Finns det någon substans i uttrycket ”du blir smartare av att äta fisk”, eller är det bara en myt? Syftet med studien är att undersöka om kosten, sömnen och fysisk aktivitet har någon betydelse för elevernas studieresultat, i form av betyg i grundskolans årskurs 8, samt om det finns skillnader kopplat till kön. Att belysa vad som är viktigt i kostens sammansättning, måltidsvanor och hur det påverkar kognitionen. Andra viktiga faktorer är fysisk aktivitet och sömn, för att uppnå goda studieresultat. Enkätmetod, tabeller, principalkomponentanalys och Pearssons korrelationskoefficient har använts. Tendensen är att ju bättre hälsovanor desto bättre betyg. Förhoppningsvis kommer denna studie att bidra till att vidga kunskaperna kring sambandet mellan goda hälsovanor (med ingående komponenter kost, sömn och fysisk aktivitet) respektive ohälsosamma hälsovanor och studieresultat inom Hem- och konsumentkunskap. Vänligen skriv ut arbetet i färg, det ökar förståelsen. / Is there any substance in the phrase "you get smarter of eating fish" or is it just a myth? The purpose of the study is to investigate whether diet, sleep and physical activity have any significance for students' study results, in terms of grades in compulsory school grade eight, and if there are differences related to gender. To highlight what is important in the composition of the diet, eating habits and how it affects cognition. Other important factors are physical activity and sleep, to achieve good study results. Survey methods, tables, principal component analysis and Pearsson correlation coefficient have been used. The tendency is that the better the health habits, the better the grade. Hopefully, this study will help to broaden the knowledge of the link between healthy lifestyle (including components of diet, sleep and physical activity) and unhealthy health habits and study results in Home- and consumer knowledge.Please print the work in color, it increases understanding.

The study aimed at evaluating tree and shrub vegetation concerning the slope of the soil in Seasonal Deciduous Forest. The vegetation assessment was conducted in 14 plots systematically distributed in the forest and divided into subplots of 10 x 10 m, in which individuals with circumference 1.3 m of soil (CAP) ≥ 30 cm were observed. These individuals represented class I while individuals with a CAP ≥ 15 < 30 cm represented class II. Vegetation was analyzed by means of the TWINSPAN (Two-way Indicator Species Analysis) method to classify groups, within which the horizontal structure of the forest was studied. In 36 subplots, morphological description of the soil profile was carried out, samples were collected for chemical analysis and clay was determined at three depths (0-10, 10-20 and 20-30 cm), as well as slope, which was classified as low slope (1 ≥ 15), medium slope (15 ≥ 35) and high slope (≥35). The relationship between clusters of vegetation, slope and soil characteristics was studied by means of Principal Component Analysis (PCA). In G1, indicator species were Trichilia claussenii, Cupania vernalis and Crysophyllum marginatum and, in G2, Luehea divaricata and Sebastiania commersoniana. In terms of horizontal structure, these species were among the three best represented ones. Both clusters occurred in areas of variable slope, however, G2 took place in an environment which was more susceptible to interference in the vegetation. From PCA, it could be observed that soil characteristics and slope explained 26% of the total variability, and, out of these, 72% was explained in the main component 1, showing a strong correlation between soil characteristics and the presence of phytosociological groups in different slopes. This relationship is stronger for the presence of the two groups in the ranges of medium and high slope, on the other hand, in terms of low slope, the two groups showed no positive correlation with soil characteristics. For G1 in high slope and G2 in medium and high slope, correlation is positive concerning the whole characteristics of cationic exchange. However, G1 in medium slope was strongly correlated to the complex of exchangeable acidity. G2 at higher slopes also shows high correlation with clay, the finer texture may confer a greater degree of aggregation and reactivity, allowing the development of large species such as Luehea divaricata and Cordia americana. In general, due to restrictions of soil and slope, maintaining of the remnants is prior, aiming at important environmental services for the region. / O estudo objetivou avaliar a vegetação arbórea e arbustiva em relação à formação de agrupamentos, declividade do terreno e influência do solo nos agrupamentos em Floresta Estacional Decidual. A avaliação da vegetação foi realizada em 14 parcelas distribuídas sistematicamente na floresta e divididas em subparcelas de 10 x 10 m, onde foram observados os indivíduos com CAP (circunferência a 1,3 m do solo) ≥ 30 cm, os quais representaram a classe I, e indivíduos com 15 ≤ CAP < 30 cm, representando a classe II. Na análise da vegetação utilizou-se o método TWINSPAN (Two-way Indicator Species Analysis) para classificação de grupos, dentro dos quais foi estudada a estrutura horizontal da floresta. Em 36 subparcelas foi realizada a descrição morfológica do perfil do solo, coletada amostra para análise química e determinação de argila em três profundidades (0-10, 10-20 e 20-30 cm), além da declividade, que foi classificada em baixa (1 ≥ 15º), média (15 ≥ 35º) e alta (≥ 35º). A relação com os grupos e características do solo foi estudada por meio de Análise de Componente Principal (PCA). No G1 as espécies indicadoras foram Trichilia claussenii, Cupania vernalis e Crysophyllum marginatum e no grupo G2 Luehea divaricata e Sebastiania commersoniania. Na estrutura horizontal essas espécies estiveram entre as três melhores representadas. Ambos os agrupamentos ocorreram em áreas com variáveis declividades, entretanto, o G2 ocorreu em ambiente mais susceptível às interferências na vegetação. A partir do PCA observou-se que as características do solo e declividade explicaram 26% da variabilidade total, sendo que desses 72% foi explicado no componente principal 1, demonstrando forte correlação entre as características dos solos e a presença dos grupos fitossociológicos em diferentes declividades. Essa relação foi mais expressiva para a presença dos dois grupos nos intervalos de média e alta declividade, por outro lado, em declividade baixa os dois grupos não apresentaram correlação positiva com as características do solo. Para G1 em alta e G2 em média e alta declividade, a correlação é positiva em relação ao conjunto de características de troca catiônica. Entretanto, o G1 em declividade média teve forte correlação com o complexo de acidez trocável. O G2 em maior declividade também apresenta alta correlação com a argila, essa textura mais fina talvez confira um maior poder de agregação e reatividade, permitindo o desenvolvimento de espécies de grande porte como Luehea divaricata e Cordia americana. De forma geral, devido às restrições de solo e declividade, a manutenção do remanescente é prioritária visando importantes serviços ambientais à região.

