Melanomas account for more than 1.7% of global cancer diagnoses and about 1% of all skin cancer diagnoses in the United States. This type of cancer occurs in the melanin-producing cells in the epidermis and exhibits distinctive variations in melanin and blood concentration values in the form of skin lesions. The current approach for evaluating skin cancer lesions involves visual inspection with a dermatoscope, typically followed by biopsy and histopathological analysis. However, this process, to decrease the risk of misdiagnosis, results in unnecessary biopsies, contributing to the emotional and financial distress of patients. The implementation of a non-invasive imaging technique to aid the analysis of skin lesions in the early stages can potentially mitigate these consequences. Hyperspectral imaging (HSI) has shown promise as a non-invasive technique to analyze skin lesions. Images taken of human skin using a hyperspectral camera are a result of numerous elements in the skin. Being a turbid, inhomogeneous material, the skin has chromophores and scattering agents, which interact with light and produce characteristic back-scattered energy that can be harnessed and examined with an HSI camera. In this study, a mathematical model of the skin is used to extract meaningful information from the hyperspectral data in the form of melanin concentration, blood volume fraction and blood oxygen saturation in the skin. The human skin is modelled as a bi-layer planar system, whose surface reflectance is theoretically calculated using the Kubelka-Munk theory and absorption laws by Beer and Lambert. Hyperspectral images of the dorsal portion of three volunteer subjects' hands 400 - 1000 nm range, were used to estimate the contributing parameters. The mean and standard deviation of these estimates are reported compared with theoretical values from the literature. The model is also evaluated for its sensitivity with respect to these parameters, and then fitted to measured hyperspectral data of three volunteer subjects in different conditions. The wavelengths and wavelength groups which were identified to result in the maximum change in percentage reflectance calculated from the model were 450 and 660 nm for melanin, 500 - 520 nm and 590 - 625 nm for blood volume fraction and 606, 646 and 750 nm for blood oxygen saturation. / Master of Science / Melanoma, the most serious type of skin cancer, develops in the melanin-producing cells in the epidermis. A characteristic marker of skin lesions is the abrupt variations in melanin and blood concentration in areas of the lesion. The present technique to inspect skin cancer lesions involves dermatoscopy, which is a qualitative visual analysis of the lesion's features using a few standardized techniques such as the 7-point checklist and the ABCDE rule. Typically, dermatoscopy is followed by a biopsy and then a histopathological analysis of the biopsy. To reduce the possibility of misdiagnosing actual melanomas, a considerable number of dermoscopically unclear lesions are biopsied, increasing emotional, financial, and medical consequences. A non-invasive imaging technique to analyze skin lesions during the dermoscopic stage can help alleviate some of these consequences. Hyperspectral imaging (HSI) is a promising methodology to non-invasively analyze skin lesions. Images taken of human skin using a hyperspectral camera are a result of numerous elements in the skin. Being a turbid, inhomogeneous material, the skin has chromophores and scattering agents, which interact with light and produce characteristic back-scattered energy that can be harnessed and analyzed with an HSI camera. In this study, a mathematical model of the skin is used to extract meaningful information from the hyperspectral data in the form of melanin concentration, blood volume fraction and blood oxygen saturation. The mean and standard deviation of these estimates are reported compared with theoretical values from the literature. The model is also evaluated for its sensitivity with respect to these parameters, and then fitted to measured hyperspectral data of six volunteer subjects in different conditions. Wavelengths which capture the most influential changes in the model response are identified to be 450 and 660 nm for melanin, 500 - 520 nm and 590 - 625 nm for blood volume fraction and 606, 646 and 750 nm for blood oxygen saturation.

No description available.

Plant-based foods are considered to be more sustainable food source than animal-based foods due to their lower environmental impact. However, there is a challenge in producing plant-based foods with similar taste, texture, and appearance to animal-based products to meet consumers expectations. The appearance, which includes color, is the first sensory attribute consumers experience of foods, and so it influences consumers’ buying decisions. Food colorants are added to match the color of plant-based foods with animal-based ones. The food colorant choice is shifting toward natural colorants due to their perceived health benefits and clean-label aspects. Therefore, this study aimed to optimize the optical properties of plant-based foods using natural food colorants. Initially, the impact of natural pigments that selectively absorb light (turmeric, red beet, and butterfly pea flower) and colloidal particles that selectively scatter light (oil droplets) on the optical properties of model plant-based oil-in-water emulsions was investigated. It was found the pigment and oil droplet characteristics, including pigment type and concentration, and droplet size and concentration, could be adjusted to modulate the chromaticness or lightness of emulsions by altering light absorption and scattering effects. This knowledge is useful to optimizing the appearance of plant-based foods by adjusting these parameters. Then, natural pigments with three primary colors (yellow, red, and blue) were blended to mimic the color of animal-based products (raw meat, cooked meats, egg, and cheese). A color matching model developed from Kubelka-Munk and color theories was then used to determine the optimum ratio of each colorant needed to match the spectral reflectance of animal-based products. The methodology developed was able to optimize the color of model plant-based emulsions to that of different food matrices. The improved understanding of the optical properties of natural pigments and color matching theory developed in this study should help to formulate plant-based foods with more similar appearances to animal-based products, thereby increasing consumers’ acceptance of plant-based foods.

