Color adjectives and radical contextualism

Radical contextualists have observed that the content of what is said by the utterance of a sentence is shaped in far-reaching ways by the context of utterance. And they have argued that the ways in which the content of what is said is shaped by context cannot be explained by semantic theory. A striking number of the examples that radical contextualists use to support their view involve sentences containing color adjectives (“red”, “green”, etc.). In this paper, I show how the most sophisticated analysis of color adjectives within the explanatory framework of compositional truth conditional semantics—recently developed by Kennedy and McNally (Synthese 174(1):79–98 2010)—needs to be modified to handle the full range of contextual variation displayed by color adjectives.

Using the significant dust deposition event on the glaciers of Mt. Elbrus, Caucasus Mountains, Russia on 5 May 2009 to develop a method for dating and "provenancing" of desert dust events recorded in snow pack

A significant desert dust deposition event occurred on Mt. Elbrus, Caucasus Mountains, Russia on 5 May 2009, where the deposited dust later appeared as a brown layer in the snow pack. An examination of dust transportation history and analysis of chemical and physical properties of the deposited dust were used to develop a new approach for high-resolution “provenancing” of dust deposition events recorded in snow pack using multiple independent techniques. A combination of SEVIRI red-green-blue composite imagery, MODIS atmospheric optical depth fields derived using the Deep Blue algorithm, air mass trajectories derived with HYSPLIT model and analysis of meteorological data enabled identification of dust source regions with high temporal (hours) and spatial (ca. 100 km) resolution. Dust, deposited on 5 May 2009, originated in the foothills of the Djebel Akhdar in eastern Libya where dust sources were activated by the intrusion of cold air from the Mediterranean Sea and Saharan low pressure system and transported to the Caucasus along the eastern Mediterranean coast, Syria and Turkey. Particles with an average diameter below 8 μm accounted for 90% of the measured particles in the sample with a mean of 3.58 μm, median 2.48 μm. The chemical signature of this long-travelled dust was significantly different from the locally-produced dust and close to that of soils collected in a palaeolake in the source region, in concentrations of hematite. Potential addition of dust from a secondary source in northern Mesopotamia introduced uncertainty in the “provenancing” of dust from this event. Nevertheless, the approach adopted here enables other dust horizons in the snowpack to be linked to specific dust transport events recorded in remote sensing and meteorological data archives.

Using the significant dust deposition event on the glaciers of Mt. Elbrus, Caucasus Mountains, Russia on 5 May 2009 to develop a method for dating and provenancing of desert dust events recorded in snow pack.

A significant desert dust deposition event occurred on Mt. Elbrus, Caucasus Mountains, Russia on 5 May 2009, where the deposited dust later appeared as a brown layer in the snow pack. An examination of dust transportation history and analysis of chemical and physical properties of the deposited dust were used to develop a new approach for high-resolution provenancing of dust deposition events recorded in snow pack using multiple independent techniques. A combination of SEVIRI red-green-blue composite imagery, MODIS atmospheric optical depth fields derived using the Deep Blue algorithm, air mass trajectories derived with HYSPLIT model and analysis of meteorological data enabled identification of dust source regions with high temporal (hours) and spatial (ca. 100 km) resolution. Dust, deposited on 5 May 2009, originated in the foothills of the Djebel Akhdar in eastern Libya where dust sources were activated by the intrusion of cold air from the Mediterranean Sea and Saharan low pressure system and transported to the Caucasus along the eastern Mediterranean coast, Syria and Turkey. Particles with an average diameter below 8 μm accounted for 90% of the measured particles in the sample with a mean of 3.58 μm, median 2.48 μm and the dominant mode of 0.60 μm. The chemical signature of this long-travelled dust was significantly different from the locally-produced dust and close to that of soils collected in a palaeolake in the source region, in concentrations of hematite and oxides of aluminium, manganese, and magnesium. Potential addition of dust from a secondary source in northern Mesopotamia introduced uncertainty in the provenancing of dust from this event. Nevertheless, the approach adopted here enables other dust horizons in the snowpack to be linked to specific dust transport events recorded in remote sensing and meteorological data archives.

