The use of computer technology to compare and analyze community college dissertations

A purpose of this research study was to demonstrate the practical linguistic study and evaluation of dissertations by using two examples of the latest technology, the microcomputer and optical scanner. That involved developing efficient methods for data entry plus creating computer algorithms appropriate for personal, linguistic studies. The goal was to develop a prototype investigation which demonstrated practical solutions for maximizing the linguistic potential of the dissertation data base. The mode of text entry was from a Dest PC Scan 1000 Optical Scanner. The function of the optical scanner was to copy the complete stack of educational dissertations from the Florida Atlantic University Library into an I.B.M. XT microcomputer. The optical scanner demonstrated its practical value by copying 15,900 pages of dissertation text directly into the microcomputer. A total of 199 dissertations or 72% of the entire stack of education dissertations (277) were successfully copied into the microcomputer's word processor where each dissertation was analyzed for a variety of syntax frequencies. The results of the study demonstrated the practical use of the optical scanner for data entry, the microcomputer for data and statistical analysis, and the availability of the college library as a natural setting for text studies. A supplemental benefit was the establishment of a computerized dissertation corpus which could be used for future research and study. The final step was to build a linguistic model of the differences in dissertation writing styles by creating 7 factors from 55 dependent variables through principal components factor analysis. The 7 factors (textual components) were then named and described on a hypothetical construct defined as a continuum from a conversational, interactional style to a formal, academic writing style. The 7 factors were then grouped through discriminant analysis to create discriminant functions for each of the 7 independent variables. The results indicated that a conversational, interactional writing style was associated with more recent dissertations (1972-1987), an increase in author's age, females, and the department of Curriculum and Instruction. A formal, academic writing style was associated with older dissertations (1972-1987), younger authors, males, and the department of Administration and Supervision. It was concluded that there were no significant differences in writing style due to subject matter (community college studies) compared to other subject matter. It was also concluded that there were no significant differences in writing style due to the location of dissertation origin (Florida Atlantic University, University of Central Florida, Florida International University).

Comparative Study of Four Portuguese 16th Century Illuminated Manueline Charters based on Spectroscopy and Chemometrics Analysis

The comparative study based on spectroscopic analysis of the materials used to produce four sixteenth-century Manueline Charters (the Charters of Alcochete, Terena, Alandroal and Evora) was performed following a systematic analytical approach. SEM–EDS, l-Raman and l-FTIR analysis highlighted interesting features between them, namely the use of different pigments and colourants (such as different green and yellow pigments), the presence of pigments alterations and the use of a non-expected extemporaneous material (with the presence of titanium white in the Charter of Alcochete). Principal component analysis restricted to the C–H absorption region (3000–2840 cm-1) was applied to 36 infrared spectra of blue historical samples from the Charters of Alcochete,Terena, Alandroal and Évora, suggesting the use of a mixture of a triglyceride and polysaccharide as binder.

Motivação e satisfação no trabalho: aplicação numa organização do setor de formação profissional

