Dental erosion has been defined as a chemical process that involves the dissolution of enamel and dentine by acid(s) not derived from bacteria when the surrounding aqueous phase is under-saturated with tooth mineral. Clinically however, dental erosion hardly ever occurs exclusively from the other modes of tooth wear such as abrasion and attrition. Hence the term erosive wear has been proposed and used to describe erosion-facilitated wear.With the prevalence of erosive wear being reported to be on the rise among children and adolescents in many countries, a plethora of oral health products such as dentifrices and mouth rinses had been put forward with claims of increasing the resistance of the enamel and / or dentine from being demineralised. However, the efficacy of these oral health products is still widely questionable as the studies carried out were mainly in vitro and / or in situ studies and the contradictory results were reported by different groups of researchers.The above mentioned discrepancies are often due to non-standardised in vitro and in situ study designs of erosion studies. Parameters such as type of acid used, concentration of acid used, duration of acid exposure, inclusion or exclusion of abrasion in the study model, ex vivo or in vivo acid challenge, ex vivo or in vivo treatment with oral health product and the nature of pellicle on the specimen are often varied.The availability of an detection tool which could be used to measure demineralisation on natural tooth surface in vivo would exclude many of the inevitable variability in in situ and in vitro study design, such as the simulation of the intra oral conditions in which the erosion challenge and intervention take place and the nature of the pellicle formed on the specimens. Hence with an in vivo detection tool, it is hopeful that the efficacy of any interventions would be evaluated more accurately and its results expounded to a wider context. It would be useful if the tool was sensitive to the very early stages of the erosion process as this would entail shorter and more economical study designs. Arising from the problems discussed above, potential non-invasive assessment methods that could be used clinically to measure demineralisation were explored and it was found that two optical methods, Optical Coherence Tomography (OCT) and Quantitative Light-induced Fluorescence (QLF) were potential methods for the tasks.The studies described in this thesis were divided into three main big sections; the first being the in vitro validation work of the two optical methods (Chapter 5 and 6), the second, validation of these methods in situ (Chapter 7) and finally the assessment of the efficacy of a high fluoride dentifrice on early enamel erosion using these two methods (Chapter 8).In the in vitro validation (Chapter 5), it was demonstrated that both QLF and OCT were able to detect erosion-interval related changes in natural surface samples eroded with orange juice for 60 minutes. However, results of Multiple Linear Regression and Paired t test suggest that QLF was more sensitive than OCT in the detection of demineralisation changes in this particular experimental setting. QLF demonstrated a R2 value of 0.590 while the best of the OCT outcome measure demonstrated a R2 value of 0.319.Further in vitro study (Chapter 6) was performed to explore the use of a moistened-exposed surface as a reference method for both OCT and QLF as it was felt that it would be beneficial if a coated reference area which posts as an additional step for error could be done away with. Results of this study showed that the moistened-exposed surface could be used a reference method for QLF only but not for OCT. Furnished with the findings of the above mentioned in vitro validation studies, an in situ validation of both the optical methods was performed (Chapter 7). It was found that OCT and QLF were able to longitudinally measure in situ demineralisation on polished and natural surfaced enamel which were subjected to 150 minutes of in vivo exposure to orange juice. Similar to the results of the in vitro study, QLF was found to be more sensitive than OCT in the detection of demineralisation changes on natural surfaced enamel. The last in situ study (Chapter 8) was to evaluate whether there was a protective effect of treating human enamel with a high-concentrated fluoride dentifrice during an active erosion phase and whether OCT and QLF were able to detect the protective effect. It was found that treating natural surface enamel with a 5000ppm NaF dentifrice increased its resistance against concurrent in vivo erosive challenge with an orange juice challenge. QLF was able to detect the protective effect of the 5000ppm NaF dentifrice on natural surface enamel against early in vivo erosion with an orange juice challenge regime while OCT did not.

Abduction prevention skills are crucial for any child to have. Unfortunately there has been a lack of research on teaching children with autism and aspergers these skills. Video modeling has been shown to be an effective method to teach children with autism various skills. Video modeling has also been shown to be cost efficient and easily implemented across various people and settings. The purpose of the present study was to assess the effectiveness of the video modeling technique for teaching children with autism and aspergers abduction prevention skills. The second purpose of the present study was to investigate the effectiveness of BST and IST for teaching children with autism and aspergers abduction prevention skills if video modeling was not effective. The results showed that the utilization of video modeling was effective in teaching all four participants abduction prevention skills.

There is limited research using small-scale simulation in applied behavior analysis. We used small-scale simulation to train firearm safety skills to 3 to 5-years-old children and assessed whether the skills generalized to the natural environment through in situ assessment. Three participants completed the training and all participants learned the safety skills from simulation training. Two of the participants acquired the safety skills after the first simulation training and the third participant required one booster training before demonstrating the safety skills in the natural environment.

