Security Enhancement of Cooperative Single Carrier Systems

In this paper, the impact of multiple active eavesdroppers on cooperative single carrier systems with multiple relays and multiple destinations is examined. To achieve the secrecy diversity gains in the form of opportunistic selection, a two-stage scheme is proposed for joint relay and destination selection, in which, after the selection of the relay with the minimum effective maximum signal-to-noise ratio (SNR) to a cluster of eavesdroppers, the destination that has the maximum SNR from the chosen relay is selected. In order to accurately assess the secrecy performance, the exact and asymptotic expressions are obtained in closed-form for several security metrics including the secrecy outage probability, the probability of non-zero secrecy rate, and the ergodic secrecy rate in frequency selective fading. Based on the asymptotic analysis, key design parameters such as secrecy diversity gain, secrecy array gain, secrecy multiplexing gain, and power cost are characterized, from which new insights are drawn. Moreover, it is concluded that secrecy performance limits occur when the average received power at the eavesdropper is proportional to the counterpart at the destination. Specifically, for the secrecy outage probability, it is confirmed that the secrecy diversity gain collapses to zero with outage floor, whereas for the ergodic secrecy rate, it is confirmed confirm that its slope collapses to zero with capacity ceiling.

Antimicrobial peptides and proinflammatory cytokines in periprosthetic joint infection

Background: Differentiation between septic and aseptic loosening of joint replacements is essential for successful revision surgery, but reliable markers for the diagnosis of low-grade infection are lacking. The present study was performed to assess intra-articular and systemic levels of antimicrobial peptides and proinflammatory cytokines as diagnostic markers for periprosthetic joint infection. Methods: Fifteen consecutive patients with staphylococcal periprosthetic joint infections and twenty control patients with aseptic loosening of total hip and knee replacements were included in this prospective, single-center, controlled clinical trial. Expression of the antimicrobial peptides human β-defensin-2 (HBD-2), human β-defensin-3 (HBD-3), and cathelicidin LL-37 (LL-37) was determined by ELISA (enzyme-linked immunosorbent assay) in serum and joint aspirates. Proinflammatory cytokines were assessed in serum and joint aspirates with use of cytometric bead arrays. C-reactive protein in serum, microbiology, and histopathology of periprosthetic tissue served as the “gold standard” for the diagnosis of infection. Results: The antimicrobial peptides HBD-3 and LL-37 were significantly elevated in joint aspirates from patients with periprosthetic joint infection compared with patients with aseptic loosening, and the area under the curve (AUC) in a receiver operating characteristic curve analysis was equal to 0.745 and 0.875, respectively. Additionally, significant local increases in the proinflammatory cytokines interleukin (IL)-1β, IL-4, IL-6, IL-17A, interferon (IFN)-γ, and tumor necrosis factor (TNF)-α were observed to be associated with infection. Logistic regression analysis indicated that the combination of an antimicrobial peptide with another synovial fluid biomarker improved diagnostic accuracy; the AUC value was 0.916 for LL-37 and IL-4, 0.895 for LL-37 and IL-6, 0.972 for HBD-3 and IL-4, and 0.849 for HBD-3 and IL-6. In contrast, the only antimicrobial peptides and cytokines in serum that showed a significant systemic increase in association with infection were HBD-2, IL-4, and IL-6 (all of which had an AUC value of <0.75). Conclusions: The present study showed promising results for the use of antimicrobial peptides and other biomarkers in synovial fluid for the diagnosis of periprosthetic joint infection, and analysis of the levels in synovial fluid was more accurate than analysis of serum.

