997 resultados para Chemical Classification
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ABSTRACT INTRODUCTION: In this study, we evaluated the chemical composition of a commercial sample of essential oil from Eucalyptus smithii R.T. Baker and its antifungal activity against Microsporum canis ATCC 32903, Microsporum gypseum ATCC 14683, Trichophyton mentagrophytes ATCC 9533, T. mentagrophytes ATCC 11480, T. mentagrophytes ATCC 11481, and Trichophyton rubrum CCT 5507. METHODS: Morphological changes in these fungi after treatment with the oil were determined by scanning electron microscopy (SEM). The antifungal activity of the oil was determined on the basis of minimum inhibitory concentration (MIC) and minimum fungicidal concentration (MFC) values. RESULTS: The compound 1,8-cineole was found to be the predominant component (72.2%) of the essential oil. The MIC values of the oil ranged from 62.5μg·mL−1 to >1,000μg·mL−1, and the MFC values of the oil ranged from 125μg·mL−1 to >1,000μg·mL−1. SEM analysis showed physical damage and morphological alterations in the fungi exposed to this oil. CONCLUSIONS: We demonstrated the potential of Eucalyptus smithii essential oil as a natural therapeutic agent for the treatment of dermatophytosis.
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Remote sensing - the acquisition of information about an object or phenomenon without making physical contact with the object - is applied in a multitude of different areas, ranging from agriculture, forestry, cartography, hydrology, geology, meteorology, aerial traffic control, among many others. Regarding agriculture, an example of application of this information is regarding crop detection, to monitor existing crops easily and help in the region’s strategic planning. In any of these areas, there is always an ongoing search for better methods that allow us to obtain better results. For over forty years, the Landsat program has utilized satellites to collect spectral information from Earth’s surface, creating a historical archive unmatched in quality, detail, coverage, and length. The most recent one was launched on February 11, 2013, having a number of improvements regarding its predecessors. This project aims to compare classification methods in Portugal’s Ribatejo region, specifically regarding crop detection. The state of the art algorithms will be used in this region and their performance will be analyzed.
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Soil conditions under pasture were examined in a range of sites representing the sequence of conversion of forest to pasture at two locations in the vicinity of Ilha de Maracã, Roraima. Comparisons were made with adjacent savana. Soil bulk densities shown to increase after forest clearance and soil chemical data indicate that the initial beneficial effects on nutrient supply of burning forest debris are rather short-lived. Very low levels of available phosphorus prevail in areas of savanna and cultivated pasture of all ages. Variations in the status of older cultivated pastures are mainly attributable to different grazing levelt.
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The species composition of the seasonal várzea forest growing on a bank of the Ilha de Marchantaria / lower Solimões-Amazonas River, Brazil was studied in an area of slightly less than one hectare. Two biomass plots were harvested. Forty-seven arboreal species representing 46 genera in 25 families were recorded. Tree density was 1086 per hectare. Total basal area was 45 m2 ha1. Mean species density was 6.5 ± 1.98 per 100 m2. The most abundant species were Crataeva benthamii(Capparidaceae), Laetia corymbutosa(Flacourtiaceae) and Vitex cymosa(Verbenaceae). The highest basal area per species was 10.2 m2 for Pseudobombax munguba(Bombacaceae). The common species are known to be typical floristic elements of the seasonal varzea forest. Above ground dry biomass was equal to 97 and 255 t ha', respectively. Its chemical composition is characterized by comparatively high bioelement contents equal to 2.4 percent on the average. Calcium was the most important bioelement. Structure of the forest and age darings of trees allow the successional classification of the stands.
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Grasslands in semi-arid regions, like Mongolian steppes, are facing desertification and degradation processes, due to climate change. Mongolia’s main economic activity consists on an extensive livestock production and, therefore, it is a concerning matter for the decision makers. Remote sensing and Geographic Information Systems provide the tools for advanced ecosystem management and have been widely used for monitoring and management of pasture resources. This study investigates which is the higher thematic detail that is possible to achieve through remote sensing, to map the steppe vegetation, using medium resolution earth observation imagery in three districts (soums) of Mongolia: Dzag, Buutsagaan and Khureemaral. After considering different thematic levels of detail for classifying the steppe vegetation, the existent pasture types within the steppe were chosen to be mapped. In order to investigate which combination of data sets yields the best results and which classification algorithm is more suitable for incorporating these data sets, a comparison between different classification methods were tested for the study area. Sixteen classifications were performed using different combinations of estimators, Landsat-8 (spectral bands and Landsat-8 NDVI-derived) and geophysical data (elevation, mean annual precipitation and mean annual temperature) using two classification algorithms, maximum likelihood and decision tree. Results showed that the best performing model was the one that incorporated Landsat-8 bands with mean annual precipitation and mean annual temperature (Model 13), using the decision tree. For maximum likelihood, the model that incorporated Landsat-8 bands with mean annual precipitation (Model 5) and the one that incorporated Landsat-8 bands with mean annual precipitation and mean annual temperature (Model 13), achieved the higher accuracies for this algorithm. The decision tree models consistently outperformed the maximum likelihood ones.
