Väriavaruuden rakenteen muokkaaminen yhtenäisyyden parantamiseksi

Pienien värierojen mittaamiseen käytetään CIE:n (The International Commission on Illumination) kehittämää ja standardoitua CIELAB – väriavaruutta ja sille suunniteltua CIEDE2000 – värieromittaria. CIELAB ei kuitenkaan ole täysin yhtenäinen ja siksi mittareita joudutaan virittämään sopivammiksi tähän väriavaruuteen. Työssä tutkitaan millä tavoin CIELAB - väriavaruutta voitaisiin korjata, jotta siitä saataisiin yhtenäisempi ja yksinkertainen ja virittämättömämpi värieromittari toimisi siinä paremmin. Työn tuloksena saatu muokattu väriavaruus paransi yhtenäisyyttä keskimäärin kymmenen prosenttia, mikä on liian vähän kun tavoitteena oli 30 - 50 prosenttia.

Intrapartum hypoxia and power spectral analysis of fetal heart rate variability

Reliable detection of intrapartum fetal acidosis is crucial for preventing morbidity. Hypoxia-related changes of fetal heart rate variability (FHRV) are controlled by the autonomic nervous system. Subtle changes in FHRV that cannot be identified by inspection can be detected and quantified by power spectral analysis. Sympathetic activity relates to low-frequency FHRV and parasympathetic activity to both low- and high-frequency FHRV. The aim was to study whether intra partum fetal acidosis can be detected by analyzing spectral powers of FHRV, and whether spectral powers associate with hypoxia-induced changes in the fetal electrocardiogram and with the pH of fetal blood samples taken intrapartum. The FHRV of 817 R-R interval recordings, collected as a part of European multicenter studies, were analyzed. Acidosis was defined as cord pH ≤ 7.05 or scalp pH ≤ 7.20, and metabolic acidosis as cord pH ≤ 7.05 and base deficit ≥ 12 mmol/l. Intrapartum hypoxia increased the spectral powers of FHRV. As fetal acidosis deepened, FHRV decreased: fetuses with significant birth acidosis had, after an initial increase, a drop in spectral powers near delivery, suggesting a breakdown of fetal compensation. Furthermore, a change in excess of 30% of the low-to-high frequency ratio of FHRV was associated with fetal metabolic acidosis. The results suggest that a decrease in the spectral powers of FHRV signals concern for fetal wellbeing. A single measure alone cannot be used to reveal fetal hypoxia since the spectral powers vary widely intra-individually. With technical developments, continuous assessment of intra-individual changes in spectral powers of FHRV might aid in the detection of fetal compromise due to hypoxia.

Theoretical Analysis and Numerical Simulation of Spectral Radiative Properties of Combustion Gases in Oxy/Air-Fired Combustion Systems

Energy efficiency is one of the major objectives which should be achieved in order to implement the limited energy resources of the world in a sustainable way. Since radiative heat transfer is the dominant heat transfer mechanism in most of fossil fuel combustion systems, more accurate insight and models may cause improvement in the energy efficiency of the new designed combustion systems. The radiative properties of combustion gases are highly wavelength dependent. Better models for calculating the radiative properties of combustion gases are highly required in the modeling of large scale industrial combustion systems. With detailed knowledge of spectral radiative properties of gases, the modeling of combustion processes in the different applications can be more accurate. In order to propose a new method for effective non gray modeling of radiative heat transfer in combustion systems, different models for the spectral properties of gases including SNBM, EWBM, and WSGGM have been studied in this research. Using this detailed analysis of different approaches, the thesis presents new methods for gray and non gray radiative heat transfer modeling in homogeneous and inhomogeneous H2O–CO2 mixtures at atmospheric pressure. The proposed method is able to support the modeling of a wide range of combustion systems including the oxy-fired combustion scenario. The new methods are based on implementing some pre-obtained correlations for the total emissivity and band absorption coefficient of H2O–CO2 mixtures in different temperatures, gas compositions, and optical path lengths. They can be easily used within any commercial CFD software for radiative heat transfer modeling resulting in more accurate, simple, and fast calculations. The new methods were successfully used in CFD modeling by applying them to industrial scale backpass channel under oxy-fired conditions. The developed approaches are more accurate compared with other methods; moreover, they can provide complete explanation and detailed analysis of the radiation heat transfer in different systems under different combustion conditions. The methods were verified by applying them to some benchmarks, and they showed a good level of accuracy and computational speed compared to other methods. Furthermore, the implementation of the suggested banded approach in CFD software is very easy and straightforward.

