Fundação de Amparo a Pesquisa do Estado de Minas Gerais / Analyses of soils and plants, essential for crop fertilization management, are based on methodologies that are time and reagent consuming. Near infrared spectroscopy (NIR - Near-infrared) has proven as a faster and cleaner alternative for simultaneous quantification of compounds. This study evaluates the methodologies based on NIR combined with multivariate calibration methods to estimate levels of silicon (Si), organic matter (O.M.) and clay in soils, and total nitrogen (N-Total) in maize and soybean leaves. Calibration of models for soil analysis was done with 170 soil samples while that for leaf analysis used 109 (58 maize and 51 soybean), obtaining their spectra in a near infrared spectroscopy NIR model 900PLS belonging to the Laboratory Fertilizers, Federal University of Uberlandia (Lafer), Uberlândia-MG, where the models were built. The mathematical method used was the partial least squares: PLS. The model validation has been crossed and the number of latent variables ranged between 5 and 8. The reference methods for comparison were: colorimetric-extraction with calcium chloride (0,01 mol L-1) for analysis of soluble Si in the soil, Walkley-Black Colorimetric analysis of O.M. and the pipette method for clay analysis. The models for determination of N-Total were compared to the Semimicro-Kjeldahl method. After calibration and cross validation, the models were tested and the results evaluated using the correlation coefficient (r), the calibration (RMSEC) and the prediction errors (RMSEP), and relative error (ER). Also, Student s t test at 0,05 significance was used to test for equality between averages. Correlations of 0,71, 0,84 and 0,85 were obtained in the calibration of models for analysis of Si content in the soil, O.M. and clay, respectively. The prediction from these models showed low correlations (lower than 0,5) with significant t test for silicon and clay. The RMSEC obtained from Si analysis was 2,03, RMSEP of 5,74 and ER of 59,2%. To O.M. the RMSEC was 0,81, RMSEP = 1,03 and ER = 39,3%. The analysis of clay presented RMSEC = 11,2, RMSEP = 16,55 and ER = 34,7%. In the analysis of maize and soybean leaf nitrogen calibration correlations of 0,85 and 0,88 were obtained, respectively. Good correlations were obtained for prediction of maize (r = 0,80) and soybean (0,76) samples, with non significant t-test, indicating that leaf analysis for the values predicted by the models NIR/PLS did not differ from those of the reference methods. Calibration and prediction errors for N in maize and soybean were smaller than 5,0 g kg-1, and the ER for N analysis in maize (8,3%) greater than that of soybean (5,7%). The observed results demonstrate greater efficiency in the use of near infrared analysis for leaf than for soil analysis. / As análises de solos e plantas, essenciais no manejo da adubação das culturas, estão baseadas em metodologias que consomem tempo e reagentes. A espectroscopia de infravermelho próximo (NIR Near-infrared) tem se mostrado uma alternativa mais rápida e limpa para quantificação simultânea de compostos. Objetivou-se nesse trabalho avaliar as metodologias baseadas na região NIR, aliada a métodos de calibração multivariada para estimar teores de silício (Si), matéria orgânica (M.O.) e argila em solos e, nitrogênio total (N-Total) em folhas de milho e soja. Para isto, 170 amostras de solos foram utilizadas para a calibração de modelos de análises de solos e 109 amostras de folhas (58 de milho e 51 de soja), sendo seus espectros obtidos em um espectrofotômetro de infravermelho próximo modelo NIR 900PLS pertencente ao Laboratório de Fertilizantes da Universidade Federal de Uberlândia (LAFER), em Uberlândia-MG, onde os modelos foram construídos. O método matemático utilizado foi o de mínimos quadrados parciais: PLS (Parcial Least Squares). A validação dos modelos foi cruzada e o número de variáveis latentes variaram entre 5 e 8. Os métodos de referência comparados foram: colorimétrico com extração por cloreto de cálcio (0,01 mol L-1) para análise do Si solúvel no solo, Walkley-Black colorimétrico para análise