Potentialities of two solventless extraction approaches—Stir bar sorptive extraction and headspace solid-phase microextraction for determination of higher alcohol acetates, isoamyl esters and ethyl esters in wines

A stir bar sorptive extraction with liquid desorption followed by large volume injection coupled to gas chromatography–quadrupole mass spectrometry (SBSE-LD/LVI-GC–qMS) was evaluated for the simultaneous determination of higher alcohol acetates (HAA), isoamyl esters (IsoE) and ethyl esters (EE) of fatty acids. The method performance was assessed and compared with other solventless technique, the solid-phase microextraction (SPME) in headspace mode (HS). For both techniques, influential experimental parameters were optimised to provide sensitive and robust methods. The SBSE-LD/LVI methodology was previously optimised in terms of extraction time, influence of ethanol in the matrix, liquid desorption (LD) conditions and instrumental settings. Higher extraction efficiency was obtained using 60 min of extraction time, 10% ethanol content, n-pentane as desorption solvent, 15 min for the back-extraction period, 10 mL min−1 for the solvent vent flow rate and 10 °C for the inlet temperature. For HS-SPME, the fibre coated with 50/30 μm divinylbenzene/carboxen/polydimethylsiloxane (DVB/CAR/PDMS) afforded highest extraction efficiency, providing the best sensitivity for the target volatiles, particularly when the samples were extracted at 25 °C for 60 min under continuous stirring in the presence of sodium chloride (10% (w/v)). Both methodologies showed good linearity over the concentration range tested, with correlation coefficients higher than 0.984 for HS-SPME and 0.982 for SBES-LD approach, for all analytes. A good reproducibility was attained and low detection limits were achieved using both SBSE-LD (0.03–28.96 μg L−1) and HS-SPME (0.02–20.29 μg L−1) methodologies. The quantification limits for SBSE-LD approach ranging from 0.11 to 96.56 μg L−and from 0.06 to 67.63 μg L−1 for HS-SPME. Using the HS-SPME approach an average recovery of about 70% was obtained whilst by using SBSE-LD obtained average recovery were close to 80%. The analytical and procedural advantages and disadvantages of these two methods have been compared. Both analytical methods were used to determine the HAA, IsoE and EE fatty acids content in “Terras Madeirenses” table wines. A total of 16 esters were identified and quantified from the wine extracts by HS-SPME whereas by SBSE-LD technique were found 25 esters which include 2 higher alcohol acetates, 4 isoamyl esters and 19 ethyl esters of fatty acids. Generally SBSE-LD provided higher sensitivity with decreased analysis time.

A graph-based framework for thermal faceprint characterization

Thermal faceprint has been paramount in the last years. Since we can handle with face recognition using images acquired in the infrared spectrum, an unique individual's signature can be obtained through the blood vessels network of the face. In this work, we propose a novel framework for thermal faceprint extraction using a collection of graph-based techniques, which were never used to this task up to date. A robust method of thermal face segmentation is also presented. The experiments, which were conducted over the UND Collection C dataset, have showed promising results. © 2011 Springer-Verlag.

Multivariate analysis for animal selection in experimental research

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

Widespread pH abnormalities in patients with malformations of cortical development and epilepsy: a phosphorus-31 brain MR spectroscopy study

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

Multivariate analysis for selecting animals for experimental research

Background Several researchers seek methods for the selection of homogeneous groups of animals in experimental studies, a fact justified because homogeneity is an indispensable prerequisite for casualization of treatments. The lack of robust methods that comply with statistical and biological principles is the reason why researchers use empirical or subjective methods, influencing their results. Objective To develop a multivariate statistical model for the selection of a homogeneous group of animals for experimental research and to elaborate a computational package to use it. Methods The set of echocardiographic data of 115 male Wistar rats with supravalvular aortic stenosis (AoS) was used as an example of model development. Initially, the data were standardized, and became dimensionless. Then, the variance matrix of the set was submitted to principal components analysis (PCA), aiming at reducing the parametric space and at retaining the relevant variability. That technique established a new Cartesian system into which the animals were allocated, and finally the confidence region (ellipsoid) was built for the profile of the animals’ homogeneous responses. The animals located inside the ellipsoid were considered as belonging to the homogeneous batch; those outside the ellipsoid were considered spurious. Results The PCA established eight descriptive axes that represented the accumulated variance of the data set in 88.71%. The allocation of the animals in the new system and the construction of the confidence region revealed six spurious animals as compared to the homogeneous batch of 109 animals. Conclusion The biometric criterion presented proved to be effective, because it considers the animal as a whole, analyzing jointly all parameters measured, in addition to having a small discard rate.