Abstract The goal of this study was to explore preoperative evaluation of patients with intracranial tumours using magnetic resonance imaging (MRI) methods: oedema-attenuated inversion recovery (EDAIR) sequence in low-field MRI, and diffusion-weighted imaging (DWI) and resting-state functional MRI (fMRI) in high-field MRI. The aim was also to increase our knowledge about the effects of brain surgery on eloquent brain cortices using new MRI techniques. The total number of patients in these studies was 50 (24 women). Enhancement of the tumour in ten patients after intravenous administration of gadolinium-based contrast agent in low-field MRI was examined with a new sequence, EDAIR, and compared with more conventionally used partial saturation spin echo sequences. EDAIR may facilitate the perception of small enhancing lesions and is valuable in low-field imaging, where T1-based contrast is inferior to high-field imaging. DWI was performed on 25 patients in order to evaluate the potential of this imaging method to assist in differential diagnosis of intracranial tumours. It was shown that apparent diffusion coefficient values of the tumour and peritumoural oedema produced by DWI were different in benign and malignant tumours. Resting-state blood oxygen level-dependent (BOLD) fMRI was performed on eight patients and ten healthy volunteers to examine if functional sensorimotor areas in the brain could be determined without any task-related activations. It was shown that intracranial tumours do not appear to hamper visualization of the sensorimotor area in resting-state BOLD fMRI when independent component analysis is performed, and this method may be used in preoperative imaging when activation studies cannot be performed. Conventional BOLD fMRI with motor and auditory stimuli was used with seven patients as the effect of brain surgery was studied. The results suggest that resection of a tumour with preoperative oedema probably decreases pressure on the brain and makes the functional cortex transiently more easily detectable in BOLD fMRI. In conclusion, the MRI imaging methods used in this study can give valuable additional information about the tumour, specifically for preoperative imaging and planning for surgery.