Os recursos humanos são considerados o ativo mais poderoso e valioso de qualquer organização, mas o seu desempenho é, de uma forma geral, influenciado pela motivação e satisfação no trabalho. Deste modo, a presente investigação pretende analisar a motivação e a satisfação dos colaboradores numa organização do sector da formação profissional. A partir deste pressuposto, pretende-se analisar a motivação e a satisfação dos colaboradores da instituição alvo do estudo, averiguar se se verifica correlação entre as vaiáveis motivacionais (sucesso, afiliação e poder) e as variáveis de satisfação (salário, promoções, colegas de trabalho, superiores hierárquicos e realização da tarefa), analisar o relacionamento entre a variável dependente (satisfação com o salário) e variáveis independentes de natureza sociodemográfica e analisar se a motivação e a satisfação global dos colaboradores são influenciadas pelas variáveis explicativas da análise fatorial de componentes principais. A análise dos dados baseou-se em 72 inquéritos por questionário que foram já validados por autores da motivação (McClelland) e satisfação (Deshpande), aplicados à totalidade dos colaboradores da empresa, ou seja, à população em estudo. Procedeu-se à análise estatística para sustentar toda a parte empírica. Os resultados mostram que os colaboradores da empresa Competir se sentem razoavelmente motivados e satisfeitos, ainda que um pouco mais motivados do que satisfeitos. Concluiu-se que, na generalidade, os colaboradores se sentem motivados essencialmente no que diz respeito ao sucesso e afiliação, e satisfeitos principalmente com os seus colegas de trabalho e com a realização da tarefa. A satisfação com o salário é mais baixa no caso de género feminino, mas tende a aumentar com a antiguidade na empresa; Motivation and Job Satisfaction: An Application in an organization of vocational training sector Abstract: Human resources are considered the most powerful and valuable asset in any organization, but its performance is, in general, influenced by motivation and job satisfaction. The present research intends to analyse the motivation and the satisfaction of the employees in an organization of vocational training sector. Based on this assumption, we intend to analyze the motivation and satisfaction of the employees of the studied institution, to verify if there is a correlation between motivational (success, affiliation and power) and satisfaction variables (salary, promotions, Work, hierarchical superiors and task accomplishment), to analyze the relationship between the dependent variable (satisfaction with the salary) and independent variables of a sociodemographic nature and to analyze if the motivation and the overall satisfaction of the employees are influenced by the explanatory variables of the principal components factorial analysis. Data analysis was based on 72 questionnaire surveys that have already been validated by the authors of motivation (McClelland) and satisfaction (Deshpande), applied to all the company's employees, i.e., the study population. In order to support all the empirical part, were proceeded to the statistical analysis. The results shows that the employees of the company Competir feel reasonably motivated and satisfied, even if a little more motivated than satisfied. It was concluded that, in general, employees feel motivated primarily with regard to success and affiliation, and especially satisfied with their co-workers and with the complete of the task. Satisfaction with salary it’s lower in the case of female gender, but tends to increase with seniority in the company.

Advanced neuroimaging methodologies to improve connectivity detection in normal and abnormal language brain networks

The language connectome was in-vivo investigated using multimodal non-invasive quantitative MRI. In PPA patients (n=18) recruited by the IRCCS ISNB, Bologna, cortical thickness measures showed a predominant reduction on the left hemisphere (p<0.005) with respect to matched healthy controls (HC) (n=18), and an accuracy of 86.1% in discrimination from Alzheimer’s disease patients (n=18). The left temporal and para-hippocampal gyri significantly correlated (p<0.01) with language fluency. In PPA patients (n=31) recruited by the Northwestern University Chicago, DTI measures were longitudinally evaluated (2-years follow-up) under the supervision of Prof. M. Catani, King’s College London. Significant differences with matched HC (n=27) were found, tract-localized at baseline and widespread in the follow-up. Language assessment scores correlated with arcuate (AF) and uncinate (UF) fasciculi DTI measures. In left-ischemic stroke patients (n=16) recruited by the NatBrainLab, King’s College London, language recovery was longitudinally evaluated (6-months follow-up). Using arterial spin labelling imaging a significant correlation (p<0.01) between language recovery and cerebral blood flow asymmetry, was found in the middle cerebral artery perfusion, towards the right. In HC (n=29) recruited by the DIBINEM Functional MR Unit, University of Bologna, an along-tract algorithm was developed suitable for different tractography methods, using the Laplacian operator. A higher left superior temporal gyrus and precentral operculum AF connectivity was found (Talozzi L et al., 2018), and lateralized UF projections towards the left dorsal orbital cortex. In HC (n=50) recruited in the Human Connectome Project, a new tractography-driven approach was developed for left association fibres, using a principal component analysis. The first component discriminated cortical areas typically connected by the AF, suggesting a good discrimination of cortical areas sharing a similar connectivity pattern. The evaluation of morphological, microstructural and metabolic measures could be used as in-vivo biomarkers to monitor language impairment related to neurodegeneration or as surrogate of cognitive rehabilitation/interventional treatment efficacy.

