The structure and function of coastal marshes results from a complex interaction of biotic and abiotic processes that continually influence the characteristics of marsh vegetation. A great deal of research has focused on how tidal processes influence vegetation dynamics along the Atlantic coast, but few studies have investigated the influence of similar processes in the marshes along the Gulf of Mexico. This study aims to identify the characteristic vegetation assemblages of the coastal marshes bordering the East Bay of Galveston Bay, Texas, and identify if elevation, inundation frequency and burning frequency are important to their structure. To identify characteristic vegetation assemblages, hierarchical cluster analysis was used. The cluster analysis resulted in seven statistically different vegetation assemblages that were used in diversity analysis and classification and regression analysis (CART) as dependent variables. Diversity measures were calculated at both the plot and assemblage scale using Shannon's diversity index and species richness. The resulting diversity measures were used as predictor variables in the CART analysis as well as regression analysis. Hydrologic modeling was accomplished using Mike 21, a flow and wave simulation model, along with a geographic information system (GIS), to model hourly inundation frequency at each of the sampled plots. The inundation frequency was then used as a predictor variable in the CART analysis and regression analysis. This study found that the main factor contributing to species richness was elevation. Vegetation assemblages at high elevations generally had high diversity, and assemblages at low elevations had lower diversity. Elevation and inundation frequency are inversely related, and the strong correlation between species richness and elevation also assumes that inundation frequency is important in structuring the marsh. Burn frequencies had no influence on diversity in general, but more frequent burning did result in monospecific stands of Spartina patens at Anahuac NWR.

The aim of this study is to investigate the distributions of polycyclic aromatic hydrocarbons (PAHs) in sediment and water (suspended particles and dissolved phase) samples collected from Dapeng Bay(coast¡Bbay¡Bwetland and mangrove). Chemical fingerprinting techniques and statistical analysis were applied to delineate the possible sources of PAHs in sediment and water samples. The average concentrations of total PAHs (£U51PAHs) ranged from 143 to 1595 ng/g dry weight (dw) in the sediments. Total PAH (£U46PAHs) concentrations varied from 11 to 38 ng/L in dissolved phase and from 1.4 to 15ng/L (252 to 772 ng/g dw) in suspended particulate phase, respectively. Comparing with sediment quality guidelines (SQGs), the total PAH concentrations in all sediment samples were below the criteria, suggesting that no adverse biological effects would arise from the PAHs in these sediments. The partition coefficients¡]KOC¡^values of PAHs were higher than predicted values. It might be attributed to soot particles which have extremely high sorption capacities. Total organic carbon¡]POC¡^and black carbon (BC) were significantly correlated with combustion PAH concentrations in Dapeng Bay. Combustion PAHs (Flt¡ÏPyr¡ÏBaA¡ÏChr¡ÏBbF¡ÏBkFa¡ÏBeP¡ÏBaP¡ÏIP¡ÏBghiP) concentrations were significantly correlated with black carbon (BC) in mangroves sediment cores and wetland A. In addition, total PAH concentrations were significantly correlated with combustion PAHs concentrations in dissolved phase. In suspended particulate phase, total PAH concentrations and combustion PAHs concentrations were significantly correlated with suspended solid (SS). Results from diagnostic ratios and hierarchical cluster analysis (HCA) both indicate that PAHs in the coast of Dapeng Bay were mainly from petrogenic sources, but from petrogenic and pyrogenic mixed sources in the wetland and mangrove inside the Dapeng Bay. In addition, the origin of perylene in Dapeng Bay and coastal sediments was mainly from the biogenic and pyrogenic, while it was from biogenic origin in wetland A and wetland B. However, the origin of perylene in mangrove M1 and mangrove M2 tended to be diagenetic.

