Conversion of a digital camera into a non-contact colorimeter for use in stone cultural heritage: The application case to Spanish granites

In this study, a digital CMOS camera was calibrated for use as a non-contact colorimeter for measuring the color of granite artworks. The low chroma values of the granite, which yield similar stimulation of the three color channels of the camera, proved to be the most challenging aspect of the task. The appropriate parameters for converting the device-dependent RGB color space into a device-independent color space were established. For this purpose, the color of a large number of Munsell samples (corresponding to the previously defined color gamut of granite) was measured with a digital camera and with a spectrophotometer (reference instrument). The color data were then compared using the CIELAB color formulae. The best correlations between measurements were obtained when the camera works to 10-bits and the spectrophotometric measures in SCI mode. Finally, the calibrated instrument was used successfully to measure the color of six commercial varieties of Spanish granite.

Evolutionary history of the recruitment of conserved developmental genes in association to the formation and diversification of a novel trait

The origin and modification of novel traits are important aspects of biological diversification. Studies combining concepts and approaches of developmental genetics and evolutionary biology have uncovered many examples of the recruitment, or co-option, of genes conserved across lineages for the formation of novel, lineage-restricted traits. However, little is known about the evolutionary history of the recruitment of those genes, and of the relationship between them -for example, whether the co-option involves whole or parts of existing networks, or whether it occurs by redeployment of individual genes with de novo rewiring. We use a model novel trait, color pattern elements on butterfly wings called eyespots, to explore these questions. Eyespots have greatly diversified under natural and sexual selection, and their formation involves genetic circuitries shared across insects.

A near real-time water surface detection method based on HSV transformation of MODIS multi-Spectral time series data

In the face of global population growth and the uneven distribution of water supply, a better knowledge of the spatial and temporal distribution of surface water resources is critical. Remote sensing provides a synoptic view of ongoing processes, which addresses the intricate nature of water surfaces and allows an assessment of the pressures placed on aquatic ecosystems. However, the main challenge in identifying water surfaces from remotely sensed data is the high variability of spectral signatures, both in space and time. In the last 10 years only a few operational methods have been proposed to map or monitor surface water at continental or global scale, and each of them show limitations. The objective of this study is to develop and demonstrate the adequacy of a generic multi-temporal and multi-spectral image analysis method to detect water surfaces automatically, and to monitor them in near-real-time. The proposed approach, based on a transformation of the RGB color space into HSV, provides dynamic information at the continental scale. The validation of the algorithm showed very few omission errors and no commission errors. It demonstrates the ability of the proposed algorithm to perform as effectively as human interpretation of the images. The validation of the permanent water surface product with an independent dataset derived from high resolution imagery, showed an accuracy of 91.5% and few commission errors. Potential applications of the proposed method have been identified and discussed. The methodology that has been developed 27 is generic: it can be applied to sensors with similar bands with good reliability, and minimal effort. Moreover, this experiment at continental scale showed that the methodology is efficient for a large range of environmental conditions. Additional preliminary tests over other continents indicate that the proposed methodology could also be applied at the global scale without too many difficulties

Insulin-like growth factor-I gene expression as a growth indicator in Nile tilapia Oreochromis niloticus L.

Somatic growth in fishes is regulated by a variety of hormones. A central step in this hormonal network is the growth hormone-insulin-like growth factor-I (IGF-I) axis. Studies conducted evaluated the relationship of hepatic IGF-I (hIGF-1) mRNA with growth as affected by feeding regimes (satiation or restricted level; daily or alternate-day feeding), temperatures (high, ambient, low) and by social stress. To develop a cellular means for the quantification of hIGF-I mRNA levels in O. niloticus, hIGF-I cDNA was isolated and cloned. The partial sequence of IGF-I cDNA encodes for signal peptide, mature protein and a portion of the E-domain. A sensitive TaqMan quantitative reverse transcription-polymerase chain reaction (qRT-PCR) assay was developed based on the mature IGF-I. Using the developed qRT-PCR assay a significant positive correlation was observed between hIGF-I mRNA levels and growth rate of fish reared under different feeding regimes (r = 0.64) and temperature conditions (r = 0.64). On the dynamics of hIGF-I gene expression in response to elevated temperature, hIGF-I mRNA levels were significantly elevated after at least 2 days of exposure to warm temperature. This validates the concept that hIGF-I gene expressions are sufficiently sensitive to be used as a rapid growth rate indicator for O. niloticus. The hIGF-I levels have a significant positive correlation with specific growth rate (length; r = 0.92), and with condition factor (r = 0.55). On the effect of social stress, differential alterations in growth rates between the dominant and subordinates were observed which was attributed more to behavioral changes as transduced by physiological regulators. The fish's relative position in the social hierarchy was consistently reflected in the levels of hIGF-I mRNA and the eye color pattern. Subordination depressed hIGF-I levels while dominance stimulated it. These findings have shown that hGF-I level remained positively correlated to growth rate as affected by feeding regime, temperature and social stress. This suggests that hIGF-I plays a key role in controlling growth in O. niloticus and indicates that IGF-I mRNA quantification could prove useful for the rapid assessment of growth rate in this species of fish.