Heart Rate Variability (HRV) analysis has been garnering attention from researchers due to its wide range of applications. Medical researchers have always been interested in Heart Rate (HR) and HRV analysis, but nowadays, investigators from variety of other fields are also probing the subject. For instance, variation in HR and HRV is connected to emotional arousal. Therefore, knowledge from the fields of affective computing and psychology, can be employed to devise machines that understand the emotional states of humans. Recent advancements in non-contact HR and HRV measurement techniques will likely further boost interest in emotional estimation through . Such measurement methods involve the extraction of the photoplethysmography (PPG) signal from the human's face through a camera. The latest approaches apply Independent Component Analysis (ICA) on the color channels of video recordings to extract a PPG signal. Other investigated methods rely on Eulerian Video Magnification (EVM) to detect subtle changes in skin color associated with PPG. The effectiveness of the EVM in HR estimation has well been established. However, to the best of our knowledge, EVM has not been successfully employed to extract HRV feature from a video of a human face. In contrast, ICA based methods have been successfully used for HRV analysis. As we demonstrate in this thesis, these two approaches for HRV feature extraction are highly sensitive to noise. Hence, when we evaluated them in indoor settings, we obtained mean absolute error in the range of 0.012 and 28.4. Therefore, in this thesis, we present two approaches to minimize the error rate when estimating physiological measurements from recorded facial videos using a standard camera. In our first approach which is based on the EVM method, we succeeded in extracting HRV measurements but we could not get rid of high frequency noise, which resulted in a high error percentage for the result of the High frequency (HF) component. Our second proposed approach solved this issue by applying ICA on the red, green and blue (RGB) colors channels and we were able to achieve lower error rates and less noisy signal as compared to previous related works. This was done by using a Buterworth filter with the subject's specific HR range as its Cut-Off. The methods were tested with 12 subjects from the DISCOVER lab at the University of Ottawa, using artificial lights as the only source of illumination. This made it a challenge for us because artificial light produces HF signals which can interfere with the PPG signal. The final results show that our proposed ICA based method has a mean absolute error (MAE) of 0.006, 0.005, 0.34, 0.57 and 0.419 for the mean HR, mean RR, LF, HF and LF/HF respectively. This approach also shows that these physiological parameters are highly correlated with the results taken from the electrocardiography (ECG).

This dissertation explored the way in which bumblebees' visual system helps them discover their first flower. Previous studies found bees have unlearned preferences for parts of a flower, such as its colour and shape. The first study pitted two variables against each other: pattern type: sunburst or bull's eye, versus the location of the pattern: shapes appeared peripherally or centrally. We observed free-flying bees in a flight cage using Radio-Frequency Identification (RFID) tracking. The results show two distinct behavioural preferences: Pattern type predicts landing: bees prefer radial over concentric patterns, regardless of whether the radial pattern is on the perimeter or near the centre of the flower. Pattern location predicts exploration: bees were more likely to explore the inside of artificial flowers if the shapes were displayed near the centre of the flower, regardless of whether the pattern was radial or concentric. As part of the second component, we implemented a mathematical model aimed at explaining how bees come to prefer radial patterns, leafy backgrounds and symmetry. The model was based on unsupervised neural networks used to describe cognitive mechanisms. The results captured with the results of multiple behavioural experiments. The model suggests that bees choose computationally "cheaper" stimuli, those that contain less information. The third study tested the computational load hypothesis generated by the artificial neural networks. Visual properties of symmetry, and spatial frequency were tested. Studying free-flying bees in a flight cage using motion-sensitive video recordings, we found that bees preferred 4-axis symmetrical patterns in both low and high frequency displays.

The main objective of this thesis is to summarize and possibly interconnect the existing methodology on principal components analysis, hierarchical clustering and topological organization in the financial and economic networks, linear regression and GARCH modeling. In the thesis the clustering ability of PCA is compared with the more conventional approaches on a set of world stock market indices returns in different time periods where the time division is represented by The World Financial Crisis of 2007-2009. It is also observed whether the clustering of DJIA index components is underlied by the industry sector to which the individual stocks belong. Joining together PCA with classical linear regression creates principal components regression which is further in the thesis applied to the German DAX 30 index logarithmic returns forecasting using various macroeconomic and financial predictors. The correlation between two energy stocks returns - Chevron and ExxonMobil is forecasted using orthogonal (or PCA) GARCH. The constructed forecast is then compared with the predictions constructed by the conventional multivariate volatility models - EWMA and DCC GARCH.