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Premature degradation of ordinary Portland cement (OPC) concrete infrastructures is a current and serious problem with overwhelming costs amounting to several trillion dollars. The use of concrete surface treatments with waterproofing materials to prevent the access of aggressive substances is an important way of enhancing concrete durability. The most common surface treatments use polymeric resins based on epoxy, silicone (siloxane), acrylics, polyurethanes or polymethacrylate. However, epoxy resins have low resistance to ultraviolet radiation while polyurethanes are sensitive to high alkalinity environments. Geopolymers constitute a group of materials with high resistance to chemical attack that could also be used for coating of concrete infrastructures exposed to harsh chemical environments. This article presents results of an experimental investigation on the resistance to chemical attack (by sulfuric and nitric acid) of several materials: OPC concrete, high performance concrete (HPC), epoxy resin, acrylic painting and a fly ash based geopolymeric mortar. Three types of acids, each with high concentrations of 10%, 20% and 30%, were used to simulate long term degradation by chemical attack. The results show that the epoxy resin had the best resistance to chemical attack, irrespective of the acid type and acid concentration.
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Given the current economic situation of the Portuguese municipalities, it is necessary to identify the priority investments in order to achieve a more efficient financial management. The classification of the road network of the municipality according to the occurrence of traffic accidents is fundamental to set priorities for road interventions. This paper presents a model for road network classification based on traffic accidents integrated in a geographic information system. Its practical application was developed through a case study in the municipality of Barcelos. An equation was defined to obtain a road safety index through the combination of the following indicators: severity, property damage only and accident costs. In addition to the road network classification, the application of the model allows to analyze the spatial coverage of accidents in order to determine the centrality and dispersion of the locations with the highest incidence of road accidents. This analysis can be further refined according to the nature of the accidents namely in collision, runoff and pedestrian crashes.
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Dissertação de mestrado em Bioinformática
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Essential oils from leaves and fruits of Protiumheptaphyllum collected in Tamandaré beach Pernambuco/Brazil were analysed by GC/MS and tested for toxicity and repellent effect against the two spotted spider mite (Tetranychus urticae). The major constituent identified in the fruits was alpha-terpinene (47.6 %) whereas oil from leaf contained mainly sesquiterpenes such as 9-epi-caryophyllene (21.4 %), trans-isolongifolanone (10.7 %) and 14-hydroxi-9-epi-caryophyllene (16.7 %). The fruit oil was found to be more effective against the mite when compared to the leaf oil. Both showed mortality properties and oviposition deterrence in higher concentration (10 µl.l-1 air), but only the essential oil from fruits induced repellence on T. urticae.
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Poly(vinylidene fluoride), PVDF, has been blended with different ionic liquids (IL) in order to evaluate the effect of the different IL anions and cations on the electroative -phase, thermal, mechanical and electrical properties of the polymer blend. [C2MIM][Cl], [C6MIM][Cl], [C10MIM][Cl], [C2MIM][NTf2], [C6MIM][NTf2], [C10MIM][NTf2] have been selected and were introduced in the polymer at a weight percentage of 40 wt%. It was found that the incorporation of ILs into the PVDF matrix leads to an increase of the -phase content due to the strong electrostatic interactions between the dipolar moments of PVDF and the ILs. Further, the incorporation of ILs into PVDF strongly decreases the elastic modulus and increases the electrical conductivity of the blend with respect to the pure polymer matrix, all these effects being accompanied by a modification of the crystallization kinetics, as indicated by the modified spherulitic microstructure. Thus, novel PVDF/IL blends films with high transparency, excellent antistatic properties, and highly polar crystal form fraction were successfully achieved.
