1,729 research outputs found
Thermoelectric power quantum oscillations in the ferromagnet UGe
We present thermoelectric power and resistivity measurements in the
ferromagnet UGe as a function of temperature and magnetic field. At low
temperature, huge quantum oscillations are observed in the thermoelectric power
as a function of the magnetic field applied along the axis. The frequencies
of the extreme orbits are determined and an analysis of the cyclotron masses is
performed following different theoretical approaches for quantum oscillations
detected in the thermoelectric power. They are compared to those obtained by
Shubnikov-de Haas experiments on the same crystal and previous de Haas-van
Alphen experiments. The agreement of the different probes confirms
thermoelectric power as an excellent probe to extract simultaneously both
microscopic and macroscopic information on the Fermi-surface properties.
Band-structure calculations of UGe in the ferromagnetic state are compared
to the experiment.Comment: 10 figures, 12 pages, accepted for publication in Phys. Rev.
Keyboards as a New Model of Computation
We introduce a new formalisation of language computation, called keyboards. We consider a set of atomic operations (writing a letter, erasing a letter, going to the right or to the left) and we define a keyboard as a set of finite sequences of such operations, called keys. The generated language is the set of words obtained by applying some non-empty sequence of those keys. Unlike classical models of computation, every key can be applied anytime. We define various classes of languages based on different sets of atomic operations, and compare their expressive powers. We also compare them to rational, context-free and context-sensitive languages. We obtain a strict hierarchy of classes, whose expressiveness is orthogonal to the one of the aforementioned classical models. We also study closure properties of those classes, as well as fundamental complexity problems on keyboards
Dissolved oxygen dynamics during a phytoplankton bloom in the Ross Sea polynya
The Ross Sea polynya is one of the most productive regions in the Southern Ocean. However, limited access and high spatio-temporal variability of physical and biological processes limit the use of conventional oceanographic methods to measure early season primary productivity. High-resolution observations from two Seagliders provide insights into the timing of a bloom in the southern Ross Sea polynya in December 2010. Changes in chlorophyll and oxygen concentrations are used to assess bloom dynamics. Using a ratio of dissolved oxygen to carbon, net primary production is estimated over the duration of the bloom showing a sensitive balance between net autotrophy and heterotrophy. The two gliders, observing spatially distinct regions during the same period, found net community production rates of -0.9±0.7 and 0.7±0.4 g C m-2 d-1. The difference highlights the spatial variability of biological processes and is probably caused by observing different stages of the bloom. The challenge of obtaining accurate primary productivity estimates highlights the need for increased observational efforts, particularly focusing on subsurface processes not resolved using surface or remote observations. Without an increased observational effort and the involvement of emerging technologies, it will not be possible to determine the seasonal trophic balance of the Ross Sea polynya and quantify the shelf's importance in carbon export
Short Flip Sequences to Untangle Segments in the Plane
A (multi)set of segments in the plane may form a TSP tour, a matching, a
tree, or any multigraph. If two segments cross, then we can reduce the total
length with the following flip operation. We remove a pair of crossing
segments, and insert a pair of non-crossing segments, while keeping the same
vertex degrees. The goal of this paper is to devise efficient strategies to
flip the segments in order to obtain crossing-free segments after a small
number of flips. Linear and near-linear bounds on the number of flips were only
known for segments with endpoints in convex position. We generalize these
results, proving linear and near-linear bounds for cases with endpoints that
are not in convex position. Our results are proved in a general setting that
applies to multiple problems, using multigraphs and the distinction between
removal and insertion choices when performing a flip.Comment: 19 pages, 10 figure
Neural NILM: Deep Neural Networks Applied to Energy Disaggregation
Energy disaggregation estimates appliance-by-appliance electricity
consumption from a single meter that measures the whole home's electricity
demand. Recently, deep neural networks have driven remarkable improvements in
classification performance in neighbouring machine learning fields such as
image classification and automatic speech recognition. In this paper, we adapt
three deep neural network architectures to energy disaggregation: 1) a form of
