Dynamic control of laser driven proton beams by exploiting self-generated, ultrashort electromagnetic pulses

As part of the ultrafast charge dynamics initiated by high intensity laser irradiations of solid targets,high amplitude EM pulses propagate away from the interaction point and are transported along anystalks and wires attached to the target. The propagation of these high amplitude pulses along a thinwire connected to a laser irradiated target was diagnosed via the proton radiography technique,measuring a pulse duration of 20 ps and a pulse velocity close to the speed of light. The strongelectric field associated with the EM pulse can be exploited for controlling dynamically the protonbeams produced from a laser-driven source. Chromatic divergence control of broadband laser drivenprotons (upto 75% reduction in divergence of >5 MeV protons) was obtained by winding the supportingwire around the proton beam axis to create a helical coil structure. In addition to providingfocussing and energy selection, the technique has the potential to post-accelerate the transiting protonsby the longitudinal component of the curved electric field lines produced by the helical coil lens.

Relativistic electron mirrors from nanoscale foils for coherent frequency upshift to the extreme ultraviolet

Reflecting light from a mirror moving close to the speed of light has been envisioned as a route towards producing bright X-ray pulses since Einstein's seminal work on special relativity. For an ideal relativistic mirror, the peak power of the reflected radiation can substantially exceed that of the incident radiation due to the increase in photon energy and accompanying temporal compression. Here we demonstrate for the first time that dense relativistic electron mirrors can be created from the interaction of a high-intensity laser pulse with a freestanding, nanometre-scale thin foil. The mirror structures are shown to shift the frequency of a counter-propagating laser pulse coherently from the infrared to the extreme ultraviolet with an efficiency >10 4 times higher than in the case of incoherent scattering. Our results elucidate the reflection process of laser-generated electron mirrors and give clear guidance for future developments of a relativistic mirror structure. 

Applications of statistical models in proportioning medium strength self-compacting concrete

Self-compacting concrete (SCC) is generally designed with a relatively higher content of finer, which includes cement, and dosage of superplasticizer than the conventional concrete. The design of the current SCC leads to high compressive strength, which is already used in special applications, where the high cost of materials can be tolerated. Using SCC, which eliminates the need for vibration, leads to increased speed of casting and thus reduces labour requirement, energy consumption, construction time, and cost of equipment. In order to obtain and gain maximum benefit from SCC it has to be used for wider applications. The cost of materials will be decreased by reducing the cement content and using a minimum amount of admixtures. This paper reviews statistical models obtained from a factorial design which was carried out to determine the influence of four key parameters on filling ability, passing ability, segregation and compressive strength. These parameters are important for the successful development of medium strength self-compacting concrete (MS-SCC). The parameters considered in the study were the contents of cement and pulverised fuel ash (PFA), water-to-powder ratio (W/P), and dosage of superplasticizer (SP). The responses of the derived statistical models are slump flow, fluidity loss, rheological parameters, Orimet time, V-funnel time, L-box, JRing combined to Orimet, JRing combined to cone, fresh segregation, and compressive strength at 7, 28 and 90 days. The models are valid for mixes made with 0.38 to 0.72 W/P ratio, 60 to 216 kg/m3 of cement content, 183 to 317 kg/m3 of PFA and 0 to 1% of SP, by mass of powder. The utility of such models to optimize concrete mixes to achieve good balance between filling ability, passing ability, segregation, compressive strength, and cost is discussed. Examples highlighting the usefulness of the models are presented using isoresponse surfaces to demonstrate single and coupled effects of mix parameters on slump flow, loss of fluidity, flow resistance, segregation, JRing combined to Orimet, and compressive strength at 7 and 28 days. Cost analysis is carried out to show trade-offs between cost of materials and specified consistency levels and compressive strength at 7 and 28 days that can be used to identify economic mixes. The paper establishes the usefulness of the mathematical models as a tool to facilitate the test protocol required to optimise medium strength SCC.