The mortality is historically one of the most important demographic indicator and definitely reflects the maturity of each country. The objective of this diploma thesis is the comparison of mortality rates in analyzed countries around the world over time and among each other using the principle component analysis that allows assessing data different way. The big advantage of this method is minimal loss of information and quite understandable interpretation of mortality in each country. This thesis offers several interesting graphical outputs, that for example confirm higher mortality rate in Eastern European countries compared to Western European countries and show that Czech republic is country where mortality has fallen most in context of post-communist countries between 1990 and 2010. Source of the data is Human Mortality Database and all data were processed in statistical tool SPSS.

The healthy condition of a rotating machine leads to safe and cheap operation of almost all industrial facilities and mechanical systems. To achieve such a goal, vibration-based condition monitoring has proved to be a well-accepted technique that detects incipient fault symptoms. The conventional way of On-Bearing Vibration Measurement (OBVM) captures symptoms of different faults, however, it requires a relatively expensive setup, an additional space for the auxiliary devices and cabling in addition to an experienced analyst. On-Shaft Vibration Measurement (OSVM) is an emerging method proposed to offer more reliable Faults Diagnosis (FD) tools with less number of sensors, minimal processing time and lower system and maintenance costs. The advancement in sensor and wireless communications technologies enables attaching a MEMS accelerometer with a miniaturised wireless data acquisition unit directly to the rotor without altering the machine dynamics. In this study, OSVM is analysed during constant speed and run-up operations of a test rig. The observations showed response modulation, hence, a Finite Element (FE) analysis has been carried out to help interpret the experimental observations. The FE analysis confirmed that the modulation is due to the rotary motion of the on-shaft sensor. A demodulation method has been developed to solve this problem. The FD capability of OSVM has been compared to that of OBVM using conventional analysis where the former provided more efficient diagnosis with less number of sensors. To incorporate more features, a method has been developed to diagnose faults based on Principal Component Analysis and Nearest Neighbour classifier. Furthermore, the method is enhanced using Linear Discriminant Analysis to do the diagnosis without the need for a classifier. Another faults diagnosis method has been developed that ensures the generalisation of extracted faults features from OSVM data of a specific machine to similar machines mounted on different foundations.

Orientador: Martin Tygel / Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Matemática Estatística e Computação Cientifica / Made available in DSpace on 2018-08-22T06:13:33Z (GMT). No. of bitstreams: 1 CostaFilho_CarlosAlbertoda_M.pdf: 3131395 bytes, checksum: f8687abfc7e346fdd8e6dc40746526e8 (MD5) Previous issue date: 2013 / Resumo: As reflexões de ondas sísmicas na subsuperfície terrestre podem ser colocadas em duas categorias disjuntas: reflexões primárias e múltiplas. Reflexões primárias carregam informações pontuais sobre um refletor específico, enquanto reflexões múltiplas carregam informações sobre interfaces e pontos de reflexão variados. Consequentemente é usual tentar atenuar reflexões múltiplas e trabalhar somente com reflexões primárias. Neste trabalho, a teoria de ondas acústicas é desenvolvida somente a partir da equação da onda. Um resultado que demonstra como a propagação de ondas acústicas pode ser descrita somente com uma única multiplicação por matriz é exposta. Este resultado permite que um algoritmo seja desenvolvido que, em teoria, pode ser usado para remover todas as reflexões múltiplas que refletiram na superfície pelo menos uma vez. Uma implementação prática deste algoritmo é mostrada. Por conseguinte, a teoria de análise de componentes independentes é apresentada. Suas considerações teóricas e práticas são abordadas. Finalmente, ela é usada em conjunção com o método de eliminação de múltiplas de superfície para atenuar múltiplas de quatro dados diferentes. Estes resultados são então analisados e a eficácia do método é avaliada / Abstract: The reflections of seismic waves in the subsurface of the Earth can be placed under two disjoint categories: primary and multiple reflections. Primary reflections carry pointwise information about a specific reflector while multiple reflections carry informations about various interfaces and reflection points. Consequently, it is customary to attempt to attenuate multiple reflections and work solely with primary reflections. In this work, the theory of acoustic waves is developed solely from the wave equation. A result that shows how acoustic wave propagation can be described as a single matrix multiplication is exposed. This result enables one to develop an algorithm that, in theory, can be used to remove all multiple reflections that have reflected on the surface at least once. The practical implementation of this algorithm is shown. Thereafter, the theory of independent component analysis is presented. Its theoretical and practical considerations are addressed. Finally, it is used in conjunction with the surface-related multiple elimination method to attenuate multiples in four different datasets. These results are then analyzed and the efficacy of the method is evaluated / Mestrado / Matematica Aplicada / Mestre em Matemática Aplicada