Noises: a Nuisance and a Resource. Development of New Decomposition Methods of Noisy Data

Noise is constant presence in measurements. Its origin is related to the microscopic properties of matter. Since the seminal work of Brown in 1828, the study of stochastic processes has gained an increasing interest with the development of new mathematical and analytical tools. In the last decades, the central role that noise plays in chemical and physiological processes has become recognized. The dual role of noise as nuisance/resource pushes towards the development of new decomposition techniques that divide a signal into its deterministic and stochastic components. In this thesis I show how methods based on Singular Spectrum Analysis have the right properties to fulfil the previously mentioned requirement. During my work I applied SSA to different signals of interest in chemistry: I developed a novel iterative procedure for the denoising of powder X-ray diffractograms; I “denoised” bi-dimensional images from experiments of electrochemiluminescence imaging of micro-beads obtaining new insight on ECL mechanism. I also used Principal Component Analysis to investigate the relationship between brain electrophysiological signals and voice emission.

Statistical learning of random probability measures

The study of random probability measures is a lively research topic that has attracted interest from different fields in recent years. In this thesis, we consider random probability measures in the context of Bayesian nonparametrics, where the law of a random probability measure is used as prior distribution, and in the context of distributional data analysis, where the goal is to perform inference given avsample from the law of a random probability measure. The contributions contained in this thesis can be subdivided according to three different topics: (i) the use of almost surely discrete repulsive random measures (i.e., whose support points are well separated) for Bayesian model-based clustering, (ii) the proposal of new laws for collections of random probability measures for Bayesian density estimation of partially exchangeable data subdivided into different groups, and (iii) the study of principal component analysis and regression models for probability distributions seen as elements of the 2-Wasserstein space. Specifically, for point (i) above we propose an efficient Markov chain Monte Carlo algorithm for posterior inference, which sidesteps the need of split-merge reversible jump moves typically associated with poor performance, we propose a model for clustering high-dimensional data by introducing a novel class of anisotropic determinantal point processes, and study the distributional properties of the repulsive measures, shedding light on important theoretical results which enable more principled prior elicitation and more efficient posterior simulation algorithms. For point (ii) above, we consider several models suitable for clustering homogeneous populations, inducing spatial dependence across groups of data, extracting the characteristic traits common to all the data-groups, and propose a novel vector autoregressive model to study of growth curves of Singaporean kids. Finally, for point (iii), we propose a novel class of projected statistical methods for distributional data analysis for measures on the real line and on the unit-circle.

Antioxidant Activity Of Hydrophilic And Lipophilic Extracts Of Brazilian Blueberries.

Hydrophilic and lipophilic extracts of ten cultivars of Highbush and Rabbiteye Brazilian blueberries (Vaccinium corymbosum L. and Vacciniumashei Reade, respectively) that are used for commercial production were analysed for antioxidant activity by the FRAP, ORAC, ABTS and β-carotene-linoleate methods. Results were correlated to the amounts of carotenoids, total phenolics and anthocyanins. Brazilian blueberries had relatively high concentration of total phenolics (1,622-3,457 mg gallic acid equivalents per 100 g DW) and total anthocyanins (140-318 mg cyanidin-3-glucoside equivalents per 100 g DW), as well as being a good source of carotenoids. There was a higher positive correlation between the amounts of these compounds and the antioxidant activity of hydrophilic compared to lipophilic extracts. There were also significant differences in the level of bioactive compounds and antioxidant activities between different cultivars, production location and year of cultivation.

Determination Of Flavanones In Orange Juices Obtained From Different Sources By Hplc/dad.

Flavanones (hesperidin, naringenin, naringin, and poncirin) in industrial, hand-squeezed orange juices and from fresh-in-squeeze machines orange juices were determined by HPLC/DAD analysis using a previously described liquid-liquid extraction method. Method validation including the accuracy was performed by using recovery tests. Samples (36) collected from different Brazilian locations and brands were analyzed. Concentrations were determined using an external standard curve. The limits of detection (LOD) and the limits of quantification (LOQ) calculated were 0.0037, 1.87, 0.0147, and 0.0066 mg 100 g(-1) and 0.0089, 7.84, 0.0302, and 0.0200 mg 100 g(-1) for naringin, hesperidin, poncirin, and naringenin, respectively. The results demonstrated that hesperidin was present at the highest concentration levels, especially in the industrial orange juices. Its average content and concentration range were 69.85 and 18.80-139.00 mg 100 g(-1). The other flavanones showed the lowest concentration levels. The average contents and concentration ranges found were 0.019, 0.01-0.30, and 0.12 and 0.1-0.17, 0.13, and 0.01-0.36 mg 100 g(-1), respectively. The results were also evaluated using the principal component analysis (PCA) multivariate analysis technique which showed that poncirin, naringenin, and naringin were the principal elements that contributed to the variability in the sample concentrations.

