Carbon isotope discrimination and yield of upland rice as affected by drought at flowering

Field experiments involving upland rice genotypes, sown in various dates in late season, were carried out to assess the relationship of carbon isotope discrimination with grain yield and drought resistance. In each one of the three years, one trial was kept under good water availability, while other suffered water shortage for a period of 18-23 days, encompassing panicle emergence and flowering. Drought stress reduced carbon isotope discrimination measured on soluble sugars (deltas) extracted from stem uppermost internode at the end of the imposition period, but had relatively less effect on bulk dry matter of leaves, sampled at the same period, or that of uppermost internodes and grains, sampled at harvest. The drought-induced reduction in deltas was accompanied of reduced spikelet fertility and grain yield. In the three trials subjected to drought, genotypes with the highest yield and spikelet fertility had the lowest deltas. However, this relationship was weak and it was concluded that deltas is not a sufficiently reliable indicator of rice drought resistance to be useful as a screening test in breeding programs. On the other hand, grain yield and spikelet fertility of genotypes which were the soonest to reach 50% flowering within the drought imposition period, were the least adversely affected by drought. Then, timing of drought in relation to panicle emergence and to flowering appeared to be a more important cause of yield variation among genotypes than variation in deltas.

Tire traces: discrimination and classification of pyrolysis-GC/MS profiles

Tire traces can be observed on several crime scenes as vehicles are often used by criminals. The tread abrasion on the road, while braking or skidding, leads to the production of small rubber particles which can be collected for comparison purposes. This research focused on the statistical comparison of Py-GC/MS profiles of tire traces and tire treads. The optimisation of the analytical method was carried out using experimental designs. The aim was to determine the best pyrolysis parameters regarding the repeatability of the results. Thus, the pyrolysis factor effect could also be calculated. The pyrolysis temperature was found to be five time more important than time. Finally, a pyrolysis at 650 °C during 15 s was selected. Ten tires of different manufacturers and models were used for this study. Several samples were collected on each tire, and several replicates were carried out to study the variability within each tire (intravariability). More than eighty compounds were integrated for each analysis and the variability study showed that more than 75% presented a relative standard deviation (RSD) below 5% for the ten tires, thus supporting a low intravariability. The variability between the ten tires (intervariability) presented higher values and the ten most variant compounds had a RSD value above 13%, supporting their high potential of discrimination between the tires tested. Principal Component Analysis (PCA) was able to fully discriminate the ten tires with the help of the first three principal components. The ten tires were finally used to perform braking tests on a racetrack with a vehicle equipped with an anti-lock braking system. The resulting tire traces were adequately collected using sheets of white gelatine. As for tires, the intravariability for the traces was found to be lower than the intervariability. Clustering methods were carried out and the Ward's method based on the squared Euclidean distance was able to correctly group all of the tire traces replicates in the same cluster than the replicates of their corresponding tire. Blind tests on traces were performed and were correctly assigned to their tire source. These results support the hypothesis that the tested tires, of different manufacturers and models, can be discriminated by a statistical comparison of their chemical profiles. The traces were found to be not differentiable from their source but differentiable from all the other tires present in the subset. The results are promising and will be extended on a larger sample set.

Characterization and discrimination of soils by their reflected electromagnetic energy

The objective of this work was to verify if reflected energy of soils can characterize and discriminate them. A spectroradiometer (Spectral reflectance between: 400-2,500 nm) was utilized in laboratory. The soils evaluated are located in Bauru region, SP, Brazil, and are classified as Typic Argiudoll (TR), Typic Eutrorthox (LR), Typic Argiudoll (PE), Typic Haplortox (LE), Typic Paleudalf (PV) and Typic Quartzipsamment (AQ). They were characterized by their spectral reflectance as for descriptive conventional methods (Brazilian and International) according to the types of spectral curves. A method for the spectral descriptive evaluation of soils was established. It was possible to characterize and discriminate the soils by their spectral reflectance, with exception for LR and TR. The spectral differences were better identified by the general shape of spectral curves, by the intensity of band absorption and angle tendencies. These characteristics were mainly influenced by organic matter, iron, granulometry and mineralogy constituents. A reduction of iron and clay contents, which influenced higher reflectance intensity and shape variations, occurred on the soils LR/TR, PE, LE, PV and AQ, on that sequence. Soils of the same group with different clay textures could be discriminated. The conventional descriptive evaluation of spectral curves was less efficient on discriminating soils. Simulated orbital data discriminated soils mainly by bands 5 and 7.

Color differences among feral pigeons (Columba livia) are not attributable to sequence variation in the coding region of the melanocortin-1 receptor gene (MC1R)

Genetic variation at the melanocortin-1 receptor (MC1R) gene is correlated with melanin color variation in many birds. Feral pigeons (Columba livia) show two major melanin-based colorations: a red coloration due to pheomelanic pigment and a black coloration due to eumelanic pigment. Furthermore, within each color type, feral pigeons display continuous variation in the amount of melanin pigment present in the feathers, with individuals varying from pure white to a full dark melanic color. Coloration is highly heritable and it has been suggested that it is under natural or sexual selection, or both. Our objective was to investigate whether MC1R allelic variants are associated with plumage color in feral pigeons.We sequenced 888 bp of the coding sequence of MC1R among pigeons varying both in the type, eumelanin or pheomelanin, and the amount of melanin in their feathers. We detected 10 non-synonymous substitutions and 2 synonymous substitution but none of them were associated with a plumage type. It remains possible that non-synonymous substitutions that influence coloration are present in the short MC1R fragment that we did not sequence but this seems unlikely because we analyzed the entire functionally important region of the gene.Our results show that color differences among feral pigeons are probably not attributable to amino acid variation at the MC1R locus. Therefore, variation in regulatory regions of MC1R or variation in other genes may be responsible for the color polymorphism of feral pigeons.

