An elementary treatise on dynamics, containing applications to thermodynamics, with numerous examples.

Mode of access: Internet.

An elementary treatise on dynamics, containing applications to thermodynamics, with numerous examples.

Mode of access: Internet.

A history of the warfare of science with theology in christendom /

Includes bibliographical references and index.

Effect of annual applications of diuron on seed yields of perennial grasses in Oregon

Prepared in cooperation with Oregon Agricultural Experiment Station.

An elementary treatise on dynamics, containing applications to thermodynamics, with numerous examples.

Mode of access: Internet.

Facilitating Realistic and Efficient Applications of Ab Initio Electronic Dynamics for Polyatomic Systems

Thesis (Ph.D.)--University of Washington, 2016-06

Applications of Quantum Field Theory, From the Formal to the Phenomenological

Thesis (Ph.D.)--University of Washington, 2016-06

GPNN: Power studies and applications of a neural network method for detecting gene-gene interactions in studies of human disease

Background The identification and characterization of genes that influence the risk of common, complex multifactorial disease primarily through interactions with other genes and environmental factors remains a statistical and computational challenge in genetic epidemiology. We have previously introduced a genetic programming optimized neural network (GPNN) as a method for optimizing the architecture of a neural network to improve the identification of gene combinations associated with disease risk. The goal of this study was to evaluate the power of GPNN for identifying high-order gene-gene interactions. We were also interested in applying GPNN to a real data analysis in Parkinson's disease. Results We show that GPNN has high power to detect even relatively small genetic effects (2–3% heritability) in simulated data models involving two and three locus interactions. The limits of detection were reached under conditions with very small heritability (

Applications of transcranial Doppler in the ICU: a review

Objective: Transcranial Doppler (TCD) ultrasonography is a technique that uses a hand-held Doppler transducer (placed on the surface of the cranial skin) to measure the velocity and pulsatility of blood flow within the intracranial and the extracranial arteries. This review critically evaluates the evidence for the use of TCD in the critical care population. Discussion: TCD has been frequently employed for the clinical evaluation of cerebral vasospasm following subarachnoid haemorrhage (SAH). To a lesser degree, TCD has also been used to evaluate cerebral autoregulatory capacity, monitor cerebral circulation during cardiopulmonary bypass and carotid endarterectomies and to diagnose brain death. Technological advances such as M mode, colour Doppler and three-dimensional power Doppler ultrasonography have extended the scope of TCD to include other non-critical care applications including assessment of cerebral emboli, functional TCD and the management of sickle cell disease. Conclusions: Despite publications suggesting concordance between TCD velocity measurements and cerebral blood flow there are few randomized controlled studies demonstrating an improved outcome with the use of TCD monitoring in neurocritical care. Newer developments in this technology include venous Doppler, functional Doppler and use of ultrasound contrast agents.

GPNN: Power studies and applications of a neural network method for detecting gene-gene interactions in studies of human disease

Background: The identification and characterization of genes that influence the risk of common, complex multifactorial disease primarily through interactions with other genes and environmental factors remains a statistical and computational challenge in genetic epidemiology. We have previously introduced a genetic programming optimized neural network (GPNN) as a method for optimizing the architecture of a neural network to improve the identification of gene combinations associated with disease risk. The goal of this study was to evaluate the power of GPNN for identifying high-order gene-gene interactions. We were also interested in applying GPNN to a real data analysis in Parkinson's disease. Results: We show that GPNN has high power to detect even relatively small genetic effects (2-3% heritability) in simulated data models involving two and three locus interactions. The limits of detection were reached under conditions with very small heritability (

Applications of the cyclone stickiness test for characterization of stickiness in food powders

The cyclone stickiness test (CST) technique was applied to measure the stickiness temperature and relative humidity of whey, honey, and apple juice powders. A moisture sorption isotherm study was conducted to analyze the surface moisture content of whey powder. The glass transition temperatures of the sample powder were analyzed using differential scanning calorimetry (DSC). The stickiness results of these products were found within 20 degrees C above their surface glass transition temperatures, which is well within the normal temperature range for glass transition in general. The results obtained by the CST technique were found consistent with DSC values.