Preference Mapping Of Dulce De Leche Commercialized In Brazilian Markets.

Dulce de leche samples available in the Brazilian market were submitted to sensory profiling by quantitative descriptive analysis and acceptance test, as well sensory evaluation using the just-about-right scale and purchase intent. External preference mapping and the ideal sensory characteristics of dulce de leche were determined. The results were also evaluated by principal component analysis, hierarchical cluster analysis, partial least squares regression, artificial neural networks, and logistic regression. Overall, significant product acceptance was related to intermediate scores of the sensory attributes in the descriptive test, and this trend was observed even after consumer segmentation. The results obtained by sensometric techniques showed that optimizing an ideal dulce de leche from the sensory standpoint is a multidimensional process, with necessary adjustments on the appearance, aroma, taste, and texture attributes of the product for better consumer acceptance and purchase. The optimum dulce de leche was characterized by high scores for the attributes sweet taste, caramel taste, brightness, color, and caramel aroma in accordance with the preference mapping findings. In industrial terms, this means changing the parameters used in the thermal treatment and quantitative changes in the ingredients used in formulations.

In Vivo Determination Of The Volatile Metabolites Of Saprotroph Fungi By Comprehensive Two-dimensional Gas Chromatography.

In this work, we discuss the use of multi-way principal component analysis combined with comprehensive two-dimensional gas chromatography to study the volatile metabolites of the saprophytic fungus Memnoniella sp. isolated in vivo by headspace solid-phase microextraction. This fungus has been identified as having the ability to induce plant resistance against pathogens, possibly through its volatile metabolites. Adequate culture media was inoculated, and its headspace was then sampled with a solid-phase microextraction fiber and chromatographed every 24 h over seven days. The raw chromatogram processing using multi-way principal component analysis allowed the determination of the inoculation period, during which the concentration of volatile metabolites was maximized, as well as the discrimination of the appropriate peaks from the complex culture media background. Several volatile metabolites not previously described in the literature on biocontrol fungi were observed, as well as sesquiterpenes and aliphatic alcohols. These results stress that, due to the complexity of multidimensional chromatographic data, multivariate tools might be mandatory even for apparently trivial tasks, such as the determination of the temporal profile of metabolite production and extinction. However, when compared with conventional gas chromatography, the complex data processing yields a considerable improvement in the information obtained from the samples. This article is protected by copyright. All rights reserved.

Profile Of Phenolic Compounds Of Brazilian Virgin Olive Oils By Rapid Resolution Liquid Chromatography Coupled To Electrospray Ionisation Time-of-flight Mass Spectrometry (rrlc-esi-tof-ms).

In recent years, agronomical researchers began to cultivate several olive varieties in different regions of Brazil to produce virgin olive oil (VOO). Because there has been no reported data regarding the phenolic profile of the first Brazilian VOO, the aim of this work was to determine phenolic contents of these samples using rapid-resolution liquid chromatography coupled to electrospray ionisation time-of-flight mass spectrometry. 25 VOO samples from Arbequina, Koroneiki, Arbosana, Grappolo, Manzanilla, Coratina, Frantoio and MGS Mariense varieties from three different Brazilian states and two crops were analysed. It was possible to quantify 19 phenolic compounds belonging to different classes. The results indicated that Brazilian VOOs have high total phenolic content because the values were comparable with those from high-quality VOOs produced in other countries. VOOs from Coratina, Arbosana and Grappolo presented the highest total phenolic content. These data will be useful in the development and improvement of Brazilian VOO.

