The Ability of Specific-wavelength LED Lights to Attract Night-flying Insects

This paper describes a portable collecting light, designed by the authors, that weighs 0.3 kg, is powered by 8 AA batteries, and uses 9 light-emitting diodes (LEDs) to attract night-flying insects. Five different wavelengths of these LED lights, all within the long-wave ultraviolet spectrum, were compared to each other and to a commercially-available 15w fluorescent ultraviolet tube light for their abilities to collect insects over a series of 5 nights in July 2016. There was no difference in order richness, total specimen abundance, or the specimen abundance of most common orders between any of the wavelengths tested. Most LED wavelengths, however, caught fewer Diptera specimens than the fluorescent tube light, largely due to a lower abundance of chironomid midges. Differences in specimen abundance were greater based on sampling date or specific sampling location than based on type of collecting light. Due to their greater portability and possibly lower bycatch of Diptera, these new LED lights are presented as a potential alternative to ultraviolet tube lights

A Multiplicative Model for Learning Distributed Text-Based Attribute Representations

In this paper we propose a general framework for learning distributed representations of attributes: characteristics of text whose representations can be jointly learned with word embeddings. Attributes can correspond to document indicators (to learn sentence vectors), language indicators (to learn distributed language representations), meta-data and side information (such as the age, gender and industry of a blogger) or representations of authors. We describe a third-order model where word context and attribute vectors interact multiplicatively to predict the next word in a sequence. This leads to the notion of conditional word similarity: how meanings of words change when conditioned on different attributes. We perform several experimental tasks including sentiment classification, cross-lingual document classification, and blog authorship attribution. We also qualitatively evaluate conditional word neighbours and attribute-conditioned text generation.Comment: 11 pages. An earlier version was accepted to the ICML-2014 Workshop on Knowledge-Powered Deep Learning for Text Minin