de M.O. e o método da Pipeta para análise da argila. Os modelos para determinação do N-Total foram comparados ao método Semimicro-Kjeldahl. Após a calibração e validação cruzada, foi feita a previsão dos modelos onde os resultados foram avaliados através do coeficiente de correlação (r), pelos erros de calibração (RMSEC) e previsão (RMSEP), e erro relativo percentual (ER), além disso, um teste t de student a 0,05 de significância foi aplicado para testar a igualdade entre as médias. Correlações de 0,71, 0,84 e 0,85 foram obtidas na calibração de modelos para análise do teor de Si no solo, M.O. e argila, respectivamente. A previsão a partir desses modelos apresentou correlações baixas (menores que 0,5) com teste t significativo para silício e argila. O RMSEC obtido na análise de Si foi de 2,03, RMSEP de 5,74 e ER de 59,2%. Para M.O. o RMSEC foi de 0,81, RMSEP=1,03 e ER=39,3%. A análise de argila teve RMSEC=11,2, RMSEP=16,55 e ER=34,7%. Na análise do N foliar em milho e soja, foram obtidas na calibração correlações de 0,85 e 0,88, respectivamente. Na previsão de amostras foram conseguidas boas correlações para milho (r=0,80) e soja (0,76), com teste t não significativo, indicando que para análises foliares os valores previstos pelos modelos NIR-PLS não diferiram dos obtidos pelos métodos de referência. Os erros de calibração e previsão para N em milho e soja foram menores que 5,0 g kg-1, sendo o ER para análise de N em milho (8,3%) maior do que o de soja (5,7%). Os resultados observados demonstram uma maior eficiência no uso do infravermelho próximo NIR-PLS para análises foliares do que para análises de solos. / Mestre em Agronomia

Fluorescence-based imaging techniques provide a simple, highly sensitive method of studying live cells and whole organisms in real time. Without question, fluorophores such as GFP, fluorescein, and rhodamines have contributed vastly to our understanding of both cell biology and biochemistry. However, most of the fluorescent molecules currently utilized suffer from one major drawback, the use of visible light. Due to cellular autofluorescence and the absorbance of incident light by cellular components, fluorescence imaging with visible wavelength fluorophores often results in high background noise and thus a low signal-to-noise ratio. Fortunately, this situation can be ameliorated by altering the wavelength of light used during imaging. Near-infrared (NIR) light (650-900 nm) is poorly absorbed by cells; therefore, fluorophores excited by this light provide a high signal-to-noise ratio and low background in cellular systems. While these properties make NIR fluorophores ideal for cellular imaging, most currently available NIR molecules cannot be used in live cells. The first half of this thesis addresses the synthetic difficulties associated with preparing NIR fluorophores that can be used within living systems. Small molecule NIR fluorophores are inherently hydrophobic which makes them unsuitable for use in the aqueous environment of the cell. Water-solubility is imparted to these dyes through highly polar sulfonates, which subsequently prevents the dyes from entering the cell. The novel work presented here details vii synthetic routes to aid in the development of sulfonated NIR fluorophores, which can be delivered into live cells through the inclusion of an esterase-labile sulfonate protecting group. Application of these synthetic techniques should allow for the development of novel NIR fluorophores with intracellular applications. The second half of this thesis addresses the need for novel NIR imaging reagents. Although several classes of NIR scaffolds do exist, most NIR probes are derivatives of a single class, heptamethine indocyanines. The work described here increases this palette by displaying the ability of NIR oxazines to function as an imaging reagent in live cells and in vivo and as a molecular sensor of biologically-relevant environmental conditions. Combined, the work contained herein has the capacity to not only advance the current NIR toolkit, but to expand it so that fluorescence imaging can move out of the dark and into the NIR light.