Comparing Near-infrared Conventional Diffuse Reflectance Spectroscopy And Hyperspectral Imaging For Determination Of The Bulk Properties Of Solid Samples By Multivariate Regression: Determination Of Mooney Viscosity And Plasticity Indices Of Natural Rubber.

Conventional reflectance spectroscopy (NIRS) and hyperspectral imaging (HI) in the near-infrared region (1000-2500 nm) are evaluated and compared, using, as the case study, the determination of relevant properties related to the quality of natural rubber. Mooney viscosity (MV) and plasticity indices (PI) (PI0 - original plasticity, PI30 - plasticity after accelerated aging, and PRI - the plasticity retention index after accelerated aging) of rubber were determined using multivariate regression models. Two hundred and eighty six samples of rubber were measured using conventional and hyperspectral near-infrared imaging reflectance instruments in the range of 1000-2500 nm. The sample set was split into regression (n = 191) and external validation (n = 95) sub-sets. Three instruments were employed for data acquisition: a line scanning hyperspectral camera and two conventional FT-NIR spectrometers. Sample heterogeneity was evaluated using hyperspectral images obtained with a resolution of 150 × 150 μm and principal component analysis. The probed sample area (5 cm(2); 24,000 pixels) to achieve representativeness was found to be equivalent to the average of 6 spectra for a 1 cm diameter probing circular window of one FT-NIR instrument. The other spectrophotometer can probe the whole sample in only one measurement. The results show that the rubber properties can be determined with very similar accuracy and precision by Partial Least Square (PLS) regression models regardless of whether HI-NIR or conventional FT-NIR produce the spectral datasets. The best Root Mean Square Errors of Prediction (RMSEPs) of external validation for MV, PI0, PI30, and PRI were 4.3, 1.8, 3.4, and 5.3%, respectively. Though the quantitative results provided by the three instruments can be considered equivalent, the hyperspectral imaging instrument presents a number of advantages, being about 6 times faster than conventional bulk spectrometers, producing robust spectral data by ensuring sample representativeness, and minimizing the effect of the presence of contaminants.

Classificação de água de coco processada e natural por meio de HCA, PCA e teores de íons metálicos determinados por ICP OES

Inductively Coupled Plasma Optical Emission Spectrometry was used to determine Ca, Mg, Mn, Fe, Zn and Cu in samples of processed and natural coconut water. The sample preparation consisted in a filtration step followed by a dilution. The analysis was made employing optimized instrumental parameters and the results were evaluated using methods of Pattern Recognition. The data showed common concentration values for the analytes present in processed and natural samples. Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA) indicated that the samples of different kinds were statistically different when the concentrations of all the analytes were considered simultaneously.

Experimento didático de quimiometria para análise exploratória de óleos vegetais comestíveis por espectroscopia no infravermelho médio e análise de componentes principais: um tutorial, parte I

This manuscript aims to show the basic concepts and practical application of Principal Component Analysis (PCA) as a tutorial, using Matlab or Octave computing environment for beginners, undergraduate and graduate students. As a practical example it is shown the exploratory analysis of edible vegetable oils by mid infrared spectroscopy.

Perfil sensorial de ovos de Páscoa

Easter egg is a popular chocolate-candy in egg form commercialized in Brazil during Easter time. In this research, Quantitative Descriptive Analysis was applied to select sensory attributes which best define the modifications in appearance, aroma, flavor and texture when cocoa butter equivalent (CBE) is added to Easter eggs. Samples with and without CBE were evaluated by a selected panel and fourteen attributes best describing similarities and differences between them, were defined. Terms definition, reference materials and a consensus ballot were developed. After a training period, panelists evaluated the samples in a Complete Block Design using a 9 cm unstructured scale. Principal Component Analysis, ANOVA and Tukey test (p<0.05) were applied to the data in order to select attributes which best discriminated and characterized the samples. Samples showed significant differences (p<0.05) in all attributes. Easter egg without CBE showed higher intensities (p<0.05) in relation to the following descriptors: brown color, characteristic aroma, cocoa mass aroma, cocoa butter aroma, characteristic flavor, cocoa mass flavor, hardness and brittleness.