Does the intake of LC-PUFAS during pregnancy affect the body composition of term neonates? Preliminary results

Background: The effect of the intake of polynsaturated long chain fatty acids (LCPUFAs) during pregnancy on fetal body composition has been assessed by studies using mostly neonatal anthropometry. Their results have been inconsistent, probably because neonatal anthropometry has several validity limitations. Air displacement plethismography (ADP) is a recently validated non-invasive method for assessing body composition in neonates. Objective: To determine the effect of the intake of LCPUFAs during pregnancy on the body composition of term neonates, measured by ADP. Methods: Cross-sectional study of a convenience sample of healthy full-term neonates and their mothers. The diet during pregnancy was assessed using a validated semi-quantitative food frequency questionnaire; Food Processor Plus® was used to convert food intake into nutritional values. Body composition was estimated by anthropometry and measured by ADP using Pea Pod™ Life Measurements Inc (fat mass - FM, fat-free mass and %FM) within the first 72h after birth. Univariate and multivariate analysis (linear regression model) were performed. Results: 54 mother-neonate pairs were included. Multivariate analysis adjusted to the maternal body mass index shows positive association between LCPUFAs intake and neonatal mid-arm circumference (= 0,610, p = 0,019) and negative association between n-6:n-3 ratio intake and neonatal %FM (= -2,744, p=0,066). Conclusion: To the best of our knowledge, this is the first study on this subject using ADP and showing a negative association between LCPUFAs n-6:n-3 ratio intake in pregnancy and neonatal %FM. This preliminary finding requires confirmation increasing the study power with a greater sample and performing interventional studies.

Dependent component analysis: a hyperspectral unmixing algorithm

Linear unmixing decomposes a hyperspectral image into a collection of reflectance spectra of the materials present in the scene, called endmember signatures, and the corresponding abundance fractions at each pixel in a spatial area of interest. This paper introduces a new unmixing method, called Dependent Component Analysis (DECA), which overcomes the limitations of unmixing methods based on Independent Component Analysis (ICA) and on geometrical properties of hyperspectral data. DECA models the abundance fractions as mixtures of Dirichlet densities, thus enforcing the constraints on abundance fractions imposed by the acquisition process, namely non-negativity and constant sum. The mixing matrix is inferred by a generalized expectation-maximization (GEM) type algorithm. The performance of the method is illustrated using simulated and real data.

Vertex component analysis: a fast algorithm to extract endmembers spectra from hyperspectral data

Chapter in Book Proceedings with Peer Review First Iberian Conference, IbPRIA 2003, Puerto de Andratx, Mallorca, Spain, JUne 4-6, 2003. Proceedings

Vertex component analysis: a fast algorithm to unmix hyperspectral data

Given a set of mixed spectral (multispectral or hyperspectral) vectors, linear spectral mixture analysis, or linear unmixing, aims at estimating the number of reference substances, also called endmembers, their spectral signatures, and their abundance fractions. This paper presents a new method for unsupervised endmember extraction from hyperspectral data, termed vertex component analysis (VCA). The algorithm exploits two facts: (1) the endmembers are the vertices of a simplex and (2) the affine transformation of a simplex is also a simplex. In a series of experiments using simulated and real data, the VCA algorithm competes with state-of-the-art methods, with a computational complexity between one and two orders of magnitude lower than the best available method.

Comparison of the pencil beam convolution algorithm and the analytical anisotropic algorithm in breast tumors

The calculation of the dose is one of the key steps in radiotherapy planning1-5. This calculation should be as accurate as possible, and over the years it became feasible through the implementation of new algorithms to calculate the dose on the treatment planning systems applied in radiotherapy. When a breast tumour is irradiated, it is fundamental a precise dose distribution to ensure the planning target volume (PTV) coverage and prevent skin complications. Some investigations, using breast cases, showed that the pencil beam convolution algorithm (PBC) overestimates the dose in the PTV and in the proximal region of the ipsilateral lung. However, underestimates the dose in the distal region of the ipsilateral lung, when compared with analytical anisotropic algorithm (AAA). With this study we aim to compare the performance in breast tumors of the PBC and AAA algorithms.

A SON Enhanced Algorithm for Observed Time Differences Based Geolocation in Real 3G Networks

Conferência - 16th International Symposium on Wireless Personal Multimedia Communications (WPMC)- Jun 24-27, 2013

The effect of long-chain polyunsaturated fatty acids intake during pregnancy on adiposity of healthy full-term offspring at birth

Objective - The adjusted effect of long-chain polyunsaturated fatty acid (LCPUFA) intake during pregnancy on adiposity at birth of healthy full-term appropriate-for-gestational age neonates was evaluated. Study Design - In a cross-sectional convenience sample of 100 mother and infant dyads, LCPUFA intake during pregnancy was assessed by food frequency questionnaire with nutrient intake calculated using Food Processor Plus. Linear regression models for neonatal body composition measurements, assessed by air displacement plethysmography and anthropometry, were adjusted for maternal LCPUFA intakes, energy and macronutrient intakes, prepregnancy body mass index and gestational weight gain. Result - Positive associations between maternal docosahexaenoic acid intake and ponderal index in male offspring (β=0.165; 95% confidence interval (CI): 0.031–0.299; P=0.017), and between n-6:n-3 LCPUFA ratio intake and fat mass (β=0.021; 95% CI: 0.002–0.041; P=0.034) and percentage of fat mass (β=0.636; 95% CI: 0.125–1.147; P=0.016) in female offspring were found. Conclusion - Using a reliable validated method to assess body composition, adjusted positive associations between maternal docosahexaenoic acid intake and birth size in male offspring and between n-6:n-3 LCPUFA ratio intake and adiposity in female offspring were found, suggesting that maternal LCPUFA intake strongly influences fetal body composition.