An effective approach for land-cover classification from airborne lidar fused with co-registered data

Airborne lidar provides accurate height information of objects on the earth and has been recognized as a reliable and accurate surveying tool in many applications. In particular, lidar data offer vital and significant features for urban land-cover classification, which is an important task in urban land-use studies. In this article, we present an effective approach in which lidar data fused with its co-registered images (i.e. aerial colour images containing red, green and blue (RGB) bands and near-infrared (NIR) images) and other derived features are used effectively for accurate urban land-cover classification. The proposed approach begins with an initial classification performed by the Dempster–Shafer theory of evidence with a specifically designed basic probability assignment function. It outputs two results, i.e. the initial classification and pseudo-training samples, which are selected automatically according to the combined probability masses. Second, a support vector machine (SVM)-based probability estimator is adopted to compute the class conditional probability (CCP) for each pixel from the pseudo-training samples. Finally, a Markov random field (MRF) model is established to combine spatial contextual information into the classification. In this stage, the initial classification result and the CCP are exploited. An efficient belief propagation (EBP) algorithm is developed to search for the global minimum-energy solution for the maximum a posteriori (MAP)-MRF framework in which three techniques are developed to speed up the standard belief propagation (BP) algorithm. Lidar and its co-registered data acquired by Toposys Falcon II are used in performance tests. The experimental results prove that fusing the height data and optical images is particularly suited for urban land-cover classification. There is no training sample needed in the proposed approach, and the computational cost is relatively low. An average classification accuracy of 93.63% is achieved.

Desert dust deposition on Mt. Elbrus, Caucasus Mountains, Russia in 2009-2012 as recorded in snow and shallow ice core: high-resolution "provenancing", transport patterns, physical properties and soluble ionic composition

A record of dust deposition events between 2009 and 2012 on Mt. Elbrus, Caucasus Mountains derived from a snow pit and a shallow ice core is presented for the first time for this region. A combination of isotopic analysis, SEVIRI red-green-blue composite imagery, MODIS atmospheric optical depth fields derived using the Deep Blue algorithm, air mass trajectories derived using the HYSPLIT model and analysis of meteorological data enabled identification of dust source regions with high temporal (hours) and spatial (cf. 20–100 km) resolution. Seventeen dust deposition events were detected; fourteen occurred in March–June, one in February and two in October. Four events originated in the Sahara, predominantly in north-eastern Libya and eastern Algeria. Thirteen events originated in the Middle East, in the Syrian Desert and northern Mesopotamia, from a mixture of natural and anthropogenic sources. Dust transportation from Sahara was associated with vigorous Saharan depressions, strong surface winds in the source region and mid-tropospheric south-westerly flow with daily winds speeds of 20–30 m s−1 at 700 hPa level and, although these events were less frequent, they resulted in higher dust concentrations in snow. Dust transportation from the Middle East was associated with weaker depressions forming over the source region, high pressure centered over or extending towards the Caspian Sea and a weaker southerly or south-easterly flow towards the Caucasus Mountains with daily wind speeds of 12–18 m s−1 at 700 hPa level. Higher concentrations of nitrates and ammonium characterise dust from the Middle East deposited on Mt. Elbrus in 2009 indicating contribution of anthropogenic sources. The modal values of particle size distributions ranged between 1.98 μm and 4.16 μm. Most samples were characterised by modal values of 2.0–2.8 μm with an average of 2.6 μm and there was no significant difference between dust from the Sahara and the Middle East.

Variação no conteúdo protéico e pigmentar em variantes cromáticas de Gracilaria domingensis nas populações naturais de Rio do Fogo-RN, BRASIL

The seaweed Gracilaria domingensis is a common species in the coast of Rio Grande do Norte. This species lives in the intertidal zone, where colour strains (red, green and brown) co-occur during the whole year. Seaweeds that live in this region are exposed to daily changes and to the rhythm of the tide. During the low tide they are exposed to dissection, hiper-or hipo-osmotic shock, high temperatures and high irradiance. The aim of this study was to analyze whether the pigment and protein content of the colour strains of G. domingensis is affected by some environmental parameters in a temporal scale. The seaweeds were collected during 10 months in the seashore of Rio do Fogo (RN). The total soluble proteins and the phycobiliprotein were extracted in phosphate buffer and the carotenoids were analyzed by a standardized method through HPLC-UV. The pigments analysis showed that phycoerithrin is the most abundant pigment in the three strains. This pigment was strongly correlated with nitrogen and the photosynthetically active radiation. Chlorophyll presented higher concentrations than carotenoids during the whole, but the ratio carotenoid/chlorophyll-a was modified by incident radiation. The most abundant carotenoid was ß-carotene and zeaxanthin, which had higher concentrations in the higher radiation months. The concentration increase of zeaxanthin in this period indicated a photoprotective response of the seaweed. The three strains presented a pigment profile that indicates different radiation tolerance profile. Our results pointed that the green strain is better adapted to high irradiance levels than the red and brown strains

Germinação de sementes de melão-de-são-caetano sob variação de água, luz e temperatura

The purpose of this study was to evaluate germination of Momordica charantia L. seeds under different conditions of: water availability (0.0, -0.2, -0.4, -0.6, -0.8 and -1.0 MPa), temperature (10, 15, 20, 25, 30 and 35 degrees C) and quality of incident light (filter dark, red, green, yellow, red off, blue, orange and without filter). For each variable evaluated, experiments were carried out in a completely randomized design with four replicates kept under controlled conditions (germination chamber). There were higher percentages of germination under conditions of mild water restriction (-0.2 MPa) and temperatures around 25 degrees C, regardless of the quality of light. Temperatures below 20 degrees C and above 30 degrees C reduced germination, although lower temperatures had strongly effects on germination. Water availability lower than -0.2 MPa strongly reduced germination, which was inhibited in the treatments of -0.8 and 1.0 MPa.

