U.S. DOL Certifies Approximately 8,600 Workers in 17 States as Eligible to Apply for Trade Adjustment Assistance

Workers facing layoffs or reduced hours due to direct foreign competition may receive Trade Adjustment Assistance to help prepare them for new jobs in emerging sectors. Includes chart of effected workplaces

Hash Embeddings for Efficient Word Representations

We present hash embeddings, an efficient method for representing words in a continuous vector form. A hash embedding may be seen as an interpolation between a standard word embedding and a word embedding created using a random hash function (the hashing trick). In hash embeddings each token is represented by $k$ $d$-dimensional embeddings vectors and one $k$ dimensional weight vector. The final $d$ dimensional representation of the token is the product of the two. Rather than fitting the embedding vectors for each token these are selected by the hashing trick from a shared pool of $B$ embedding vectors. Our experiments show that hash embeddings can easily deal with huge vocabularies consisting of millions of tokens. When using a hash embedding there is no need to create a dictionary before training nor to perform any kind of vocabulary pruning after training. We show that models trained using hash embeddings exhibit at least the same level of performance as models trained using regular embeddings across a wide range of tasks. Furthermore, the number of parameters needed by such an embedding is only a fraction of what is required by a regular embedding. Since standard embeddings and embeddings constructed using the hashing trick are actually just special cases of a hash embedding, hash embeddings can be considered an extension and improvement over the existing regular embedding types

Animal Industry News, 2009, Vol. 10, no. 1

Newsletter produced by Department of Agriculture and Land Stewardship about the animal industry in Iowa

Multiple Pulse Line Narrowing: Approaches for Solid State NMR Imaging

The application of NMR imaging to problems in materials science, and in particular to nondestructive evaluation, has been hindered by a lack of appropriate NMR techniques to image rigid solids. NMR imaging of solids is made difficult by the typically broad NMR lines observed in the solid state. Molecular motion in liquids narrows the NMR line, making possible the high quality images obtained in medical imaging. The molecular motion present in some solids has been exploited to obtain NMR images materials such as elastomers [1,2]. Alternatively, the solid component of materials has been inferred from the absence of signals in NMR images of imbibed fluids. Here we discuss a class of NMR imaging methods which aim to reduce the apparent solid state linewidth to values approximating those in liquid samples

Fourier Transform Raman Spectroscopy of Photoactive Proteins with Near-Infrared Excitation

This is the publisher's version, also available electronically from http://www.opticsinfobase.org/as/abstract.cfm?URI=as-44-7-1103.The Fourier transform (FT) Raman spectroscopic treatment of the photoactive proteins bacteriorhodopsin and the photosynthetic reaction center is reported, with excitation at 1.06 μm. Excitation at this wavelength circumvents the limitations on resonance Raman spectroscopy of these proteins imposed by their photolability and by the fluorescence of free pigments or impurities. The spectra are dominated by nonresonant Raman scattering by the protein-bound pigments retinal (in bacteriorhodopsin) and bacteriopheophytin, bacteriochlorophyll, and carotenoids (in reaction centers). The relative intensities of retinylidene modes in the spectrum for nonresonant FT Raman spectroscopy of bacteriorhodopsin are nearly identical to those observed in the resonance Raman spectrum of bacteriorhodopsin