992 resultados para spectral composition


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This paper explores models of teaching and learning music composition in higher education. It analyses the pedagogical approaches apparent in the literature on teaching and learning composition in schools and universities, and introduces a teaching model as: learning from the masters; mastery of techniques; exploring ideas; and developing voice. It then presents a learning model developed from a qualitative study into students’ experiences of learning composition at university as: craft, process and art. The relationship between the students’ experiences and the pedagogical model is examined. Finally, the implications for composition curricula in higher education are presented.

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The dynamics of droplets exhaled from the respiratory system during coughing or talking is addressed. A mathematical model is presented accounting for the motion of a droplet in conjunction with its evaporation. Droplet evaporation and motion are accounted for under two scenarios: 1) A well mixed droplet and 2) A droplet with inner composition variation. A multiple shells model was implemented to account for internal mass and heat transfer and for concentration and temperature gradients inside the droplet. The trajectories of the droplets are computed for a range of conditions and the spatial distribution and residence times of such droplets are evaluated.

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The use of appropriate features to characterize an output class or object is critical for all classification problems. This paper evaluates the capability of several spectral and texture features for object-based vegetation classification at the species level using airborne high resolution multispectral imagery. Image-objects as the basic classification unit were generated through image segmentation. Statistical moments extracted from original spectral bands and vegetation index image are used as feature descriptors for image objects (i.e. tree crowns). Several state-of-art texture descriptors such as Gray-Level Co-Occurrence Matrix (GLCM), Local Binary Patterns (LBP) and its extensions are also extracted for comparison purpose. Support Vector Machine (SVM) is employed for classification in the object-feature space. The experimental results showed that incorporating spectral vegetation indices can improve the classification accuracy and obtained better results than in original spectral bands, and using moments of Ratio Vegetation Index obtained the highest average classification accuracy in our experiment. The experiments also indicate that the spectral moment features also outperform or can at least compare with the state-of-art texture descriptors in terms of classification accuracy.

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We have recently demonstrated the geographic isolation of rice tungro bacilliform virus (RTBV) populations in the tungro-endemic provinces of Isabela and North Cotabato, Philippines. In this study, we examined the genetic structure of the virus populations at the tungro-outbreak sites of Lanao del Norte, a province adjacent to North Cotabato. We also analyzed the virus populations at the tungro-endemic sites of Subang, Indonesia, and Dien Khanh, Vietnam. Total DNA extracts from 274 isolates were digested with EcoRV restriction enzyme and hybridized with a full-length probe of RTBV. In the total population, 22 EcoRV-restricted genome profiles (genotypes) were identified. Although overlapping genotypes could be observed, the outbreak sites of Lanao del Norte had a genotype combination distinct from that of Subang or Dien Khanh but a genotype combination similar to that identified earlier from North Cotabato, the adjacent endemic province. Sequence analysis of the intergenic region and part of the ORF1 RTBV genome from randomly selected genotypes confirms the geographic clustering of RTBV genotypes and, combined with restriction analysis, the results suggest a fragmented spatial distribution of RTBV local populations in the three countries. Because RTBV depends on rice tungro spherical virus (RTSV) for transmission, the population dynamics of both tungro viruses were then examined at the endemic and outbreak sites within the Philippines. The RTBV genotypes and the coat protein RTSV genotypes were used as indicators for virus diversity. A shift in population structure of both viruses was observed at the outbreak sites with a reduced RTBV but increased RTSV gene diversity

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The NIR spectra of reichenbachite, scholzite and parascholzite have been studied at 298 K. The spectra of the minerals are different, in line with composition and crystal structural variations. Cation substitution effects are significant in their electronic spectra and three distinctly different electronic transition bands are observed in the near-infrared spectra at high wavenumbers in the 12000-7600 cm-1 spectral region. Reichenbachite electronic spectrum is characterised by Cu(II) transition bands at 9755 and 7520 cm-1. A broad spectral feature observed for ferrous ion in the 12000-9000 cm-1 region both in scholzite and parascholzite. Some what similarities in the vibrational spectra of the three phosphate minerals are observed particularly in the OH stretching region. The observation of strong band at 5090 cm-1 indicates strong hydrogen bonding in the structure of the dimorphs, scholzite and parascholzite. The three phosphates exhibit overlapping bands in the 4800-4000 cm-1 region resulting from the combinations of vibrational modes of (PO4)3- units.

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A series of lithium niobate powders were synthesized by the combustion method at different heating rates. The effect of heating rate on the crystal composition of lithium niobate powders was investigated by powder X-ray diffraction measurements. It has been found that the lithium content in the as-synthesized lithium niobate powders increases with decreasing the heating rate. On the basis of the existed structure-property relationship of lithium niobate single crystals, it was concluded that high quality lithium niobate powders can be effectively synthesized at a lower heating rate (in the range of 5-10 C/min) by the combustion method.

