4,228 research outputs found
In Support of Tolerated Use: Rethinking Harms, Moral Rights and Remedies in Australian Copyright Law
In this article, we propose a thought experiment: what if copyright law could better incorporate social and cultural norms around content engagement and re-use? We draw on empirical research that explores the norms of different creative communities when they re- use the work of others, and the norms of consumers around sharing. We outline how both creators and copyright users engage almost daily in small-scale infringement that does not substitute or disrupt copyright owners’ established markets, either because the uses are highly transformative, or personal and unremarkable. We suggest that copyright could better reflect these norms if both norms and moral rights were considered as part of a remedies assessment. We propose that in cases where work has been attributed and treated with integrity, and where the use does not directly cause economic harm to the copyright owner, courts should award only nominal damages and decline to order injunctive relief
Tools for Optimization of Biomass-to-Energy Conversion Processes
Biomasses are renewable sources used in energy conversion processes to obtain diverse products through different technologies. The production chain, which involves delivery, logistics, pre-treatment, storage and conversion as general components, can be costly and uncertain due to inherent variability. Optimization methods are widely applied for modeling the biomass supply chain (BSC) for energy processes. In this qualitative review, the main aspects and global trends of using geographic information systems (GISs), linear programming (LP) and neural networks to optimize the BSC are presented. Modeling objectives and factors considered in studies published in the last 25 years are reviewed, enabling a broad overview of the BSC to support decisions at strategic, tactical and operational levels. Combined techniques have been used for different purposes: GISs for spatial analyses of biomass; neural networks for higher heating value (HHV) correlations; and linear programming and its variations for achieving objectives in general, such as costs and emissions reduction. This study reinforces the progress evidenced in the literature and envisions the increasing inclusion of socio-environmental criteria as a challenge in future modeling efforts
The Herschel Virgo Cluster Survey XVI: a cluster inventory
Herschel FIR observations are used to construct Virgo cluster galaxy
luminosity functions and to show that the cluster lacks the very bright and the
numerous faint sources detected in field galaxy surveys. The far-infrared SEDs
are fitted to obtain dust masses and temperatures and the dust mass function.
The cluster is over dense in dust by about a factor of 100 compared to the
field. The same emissivity (beta) temperature relation applies for different
galaxies as that found for different regions of M31. We use optical and HI data
to show that Virgo is over dense in stars and atomic gas by about a factor of
100 and 20 respectively. Metallicity values are used to measure the mass of
metals in the gas phase. The mean metallicity is about 0.7 solar and 50% of the
metals are in the dust. For the cluster as a whole the mass density of stars in
galaxies is 8 times that of the gas and the gas mass density is 130 times that
of the metals. We use our data to consider the chemical evolution of the
individual galaxies, inferring that the measured variations in effective yield
are due to galaxies having different ages, being affected to varying degrees by
gas loss. Four galaxy scaling relations are considered: mass-metallicity,
mass-velocity, mass-star formation rate and mass-radius - we suggest that
initial galaxy mass is the prime driver of a galaxy's ultimate destiny.
Finally, we use X-ray observations and galaxy dynamics to assess the dark and
baryonic matter content compared to the cosmological model
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Feasibility study and design concept for an orbiting ice-penetrating radar sounder to characterize in three-dimensions the Europan ice mantle down to (and including) any ice/ocean interface
This report presents a radar sounding model based on the range of current working hypotheses for the nature of Europa's icy shell.Institute for Geophysic
Combination of XANES spectroscopy and molecular dynamics to probe the local structure in disordered systems
Individual configurations obtained from molecular dynamics have been combined with the computation of x-ray absorption near-edge structure (XANES) spectra to obtain a theoretical estimation of the spectrum corresponding to a system in a condensed medium lacking long-range order. The influence of the different geometries on the spectrum is studied. The results obtained indicate that the reproduction of the features of the XANES spectrum requires a good sampling of geometrical arrangements. As a test case, an aqueous solution of Cr(H2O)6 3+ was selected, since its simulation reproduces well structural results. The contribution of the second hydration shell on the shape of the spectrum was determined.Dirección General de Investigación Científica y Técnica IFD97-118
Ram-pressure stripped molecular gas in the Virgo spiral galaxy NGC 4522
IRAM 30m 12CO(1-0) and 12CO(2-1) HERA observations are presented for the
ram-pressure stripped Virgo spiral galaxy NGC 4522. The CO emission is detected
in the galactic disk and the extraplanar gas. The extraplanar CO emission