The objectives of this research were to develop and evaluate a field method for in situ measurement of soil properties using visible near-infrared reflectance spectroscopy (Vis-NIRS). A probe with an independent light source for acquiring soil reflectance spectra from soil cores was developed around an existing portable field spectrometer (ASD FieldSpecPro, Boulder, CO, USA; 350-2500 nm). Initial experiments tested the ability of the acquired spectra to predict plant root density, an important property in soil carbon dynamics. Reflectance spectra were acquired from soil containing ryegrass roots (Lolium multiflorum) grown in Allophanic and Fluvial Recent soils in a glasshouse pot trial. Differences in root density were created by differential nitrogen and phosphorus fertilization. Partial least squares regression (PLSR) was used to calibrate spectral data (pre-processed by smoothing and transforming spectra to the first derivative) against laboratory-measured root density data (wet-sieve technique). The calibration model successfully predicted root densities (r2 = 0.85, RPD = 2.63, RMSECV = 0.47 mg cm-3) observed in the pots to a moderate level of accuracy. This soil reflectance probe was then tested using a soil coring system to acquire reflectance spectra from two soils under pasture (0-60 mm soil depths) that had contrasting root densities. The PLSR calibration models for predicting root density were more accurate when soil samples from the two soils were separated rather than grouped. A more accurate prediction was found in Allophanic soils (r2 = 0.83, RPD = 2.44, RMSECV = 1.96 mg g-1) than in Fluvial Recent soils (r2 = 0.75, RPD = 1.98, RMSECV = 5.11 mg g-1). The Vis-NIRS technique was then modified slightly to work on a soil corer that could be used to measure root contents from deeper soil profiles (15- 600 mm depth) in arable land (90-day-old maize crop grown in Fluvial Recent soils). PLSR calibration models were constructed to predict the full range of maize root densities (r2 = 0.83, RPD = 2.42, RMSECV = 1.21 mg cm-3) and also soil carbon (C) and nitrogen (N) concentrations that had been determined in the laboratory (LECO FP- 2000 CNS Analyser; Leco Corp., St Joseph, MI, USA). Further studies concentrated on improving the Vis-NIRS technique for prediction of total C and N concentrations in differing soil types within different soil orders in the field. The soil coring method used in the maize studies was evaluated in permanent and recent pastoral soils (Pumice, Allophanic and Tephric Recent in the Taupo-Rotorua Volcanic Zone, North Island) with a wide range of soil organic matter contents resulting from different times (1-5 years) since conversion from forest soils. Without any sample preparation, other than the soil surface left after coring, it was possible to predict soil C and N concentrations with moderate success (C prediction r2 = 0.75, RMSEP = 1.23%, RPD = 1.97; N prediction r2 = 0.80, RMSEP = 0.10%, RPD = 2.15) using a technique of acquiring soil reflectance spectra from the horizontal cross-section of a soil core (H method). The soil probe was then modified to acquire spectra from the curved vertical wall of a soil core (V method), allowing the spectrometer’s field of view to increase to record the reflectance features of the whole soil sample taken for laboratory analysis. Improved predictions of soil C and N concentrations were achieved with the V method of spectral acquisition (C prediction r2 = 0.97, RMSECV = 0.21%, RPD = 5.80; N prediction r2 = 0.96, RMSECV = 0.02%, RPD = 5.17) compared to the H method (C prediction r2 = 0.95, RMSECV = 0.27%, RPD = 4.45; N prediction r2 = 0.94, RMSECV = 0.03%, RPD = 4.25). The V method was tested for temporal robustness by assessing its ability to predict soil C and N concentrations of Fluvial Recent soils under permanent pasture in different seasons. When principal component analysis (PCA) was used to ensure that the spectral dimensions (which were responsive to water content) of the data set used for developing the PLSR calibration model embraced those of the “unknown” soil samples, it was possible to predict soil C and N concentrations in “unknown” samples of widely different water contents (in May and November), with a high level of accuracy (C prediction r2 = 0.97, RMSEP = 0.36%, RPD = 3.43; N prediction r2 = 0.95, RMSEP = 0.03%, RPD = 3.44). This study indicates that Vis-NIRS has considerable potential for rapid in situ assessment of soil C, N and root density. The results demonstrate that field root densities in pastoral and arable soil can be predicted independently from total soil C, which will allow researchers to predict C sequestration from root production. The recommended “V” technique can be used to assess spatial and temporal variability of soil carbon and nitrogen within soil profiles and across the landscape. It can also be used to assess the rate of C sequestration and organic matter synthesis via root density prediction. It reduces the time, labour and cost of conventional soil analysis and root density measurement.