Cross-participant modelling based on joint or disjoint feature selection: an fMRI conceptual decoding study

Multivariate classification techniques have proven to be powerful tools for distinguishing experimental conditions in single sessions of functional magnetic resonance imaging (fMRI) data. But they are vulnerable to a considerable penalty in classification accuracy when applied across sessions or participants, calling into question the degree to which fine-grained encodings are shared across subjects. Here, we introduce joint learning techniques, where feature selection is carried out using a held-out subset of a target dataset, before training a linear classifier on a source dataset. Single trials of functional MRI data from a covert property generation task are classified with regularized regression techniques to predict the semantic class of stimuli. With our selection techniques (joint ranking feature selection (JRFS) and disjoint feature selection (DJFS)), classification performance during cross-session prediction improved greatly, relative to feature selection on the source session data only. Compared with JRFS, DJFS showed significant improvements for cross-participant classification. And when using a groupwise training, DJFS approached the accuracies seen for prediction across different sessions from the same participant. Comparing several feature selection strategies, we found that a simple univariate ANOVA selection technique or a minimal searchlight (one voxel in size) is appropriate, compared with larger searchlights.

Optimization study of hybrid spot-welded/bonded single-lap joints

Joining of components with structural adhesives is currently one of the most widespread techniques for advanced structures (e.g., aerospace or aeronautical). Adhesive bonding does not involve drilling operations and it distributes the load over a larger area than mechanical joints. However, peak stresses tend to develop near the overlap edges because of differential straining of the adherends and load asymmetry. As a result, premature failures can be expected, especially for brittle adhesives. Moreover, bonded joints are very sensitive to the surface treatment of the material, service temperature, humidity and ageing. To surpass these limitations, the combination of adhesive bonding with spot-welding is a choice to be considered, adding a few advantages like superior static strength and stiffness, higher peeling and fatigue strength and easier fabrication, as fixtures during the adhesive curing are not needed. The experimental and numerical study presented here evaluates hybrid spot-welded/bonded single-lap joints in comparison with the purely spot-welded and bonded equivalents. A parametric study on the overlap length (LO) allowed achieving different strength advantages, up to 58% compared to spot-welded joints and 24% over bonded joints. The Finite Element Method (FEM) and Cohesive Zone Models (CZM) for damage growth were also tested in Abaqus® to evaluate this technique for strength prediction, showing accurate estimations for all kinds of joints.

Strength prediction of single- and double-lap joints by standard and extended finite element modelling

The structural integrity of multi-component structures is usually determined by the strength and durability of their unions. Adhesive bonding is often chosen over welding, riveting and bolting, due to the reduction of stress concentrations, reduced weight penalty and easy manufacturing, amongst other issues. In the past decades, the Finite Element Method (FEM) has been used for the simulation and strength prediction of bonded structures, by strength of materials or fracture mechanics-based criteria. Cohesive-zone models (CZMs) have already proved to be an effective tool in modelling damage growth, surpassing a few limitations of the aforementioned techniques. Despite this fact, they still suffer from the restriction of damage growth only at predefined growth paths. The eXtended Finite Element Method (XFEM) is a recent improvement of the FEM, developed to allow the growth of discontinuities within bulk solids along an arbitrary path, by enriching degrees of freedom with special displacement functions, thus overcoming the main restriction of CZMs. These two techniques were tested to simulate adhesively bonded single- and double-lap joints. The comparative evaluation of the two methods showed their capabilities and/or limitations for this specific purpose.

Effect of temperature on the shear strength of aluminium single lap bonded joints for high temperature applications

An experimental and numerical investigation into the shear strength behaviour of adhesive single lap joints (SLJs) was carried out in order to understand the effect of temperature on the joint strength. The adherend material used for the experimental tests was an aluminium alloy in the form of thin sheets, and the adhesive used was a high-strength high temperature epoxy. Tensile tests as a function of temperature were performed and numerical predictions based on the use of a bilinear cohesive damage model were obtained. It is shown that at temperatures below Tg, the lap shear strength of SLJs increased, while at temperatures above Tg, a drastic drop in the lap shear strength was observed. Comparison between the experimental and numerical maximum loads representing the strength of the joints shows a reasonably good agreement.

