Estimation of calcium carbonate in soils

RESP-13

Analysis of the wind tunnel test of a tilt rotor power force model

Two series of wind tunnel tests were made to determine performance, stability and control, and rotor wake interaction on the airframe, using a one-tenth scale powered force model of a tilt rotor aircraft. Testing covered hover (IGE/OCE), helicopter, conversion, and airplane flight configurations. Forces and moments were recorded for the model from predetermined trim attitudes. Control positions were adjusted to trim flight (one-g lift, pitching moment and drag zero) within the uncorrected test data balance accuracy. Pitch and yaw sweeps were made about the trim attitudes with the control held at the trimmed settings to determine the static stability characteristics. Tail on, tail off, rotors on, and rotors off configurations were testes to determine the rotor wake effects on the empennage. Results are presented and discussed

The fundamental solution of the unidirectional pulse propagation equation

The fundamental solution of a variant of the three-dimensional wave equation known as "unidirectional pulse propagation equation" (UPPE) and its paraxial approximation is obtained. It is shown that the fundamental solution can be presented as a projection of a fundamental solution of the wave equation to some functional subspace. We discuss the degree of equivalence of the UPPE and the wave equation in this respect. In particular, we show that the UPPE, in contrast to the common belief, describes wave propagation in both longitudinal and temporal directions, and, thereby, its fundamental solution possesses a non-causal character.Comment: accepted to J. Math. Phy

New Hypothesis for Cause of Epidemic among Native Americans, New England, 1616–1619

This epidemic may have been leptospirosis complicated by Weil syndrome

Origin Gaps and the Eternal Sunshine of the Second-Order Pendulum

The rich experiences of an intentional, goal-oriented life emerge, in an unpredictable fashion, from the basic laws of physics. Here I argue that this unpredictability is no mirage: there are true gaps between life and non-life, mind and mindlessness, and even between functional societies and groups of Hobbesian individuals. These gaps, I suggest, emerge from the mathematics of self-reference, and the logical barriers to prediction that self-referring systems present. Still, a mathematical truth does not imply a physical one: the universe need not have made self-reference possible. It did, and the question then is how. In the second half of this essay, I show how a basic move in physics, known as renormalization, transforms the "forgetful" second-order equations of fundamental physics into a rich, self-referential world that makes possible the major transitions we care so much about. While the universe runs in assembly code, the coarse-grained version runs in LISP, and it is from that the world of aim and intention grows.Comment: FQXI Prize Essay 2017. 18 pages, including afterword on Ostrogradsky's Theorem and an exchange with John Bova, Dresden Craig, and Paul Livingsto

The Conditional Lucas & Kanade Algorithm

The Lucas & Kanade (LK) algorithm is the method of choice for efficient dense image and object alignment. The approach is efficient as it attempts to model the connection between appearance and geometric displacement through a linear relationship that assumes independence across pixel coordinates. A drawback of the approach, however, is its generative nature. Specifically, its performance is tightly coupled with how well the linear model can synthesize appearance from geometric displacement, even though the alignment task itself is associated with the inverse problem. In this paper, we present a new approach, referred to as the Conditional LK algorithm, which: (i) directly learns linear models that predict geometric displacement as a function of appearance, and (ii) employs a novel strategy for ensuring that the generative pixel independence assumption can still be taken advantage of. We demonstrate that our approach exhibits superior performance to classical generative forms of the LK algorithm. Furthermore, we demonstrate its comparable performance to state-of-the-art methods such as the Supervised Descent Method with substantially less training examples, as well as the unique ability to "swap" geometric warp functions without having to retrain from scratch. Finally, from a theoretical perspective, our approach hints at possible redundancies that exist in current state-of-the-art methods for alignment that could be leveraged in vision systems of the future.Comment: 17 pages, 11 figure