The objectives of this research were to develop and evaluate a field method for in situ measurement of soil properties using visible near-infrared reflectance spectroscopy (Vis-NIRS). A probe with an independent light source for acquiring soil reflectance spectra from soil cores was developed around an existing portable field spectrometer (ASD FieldSpecPro, Boulder, CO, USA; 350-2500 nm). Initial experiments tested the ability of the acquired spectra to predict plant root density, an important property in soil carbon dynamics. Reflectance spectra were acquired from soil containing ryegrass roots (Lolium multiflorum) grown in Allophanic and Fluvial Recent soils in a glasshouse pot trial. Differences in root density were created by differential nitrogen and phosphorus fertilization. Partial least squares regression (PLSR) was used to calibrate spectral data (pre-processed by smoothing and transforming spectra to the first derivative) against laboratory-measured root density data (wet-sieve technique). The calibration model successfully predicted root densities (r2 = 0.85, RPD = 2.63, RMSECV = 0.47 mg cm-3) observed in the pots to a moderate level of accuracy. This soil reflectance probe was then tested using a soil coring system to acquire reflectance spectra from two soils under pasture (0-60 mm soil depths) that had contrasting root densities. The PLSR calibration models for predicting root density were more accurate when soil samples from the two soils were separated rather than grouped. A more accurate prediction was found in Allophanic soils (r2 = 0.83, RPD = 2.44, RMSECV = 1.96 mg g-1) than in Fluvial Recent soils (r2 = 0.75, RPD = 1.98, RMSECV = 5.11 mg g-1). The Vis-NIRS technique was then modified slightly to work on a soil corer that could be used to measure root contents from deeper soil profiles (15- 600 mm depth) in arable land (90-day-old maize crop grown in Fluvial Recent soils). PLSR calibration models were constructed to predict the full range of maize root densities (r2 = 0.83, RPD = 2.42, RMSECV = 1.21 mg cm-3) and also soil carbon (C) and nitrogen (N) concentrations that had been determined in the laboratory (LECO FP- 2000 CNS Analyser; Leco Corp., St Joseph, MI, USA). Further studies concentrated on improving the Vis-NIRS technique for prediction of total C and N concentrations in differing soil types within different soil orders in the field. The soil coring method used in the maize studies was evaluated in permanent and recent pastoral soils (Pumice, Allophanic and Tephric Recent in the Taupo-Rotorua Volcanic Zone, North Island) with a wide range of soil organic matter contents resulting from different times (1-5 years) since conversion from forest soils. Without any sample preparation, other than the soil surface left after coring, it was possible to predict soil C and N concentrations with moderate success (C prediction r2 = 0.75, RMSEP = 1.23%, RPD = 1.97; N prediction r2 = 0.80, RMSEP = 0.10%, RPD = 2.15) using a technique of acquiring soil reflectance spectra from the horizontal cross-section of a soil core (H method). The soil probe was then modified to acquire spectra from the curved vertical wall of a soil core (V method), allowing the spectrometer’s field of view to increase to record the reflectance features of the whole soil sample taken for laboratory analysis. Improved predictions of soil C and N concentrations were achieved with the V method of spectral acquisition (C prediction r2 = 0.97, RMSECV = 0.21%, RPD = 5.80; N prediction r2 = 0.96, RMSECV = 0.02%, RPD = 5.17) compared to the H method (C prediction r2 = 0.95, RMSECV = 0.27%, RPD = 4.45; N prediction r2 = 0.94, RMSECV = 0.03%, RPD = 4.25). The V method was tested for temporal robustness by assessing its ability to predict soil C and N concentrations of Fluvial Recent soils under permanent pasture in different seasons. When principal component analysis (PCA) was used to ensure that the spectral dimensions (which were responsive to water content) of the data set used for developing the PLSR calibration model embraced those of the “unknown” soil samples, it was possible to predict soil C and N concentrations in “unknown” samples of widely different water contents (in May and November), with a high level of accuracy (C prediction r2 = 0.97, RMSEP = 0.36%, RPD = 3.43; N prediction r2 = 0.95, RMSEP = 0.03%, RPD = 3.44). This study indicates that Vis-NIRS has considerable potential for rapid in situ assessment of soil C, N and root density. The results demonstrate that field root densities in pastoral and arable soil can be predicted independently from total soil C, which will allow researchers to predict C sequestration from root production. The recommended “V” technique can be used to assess spatial and temporal variability of soil carbon and nitrogen within soil profiles and across the landscape. It can also be used to assess the rate of C sequestration and organic matter synthesis via root density prediction. It reduces the time, labour and cost of conventional soil analysis and root density measurement.