Pomacanthus maculosus (Forsskål, 1775)

This is one of the largest species of angelfish reaching almost 20 inches (50cm) in length. As an adult it has a violet blue body with a large yellow blotch on the side that some say resembles the continent of Africa. As a juvenile it is similar in appearance (and easily confused with) other young Pomacanthus, especially the Blue-ring Angelfish P. annularis. But as its color pattern begins to metamorphosis, the sub-adult begins to look very much like the Arabian Angelfish P. asfur. It will have a similar looking vertical yellow bar on its body, but lack the bright yellow tailfin of the Arabian Angel. Its yellow marking develops as a characteristic "yellowband", finally becoming more prominent and blotch-like as the fish ages. Hence this fish is also known by a number of descriptive common names including Yellowbar Angelfish, Half Moon Angelfish, Map Angelfish, Yellow-Band Angelfish, Yellow-blotch Angelfish, Blue-moon Angelfish, and more.

Caracterização ambiental de bancos areno-lamosos nos campos petrolíferos de Macau e Serra (RN), como subsídio às medidas mitigadoras ao processo erosivo

On Rio Grande do Norte northern coast the process of sediment transport are intensely controlled by wind and sea (waves and currents) action, causing erosion and shoreline morphological instability. Due to the importance of such coastal zone it was realized the multi-spectral mapping and physical-chemical characterization of mudflats and mangroves aiming to support the mitigating actions related to the containment of the erosive process on the oil fields of Macau and Serra installed at the study area. The multi-spectral bands of 2000 and 2008 LANDSAT 5 TM images were submitted on the several digital processing steps and RGB color compositions integrating spectral bands and Principal Components. Such processing methodology was important to the mapping of different units on surface, together with field works. It was possible to make an analogy of the spectral characteristics of wetlands with vegetations areas (mangrove), showing the possibility to make a restoration of this area, contributing with the environmental monitoring of that ecosystem. The maps of several units were integrated in GIS environment at 1:60,000 scale, including the classification of features according to the presence or absence of vegetation cover. Thus, the strategy of methodology established that there are 10.13 km2 at least of sandy-muddy and of these approximately 0.89 km2 with the possibility to be used in a reforestation of typical flora of mangrove. The physical-chemical characterization showed areas with potential to introduce local species of mangrove and they had a pH above neutral with a mean of 8.4. The characteristic particle size is sand in the fine fractions, the high levels of carbonate, organic matter and major and trace element in general are concentrated where the sediment had the less particles size, showing the high correlation that those elements have with smaller particles of sediment. The application of that methodological strategy is relevant to the better understanding of features behavior and physical-chemical data of sediment samples collected on field allow the analysis of efficiency/capability of sandy-muddy to reforestation with local mangrove species for mitigation of the erosive action and coastal processes on the areas occupied by the oil industry

Superpixel-based roughness measure for multispectral satellite image segmentation

The new generation of artificial satellites is providing a huge amount of Earth observation images whose exploitation can report invaluable benefits, both economical and environmental. However, only a small fraction of this data volume has been analyzed, mainly due to the large human resources needed for that task. In this sense, the development of unsupervised methodologies for the analysis of these images is a priority. In this work, a new unsupervised segmentation algorithm for satellite images is proposed. This algorithm is based on the rough-set theory, and it is inspired by a previous segmentation algorithm defined in the RGB color domain. The main contributions of the new algorithm are: (i) extending the original algorithm to four spectral bands; (ii) the concept of the superpixel is used in order to define the neighborhood similarity of a pixel adapted to the local characteristics of each image; (iii) and two new region merged strategies are proposed and evaluated in order to establish the final number of regions in the segmented image. The experimental results show that the proposed approach improves the results provided by the original method when both are applied to satellite images with different spectral and spatial resolutions.