Master of Science / Department of Kinesiology / Thomas J. Barstow / Near infrared spectroscopy is currently routinely used to assess tissue (muscle) oxygenation at rest and during exercise. While most investigators assume that hemoglobin ([Hb]) is the major contributor to the responses seen during exercise, the relative contribution of myoglobin ([Mb]) to the NIRS signals remains controversial. PURPOSE: a) To calculate the range of light absorbing potential (LAP) of hemoglobin and myoglobin in mammalian skeletal muscle at rest based on analysis of published chemical and morphometric data in humans and other mammals (Part 1), and b) use the information in a) to interpret changes in total [Hb+Mb] from NIRS during exercise (Part 2). METHODS: Part 1: Information was retrieved from five published studies with regard to capillary density (#caps/mm2) and [Mb] in skeletal muscle of human, horse and rat. Preference was given to studies in which both measurements were provided for the same muscles. [Hb] in skeletal muscle was estimated as a function of capillary density, [Hb] in systemic blood, and the ratio of capillary-to-systemic hematocrit at rest and during exercise. Part 2: Changes in total [Hb] + [Mb] (as t[Hb+Mb]) from published NIRS data obtained from human subjects performing cycling or knee extension exercise were interpreted in the context of the results of Part 1. RESULTS: Part 1: Individual group mean values for skeletal muscle [Mb] in the literature ranged from 0.25-0.67 mM in human samples, with a similar range for muscles of the rat hindlimb; horse limb muscles tended to be higher (up to 1.0 mM). Capillary densities ranged from ~200 to 600 caps/mm2 in human and rat muscles, and up to 800 caps/mm2 in horse muscle. Assuming a resting capillary hematocrit of 22% and 4 fold greater LAP for each mole [Hb] vs [Mb], the resulting estimation of capillary [Hb] ranged from ~0.03 to 0.09 mM in human and rat muscles, and up to ~0.13 mM in horse muscles. The results suggest that [Mb] could contribute ~50-70% of the total LAP at rest in human skeletal muscle. Part 2: With exercise, total heme by NIRS can increase ≥ 30% in individual human subjects. Assuming this increase reflects only increased [Hb], this fits well with the observed increase in capillary hematocrit with exercise. CONCLUSIONS: 1) In skeletal muscle at rest, [Mb] is likely to be at least as significant a light absorbing heme as is [Hb] in most mammalian muscles, including the human leg. 2) Observed increases in t[Hb+Mb] with NIRS during exercise can be explained by an increase in capillary hematocrit, even in the presence of significant [Mb].

Master of Science / Department of Diagnostic Medicine/Pathobiology / Larry C. Hollis / Mark F. Spire / Two studies were undertaken to evaluate the use of Near Infrared Spectroscopy (NIRS) to determine arterial oxygen saturation (StO[subscript]2) in cattle with naturally-occurring Undifferentiated Bovine Respiratory Disease (UBRD) and experimentally-induced UBRD utilizing Mannheimia haemolytica. The first study was a natural infection model utilizing 679 beef heifers weighing approximately 227 kg (500 pounds) originating from a southeastern U.S. salebarn. Heifers were evaluated for UBRD upon feedlot arrival, at revaccination, at day 35 on feed, at re-implant time, and two weeks prior to shipment for slaughter. Animals deemed to have UBRD were treated for UBRD and data was collected for 5 days following treatment, while a comparable healthy cohort was also evaluated at the time of treatment. There was a trend for NIRS to be able to predict the incidence of subsequent UBRD when cattle were evaluated on arrival (p=0.0552). However, the ability to detect UBRD in clinically ill cattle was not significantly different (p>0.1690) when compared to healthy cohorts in this model. When carcass characteristics were evaluated at each time point, NIRS StO[subscript]2 values were able to differentiate between yield grades of animals with UBRD and healthy cohorts when evaluated at revaccination, day 35, re-implant, and pre-shipping (p<0.0199). NIRS tended to be able to differentiate yield grades at initial processing (p=0.0513). StO[subscript]2 was not a predictor of quality grade at any time point (p>0.1023), nor was there any correlation between lung lesions at slaughter and StO[subscript]2 (p>0.2292). The second study involved 12 head of 181 kg (400 pound) heifers which were subjected to an experimental challenge model of Mannheimia haemolytica. Animals were evaluated daily and StO[subscript]2 readings recorded 12 hours pre-inoculation, at inoculation, 6, 12 and 24 hours post inoculation and daily for the next 12 days. While NIRS could not definitively differentiate healthy cohort cattle from challenge cattle (p>0.0713), there were trends toward challenge cattle having lower StO[subscript]2 values than healthy controls. The authors conclude that while these studies did not provide conclusive evidence of the ability of NIRS to detect UBRD, further studies with a machine that is specifically calibrated and designed for use with cattle should be performed.