The Effects of Anesthetic Induced Loss of Consciousness on Quantitative Electroen Cephalogram, and Bispectral and Spectral Entropy Indices. Studies on Healthy Male

Changes in the electroencephalography (EEG) signal have been used to study the effects of anesthetic agents on the brain function. Several commercial EEG based anesthesia depth monitors have been developed to measure the level of the hypnotic component of anesthesia. Specific anesthetic related changes can be seen in the EEG, but still it remains difficult to determine whether the subject is consciousness or not during anesthesia. EEG reactivity to external stimuli may be seen in unconsciousness subjects, in anesthesia or even in coma. Changes in regional cerebral blood flow, which can be measured with positron emission tomography (PET), can be used as a surrogate for changes in neuronal activity. The aim of this study was to investigate the effects of dexmedetomidine, propofol, sevoflurane and xenon on the EEG and the behavior of two commercial anesthesia depth monitors, Bispectral Index (BIS) and Entropy. Slowly escalating drug concentrations were used with dexmedetomidine, propofol and sevoflurane. EEG reactivity at clinically determined similar level of consciousness was studied and the performance of BIS and Entropy in differentiating consciousness form unconsciousness was evaluated. Changes in brain activity during emergence from dexmedetomidine and propofol induced unconsciousness were studied using PET imaging. Additionally, the effects of normobaric hyperoxia, induced during denitrogenation prior to xenon anesthesia induction, on the EEG were studied. Dexmedetomidine and propofol caused increases in the low frequency, high amplitude (delta 0.5-4 Hz and theta 4.1-8 Hz) EEG activity during stepwise increased drug concentrations from the awake state to unconsciousness. With sevoflurane, an increase in delta activity was also seen, and an increase in alpha- slow beta (8.1-15 Hz) band power was seen in both propofol and sevoflurane. EEG reactivity to a verbal command in the unconsciousness state was best retained with propofol, and almost disappeared with sevoflurane. The ability of BIS and Entropy to differentiate consciousness from unconsciousness was poor. At the emergence from dexmedetomidine and propofol induced unconsciousness, activation was detected in deep brain structures, but not within the cortex. In xenon anesthesia, EEG band powers increased in delta, theta and alpha (8-12Hz) frequencies. In steady state xenon anesthesia, BIS and Entropy indices were low and these monitors seemed to work well in xenon anesthesia. Normobaric hyperoxia alone did not cause changes in the EEG. All of these results are based on studies in healthy volunteers and their application to clinical practice should be considered carefully.

Support vector machines in spectral data classification

Työssä käydään läpi tukivektorikoneiden teoreettista pohjaa sekä tutkitaan eri parametrien vaikutusta spektridatan luokitteluun.

Detection of Illicit Drugs and Drug Precursors with Cantilever-Enhanced Photoacoustic Spectroscopy