follows the morphology of the atomic gas closely but is less extended. The CO
maxima do not appear to correspond to regions where there is peak massive star
formation as probed by Halpha emission. The presence of molecular gas is a
necessary but not sufficient condition for star formation. Compared to the disk
gas, the molecular fraction of the extraplanar gas is 30% lower and the star
formation efficiency of the extraplanar gas is about 3 times lower. The
comparison with an existing dynamical model extended by a recipe for
distinguishing between atomic and molecular gas shows that a significant part
of the gas is stripped in the form of overdense arm-like structures. It is
argued that the molecular fraction depends on the square root of the total
large-scale density. Based on the combination of the CO/Halpha and an
analytical model, the total gas density is estimated to be about 4 times lower
than that of the galactic disk. Molecules and stars form within this dense gas
according to the same laws as in the galactic disk, i.e. they mainly depend on
the total large-scale gas density. Star formation proceeds where the local
large-scale gas density is highest. Given the complex 3D morphology this does
not correspond to the peaks in the surface density. In the absence of a
confining gravitational potential, the stripped gas arms will most probably
disperse; i.e. the density of the gas will decrease and star formation will
cease.Comment: 11 pages, 15 figures, A&A accepted for publicatio
The identification of dust heating mechanisms in nearby galaxies using Herschel 160/250 and 250/350 micron surface brightness ratios
We examined variations in the 160/250 and 250/350 micron surface brightness
ratios within 24 nearby (<30 Mpc) face-on spiral galaxies observed with the
Herschel Space Observatory to identify the heating mechanisms for dust emitting
at these wavelengths. The analysis consisted of both qualitative and
quantitative comparisons of the 160/250 and 250/350 micron ratios to H alpha
and 24 micron surface brightnesses, which trace the light from star forming
regions, and 3.6 micron emission, which traces the light from the older stellar
populations of the galaxies. We find broad variations in the heating mechanisms
for the dust. In one subset of galaxies, we found evidence that emission at
<=160 microns (and in rare cases potentially at <=350 microns) originates from
dust heated by star forming regions. In another subset, we found that the
emission at >=250 microns (and sometimes at >=160 microns) originates from dust
heated by the older stellar population. In the rest of the sample, either the
results are indeterminate or both of these stellar populations may contribute
equally to the global dust heating. The observed variations in dust heating
mechanisms does not necessarily match what has been predicted by dust emission
and radiative transfer models, which could lead to overestimated dust
temperatures, underestimated dust masses, false detections of variability in
dust emissivity, and inaccurate star formation rate measurements.Comment: Accepted for publication in MNRA
Molecular-dynamics-based investigation of scattering path contributions to the EXAFS spectrum: The Cr3¿ aqueous solution case
Extended x-ray absorption fine structure spectra were computed based on molecular-dynamics (MD) struc- tural data of a [ Cr(H2O)6 ]3+ aqueous solution using nonempirical cation-water potentials. An excellent re- production of the experimental spectrum was achieved. A simple estimation of Debye-Waller factors of the multiple-scattering paths is deduced from MD simulations. The influence of the single-scattering path due to the second hydration shell as compared with the multiple-scattering paths within the first hydration shell allows a reasonable determination of the second hydration shell distance R(Cr-OII) within 0.1 Å
Ps and Qs: Quantization-aware pruning for efficient low latency neural network inference
Efficient machine learning implementations optimized for inference in
hardware have wide-ranging benefits, depending on the application, from lower
inference latency to higher data throughput and reduced energy consumption. Two
popular techniques for reducing computation in neural networks are pruning,
removing insignificant synapses, and quantization, reducing the precision of
the calculations. In this work, we explore the interplay between pruning and
quantization during the training of neural networks for ultra low latency
applications targeting high energy physics use cases. Techniques developed for
this study have potential applications across many other domains. We study
various configurations of pruning during quantization-aware training, which we
term quantization-aware pruning, and the effect of techniques like
regularization, batch normalization, and different pruning schemes on
performance, computational complexity, and information content metrics. We find
that quantization-aware pruning yields more computationally efficient models
than either pruning or quantization alone for our task. Further,
quantization-aware pruning typically performs similar to or better in terms of
computational efficiency compared to other neural architecture search
techniques like Bayesian optimization. Surprisingly, while networks with
different training configurations can have similar performance for the
benchmark application, the information content in the network can vary
significantly, affecting its generalizability.Comment: 22 pages, 7 Figures, 1 Tabl
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