Bilayer segmentation of live video in uncontrolled environments for background substitution: an overview and main challenges

Bilayer segmentation of live video in uncontrolled environments is an essential task for home applications in which the original background of the scene must be replaced, as in videochats or traditional videoconference. The main challenge in such conditions is overcome all difficulties in problem-situations (e. g., illumination change, distract events such as element moving in the background and camera shake) that may occur while the video is being captured. This paper presents a survey of segmentation methods for background substitution applications, describes the main concepts and identifies events that may cause errors. Our analysis shows that although robust methods rely on specific devices (multiple cameras or sensors to generate depth maps) which aid the process. In order to achieve the same results using conventional devices (monocular video cameras), most current research relies on energy minimization frameworks, in which temporal and spacial information are probabilistically combined with those of color and contrast.

Informatics for cross-sample analysis with comprehensive two-dimensional gas chromatography and high-resolution mass spectrometry (GCxGC-HRMS)

This paper describes informatics for cross-sample analysis with comprehensive two-dimensional gas chromatography (GCxGC) and high-resolution mass spectrometry (HRMS). GCxGC-HRMS analysis produces large data sets that are rich with information, but highly complex. The size of the data and volume of information requires automated processing for comprehensive cross-sample analysis, but the complexity poses a challenge for developing robust methods. The approach developed here analyzes GCxGC-HRMS data from multiple samples to extract a feature template that comprehensively captures the pattern of peaks detected in the retention-times plane. Then, for each sample chromatogram, the template is geometrically transformed to align with the detected peak pattern and generate a set of feature measurements for cross-sample analyses such as sample classification and biomarker discovery. The approach avoids the intractable problem of comprehensive peak matching by using a few reliable peaks for alignment and peak-based retention-plane windows to define comprehensive features that can be reliably matched for cross-sample analysis. The informatics are demonstrated with a set of 18 samples from breast-cancer tumors, each from different individuals, six each for Grades 1-3. The features allow classification that matches grading by a cancer pathologist with 78% success in leave-one-out cross-validation experiments. The HRMS signatures of the features of interest can be examined for determining elemental compositions and identifying compounds.

Deforestation and forest degradation monitoring and assessment of biomass and carbon stock of lowland rainforest in the Analanjirofo region, Madagascar

Madagascar is currently developing a policy and strategies to enhance the sustainable management of its natural resources, encouraged by United Nations Framework Convention on Climate Change (UNFCCC) and REDD. To set up a sustainable financing scheme methodologies have to be provided that estimate, prevent and mitigate leakage, develop national and regional baselines, and estimate carbon benefits. With this research study this challenge was tried to be addressed by analysing a lowland rainforest in the Analanjirofo region in the district of Soanierana Ivongo, North East of Madagascar. For two distinguished forest degradation stages: “low degraded forest” and “degraded forest” aboveground biomass and carbon stock was assessed. The corresponding rates of carbon within those two classes were calculated and linked to a multi-temporal set of SPOT satellite data acquired in 1991, 2004 and 2009. Deforestation and particularly degradation and the related carbon stock developments were analysed. With the assessed data for the 3 years 1991, 2004 and 2009 it was possible to model a baseline and to develop a forest prediction for 2020 for Analanjirofo region in the district of Soanierana Ivongo. These results, developed applying robust methods, may provide important spatial information regarding the priorities in planning and implementation of future REDD+ activities in the area.

IDENTIFICATION OF GENES CONTROLLING BIOLOGICAL PROCESSES AND PATHWAYS THROUGH STATISTICAL ANALYSIS AND NETWORK RECONSTRUCTION

The developmental processes and functions of an organism are controlled by the genes and the proteins that are derived from these genes. The identification of key genes and the reconstruction of gene networks can provide a model to help us understand the regulatory mechanisms for the initiation and progression of biological processes or functional abnormalities (e.g. diseases) in living organisms. In this dissertation, I have developed statistical methods to identify the genes and transcription factors (TFs) involved in biological processes, constructed their regulatory networks, and also evaluated some existing association methods to find robust methods for coexpression analyses. Two kinds of data sets were used for this work: genotype data and gene expression microarray data. On the basis of these data sets, this dissertation has two major parts, together forming six chapters. The first part deals with developing association methods for rare variants using genotype data (chapter 4 and 5). The second part deals with developing and/or evaluating statistical methods to identify genes and TFs involved in biological processes, and construction of their regulatory networks using gene expression data (chapter 2, 3, and 6). For the first part, I have developed two methods to find the groupwise association of rare variants with given diseases or traits. The first method is based on kernel machine learning and can be applied to both quantitative as well as qualitative traits. Simulation results showed that the proposed method has improved power over the existing weighted sum method (WS) in most settings. The second method uses multiple phenotypes to select a few top significant genes. It then finds the association of each gene with each phenotype while controlling the population stratification by adjusting the data for ancestry using principal components. This method was applied to GAW 17 data and was able to find several disease risk genes. For the second part, I have worked on three problems. First problem involved evaluation of eight gene association methods. A very comprehensive comparison of these methods with further analysis clearly demonstrates the distinct and common performance of these eight gene association methods. For the second problem, an algorithm named the bottom-up graphical Gaussian model was developed to identify the TFs that regulate pathway genes and reconstruct their hierarchical regulatory networks. This algorithm has produced very significant results and it is the first report to produce such hierarchical networks for these pathways. The third problem dealt with developing another algorithm called the top-down graphical Gaussian model that identifies the network governed by a specific TF. The network produced by the algorithm is proven to be of very high accuracy.