The WASP project in the era of robotic telescope networks

We present the current status of the WASP project, a pair of wide angle photometric telescopes, individually called SuperWASP. SuperWASP-I is located in La Palma, and SuperWASP-II at Sutherland in South Africa. SW-I began operations in April 2004. SW-II is expected to be operational in early 2006. Each SuperWASP instrument consists of up to 8 individual cameras using ultra-wide field lenses backed by high-quality passively cooled CCDs. Each camera covers 7.8 x 7.8 sq degrees of sky, for nearly 500 sq degrees of total sky coverage. One of the current aims of the WASP project is the search for extra-solar planet transits with a focus on brighter stars in the magnitude range similar to 8 to 13. Additionally, WASP will search for, optical transients, track Near-Earth Objects, and study many types of variable stars and extragalactic objects. The collaboration has developed a custom-built reduction pipeline that achieves better than I percent photometric precision. We discuss future goals, which include: nightly on-mountain reductions that could be used to automatically drive alerts via a small robotic telescope network, and possible roles of the WASP telescopes as providers in such a network. Additional technical details of the telescopes, data reduction, and consortium members and institutions can be found on the web site at: http://www.superwasp.org/. (c) 2006 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Synchronous Islanded Operation of a Diesel Generator

The amount of distributed generation connected to the distribution network is increasing. To use this resource more effectively, splitting of the distribution network, or islanding the system, for prevention of power outages is being considered by some utilities. In this paper an islanding method that avoids out-ofsynchronism re-closure is proposed. The island is kept in synchronism with the rest of the utility while it is not electrically connected. This is referred to as synchronous islanded operation. A phase difference control algorithm, developed by the authors, was tested in a single set scenario on a 50-kVA diesel generator using two different governors. These are the “standard product” variable gain governor of the diesel generator and a governor developed by the authors, which utilizes supplementary inputs in addition to engine speed. The results show that phase difference can be controlled within acceptable limits, both in steady state and after load disturbances are applied. The advantages of employing supplementary governor inputs are fully evaluated.

A new Jacobian matrix for optimal learning of single-layer neural networks

This paper investigates the learning of a wide class of single-hidden-layer feedforward neural networks (SLFNs) with two sets of adjustable parameters, i.e., the nonlinear parameters in the hidden nodes and the linear output weights. The main objective is to both speed up the convergence of second-order learning algorithms such as Levenberg-Marquardt (LM), as well as to improve the network performance. This is achieved here by reducing the dimension of the solution space and by introducing a new Jacobian matrix. Unlike conventional supervised learning methods which optimize these two sets of parameters simultaneously, the linear output weights are first converted into dependent parameters, thereby removing the need for their explicit computation. Consequently, the neural network (NN) learning is performed over a solution space of reduced dimension. A new Jacobian matrix is then proposed for use with the popular second-order learning methods in order to achieve a more accurate approximation of the cost function. The efficacy of the proposed method is shown through an analysis of the computational complexity and by presenting simulation results from four different examples.

Diffraction-limited performance and focusing of high harmonics from relativistic plasmas

When a pulse of light reflects from a mirror that is travelling close to the speed of light, Einstein's theory of relativity predicts that it will be up-shifted to a substantially higher frequency and compressed to a much shorter duration. This scenario is realized by the relativistically oscillating plasma surface generated by an ultraintense laser focused onto a solid target. Until now, it has been unclear whether the conditions necessary to exploit such phenomena can survive such an extreme interaction with increasing laser intensity. Here, we provide the first quantitative evidence to suggest that they can. We show that the occurrence of surface smoothing on the scale of the wavelength of the generated harmonics, and plasma denting of the irradiated surface, enables the production of high-quality X-ray beams focused down to the diffraction limit. These results improve the outlook for generating extreme X-ray fields, which could in principle extend to the Schwinger limit.

SHEPARD: Scheduling on heterogeneous platforms using application resource demands

Heterogeneous computing technologies, such as multi-core CPUs, GPUs and FPGAs can provide significant performance improvements. However, developing applications for these technologies often results in coupling applications to specific devices, typically through the use of proprietary tools. This paper presents SHEPARD, a compile time and run-time framework that decouples application development from the target platform and enables run-time allocation of tasks to heterogeneous computing devices. Through the use of special annotated functions, called managed tasks, SHEPARD approximates a task's performance on available devices, and coupled with the approximation of current device demand, decides which device can satisfy the task with the lowest overall execution time. Experiments using a task parallel application, based on an in-memory database, demonstrate the opportunity for automatic run-time task allocation to achieve speed-up over a static allocation to a single specific device. © 2014 IEEE.

POINT-AGAPE pixel lensing survey of M31 - Evidence for a MACHO contribution to galactic halos

The POINT-AGAPE collaboration is carrying out a search for gravitational microlensing toward M31 to reveal galactic dark matter in the form of MACHOs (Massive Astrophysical Compact Halo Objects) in the halos of the Milky Way and M31. A high-threshold analysis of 3 years of data yields 6 bright, short- duration microlensing events, which are confronted to a simulation of the observations and the analysis. The observed signal is much larger than expected from self lensing alone and we conclude, at the 95% confidence level, that at least 20% of the halo mass in the direction of M31 must be in the form of MACHOs if their average mass lies in the range 0.5-1 M-circle dot. This lower bound drops to 8% for MACHOs with masses similar to 0.01 M-circle dot. In addition, we discuss a likely binary microlensing candidate with caustic crossing. Its location, some 32' away from the centre of M31, supports our conclusion that we are detecting a MACHO signal in the direction of M31.