Tests of Joint Hypotheses for Time Series Regression with a Unit Root

This Paper Studies Tests of Joint Hypotheses in Time Series Regression with a Unit Root in Which Weakly Dependent and Heterogeneously Distributed Innovations Are Allowed. We Consider Two Types of Regression: One with a Constant and Lagged Dependent Variable, and the Other with a Trend Added. the Statistics Studied Are the Regression \"F-Test\" Originally Analysed by Dickey and Fuller (1981) in a Less General Framework. the Limiting Distributions Are Found Using Functinal Central Limit Theory. New Test Statistics Are Proposed Which Require Only Already Tabulated Critical Values But Which Are Valid in a Quite General Framework (Including Finite Order Arma Models Generated by Gaussian Errors). This Study Extends the Results on Single Coefficients Derived in Phillips (1986A) and Phillips and Perron (1986).

Fitting models for the joint action of two drugs using SAS(R)

Combinations of drugs are increasingly being used for a wide variety of diseases and conditions. A pre-clinical study may allow the investigation of the response at a large number of dose combinations. In determining the response to a drug combination, interest may lie in seeking evidence of synergism, in which the joint action is greater than the actions of the individual drugs, or of antagonism, in which it is less. Two well-known response surface models representing no interaction are Loewe additivity and Bliss independence, and Loewe or Bliss synergism or antagonism is defined relative to these. We illustrate an approach to fitting these models for the case in which the marginal single drug dose-response relationships are represented by four-parameter logistic curves with common upper and lower limits, and where the response variable is normally distributed with a common variance about the dose-response curve. When the dose-response curves are not parallel, the relative potency of the two drugs varies according to the magnitude of the desired effect and the models for Loewe additivity and synergism/antagonism cannot be explicitly expressed. We present an iterative approach to fitting these models without the assumption of parallel dose-response curves. A goodness-of-fit test based on residuals is also described. Implementation using the SAS NLIN procedure is illustrated using data from a pre-clinical study. Copyright © 2007 John Wiley & Sons, Ltd.

Accurate molecular structures of chlorothiazide and hydrochlorothiazide by joint refinement against powder neutron and X-ray diffraction data

The compounds chlorothiazide and hydrochlorothiazide (crystalline form II) have been studied in their fully hydrogenous forms by powder neutron diffraction on the GEM diffractometer. The results of joint Rietveld refinement of the structures against multi-bank neutron and single-bank X-ray powder data are reported and show that accurate and precise structural information can be obtained from polycrystalline molecular organic materials by this route.

Cyclic prefixed OQAM-OFDM and its application to single-carrier FDMA

Single-carrier frequency division multiple access (SC-FDMA) has appeared to be a promising technique for high data rate uplink communications. Aimed at SC-FDMA applications, a cyclic prefixed version of the offset quadrature amplitude modulation based OFDM (OQAM-OFDM) is first proposed in this paper. We show that cyclic prefixed OQAMOFDM CP-OQAM-OFDM) can be realized within the framework of the standard OFDM system, and perfect recovery condition in the ideal channel is derived. We then apply CP-OQAMOFDM to SC-FDMA transmission in frequency selective fading channels. Signal model and joint widely linear minimum mean square error (WLMMSE) equalization using a prior information with low complexity are developed. Compared with the existing DFTS-OFDM based SC-FDMA, the proposed SC-FDMA can significantly reduce envelope fluctuation (EF) of the transmitted signal while maintaining the bandwidth efficiency. The inherent structure of CP-OQAM-OFDM enables low-complexity joint equalization in the frequency domain to combat both the multiple access interference and the intersymbol interference. The joint WLMMSE equalization using a prior information guarantees optimal MMSE performance and supports Turbo receiver for improved bit error rate (BER) performance. Simulation resultsconfirm the effectiveness of the proposed SC-FDMA in termsof EF (including peak-to-average power ratio, instantaneous-toaverage power ratio and cubic metric) and BER performances.

