Contemporary take on Caesar a triumph of style over substance [Review]

AFTER a great deal of success with last year's "emo" adaptation of Hamlet, David Berthold begins La Boite Theatre Company's 2011 season, his second season at the helm, with an adaptation of Julius Caesar.

Applying ISOMAP to the learning of hyperspectral image

In this paper, we present the application of a non-linear dimensionality reduction technique for the learning and probabilistic classification of hyperspectral image. Hyperspectral image spectroscopy is an emerging technique for geological investigations from airborne or orbital sensors. It gives much greater information content per pixel on the image than a normal colour image. This should greatly help with the autonomous identification of natural and manmade objects in unfamiliar terrains for robotic vehicles. However, the large information content of such data makes interpretation of hyperspectral images time-consuming and userintensive. We propose the use of Isomap, a non-linear manifold learning technique combined with Expectation Maximisation in graphical probabilistic models for learning and classification. Isomap is used to find the underlying manifold of the training data. This low dimensional representation of the hyperspectral data facilitates the learning of a Gaussian Mixture Model representation, whose joint probability distributions can be calculated offline. The learnt model is then applied to the hyperspectral image at runtime and data classification can be performed.

An integrated approach to cryptographic mitigation of denial-of-service attacks

Gradual authentication is a principle proposed by Meadows as a way to tackle denial-of-service attacks on network protocols by gradually increasing the confidence in clients before the server commits resources. In this paper, we propose an efficient method that allows a defending server to authenticate its clients gradually with the help of some fast-to-verify measures. Our method integrates hash-based client puzzles along with a special class of digital signatures supporting fast verification. Our hash-based client puzzle provides finer granularity of difficulty and is proven secure in the puzzle difficulty model of Chen et al. (2009). We integrate this with the fast-verification digital signature scheme proposed by Bernstein (2000, 2008). These schemes can be up to 20 times faster for client authentication compared to RSA-based schemes. Our experimental results show that, in the Secure Sockets Layer (SSL) protocol, fast verification digital signatures can provide a 7% increase in connections per second compared to RSA signatures, and our integration of client puzzles with client authentication imposes no performance penalty on the server since puzzle verification is a part of signature verification.

The application of Raman spectroscopy to the study of the uranyl mineral coconinoite Fe2Al2(UO2)2(PO4)4(SO4)(OH)2•20H2O

Raman spectra of the uranyl containing mineral coconinoite, Fe2Al2(UO2)2(PO4)4(SO4)(OH)2•20H2O, are presented and compared with the mineral’s infrared spectra. Bands connected with (UO2)2+, (PO4)3- , (SO4)2-, (OH)- and H2O stretching and bending vibrations, are assigned. Approximate U-O bond lengths in uranyl, (UO2)2+, and O-H...O hydrogen bond lengths are calculated from the wavenumbers of the U-O stretching vibrations and (OH)- and H2O stretching vibrations, respectively, and compared with published data for similar natural and synthetic compounds.

How can soil monitoring networks be used to improve predictions of organic carbon pool dynamics and CO2 fluxes in agricultural soils?

Abstract As regional and continental carbon balances of terrestrial ecosystems become available, it becomes clear that the soils are the largest source of uncertainty. Repeated inventories of soil organic carbon (SOC) organized in soil monitoring networks (SMN) are being implemented in a number of countries. This paper reviews the concepts and design of SMNs in ten countries, and discusses the contribution of such networks to reducing the uncertainty of soil carbon balances. Some SMNs are designed to estimate country-specific land use or management effects on SOC stocks, while others collect soil carbon and ancillary data to provide a nationally consistent assessment of soil carbon condition across the major land-use/soil type combinations. The former use a single sampling campaign of paired sites, while for the latter both systematic (usually grid based) and stratified repeated sampling campaigns (5–10 years interval) are used with densities of one site per 10–1,040 km². For paired sites, multiple samples at each site are taken in order to allow statistical analysis, while for the single sites, composite samples are taken. In both cases, fixed depth increments together with samples for bulk density and stone content are recommended. Samples should be archived to allow for re-measurement purposes using updated techniques. Information on land management, and where possible, land use history should be systematically recorded for each site. A case study of the agricultural frontier in Brazil is presented in which land use effect factors are calculated in order to quantify the CO2 fluxes from national land use/management conversion matrices. Process-based SOC models can be run for the individual points of the SMN, provided detailed land management records are available. These studies are still rare, as most SMNs have been implemented recently or are in progress. Examples from the USA and Belgium show that uncertainties in SOC change range from 1.6–6.5 Mg C ha−1 for the prediction of SOC stock changes on individual sites to 11.72 Mg C ha−1 or 34% of the median SOC change for soil/land use/climate units. For national SOC monitoring, stratified sampling sites appears to be the most straightforward attribution of SOC values to units with similar soil/land use/climate conditions (i.e. a spatially implicit upscaling approach). Keywords Soil monitoring networks - Soil organic carbon - Modeling - Sampling design

Regular exercise participation mediates the affective response to acute bouts of vigorous exercise

Physical inactivity is a leading factor associated with cardiovascular disease and a major contributor to the global burden of disease in developed countries. Subjective mood states associated with acute exercise are likely to influence future exercise adherence and warrant further investigation. The present study examined the effects of a single bout of vigorous exercise on mood and anxiety between individuals with substantially different exercise participation histories. Mood and anxiety were assessed one day before an exercise test (baseline), 5 minutes before (pre-test) and again 10 and 25 minutes post-exercise. Participants were 31 university students (16 males, 15 females; Age M = 20), with 16 participants reporting a history of regular exercise with the remaining 15 reporting to not exercise regularly. Each participant completed an incremental exercise test on a Monark cycle ergometer to volitional exhaustion. Regular exercisers reported significant post-exercise improvements in mood and reductions in state anxiety. By contrast, non-regular exercisers reported an initial decline in post-exercise mood and increased anxiety, followed by an improvement in mood and reduction in anxiety back to pre-exercise levels. Our findings suggest that previous exercise participation mediates affective responses to acute bouts of vigorous exercise. We suggest that to maximise positive mood changes following exercise, practitioners should carefully consider the individual’s exercise participation history before prescribing new regimes.

Available evidence does not support routine administration of antipyretics to reduce duration of fever or illness

Commentary on : Carey JV. Literature review : should antipyretic therapies routinely be administered to patients with [corrected] fever? J Clin Nurs 2010;19:2377–93.