Compressão auto-adaptativa de imagens coloridas

Image compress consists in represent by small amount of data, without loss a visual quality. Data compression is important when large images are used, for example satellite image. Full color digital images typically use 24 bits to specify the color of each pixel of the Images with 8 bits for each of the primary components, red, green and blue (RGB). Compress an image with three or more bands (multispectral) is fundamental to reduce the transmission time, process time and record time. Because many applications need images, that compression image data is important: medical image, satellite image, sensor etc. In this work a new compression color images method is proposed. This method is based in measure of information of each band. This technique is called by Self-Adaptive Compression (S.A.C.) and each band of image is compressed with a different threshold, for preserve information with better result. SAC do a large compression in large redundancy bands, that is, lower information and soft compression to bands with bigger amount of information. Two image transforms are used in this technique: Discrete Cosine Transform (DCT) and Principal Component Analysis (PCA). Primary step is convert data to new bands without relationship, with PCA. Later Apply DCT in each band. Data Loss is doing when a threshold discarding any coefficients. This threshold is calculated with two elements: PCA result and a parameter user. Parameters user define a compression tax. The system produce three different thresholds, one to each band of image, that is proportional of amount information. For image reconstruction is realized DCT and PCA inverse. SAC was compared with JPEG (Joint Photographic Experts Group) standard and YIQ compression and better results are obtain, in MSE (Mean Square Root). Tests shown that SAC has better quality in hard compressions. With two advantages: (a) like is adaptive is sensible to image type, that is, presents good results to divers images kinds (synthetic, landscapes, people etc., and, (b) it need only one parameters user, that is, just letter human intervention is required

Strutural and optical approach of CdS@ZnS core-shell system

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Papel de sinais cromáticos na identificação de parceiros sexuais em sagüi comum (callithrix jacchus)

The literature concerning color vision shows a trichromatic advantage in detecting ripe fruits and young leaves, but there are contradictory results. There is also the suggestion of this type of vision being adapted to perceive socio-sexual signals. Indeed, Old World primates utilize the skin color of conspecifics as a factor of attraction. But in New World primates there is no record of a coloration signal in the body that can be utilized by other group members. The present study aims to: 1- test whether there is a relation between coloration of body regions and ovulatory cycle in female Callithrix jacchus; 2- Determine if this species uses visual signals to choose mates that are sexually receptive. We collected feces from six females during one month to quantify progesterone concentration by EIA. Body region coloration was measured using a portable spectrometer and modeled to obtain the quantum catch of each photoreceptor, the opponency channels and chromatic distance between the points in units of JND. We recorded the behavior of six males exposed to three pairs of females with a cycling and a non-cycling female in each pair using a transparent plexiglass apparatus. The color of different body regions presented a correlation between progesterone concentration and the yellow-blue and red-green visual axes, with the genitalia as the region showing the highest correlation. The visual axis more apt to see the color variations was the yellow-blue in dichromats, and in trichromats were the red-green to face, yellow-blue to abdomen and both chromatic axes to genitalia. There was no difference in the signal detectability between trichromats and dichromats, but the perception pattern differed between the phenotypes, with a better signal detection by the dichromat phenotype 562 and the trichromat phenotype 543/562. During the behavioral experiments males presented longer gaze duration in periods of experimental manipulation and gaze duration was always longer towards cycling females compared to non-cycling females. Male locomotion during experimental manipulation was greater than in the control only during the periovulatory period of the female, indicating greater excitement. The behavior of cycling females was more active than the behavior of the non-cycling ones regarding locomotion and touching of the plexiglass division of the apparatus. Male gaze duration to cycling females increased with decreasing progesterone concentration, but none of the coloration parameters was correlated to the mate preference exhibited. This coloration signal can transmit information to animals of the group about fertility of female. Different from the intense red of the genitalia swellings of Old World primates, marmoset female genitalia became more bluish-green in the fertile period. Males chose fertile females and were able to visually identify the periovulatory period of females. Choice is related to progesterone concentration, but our results do not show relation between coloration and mate preference. Maybe some behavioral measure is associated with the choice

Spectroscopic properties and upconversion mechanisms in Er3+-doped fluoroindate glasses

Fluorindate glasses containing 1,2,3,4 ErF3 mol % were prepared in a dry box under argon atmosphere. Absorption, Stokes luminescence (under visible and infrared excitation), the dependence of 4S3/2, 4I11/2, and 4I13/2 lifetimes with Er concentration, and upconversion under Ti-saphire laser excitation at λ=790 nm were measured, mostly at T=77 and 300 K. The upconversion results in a strong green emission and weaker blue and red emissions whose intensity obeys a power-law behavior I∼Pn, where P is the infrared excitation power and n=1.6, 2.1, and 2.9 for the red, green, and blue emissions, respectively. The red emission exponent n=1.5 can be explained by a cross relaxation process. The green and blue emissions are due to excited state absorption (ESA) and energy transfer (ET) processes that predict a factor n=2 and n=3 for the green and blue emissions, respectively. From transient measurements we concluded that for lightly doped samples the green upconverted emission is originated due to both processes ESA and ET. However, for heavily doped samples ET is the dominant process.