The concept of a hub airport has evolved widening its scope as a national civil aviation policy-making tool, due to the ability to deliver wider socio-economic benefits to a country. However, not all airports can be converted into hubs. This research proposes a methodological approach to structural analysis of the airport industry, that could be applied to determine the competitive position of an airport in a given aviation network and devise airport strategies and national policy measures to improve the current position of the airport. This study presents a twelve-group taxonomy of airports, which analyses the changing geography of the airport industry in the East (Asia and The Middle East). Multivariate data have been used in a two-step Agglomerative Hierarchical Clustering exercise which represents three airport strategies: namely, degree-of-airport-activity (size and intensity of operations), network strategies (international and domestic hub), and the market segmentation strategies (service and destination orientation). Principal Component Analysis has been utilised as a data reduction tool. The study confirms the general hypothesis that a sound macro environment and liberalised approach to economic regulation in the air transport industry are important for successful hub operations. In addition, it sheds light on the fact that while the factors of geographical advantage, economic development, urbanisation, tourism and business attractiveness, physical and intellectual infrastructure, and political and administrative frameworks, are all basic prerequisites (qualifiers) for successful hubbing in the region, those factors would not necessarily guarantee a hub status unless the governments are also committed to develop the sector and take timely decisions (differentiators) to allow airports to benefit from the first mover advantage. Application of the proposed taxonomy was tested on a case study of the major international airport of Sri Lanka, to provide policy inputs to develop the airport that is currently identified as being overshadowed by the mega hubs in the region.

This study investigated the concentration distributions of polyclic aromatic hydrocarbons (PAHs) in the sediment cores collected from Fang-Liao submarine canyon. Chemical fingerprinting techniques and statistical analysis were applied to delineate the possible sources of the PAHs in deposited sediment core samples. It is noteworthy that all cores were not dated; therefore the deposition age could not estimate from the depth of deposition directly. The average concentrations of polyclic aromatic hydrocarbons (£U51PAHs) were found ranged from 229 to 638 (ng/g dry wt) in the sediment cores in Fang-Liao submarine canyon. In addition, the low molecular weight PAHs (2-3 ring PAHs) were found dominant in the PAH composition pattern of most samples. Total PAH concentrations were significantly correlated with total organic carbon (TOC) in all the sediment cores. Compared with sediment quality guidelines (SQGs), the PAH concentrations of all sediment samples were lower than those outlined in the criteria, that suggests no evident adverse biological effects caused by PAHs. Results also showed that total PAH concentration of surface sediments (0-2 cm) decreased with the water depth. Identification of PAHs sources suggests that all up-cores were dominated by petrogenic sources, but all down-cores except for S17 and S18 were dominated by pyrogenic sources or mixed sources. In contrast, biogenic sources were found dominant in S17 and S18 as they were characterized by higher ratio of perylene/£Upenta-PAHs(%). Compared with literature, the sediment cores of Fang-Liao submarine canyon were moderately polluted with PAHs. Analysis of diagnostic ratios and hierarchical cluster analysis (HCA) as well as principal component analysis (PCA) all indicate PAHs sources of Fang-Liao submarine canyon were mainly from petroleum and petroleum combustion sources for site of S3,S5,S7,S8 and S17; while pyrogenic or mixed sources for site of S1,S2,S9,S18 and S33.