Stereological estimation of particle shape and orientation from volume tensors

In the present paper, we describe new robust methods of estimating cell shape and orientation in 3D from sections. The descriptors of 3D cell shape and orientation are based on volume tensors which are used to construct an ellipsoid, the Miles ellipsoid, approximating the average cell shape and orientation in 3D. The estimators of volume tensors are based on observations in several optical planes through sampled cells. This type of geometric sampling design is known as the optical rotator. The statistical behaviour of the estimator of the Miles ellipsoid is studied under a flexible model for 3D cell shape and orientation. In a simulation study, the lengths of the axes of the Miles ellipsoid can be estimated with CVs of about 2% if 100 cells are sampled. Finally, we illustrate the use of the developed methods in an example, involving neurons in the medial prefrontal cortex of rat.

Use of echocardiography reveals reestablishment of ventricular pumping efficiency and partial ventricular wall motion recovery upon ventricular cryoinjury in the zebrafish

AIMS While zebrafish embryos are amenable to in vivo imaging, allowing the study of morphogenetic processes during development, intravital imaging of adults is hampered by their small size and loss of transparency. The use of adult zebrafish as a vertebrate model of cardiac disease and regeneration is increasing at high speed. It is therefore of great importance to establish appropriate and robust methods to measure cardiac function parameters. METHODS AND RESULTS Here we describe the use of 2D-echocardiography to study the fractional volume shortening and segmental wall motion of the ventricle. Our data show that 2D-echocardiography can be used to evaluate cardiac injury and also to study recovery of cardiac function. Interestingly, our results show that while global systolic function recovered following cardiac cryoinjury, ventricular wall motion was only partially restored. CONCLUSION Cryoinjury leads to long-lasting impairment of cardiac contraction, partially mimicking the consequences of myocardial infarction in humans. Functional assessment of heart regeneration by echocardiography allows a deeper understanding of the mechanisms of cardiac regeneration and has the advantage of being easily transferable to other cardiovascular zebrafish disease models.

The trade credit in the Spanish agrofood industry

Selling on credit is rather frequent in Mediterranean countries. Its generalized use can lead to excessive enlargements of the payment periods and consequently can deteriorate the profitability of firms. In spite of the relevance of this problem there are few empirical researches. This work intends to fill this gap and to shed light on the factors related to the extension of trade credit. In the theoretical and empirical literature, different motives have been proposed to explain this issue: a mechanism to reduce transaction costs, a financial alternative to the bank system and an additional tool to improve commercial activities. To contrast these ideas a panel of 388 firms of the Spanish agrofood industry has been taken, and static and dynamic regression models have been estimated by using robust methods to heteroskedasticity, autocorrelation and endogeneity of the explanatory variables. The results confirm that trade credit receivable is associated with more active firms and with cheaper bank financing. Other factors with positive relationships are short-term bank debts and accounts payable. These findings are consistent with commercial motives, rather than a pure financial view, in the sense that financial distressed producers extend trade credit as a way of promoting their products and in turn increasing their sales.

(Bio)funcionalização de superfícies nanoestruturadas para eletrocatálise e desenvolvimento de biossensores eletroquímicos e óticos

Tese de doutoramento, Química (Química Física), Universidade de Lisboa, Faculdade de Ciências, 2016

Public opinion of a proposed wind farm situated close to a populated area in New Zealand: Results from a cross-sectional study

In accordance with New Zealand’s Resource Management Act 1991, in 2003, electricity generating company Genesis Energy made public its intention to apply for consent to build the Awhitu wind farm. Several community groups claiming to represent the majority opposed this application and in September 2004 consent was declined. The aim was to investigate the attitudes of local community members to the proposed wind farm. A survey was mailed to 500 Franklin residents, systematically selected from the local 2004/2005 telephone directory. Forty questionnaires were returned undelivered. Of the remaining 460, completed questionnaires were returned from 46% (211). Most, 70% (145), residents supported a wind farm being built in their area, with 17% (35) neutral, and only 13% (28) against the farm. There was no statistical difference in respondents’ attitudes between sex, age, or residential proximity to the farm. Respondents listed renewable resource (83%), suitability (78%), and environmental friendliness (76%) as main advantages. Visual unsightliness (24%) and noise pollution (21%) were listed as main perceived disadvantages. Contrary to the assertions of several lobby groups, the majority of local residents support the construction of the Awhitu wind farm. Scientifically robust methods are essential to measure appropriately community attitudes, particularly on contentious issues.

Quantifying and Modeling the Influence of Forest on the Magnitude and Duration of Mountain Snow Storage in the Pacific Northwest, USA

Thesis (Ph.D.)--University of Washington, 2016-08