The manufacturing process of a photovoltaic Si wafer comprises of first a high temperature heating process to produce a Si ingot from polycrystalline Silicon, which is then cut into bricks and subsequently sawn into wafers using a wire saw. These processes create residual stresses both from the thermal gradient induced by solidification and from either the rolling-indenting or scratching-indenting processes caused by the type of wire saw used. The objective of this research is to study silicon wafer residual stress as a result of the typical industry manufacturing processes and by doing so, better understand the mechanical properties that lead to increased fracture. This thesis aims to quantify the amount of residual stress generated by the solidification/thermal gradient produced during the casting of Si ingots separately from the residual stress generated by the wire sawing process. Samples from industry are used to compare the effects of the manufacturing processes on residual stress in multi-crystalline silicon (mc-Si) wafers including the effects of fixed abrasive diamond wire sawing (DWS) vs. loose abrasive (LAWS) slurry wire sawing used in the wafering process. Near-infrared birefringence polariscopy and polarized micro-Raman spectroscopy are used to study wafer residual stresses within grains and at grain boundaries in mc-Si as a function of etch-depth. While near-infrared birefringence polariscopy allows for the measurement of full-field maximum shear stress, micro-Raman spectroscopy provides decomposition of the stress tensor into both principal and shear in-plane stress components. Consequently, regions of high tensile stress, which are detrimental to the mechanical integrity of the wafer, can be easily identified. In addition to the mechanical characterization, the residual stress produced by the thermal gradient/solidification process for multi-crystalline Si wafers was also correlated to electrical performance of mc-Si wafers using photoluminescence.

Thesis (PhD)--Stellenbosch University, 2013. / ENGLISH ABSTRACT: Concrete evidence of dryland salinity was observed in the Berg River catchment in the Western Cape Province of South Africa. Soil salinization is a global land degradation hazard that negatively affects the productivity of soils. Timely and accurate detection of soil salinity is crucial for soil salinity monitoring and mitigation. It would be restrictive in terms of costs to use traditional wet chemistry methods to detect and monitor soil salinity in the entire Berg River catchment. The goal of this study was to investigate less tedious, accurate and cost effective techniques for better monitoring. Firstly, hyperspectral remote sensing (HRS) techniques that can best predict electrical conductivity (EC) in the soil using individual bands, a unique normalized difference soil salinity index (NDSI), partial least squares regression (PLSR) and bagging PLSR were investigated. Spectral reflectance of dry soil samples was measured using an analytical spectral device FieldSpec spectrometer in a darkroom. Soil salinity predictive models were computed using a training dataset (n = 63). An independent validation dataset (n = 32) was used to validate the models. Also, field-based regression predictive models for EC, pH, soluble Ca, Mg, Na, Cl and SO4 were developed using soil samples (n = 23) collected in the Sandspruit catchment. These soil samples were not ground or sieved and the spectra were measured using the sun as a source of energy to emulate field conditions. Secondly, the value of NIR spectroscopy for the prediction of EC, pH, soluble Ca, Mg, Na, Cl, and SO4 was evaluated using 49 soil samples. Spectral reflectance of dry soil samples was measured using the Bruker multipurpose analyser spectrometer. “Leave one out” cross validation (LOOCV) was used to calibrate PLSR predictive models for EC, pH, soluble Ca, Mg, Na, Cl, and SO4. The models were validated using R2, root mean square error of cross validation (RMSECV), ratio of prediction to deviation (RPD) and the ratio of prediction to interquartile distance (RPIQ). Thirdly, owing to the suitability of land components to map soil properties, the value of digital elevation models (DEMs) to delineate accurate land components was investigated. Land