Little green steps: sustainability practice for early years comes to WA.

Little Green Steps, a training workshop on education for sustainability for early years educators, was recently conducted by the Australian Association for Environmental Education - Western Australian Chapter (MEE-WAJ. With a grant from the Waste Authority of Western Australia, AAEE-WA was able to provide professional learning for staff of childcare services, kindergartens and preschools. The purpose of the training was to encourage sustainable practice through zero waste policy and practical implementation of these practices for children, staff and parents. This training was developed by Lady Gowrie Child Centre In Sydney and the Department of Environment, Climate Change and Water in New South Wales, and assisted in the setting up of the professional development component of Gosford City and Wyong Shire Councils' Little Green Steps Program. To increase national exposure to the program two days were offered in WA. Each day stood alone as a discrete training program

Parametric oscillator tuning curve from observations of total parametric fluorescence

Measurements of total emitted parametric fluorescence power are presented and used to fix one point on the predicted tuning curve of a parametric oscillator. The method is particularly useful for predicting the tuning curve of infrared pumped parametric oscillators. Experimental results, which verify the usefulness of the technique in a 1.06-μ-pumped oscillator, are presented

Frequency analysis via the method of moment functionals

Several variants are presented of a linear-in-parameters least squares formulation for determining the transfer function of a stable linear system at specified frequencies given a finite set of Fourier series coefficients calculated from transient nonstationary input-output data. The basis of the technique is Shinbrot's classical method of moment functionals using complex Fourier based modulating functions to convert a differential equation model on a finite time interval into an algebraic equation which depends linearly on frequency-related parameters

Comparison of Standard Length, Fork Length, and Total Length for Measuring West Coast Marine Fishes

Measurements of adult marine fishes on the U.S. west coast are usually made using one of three methods: standard length, fork length, or total length. Each method has advantages and disadvantages. In this paper we attempt to determine whether one method is faster and/or more reliable than the other methods. We found that all three methods were comparable. There was no appreciable difference in the time it took to measure fish using the different methods. Fork length had the most reproducible results; however, it had the highest level of bias between researchers. We therefore suggest that selection of measurement type be based on what other researchers have used for the species under study. The best improvement in measurement reliability probably occurs by adequate training of personnel and not type of measurement used

Suppression of spin-pumping by a MgO tunnel-barrier

Spin-pumping generates pure spin currents in normal metals at the ferromagnet (F)/normal metal (N) interface. The efficiency of spin-pumping is given by the spin mixing conductance, which depends on N and the F/N interface. We directly study the spin-pumping through an MgO tunnel-barrier using the inverse spin Hall effect, which couples spin and charge currents and provides a direct electrical detection of spin currents in the normal metal. We find that spin-pumping is suppressed by the tunnel-barrier, which is contrary to recent studies that suggest that the spin mixing conductance can be enhanced by a tunnel-barrier inserted at the interface

Identifying Galaxy Mergers in Observations and Simulations with Deep Learning

Mergers are an important aspect of galaxy formation and evolution. We aim to test whether deep learning techniques can be used to reproduce visual classification of observations, physical classification of simulations and highlight any differences between these two classifications. With one of the main difficulties of merger studies being the lack of a truth sample, we can use our method to test biases in visually identified merger catalogues. A convolutional neural network architecture was developed and trained in two ways: one with observations from SDSS and one with simulated galaxies from EAGLE, processed to mimic the SDSS observations. The SDSS images were also classified by the simulation trained network and the EAGLE images classified by the observation trained network. The observationally trained network achieves an accuracy of 91.5% while the simulation trained network achieves 65.2% on the visually classified SDSS and physically classified EAGLE images respectively. Classifying the SDSS images with the simulation trained network was less successful, only achieving an accuracy of 64.6%, while classifying the EAGLE images with the observation network was very poor, achieving an accuracy of only 53.0% with preferential assignment to the non-merger classification. This suggests that most of the simulated mergers do not have conspicuous merger features and visually identified merger catalogues from observations are incomplete and biased towards certain merger types. The networks trained and tested with the same data perform the best, with observations performing better than simulations, a result of the observational sample being biased towards conspicuous mergers. Classifying SDSS observations with the simulation trained network has proven to work, providing tantalizing prospects for using simulation trained networks for galaxy identification in large surveys.Comment: Submitted to A&A, revised after first referee report. 20 pages, 22 figures, 14 tables, 1 appendi

Surface spin flip probability of mesoscopic Ag wires

Spin relaxation in mesoscopic Ag wires in the diffusive transport regime is studied via nonlocal spin valve and Hanle effect measurements performed on permalloy/Ag lateral spin valves. The ratio between momentum and spin relaxation times is not constant at low temperatures. This can be explained with the Elliott-Yafet spin relaxation mechanism by considering the momentum surface relaxation time as being temperature dependent. We present a model to separately determine spin flip probabilities for phonon, impurity and surface scattering and find that the spin flip probability is highest for surface scattering.Comment: 5 pages, 4 figure