The objectives of this research were to develop and evaluate a field method for in situ measurement of soil properties using visible near-infrared reflectance spectroscopy (Vis-NIRS). A probe with an independent light source for acquiring soil reflectance spectra from soil cores was developed around an existing portable field spectrometer (ASD FieldSpecPro, Boulder, CO, USA; 350-2500 nm). Initial experiments tested the ability of the acquired spectra to predict plant root density, an important property in soil carbon dynamics. Reflectance spectra were acquired from soil containing ryegrass roots (Lolium multiflorum) grown in Allophanic and Fluvial Recent soils in a glasshouse pot trial. Differences in root density were created by differential nitrogen and phosphorus fertilization. Partial least squares regression (PLSR) was used to calibrate spectral data (pre-processed by smoothing and transforming spectra to the first derivative) against laboratory-measured root density data (wet-sieve technique). The calibration model successfully predicted root densities (r2 = 0.85, RPD = 2.63, RMSECV = 0.47 mg cm-3) observed in the pots to a moderate level of accuracy. This soil reflectance probe was then tested using a soil coring system to acquire reflectance spectra from two soils under pasture (0-60 mm soil depths) that had contrasting root densities. The PLSR calibration models for predicting root density were more accurate when soil samples from the two soils were separated rather than grouped. A more accurate prediction was found in Allophanic soils (r2 = 0.83, RPD = 2.44, RMSECV = 1.96 mg g-1) than in Fluvial Recent soils (r2 = 0.75, RPD = 1.98, RMSECV = 5.11 mg g-1). The Vis-NIRS technique was then modified slightly to work on a soil corer that could be used to measure root contents from deeper soil profiles (15- 600 mm depth) in arable land (90-day-old maize crop grown in Fluvial Recent soils). PLSR calibration models were constructed to predict the full range of maize root densities (r2 = 0.83, RPD = 2.42, RMSECV = 1.21 mg cm-3) and also soil carbon (C) and nitrogen (N) concentrations that had been determined in the laboratory (LECO FP- 2000 CNS Analyser; Leco Corp., St Joseph, MI, USA). Further studies concentrated on improving the Vis-NIRS technique for prediction of total C and N concentrations in differing soil types within different soil orders in the field. The soil coring method used in the maize studies was evaluated in permanent and recent pastoral soils (Pumice, Allophanic and Tephric Recent in the Taupo-Rotorua Volcanic Zone, North Island) with a wide range of soil organic matter contents resulting from different times (1-5 years) since conversion from forest soils. Without any sample preparation, other than the soil surface left after coring, it was possible to predict soil C and N concentrations with moderate success (C prediction r2 = 0.75, RMSEP = 1.23%, RPD = 1.97; N prediction r2 = 0.80, RMSEP = 0.10%, RPD = 2.15) using a technique of acquiring soil reflectance spectra from the horizontal cross-section of a soil core (H method). The soil probe was then modified to acquire spectra from the curved vertical wall of a soil core (V method), allowing the spectrometer’s field of view to increase to record the reflectance features of the whole soil sample taken for laboratory analysis. Improved predictions of soil C and N concentrations were achieved with the V method of spectral acquisition (C prediction r2 = 0.97, RMSECV = 0.21%, RPD = 5.80; N prediction r2 = 0.96, RMSECV = 0.02%, RPD = 5.17) compared to the H method (C prediction r2 = 0.95, RMSECV = 0.27%, RPD = 4.45; N prediction r2 = 0.94, RMSECV = 0.03%, RPD = 4.25). The V method was tested for temporal robustness by assessing its ability to predict soil C and N concentrations of Fluvial Recent soils under permanent pasture in different seasons. When principal component analysis (PCA) was used to ensure that the spectral dimensions (which were responsive to water content) of the data set used for developing the PLSR calibration model embraced those of the “unknown” soil samples, it was possible to predict soil C and N concentrations in “unknown” samples of widely different water contents (in May and November), with a high level of accuracy (C prediction r2 = 0.97, RMSEP = 0.36%, RPD = 3.43; N prediction r2 = 0.95, RMSEP = 0.03%, RPD = 3.44). This study indicates that Vis-NIRS has considerable potential for rapid in situ assessment of soil C, N and root density. The results demonstrate that field root densities in pastoral and arable soil can be predicted independently from total soil C, which will allow researchers to predict C sequestration from root production. The recommended “V” technique can be used to assess spatial and temporal variability of soil carbon and nitrogen within soil profiles and across the landscape. It can also be used to assess the rate of C sequestration and organic matter synthesis via root density prediction. It reduces the time, labour and cost of conventional soil analysis and root density measurement.