Low-Temperature Fluorocarbonate Mineralization in Lower Devonian Rhynie Chert, UK

Funding: J.G.T.A was partially funded by the Natural Environment Research Council, grant number NE/T003677/1. Acknowledgments: We are grateful to W. Ritchie, J. Johnston, and J. Bowie for skilled technicalsupport. Samples were archived by N.H. Trewin, C.M. Rice and S. Fayers.Peer reviewedPublisher PD

What’s wrong with the minimal conception of innateness in cognitive science?

One of the classic debates in cognitive science is between nativism and empiricism about the development of psychological capacities. In principle, the debate is empirical. However, in practice nativist hypotheses have also been challenged for relying on an ill-defined, or even unscientific, notion of innateness as that which is “not learned”. Here this minimal conception of innateness is defended on four fronts. First, it is argued that the minimal conception is crucial to understanding the nativism-empiricism debate, when properly construed; Second, various objections to the minimal conception—that it risks overgeneralization, lacks an account of learning, frustrates genuine explanations of psychological development, and fails to unify different notions of innateness across the sciences—are rebutted. Third, it is argued that the minimal conception avoids the shortcomings of primitivism, the prominent view that innate capacities are those that are not acquired via a psychological process in development. And fourth, the minimal conception undermines some attempts to identify innateness with a natural kind. So in short, we have little reason to reject, and good reason to accept, the minimal conception of innateness in cognitive science

Agricultural Research Service research highlights in remote sensing for calendar year 1981

Selected examples of research accomplishments related to remote sensing are compiled. A brief statement is given to highlight the significant results of each research project. A list of 1981 publication and location contacts is given also. The projects cover emission and reflectance analysis, identification of crop and soil parameters, and the utilization of remote sensing data

Agricultural Research Service research highlights in remote sensing for calendar year 1980

The AR research mission in remote sensing is to develop the basic understanding of the soil plant animal atmosphere continuum in agricultural ecosystems and to determine when remotely sensed data can be used to provide information about these agricultural ecosystems. A brief statement of the significant results of each project is given. A list of 1980 publication and location contacts is also given

Masculinity at work: The experiences of men in female dominated occupations

This paper presents the findings of a research project on the implications of men's non-traditional career choices for their experiences within the organization and for gender identity. The research is based on 40 in-depth interviews with male workers from four occupational groups: librarian-ship, cabin crew, nurses and primary school teachers. Results suggest a typology of male workers in female dominated occupations: seekers (who actively seek the career), finders (who find the occupation in the process of making general career decisions) and settlers (who settle into the career after periods of time in mainly male dominated occupations). Men benefit from their minority status through assumptions of enhanced leadership (the assumed authority effect), by being given differential treatment (the special consideration effect) and being associated with a more careerist attitude to work (the career effect). At the same time, they feel comfortable working with women (the zone of comfort effect). Despite this comfort, men adopt a variety of strategies to re-establish a masculinity that has been undermined by the 'feminine' nature of their work. These include re-labeling, status enhancement and distancing from the feminine. The dynamics of maintaining and reproducing masculinities within the non-traditional work setting are discussed in the light of recent theorising around gender, masculinity and work

Improved Limits on B0B^{0} decays to invisible (+γ)(+\gamma) final states

We establish improved upper limits on branching fractions for B0 decays to final States 10 where the decay products are purely invisible (i.e., no observable final state particles) and for final states where the only visible product is a photon. Within the Standard Model, these decays have branching fractions that are below the current experimental sensitivity, but various models of physics beyond the Standard Model predict significant contributions for these channels. Using 471 million BB pairs collected at the Y(4S) resonance by the BABAR experiment at the PEP-II e+e- storage ring at the SLAC National Accelerator Laboratory, we establish upper limits at the 90% confidence level of 2.4x10^-5 for the branching fraction of B0-->Invisible and 1.7x10^-5 for the branching fraction of B0-->Invisible+gammaComment: 8 pages, 3 postscript figures, submitted to Phys. Rev. D (Rapid Communications

FreezeOut: Accelerate Training by Progressively Freezing Layers

The early layers of a deep neural net have the fewest parameters, but take up the most computation. In this extended abstract, we propose to only train the hidden layers for a set portion of the training run, freezing them out one-by-one and excluding them from the backward pass. Through experiments on CIFAR, we empirically demonstrate that FreezeOut yields savings of up to 20% wall-clock time during training with 3% loss in accuracy for DenseNets, a 20% speedup without loss of accuracy for ResNets, and no improvement for VGG networks. Our code is publicly available at https://github.com/ajbrock/FreezeOutComment: Extended Abstrac

SMASH: One-Shot Model Architecture Search through HyperNetworks

Designing architectures for deep neural networks requires expert knowledge and substantial computation time. We propose a technique to accelerate architecture selection by learning an auxiliary HyperNet that generates the weights of a main model conditioned on that model's architecture. By comparing the relative validation performance of networks with HyperNet-generated weights, we can effectively search over a wide range of architectures at the cost of a single training run. To facilitate this search, we develop a flexible mechanism based on memory read-writes that allows us to define a wide range of network connectivity patterns, with ResNet, DenseNet, and FractalNet blocks as special cases. We validate our method (SMASH) on CIFAR-10 and CIFAR-100, STL-10, ModelNet10, and Imagenet32x32, achieving competitive performance with similarly-sized hand-designed networks. Our code is available at https://github.com/ajbrock/SMAS

Generative and Discriminative Voxel Modeling with Convolutional Neural Networks

When working with three-dimensional data, choice of representation is key. We explore voxel-based models, and present evidence for the viability of voxellated representations in applications including shape modeling and object classification. Our key contributions are methods for training voxel-based variational autoencoders, a user interface for exploring the latent space learned by the autoencoder, and a deep convolutional neural network architecture for object classification. We address challenges unique to voxel-based representations, and empirically evaluate our models on the ModelNet benchmark, where we demonstrate a 51.5% relative improvement in the state of the art for object classification.Comment: 9 pages, 5 figures, 2 table