Superação de dormência e influência dos fatores ambientais na germinação de sementes de Spermacoce latifolia

Understanding basic information on weed biology contributes to the implementation of appropriate management and control strategies. Thus, this work was developed to evaluate the germination of Spermacoce latifolia Aubl. seeds, an important weed in reforestation areas. The seeds were subjected to dormancy break treatments, in which the mechanical scarification, chemical treatment (H2SO 4 and KNO 3), heat treatment, and control, were evaluated. Three more tests were done determinate the effects of temperature (10, 15, 20, 25, 30 and 35°C), light filters (absence of light and red, green, yellow, distant red, blue, orange and clear light) and water availability (0.0, -0.2, -0.4, -0.6, -0.8 and -1.0 MPa) on the seeds germination and vigor. The treatments were arranged in a completely randomized design with four replications, and the experimental plot was constituted by gerbox plastic boxes with 50 seeds. The mechanical scarification (sanding) provided the best dormancy break, indicating that Spermacoce latifolia seeds have tegument water impermeability. The seeds showed higher germination percentage under conditions of mild water stress (-0.2 MPa) and the optimal temperature was 25°C. The blue light reduced seed germination.

Escala diagramática para quantificação da severidade de manchas em folhas de Eucalyptus globulus Labill. causadas por Teratosphaeria nubilosa (Cooke) Crous & U. Braun

The leaf spot (Mycosphaerella leaf disease = MLD) caused by Teratosphaeria nubilosa has caused damage in eucalypt plantations in southern and southeastern Brazil. The need to assess the disease in the field to evaluate of this damage, efficiency control, evaluation of germplasm induces to the necessity of having a visual scale for evaluation of disease. The objective was to develop a diagrammatic scale for young leaves and one for adult leaves of Eucalyptus globules for MLD. To do so, the leaves collected in the field were scanned for image analysis. The damaged area, the healthy leaf area and the external area of the same scale RGB (Red, Green, Blue) were determined. Subsequently, it was determinate the levels of severity depending on the sample distribution with seven levels for young leaves and six for adult leaves. For the visual acuity test and validate the scale, the leaves were evaluated for severity, with and without scale. With this proposed scales, the assessors showed good accuracy both for young and adult leaves with R2=0,98 and R2=0,80, respectively. The importance of the development of diagrammatic scales for assessing MLD in eucalyptus must to the fact that allows quantification of the symptoms accurately and precisely.

Applying machine learning based on multiscale classifiers to detect remote phenology patterns in Cerrado savanna trees

Plant phenology is one of the most reliable indicators of species responses to global climate change, motivating the development of new technologies for phenological monitoring. Digital cameras or near remote systems have been efficiently applied as multi-channel imaging sensors, where leaf color information is extracted from the RGB (Red, Green, and Blue) color channels, and the changes in green levels are used to infer leafing patterns of plant species. In this scenario, texture information is a great ally for image analysis that has been little used in phenology studies. We monitored leaf-changing patterns of Cerrado savanna vegetation by taking daily digital images. We extract RGB channels from the digital images and correlate them with phenological changes. Additionally, we benefit from the inclusion of textural metrics for quantifying spatial heterogeneity. Our first goals are: (1) to test if color change information is able to characterize the phenological pattern of a group of species; (2) to test if the temporal variation in image texture is useful to distinguish plant species; and (3) to test if individuals from the same species may be automatically identified using digital images. In this paper, we present a machine learning approach based on multiscale classifiers to detect phenological patterns in the digital images. Our results indicate that: (1) extreme hours (morning and afternoon) are the best for identifying plant species; (2) different plant species present a different behavior with respect to the color change information; and (3) texture variation along temporal images is promising information for capturing phenological patterns. Based on those results, we suggest that individuals from the same species and functional group might be identified using digital images, and introduce a new tool to help phenology experts in the identification of new individuals from the same species in the image and their location on the ground. © 2013 Elsevier B.V. All rights reserved.

Processamento digital de imagens para identificação da sigatoka negra em bananais utilizando análise de componentes principais e redes neurais artificiais

Pós-graduação em Agronomia (Energia na Agricultura) - FCA