The superluminous supernova PS1-11ap: bridging the gap between low and high redshift

We present optical photometric and spectroscopic coverage of the superluminous supernova (SLSN) PS1-11ap, discovered with the Pan-STARRS1 Medium Deep Survey at z = 0.524. This intrinsically blue transient rose slowly to reach a peak magnitude of Mu = −21.4 mag and bolometric luminosity of 8 × 1043 erg s−1 before settling on to a relatively shallow gradient of decline. The observed decline is significantly slower than those of the SLSNe-Ic which have been the focus of much recent attention. Spectroscopic similarities with the lower redshift SN2007bi and a decline rate similar to 56Co decay time-scale initially indicated that this transient could be a candidate for a pair instability supernova (PISN) explosion. Overall the transient appears quite similar to SN2007bi and the lower redshift object PTF12dam. The extensive data set, from 30 d before peak to 230 d after, allows a detailed and quantitative comparison with published models of PISN explosions. We find that the PS1-11ap data do not match these model explosion parameters well, supporting the recent claim that these SNe are not pair instability explosions. We show that PS1-11ap has many features in common with the faster declining SLSNe-Ic, and the light-curve evolution can also be quantitatively explained by the magnetar spin-down model. At a redshift of z = 0.524, the observer-frame optical coverage provides comprehensive rest-frame UV data and allows us to compare it with the SLSNe recently found at high redshifts between z = 2 and 4. While these high-z explosions are still plausible PISN candidates, they match the photometric evolution of PS1-11ap and hence could be counterparts to this lower redshift transient.

Implementation of phantom-less IMRT delivery verification using Varian DynaLog files and R/V output

This study aims to evaluate the use of Varian radiotherapy dynamic treatment log (DynaLog) files to verify IMRT plan delivery as part of a routine quality assurance procedure. Delivery accuracy in terms of machine performance was quantified by multileaf collimator (MLC) position errors and fluence delivery accuracy for patients receiving intensity modulated radiation therapy (IMRT) treatment. The relationship between machine performance and plan complexity, quantified by the modulation complexity score (MCS) was also investigated. Actual MLC positions and delivered fraction of monitor units (MU), recorded every 50 ms during IMRT delivery, were extracted from the DynaLog files. The planned MLC positions and fractional MU were taken from the record and verify system MLC control file. Planned and delivered beam data were compared to determine leaf position errors with and without the overshoot effect. Analysis was also performed on planned and actual fluence maps reconstructed from the MLC control file and delivered treatment log files respectively. This analysis was performed for all treatment fractions for 5 prostate, 5 prostate and pelvic node (PPN) and 5 head and neck (H&N) IMRT plans, totalling 82 IMRT fields in ∼5500 DynaLog files. The root mean square (RMS) leaf position errors without the overshoot effect were 0.09, 0.26, 0.19 mm for the prostate, PPN and H&N plans respectively, which increased to 0.30, 0.39 and 0.30 mm when the overshoot effect was considered. Average errors were not affected by the overshoot effect and were 0.05, 0.13 and 0.17 mm for prostate, PPN and H&N plans respectively. The percentage of pixels passing fluence map gamma analysis at 3%/3 mm was 99.94 ± 0.25%, which reduced to 91.62 ± 11.39% at 1%/1 mm criterion. Leaf position errors, but not gamma passing rate, were directly related to plan complexity as determined by the MCS. Site specific confidence intervals for average leaf position errors were set at -0.03-0.12 mm for prostate and -0.02-0.28 mm for more complex PPN and H&N plans. For all treatment sites confidence intervals for RMS errors with the overshoot was set at 0-0.50 mm and for the percentage of pixels passing a gamma analysis at 1%/1 mm a confidence interval of 68.83% was set also for all treatment sites. This work demonstrates the successful implementation of treatment log files to validate IMRT deliveries and how dynamic log files can diagnose delivery errors not possible with phantom based QC. Machine performance was found to be directly related to plan complexity but this is not the dominant determinant of delivery accuracy.

A multi-output two-stage locally regularized model construction method using the extreme learning machine

This paper investigates the construction of linear-in-the-parameters (LITP) models for multi-output regression problems. Most existing stepwise forward algorithms choose the regressor terms one by one, each time maximizing the model error reduction ratio. The drawback is that such procedures cannot guarantee a sparse model, especially under highly noisy learning conditions. The main objective of this paper is to improve the sparsity and generalization capability of a model for multi-output regression problems, while reducing the computational complexity. This is achieved by proposing a novel multi-output two-stage locally regularized model construction (MTLRMC) method using the extreme learning machine (ELM). In this new algorithm, the nonlinear parameters in each term, such as the width of the Gaussian function and the power of a polynomial term, are firstly determined by the ELM. An initial multi-output LITP model is then generated according to the termination criteria in the first stage. The significance of each selected regressor is checked and the insignificant ones are replaced at the second stage. The proposed method can produce an optimized compact model by using the regularized parameters. Further, to reduce the computational complexity, a proper regression context is used to allow fast implementation of the proposed method. Simulation results confirm the effectiveness of the proposed technique. © 2013 Elsevier B.V.

