Photoacoustic tomography using a Mach-Zehnder interferometer as an acoustic line detector

A three-dimensional photoacoustic imaging method is presented that uses a Mach-Zehnder interferometer for measurement of acoustic waves generated in an object by irradiation with short laser pulses. The signals acquired with the interferometer correspond to line integrals over the acoustic wave field. An algorithm for reconstruction of a three-dimensional image from such signals measured at multiple positions around the object is shown that is a combination of a frequency-domain technique and the inverse Radon transform. From images of a small source scanning across the interferometer beam it is estimated that the spatial resolution of the imaging system is in the range of 100 to about 300 mum, depending on the interferometer beam width and the size of the aperture formed by the scan length divided by the source-detector distance. By taking an image of a phantom it could be shown that the imaging system in its present configuration is capable of producing three-dimensional images of objects with an overall size in the range of several millimeters to centimeters. Strategies are proposed how the technique can be scaled for imaging of smaller objects with higher resolution.     

Insulin sensitivity in type 2 diabetes: univariate and multivariate techniques to derive estimates of insulin sensitivity from the insulin modified intravenous glucose tolerance test (FSIGT)

The use of univariate and multivariate techniques to derive estimates of insulin sensitivity from the insulin modified FSIGT were investigated in 12 Type 2 diabetic subjects aged (mean+/-S.D.) 59+/-9.5 years and BMI 28.1+/-2.2 kg m(-2), who underwent both a FSIGT and an isoglycemic hyperinsulinemic clamp. Reproducibility of the FSIGT was tested in four patients on three separate occasions. FSIGT data were assessed by both univariate and multivariate techniques. The sensitivity index for the FSIGT ranged from 0.162 to 3.292 (mean 1.378) x 10(-4) x l min(-1) mU(-1) for the univariate approach and from 0.163 to 2.727 (mean 1.378) x 10(-4) x l min(-1) mU(-1) for the multivariate method. Mean S(Iclamp) was 44.41 x 10(-4) x l(-2) min(-1) x mU(-1) (range 22.0-77.92). The correlation of the insulin sensitivity indices between the clamp and the FSIGT was 0.51 (P=0.056) for the univariate and 0.67 (P=0.017) for the multivariate analyses. Repeated FSIGTs showed a lower variability for the multivariate than for the standard approach.     

A theoretical investigation of reference frames for the planning of speech movements.

Does the speech motor control system use invariant vocal tract shape targets when producing vowels and semivowels? A 4-part theoretical treatment favoring models whose only invariant targets are regions in auditory perceptual space over models that posit invariant constriction targets is presented. Auditory target regions are hypothesized to arise during development as an emergent property of neural map formation in the auditory system. Furthermore, speech movements are planned as trajectories in auditory perceptual space. These trajectories are then mapped into articulator movements through a neural mapping that allows motor equivalent variability in constriction locations and degrees when needed. These hypotheses are illustrated using computer simulations of the DIVA model of speech acquisition and production. Finally, several difficult challenges to proponents of constriction theories based on this theoretical treatment are posed. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Teaching social responsibility

I define a socially responsible enterprise as one that in some way promotes the general welfare and dignity of humanity and is respectful of the Earth and its finite resources. I have implemented teaching about social responsibility into a freshman-level computer programming class designed for all engineering majors. By means of ethical problem-solving and reflective writing assignments, students are challenged to define and develop their sense of social responsibility at the same time that they are learning engineering fundamentals. Several of the student assignments are based on scenarios adapted from the author's engineering experience. Thus, the emphasis is on ethical dilemmas and issues encountered in daily professional life, including the important one of selecting an employer or project     

Fiber-optic localization by geometric space coding with a two-dimensional gray code

With the objective of monitoring motion within a room, we segment the two-dimensional (2D) floor space into discrete cells and encode each cell with a binary code word generated by a fiber. We design a set of k-neighbor-local codes to localize an extended object and, particularly when k = 2, employ a 2D gray code to localize a human by tracking his or her footsteps. Methods for implementing the codes in a fiber web are discussed, and we demonstrate the experimental result with the fiber mat. The observed system performance confirms the theoretical analysis. The space coding technique is a promising low-cost candidate not only for human tracking but also for other applications such as human gait analysis.     