Submitted by Biblioteca Central (biblioteca@unicap.br) on 2018-06-05T17:18:37Z No. of bitstreams: 2 vicente_natanael_lima_silva.pdf: 2871330 bytes, checksum: 1730e0371d28b2975de3c999a484a82b (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Made available in DSpace on 2018-06-05T17:18:37Z (GMT). No. of bitstreams: 2 vicente_natanael_lima_silva.pdf: 2871330 bytes, checksum: 1730e0371d28b2975de3c999a484a82b (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Previous issue date: 2018-04-10 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES# / #2075167498588264571# / #600 / In the State of Pernambuco, as well as throughout the Northeast region of Brazil, the expressive interaction between climate elements and human activities is evident. Numerous scientific studies have already demonstrated a significant correlation between climate behavior with social, economic, cultural, etc. This work served as a case study of the application of the multivariate statistical technique of Principal Components Analysis (PCA) in the making of socioeconomic diagnoses, where the elements of the climate were used as independent variables on the socioeconomic responses (Gross Domestic Product and Municipal Development Index) Of some municipalities that presented significant development in the State of Pernambuco - Brazil, between 1999 and 2013. Even considering the climatic, socioeconomic and essential dependence of water for the economic development of the municipalities studied, the PCA showed that the socioeconomic indexes of the municipalities located in the Sertão (Petrolina and Arcoverde) will present a higher correlation with the indices of temperature and Insulation, in the Agreste and Zona da Mata (Garanhuns and Surubim) evaporation and temperatures, in the Litoral (Recife) precipitation and humidity. The PCA was also effective in allowing the removal or disposal of variables that presented low variability or were redundant because they were correlated with those of greater importance for the first two main components. Understanding the behavior of climate elements and their consequences on human activities is of fundamental importance in helping public policies to mitigate the adverse effects of environmental change. / No Estado de Pernambuco, assim como em toda a região do Nordeste do Brasil, é evidente a expressiva interação existente entre os elementos do clima e as atividades humanas. Inúmeros estudos científicos já demostraram uma significativa correlação entre o comportamento climático com os aspectos sociais, econômicos, culturais, etc. Este trabalho serviu como estudo de caso da aplicação da técnica estatística multivariada de Análise de Componentes Principais (ACP) na confecção de diagnósticos socioeconômicos, onde foram utilizados os elementos do clima como independentes sobre as variáveis respostas socioeconômicas (Produto Interno Bruto e Índice de Desenvolvimento Municipal) de alguns municípios que apresentaram expressivo desenvolvimento no Estado de Pernambuco – Brasil, entre os anos de 1999 e 2013. Mesmo considerando as diferenças climáticas, socioeconômicas e a imprescindível dependência da água para o desenvolvimento econômico dos municípios estudados, a ACP demostrou que os índices socioeconômicos dos municípios localizados no Sertão (Petrolina e Arcoverde) apresentarão maior correlação com os índices de temperaturas e Insolação, no Agreste e Zona da Mata (Garanhuns e Surubim) a evaporação e temperaturas, no Litoral (Recife) a precipitação e umidade. ACP mostrou-se também efetiva em permitir a retirada ou descarte de variáveis que apresentaram baixa variabilidade ou foram redundantes por estarem correlacionadas com as de maior importância para dois primeiros componentes principais. A compreensão do comportamento dos elementos do clima e de suas consequências sobre as atividades humanas é de fundamental importância no auxílio às políticas públicas, que visem à mitigação de efeitos adversos provocados pelas alterações ambientais.