Filling the gap: A 60 ky record of mixed carbonate-siliciclastic turbidite deposition from the Great Barrier Reef

Late Pleistocene to Holocene margin sedimentation on the Great Barrier Reef, a mixed carbonatesiliciclastic margin, has been explained by a transgressive shedding model. This model has challenged widely accepted sequence stratigraphic models in terms of the timing and type of sediment (i.e. carbonate vs. siliciclastic) deposited during sea-level oscillations. However, this model documents only hemipelagic sedimentation and the contribution of coarse-grained turbidite deposition, and the role of submarine canyons in this process, remain elusive on this archetypal margin. Here we present a new model of turbidite deposition for the last 60 ky in the north-eastern Australia margin. Using highresolution bathymetry, 58 new and existing radiometric ages, and the composition of 81 turbidites from 15 piston cores, we found that the spatial and temporal variation of turbidites is controlled by the relationship between sea-level change and the variable physiography along the margin. Siliciclastic and mixed carbonate-siliciclastic turbidites were linked to canyons indenting the shelf-break and the welldeveloped shelf-edge reef barriers that stored sediment behind them. Turbidite deposition was sustained while the sea-level position allowed the connection and sediment bypassing through the interreef passages and canyons. Carbonate turbidites dominated in regions with more open conditions at the outer-shelf and where slope-confined canyons dominated or where canyons are generally less abundant. The turn-on and maintenance of carbonate production during sea-level fluctuations also influenced the timing of carbonate turbidite deposition. We show that a fundamental understanding of the variable physiography inherent to mixed carbonate-siliciclastic margins is essential to accurately interpret deep-water, coarse-grained deposition within a sequence stratigraphic context. 

Design methodology for low power and arametric robustness through output-quality modulation:Application to color-interpolation filtering

Power dissipation and robustness to process variation have conflicting design requirements. Scaling of voltage is associated with larger variations, while Vdd upscaling or transistor upsizing for parametric-delay variation tolerance can be detrimental for power dissipation. However, for a class of signal-processing systems, effective tradeoff can be achieved between Vdd scaling, variation tolerance, and output quality. In this paper, we develop a novel low-power variation-tolerant algorithm/architecture for color interpolation that allows a graceful degradation in the peak-signal-to-noise ratio (PSNR) under aggressive voltage scaling as well as extreme process variations. This feature is achieved by exploiting the fact that all computations used in interpolating the pixel values do not equally contribute to PSNR improvement. In the presence of Vdd scaling and process variations, the architecture ensures that only the less important computations are affected by delay failures. We also propose a different sliding-window size than the conventional one to improve interpolation performance by a factor of two with negligible overhead. Simulation results show that, even at a scaled voltage of 77% of nominal value, our design provides reasonable image PSNR with 40% power savings. © 2006 IEEE.

Design methodology to trade off power, output quality and error resiliency: Application to color interpolation filtering

Power dissipation and tolerance to process variations pose conflicting design requirements. Scaling of voltage is associated with larger variations, while Vdd upscaling or transistor up-sizing for process tolerance can be detrimental for power dissipation. However, for certain signal processing systems such as those used in color image processing, we noted that effective trade-offs can be achieved between Vdd scaling, process tolerance and "output quality". In this paper we demonstrate how these tradeoffs can be effectively utilized in the development of novel low-power variation tolerant architectures for color interpolation. The proposed architecture supports a graceful degradation in the PSNR (Peak Signal to Noise Ratio) under aggressive voltage scaling as well as extreme process variations in. sub-70nm technologies. This is achieved by exploiting the fact that some computations are more important and contribute more to the PSNR improvement compared to the others. The computations are mapped to the hardware in such a way that only the less important computations are affected by Vdd-scaling and process variations. Simulation results show that even at a scaled voltage of 60% of nominal Vdd value, our design provides reasonable image PSNR with 69% power savings.

DEPENDENCE OF LIGHT OUTPUT FROM NOMINALLY SMOOTH AL-OX-AU TUNNEL-JUNCTIONS ON ELECTRODE MORPHOLOGY

The light output from nominally smooth Al-Ox-Au tunnel junctions is observed to be substantially independent of the deposition rate of the Au film electrode. Films deposited quickly (2 nm s-1) and those deposited slowly (0.16 nm s-1) have similar spectral dependences and intensities. (This is in contrast to roughened films where those deposited quickly give out less light, especially towards the blue end of the spectrum.) The behaviour can be interpreted in terms of the ratio l(ph)/l(em) where l(ph) and l(em) are the mean free paths of surface plasmons between external photon emissions and internal electromagnetic absorptions respectively. Once l(ph)/l(em) exceeds 100, as it does on smooth films, grain size has little further effect on the spectral shape of the light output. In fast-deposited films there are two compensating effects on the output intensity: grain boundary scattering decreases it and greater surface roughness increases it.