In this study, cantilever-enhanced photoacoustic spectroscopy (CEPAS) was applied in different drug detection schemes. The study was divided into two different applications: trace detection of vaporized drugs and drug precursors in the gas-phase, and detection of cocaine abuse in hair. The main focus, however, was the study of hair samples. In the gas-phase, methyl benzoate, a hydrolysis product of cocaine hydrochloride, and benzyl methyl ketone (BMK), a precursor of amphetamine and methamphetamine were investigated. In the solid-phase, hair samples from cocaine overdose patients were measured and compared to a drug-free reference group. As hair consists mostly of long fibrous proteins generally called keratin, proteins from fingernails and saliva were also studied for comparison. Different measurement setups were applied in this study. Gas measurements were carried out using quantum cascade lasers (QLC) as a source in the photoacoustic detection. Also, an external cavity (EC) design was used for a broader tuning range. Detection limits of 3.4 particles per billion (ppb) for methyl benzoate and 26 ppb for BMK in 0.9 s were achieved with the EC-QCL PAS setup. The achieved detection limits are sufficient for realistic drug detection applications. The measurements from drug overdose patients were carried out using Fourier transform infrared (FTIR) PAS. The drug-containing hair samples and drug-free samples were both measured with the FTIR-PAS setup, and the measured spectra were analyzed statistically with principal component analysis (PCA). The two groups were separated by their spectra with PCA and proper spectral pre-processing. To improve the method, ECQCL measurements of the hair samples, and studies using photoacoustic microsampling techniques, were performed. High quality, high-resolution spectra with a broad tuning range were recorded from a single hair fiber. This broad tuning range of an EC-QCL has not previously been used in the photoacoustic spectroscopy of solids. However, no drug detection studies were performed with the EC-QCL solid-phase setup.

Tuning cell motility : roles of nestin and vimentin in cancer cell invasion and motility

The cytoskeleton is a key feature of both prokaryotic and eukaryotic cells. Itis comprised of three protein families, one of which is the intermediate filaments (IFs). Of these, the IFs are the largest and most diverse. The IFs are expressed throughout life, and are involved in the regulation of cell differentiation, homeostasis, ageing and pathogenesis. The IFs not only provide structural integrity to the cell, they are also involved in a range of cellular functions from organelle trafficking and cell migration to signalling transduction. The IFs are highly dynamic proteins, able to respond and adapt their network rapidly in response to intra- and extra- cellular cues. Consequently they interact with a whole host of cellular signalling proteins, regulating function, and activity, and cellular localisation. While the function of some of the better-known IFs such as the keratins is well studied, the understanding of the function of two IFs, nestin and vimentin, is poor. Nestin is well known as a marker of differentiation and is expressed in some cancers. In cancer, nestin is primarily described as is a promoter of cell motility, however, how it fulfils this role remains undefined. Vimentin too is expressed in cancer, and is known to promote cell motility and is used as a marker for epithelial to mesenchymal transition (EMT). It is only in the last decade that studies have addressed the role that vimentin plays in cell motility and EMT. This work provides novel insight into how the IFs, nestin and vimentin regulate cell motility and invasion. In particular we show that nestin regulates the cellular localisation and organisation of two key facilitators of cell migration, focal adhesion kinase and integrins. We identify nestin as a regulator of extracellular matrix degradation and integrin-mediated cell invasion. Two further studies address the specific regulation of vimentin by phosphorylation. A detailed characterisation study identified key phosphorylation sites on vimentin, which are critical for proper organisation of the vimentin network. Furthermore, we show that the bioactive sphingolipids are vimentin network regulators. Specifically, the sphingolipids induced RhoA kinasedependent (ROCK) phosphorylation at vimentin S71, which lead to filament reorganisation and inhibition of cell migration. Together these studies shed new light into the regulation of nestin and vimentin during cell motility.

Intensification of hemicellulose hot-water extraction from spruce wood by parameter tuning

