Rate-dependent fracture toughness of polycrystalline ice

A series of three-point bend tests using single edge notched testpieces of pure polycrystalline ice have been performed at three different temperatures (–20°C, –30°C and –40°C). The displacement rate was varied from 1 mm/min to 100 mm/min, producing the crack tip strain rates from about 10–3 to 10–1 s–1. The results show that (a) the fracture toughness of pure polycrystalline ice given by the critical stress intensity factor (K IC) is much lower than that measured from the J—integral under identical conditions; (b) from the determination of K IC, the fracture toughness of pure polycrystalline ice decreases with increasing strain rate and there is good power law relationship between them; (c) from the measurement of the J—integral, a different tendency was appeared: when the crack tip strain rate exceeds a critical value of 6 × 10–3 s–1, the fracture toughness is almost constant but when the crack tip strain rate is less than this value, the fracture toughness increases with decreasing crack tip strain rate. Re-examination of the mechanisms of rate-dependent fracture toughness of pure polycrystalline ice shows that the effect of strain rate is related not only to the blunting of crack tips due to plasticity, creep and stress relaxation but also to the nucleation and growth of microcracks in the specimen.

Disorder and dissolution enhancement: Deposition of ibuprofen on to insoluble polymers

Microcrystalline cellulose (MCC) and cross-linked polyvinylpyrrolidone (PVP-CL) were examined as polymeric carriers to support amorphous ibuprofen (IB). Drug/cartier systems were prepared as physical mixes, and drug was loaded onto the polymers by hot mix and solvent deposition methods. The systems were examined using differential scanning calorimetry (DSC), X-ray powder diffractometry (XRD) and by dissolution testing. PVP-CL reduced drug crystallinity more than MCC and, surprisingly, even very simple mixing of ibuprofen with PVP-CL induced disordering of the drug. Increased ibuprofen dissolution rates were achieved with both polymers, in the order of solvent deposition > hot mixes > physical mixes. The increased dissolution rates could be attributed to a combination of faster dissolution from amorphous ibuprofen, microcrystalline drug deposition on carrier surfaces and polymer swelling. However, no clear relationship was observed between ibuprofen dissolution rates (using first order, Higuchi or Hixson-Crowell relationships) and drug crystallinity. (C) 2005 Elsevier B.V. All rights reserved.

Reduced heart rate responding to trauma reliving in trauma survivors with PTSD: correlates and consequences

The authors investigated whether heart rate (HR) responses to voluntary recall of trauma memories (a) are related to posttraumatic stress disorder (PTSD), and (b) predict recovery 6 months later. Sixty-two assault survivors completed a recall task modeled on imaginal reliving in the initial weeks postassault. Possible cognitive modulators of HR responsivity were assessed; dissociation, rumination, trauma memory disorganization. Individuals with PTSD showed a reduced HR response to reliving compared to those without PTSD, but reported greater distress. Notably, higher HR response but not self-reported distress during reliving predicted greater symptom reduction at follow-up in participants with PTSD. Engagement in rumination was the only cognitive factor that predicted lower HR response. The data are in contrast to studies using trauma reminders to trigger memories, which have found greater physiological reactivity in PTSD. The authors' observations are consistent with models of PTSD that highlight differences between cued or stimulus-driven retrieval and intentional trauma recall, and with E B. Foa and M.J. Kozak (1986) hypothesis that full activation of trauma memories facilitates emotional processing.

From base-rate to cumulative respect

The tendency to neglect base-rates in judgment under uncertainty may be "notorious," as Barbey & Sloman (B&S) suggest, but it is neither inevitable (as they document; see also Koehler 1996) nor unique. Here we would like to point out another line of evidence connecting ecological rationality to dual processes, the failure of individuals to appropriately judge cumulative probability.

An efficient low power FFT implementation for multiband full-rate ultra-wideband (UWB) receivers

This paper discusses the design, implementation and synthesis of an FFT module that has been specifically optimized for use in the OFDM based Multiband UWB system, although the work is generally applicable to many other OFDM based receiver systems. Previous work has detailed the requirements for the receiver FFT module within the Multiband UWB ODFM based system and this paper draws on those requirements coupled with modern digital architecture principles and low power design criteria to converge on our optimized solution. The FFT design obtained in this paper is also applicable for implementation of the transmitter IFFT module therefore only needing one FFT module for half-duplex operation. The results from this paper enable the baseband designers of the 200Mbit/sec variant of Multiband UWB systems (and indeed other OFDM based receivers) using System-on-Chip (SoC), FPGA and ASIC technology to create cost effective and low power solutions biased toward the competitive consumer electronics market.

Soft-bit and numerical precision requirements on multiband full-rate ultra-wideband (UWB) receivers

This paper discusses the architectural design, implementation and associated simulated peformance results of a possible receiver solution fir a multiband Ultra-Wideband (UWB) receiver. The paper concentrates on the tradeoff between the soft-bit width and numerical precision requirements for the receiver versus performance. The required numerical precision results obtained in this paper can be used by baseband designers of cost effective UWB systems using Systein-on-Chip (SoC), FPGA and ASIC technology solutions biased toward the competitive consumer electronics market(1).

Increasing detection rate of user-to-root attacks using genetic algorithms

An extensive set of machine learning and pattern classification techniques trained and tested on KDD dataset failed in detecting most of the user-to-root attacks. This paper aims to provide an approach for mitigating negative aspects of the mentioned dataset, which led to low detection rates. Genetic algorithm is employed to implement rules for detecting various types of attacks. Rules are formed of the features of the dataset identified as the most important ones for each attack type. In this way we introduce high level of generality and thus achieve high detection rates, but also gain high reduction of the system training time. Thenceforth we re-check the decision of the user-to- root rules with the rules that detect other types of attacks. In this way we decrease the false-positive rate. The model was verified on KDD 99, demonstrating higher detection rates than those reported by the state- of-the-art while maintaining low false-positive rate.

Fast kernel classifier construction using orthogonal forward selection to minimise leave-one-out misclassification rate

We propose a simple yet computationally efficient construction algorithm for two-class kernel classifiers. In order to optimise classifier's generalisation capability, an orthogonal forward selection procedure is used to select kernels one by one by minimising the leave-one-out (LOO) misclassification rate directly. It is shown that the computation of the LOO misclassification rate is very efficient owing to orthogonalisation. Examples are used to demonstrate that the proposed algorithm is a viable alternative to construct sparse two-class kernel classifiers in terms of performance and computational efficiency.

A fast linear-in-the-parameters classifier construction algorithm using orthogonal forward selection to minimize leave-one-out misclassification rate

We propose a simple and computationally efficient construction algorithm for two class linear-in-the-parameters classifiers. In order to optimize model generalization, a forward orthogonal selection (OFS) procedure is used for minimizing the leave-one-out (LOO) misclassification rate directly. An analytic formula and a set of forward recursive updating formula of the LOO misclassification rate are developed and applied in the proposed algorithm. Numerical examples are used to demonstrate that the proposed algorithm is an excellent alternative approach to construct sparse two class classifiers in terms of performance and computational efficiency.