recurrent neural network called `long short-term memory' (LSTM); 2) denoising
autoencoders; and 3) a network which regresses the start time, end time and
average power demand of each appliance activation. We use seven metrics to test
the performance of these algorithms on real aggregate power data from five
appliances. Tests are performed against a house not seen during training and
against houses seen during training. We find that all three neural nets achieve
better F1 scores (averaged over all five appliances) than either combinatorial
optimisation or factorial hidden Markov models and that our neural net
algorithms generalise well to an unseen house.Comment: To appear in ACM BuildSys'15, November 4--5, 2015, Seou
Polarimetric variations of binary stars. III Periodic polarimetric variations of the Herbig Ae/Be star MWC 1080
We present polarimetric observations of a massive pre-main sequence
short-period binary star of the Herbig Ae/Be type, MWC 1080. The mean
polarization at 7660 A is 1.60% at 81.6 deg, or 0.6% at 139 deg if an estimate
of the interstellar polarization is subtracted. The intrinsic polarization
points to an asymmetric geometry of the circumstellar or circumbinary
environment while the 139 deg intrinsic position angle traces the axis of
symmetry of the system and is perpendicular to the position angle of the
outflow cavity. The polarization and its position angle are clearly variable,
at all wavelengths, and on time scales of hours, days, months, and years.
Stochastic variability is accompanied by periodic variations caused by the
orbital motion of the stars in their dusty environment. These periodic
polarimetric variations are the first phased-locked ones detected for a
pre-main sequence binary. The variations are not simply double-periodic (seen
twice per orbit) but include single-periodic (seen once per orbit) and
higher-order variations. The presence of single-periodic variations could be
due to non equal mass stars, the presence of dust grains, an asymmetric
configuration of the circumstellar or circumbinary material, or the
eccentricity of the orbit. MWC 1080 is an eclipsing binary with primary and
secondary eclipses occurring at phases 0.0 and 0.55. The signatures of the
eclipses are seen in the polarimetric observations.Comment: 30 pages, 8 figures, to be published in the Astronomical Journa
Recurrent Latent Variable Networks for Session-Based Recommendation
In this work, we attempt to ameliorate the impact of data sparsity in the
context of session-based recommendation. Specifically, we seek to devise a
machine learning mechanism capable of extracting subtle and complex underlying
temporal dynamics in the observed session data, so as to inform the
recommendation algorithm. To this end, we improve upon systems that utilize
deep learning techniques with recurrently connected units; we do so by adopting
concepts from the field of Bayesian statistics, namely variational inference.
Our proposed approach consists in treating the network recurrent units as
stochastic latent variables with a prior distribution imposed over them. On
this basis, we proceed to infer corresponding posteriors; these can be used for
prediction and recommendation generation, in a way that accounts for the
uncertainty in the available sparse training data. To allow for our approach to
easily scale to large real-world datasets, we perform inference under an
approximate amortized variational inference (AVI) setup, whereby the learned
posteriors are parameterized via (conventional) neural networks. We perform an
extensive experimental evaluation of our approach using challenging benchmark
datasets, and illustrate its superiority over existing state-of-the-art
techniques
New Candidate Interstellar Particle in Stardust IS Aerogel Collector: Analysis by STXM and Ptychography
The Stardust Interstellar Preliminary Examination (ISPE) reported in 2014 the discovery of 7 probable contemporary interstellar (IS) particles captured in Stardust IS Collector aerogel and foils. The ISPE reports represented work done over 6 years by more than 60 scientists and >30,000 volunteers, which emphasizes the challenge identifying and analyzing Stardust IS samples was far beyond the primary Stardust cometary collection. We present a new potentially interstellar particle resulting from a continuation of analyses of the IS aerogel collection
Spatial Analysis of Land Use by Cattle Herds in a Village of the Sudanese Zone in Senegal. Application for Grazing System Improvement
Spatial analysis of land use by cattle herds in the sub-humid area of Senegal is conducted through the utilisation of a Geographic Information System. This tool allows us to establish relationships between spatial practices, ruminant nutrition and performances. It gives leads to proposals for the improvement of the extensive ruminant feeding system
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