A Kernel-Based Calculation of Information on a Metric Space

Kernel density estimation is a technique for approximating probability distributions. Here, it is applied to the calculation of mutual information on a metric space. This is motivated by the problem in neuroscience of calculating the mutual information between stimuli and spiking responses; the space of these responses is a metric space. It is shown that kernel density estimation on a metric space resembles the k-nearest-neighbor approach. This approach is applied to a toy dataset designed to mimic electrophysiological data

A First Glimpse of String Theory in the Sky?

We propose a new method for identifying new physics imprints on present observational data in cosmology whereby signatures of string theory are clearly distinguished from imprints of possible features on the inflaton potential. Our method relies on the cross-correlations spectra of cosmic shear from large scale structure (LSS) with the CMB temperature anisotropies and E-mode polarization, by using the following properties: inflationary cosmology provides only one source term for all CMB spectra and LSS which highly constrains any deviations from the standard predictions; string theory can add new non-inflationary channels to the source of perturbations as well as modify clustering properties at large scales. Discrepancies in the source terms of correlations and clustering properties provide the evidence for new physics. Models of single-field inflation with a feature are disfavored even with present data. Upcoming WMAP results and future data from weak lensing of LSS will further improve our ability to probe new physics in this manner and could open the first direct window to string theory.Comment: 14 pages, 7 figures, Revtex, typos corrected and references adde

Pulse analysis of acoustic emission signals

A method for the signature analysis of pulses in the frequency domain and the time domain is presented. Fourier spectrum, Fourier transfer function, shock spectrum and shock spectrum ratio were examined in the frequency domain analysis, and pulse shape deconvolution was developed for use in the time domain analysis. Comparisons of the relative performance of each analysis technique are made for the characterization of acoustic emission pulses recorded by a measuring system. To demonstrate the relative sensitivity of each of the methods to small changes in the pulse shape, signatures of computer modeled systems with analytical pulses are presented. Optimization techniques are developed and used to indicate the best design parameters values for deconvolution of the pulse shape. Several experiments are presented that test the pulse signature analysis methods on different acoustic emission sources. These include acoustic emissions associated with: (1) crack propagation, (2) ball dropping on a plate, (3) spark discharge and (4) defective and good ball bearings. Deconvolution of the first few micro-seconds of the pulse train are shown to be the region in which the significant signatures of the acoustic emission event are to be found

Development and use of an extensometer for determining the mechanical compliance of crack toughness test specimens

Extensometer for determining mechanical compliance of crack toughness test specimen

Pulse analysis of acoustic emission signals

A method for the signature analysis of pulses in the frequency domain and the time domain is presented. Fourier spectrum, Fourier transfer function, shock spectrum and shock spectrum ratio were examined in the frequency domain analysis and pulse shape deconvolution was developed for use in the time domain analysis. Comparisons of the relative performance of each analysis technique are made for the characterization of acoustic emission pulses recorded by a measuring system. To demonstrate the relative sensitivity of each of the methods to small changes in the pulse shape, signatures of computer modeled systems with analytical pulses are presented. Optimization techniques are developed and used to indicate the best design parameter values for deconvolution of the pulse shape. Several experiments are presented that test the pulse signature analysis methods on different acoustic emission sources. These include acoustic emission associated with (a) crack propagation, (b) ball dropping on a plate, (c) spark discharge, and (d) defective and good ball bearings. Deconvolution of the first few micro-seconds of the pulse train is shown to be the region in which the significant signatures of the acoustic emission event are to be found

Nocturnal Flight Periodicity of the Caddisflies (Trichoptera) in Forest and Meadow Habitats of a First Order Michigan Stream

Using ultraviolet light traps, over 5000 caddisfly specimens were collected from a forest and a meadow habitat of Fairbanks Creek in northern Lower Michigan. Samples were collected every 15 minutes, interspersed with 15 minutes of no sampling, from sunset to sunrise during 5 nights from late June to mid-July 2014. Despite having fundamentally different caddisfly assemblages dominated by different species, mean specimen abundance and mean species richness in both habitats exhibited similar trends: peaking between 22:30 and 23:00, decreasing until 02:00 or 02:30, increasing again slightly during the later morning periods, and then decreasing to near zero by 06:00. On average, \u3e90% of species from the forest site were caught by 00:00 and 100% by 02:00, whereas meadow site richness didn’t reach 90% until 01:00 and 100% until 05:00. Species richness per night correlated strongly with dew point for both sites, reflecting consistently warm temperatures throughout the sampling period. Our results suggest that caddisfly flight is controlled by both innate behavior and environmental factors like temperature, and that sampling should continue late into the night to maximize capture, especially in open-canopied areas