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Propolis is a chemically complex biomass produced by honeybees (Apis mellifera) from plant resins added of salivary enzymes, beeswax, and pollen. The biological activities described for propolis were also identified for donor plants resin, but a big challenge for the standardization of the chemical composition and biological effects of propolis remains on a better understanding of the influence of seasonality on the chemical constituents of that raw material. Since propolis quality depends, among other variables, on the local flora which is strongly influenced by (a)biotic factors over the seasons, to unravel the harvest season effect on the propolis chemical profile is an issue of recognized importance. For that, fast, cheap, and robust analytical techniques seem to be the best choice for large scale quality control processes in the most demanding markets, e.g., human health applications. For that, UV-Visible (UV-Vis) scanning spectrophotometry of hydroalcoholic extracts (HE) of seventy-three propolis samples, collected over the seasons in 2014 (summer, spring, autumn, and winter) and 2015 (summer and autumn) in Southern Brazil was adopted. Further machine learning and chemometrics techniques were applied to the UV-Vis dataset aiming to gain insights as to the seasonality effect on the claimed chemical heterogeneity of propolis samples determined by changes in the flora of the geographic region under study. Descriptive and classification models were built following a chemometric approach, i.e. principal component analysis (PCA) and hierarchical clustering analysis (HCA) supported by scripts written in the R language. The UV-Vis profiles associated with chemometric analysis allowed identifying a typical pattern in propolis samples collected in the summer. Importantly, the discrimination based on PCA could be improved by using the dataset of the fingerprint region of phenolic compounds ( = 280-400m), suggesting that besides the biological activities of those secondary metabolites, they also play a relevant role for the discrimination and classification of that complex matrix through bioinformatics tools. Finally, a series of machine learning approaches, e.g., partial least square-discriminant analysis (PLS-DA), k-Nearest Neighbors (kNN), and Decision Trees showed to be complementary to PCA and HCA, allowing to obtain relevant information as to the sample discrimination.
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This paper reports the first attempt of characterizing various physical, mechanical and chemical properties of Quiscal fibres, used by the native communities in Chile and investigating the influence of atmospheric dielectric barrier discharge plasma treatment on various properties such as diameter and linear density, fat, wax and impurity%, moisture regain, chemical elements and groups, thermal degradation, surface morphology, etc. According to the experimental observations, Quiscal fibre has lower tenacity than most of the technical grade natural fibres such as sisal, hemp, flax, etc., and plasma treatment at optimum dose improved its tenacity to the level of sisal fibres. Plasma treatment also reduced the amount of fat, wax and other foreign impurities present in Quiscal fibres as well as removed lignin and hemicellulose partially from the fibre structure. Plasma treatment led to functionalization of Quiscal fibre surface with chemical groups, as revealed from attenuated total reflection spectroscopy and also confirmed from the elemental analysis using energy dispersive Xray technique and pH and conductivity measurements of fibre aqueous extract. The wetting behavior of Quiscal fibre also improved considerably through plasma treatment. However, untreated and plasma treated Quiscal fibres showed similar thermal degradation behavior, except the final degradation stage, in which plasma treated fibres showed higher stability and incomplete degradation unlike the untreated fibres. The experimental results suggested that the plasma treated Quiscal fibres, like other technical grade natural fibres, can find potential application as reinforcement of composite materials for various industrial applications.
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Las fibras del seudotallo de plátano (FSP) fueron modificadas mediante epiclorhidrina (EP), anhídrido acético (AA), y su combinación (AA_EP), y con plasma a tres descargas de barrera dieléctrica (DBD) 1, 3 y 6 kW min m-2. Las FSP tratadas y sin tratar fueron caracterizadas mediante espectroscopia infrarroja por la transformada de Fourier (FT-IR), termogravimetría (TGA), microscopía electrónica de barrido (SEM) y pruebas mecánicas de tensión y de humectabilidad. Los espectros FT-IR, las micrografías SEM, y el análisis TGA indicaron pérdidas de lignina, hemicelulosa, impurezas y ceras. Estos efectos en conjunto con las reacciones de grupos OH y -C-C-, con los tratamientos químicos y de plasma respectivamente, incrementaron la hidrofobicidad de las FSP tratadas. Los tratamientos químicos produjeron reacciones de esterificación, eterificación y entrecruzamiento de los grupos OH libres en las FSP, lo que hizo que mostraran mayor rigidez que las expuestas al plasma. Las micrografías SEM mostraron que las FSP expuestas al plasma quedaron con superficie más irregular y rugosa que la de las FSP tratadas químicamente. La humectabilidad de las fibras, medida mediante pruebas de ángulo de contacto, se redujo como consecuencia de ambos tratamientos, característica importante para un relleno en los materiales compuestos.
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Qualitative and quantitative analyses of the volatile constituents from resin of Protium heptaphyllum (Aubl.) Marchand subsp. ulei (Swat) Daly (PHU), and Protium heptaphyllum (Aubl.) Marchand subsp. heptaphyllum (PHH), Burseraceae were performed using GC-MS and GC-FID. The resins were collected around the city of Cruzeiro do Sul, state of Acre, Brazil. Essential oils from the two subspecies were extracted by hydrodistillation with a yield of 8.6% (PHU) and 11.3% (PHH); the main components were terpinolene (42.31%) and p-cymene (39.93%) for subspecies ulei (PHU) and heptaphyllum (PHH), respectively.