Applications of the behavioural homogeneity evaluation framework: the predictive ability of consumer involvement for international food market segmentation

This article proposes a framework of alternative international marketing strategies, based on the evaluation of intra- and inter-cultural behavioural homogeneity for market segmentation. The framework developed in this study provides a generic structure to behavioural homogeneity, proposing consumer involvement as a construct with unique predictive ability for international marketing strategy decisions. A model-based segmentation process, using structural equation models, is implemented to illustrate the application of the framework.

Phakometric measurement of ocular surface radius of curvature and alignment: evaluation of method with physical model eyes

Ophthalmophakometric measurements of ocular surface radius of curvature and alignment were evaluated on physical model eyes encompassing a wide range of human ocular dimensions. The results indicated that defocus errors arising from imperfections in the ophthalmophakometer camera telecentricity and light source collimation were smaller than experimental errors. Reasonable estimates emerged for anterior lens surface radius of curvature (accuracy: 0.02–0.10 mm; precision 0.05–0.09 mm), posterior lens surface radius of curvature (accuracy: 0.10–0.55 mm; precision 0.06–0.20 mm), eye rotation (accuracy: 0.00–0.32°; precision 0.06–0.25°), lens tilt (accuracy: 0.00–0.33°; precision 0.05–0.98°) and lens decentration (accuracy: 0.00–0.07 mm; precision 0.00–0.07 mm).

Applications of ultralong Raman fibre lasers in photonics

This thesis presents a numerical and experimental investigation on applications of ultralong Raman fibre lasers in optical communications, supercontinuum generation and soliton transmission. The research work is divided in four main sections. The first involves the numerical investigation of URFL intra-cavity power and the relative intensity noise transfer evolution along the transmission span. The performance of the URFL is compared with amplification systems of similar complexity. In the case of intracavity power evolution, URFL is compared with a first order Raman amplification system. For the RIN transfer investigation, URFL is compared with a bi-directional dual wavelength pumping system. The RIN transfer function is investigated for several cavity design parameters such as span length, pump distribution and FBG reflectivity. The following section deals with experimental results of URFL cavities. The enhancement of the available spectral bandwidth in the C-band and its spectral flatness are investigated for single and multi-FBGs cavity system. Further work regarding extended URFL cavity in combination with Rayleigh scattering as random distributed feedback produced a laser cavity with dual wavelength outputs independent to each other. The last two sections relate to URFL application in supercontinuum (SC) generation and soliton transmission. URFL becomes an enhancement structure for SC generation. This thesis shows successful experimental results of SC generation using conventional single mode optical fibre and pumped with a continuous wave source. The last section is dedicated to soliton transmission and the study of soliton propagation dynamics. The experimental results of exact soliton transmission over multiple soliton periods using conventional single mode fibre are shown in this thesis. The effect of the input signal, pump distribution, span length and FBGs reflectivity on the soliton propagation dynamics is investigated experimentally and numerically.

Applications of fractals to image data compression

Digital image processing is exploited in many diverse applications but the size of digital images places excessive demands on current storage and transmission technology. Image data compression is required to permit further use of digital image processing. Conventional image compression techniques based on statistical analysis have reached a saturation level so it is necessary to explore more radical methods. This thesis is concerned with novel methods, based on the use of fractals, for achieving significant compression of image data within reasonable processing time without introducing excessive distortion. Images are modelled as fractal data and this model is exploited directly by compression schemes. The validity of this is demonstrated by showing that the fractal complexity measure of fractal dimension is an excellent predictor of image compressibility. A method of fractal waveform coding is developed which has low computational demands and performs better than conventional waveform coding methods such as PCM and DPCM. Fractal techniques based on the use of space-filling curves are developed as a mechanism for hierarchical application of conventional techniques. Two particular applications are highlighted: the re-ordering of data during image scanning and the mapping of multi-dimensional data to one dimension. It is shown that there are many possible space-filling curves which may be used to scan images and that selection of an optimum curve leads to significantly improved data compression. The multi-dimensional mapping property of space-filling curves is used to speed up substantially the lookup process in vector quantisation. Iterated function systems are compared with vector quantisers and the computational complexity or iterated function system encoding is also reduced by using the efficient matching algcnithms identified for vector quantisers.