Optimização da lista de células vizinhas em redes LTE

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia de Electrónica e Telecomunicações

Comparação entre o pencil beam convolution algorithm e o analytical anisotropic algorithm em tumores de mama

Objectivo do estudo: comparar o desempenho dos algoritmos Pencil Beam Convolution (PBC) e do Analytical Anisotropic Algorithm (AAA) no planeamento do tratamento de tumores de mama com radioterapia conformacional a 3D.

Wind-CSP short-term coordination by MILP approach

This paper is on the maximization of total profit in a day-ahead market for a price-taker producer needing a short-term scheduling for wind power plants coordination with concentrated solar power plants, having thermal energy storage systems. The optimization approach proposed for the maximization of profit is a mixed-integer linear programming problem. The approach considers not only transmission grid constraints, but also technical operating constraints on both wind and concentrated solar power plants. Then, an improved short-term scheduling coordination is provided due to the more accurate modelling presented in this paper. Computer simulation results based on data for the Iberian wind and concentrated solar power plants illustrate the coordination benefits and show the effectiveness of the approach.

Short-term Value for the Water Stored in Headsensitivity Power System Reservoirs

As it is well known, competitive electricity markets require new computing tools for generation companies to enhance the management of its resources. The economic value of the water stored in a power system reservoir is crucial information for enhancing the management of the reservoirs. This paper proposes a practical deterministic approach for computing the short-term economic value of the water stored in a power system reservoir, emphasizing the need to considerer water stored as a scarce resource with a short-term economic value. The paper addresses a problem concerning reservoirs with small storage capacities, i.e., the reservoirs considered as head-sensitivity. More precisely, the respective hydro plant is head-dependent and a pure linear approach is unable to capture such consideration. The paper presents a case study supported by the proposed practical deterministic approach and applied on a real multi-reservoir power system with three cascaded reservoirs, considering as input data forecasts for the electric energy price and for the natural inflow into the reservoirs over the schedule time horizon. The paper presents various water schedules due to different final stored water volume conditions on the reservoirs. Also, it presents the respective economic value of the water for the reservoirs at different stored water volume conditions.

Metaheuristic approach to the Holt-Winters optimal short term load forecast

Electricity short-term load forecast is very important for the operation of power systems. In this work a classical exponential smoothing model, the Holt-Winters with double seasonality was used to test for accurate predictions applied to the Portuguese demand time series. Some metaheuristic algorithms for the optimal selection of the smoothing parameters of the Holt-Winters forecast function were used and the results after testing in the time series showed little differences among methods, so the use of the simple local search algorithms is recommended as they are easier to implement.

Metaheuristhic approach to the Holt-Winters optimal short term load forecast

Electricity short-term load forecast is very important for the operation of power systems. In this work a classical exponential smoothing model, the Holt-Winters with double seasonality was used to test for accurate predictions applied to the Portuguese demand time series. Some metaheuristic algorithms for the optimal selection of the smoothing parameters of the Holt-Winters forecast function were used and the results after testing in the time series showed little differences among methods, so the use of the simple local search algorithms is recommended as they are easier to implement.

Coding mode decision algorithm for binary descriptor coding

In visual sensor networks, local feature descriptors can be computed at the sensing nodes, which work collaboratively on the data obtained to make an efficient visual analysis. In fact, with a minimal amount of computational effort, the detection and extraction of local features, such as binary descriptors, can provide a reliable and compact image representation. In this paper, it is proposed to extract and code binary descriptors to meet the energy and bandwidth constraints at each sensing node. The major contribution is a binary descriptor coding technique that exploits the correlation using two different coding modes: Intra, which exploits the correlation between the elements that compose a descriptor; and Inter, which exploits the correlation between descriptors of the same image. The experimental results show bitrate savings up to 35% without any impact in the performance efficiency of the image retrieval task. © 2014 EURASIP.

Neighbour list optimization for real LTE radio network

With the increasing complexity of current networks, it became evident the need for Self-Organizing Networks (SON), which aims to automate most of the associated radio planning and optimization tasks. Within SON, this paper aims to optimize the Neighbour Cell List (NCL) for Long Term Evolution (LTE) evolved NodeBs (eNBs). An algorithm composed by three decisions were were developed: distance-based, Radio Frequency (RF) measurement-based and Handover (HO) stats-based. The distance-based decision, proposes a new NCL taking account the eNB location and interference tiers, based in the quadrants method. The last two algorithms consider signal strength measurements and HO statistics, respectively; they also define a ranking to each eNB and neighbour relation addition/removal based on user defined constraints. The algorithms were developed and implemented over an already existent radio network optimization professional tool. Several case studies were produced using real data from a Portuguese LTE mobile operator. © 2014 IEEE.