoring the presence of this exotic pest in Brazil. © 2012 Blackwell Verlag, GmbH.

Comparison between known propagation models using least squares tuning algorithm on 5.8 GHz in Amazon region cities

ABSTRACT: This paper presents a performance comparison between known propagation Models through least squares tuning algorithm for 5.8 GHz frequency band. The studied environment is based on the 12 cities located in Amazon Region. After adjustments and simulations, SUI Model showed the smaller RMS error and standard deviation when compared with COST231-Hata and ECC-33 models.

Independência funcional de idosos no pós-operatório de cirurgia de fêmur proximal: papel do cuidador

Pós-graduação em Saúde Coletiva - FMB

A brief look at the least-squares approach as a classifier applied to restricted-vocabulary speech recognition

In this letter, a speech recognition algorithm based on the least-squares method is presented. Particularly, the intention is to exemplify how such a traditional numerical technique can be applied to solve a signal processing problem that is usually treated by using more elaborated formulations.

Least-cost Disjoint Paths with Dependent Cost Structure in Wavelength Continuous Optical WDM Networks

One of the important issues in establishing a fault tolerant connection in a wavelength division multiplexing optical network is computing a pair of disjoint working and protection paths and a free wavelength along the paths. While most of the earlier research focused only on computing disjoint paths, in this work we consider computing both disjoint paths and a free wavelength along the paths. The concept of dependent cost structure (DCS) of protection paths to enhance their resource sharing ability was proposed in our earlier work. In this work we extend the concept of DCS of protection paths to wavelength continuous networks. We formalize the problem of computing disjoint paths with DCS in wavelength continuous networks and prove that it is NP-complete. We present an iterative heuristic that uses a layered graph model to compute disjoint paths with DCS and identify a free wavelength.

Constrained least square pre-distortion scheme for multiuser ultra-wideband

The study proposes a constrained least square (CLS) pre-distortion scheme for multiple-input single-output (MISO) multiple access ultra-wideband (UWB) systems. In such a scheme, a simple objective function is defined, which can be efficiently solved by a gradient-based algorithm. For the performance evaluation, scenarios CM1 and CM3 of the IEEE 802.15.3a channel model are considered. Results show that the CLS algorithm has a fast convergence and a good trade-off between intersymbol interference (ISI) and multiple access interference (MAI) reduction and signal-to-noise ratio (SNR) preservation, performing better than time-reversal (TR) pre-distortion.

Soil compressibility and least limiting water range of a constructed soil under cover crops after coal mining in Southern Brazil

The use of cover crops affects the support capacity of soil and least limiting water range to crop growth. The objective of this study was to quantify preconsolidation pressure (sigma(p)), compression index (CI) and least limiting water range (LLWR) of a reclaimed coal mining soil under different cover crops, in Candiota, RS, Brazil. In the experiment, with randomized blocks design and four replicates, the following cover crops (treatments) were evaluated: Hemarthria altissima (Poir.) Stapf & C.E. Hubbard, treatment 1 (T1), Paspalum notatum Flugge, treatment 4 (T4), Cynodon dactilon (L) Pers., treatment 5 (T5), control Brachiaria brizantha (Hochst.) Stapf, treatment 7 (T7) and without cover crop treatment 8 (reference treatment, T8). Soil compression and least limiting water range were evaluated with undisturbed samples at a depth of 0.00-0.05 m. In order to evaluate parameters of soil compressibility, the soil samples were saturated with water and subjected to -10 kPa matric potential and then submitted to a uniaxial compression test under the following pressures: 25, 50, 100, 200, 400, 800 and 1600 kPa. Cover crops decreased the preconsolidation pressure of constructed soils after coal mining and the greatest soil reclamation was obtained with the H. altissima cover crop, where the lowest degree of soil compactness and soil load capacity were observed. Soils cultivated under H. altissima or B. brizantha presented the highest least limiting water range and these two cover crops generated similar soil critical bulk density obtained by least limiting water range and soil load support capacity. (C) 2012 Elsevier B.V. All rights reserved.

Risk factors for blindness in patients with open-angle glaucoma followed-up for at least 15 years

Purpose: To determine the proportion of blindness and investigate the relationships between risk factors based on clinical characteristics and development of blindness in patients with primary open-angle glaucoma (POAG) treated for at least 15 years. Methods: A retrospective observational chart review was performed with 403 patients referred to a tertiary level hospital, each with a diagnosis of primary open-angle glaucoma, treated for at least 15 years. Blindness attributable to glaucoma was defined based on visual acuity and/or visual field tests. Variables considered to be possible risk factors for blindness were evaluated using odds ratio (OR), confidence interval (95% CI), and univariate and multivariate analyses. Results: Thirty-one patients became blind [13/53 (24.5%) - unilaterally and 18/53 (34%) - bilaterally] during the follow-up period of treatment (19.5 +/- 4.6 years, range 15-31 years). Multivariate statistics with regression analysis revealed that persistency on initial therapy <= 6 months was significantly associated with blindness, both unilateral (OR: 8.4; 95% CI: 1.3-56.4) and bilateral (OR: 7.2; 95% CI: 1.3-39.6). Other potential factors such as race, age, gender or number of medications were not associated with blindness. Conclusion: Blindness from primary open-angle glaucoma was not uncommon in this population of treated patients after the long follow-up period proposed. Persistence rates with the first therapy, as measured by a medical decision to change, were low. Persistence <= 6 months was statistically associated with the development of unilateral and bilateral blindness from glaucoma.

Semi-supervised dimensionality reduction based on partial least squares for visual analysis of high dimensional data

Dimensionality reduction is employed for visual data analysis as a way to obtaining reduced spaces for high dimensional data or to mapping data directly into 2D or 3D spaces. Although techniques have evolved to improve data segregation on reduced or visual spaces, they have limited capabilities for adjusting the results according to user's knowledge. In this paper, we propose a novel approach to handling both dimensionality reduction and visualization of high dimensional data, taking into account user's input. It employs Partial Least Squares (PLS), a statistical tool to perform retrieval of latent spaces focusing on the discriminability of the data. The method employs a training set for building a highly precise model that can then be applied to a much larger data set very effectively. The reduced data set can be exhibited using various existing visualization techniques. The training data is important to code user's knowledge into the loop. However, this work also devises a strategy for calculating PLS reduced spaces when no training data is available. The approach produces increasingly precise visual mappings as the user feeds back his or her knowledge and is capable of working with small and unbalanced training sets.

Memory in children with temporal lobe epilepsy is at least partially explained by executive dysfunction

An association between memory and executive dysfunction (ED) has been demonstrated in patients with mixed neurological disorders. We aimed to investigate the impact of ED in memory tasks of children with temporal lobe epilepsy (TLE). We evaluated 36 children with TLE and 28 controls with tests for memory, learning, attention, mental flexibility, and mental tracking. Data analysis was composed of comparison between patients and controls in memory and executive function; correlation between memory and executive function tests; and comparison between patients with mild and severe ED in memory tests. Children with TLE had worse performance in focused attention, immediate and delayed recall, phonological memory, mental tracking, planning, and abstraction. Planning, abstraction, and mental tracking were correlated with visual and verbal memory. Children with severe ED had worse performance in verbal and visual memory and learning tests. This study showed that ED was related to memory performance in children with TLE. (C) 2012 Elsevier Inc. All rights reserved.