The thesis comprises four papers. The overall aim was to illuminate meanings of becoming and being burnt out respectively not becoming or being burnt out. The papers deal with two groups of healthcare personnel, one group on sick leave due to medically assessed burnout (n=20) and one group who showed no indications of burnout (n=20) from the same workplaces at psychiatric (n=7) and elderly (n=7) care units. A further aim was to describe personality traits and to elucidate perceptions of conscience (PCQ), stress of conscience (SCQ), moral sensitivity (MSQ-R), social support (SocIS) and resilience (RS) among the people in these two groups. Papers I and II are based on the text of narrative interviews interpreted using a phenomenological-hermeneutic method. Papers III and IV are based on data, pertaining to the same participants as in Papers I and II, derived from the following questionnaires; Cattell’s Sixteen Personality Factors Questionnaire (16PF) (III), ‘Perception of Conscience’ (PCQ), ‘Stress of Conscience’ (SCQ), ‘Moral Sensitivity Revised’ (MSQ-R), ‘Social Interactions Scale’ (SocIS) and ‘Resilience Scale’ (RS) (IV). Conventional statistical methods and Partial Least Square Regression (PLSR) were used to analyse the data (III, IV). In Paper I the aim was to illuminate meanings of becoming and being burnt out as narrated by healthcare personnel. The results show that meanings of becoming and being burnt out is to be torn between what one wants to manage and what one can actually manage. It is as if one’s ideals become more like demands for, regardless of the circumstances, one must be and show that one is capable and independent. It also means being dissatisfied with oneself for not living up to one’s own ideals as well as being disappointed in other people for not providing the confirmation one strives for. Feelings that one is a victim of circumstances emerge. Becoming and being burnt out leads to a futile struggle to live up to one’s ideals and when failing to unite one’s ideal picture with one’s reality one finally reaches an overwhelming feebleness. In Paper II the aim was to illuminate meanings of not becoming or being burnt out at workplaces where others developed burnout, as narrated by healthcare personnel. The results show that meanings of not becoming or being burnt out are to be rooted in an outlook on life which perceives its many-sidedness of prosperity, adversity, strength and weakness in oneself and others. An openness towards the circumstances of life emerges. Being able to judge the possibilities of influencing things, as well as being able to let go of injustice and look after oneself with a clear conscience are revealed as meanings of not becoming and being burnt out. In Paper III the aim was to describe personality traits among burnt out and non-burnt out healthcare personnel from the same workplaces. The results show, that the people in the burnt out group had lower scores regarding emotional stability and higher scores regarding anxiety than the people in the non-burnt out group but the results also showed a wide variation of personality traits within the groups. The most important indicators for belonging to the burnt out group were openness to changes and anxiety, and for belonging to the non-burnt out group, emotional stability, liveliness, privateness and tension. In Paper IV the aims were to elucidate perceptions of conscience, stress of conscience, moral sensitivity, social support and resilience among burnt out and non-burnt out healthcare personnel from the same workplaces. The results show that higher levels of stress of conscience and moral sensitivity, a perception of conscience as a burden, having to deaden one’s conscience in order to keep working in healthcare and perceiving a lack of support from those around them characterize the burnt out group. Those in the non-burnt out group are characterised by lower levels of stress of conscience, an out-look on life with a forbearing attitude, a perception of conscience as an asset, an ability to deal with one’s conscience in a constructive way and a perception of receiving support from those around them. The comprehensive understanding from the four papers (I-IV) is discussed in light of a theoretical framework derived from Emmy van Deurzens thoughts about the four life worlds: the natural world (the physical world), the public world (the social world), the private world (the psychological world) and the ideal world (the spiritual world). The result can be summarized in terms of the human condition in life and demonstrates the essential importance of reconciling the vita activa (the active life of labor, work and action), the vita contemplativa (thinking, willing and judging) and not least the vita regenerativa (rest and recovery) in order to avoid being burned out. / Samvetsstress i vården

This thesis is a part of a project where a new method, the base descriptor approach, is studied. The purpose of this method is to reduce drift and extract vital information from electronic tongue measurements. Reference solutions, called descriptors, are measured and the measurements are used to find base descriptors. A base descriptor is, in this thesis, a regression vector for prediction of the property that the descriptor represent. The property is in this case the concentration of a chemical substance in the descriptor solution. Measurements from test samples, in this case fruit juices, are projected onto the base descriptors to extract vital and drift-stable information from the test samples. The base descriptors are used to determine the concentrations of the descriptors'chemical substances in the juices and thereby also to classify the different juices. It is assumed that the measurements of samples of juices and descriptors drift the same way. This assumption has to be true in order for the base descriptor approach to work. The base descriptors are calculated by multivariate regression methods like partial least squares regression (PLSR) and principal component regression (PCR). Only two of the descriptors tested in this thesis worked as basis for base descriptors. The base descriptors'predictions of the concentrations of chemical substances in the juices are hard to evaluate since the true concentrations are unknown. Comparing the projections of juice measurements onto the base descriptors with a classification model on the juice measurements performed by principal component analysis (PCA), there is no significant difference in drift of the juice measurements in the results of the two methods. The base descriptors, however, separates the juices for classification somewhat better than the classification of juices performed by PCA.

