Energy and energy flux in axisymmetric slow and fast waves

Aims: We aim to calculate the kinetic, magnetic, thermal, and total energy densities and the flux of energy in axisymmetric sausage modes. The resulting equations should contain as few parameters as possible to facilitate applicability for different observations. 

Methods: The background equilibrium is a one-dimensional cylindrical flux tube model with a piecewise constant radial density profile. This enables us to use linearised magnetohydrodynamic equations to calculate the energy densities and the flux of energy for axisymmetric sausage modes. 

Results: The equations used to calculate the energy densities and the flux of energy in axisymmetric sausage modes depend on the radius of the flux tube, the equilibrium sound and Alfvén speeds, the density of the plasma, the period and phase speed of the wave, and the radial or longitudinal components of the Lagrangian displacement at the flux tube boundary. Approximate relations for limiting cases of propagating slow and fast sausage modes are also obtained. We also obtained the dispersive first-order correction term to the phase speed for both the fundamental slow body mode under coronal conditions and the slow surface mode under photospheric conditions.

Aristarchos RISE2: A Wide-Field Fast Imager for Exoplanet Transit Timing

The detection of exoplanets is currently of great topical interest in astronomy. The Rapid Imager for Surveys of Exoplanets 2 (RISE2) camera will be built for exoplanet studies and in particular for detection of transit timing variations (TTV) induced by the presence of a third body in the system. It will be identical to RISE which has been running successfully on the 2m Liverpool Telescope since 2008 but modified for the 2.3m ARISTARCHOS telescope. For TTV work the RISE/LT combination is regularly producing timings with accuracy <10 seconds making it the best suited instrument for this work. Furthermore, RISE2/AT has the added benefit of being located at a significantly different longitude to the LT/RISE on La Palma, hence extending the transit coverage.

PS1-10bzj: A Fast, Hydrogen-poor Superluminous Supernova in a Metal-poor Host Galaxy

We present observations and analysis of PS1-10bzj, a superluminous supernova (SLSN) discovered in the Pan-STARRS Medium Deep Survey at a redshift z = 0.650. Spectroscopically, PS1-10bzj is similar to the hydrogen-poor SLSNe 2005ap and SCP 06F6, though with a steeper rise and lower peak luminosity (M bol ~= -21.4 mag) than previous events. We construct a bolometric light curve, and show that while PS1-10bzj's energetics were less extreme than previous events, its luminosity still cannot be explained by radioactive nickel decay alone. We explore both a magnetar spin-down and circumstellar interaction scenario and find that either can fit the data. PS1-10bzj is located in the Extended Chandra Deep Field South and the host galaxy is imaged in a number of surveys, including with the Hubble Space Telescope. The host is a compact dwarf galaxy (MB ≈ -18 mag, diameter

Temporal Narrowing of Neutrons Produced by High-Intensity Short-Pulse Lasers

The production of neutron beams having short temporal duration is studied using ultraintense laser pulses. Laser-accelerated protons are spectrally filtered using a laser-triggered microlens to produce a short duration neutron pulse via nuclear reactions induced in a converter material (LiF). This produces a similar to 3 ns duration neutron pulse with 10(4) n/MeV/sr/shot at 0.56 m from the laser-irradiated proton source. The large spatial separation between the neutron production and the proton source allows for shielding from the copious and undesirable radiation resulting from the laser-plasma interaction. This neutron pulse compares favorably to the duration of conventional accelerator sources and should scale up with, present and future, higher energy laser facilities to produce brighter and shorter neutron beams for ultrafast probing of dense materials.

Accounting for clean, fast and high yielding reactions under microwave conditions

Thermal reactions proceed optimally when they are rapidly heated to the highest tolerable temperature, held there for the shortest possible time and then quenched. This is explained through assessments of reaction kinetics in literature examples and models. Although presently available microwave equipment is better suited to rapid heating than resistance-heated systems, the findings do not depend upon the method of heating. Claims that microwave heated reactions proceed faster and more cleanly than their conventionally heated counterparts are valid only when comparably rapid heating and cooling cannot be obtained by conventional heating. These findings suggest that rigid adherence to the sixth principle of green chemistry, relating to the use of ambient temperature and pressure, may not always afford optimal results. © 2010 The Royal Society of Chemistry.