Técnicas de caracterização microestrutural, incluindo microanálise química EDS (energy dispersive spectrometry), foram usadas para investigar as inclusões não-metálicas de amostras ferrosas da Real Fábrica de Ferro São João de Ipanema (Sorocaba, século XIX), da Ponte D. Pedro II (Bahia, produzida na Escócia, Mossend Iron Works, século XIX) e dos sítios arqueológicos de São Miguel das Missões (Rio Grande do Sul, século XVII) e de Afonso Sardinha (Sorocaba, século XVI). Estes resultados foram analisados por métodos estatísticos com o objetivo de estabelecer a assinatura química de cada uma das quatro procedências testadas. A análise dos gráficos bivariantes dos resultados de microanálise de inclusões \"globais\" (% SiO2 versus %Al2O3; %CaO versus %K2O; %MgO versus %Al2O3 e % SiO2 versus %FeO) não permitiu separar os resultados em agrupamentos significativos com relação à procedência das amostras. Os resultados de microanálise da correlação dos teores de %TiO2 e %V2O5 presentes na fase wüstita da microestrutura das inclusões de escória mostraram, no entanto, um agrupamento significativo para os resultados dos artefatos ferrosos de Bahia e de Missões, mas não permitiram separar os resultados dos artefatos de Ipanema e de Sardinha. Deste modo, foi usada a análise hierárquica de conglomerados dos resultados de microanálise das inclusões \"globais\" e de seus microconstituintes (fase wüstita e \"matriz\") com o objetivo de separar os resultados em quatro grupos coincidentes com as quatro procedências investigadas. Somente a análise hierárquica de conglomerados usando os teores de %MgO, %TiO2, %V2O5, %MnO e %Al2O3 presentes na fase wüstita permitiu separar com sucesso os quatro grupos de resultados. Finalmente, a baixa fração volumétrica de inclusões de escória das amostras de Ipanema (~1% contra uma média de 4% das demais amostras) indica a existência de certo grau de domínio tecnológico dos processos produtivos da Real Fábrica de Ferro São João de Ipanema. / Microstructural characterization techniques, including EDX (Energy Dispersive X-ray Analysis) microanalyses, were used to investigate the slag inclusions of the microstructure of ferrous artifacts of the Royal Iron Factory of São João de Ipanema (first steel plant of Brazil, XIX century), the D. Pedro II Bridge (located in Bahia, assembled in XIX century and produced in Scotland) and the archaeological sites of São Miguel de Missões (Rio Grande do Sul, Brazil, production site of iron artifacts, the XVIII century) and Afonso Sardinha (São Paulo, Brazil production site of iron artifacts, XVI century). The microanalyses results were analyzed by a hierarchical cluster analysis and the dendrogram with the microanalyses results of the wustite phase (using as critical variables the contents of MnO, MgO, Al2O3, V2O5 and TiO2) allowed the identification of four clusters, which successfully represented the samples of the four production sites (Ipanema, Sardinha, Missões and Bahia). The comparatively low volumetric fraction of slag inclusions in the samples of Ipanema (~1% whit an average of 4% others samples) indicated the existence of some degree of proficiency in the ironmaking processing of the Royal Iron Factory of São João de Ipanema.

Técnicas de caracterização microestrutural, incluindo microanálise química EDS (energy dispersive spectrometry), foram usadas para investigar as inclusões não-metálicas de amostras ferrosas da Real Fábrica de Ferro São João de Ipanema (Sorocaba, século XIX), da Ponte D. Pedro II (Bahia, produzida na Escócia, Mossend Iron Works, século XIX) e dos sítios arqueológicos de São Miguel das Missões (Rio Grande do Sul, século XVII) e de Afonso Sardinha (Sorocaba, século XVI). Estes resultados foram analisados por métodos estatísticos com o objetivo de estabelecer a assinatura química de cada uma das quatro procedências testadas. A análise dos gráficos bivariantes dos resultados de microanálise de inclusões \"globais\" (% SiO2 versus %Al2O3; %CaO versus %K2O; %MgO versus %Al2O3 e % SiO2 versus %FeO) não permitiu separar os resultados em agrupamentos significativos com relação à procedência das amostras. Os resultados de microanálise da correlação dos teores de %TiO2 e %V2O5 presentes na fase wüstita da microestrutura das inclusões de escória mostraram, no entanto, um agrupamento significativo para os resultados dos artefatos ferrosos de Bahia e