The world’s population is increasing and along with it, the demand for food. A novel parametric model (Volterra Non-linear Regressive with eXogenous inputs (VNRX)) is introduced for quantifying influences of individual and multiple soil properties on crop yield and normalised difference vegetation Index. The performance was compared to a random forest method over two consecutive years, with the best results of 55.6% and 52%, respectively. The VNRX was then implemented using high sampling resolution soil data collected with an on-line visible and near infrared (vis-NIR) spectroscopy sensor predicting yield variation of 23.21%. A hyperspectral imager coupled with partial least squares regression was successfully applied in the detection of fusarium head blight and yellow rust infection in winter wheat and barley canopies, under laboratory and on-line measurement conditions. Maps of the two diseases were developed for four fields. Spectral indices of the standard deviation between 500 to 650 nm, and the squared difference between 650 and 700 nm, were found to be useful in differentiating between the two diseases, in the two crops, under variable water stress. The optimisation of the hyperspectral imager for field measurement was based on signal-to-noise ratio, and considered; camera angle and distance, integration time, and light source angle and distance from the crop canopy. The study summarises in the proposal of a new method of disease management through suggested selective harvest and fungicide applications, for winter wheat and barley which theoretically reduced fungicide rate by an average of 24% and offers a combined saving of the two methods of £83 per hectare.

Submitted by ROMÁRIO PIMENTA GOMES null (rpgagronomia@gmail.com) on 2017-09-26T18:24:04Z No. of bitstreams: 1 Dissertação_Romário_Pimenta_Gomes.pdf: 4952587 bytes, checksum: 38b374e1aebb3432a8e755c6e9f28a77 (MD5) / Approved for entry into archive by Monique Sasaki (sayumi_sasaki@hotmail.com) on 2017-09-28T13:04:39Z (GMT) No. of bitstreams: 1 gomes_rp_me_jabo.pdf: 4952587 bytes, checksum: 38b374e1aebb3432a8e755c6e9f28a77 (MD5) / Made available in DSpace on 2017-09-28T13:04:39Z (GMT). No. of bitstreams: 1 gomes_rp_me_jabo.pdf: 4952587 bytes, checksum: 38b374e1aebb3432a8e755c6e9f28a77 (MD5) Previous issue date: 2017-07-27 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / Nos solos tropicais, o fenômeno de adsorção de fósforo é regido pela mineralogia da fração argila, que, por sua vez, é afetada pelo material de origem e intensidade de dissecação da paisagem. Desse modo, objetivou-se relacionar o fósforo total e adsorvido com principais minerais da fração argila dos solos do Planalto Ocidental Paulista, São Paulo, associando com a geologia e o grau de dissecação da paisagem. Foram selecionadas cinquenta e cinco amostras de solo representativas da variabilidade fisiográfica do Planalto Ocidental Paulista, na profundidade de 0,0 – 0,2 m, para a caracterização das formas de fósforo, mineralogia da argila por difração de raios-x (DRX) e espectroscopia de reflectância difusa (ERD); utilizou-se também calibração quimiométrica através da regressão de mínimos quadrados parciais (PLSR). Verificou-se que o P total e o P adsorvido são influenciados pela geologia e grau de dissecação da paisagem, e são covariativos dos óxidos de Fe e Al, sendo esses óxidos importantes indicadores de ambientes com maiores e menores potenciais de adsorção e com baixos e altos teores de P. A caracterização das curvas espectrais permite diferenciar o conteúdo de P total com base na mineralogia da fração argila. A análise por regressão de mínimos quadrados parciais (PLSR) dos dados espectrais evidencia a influência dos óxidos de ferro no conteúdo de P total e adsorvido, sendo a Hm ao P total e a Gt ao P adsorvido. / In tropical soils, the phenomenon of phosphorus adsorption is governed by the mineralogy of the clay fraction, which in turn is affected by the material of origin and intensity of dissection of the landscape. the objective was to relate the total phosphorus and adsorbed with the main minerals of the clay fraction of the soils of the Planalto Ocidental Paulista, associating with the geology and the degree of dissection of the landscape. Were selected fifty - five soil samples representative of the physiographic variability of the Planalto Ocidental Paulista, in the depth of 0.0 - 0.2 m, for the characterization of phosphorus forms, clay mineralogy by X - ray diffraction (XRD) and diffuse reflectance spectroscopy (DRS); it was also used chemometric calibration Through the partial least squares regression (PLSR). It was verified that the total P and adsorbed P are influenced by the geology and degree of dissection of the landscape, and are covariate of the Fe and Al oxides, and these oxides are important indicators of environments with higher and lower adsorption potentials and with low and high levels of P. The characterization of the spectral curves allows to differentiate the total P content based on the mineralogy of the clay fraction. Partial least squares regression analysis (PLSR) of the spectral data shows the influence of iron oxides on the total and adsorbed P content, with Hm at the total P and Gt at the adsorbed P.