Classical novae from the POINT-AGAPE microlensing survey of M31 - I. The nova catalogue

The POINT-AGAPE (Pixel-lensing Observations with the Isaac Newton Telescope-Andromeda Galaxy Amplified Pixels Experiment) survey is an optical search for gravitational microlensing events towards the Andromeda galaxy (M31). As well as microlensing, the survey is sensitive to many different classes of variable stars and transients. Here we describe the automated detection and selection pipeline used to identify M31 classical novae (CNe) and we present the resulting catalogue of 20 CN candidates observed over three seasons. CNe are observed both in the bulge region as well as over a wide area of the M31 disc. Nine of the CNe are caught during the final rise phase and all are well sampled in at least two colours. The excellent light-curve coverage has allowed us to detect and classify CNe over a wide range of speed class, from very fast to very slow. Among the light curves is a moderately fast CN exhibiting entry into a deep transition minimum, followed by its final decline. We have also observed in detail a very slow CN which faded by only 0.01 mag d(-1) over a 150-d period. We detect other interesting variable objects, including one of the longest period and most luminous Mira variables. The CN catalogue constitutes a uniquely well-sampled and objectively-selected data set with which to study the statistical properties of CNe in M31, such as the global nova rate, the reliability of novae as standard-candle distance indicators and the dependence of the nova population on stellar environment. The findings of this statistical study will be reported in a follow-up paper.

The POINT-AGAPE survey: 4 high signal-to-noise microlensing candidates detected towards M 31

We have carried out a survey of the Andromeda galaxy for unresolved microlensing (pixel lensing). We present a subset of four short timescale, high signal-to-noise microlensing candidates found by imposing severe selection criteria: the source flux variation exceeds the flux of an R = 21 magnitude star and the full width at half maximum timescale is less than 25 days. Remarkably, in three out of four cases, we have been able to measure or strongly constrain the Einstein crossing time of the event. One event, which lies projected on the M 31 bulge, is almost certainly due to a stellar lens in the bulge of M 31. The other three candidates can be explained either by stars in M 31 and M 32 or by MACHOs.

The mend of the bend-flexor pollicis longus tendon has an additional pulley distal to its point of angulation

The tendon of flexor pollicis longus angulates at the trapezio-metacarpal joint level. The degree of angulation varies with extent of radial/ulnar deviation (Rack and Ross [1984] J. Physiol. 351:99–110). We report a fibrous pulley at this level that helps stabilize the tendon and facilitates its action. The morphology of the pulley is described. We believe that it has an important role to play in the unique function of the tendon facilitating the movement of the thumb perpendicular to the plane of the thumbnail. Clin. Anat. 21:427–432, 2008. © 2008 Wiley-Liss, Inc

Integrating Multiple Point Statistics with Aerial Geophysical Data to assist Groundwater Flow Models

The process of accounting for heterogeneity has made significant advances in statistical research, primarily in the framework of stochastic analysis and the development of multiple-point statistics (MPS). Among MPS techniques, the direct sampling (DS) method is tested to determine its ability to delineate heterogeneity from aerial magnetics data in a regional sandstone aquifer intruded by low-permeability volcanic dykes in Northern Ireland, UK. The use of two two-dimensional bivariate training images aids in creating spatial probability distributions of heterogeneities of hydrogeological interest, despite relatively ‘noisy’ magnetics data (i.e. including hydrogeologically irrelevant urban noise and regional geologic effects). These distributions are incorporated into a hierarchy system where previously published density function and upscaling methods are applied to derive regional distributions of equivalent hydraulic conductivity tensor K. Several K models, as determined by several stochastic realisations of MPS dyke locations, are computed within groundwater flow models and evaluated by comparing modelled heads with field observations. Results show a significant improvement in model calibration when compared to a simplistic homogeneous and isotropic aquifer model that does not account for the dyke occurrence evidenced by airborne magnetic data. The best model is obtained when normal and reverse polarity dykes are computed separately within MPS simulations and when a probability threshold of 0.7 is applied. The presented stochastic approach also provides improvement when compared to a previously published deterministic anisotropic model based on the unprocessed (i.e. noisy) airborne magnetics. This demonstrates the potential of coupling MPS to airborne geophysical data for regional groundwater modelling.