components extracted from the second version of the 30-m advanced spaceborne thermal emission and reflection radiometer global DEM (ASTER GDEM2), the 90-m shuttle radar topography mission DEM (SRTM DEM), two versions of the 5-m Stellenbosch University DEMs (SUDEM L1 and L2) and a 5-m DEM (GEOEYE DEM) derived from GeoEye stereo-images were compared. Land components were delineated using the slope gradient and aspect derivatives of each DEM. The land components were visually inspected and quantitatively analysed using the slope gradient standard deviation measure and the mean slope gradient local variance ratio for accuracy. Fourthly, the spatial accuracy of hydrological parameters (streamlines and catchment boundaries) delineated from the 5-m resolution SUDEM (L1 and L2), the 30-m ASTER GDEM2 and the 90-m SRTM was evaluated. Reference catchment boundary and streamlines were generated from the 1.5-m GEOEYE DEM. Catchment boundaries and streamlines were extracted from the DEMs using the Arc Hydro module for ArcGIS. Visual inspection, correctness index, a new Euclidean distance index and figure of merit index were used to validate the results. Finally, the value of terrain attributes to model soil salinity based on the EC of the soil and groundwater was investigated. Soil salinity regression predictive models were developed using CurveExpert software. In addition, stepwise multiple linear regression soil salinity predictive models based on annual evapotranspiration, the aridity index and terrain attributes were developed using Statgraphics software. The models were validated using R2, standard error and correlation coefficients. The models were also independently validated using groundwater hydro-census data covering the Sandspruit catchment. This study found that good predictions of soil salinity based on bagging PLSR using first derivative reflectance (R2 = 0.85), PLSR using untransformed reflectance (R2 = 0.70), a unique NDSI (R2 = 0.65) and the untransformed individual band at 2257 nm (R2 = 0.60) predictive models were achieved. Furthermore, it was established that reliable predictions of EC, pH, soluble Ca, Mg, Na, Cl and SO4 in the field are possible using first derivative reflectance. The R2 for EC, pH, soluble Ca, Mg, Na, Cl and SO4 predictive models are 0.85, 0.50, 0.65, 0.84, 0.79, 0.81 and 0.58 respectively. Regarding NIR spectroscopy, validation R2 for all the PLSR predictive models ranged from 0.62 to 0.87. RPD values were greater than 1.5 for all the models and RMSECV ranged from 0.22 to 0.51. This study affirmed that NIR spectroscopy has the potential to be used as a quick, reliable and less expensive method for evaluating salt-affected soils. As regards hydrological parameters, the study concluded that valuable hydrological parameters can be derived from DEMs. A new Euclidean distance ratio was proved to be a reliable tool to compare raster data sets. Regarding land components, it was concluded that higher resolution DEMs are required for delineating meaningful land components. It seems probable that land components may improve salinity modelling using hydrological modelling and that they can be integrated with other data sets to map soil salinity more accurately at catchment level. In the case of terrain attributes, the study established that promising soil salinity predictions could be made based on slope, elevation, evapotranspiration and terrain wetness index (TWI). Stepwise multiple linear regressions soil salinity predictive model based on elevation, evapotranspiration and TWI yielded slightly more accurate prediction of soil salinity. Overall, the study showed that it is possible to enhance soil salinity monitoring using HRS, NIR spectroscopy, land components, hydrological parameters and terrain attributes. / AFRIKAANSE OPSOMMING: Konkrete bewyse van droëland sout is waargeneem in die Bergrivier opvanggebied in die Wes- Kaap van Suid-Afrika. Verbrakking van grond is 'n wêreldwye probleem wat ‘n negatiewe invloed op die produktiwiteit van grond kan hê. Tydige en akkurate herkenning van verandering in grond soutgehalte is ‘n noodsaaklike aksie vir voorkoming. Dit sou beperkend wees in terme van koste om konvensionele nat chemiese metodes te gebruik vir die opsporing en monitering daarvan in die hele Bergrivier