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The use of Silicon Carbide Field Effect Transistor (SiC-FET) sensors in cyclic operation is a proven way to quantify different gases. The standard workflow involves extracting shape-defining features such as averages and slopes of the sensor signal. This work’s main goal is to verify if frequency modulation can be used to simultaneously quantify Nitric Oxide (NO), Nitrogen Dioxide (NO2) and Ammonia (NH3). Linear models were chosen, namely: Ordinary Least Squares (OLS), Principal Components Regression (PCR), Partial Least Squares Regression (PLSR) and Ridge regression. Results indicate that these models fail to predict concentrations completely for every gas. Analysis indicates that the features are not linear in terms of concentrations. This work is concluded by recommending a few other alternatives before discarding frequency cycling completely: non-parametric models of regression and different frequency regime, namely the use of triangular waves in future experiments.

<p>In recent years, measuring customer satisfaction has become one of the key concerns of market research studies. One of the basic features of leading companies is their success in fulfilling their customers’ demands. For that reason, companies attempt to find out what essential factors dominate their customers’ purchasing habits.</p> <p>Millennium Research Group (MRG) - a global authority on medical tech- nology market intelligence - uses a web-based survey tool to collect informa- tion about customers’ level of satisfaction. One of their surveys is designed to gather information about the practitioner’s level of satisfaction on different brands of dental implants. The Dental Implants dataset obtained from the survey tool has thirty-four attributes, and practitioners were asked to rank or specify their level of satisfaction by assigning a score to each attribute.</p> <p>The basic question asked by the company was whether the attributes were useful to make customer behavior predictions. The aim of this study is to assess the reliability and accuracy of these measures and to build a model for future predictions, then, determine the attributes that are most influential</p> <p>in the practitioners’ purchasing decisions. Classification and regression trees (CART) and Partial least squares regression (PLSR) are the two statistical approaches used in this study to build a prediction model for the Dental Implants dataset.</p> <p>The prediction models generated, using both of the techniques, have rel- atively small prediction powers; which may be perceived as an indication of deficiency in the dataset. However, getting a small prediction power is gener- ally expected in market research studies. The research then attempts to find ways to improve the power of these models to get more accurate results. The model generated by CART analysis tends to have better prediction power and is more suitable for future predictions. Although PLSR provides extremely small prediction power, it helps finding out the most important attributes that influence the practitioners’ purchasing decisions. Improvements in pre- diction are sought by restricting the cases in the data to subsets that show better alignment between predictors and customer purchasing behaviour.</p> / Master of Science (MSc)

A adoção de medidas afinadas à conservação do solo não é apenas uma necessidade, há muito passou a ser estratégico desenvolver técnicas que preencham as lacunas de informação e maximizem o uso adequado do solo. A diferenciação textural entre horizontes de solos é um dos principais aspectos a ser considerado quando do planejamento do uso do solo, pois se relaciona estreitamente com fatores como o enraizamento, a percolação e disponibilidade de água e a susceptibilidade dos solos à erosão. Diante disso, objetivou-se desenvolver Índices Espectroscópicos de Relação Textural (IERT) que estabeleçam quantitativamente o grau de diferenciação textural em perfis de solos via espectroscopia VisNIR-SWIR (350-2.500 nm) e MidIR (4000 - 400 cm-1). Foram utilizados dados espectrais de 150 perfis de solos descritos morfologicamente