Elastic moduli approximation of higher symmetry for the acoustical properties of an anisotropic material

The issue of how to define and determine an optimal acoustical fit to a set of anisotropic elastic constants is addressed. The optimal moduli are defined as those which minimize the mean squared difference in the acoustical tensors between the given moduli and all possible moduli of a chosen higher material symmetry. The solution is shown to be identical to minimizing a Euclidean distance function, or equivalently, projecting the tensor of elastic stiffness onto the appropriate symmetry. This has implications for how to best select anisotropic constants to acoustically model complex materials.Comment: 20 page

On the generality of the effect of experiencing prior gains and losses on the Iowa gambling task: A study on young and old adults

Prospect Theory predicts that people tend to be more risk seeking if their reference point is perceived as a loss and more risk averse when the reference point is perceived as a gain. In line with this prediction, Franken, Georgieva, Muris and Dijksterhuis (2006) showed that young adults who had a prior experience of monetary gains make more safe choices on subsequent decisions than subjects who had an early experience of losses. There are no experimental studies on how experiencing prior gains and losses differently influences young and older adults on a subsequent decision-making task (the Iowa Gambling Task). Hence, in the current paper, adapting the methodology employed by Franken et al.’s (2006), we intended to test the generality of their effect across the life span. Overall, we found that subjects who experienced prior monetary gains or prior monetary losses did not display significant differences in safe/risky choices on subsequent performance in the Iowa Gambling task. Furthermore, the impact of prior gains and losses on risky/safe card selection did not significantly differ between young and older adults. These results showed that the effect found in the Franken et al.’s study (2006) is limited in its generality

Anatomy of the supraventricular crest in human hearts

The supraventricular crest is a fleshy trabecula of the right ventricle that has an important function in guiding the blood flow. However, controversy persists regarding its anatomical constitution. In this study, we aimed to investigate its frequency, formation, termination, morphometry, and relationships with the septomarginal trabecula, septal papillary muscle, right atrioventricular ring, and left posterior semilunar valve of the pulmonary trunk valve. Our material consisted of 50 hearts from adult individuals of both sexes that had been preserved in 10% formalin. They were opened along the arterial cone by means of an incision starting at the pulmonary trunk and ending at the right margin. The supraventricular crest was always present. The marginal (right) extremity was formed by two to six muscle bundles that joined together (88%). On the septal (left) side, the single muscle bundle penetrated the interventricular septum directly (88%) or by means of two or three divisions (12%). It could form a septal band (52%) and could pass over the septal papillary muscle (43.5%) or just below it (34.8%). There was a relationship of muscle fibres between these two structures in 64% of cases. Dissection of the septal band demonstrated continuity with the septomarginal trabecula (46%). In 80% of cases, the crest was connected to the right atrioventricular ring and it participated in its outline directly (64%) or by means of muscle expansions (16%). Its muscle fibres bordered the left semilunar valve of the pulmonary valve in 50% of cases. Regarding morphometry, we observed that the length varied little with increasing weight of the heart (22.6%), but the height and width increased markedly with increasing weight of the heart. Folia Morphol 2010; 69, 1: 42-4

The impact of failures and successes on affect and self-esteem in young and older adults

Little is known about the impact of success and failure events on age-related changes in affect states and, particularly, in self-esteem levels. To fill this gap in the literature, in the present study changes in affect and self-esteem in 100 young (19 - 30 years) and 102 older adults (65-81 years) were assessed after participants experienced success and failure in a demanding cognitive task. Overall, the success-failure manipulation induced changes on affect states and on state self-esteem, not on trait self-esteem. Regarding age differences, older and young adults were affected to the same extent by experiences of successes and failures. Theoretical considerations of the empirical findings are provided in the general discussion

Estresse por déficit hídrico em plantas forrageiras.

bitstream/CNPC-2010/23051/1/doc89.pd

Searching for Planets in the Hyades II: Some Implications of Stellar Magnetic Activity