Melanomas account for more than 1.7% of global cancer diagnoses and about 1% of all skin cancer diagnoses in the United States. This type of cancer occurs in the melanin-producing cells in the epidermis and exhibits distinctive variations in melanin and blood concentration values in the form of skin lesions. The current approach for evaluating skin cancer lesions involves visual inspection with a dermatoscope, typically followed by biopsy and histopathological analysis. However, to decrease the risk of misdiagnosis in this process requires invasive biopsies, contributing to the emotional and financial distress of patients. The implementation of a non-invasive imaging technique to aid the analysis of skin lesions in the early stages can potentially mitigate these consequences. Hyperspectral imaging (HSI) has shown promise as a non-invasive technique to analyze skin lesions. Images taken of human skin using a hyperspectral camera are a result of numerous elements in the skin. Being a turbid, inhomogeneous material, the skin has chromophores and scattering agents, which interact with light and produce characteristic back-scattered energy that can be harnessed and examined with an HSI camera. To achieve this in this study, a mathematical model of the skin is used to extract meaningful information from the hyperspectral data in the form of parameters such as melanin concentration, blood volume fraction and blood oxygen saturation in the skin. The human skin is modelled as a bi-layer planar system, whose surface reflectance is theoretically calculated using the Kubelka-Munk theory and absorption laws by Beer and Lambert. The model is evaluated for its sensitivity to the parameters and then fitted to measured hyperspectral data of four volunteer subjects in different conditions. Mean values of melanin, blood volume fraction and oxygen saturation obtained for each of the subjects are reported and compared with theoretical values from literature. Sensitivity analysis revealed wavelengths and wavelength groups which resulted in maximum change in percentage reflectance calculated from the model were 450 and 660 nm for melanin, 500 - 520 nm and 590 - 625 nm for blood volume fraction and 606, 646 and 750 nm for blood oxygen saturation. / Master of Science / Melanoma, the most serious type of skin cancer, develops in the melanin-producing cells in the epidermis. A characteristic marker of skin lesions is the abrupt variations in melanin and blood concentration in areas of the lesion. The present technique to inspect skin cancer lesions involves dermatoscopy, which is a qualitative visual analysis of the lesion’s features using a few standardized techniques such as the 7-point checklist and the ABCDE rule. Typically, dermatoscopy is followed by a biopsy and then a histopathological analysis of the biopsy. To reduce the possibility of misdiagnosing actual melanomas, a considerable number of dermoscopically unclear lesions are biopsied, increasing emotional, financial, and medical consequences. A non-invasive imaging technique to analyze skin lesions during the dermoscopic stage can help alleviate some of these consequences. Hyperspectral imaging (HSI) is a promising methodology to non-invasively analyze skin lesions. Images taken of human skin using a hyperspectral camera are a result of numerous elements in the skin. Being a turbid, inhomogeneous material, the skin has chromophores and scattering agents, which interact with light and produce characteristic back-scattered energy that can be harnessed and analyzed with an HSI camera. In this study, a mathematical model of the skin is used to extract meaningful information from the hyperspectral data in the form of melanin concentration, blood volume fraction and blood oxygen saturation. The mean and standard deviation of these estimates are reported and compared with theoretical values from the literature. The model is also evaluated for its sensitivity with respect to these parameters to identify the most relevant wavelengths.