de Missões, mas não permitiram separar os resultados dos artefatos de Ipanema e de Sardinha. Deste modo, foi usada a análise hierárquica de conglomerados dos resultados de microanálise das inclusões \"globais\" e de seus microconstituintes (fase wüstita e \"matriz\") com o objetivo de separar os resultados em quatro grupos coincidentes com as quatro procedências investigadas. Somente a análise hierárquica de conglomerados usando os teores de %MgO, %TiO2, %V2O5, %MnO e %Al2O3 presentes na fase wüstita permitiu separar com sucesso os quatro grupos de resultados. Finalmente, a baixa fração volumétrica de inclusões de escória das amostras de Ipanema (~1% contra uma média de 4% das demais amostras) indica a existência de certo grau de domínio tecnológico dos processos produtivos da Real Fábrica de Ferro São João de Ipanema. / Microstructural characterization techniques, including EDX (Energy Dispersive X-ray Analysis) microanalyses, were used to investigate the slag inclusions of the microstructure of ferrous artifacts of the Royal Iron Factory of São João de Ipanema (first steel plant of Brazil, XIX century), the D. Pedro II Bridge (located in Bahia, assembled in XIX century and produced in Scotland) and the archaeological sites of São Miguel de Missões (Rio Grande do Sul, Brazil, production site of iron artifacts, the XVIII century) and Afonso Sardinha (São Paulo, Brazil production site of iron artifacts, XVI century). The microanalyses results were analyzed by a hierarchical cluster analysis and the dendrogram with the microanalyses results of the wustite phase (using as critical variables the contents of MnO, MgO, Al2O3, V2O5 and TiO2) allowed the identification of four clusters, which successfully represented the samples of the four production sites (Ipanema, Sardinha, Missões and Bahia). The comparatively low volumetric fraction of slag inclusions in the samples of Ipanema (~1% whit an average of 4% others samples) indicated the existence of some degree of proficiency in the ironmaking processing of the Royal Iron Factory of São João de Ipanema.

Abstract This research explored professional singers’ pronunciation of German in Frauenliebe und Leben, a song cycle, composed in 1840 by Robert Schumann (1810–1856). Adopting a two-fold approach, the thesis examined pronunciation from the viewpoints of normative German pronunciation and vocal pedagogy, paying special attention to the relationship between the two sets of norms. Normative German pronunciation is based on ‘reine Hochlautung’ as defined by Theodor Siebs, as well as on his instructions to classical singers. Norms of pronunciation used in vocal pedagogy were derived from 11 German pronunciation manuals for classical singers. At the centre of this study were 11 elements of the German language: the phonemes /s/, /r/, /b/, /d/ and /g/, the suffix -ig, double consonants, connecting consonants, the letter combination ng, liaison and diphthongs in a melismatic setting. Twelve professional singers’ – Anne Sofie von Otter, Barbara Bonney, Brigitte Fassbaender, Elly Ameling, Elisabeth Grümmer, Irmgard Seefried, Janet Baker, Jessye Norman, Kathleen Ferrier, Soile Isokoski, Marjana Lipovšek, Tamara Takács – pronunciation of these elements was studied via their recording of Frauenliebe und Leben between 1950 and 1997. Both descriptive statistical analysis methods and hierarchical cluster analysis were applied to the data. A reliability analysis was conducted using intra-category correlations and relative frequencies. This analysis indicated a reasonable degree of reliability. Descriptive statistical analysis methods yielded the result that the actual pronunciation of the professional singers, as evidenced by their recordings, was considerably more varied than what could be expected on the basis of normative or pedagogical norms. Hierarchical cluster analysis, too, showed that the professional singers shared the same category to a moderate degree. We may conclude that vocal pedagogical theory needs to be further developed, because pedagogical norms for pronunciation proved partially confusing and difficult to grasp. In addition, specific attention must be given to source critique. The actual pronunciation of professional singers challenges singing instructors to reflect on how they teach German pronunciation and what they can do to help their students develop the skills