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The use of appropriate features to represent an output class or object is critical for all classification problems. In this paper, we propose a biologically inspired object descriptor to represent the spectral-texture patterns of image-objects. The proposed feature descriptor is generated from the pulse spectral frequencies (PSF) of a pulse coupled neural network (PCNN), which is invariant to rotation, translation and small scale changes. The proposed method is first evaluated in a rotation and scale invariant texture classification using USC-SIPI texture database. It is further evaluated in an application of vegetation species classification in power line corridor monitoring using airborne multi-spectral aerial imagery. The results from the two experiments demonstrate that the PSF feature is effective to represent spectral-texture patterns of objects and it shows better results than classic color histogram and texture features.

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Human hair fibres are ubiquitous in nature and are found frequently at crime scenes often as a result of exchange between the perpetrator, victim and/or the surroundings according to Locard's Principle. Therefore, hair fibre evidence can provide important information for crime investigation. For human hair evidence, the current forensic methods of analysis rely on comparisons of either hair morphology by microscopic examination or nuclear and mitochondrial DNA analyses. Unfortunately in some instances the utilisation of microscopy and DNA analyses are difficult and often not feasible. This dissertation is arguably the first comprehensive investigation aimed to compare, classify and identify the single human scalp hair fibres with the aid of FTIR-ATR spectroscopy in a forensic context. Spectra were collected from the hair of 66 subjects of Asian, Caucasian and African (i.e. African-type). The fibres ranged from untreated to variously mildly and heavily cosmetically treated hairs. The collected spectra reflected the physical and chemical nature of a hair from the near-surface particularly, the cuticle layer. In total, 550 spectra were acquired and processed to construct a relatively large database. To assist with the interpretation of the complex spectra from various types of human hair, Derivative Spectroscopy and Chemometric methods such as Principal Component Analysis (PCA), Fuzzy Clustering (FC) and Multi-Criteria Decision Making (MCDM) program; Preference Ranking Organisation Method for Enrichment Evaluation (PROMETHEE) and Geometrical Analysis for Interactive Aid (GAIA); were utilised. FTIR-ATR spectroscopy had two important advantages over to previous methods: (i) sample throughput and spectral collection were significantly improved (no physical flattening or microscope manipulations), and (ii) given the recent advances in FTIR-ATR instrument portability, there is real potential to transfer this work.s findings seamlessly to on-field applications. The "raw" spectra, spectral subtractions and second derivative spectra were compared to demonstrate the subtle differences in human hair. SEM images were used as corroborative evidence to demonstrate the surface topography of hair. It indicated that the condition of the cuticle surface could be of three types: untreated, mildly treated and treated hair. Extensive studies of potential spectral band regions responsible for matching and discrimination of various types of hair samples suggested the 1690-1500 cm-1 IR spectral region was to be preferred in comparison with the commonly used 1750-800 cm-1. The principal reason was the presence of the highly variable spectral profiles of cystine oxidation products (1200-1000 cm-1), which contributed significantly to spectral scatter and hence, poor hair sample matching. In the preferred 1690-1500 cm-1 region, conformational changes in the keratin protein attributed to the α-helical to β-sheet transitions in the Amide I and Amide II vibrations and played a significant role in matching and discrimination of the spectra and hence, the hair fibre samples. For gender comparison, the Amide II band is significant for differentiation. The results illustrated that the male hair spectra exhibit a more intense β-sheet vibration in the Amide II band at approximately 1511 cm-1 whilst the female hair spectra displayed more intense α-helical vibration at 1520-1515cm-1. In terms of chemical composition, female hair spectra exhibit greater intensity of the amino acid tryptophan (1554 cm-1), aspartic and glutamic acid (1577 cm-1). It was also observed that for the separation of samples based on racial differences, untreated Caucasian hair was discriminated from Asian hair as a result of having higher levels of the amino acid cystine and cysteic acid. However, when mildly or chemically treated, Asian and Caucasian hair fibres are similar, whereas African-type hair fibres are different. In terms of the investigation's novel contribution to the field of forensic science, it has allowed for the development of a novel, multifaceted, methodical protocol where previously none had existed. The protocol is a systematic method to rapidly investigate unknown or questioned single human hair FTIR-ATR spectra from different genders and racial origin, including fibres of different cosmetic treatments. Unknown or questioned spectra are first separated on the basis of chemical treatment i.e. untreated, mildly treated or chemically treated, genders, and racial origin i.e. Asian, Caucasian and African-type. The methodology has the potential to complement the current forensic analysis methods of fibre evidence (i.e. Microscopy and DNA), providing information on the morphological, genetic and structural levels.