B-spline neural network based single-carrier frequency domain equalisation for Hammerstein channels

A practical single-carrier (SC) block transmission with frequency domain equalisation (FDE) system can generally be modelled by the Hammerstein system that includes the nonlinear distortion effects of the high power amplifier (HPA) at transmitter. For such Hammerstein channels, the standard SC-FDE scheme no longer works. We propose a novel Bspline neural network based nonlinear SC-FDE scheme for Hammerstein channels. In particular, we model the nonlinear HPA, which represents the complex-valued static nonlinearity of the Hammerstein channel, by two real-valued B-spline neural networks, one for modelling the nonlinear amplitude response of the HPA and the other for the nonlinear phase response of the HPA. We then develop an efficient alternating least squares algorithm for estimating the parameters of the Hammerstein channel, including the channel impulse response coefficients and the parameters of the two B-spline models. Moreover, we also use another real-valued B-spline neural network to model the inversion of the HPA’s nonlinear amplitude response, and the parameters of this inverting B-spline model can be estimated using the standard least squares algorithm based on the pseudo training data obtained as a byproduct of the Hammerstein channel identification. Equalisation of the SC Hammerstein channel can then be accomplished by the usual one-tap linear equalisation in frequency domain as well as the inverse Bspline neural network model obtained in time domain. The effectiveness of our nonlinear SC-FDE scheme for Hammerstein channels is demonstrated in a simulation study.

Participation of peripheral tachykinin NK(1) receptors in the carrageenan-induced inflammation of the rat temporomandibular joint

Temporomandibular disorders represent one of the major challenges in dentistry therapeutics. This study was undertaken to evaluate the time course of carrageenan-induced inflammation in the rat temporomandibular joint (TMJ) and to investigate the role of tachykinin NK(1) receptors. Inflammation was induced by a single intra-articular (i.art.) injection of carrageenan into the left TMJ (control group received sterile saline). Inflammatory parameters such as plasma extravasation, leukocyte influx and mechanical allodynia (measured as the head-withdrawal force threshold) and TNF alpha and IL-1 beta concentrations were measured in the TMJ lavages at selected time-points. The carrageenan-induced responses were also evaluated after treatment with the NK(1) receptor antagonist SR140333. The i.art. injection of carrageenan into the TMJ caused a time-dependent plasma extravasation associated with mechanical allodynia, and a marked neutrophil accumulation between 4 and 24 h. Treatment with SR140333 substantially inhibited the increase in plasma extravasation and leukocyte influx at 4 and 24 h, as well as the production of TNF alpha and IL-1 beta into the joint cavity, but failed to affect changes in head-withdrawal threshold. The results obtained from the present TMJ-arthritis model provide, for the first time, information regarding the time course of this experimental inflammatory process. In addition, our data show that peripheral NK(1) receptors mediate the production of both TNF alpha and IL-1 beta in the TMJ as well as some of the inflammatory signs, such as plasma extravasation and leukocyte influx, but not the nociceptive component. 2008 European Federation of Chapters of the International Association for the Study of Pain. Published by Elsevier Ltd. All rights reserved.

Ageing effects on knee and ankle joint angles at key events and phases of the gait cycle.

The objective of this research was to determine whether joint angles at critical gait events and during major energy generation/absorption phases of the gait cycle would reliably discriminate age-related degeneration during unobstructed walking. The gaits of 24 healthy adults (12 young and 12 elderly) were analysed using the PEAK Motus motion analysis system. The elderly participants showed significantly greater single (60.3% versus 62.3%, p < 0.01) and double ( p < 0.05) support times, reduced knee flexion (47.7° versus 43.0°, p < 0.05) and ankle plantarflexion (16.8° compared to 3.3°, p = 0.053) at toe off, reduced knee flexion during push-off and reduced ankle dorsiflexion (16.8° compared to 22.0°, p < 0.05) during the swing phase. The plantarflexing ankle joint motion during the stance to swing phase transition (A₂) for the young group (31.3°) was about twice ( p < 0.05) that of the elderly (16.9°). Reduced knee extension range of motion suggests that the elderly favoured a flexed-knee gait to assist in weight acceptance. Reduced dorsiflexion by the elderly in the swing phase implies greater risk of toe contact with obstacles. Overall, the results suggest that joint angle measures at critical events/phases in the gait cycle provide a useful indication of age-related degeneration in the control of lower limb trajectories during unobstructed walking.