The sacred edict; with a translation of the colloquial rendering, notes and vocabulary, by F. W. Baller. Prepared for the use of junior members of the China Inland Mission.

http://www.archive.org/details/thesacrededict01kanguoft

PHOTOREFRACTIVE CRYSTAL-BASED ACOUSTO-OPTIC IMAGING IN THE NEAR-INFRARED AND ITS APPLICATIONS

Acousto-optic (AO) sensing and imaging (AOI) is a dual-wave modality that combines ultrasound with diffusive light to measure and/or image the optical properties of optically diffusive media, including biological tissues such as breast and brain. The light passing through a focused ultrasound beam undergoes a phase modulation at the ultrasound frequency that is detected using an adaptive interferometer scheme employing a GaAs photorefractive crystal (PRC). The PRC-based AO system operating at 1064 nm is described, along with the underlying theory, validating experiments, characterization, and optimization of this sensing and imaging apparatus. The spatial resolution of AO sensing, which is determined by spatial dimensions of the ultrasound beam or pulse, can be sub-millimeter for megahertz-frequency sound waves.A modified approach for quantifying the optical properties of diffuse media with AO sensing employs the ratio of AO signals generated at two different ultrasound focal pressures. The resulting “pressure contrast signal” (PCS), once calibrated for a particular set of pressure pulses, yields a direct measure of the spatially averaged optical transport attenuation coefficient within the interaction volume between light and sound. This is a significant improvement over current AO sensing methods since it produces a quantitative measure of the optical properties of optically diffuse media without a priori knowledge of the background illumination. It can also be used to generate images based on spatial variations in both optical scattering and absorption. Finally, the AO sensing system is modified to monitor the irreversible optical changes associated with the tissue heating from high intensity focused ultrasound (HIFU) therapy, providing a powerful method for noninvasively sensing the onset and growth of thermal lesions in soft tissues. A single HIFU transducer is used to simultaneously generate tissue damage and pump the AO interaction. Experimental results performed in excised chicken breast demonstrate that AO sensing can identify the onset and growth of lesion formation in real time and, when used as feedback to guide exposure parameters, results in more predictable lesion formation.

EXPERIMENTAL INVESTIGATION OF LINEAR BUBBLE DYNAMICS IN A VISCOELASTIC XANTHAN GEL

Oceanic bubble plumes caused by ship wakes or breaking waves disrupt sonar communi- cation because of the dramatic change in sound speed and attenuation in the bubbly fluid. Experiments in bubbly fluids have suffered from the inability to quantitatively characterize the fluid because of continuous air bubble motion. Conversely, single bubble experiments, where the bubble is trapped by a pressure field or stabilizing object, are limited in usable frequency range, apparatus complexity, or the invasive nature of the stabilizing object (wire, plate, etc.). Suspension of a bubble in a viscoelastic Xanthan gel allows acoustically forced oscilla- tions with negligible translation over a broad frequency band. Assuming only linear, radial motion, laser scattering from a bubble oscillating below, through, and above its resonance is measured. As the bubble dissolves in the gel, different bubble sizes are measured in the range 240 – 470 μm radius, corresponding to the frequency range 6 – 14 kHz. Equalization of the cell response in the raw data isolates the frequency response of the bubble. Compari- son to theory for a bubble in water shows good agreement between the predicted resonance frequency and damping, such that the bubble behaves as if it were oscillating in water.

A FLOW-THROUGH ACOUSTIC WAVEGUIDE FOR TWO-PHASE BUBBLY FLOW VOID FRACTION MEASUREMENT

In the Spallation Neutron Source (SNS) facility at Oak Ridge National Laboratory (ORNL), the deposition of a high-energy proton beam into the liquid mercury target forms bubbles whose asymmetric collapse cause Cavitation Damage Erosion (CDE) to the container walls, thereby reducing its usable lifetime. One proposed solution for mitigation of this damage is to inject a population of microbubbles into the mercury, yielding a compliant and attenuative medium that will reduce the resulting cavitation damage. This potential solution presents the task of creating a diagnostic tool to monitor bubble population in the mercury flow in order to correlate void fraction and damage. Details of an acoustic waveguide for the eventual measurement of two-phase mercury-helium flow void fraction are discussed. The assembly’s waveguide is a vertically oriented stainless steel cylinder with 5.08cm ID, 1.27cm wall thickness and 40cm length. For water experiments, a 2.54cm thick stainless steel plate at the bottom supports the fluid, provides an acoustically rigid boundary condition, and is the mounting point for a hydrophone. A port near the bottom is the inlet for the fluid of interest. A spillover reservoir welded to the upper portion of the main tube allows for a flow-through design, yielding a pressure release top boundary condition for the waveguide. A cover on the reservoir supports an electrodynamic shaker that is driven by linear frequency sweeps to excite the tube. The hydrophone captures the frequency response of the waveguide. The sound speed of the flowing medium is calculated, assuming a linear dependence of axial mode number on modal frequency (plane wave). Assuming that the medium has an effective-mixture sound speed, and that it contains bubbles which are much smaller than the resonance radii at the highest frequency of interest (Wood’s limit), the void fraction of the flow is calculated. Results for water and bubbly water of varying void fraction are presented, and serve to demonstrate the accuracy and precision of the apparatus.

The Specialized Mappings Architecture

A probabilistic, nonlinear supervised learning model is proposed: the Specialized Mappings Architecture (SMA). The SMA employs a set of several forward mapping functions that are estimated automatically from training data. Each specialized function maps certain domains of the input space (e.g., image features) onto the output space (e.g., articulated body parameters). The SMA can model ambiguous, one-to-many mappings that may yield multiple valid output hypotheses. Once learned, the mapping functions generate a set of output hypotheses for a given input via a statistical inference procedure. The SMA inference procedure incorporates an inverse mapping or feedback function in evaluating the likelihood of each of the hypothesis. Possible feedback functions include computer graphics rendering routines that can generate images for given hypotheses. The SMA employs a variant of the Expectation-Maximization algorithm for simultaneous learning of the specialized domains along with the mapping functions, and approximate strategies for inference. The framework is demonstrated in a computer vision system that can estimate the articulated pose parameters of a human’s body or hands, given silhouettes from a single image. The accuracy and stability of the SMA are also tested using synthetic images of human bodies and hands, where ground truth is known.