Fast Byzantine Leader Election in Dynamic Networks

We study the fundamental Byzantine leader election problem in dynamic networks where the topology can change from round to round and nodes can also experience heavy {\em churn} (i.e., nodes can join and leave the network continuously over time). We assume the full information model where the Byzantine nodes have complete knowledge about the entire state of the network at every round (including random choices made by all the nodes), have unbounded computational power and can deviate arbitrarily from the protocol. The churn is controlled by an adversary that has complete knowledge and control over which nodes join and leave and at what times and also may rewire the topology in every round and has unlimited computational power, but is oblivious to the random choices made by the algorithm. Our main contribution is an $O(\log^3 n)$ round algorithm that achieves Byzantine leader election under the presence of up to $O({n}^{1/2 - \epsilon})$ Byzantine nodes (for a small constant $\epsilon > 0$) and a churn of up to \\$O(\sqrt{n}/\poly\log(n))$ nodes per round (where $n$ is the stable network size).The algorithm elects a leader with probability at least $1-n^{-\Omega(1)}$ and guarantees that it is an honest node with probability at least $1-n^{-\Omega(1)}$; assuming the algorithm succeeds, the leader's identity will be known to a $1-o(1)$ fraction of the honest nodes. Our algorithm is fully-distributed, lightweight, and is simple to implement. It is also scalable, as it runs in polylogarithmic (in $n$) time and requires nodes to send and receive messages of only polylogarithmic size per round.To the best of our knowledge, our algorithm is the first scalable solution for Byzantine leader election in a dynamic network with a high rate of churn; our protocol can also be used to solve Byzantine agreement in a straightforward way.We also show how to implement an (almost-everywhere) public coin with constant bias in a dynamic network with Byzantine nodes and provide a mechanism for enabling honest nodes to store information reliably in the network, which might be of independent interest.

A Fast Algorithm for Sparse Support Vector Machines for Mobile Computing Applications

This research presents a fast algorithm for projected support vector machines (PSVM) by selecting a basis vector set (BVS) for the kernel-induced feature space, the training points are projected onto the subspace spanned by the selected BVS. A standard linear support vector machine (SVM) is then produced in the subspace with the projected training points. As the dimension of the subspace is determined by the size of the selected basis vector set, the size of the produced SVM expansion can be specified. A two-stage algorithm is derived which selects and refines the basis vector set achieving a locally optimal model. The model expansion coefficients and bias are updated recursively for increase and decrease in the basis set and support vector set. The condition for a point to be classed as outside the current basis vector and selected as a new basis vector is derived and embedded in the recursive procedure. This guarantees the linear independence of the produced basis set. The proposed algorithm is tested and compared with an existing sparse primal SVM (SpSVM) and a standard SVM (LibSVM) on seven public benchmark classification problems. Our new algorithm is designed for use in the application area of human activity recognition using smart devices and embedded sensors where their sometimes limited memory and processing resources must be exploited to the full and the more robust and accurate the classification the more satisfied the user. Experimental results demonstrate the effectiveness and efficiency of the proposed algorithm. This work builds upon a previously published algorithm specifically created for activity recognition within mobile applications for the EU Haptimap project [1]. The algorithms detailed in this paper are more memory and resource efficient making them suitable for use with bigger data sets and more easily trained SVMs.

Fast Rule Mining over Multi-dimensional Windows

Association rule mining is an indispensable tool for discovering
insights from large databases and data warehouses.
The data in a warehouse being multi-dimensional, it is often
useful to mine rules over subsets of data defined by selections
over the dimensions. Such interactive rule mining
over multi-dimensional query windows is difficult since rule
mining is computationally expensive. Current methods using
pre-computation of frequent itemsets require counting
of some itemsets by revisiting the transaction database at
query time, which is very expensive. We develop a method
(RMW) that identifies the minimal set of itemsets to compute
and store for each cell, so that rule mining over any
query window may be performed without going back to the
transaction database. We give formal proofs that the set of
itemsets chosen by RMW is sufficient to answer any query
and also prove that it is the optimal set to be computed
for 1 dimensional queries. We demonstrate through an extensive
empirical evaluation that RMW achieves extremely
fast query response time compared to existing methods, with
only moderate overhead in pre-computation and storage