This thesis is about modelling and predicting the perceived whiteness of plain paper from the paper composition, including fluorescent whitening agents. This involves psychophysical modelling of perceived whiteness from measurable light reflectance properties, and physical modelling of light scattering and fluorescence from the paper composition. Existing models are first tested and improvements are suggested and evaluated. A colour appearance model including simultaneous contrast effects (CIECAM02-m2), earlier tested on coloured surfaces, is successfully applied to perceived whiteness. An extension of the Kubelka-Munk light scattering model including fluorescence for turbid media of finite thickness is successfully tested for the first time on real papers. It is extended to layered constructions with different layer optical properties and modified to enable parameter estimation with conventional d/0° spectrophotometers used in the paper industry. Lateral light scattering is studied to enable simulating the spatially resolved radiance factor from layered constructions, and angle-resolved radiance factor simulations are performed to study angular variation of whiteness. It is shown that the linear CIE whiteness equation fails to predict the perceived whiteness of highly white papers with distinct bluish tint. This equation is applicable only in a defined region of the colour space, a condition that is shown to be not fulfilled by many commercial office papers, although they appear white to most observers. The proposed non-linear whiteness equations give to these papers a whiteness value that correlates with their perceived whiteness, while application of the CIE whiteness equation outside its region of validity overestimates perceived whiteness. It is shown that the fluorescence efficiency of FWA is essentially dependent only on the ability of the FWA to absorb light in its absorption band. Increased FWA concentration leads accordingly to increased whiteness. However, since FWA absorbs light in the violet-blue region of the electromagnetic spectrum, the reflectance factor decreases in that region with increasing FWA amount. This violet-blue absorption tends to give a greener shade to the paper and explains most of the observed greening and whiteness saturation at larger FWA concentrations. A red-ward shift of the quantum efficiency is observed with increasing FWA concentration, but this is shown to have a negligible effect on the whiteness value. The results are directly applicable to industrial applications for better instrumental measurement of whiteness and thereby optimising the use of FWA with the goal to improve the perceived whiteness. / PaperOpt

This thesis is about modelling and predicting the perceived whiteness of plain paper from the paper composition, including fluorescent whitening agents. This includes psycho-physical modelling of perceived whiteness from measurable light reflectance properties, and physical modelling of light scattering and fluorescence from the paper composition. Existing models are first tested and improvements are suggested and evaluated. The standardised and widely used CIE whiteness equation is first tested on commercial office papers with visual evaluations by different panels of observers, and improved models are validated. Simultaneous contrast effects, known to affect the appearance of coloured surfaces depending on the surrounding colour, are shown to significantly affect the perceived whiteness. A colour appearance model including simultaneous contrast effects  (CIECAM02-m2), earlier tested on coloured surfaces, is successfully applied to perceived whiteness. A recently proposed extension of the Kubelka-Munk light scattering model including fluorescence for turbid media of finite thickness is successfully tested for the first time on real papers. It is shown that the linear CIE whiteness equation fails to predict the perceived whiteness of highly white papers with distinct bluish tint. This equation is applicable only in a defined region of the colour space, a condition that is shown to be not fulfilled by many commercial office papers, although they appear white to most observers. The proposed non-linear whiteness equations give to these papers a whiteness value that correlates with their perceived whiteness, while application of the CIE whiteness equation outside its region of validity overestimates perceived whiteness. It is shown that the quantum efficiency of two different fluorescent whitening agents (FWA) in plain paper is rather constant with FWA type, FWA concentration, filler content, and fibre type. Hence, the fluorescence efficiency is essentially dependent only on the ability of the FWA to absorb light in its absorption band.  Increased FWA concentration leads accordingly to increased whiteness. However, since FWA absorbs light in the violet-blue region of the electromagnetic spectrum, the reflectance factor decreases in that region with increasing FWA amount. This violet-blue absorption tends to give a greener shade to the paper and explains most of the observed greening and whiteness saturation at larger FWA concentrations. A red-ward shift of the quantum efficiency is observed with increasing FWA concentration, but this is shown to have a negligible effect on the whiteness value. The results are directly applicable to industrial applications for better instrumental measurement of whiteness and thereby optimising the use of FWA with the goal to improve the perceived whiteness. In addition, a modular Monte Carlo simulation tool, Open PaperOpt, is developed to allow future spatial- and angle-resolved particle level light scattering simulation. / PaperOpt

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No description available.