pertencentes a nove municípios das regiões Sudeste e Centro-Oeste do Brasil. Três modelos espectrais, VisNIR-SWIR, MidIR e VisNIR-SWIR-MidIR foram associados aos teores analíticos de matéria orgânica dos horizontes A e B, totalizando nove modelos, afim de se verificar o potencial daqueles puramente espectrais. Todos os modelos foram estudados por análises de funções discriminantes (CP-AFD) e regressão por mínimos quadrados (PLSR). A construção dos IERT\'s, num total de 15, cinco para cada modelo espectral, considerou a diferença de reflectância em bandas específicas ou associações entre elas, as quais foram selecionadas com base no estudo qualitativo e quantitativo das curvas espectrais. De modo geral, a diferenciação entre horizontes é ditada pelas regiões espectrais associadas principalmente aos óxidos de Fe, minerais de argila e quartzo. É possível determinar o grau de diferenciação textural entre horizontes de perfis de solos com excelente acurácia através de dados espectrais com taxa de acerto global de até 100 %, R2 de 0,76 a 0,82 e RPD de 2,02 a 2,35 nos modelos puramente espectrais, com destaque à região MidIR. O uso de IERT\'s produz bons a excelentes resultados, com R2 de 0,71 a 0,80 e RDP de 1,84 a 2,21 para os melhores índices de cada região espectral. O uso de índices espectrais reduz a dependência de métodos estatísticos avançados e dá suporte ao desenvolvimento de equipamentos óticos que trabalhem em regiões espectrais específicas, reduzindo custos e maximizando a aplicabilidade da técnica. Estudos abrangentes e exaustivos são indispensáveis antes que novos métodos como este se estabeleçam, particularmente em ciência do solo, na qual o objeto de estudo é, por natureza, complexo e intrigante. / The adoption of measures related to soil conservation is not only a necessity, long it has become strategic to develop techniques that meet the information deficits and maximize the appropriate use of land. The textural differentiation between soil horizons is one of the main aspects to be considered dealing with land use planning as it closely relates to factors such as rooting, percolation and water availability and the susceptibility of soils to erosion. Therefore, it was aimed to develop Spectral Textural Ratio Indices (STRI) that quantitatively establish the degree of textural differentiation in soil profiles through VisNIR-SWIR (350-2500 nm) and MidIR (4000- 400 cm-1) spectroscopy. Spectral data of 150 soil profiles morphologically described belonging to nine municipalities in the Southeast and Midwest of Brazil were used. Three spectral models, VisNIR-SWIR, MidIR and VisNIR-SWIR-MidIR were associated with analytical organic matter content of the A and B horizons, comprising nine models in order to verify the potential of those purely spectral. All models were studied by discriminant functions analysis (CP-DFA) and Partial Least Square Regression (PLSR). The construction of the STRIs, a total of 15, five for each spectral model, considered the reflectance difference in specific bands or associations between them, which were selected based on the qualitative and quantitative study of spectral curves. In general, the differentiation between horizons is dictated primarily by spectral regions associated with iron oxides, clay minerals and quartz. It is possible to determine the degree of textural differentiation between soil profile horizons with great accuracy through spectral data with overall accuracy rate of up to 100%, R2 from 0.76 to 0.82 and RPD from 2.02 to 2.35 in the purely spectral models, with emphasis on MidIR region. The use of STRIs produces good to excellent results, with R2 ranging from 0.71 to 0.80 and RPD ranging from 1.84 to 2.21 for the best rates of each spectral region. The use of spectral indices reduces reliance on advanced statistical methods and supports the development of optical devices that work in specific spectral regions, reducing costs and maximizing the applicability of the technique. Large and exhaustive studies are imperatives before new methods like this are established, particularly in soil science, in which the object of study is by nature complex and intriguing.