Color sensation in figurative painting

The figurative painter accesses very complex levels of knowledge. To produce a painting requires, first, a deep analysis of the image of the reality and, afterwards, the study of the reconstruction of this reality. This is not about a process of copying, but a process of the comprehension of the concepts that appear in the representation. The drawing guides us in the process of the production of the surface and in the distribution of the colours that, after all, are the data with which the vision mechanism builds the visual reality. Knowing the colour and its behaviour have always been a requirement for the figurative painter. From that knowledge we can draw wider conclusions.

EEG windowed statistical wavelet scoring for evaluation and discrimination of muscular artifacts

EEG recordings are usually corrupted by spurious extra-cerebral artifacts, which should be rejected or cleaned up by the practitioner. Since manual screening of human EEGs is inherently error prone and might induce experimental bias, automatic artifact detection is an issue of importance. Automatic artifact detection is the best guarantee for objective and clean results. We present a new approach, based on the time–frequency shape of muscular artifacts, to achieve reliable and automatic scoring. The impact of muscular activity on the signal can be evaluated using this methodology by placing emphasis on the analysis of EEG activity. The method is used to discriminate evoked potentials from several types of recorded muscular artifacts—with a sensitivity of 98.8% and a specificity of 92.2%. Automatic cleaning ofEEGdata are then successfully realized using this method, combined with independent component analysis. The outcome of the automatic cleaning is then compared with the Slepian multitaper spectrum based technique introduced by Delorme et al (2007 Neuroimage 34 1443–9).

The use of micro-XRD for the study of glaze color decorations

The compounds responsible for the colours and decorations in glass and glazed ceramics include: colouring agents (transition metal ions), pigments (micro-and nano-precipitates of compounds that either do not dissolve or recrystallize in the glassy matrix) and opacifiers (microcrystalline compounds with high light scattering capability). Their composition, structure and range of stability are highly dependent not only on the composition but also on the procedures followed to obtain them. Chemical composition of the colorants and crystallites may be obtained by means of SEM-EDX and WDX. Synchrotron Radiation micro-X-ray Diffraction has a small beam size adequate (10 to 50 microns footprint size) to obtain the structural information of crystalline compounds and high brilliance, optimal for determining the crystallites even when present in low amounts. In addition, in glass decorations the crystallites often appear forming thin layers (from 10 to 100 micrometers thick) and they show a depth dependent composition and crystal structure. Their nature and distribution across the glass/glazes decorations gives direct information on the technology of production and stability and may be related to the color and appearance. A selection of glass and glaze coloring agents and decorations are studied by means of SR-micro- XRD and SEM-EDX including: manganese brown, antimony yellow, red copper lusters and cobalt blue. The selection includes Medieval (Islamic, and Hispano Moresque) and renaissance tin glazed ceramics from the 10th to the 17th century AD.

Coherency and sharpness measures by using ICA algorithms. An investigation for Alzheimer’s disease discrimination

In this paper, we present a comprehensive study of different Independent Component Analysis (ICA) algorithms for the calculation of coherency and sharpness of electroencephalogram (EEG) signals, in order to investigate the possibility of early detection of Alzheimer’s disease (AD). We found that ICA algorithms can help in the artifact rejection and noise reduction, improving the discriminative property of features in high frequency bands (specially in high alpha and beta ranges). In addition to different ICA algorithms, the optimum number of selected components is investigated, in order to help decision processes for future works.

Investigation of ICA algorithms for feature extraction of EEG signals in discrimination of Alzheimer disease

In this paper we present a quantitative comparisons of different independent component analysis (ICA) algorithms in order to investigate their potential use in preprocessing (such as noise reduction and feature extraction) the electroencephalogram (EEG) data for early detection of Alzhemier disease (AD) or discrimination between AD (or mild cognitive impairment, MCI) and age-match control subjects.

Retrieving Cloud Characteristics from Ground-Based Daytime Color All-Sky Images

A discussion is presented of daytime sky imaging and techniques that may be applied to the analysis of full-color sky images to infer cloud macrophysical properties. Descriptions of two different types of skyimaging systems developed by the authors are presented, one of which has been developed into a commercially available instrument. Retrievals of fractional sky cover from automated processing methods are compared to human retrievals, both from direct observations and visual analyses of sky images. Although some uncertainty exists in fractional sky cover retrievals from sky images, this uncertainty is no greater than that attached to human observations for the commercially available sky-imager retrievals. Thus, the application of automatic digital image processing techniques on sky images is a useful method to complement, or even replace, traditional human observations of sky cover and, potentially, cloud type. Additionally, the possibilities for inferring other cloud parameters such as cloud brokenness and solar obstruction further enhance the usefulness of sky imagers

The Law of Lending Discrimination, June 2010

The purpose of this article is two-fold. First, it provides an overview of the types of lending discrimination, discusses what laws apply to lending discrimination, and explains how to establish a prima facie case and pretext. This discussion will borrow concepts and case law from the areas of employment discrimination and the related issue of rental discrimination. Each of these areas share similar required elements as well as the need to establish pre-text. Second, this article provides an overview of predatory lending practices, applicable law, and potential remedies.