Fast Mining of Interesting Phrases from Subsets of Text Corpora

We address the problem of mining interesting phrases from subsets of a text corpus where the subset is specified using a set of features such as keywords that form a query. Previous algorithms for the problem have proposed solutions that involve sifting through a phrase dictionary based index or a document-based index where the solution is linear in either the phrase dictionary size or the size of the document subset. We propose the usage of an independence assumption between query keywords given the top correlated phrases, wherein the pre-processing could be reduced to discovering phrases from among the top phrases per each feature in the query. We then outline an indexing mechanism where per-keyword phrase lists are stored either in disk or memory, so that popular aggregation algorithms such as No Random Access and Sort-merge Join may be adapted to do the scoring at real-time to identify the top interesting phrases. Though such an approach is expected to be approximate, we empirically illustrate that very high accuracies (of over 90%) are achieved against the results of exact algorithms. Due to the simplified list-aggregation, we are also able to provide response times that are orders of magnitude better than state-of-the-art algorithms. Interestingly, our disk-based approach outperforms the in-memory baselines by up to hundred times and sometimes more, confirming the superiority of the proposed method.

A Fast Analysis Method for the Groove Gap Waveguide Using Transmission Line Theory

The Groove Gap Waveguide (GGW) shows a behavior similar to the classical rectangular waveguide (RWG), but it is formed by two pieces which do not require metal contact. This feature suggests the GGW as a suitable alternative to the RGW for mm-wave frequencies, where ensuring the proper metal contact according to the wavelength size results challenging. Nevertheless, there is a lack of effective analysis tools for the complex GGW topology, and assuming a direct equivalence between the RGW and the GGW is too rough, so that dilatory full-wave simulations are required. This work presents a fast analysis method based on transmission line theory, which establishes the proper correspondence between the GGW and the RWG. In addition, below cutoff behavior of the GGW is studied for the first time. Several numerical tests and two manufactured prototypes validate the proposed method, which seems very adequate to optimize future GGW structures.

Fast response to human voices in autism

Individuals with autism spectrum disorders (ASD) are reported to allocate less spontaneous attention to voices. Here, we investigated how vocal sounds are processed in ASD adults, when those sounds are attended. Participants were asked to react as fast as possible to target stimuli (either voices or strings) while ignoring distracting stimuli. Response times (RTs) were measured. Results showed that, similar to neurotypical (NT) adults, ASD adults were faster to recognize voices compared to strings. Surprisingly, ASD adults had even shorter RTs for voices than the NT adults, suggesting a faster voice recognition process. To investigate the acoustic underpinnings of this effect, we created auditory chimeras that retained only the temporal or the spectral features of voices. For the NT group, no RT advantage was found for the chimeras compared to strings: both sets of features had to be present to observe an RT advantage. However, for the ASD group, shorter RTs were observed for both chimeras. These observations indicate that the previously observed attentional deficit to voices in ASD individuals could be due to a failure to combine acoustic features, even though such features may be well represented at a sensory level.

Magnetic collimation of petawatt driven fast electron beam for prospective fast ignition studies

Collimated transport of fast electron beam through solid density matter is one of the key issues behind the success of the fast ignition scheme by means of which the required amount of ignition energy can be delivered to the hot spot region of the compressed fuel. Here we report on a hot electron beam collimation scheme in solids by tactfully using the strong magnetic fields generated by an electrical resistivity gradient according to Faraday's law. This was accomplished by appropriately fabricating the targets in such a way that the electron beam is directed to flow in a metal which is embedded in a much lower resistivity and atomic number metal. Experimental results showed guided transport of hot electron beam over hundreds of microns length inside solid density plasma, which were obtained from two experiments examining the scheme for petawatt laser driven hot electron beam while employing various target configurations.