The growing population on earth along with diminishing fossil deposits and the climate change debate calls out for a better utilization of renewable, bio-based materials. In a biorefinery perspective, the renewable biomass is converted into many different products such as fuels, chemicals, and materials, quite similar to the petroleum refinery industry. Since forests cover about one third of the land surface on earth, ligno-cellulosic biomass is the most abundant renewable resource available. The natural first step in a biorefinery is separation and isolation of the different compounds the biomass is comprised of. The major components in wood are cellulose, hemicellulose, and lignin, all of which can be made into various end-products. Today, focus normally lies on utilizing only one component, e.g., the cellulose in the Kraft pulping process. It would be highly desirable to utilize all the different compounds, both from an economical and environmental point of view. The separation process should therefore be optimized. Hemicelluloses can partly be extracted with hot-water prior to pulping. Depending in the severity of the extraction, the hemicelluloses are degraded to various degrees. In order to be able to choose from a variety of different end-products, the hemicelluloses should be as intact as possible after the extraction. The main focus of this work has been on preserving the hemicellulose molar mass throughout the extraction at a high yield by actively controlling the extraction pH at the high temperatures used. Since it has not been possible to measure pH during an extraction due to the high temperatures, the extraction pH has remained a “black box”. Therefore, a high-temperature in-line pH measuring system was developed, validated, and tested for hot-water wood extractions. One crucial step in the measurements is calibration, therefore extensive efforts was put on developing a reliable calibration procedure. Initial extractions with wood showed that the actual extraction pH was ~0.35 pH units higher than previously believed. The measuring system was also equipped with a controller connected to a pump. With this addition it was possible to control the extraction to any desired pH set point. When the pH dropped below the set point, the controller started pumping in alkali and by that the desired set point was maintained very accurately. Analyses of the extracted hemicelluloses showed that less hemicelluloses were extracted at higher pH but with a higher molar-mass. Monomer formation could, at a certain pH level, be completely inhibited. Increasing the temperature, but maintaining a specific pH set point, would speed up the extraction without degrading the molar-mass of the hemicelluloses and thereby intensifying the extraction. The diffusion of the dissolved hemicelluloses from the wood particle is a major part of the extraction process. Therefore, a particle size study ranging from 0.5 mm wood particles to industrial size wood chips was conducted to investigate the internal mass transfer of the hemicelluloses. Unsurprisingly, it showed that hemicelluloses were extracted faster from smaller wood particles than larger although it did not seem to have a substantial effect on the average molar mass of the extracted hemicelluloses. However, smaller particle sizes require more energy to manufacture and thus increases the economic cost. Since bark comprises 10 – 15 % of a tree, it is important to also consider it in a biorefinery concept. Spruce inner and outer bark was hot-water extracted separately to investigate the possibility to isolate the bark hemicelluloses. It was showed that the bark hemicelluloses comprised mostly of pectic material and differed considerably from the wood hemicelluloses. The bark hemicelluloses, or pectins, could be extracted at lower temperatures than the wood hemicelluloses. A chemical characterization, done separately on inner and outer bark, showed that inner bark contained over 10 % stilbene glucosides that could be extracted already at 100 °C with aqueous acetone.

Tympanometry and Spectral Gradient Acoustic Reflectometry in the Diagnosis of Otitis Media in Young Children

Acute otitis media (AOM) is the most prevalent bacterial infection among children. Tympanometry and spectral gradient acoustic reflectometry (SG-AR) are adjunctive diagnostic tools to pneumatic otoscopy. The aim was to investigate the diagnostic accuracy and success rates of tympanometry and SG-AR performed by physicians and nurses. The study populations comprised 515 (I-II), 281 (III), and 156 (IV) outpatients (6-35 months). Physicians performed 4246 tympanometric (I) and SG-AR (II) examinations. Nurses performed 1782 (III) and 753 (IV) examinations at symptomatic and asymptomatic visits, respectively. Pneumatic otoscopy by the physician was the diagnostic standard. The accuracy of test results by physicians or nurses (I-IV) and the proportion of visits with accurate exclusive test results from both ears (III-IV) were analyzed. Type B tympanogram and SG-AR level 5 (<49˚) predicted middle ear effusion (MEE). At asymptomatic visits, type A and C1 tympanograms (peak pressure > -200 daPa) and SG-AR level 1 (>95˚) indicated healthy middle ear. Negative predictive values of type A and C1 tympanograms by nurses in excluding AOM at symptomatic and MEE at asymptomatic visits were 94% and 95%, respectively. Nurses obtained type A or C1 tympanogram from both ears at 94/459 (20%) and 81/196 (41%) of symptomatic and asymptomatic visits, respectively. SG-AR level 1 was rarely obtained from both ears. Type A and C1 tympanograms were accurate in excluding AOM at symptomatic and MEE at asymptomatic visits. However, nurses obtained these tympanograms from both ears only at one fifth of symptomatic visits and less than half of asymptomatic visits.

