The influence of habitat quality on the foraging strategies of the entomopathogenic nematodes Steinernema carpocapsae and Heterorhabditis megidis

Entomopathogenic nematodes (EPN) are soil-transmitted parasites and their foraging strategies are believed to range from ‘ambush’ to ‘cruise’ foragers. However, research on their behaviour has not considered the natural habitat of these nematodes. We hypothesized that EPN behaviour would be influenced by soil habitat quality and tested this hypothesis using 2 EPN species Steinernema carpocapsae (an ‘ambusher’) and Heterorhabditis megidis (a ‘cruiser’) in 2 contrasting habitats, sand and peat. As predicted from previous studies, in sand most S. carpocapsae remained at the point of application and showed no taxis towards hosts, but in peat S. carpocapsae dispersed much more and showed a highly significant taxis towards hosts. H. megidis dispersed well in both media, but only showed taxis towards hosts in sand. In outdoor mesocosms in which both species were applied, S. carpocapsae outcompeted H. megidis in terms of host finding in peat, whereas the opposite was true in sand. Our data suggest that these 2 EPN may be habitat specialists and highlight the difficulties of studying soil-transmitted parasites in non-soil media

Robustness of System-Filter Separation for the Feedback Control of a Quantum Harmonic Oscillator Undergoing Continuous Position Measurement

We consider the effects of experimental imperfections on the problem of estimation-based feedback control of a trapped particle under continuous position measurement. These limitations violate the assumption that the estimator (i.e. filter) accurately models the underlying system, thus requiring a separate analysis of the system and filter dynamics. We quantify the parameter regimes for stable cooling, and show that the control scheme is robust to detector inefficiency, time delay, technical noise, and miscalibrated parameters. We apply these results to the specific context of a weakly interacting Bose-Einstein condensate (BEC). Given that this system has previously been shown to be less stable than a feedback-cooled BEC with strong interatomic interactions, this result shows that reasonable experimental imperfections do not limit the feasibility of cooling a BEC by continuous measurement and feedback.Comment: 14 pages, 8 figure

A Framework for Bioacoustic Vocalization Analysis Using Hidden Markov Models

Using Hidden Markov Models (HMMs) as a recognition framework for automatic classification of animal vocalizations has a number of benefits, including the ability to handle duration variability through nonlinear time alignment, the ability to incorporate complex language or recognition constraints, and easy extendibility to continuous recognition and detection domains. In this work, we apply HMMs to several different species and bioacoustic tasks using generalized spectral features that can be easily adjusted across species and HMM network topologies suited to each task. This experimental work includes a simple call type classification task using one HMM per vocalization for repertoire analysis of Asian elephants, a language-constrained song recognition task using syllable models as base units for ortolan bunting vocalizations, and a stress stimulus differentiation task in poultry vocalizations using a non-sequential model via a one-state HMM with Gaussian mixtures. Results show strong performance across all tasks and illustrate the flexibility of the HMM framework for a variety of species, vocalization types, and analysis tasks

A Framework for Bioacoustic Vocalization Analysis Using Hidden Markov Models

Using Hidden Markov Models (HMMs) as a recognition framework for automatic classification of animal vocalizations has a number of benefits, including the ability to handle duration variability through nonlinear time alignment, the ability to incorporate complex language or recognition constraints, and easy extendibility to continuous recognition and detection domains. In this work, we apply HMMs to several different species and bioacoustic tasks using generalized spectral features that can be easily adjusted across species and HMM network topologies suited to each task. This experimental work includes a simple call type classification task using one HMM per vocalization for repertoire analysis of Asian elephants, a language-constrained song recognition task using syllable models as base units for ortolan bunting vocalizations, and a stress stimulus differentiation task in poultry vocalizations using a non-sequential model via a one-state HMM with Gaussian mixtures. Results show strong performance across all tasks and illustrate the flexibility of the HMM framework for a variety of species, vocalization types, and analysis tasks

Tax-planning techniques for individuals; Studies in federal taxation 2

https://egrove.olemiss.edu/aicpa_guides/1248/thumbnail.jp

Transfer Printing of Photonic Nanostructures to Silicon Integrated Circuits

Optical systems require the integration of technologies fabricated on different materials. We use a transfer printing technique to integrate pre-processed III-V, polymer and silicon membrane devices onto passive optical circuits with nano-metric positional accuracy