required for a critical listening of recordings. / Tiivistelmä Eksperttilaulajien saksan kielen ääntämistä havainnoitiin Robert Schumannin (1810–1856) vuonna 1840 säveltämässä laulusarjassa Frauenliebe und Leben, ja ääntämistä tutkittiin suhteessa sekä saksan kirjakielen ääntämisnormistoon että pedagogiseen ääntämisnormistoon. Tutkimuksessa syvennyttiin myös ääntämisnormistojen välisen suhteen tarkasteluun. Saksan kirjakielen ääntämisnormisto perustui Theodor Siebsin reine Hochlautung -ääntämistapaan sekä Siebsin klassisen laulun ohjeistuksiin. Pedagoginen ääntämisnormisto eli klassisille laulajille osoitetut saksan kielen ääntämisen oppaat oli rajattu yhteentoista teokseen. Tutkittavana oli yksitoista saksan kielen elementtiä: konsonantit s, r, b, d, g, suffiksi -ig, kirjainyhdistelmä ng, kaksoiskonsonantit, konsonanttien yhdistäminen, vokaalien sitominen ja diftongit. Laulusarjan levyttäneitä eksperttilaulajia oli kaksitoista: Anne Sofie von Otter, Barbara Bonney, Brigitte Fassbaender, Elly Ameling, Elisabeth Grümmer, Irmgard Seefried, Janet Baker, Jessye Norman, Kathleen Ferrier, Soile Isokoski, Marjana Lipovšek ja Tamara Takács. Äänitteet olivat vuosien 1950 ja 1997 väliseltä ajalta. Tutkimuksessa käytettiin perinteisiä kuvailevia tilastollisia analyysimenetelmiä ja hierarkkista ryhmittelyanalyysia. Aineiston luotettavuutta tarkasteltiin reliabiliteettianalyysin avulla. Reliabiliteettianalyysi osoitti, että aineistolle saavutettiin kohtuullinen luotettavuus. Kuvailevien tilastollisten analyysimenetelmien tuloksena oli havainto, että eksperttilaulajien ääntäminen äänitteissä oli huomattavasti monimuotoisempaa kuin saksan kirjakielen ja pedagoginen ääntämisnormisto antoivat olettaa. Hierarkkinen ryhmittelyanalyysi puolestaan osoitti, että eksperttilaulajien sijoittuminen samaan ryhmään oli maltillista. Tutkimus vahvistaa käsitystä, että laulupedagogista teoriaa tulee tarkastella dynaamisena, alati muuttuvana ilmiönä. Tutkimuksen perusteella myös havaitaan, että eksperttilaulajien ääntäminen noudattaa laulupedagogiikassa käytettyjä ääntämisen ohjeistuksia vain osin. Eksperttilaulajien ääntämisen käytäntö täten haastaa laulupedagogit pohtimaan sitä, kuinka he itse opettavat saksan kieltä, ja sitä, kuinka he liittävät opetustyöhönsä äänitteiden kriittisen kuuntelemisen taidon ja lauluoppaiden kriittisen käytön.

This dissertation thesis deals with similarity measures for nominal data in hierarchical clustering, which can cope with variables with more than two categories, and which aspire to replace the simple matching approach standardly used in this area. These similarity measures take into account additional characteristics of a dataset, such as frequency distribution of categories or number of categories of a given variable. The thesis recognizes three main aims. The first one is an examination and clustering performance evaluation of selected similarity measures for nominal data in hierarchical clustering of objects and variables. To achieve this goal, four experiments dealing both with the object and variable clustering were performed. They examine the clustering quality of the examined similarity measures for nominal data in comparison with the commonly used similarity measures using a binary transformation, and moreover, with several alternative methods for nominal data clustering. The comparison and evaluation are performed on real and generated datasets. Outputs of these experiments lead to knowledge, which similarity measures can generally be used, which ones perform well in a particular situation, and which ones are not recommended to use for an object or variable clustering. The second aim is to propose a theory-based similarity measure, evaluate its properties, and compare it with the other examined similarity measures. Based on this aim, two novel similarity measures, Variable Entropy and Variable Mutability are proposed; especially, the former one performs very well in datasets with a lower number of variables. The third aim of this thesis is to provide a convenient software implementation based on the examined similarity measures for nominal data, which covers the whole clustering process from a computation of a proximity matrix to evaluation of resulting clusters. This goal was also achieved by creating the nomclust package for the software R, which covers this issue, and which is freely available.

