Suppression of the near-infrared OH night sky lines with fibre Bragg gratings - first results

The background noise between 1 and 1.8 microns in ground-based instruments is dominated by atmospheric emission from hydroxyl molecules. We have built and commissioned a new instrument, GNOSIS, which suppresses 103 OH doublets between 1.47 - 1.7 microns by a factor of ~1000 with a resolving power of ~10,000. We present the first results from the commissioning of GNOSIS using the IRIS2 spectrograph at the AAT. The combined throughput of the GNOSIS fore-optics, grating unit and relay optics is ~36 per cent, but this could be improved to ~46 per cent with a more optimal design. We measure strong suppression of the OH lines, confirming that OH suppression with fibre Bragg gratings will be a powerful technology for low resolution spectroscopy. The integrated OH suppressed background between 1.5 and 1.7 microns is reduced by a factor of 9 compared to a control spectrum using the same system without suppression. The potential of low resolution OH suppressed spectroscopy is illustrated with example observations. The GNOSIS background is dominated by detector dark current below 1.67 microns and by thermal emission above 1.67 microns. After subtracting these we detect an unidentified residual interline component of ~ 860 +/ 210 ph/s/m^2/micron/arcsec^2. This component is equally bright in the suppressed and control spectra. We have investigated the possible source of the interline component, but were unable to discriminate between a possible instrumental artifact and intrinsic atmospheric emission. Resolving the source of this emission is crucial for the design of fully optimised OH suppression spectrographs. The next generation OH suppression spectrograph will be focussed on resolving the source of the interline component, taking advantage of better optimisation for a FBG feed. We quantify the necessary improvements for an optimal OH suppressing fibre spectrograph design.Comment: Accepted for publication in MNRAS. 15 pages, 18 figure

Sunscreens - Which and what for?

It is well established that sun exposure is the main cause for the development of skin cancer. Chronic continuous UV radiation is believed to induce malignant melanoma, whereas intermittent high-dose UV exposure contributes to the occurrence of actinic keratosis as precursor lesions of squamous cell carcinoma as well as basal cell carcinoma. Not only photocarcinogenesis but also the mechanisms of photoaging have recently become apparent. In this respect the use of sunscreens seemed to prove to be more and more important and popular within the last decades. However, there is still inconsistency about the usefulness of sunscreens. Several studies show that inadequate use and incomplete UV spectrum efficacy may compromise protection more than previously expected. The sunscreen market is crowded by numerous products. Inorganic sunscreens such as zinc oxide and titanium oxide have a wide spectral range of activity compared to most of the organic sunscreen products. It is not uncommon for organic sunscreens to cause photocontact allergy, but their cosmetic acceptability is still superior to the one given by inorganic sunscreens. Recently, modern galenic approaches such as micronization and encapsulation allow the development of high-quality inorganic sunscreens. The potential systemic toxicity of organic sunscreens has lately primarily been discussed controversially in public, and several studies show contradictory results. Although a matter of debate, at present the sun protection factor (SPF) is the most reliable information for the consumer as a measure of sunscreen filter efficacy. In this context additional tests have been introduced for the evaluation of not only the protective effect against erythema but also protection against UV-induced immunological and mutational effects. Recently, combinations of UV filters with agents active in DNA repair have been introduced in order to improve photoprotection. This article reviews the efficacy of sunscreens in the prevention of epithelial and nonepithelial skin cancer, the effect on immunosuppression and the value of the SPF as well as new developments on the sunscreen market. Copyright (C) 2005 S. Karger AG, Basel

Keck Planet Finder: design updates

The Keck Planet Finder (KPF) is a fiber-fed, high-resolution, high-stability spectrometer in development at the UC Berkeley Space Sciences Laboratory for the W.M. Keck Observatory. KPF is designed to characterize exoplanets via Doppler spectroscopy with a goal of a single measurement precision of 0.3 m s-1 or better, however its resolution and stability will enable a wide variety of astrophysical pursuits. Here we provide post-preliminary design review design updates for several subsystems, including: the main spectrometer, the fabrication of the Zerodur optical bench; the data reduction pipeline; fiber agitator; fiber cable design; fiber scrambler; VPH testing results and the exposure meter

Keck Planet Finder: design updates

The Keck Planet Finder (KPF) is a fiber-fed, high-resolution, high-stability spectrometer in development at the UC Berkeley Space Sciences Laboratory for the W.M. Keck Observatory. KPF is designed to characterize exoplanets via Doppler spectroscopy with a goal of a single measurement precision of 0.3 m s-1 or better, however its resolution and stability will enable a wide variety of astrophysical pursuits. Here we provide post-preliminary design review design updates for several subsystems, including: the main spectrometer, the fabrication of the Zerodur optical bench; the data reduction pipeline; fiber agitator; fiber cable design; fiber scrambler; VPH testing results and the exposure meter

Towards interpreting recurrent neural networks through probabilistic abstraction

National Research Foundation (NRF) Singapore under its AI Singapore Programm

Exploring spatial-frequency-sequential relationships for motor imagery classification with recurrent neural network

Abstract Background Conventional methods of motor imagery brain computer interfaces (MI-BCIs) suffer from the limited number of samples and simplified features, so as to produce poor performances with spatial-frequency features and shallow classifiers. Methods Alternatively, this paper applies a deep recurrent neural network (RNN) with a sliding window cropping strategy (SWCS) to signal classification of MI-BCIs. The spatial-frequency features are first extracted by the filter bank common spatial pattern (FB-CSP) algorithm, and such features are cropped by the SWCS into time slices. By extracting spatial-frequency-sequential relationships, the cropped time slices are then fed into RNN for classification. In order to overcome the memory distractions, the commonly used gated recurrent unit (GRU) and long-short term memory (LSTM) unit are applied to the RNN architecture, and experimental results are used to determine which unit is more suitable for processing EEG signals. Results Experimental results on common BCI benchmark datasets show that the spatial-frequency-sequential relationships outperform all other competing spatial-frequency methods. In particular, the proposed GRU-RNN architecture achieves the lowest misclassification rates on all BCI benchmark datasets. Conclusion By introducing spatial-frequency-sequential relationships with cropping time slice samples, the proposed method gives a novel way to construct and model high accuracy and robustness MI-BCIs based on limited trials of EEG signals

Influence of fire prevention management strategies on the diversity of butterfly fauna in the eastern Pyrenees

Fire prevention management is becoming a necessity in many Mediterranean locations to regulate fire of natural or human origin. However, very few studies have determined the real effects of the strategies adopted on local fauna. Butterflies are sensitive to local changes and they can thus serve as indicators of environmental changes. Three different types of fire prevention management approaches in three different localities in the Eastern Pyrenees (France) were performed and the butterfly community composition was investigated. We show that of the 80 species of butterflies observed, 36 % can be considered as biological markers. An original objective treatment of data using hierarchical distance analysis combined with a neural network analysis (Self-Organizing Maps) was applied in this study. Our conclusions are that the overall number of species is maintained independently of the fire prevention type but that some important changes are observed among butterfly communities, with a clear reduction of the numbers of endemic/specialized species in favour of generalist ones for the two most drastic fire prevention management approaches studied here. The influence of such approaches is discussed on the basis of the conservation of Mediterranean species of Lepidoptera

Improving Long-Term Online Prediction with Decoupled Extended Kalman Filters

Long short-term memory (LSTM) recurrent neural networks (RNNs) outperform traditional RNNs when dealing with sequences involving not only short-term but also long-term dependencies. The decoupled extended Kalman filter learning algorithm (DEKF) works well in online environments and reduces significantly the number of training steps when compared to the standard gradient-descent algorithms