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Road deposited solids are a mix of pollutants originating from a range of anthropogenic sources common to urban land uses and soil inputs from surrounding areas. These particles accumulate potentially toxic pollutants thereby posing a threat to receiving waters. Reliable estimation of sources of particulate pollutants in build-up and quantification of particle composition is important for the development of best management practices for stormwater quality mitigation. The research study analysed build-up pollutants from sixteen different urban road surfaces and soil from four background locations. The road surfaces were selected from residential, industrial and commercial land uses from four suburbs in Gold Coast, Australia. Collected build-up samples were analysed for solids load, organic matter and mineralogy. The soil samples were analysed for mineralogy. Quantitative and qualitative analysis of mineralogical data, along with multivariate data analysis were employed to identify the relative source contributions to road deposited solids. The build-up load on road surfaces in different suburbs showed significant differences due to the nature of anthropogenic activities, road texture depth and antecedent dry period. Analysis revealed that build-up pollutants consists primarily of soil derived minerals (60%) and the remainder is composed of traffic generated pollutants and organic matter. Major mineral components detected were quartz and potential clay forming minerals such as albite, microline, chlorite and muscovite. An average of 40-50% of build-up pollutants by weight was made up of quartz. Comparison of the mineral component of build-up pollutants with background soil samples indicated that the minerals primarily originate from surrounding soils. About 2.2% of build-up pollutants were organic matter which originates largely from plant matter. Traffic related pollutants which are potentially toxic to the receiving water environment represented about 30% of the build-up pollutants at the study sites.

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Films found on the windows of residential buildings have been studied. The main aim of the paper was to assess the roles of the films in the accumulation of potentially toxic chemicals in residential buildings. Thus the elemental and polycyclic aromatic hydrocarbon compositions of the surface films from the glass windows of eighteen residential buildings were examined. The presence of sample amounts of inorganic elements (4.0–1.2 × 106 μg m−2) and polycyclic aromatic hydrocarbons in the films (BDL - 620.1 ng m−2) has implications for human exposure and the fate of pollutants in the urban environment. To facilitate the interpretation of the results, data matrices consisting of the chemical composition of the films and the building characteristics were subjected to multivariate data analysis methods, and these revealed that the accumulation of the chemicals was strongly dependent on building characteristics such as the type of glass used for the window, the distance from a major road, age of the building, distance from an industrial activity, number of smokers in the building and frequency of cooking in the buildings. Thus, building characteristics which minimize the accumulation of pollutants on the surface films need to be encouraged.

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Background The vast sequence divergence among different virus groups has presented a great challenge to alignment-based analysis of virus phylogeny. Due to the problems caused by the uncertainty in alignment, existing tools for phylogenetic analysis based on multiple alignment could not be directly applied to the whole-genome comparison and phylogenomic studies of viruses. There has been a growing interest in alignment-free methods for phylogenetic analysis using complete genome data. Among the alignment-free methods, a dynamical language (DL) method proposed by our group has successfully been applied to the phylogenetic analysis of bacteria and chloroplast genomes. Results In this paper, the DL method is used to analyze the whole-proteome phylogeny of 124 large dsDNA viruses and 30 parvoviruses, two data sets with large difference in genome size. The trees from our analyses are in good agreement to the latest classification of large dsDNA viruses and parvoviruses by the International Committee on Taxonomy of Viruses (ICTV). Conclusions The present method provides a new way for recovering the phylogeny of large dsDNA viruses and parvoviruses, and also some insights on the affiliation of a number of unclassified viruses. In comparison, some alignment-free methods such as the CV Tree method can be used for recovering the phylogeny of large dsDNA viruses, but they are not suitable for resolving the phylogeny of parvoviruses with a much smaller genome size.

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INTRODUCTION: Breast milk fatty acids play a major role in infant development. However, no data have compared the breast milk composition of different ethnic groups living in the same environment. We aimed to (i) investigate breast milk fatty acid composition of three ethnic groups in Singapore and (ii) determine dietary fatty acid patterns in these groups and any association with breast milk fatty acid composition. MATERIALS AND METHODS: This was a prospective study conducted at a tertiary hospital in Singapore. Healthy pregnant women with the intention to breastfeed were recruited. Diet profile was studied using a standard validated 3-day food diary. Breast milk was collected from mothers at 1 to 2 weeks and 6 to 8 weeks postnatally. Agilent gas chromatograph (6870N) equipped with a mass spectrometer (5975) and an automatic liquid sampler (ALS) system with a split mode was used for analysis. RESULTS: Seventy-two breast milk samples were obtained from 52 subjects. Analysis showed that breast milk ETA (Eicosatetraenoic acid) and ETA:EA (Eicosatrienoic acid) ratio were significantly different among the races (P = 0.031 and P = 0.020), with ETA being the highest among Indians and the lowest among Malays. Docosahexaenoic acid was significantly higher among Chinese compared to Indians and Malays. No difference was demonstrated in n3 and n6 levels in the food diet analysis among the 3 ethnic groups. CONCLUSIONS: Differences exist in breast milk fatty acid composition in different ethnic groups in the same region, although no difference was demonstrated in the diet analysis. Factors other than maternal diet may play a role in breast milk fatty acid composition.