Made available in DSpace on 2017-07-21T18:53:09Z (GMT). No. of bitstreams: 1 Mary Dias Queji.pdf: 909281 bytes, checksum: 0364cd27c13b09019850a0944168a898 (MD5) Previous issue date: 2008-04-05 / The agro industry of the apple generates, during the processing, the pomace which is considered the main by-product. Studies show that of the total amount of fruit that is processed to obtain the apple juice, 20 to 40 correspond to this by-product, which, is usually destined as a complement in animal feed or delivered onto the soil as organic fertilizer. The chemical composition, in moist base, is constituted by moisture (80), fibers (5) and soluble solids (14) represented, mainly, by fructose, glucose and sucrose, as well as, by organic acids, represented, in the most part by malic acid. The apple pomace also presents phenolic compounds that are target nutrients of great sensory and nutritional importance. Therefore, the quantification of its constituents represents an important source of data in the characterization of apple pomace for biotechnological purposes, seeking to attribute an appropriate use for this by-product. The conventional methodologies used for the quantification of sugars, organic acids and total phenols, although being part of the routine analyses in the quality control laboratories, are onerous, time consuming and generate residues. The aim of this study was to develop a fast, versatile analytical technique, of low cost and no pollutant, using the diffuse reflectance infrared spectroscopy (DRIFTS) allied to methods of multivariate calibration (PLSR). For the construction of the multivariate models, the averages of the concentrations of the simple sugars, malic acid and total phenols were used, obtained by the conventional methodologies, as well as the data in the medium infrared spectroscopy (MID) and near (NIR), obtained in duplicate, and of the 52 spectra obtained for the samples of apple pomace, 47 made part of the set calibration and 5 of the set validation. The regression models for the prediction of the concentration of fructose, sucrose, total phenols and malic acid obtained better results in MID, with averages of relative standard errors of 3.9 (with 5 Latents Variable), 6.6 (with 5 Latents Variable), 6.4 (with 4 Latents Variable) and 5.9 (with 5 Latents Variable), respectively. Already the best capacity prediction for glucose concentration was obtained by NIR, in which the average of relative standard error was 7.4 (with 6 Latents Variable). The obtained results demonstrate the good capacity of prediction of the multivariate models based in infrared spectroscopy and characteristic advantages of the association DRIFTPLSR. / A agroindústria da maçã gera, durante o processamento, o bagaço que é considerado o principal subproduto deste setor. Levantamentos mostram que da quantidade total de fruta que é processada para a obtenção do suco de maçã, 20 a 40 correspondem a este subproduto, que, normalmente, é destinado como complemento na alimentação animal ou dispensado no solo como adubo orgânico. Sua composição química, em base úmida, é constituída por umidade (80), fibras (5) e sólidos solúveis (14), estes últimos representados, principalmente, por frutose, glucose e sacarose, bem como, ácidos orgânicos, representados, majoritariamente pelo ácido málico. O bagaço da maçã também apresenta compostos fenólicos, que são fito-nutrientes de grande importância sensorial e nutricional. Portanto, a quantificação desses constituintes representa uma importante fonte de dados na caracterização do bagaço de maçã para finalidades biotecnológicas, visando atribuir um fim mais nobre a este subproduto. As metodologias convencionais empregadas para a quantificação de açúcares, ácidos orgânicos e fenóis totais, embora façam parte das análises de rotina nos laboratórios de controle de qualidade, são onerosas, demoradas e geram resíduos. O objetivo deste trabalho foi desenvolver uma técnica analítica rápida, versátil, de baixo custo e não poluente. Para tal, utilizou-se a espectroscopia no infravermelho por refletância difusa (DRIFTS) aliada a métodos de calibração multivariada (Regressão de Mínimos Quadrados Parciais - PLSR). Para a construção dos modelos multivariados, foram utilizadas as médias das concentrações dos açúcares simples, ácido málico e fenóis totais, obtidas pelas metodologias convencionais, bem como, os dados de espectroscopia no infravermelho médio (MID) e próximo (NIR). Os espectros foram obtidos em duplicata, sendo que dos 52 espectros das amostras de bagaço de maçã, 47 fizeram parte do conjunto de calibração e 5 do conjunto de validação externa. Os modelos de regressão para a previsão da concentração de frutose, sacarose, fenóis totais e ácido málico obtiveram melhores resultados no MID, com médias de erro padrão relativo de 3.9 (com 5 Variáveis Latentes), 6.6 (com 5 Variáveis Latentes), 6.4 (com 4 Variáveis Latentes) e 5.9 (com 5 Variáveis Latentes), respectivamente. Já a melhor capacidade de previsão para a concentração de glucose foi obtida pelo NIR, na qual a média de erro padrão relativo foi de 7.4 (com 6 Variáveis Latentes). Os resultados obtidos demonstram a boa capacidade de previsão dos modelos multivariados fundamentados em espectroscopia no infravermelho e vantagens características da associação DRIFT-PLSR.