Spectral characteristics of bacteriorhodopsin water solution

The object of the study is bacteriorhodopsin. This light-sensitive protein have been selected as perspective substance for optical and optoelectronic applications. Bacteriorhodopsin carries out pumping protons through the cell membrane. Biomolecule converts light into an electric signal when sandwiched between electrodes. These properties were utilized in this research to implement photosensors on the basis of BR layers. These properties were utilized in this research to the bR water solution. According to the absorption spectra and using Kramers – Kronig relation the extinction coefficient has been calculated, as well as the related change of the refractive index value.

Spectral Analysis of Symmetric and Anti-Symmetric Pairwise Kernels

This work investigates theoretical properties of symmetric and anti-symmetric kernels. First chapters give an overview of the theory of kernels used in supervised machine learning. Central focus is on the regularized least squares algorithm, which is motivated as a problem of function reconstruction through an abstract inverse problem. Brief review of reproducing kernel Hilbert spaces shows how kernels define an implicit hypothesis space with multiple equivalent characterizations and how this space may be modified by incorporating prior knowledge. Mathematical results of the abstract inverse problem, in particular spectral properties, pseudoinverse and regularization are recollected and then specialized to kernels. Symmetric and anti-symmetric kernels are applied in relation learning problems which incorporate prior knowledge that the relation is symmetric or anti-symmetric, respectively. Theoretical properties of these kernels are proved in a draft this thesis is based on and comprehensively referenced here. These proofs show that these kernels can be guaranteed to learn only symmetric or anti-symmetric relations, and they can learn any relations relative to the original kernel modified to learn only symmetric or anti-symmetric parts. Further results prove spectral properties of these kernels, central result being a simple inequality for the the trace of the estimator, also called the effective dimension. This quantity is used in learning bounds to guarantee smaller variance.

Spectral retinal image processing and analysis for ophthalmology

Diabetic retinopathy, age-related macular degeneration and glaucoma are the leading causes of blindness worldwide. Automatic methods for diagnosis exist, but their performance is limited by the quality of the data. Spectral retinal images provide a significantly better representation of the colour information than common grayscale or red-green-blue retinal imaging, having the potential to improve the performance of automatic diagnosis methods. This work studies the image processing techniques required for composing spectral retinal images with accurate reflection spectra, including wavelength channel image registration, spectral and spatial calibration, illumination correction, and the estimation of depth information from image disparities. The composition of a spectral retinal image database of patients with diabetic retinopathy is described. The database includes gold standards for a number of pathologies and retinal structures, marked by two expert ophthalmologists. The diagnostic applications of the reflectance spectra are studied using supervised classifiers for lesion detection. In addition, inversion of a model of light transport is used to estimate histological parameters from the reflectance spectra. Experimental results suggest that the methods for composing, calibrating and postprocessing spectral images presented in this work can be used to improve the quality of the spectral data. The experiments on the direct and indirect use of the data show the diagnostic potential of spectral retinal data over standard retinal images. The use of spectral data could improve automatic and semi-automated diagnostics for the screening of retinal diseases, for the quantitative detection of retinal changes for follow-up, clinically relevant end-points for clinical studies and development of new therapeutic modalities.

Spectral Retinal Images Reconstruction

While red-green-blue (RGB) image of retina has quite limited information, retinal multispectral images provide both spatial and spectral information which could enhance the capability of exploring the eye-related problems in their early stages. In this thesis, two learning-based algorithms for reconstructing of spectral retinal images from the RGB images are developed by a two-step manner. First, related previous techniques are reviewed and studied. Then, the most suitable methods are enhanced and combined to have new algorithms for the reconstruction of spectral retinal images. The proposed approaches are based on radial basis function network to learn a mapping from tristimulus colour space to multi-spectral space. The resemblance level of reproduced spectral images and original images is estimated using spectral distance metrics spectral angle mapper, spectral correlation mapper, and spectral information divergence, which show a promising result from the suggested algorithms.