No description available.

Smokeless powders are a set of energetic materials, known as low explosives, which are typically utilized for reloading ammunition. There are three types which differ in their primary energetic materials; where single base powders contain nitrocellulose as their primary energetic material, double and triple base powders contain nitroglycerin in addition to nitrocellulose, and triple base powders also contain nitroguanidine. Additional organic compounds, while not proprietary to specific manufacturers, are added to the powders in varied ratios during the manufacturing process to optimize the ballistic performance of the powders. The additional compounds function as stabilizers, plasticizers, flash suppressants, deterrents, and opacifiers. Of the three smokeless powder types, single and double base powders are commercially available, and have been heavily utilized in the manufacture of improvised explosive devices. Forensic smokeless powder samples are currently analyzed using multiple analytical techniques. Combined microscopic, macroscopic, and instrumental techniques are used to evaluate the sample, and the information obtained is used to generate a list of potential distributors. Gas chromatography – mass spectrometry (GC-MS) is arguably the most useful of the instrumental techniques since it distinguishes single and double base powders, and provides additional information about the relative ratios of all the analytes present in the sample. However, forensic smokeless powder samples are still limited to being classified as either single or double base powders, based on the absence or presence of nitroglycerin, respectively. In this work, the goal was to develop statistically valid classes, beyond the single and double base designations, based on multiple organic compounds which are commonly encountered in commercial smokeless powders. Several chemometric techniques were applied to smokeless powder GC-MS data for determination of the classes, and for assignment of test samples to these novel classes. The total ion spectrum (TIS), which is calculated from the GC-MS data for each sample, is obtained by summing the intensities for each mass-to-charge (m/z) ratio across the entire chromatographic profile. A TIS matrix comprising data for 726 smokeless powder samples was subject to agglomerative hierarchical cluster (AHC) analysis, and six distinct classes were identified. Within each class, a single m/z ratio had the highest intensity for the majority of samples, though the m/z ratio was not always unique to the specific class. Based on these observations, a new classification method known as the Intense Ion Rule (IIR) was developed and used for the assignment of test samples to the AHC designated classes. Discriminant models were developed for assignment of test samples to the AHC designated classes using k-Nearest Neighbors (kNN) and linear and quadratic discriminant analyses (LDA and QDA, respectively). Each of the models were optimized using leave-one-out (LOO) and leave-group-out (LGO) cross-validation, and the performance of the models was evaluated by calculating correct classification rates for assignment of the cross-validation (CV) samples to the AHC designated classes. The optimized models were utilized to assign test samples to the AHC designated classes. Overall, the QDA LGO model achieved the highest correct classification rates for assignment of both the CV samples and the test samples to the AHC designated classes. In forensic application, the goal of an explosives analyst is to ascertain the manufacturer of a smokeless powder sample. In addition, knowledge about the probability of a forensic sample being produced by a specific manufacturer could potentially decrease the time invested by an analyst during investigation by providing a shorter list of potential manufacturers. In this work, Bayes* Theorem and Bayesian Networks were investigated as an additional tool to be utilized in forensic casework. Bayesian Networks were generated and used to calculate posterior probabilities of a test sample belonging to specific manufacturers. The networks were designed to include manufacturer controlled powder characteristics such as shape, color, and dimension; as well as, the relative intensities of the class associated ions determined from cluster analysis. Samples were predicted to belong to a manufacturer based on the highest posterior probability. Overall percent correct rates were determined by calculating the percentage of correct predictions; that is, where the known and predicted manufacturer were the same. The initial overall percent correct rate was 66%. The dimensions of the smokeless powders were added to the network as average diameter and average length nodes. Addition of average diameter and length resulted in an overall prediction rate of 70%.