opvanggebied. Die doel van hierdie studie was om ondersoek in te stel na minder tydsame, akkurate en koste-effektiewe tegnieke vir beter monitering. Eerstens, is hiperspektrale afstandswaarnemings (HRS) tegnieke wat die beste in staat is elektriese geleidingsvermoë (EG) in die grond te kan voorspel deur gebruik te maak van individuele bande, 'n unieke genormaliseerde grond soutindeks verskil (NDSI), parsiële kleinste kwadratiese regressie (PLSR) en afwyking in PLSR, is ondersoek. Spektrale reflektansie van droë grondmonsters is gemeet deur gebruik te maak van 'n spektrale analitiese toestel: FieldSpec spektrometer in 'n donkerkamer. Voorspellings modelle vir grond soutgehalte is bereken met behulp van 'n toets datastel (n = 63). 'n onafhanklike validasie datastel (n = 32) is gebruik om die modelle te evalueer. Daarbenewens is veld-gebaseerde regressie voorspellings modelle vir EG, pH oplosbare Ca, Mg, Na, Cl and SO4 ontwikkel deur gebruik te maak van grondmonsters (n = 23) versamel in the Sandpruit opvangsgebied. Hierdie grondmonsters is nie gemaal of gesif nie en die spectra is gemeet deur gebruik te maak van die son as ‘n bron van energie om veld toestande na te boots. Tweedens, is die waarde van NIR spektroskopie vir die voorspelling van die EG, pH, oplosbare Ca, Mg, Na, Cl, en SO4 met behulp van 49 grondmonsters geëvalueer. Spektrale reflektansie van droë grondmonsters is gemeet deur gebruik te maak van die Bruker NIR veeldoelige analiseerder . Kruisvalidering (LOOCV) is gebruik om PLSR voorspellings modelle vir EG, pH, oplosbare Ca, Mg, Na, Cl, en SO4 te kalibreer. Hierdie modelle is gevalideer: R2, wortel-gemiddelde-kwadraat fout kruisvalidering (RMSECV), verhouding van voorspellings afwyking (RPD) en die verhouding van die voorspelling se inter-kwartiel afstand (RPIQ). Derdens is land komponente gekarteer vanweë die nut daat van tov grondeienskappe, en die waarde van DEMs is ondersoek om akkurate land komponente af te baken. Land komponente uit die tweede weergawe van die 30 m gevorderde ruimte termiese emissie en refleksie radio globale DEM (ASTER GDEM2), die 90-m ruimtetuig radar topografie sending DEM (SRTM DEM), twee weergawes van die 5 m Universiteit van Stellenbosch DEMs (SUDEM L1 en L2) en 'n 5 m DEM (GEOEYE DEM) afgelei van GeoEye stereo-beelde, is vergelyk. Land komponente is afgebaken met behulp van helling, gradiënt en aspek afgeleides van elke DEM. Die land komponente is visueel geïnspekteer en kwantitatief ontleed met behulp van die helling gradiënt standaardafwyking te meet en die gemiddelde helling-gradiënt-plaaslike variansie verhouding vir akkuraatheid. Vierdens, is die ruimtelike akkuraatheid van hidrologiese parameters (stroomlyn en opvanggebied grense) geëvalueer soos afgelei vanaf die 5 m resolusie SUDEM (L1 en L2), die 30 m ASTER GDEM2 en die 90 m SRTM . Die verwysings opvanggebied grens en stroomlyn is gegenereer vanaf die 1,5-m GEOEYE DEM. Opvanggebied grense en stroomlyn uit die DEMs is bepaal deur gebruik te maak van die Arc Hydro module in ArcGIS. Visuele inspeksie, korrektheid indeks, 'n nuwe Euklidiese afstand indeks en die indikasie-van-meriete indeks is gebruik om die resultate te valideer. Laastens is die waarde van die terrein eienskappe om grond southalte te modeleer ondersoek, gebaseer op die EG van die grond en grondwater. Grond soutgehalte regressie voorspellings modelle is ontwikkel met behulp van CurveExpert sagteware. Verder, stapsgewyse meervoudige lineêre regressie grond soutgehalte voorspellings modelle gebaseer op jaarlikse evapotranspirasie, die dorheids indeks en terrein eienskappe is ontwikkel met behulp van Statgraphics sagteware. Die modelle is gevalideer deur gebruik te maak van R2, standaardfout en korrelasiekoëffisiënte. Die modelle is ook onafhanklik bekragtig deur die gebruik van grondwater hidro-sensus-data wat die Sandspruit opvanggebied insluit. Hierdie studie het bevind dat 'n goeie voorspelling van grond soutgehalte gebaseer op uitsak PLSR met behulp van eerste orde afgeleide reflektansie (R2 = 0,85), PLSR deur gebruik te maak van ongetransformeerde reflektansie (R2 = 0,70), 'n unieke NDSI (R2 = 0,65) en die ongetransformeerde individuele band op 2257 nm (R2 = 0,60) voorspellings modelle verkry is. Verder is vasgestel dat betroubare voorspellings van die