The Hyades constitute a homogeneous sample of stars ideal for investigating the dependence of planet formation on the mass of the central star. Due to their youth, Hyades members are much more chromospherically active than stars traditionally surveyed for planets using high precision radial velocity (RV) techniques. Therefore, we have conducted a detailed investigation of whether magnetic activity of our Hyades target stars will interfere with our ability to make precise RV searches for substellar companions. We measure chromospheric activity (which we take as a proxy for magnetic activity) by computing the equivalent of the R'HK activity index from the Ca II K line. is not constant in the Hyades: we confirm that it decreases with increasing temperature in the F stars, and also find it decreases for stars cooler than mid-K. We examine correlations between simultaneously measured R'HK and RV using both a classical statistical test and a Bayesian odds ratio test. We find that there is a significant correlation between R'HK and the RV in only 5 of the 82 stars in this sample. Thus, simple Rprime HK-RV correlations will generally not be effective in correcting the measured RV values for the effects of magnetic activity in the Hyades. We argue that this implies long timescale activity variations (of order a few years; i.e., magnetic cycles or growth and decay of plage regions) will not significantly hinder our search for planets in the Hyades if the stars are closely monitored for chromospheric activity. The trends in the RV scatter (sigma'_v) with , vsini, and P_rot for our stars is generally consistent with those found in field stars in the Lick planet search data, with the notable exception of a shallower dependence of sigma'_v on for F stars.Comment: 15 pages, 7 figures, 3 tables; To appear in the July 2002 issue of The Astronomical Journa

Tracing the identity of Parmigiano Reggiano “Prodotto di Montagna - Progetto Territorio” cheese using NMR spectroscopy and multivariate data analysis

Background Nuclear magnetic resonance (NMR) spectroscopy is one of the well-established tools for food metabolomic analysis, as it proved to be very effective in authenticity and quality control of dairy products, as well as to follow product evolution during processing and storage. The analytical assessment of the EU mountain denomination label, specifically for Parmigiano Reggiano "Prodotto di Montagna - Progetto Territorio" (Mountain-CQ) cheese, has received limited attention. Although it was established in 2012 the EU mountain denomination label has not been much studied from an analytical point of view. Nonetheless, tracing a specific profile for the mountain products is essential to support the value chain of this specialty. Results The aim of the study was to produce an identity profile for Parmigiano Reggiano “Prodotto di Montagna - Progetto Territorio” (Mountain-CQ) cheese, and to differentiate it from Parmigiano Reggiano PDO samples (conventional-PDO) using 1H NMR spectroscopy coupled with multivariate data analysis. Three different approaches were applied and compared. First, the spectra-as-such were analysed after proper preprocessing. For the other two approaches, Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS) was used for signals resolution and features extraction, either individually on manually-defined spectral intervals or by reapplying MCR-ALS on the whole spectra with selectivity constraints using the reconstructed “pure profiles” as initial estimates and targets. All approaches provided comparable information regarding the samples’ distribution, as in all three cases the separation between the two product categories conventional-PDO and Mountain-CQ could be highlighted. Moreover, a novel MATLAB toolbox for features extraction via MCR-ALS was developed and used in synergy with the Chenomx library, allowing for a putative identification of the selected features. Significance A first identity profile for Parmigiano Reggiano “Prodotto di Montagna - Progetto Territorio” obtained by interpreting the metabolites signals in NMR spectroscopy was obtained. Our workflow and toolbox for generating the features dataset allows a more straightforward interpretation of the results, to overcome the limitations due to dimensionality and to peaks overlapping, but also to include the signals assignment and matching since the early stages of the data processing and analysis