Internal waves (IWs) owe their existence to the stratification in the medium. These waves affect acoustic transmission greatly. Impact of these waves on acoustic transmission in deep water is fairly well understood due to better performance of well-celebrated Garrett-Munk (GM) model. However, in shallow waters, predicting these waves is not as easy, because of interactions with the bottom and surface. Hence two experiments, one during October 2002 and the other during October 2004 were conducted to characterize IWs in the shallow waters of northeastern Arabian Sea. The first experiment was carried out during October 2002 south of Gulf of Kutch (GOK) and the second experiment during October 2004 both south and north of GOK. During these experiments CTD moorings were deployed and temperature and salinity (TS) data were collected at 5 seconds interval. CTD Yo-Yo collected vertical profiles of TS at a sampling interval of 2.5 minutes for 3.5 hours during October 2002 and 1 hour during October 2004 experiment. In addition, during the first experiment, currents were measured using a vessel mounted Acoustic Doppler Current Profiler (ADCP), and in both experiments CTD TS profiles were taken from the ship. This data set has been used for characterizing internal waves in the northeastern Arabian Sea. Experiment conducted during October 2002, south of GOK has revealed large tidal ranges. The barotropic tidal range at the experimental site was 1.5m. Current observations made using the vessel mounted ADCP, along the shore and across the shore, showed signs of first mode (baroclinic) oscillations; currents in the top and bottom layers were in opposing directions. They were found to be southwesterly in the top layer and northeasterly in the bottom layer. Time - depth sections of TS profiles from CTD yo-yo data, revealed the presence of high frequency internal waves and solitons overriding on low frequency trend. Moored CTD time series of temperature records showed the presence of internal solitons, which caused a vertical displacement of about 8m in the isotherms, which is equivalent to 3OC change in temperature, in less than 10 minutes. Passage of internal solitons induced vertical mixing causing the mixed layer to deepen by about 10m and current speed increased by about 0.1 m/s. Internal solitons were traveling towards northwest and current vectors suggest that they were generated when the internal tide is reflected from the bottom. Vertical displacement spectra agreed well with GM spectra when solitons were not present. However, when the solitons were present the displacement spectra had higher energy levels compared to the GM spectra. Another experiment was done in October 2004, mainly aimed at characterizing internal solitons and to verify the consistency of the results obtained during October 2002 experiment. This experiment also showed that IWs of both high and low frequency along with internal solitons were present at the experimental site. It was found that internal solitons were more energetic during spring tide than the neap. The observed amplitudes of these solitons were around 12m and were not rank ordered suggesting that the experimental site is close to the generation point. It is believed that, generally, solitons get phase locked to the barotropic tide’s trough and travel. Such phase locking was not observed at the experimental site. They were observed riding on both troughs and crests of barotropic tide. One of the aims of this thesis is to develop a simulation model based on Garrett-Munk steady state internal wave spectrum. Hence, an internal wave model IWAVE was developed to simulate the sound speed structure due to internal waves. Sound speed structure is simulated instead of TS structure, because of their direct utility in sonar range prediction models. Since the GM model is a deep-water and mid-latitude model, it was calibrated to suite shallow-water tropical environment by incorporating the site and region specific parameters. EOFs and Dynamical modes estimated using TS profiles were used to identify the site-specific parameters of the GM model. Values for characteristic mode number and spectral slope used in the GM model are 3 and 2 respectively. However, it was found that they are different in the northeastern Arabian Sea. At this site, the characteristic mode number was found to be 1 and the spectral slope was found to be 3. The modified model was validated against the measured sound speed profiles. In the first case, the first sound speed profile (TS) of the CTD yo-yo data (20 October 2002) was used for predicting the remaining profiles and compared them with observations. This was done to verify the model’s ability to predict high frequency case (TS profiles are measured at every 2.5min.). In the second case, during October 2004, TS profiles collected at every one-hour for 24 hours were used. This gives an idea of the model’s performance for the low frequency case. The variances of the measured and simulated sound speed profiles matched well in both cases with the modified GM model.

Electron vortex beams (EVBs) are electron beams with a doughnut-like intensity profile, carrying orbital angular momentum due to their helical phase shift distribution. When employed in an electron microscope, they are expected to be efficient for the detection of magnetic signals. In this report I have investigated high angle annular dark field (HAADF) images obtained using EVBs. This was done for 300 K and 5K. For 5 K,  I also compared HAADF images from an ordinary electron beam with HAADF images from an electron vortex beam. What was found was that EVBs produced doughnuts around the atomic columns. However, when taking the size of the electron source into account, this phenomena could no longer  be observed. When comparing images from EVBs with images from ordinary electron beams, I found that the intensity of scattered electrons around atomic columns was broader for EVBs. This was persistent even after taking the source size into account. / Elektronvirvelstrålar (EVS) är elektronstrålar med en munk-liknande intensitetsprofil. Dessa bär på rörelsemängdsmoment på grund av sin fasdistribution. När de används i ett elektronmikroskop förväntas de vara effektiva för detektering av magnetiska signaler. I denna uppsats har jag undersökt high angle annular dark field (HAADF) bilder som erhållits med hjälp av EVS. Detta gjordes för 300 K och 5K. För 5 K, jämförde jag även HAADF bilder från en vanlig elektronstråle med HAADF bilder från en elektronvirvelstråle. Vad jag fann var att EVS producerade en munkformad intensitetsfördelning runt atomerna. Men när hänsyn till storleken på elektronkällan togs i beaktande kunde inte detta fenomen observeras längre. När bilder från EVS jämfördes med bilder från vanliga elektronstrålar, fann jag att intensiteten av spridda elektroner runt atomkolumnerna var bredare för EVS. Detta kunde observeras även efter att jag tagit hänsyn till elektronkällans storlek.