EG, pH, oplosbare Ca, Mg, Na, Cl en SO4 in die veld moontlik is met behulp van eerste afgeleide reflektansie. Die R2 van EG, pH, oplosbare Ca, Mg, Na, Cl en SO4 is 0.85, 0.50, 0.65, 0.84, 0.79, 0.81 en 0.58 onderskeidelik. Ten opsigte van NIR spektroskopie het die validasie van R2 vir al die PLSR voorspellings modelle gewissel tussen 0,62-0,87. Die RPD waardes was groter as 1,5 vir al die modelle en RMSECV het gewissel tussen 0,22-0,51. Hierdie studie het bevestig dat NIR spektroskopie die potensiaal het om gebruik te word as 'n vinnige, betroubare en goedkoper metode vir die analise van soutgeaffekteerde gronde. T.o.v. hidrologiese parameters, het die studie tot die gevolgtrekking gekom dat waardevolle hidrologiese parameters afgelei kan word uit DEMs. 'n nuwe Euklidiese afstand verhouding is bevestig as 'n betroubare hulpmiddel om raster datastelle te vergelyk. Ten opsigte van grond komponente, is daar tot die gevolgtrekking gekom dat hoër resolusie DEMs nodig is vir die bepaling van sinvolle land komponente. Dit lyk waarskynlik dat die land komponent soutgehalte modellering hidrologiese modellering verbeter en dat hulle geïntegreer kan word met ander datastelle vir meer akkurate kaarte op opvangsgebied skaal. In die geval van die terrein eienskappe het, die studie vasgestel dat belowende grond soutgehalte voorspellings gemaak kan word gebaseer op helling, elevasie, evapotranspirasie en terrein natheid indeks (TWI). 'n stapsgewyse meervoudige lineêre regressie grond soutgehalte voorspellings model wat gebaseer is op elevasie, evapotranspirasie en TWI het effens meer akkurate voorspellings van die grond soutgehalte gelewer. In geheel gesien, het die studie getoon dat dit moontlik is om grond soutgehalte monitering te verbeter met behulp van HRS, NIR spektroskopie, land komponente, hidrologiese parameters en terrein eienskappe. / The Agricultural Research Council (ARC), Water Research Commission and the National Research Foundation for funding.

Spectroscopy and other optical methods can often be employed with limited or no sample preparation, making them well suited for in situ and in vivo analysis. This dissertation focuses on the use of a near-infrared spectroscopy (NIRS) and polarized light scatter for two such applications: the assessment of cardiovascular disease, and the validation of cleaning processes for pharmaceutical equipment.There is a need for more effective in vivo techniques for assessing intravascular disorders, such as aortic aneurysms and vulnerable atherosclerotic plaques. These, and other cardiovascular disorders, are often associated with structural remodeling of vascular walls. NIRS has previously been demonstrated as an effective technique for the analysis of intact biological samples. In this research, traditional NIRS is used in the analysis of aortic tissue samples from a murine knockout model that develops abdominal aortic aneurysms (AAAs) following infusion of angiotensin II. Effective application of NIRS in vivo, however, requires a departure from traditional instrumental principles. Toward this end, the groundwork for a fiber optic-based catheter system employing a novel optical encoding technique, termed molecular factor computing (MFC), was developed for differentiating cholesterol, collagen and elastin through intervening red blood cell solutions. In MFC, the transmission spectra of chemical compounds are used to collect measurements directly correlated to the desired sample information.Pharmaceutical cleaning validation is another field that can greatly benefit from novel analytical methods. Conventionally cleaning validation is accomplished through surface residue sampling followed by analysis using a traditional analytical method. Drawbacks to this approach include cost, analysis time, and uncertainties associated with the sampling and extraction methods. This research explores the development of in situ cleaning validation methods to eliminate these issues. The use of light scatter and polarization was investigated for the detection and quantification of surface residues. Although effective, the ability to discriminate between residues was not established with these techniques. With that aim in mind, the differentiation of surface residues using NIRS and MFC was also investigated.