A metabolomic data fusion approach to support gliomas grading

Magnetic resonance imaging (MRI) is the current gold standard for the diagnosis of brain tumors. However, despite the development of MRI techniques, the differential diagnosis of central nervous system (CNS) primary pathologies, such as lymphoma and glioblastoma or tumor-like brain lesions and glioma, is often challenging. MRI can be supported by in vivo magnetic resonance spectroscopy (MRS) to enhance its diagnostic power and multiproject-multicenter evaluations of classification of brain tumors have shown that an accuracy around 90% can be achieved for most of the pairwise discrimination problems. However, the survival rate for patients affected by gliomas is still low. The High-Resolution Magic-Angle-Spinning Nuclear Magnetic Resonance (HR-MAS NMR) metabolomics studies may be helpful for the discrimination of gliomas grades and the development of new strategies for clinical intervention. Here, we propose to use T2-filtered, diffusion-filtered and conventional water-presaturated spectra to try to extract as much information as possible, fusing the data gathered by these different NMR experiments and applying a chemometric approach based on Multivariate Curve Resolution (MCR). Biomarkers important for glioma's discrimination were found. In particular, we focused our attention on cystathionine (Cyst) that shows promise as a biomarker for the better prognosis of glioma tumors

A metabolomic data fusion approach to support gliomas grading

Magnetic resonance imaging (MRI) is the current gold standard for the diagnosis of brain tumors. However, despite the development of MRI techniques, the differential diagnosis of central nervous system (CNS) primary pathologies, such as lymphoma and glioblastoma or tumor-like brain lesions and glioma, is often challenging. MRI can be supported by in vivo magnetic resonance spectroscopy (MRS) to enhance its diagnostic power and multiproject-multicenter evaluations of classification of brain tumors have shown that an accuracy around 90% can be achieved for most of the pairwise discrimination problems. However, the survival rate for patients affected by gliomas is still low. The High-Resolution Magic-Angle-Spinning Nuclear Magnetic Resonance (HR-MAS NMR) metabolomics studies may be helpful for the discrimination of gliomas grades and the development of new strategies for clinical intervention. Here, we propose to use T2-filtered, diffusion-filtered and conventional water-presaturated spectra to try to extract as much information as possible, fusing the data gathered by these different NMR experiments and applying a chemometric approach based on Multivariate Curve Resolution (MCR). Biomarkers important for glioma's discrimination were found. In particular, we focused our attention on cystathionine (Cyst) that shows promise as a biomarker for the better prognosis of glioma tumors

Optimization of Supercritical Carbon Dioxide Extraction of Rice Bran Oil and γ-Oryzanol Using Multi-Factorial Design of Experiment

After rice harvesting, the milling processes generate many by-products including husk, bran, germs, and broken rice representing around 40% of the total grain. Bran, one of the external cereal layers, contains proteins, dietary fibers, minerals, and lipids. One of the most common rice bran utilization is the extraction of rice bran oil (RBO). Among all vegetable oils, RBO presents a unique chemical composition rich in antioxidant compounds such as γ-oryzanol that provide several beneficial properties. RBO is generally extracted by exploiting hexane, a solvent toxic to the environment and human health. The growing demand for this oil has led researchers to look for more sustainable extraction techniques. Supercritical carbon dioxide (SC-CO2) has been successfully applied to extract oil and functional compounds from several matrices. In this work, the SC-CO2 extraction of RBO was optimized using a Design of Experiment (DoE) on a pilot scale. "The DoE approach involving multilinear regression allowed modelling the yield in RBO and gamma oryzanol as a function of temperature and pressure, keeping the extraction time constant, as decided by the company. This approach made it possible to optimize the extraction yield and to identify the best temperature (40 °C), while also highlighting that pressure did not play any influential role in the process, at least concerning the analyzed experimental domain on this industrial plant. A model for computing the extraction yield as a function of temperature and pressure was obtained. This study shows that it is possible to obtain good quality RBO, rich in γ-oryzanol and essential fatty acids, using low temperatures and pressures, starting from a rice milling by-product. Graphical Abstract: [Figure not available: see fulltext.