12.2--Laser-triggered megavolt switching

Laser-initiated breakdown of high-voltage spark gaps has been extended to the megavolt range through the use of a novel coaxial triggering geometry. In this configuration, a 100-to 250-megawatt ruby laser of 1.4- to 3.5-joules output was aligned along the interelectrode axis of the spark gap. The laser beam passed through a hemispherical electrode, mounted on a hollow shaft, and was focused by a lens internal to this electrode at the opposite-switch electrode surface. Based on investigations of the effect of polarity on switch performance, i.e., least delay and jitter, it was concluded that 1) irradiation of the charged electrode was preferred and 2) irradiation of positive-rather than negative-charged electrodes gave best performance. Delay times between arrival of the laser pulse and complete gap closure as short as 2 ns with unmeasurable jitter (< 1 ns) were readily attainable under various conditions (high-pressure and high-reduced fields). By recourse to classical arc breakdown theories, i.e., Townsend avalanche and streamer mechanisms, it was concluded that the variation of delay with reduced field follows an avalanche process. However, for an explanation of extremely short delays observed (high-velocity closure rates), a streamer mechanism is necessary. Photographs of laser-triggered breakdown gave consistently single-channel straight arc breakdown with the absence of lossy arrested discharges, while self-breakdown or mechanically triggered breakdown produced longer and irregular breakdown channels with numerous energy-absorbing arrested leaders. This observation is in concert with the extremely short delays observed and leads us to suspect that volume dielectric breakdown or at least arc channel preparation is responsible for the observed results.     

An investigative study of a wave-energy device

This paper presents the methodology and design of an offshore float device to capture the power in waves. Results, both experimental and theoretical, reveal that a simple modification of a mechanical cycle can lead to a significant increase in the energy that is developed. A prototype device, to be tested on the Great Lakes, is presented with experimental results obtained from laboratory testing. The responses of the prototype system are correlated to illustrate that wave power can provide significant amounts of energy. The novel method analyzed, when employed on other float devices, increases the energy output of the system. The recovery concept presented increases the deliverable energy that can be captured from a bouyant float following the free passage of a wave: this is accomplished by sequential capture (preloading) and release of the buoyant float at critical stages of wave passage. Displacement-work-energy concepts presented illustrate that preloading a float in the trough of the wave and subsequent release of it under the wave crest, as a mechanical cycle, can lead to a return of more energy than was required to preload the float and provide a net increase of energy that might be extracted from a wave alone.     

Prediction of insemination outcomes in Holstein dairy cattle using alternative machine learning algorithms

When making the decision about whether or not to breed a given cow, knowledge about the expected outcome would have an economic impact on profitability of the breeding program and net income of the farm. The outcome of each breeding can be affected by many management and physiological features that vary between farms and interact with each other. Hence, the ability of machine learning algorithms to accommodate complex relationships in the data and missing values for explanatory variables makes these algorithms well suited for investigation of reproduction performance in dairy cattle. The objective of this study was to develop a user-friendly and intuitive on-farm tool to help farmers make reproduction management decisions. Several different machine learning algorithms were applied to predict the insemination outcomes of individual cows based on phenotypic and genotypic data. Data from 26 dairy farms in the Alta Genetics (Watertown, WI) Advantage Progeny Testing Program were used, representing a 10-yr period from 2000 to 2010. Health, reproduction, and production data were extracted from on-farm dairy management software, and estimated breeding values were downloaded from the US Department of Agriculture Agricultural Research Service Animal Improvement Programs Laboratory (Beltsville, MD) database. The edited data set consisted of 129,245 breeding records from primiparous Holstein cows and 195,128 breeding records from multiparous Holstein cows. Each data point in the final data set included 23 and 25 explanatory variables and 1 binary outcome for of 0.756 ± 0.005 and 0.736 ± 0.005 for primiparous and multiparous cows, respectively. The naïve Bayes algorithm, Bayesian network, and decision tree algorithms showed somewhat poorer classification performance. An information-based variable selection procedure identified herd average conception rate, incidence of ketosis, number of previous (failed) inseminations, days in milk at breeding, and mastitis as the most effective explanatory variables in predicting pregnancy outcome.