No description available.

Children and adolescents are thought to use oxidative metabolism to a greater extent than adults during high intensity exercise. The studies reported in this thesis examine the nature and implications of age-related differences in muscle metabolism during high intensity exercise and recovery. Chapter 4 concluded that during heavy intensity exercise, phosphocreatine (PCr) kinetics did not differ with age or sex, while Chapter 5 revealed that during very heavy intensity exercise, the fundamental τ was slower and slow component amplitude greater in men compared with adolescent boys, indicating that exercise intensity might play a role in determining age-related differences in muscle metabolism. In Chapter 6, two bouts of very heavy intensity exercise were completed, and prior exercise reduced the PCr slow component amplitude in men but not boys. Deoxyhaemoglobin (HHb) kinetics was faster in adolescents compared with adults during both heavy and very heavy intensity exercise, indicating that matching of oxygen delivery to oxygen utilisation is less precise at the onset of exercise in adolescents compared with adults. PCr recovery from high intensity exercise was faster in boys than men, but not different in girls and women, as described in Chapter 7. The speed of PCr recovery was correlated with maturity in adolescents, but was not correlated with end-exercise [PCr] or pH. Two different tests to measure mitochondrial capacity in adolescents were evaluated in Chapter 8, and a fitted curve and gated test were both used to determine PCr recovery kinetics. Finally, in Chapter 9, age-related differences in muscle metabolism and oxygenation during fatiguing exercise were examined; a strong trend for greater fatigue in adults compared with adolescents was accompanied by greater metabolic perturbation in adults. Overall, these data show that muscle metabolism and oxygenation differs between adolescents and adults during and following very high intensity exercise.

Personalized medicine can be an approach to address the unsatisfactory treatment outcomes in inflammatory conditions such as cancer, arthritis, and cardiovascular diseases. A common feature of chronic diseases is the infiltration of pro-inflammatory macrophages at the disease loci. Infiltrating macrophages have been previously utilized for disease diagnosis. These features suggest that macrophages can be broadly applicable targets for simultaneous therapy and diagnosis. Cyclooxygenase-2 (COX-2), an enzyme involved in the biosynthesis of a lipid inflammatory mediator, prostaglandin E2 (PGE2), is over expressed in macrophages infiltrating the pathological site. Inhibition of PGE2 leads to reduced inflammation, pain and macrophage infiltration. To utilize macrophages for the purpose of simultaneous therapy and diagnosis, we proposed to integrate therapeutic and imaging capabilities on a single nanomedicine platform, referred as theranostics. A stable 19F MRI visible nanoemulsion platform was developed, incorporating celecoxib for COX-2 inhibition and near-infrared fluorescent dye(s) for fluorescence imaging. We hypothesized that inhibition of COX-2 in macrophages using a theranostic nanoemulsion will reduce the inflammation (and pain), and that this response can be visualized by monitoring changes in macrophage infiltration. In vitro characterization demonstrated that the theranostic displays excellent stability with no toxicity, and significant uptake in macrophages. Furthermore, it delivers celecoxib to macrophages and reduces PGE2 production from these cells. In vivo studies in a murine paw inflammation model showed nanoemulsion presence at the inflamed site, specifically in COX-2 expressing macrophages compared to neutrophils. Supporting our hypothesis, celecoxib delivered through a nanoemulsion demonstrated time-dependent reduction in fluorescence from the inflamed paw, indicative of reduced macrophage infiltration. In a neuropathic pain model, celecoxib delivered to macrophages led to reduced pain concomitant with reduced macrophage infiltration at the inflamed site compared to free drug control (cross reference: Kiran Vasudeva, Dissertation, 2015). In conclusion, inhibition of COX-2 in macrophages using theranostic nanoemulsions proves to be an effective and generalized strategy facilitating simultaneous therapy and diagnosis, which can be applied to many chronic diseases. The diagnostic information during therapy can be used to tailor the treatment and reduce patient variability leading to personalized medicine. / Mylan School of Pharmacy and the Graduate School of Pharmaceutical Sciences; / Pharmaceutics / PhD; / Dissertation;