Proactive Relay Selection with Joint Impact of Hardware Impairment and Co-channel Interference

In this paper, we investigate the end-to-end performance of dual-hop proactive decode-and-forward relaying networks with Nth best relay selection in the presence of two practical deleterious effects: i) hardware impairment and ii) cochannel interference. In particular, we derive new exact and asymptotic closed-form expressions for the outage probability and average channel capacity of Nth best partial and opportunistic relay selection schemes over Rayleigh fading channels. Insightful discussions are provided. It is shown that, when the system cannot select the best relay for cooperation, the partial relay selection scheme outperforms the opportunistic method under the impact of the same co-channel interference (CCI). In addition, without CCI but under the effect of hardware impairment, it is shown that both selection strategies have the same asymptotic channel capacity. Monte Carlo simulations are presented to corroborate our analysis.

Interpretable semantic vectors from a joint model of brain-and text-based meaning

Vector space models (VSMs) represent word meanings as points in a high dimensional space. VSMs are typically created using a large text corpora, and so represent word semantics as observed in text. We present a new algorithm (JNNSE) that can incorporate a measure of semantics not previously used to create VSMs: brain activation data recorded while people read words. The resulting model takes advantage of the complementary strengths and weaknesses of corpus and brain activation data to give a more complete representation of semantics. Evaluations show that the model 1) matches a behavioral measure of semantics more closely, 2) can be used to predict corpus data for unseen words and 3) has predictive power that generalizes across brain imaging technologies and across subjects. We believe that the model is thus a more faithful representation of mental vocabularies.

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.

Shape Memory Alloy Features for Seismic Retrofitting of External RC Beam-Column Joint

Shape memory alloys (SMAs) have the ability to undergo large deformations with minimum residual strain and also the extraordinary ability to undergo reversible hysteretic shape change known as the shape memory effect. The shape memory effect of these alloys can be utilised to develop a convenient way of actively confining concrete sections to improve their shear strength, flexural ductility and ultimate strain capacity. Most of the previous work on active confinement of concrete using SMA has been carried out on circular sections. In this study retrofitting strategies for active confinement of non-circular sections have been proposed. The proposed schemes presented in this paper are conceived with an aim to seismically retrofit a beam-column joint in non-seismically designed reinforced concrete buildings.

The complex material behaviour of SMAs depends on number of parameters. Depending upon the alloying elements, SMAs exhibit different behaviour in different conditions and are highly sensitive to variation in temperature, phase in which it is used, loading pattern, strain rate and pre-strain conditions. Therefore, a detailed discussion on the behaviour of SMAs under different thermo-mechanical conditions is presented first in this paper.

The influence of area level social deprivation on preoperative disease severity and postoperative outcomes following unicompartmental knee joint replacement

BACKGROUND: This study investigated the effect of socioeconomic deprivation on preoperative disease and outcome following unicompartmental knee replacement (UKR).

METHODS: 307 Oxford UKRs implanted between 2008 and 2013 under the care of one surgeon using the same surgical technique were analysed. Deprivation was quantified using the Northern Ireland Multiple Deprivation Measure. Preoperative disease severity and postoperative outcome were measured using the Oxford Knee Score (OKS).

RESULTS: There was no difference in preoperative OKS between deprivation groups. Preoperative knee range of motion (ROM) was significantly reduced in more deprived patients with 10° less ROM than least deprived patients. Postoperatively there was no difference in OKS improvement between deprivation groups (p=0.46), with improvements of 19.5 and 21.0 units in the most and least deprived groups respectively. There was no significant association between deprivation and OKS improvement on unadjusted or adjusted analysis. Preoperative OKS, Short Form 12 mental component score and length of stay were significant independent predictors of OKS improvement. A significantly lower proportion of the most deprived group (15%) reported being able to walk an unlimited distance compared to the least deprived group (41%) one year postoperatively.

CONCLUSION: More deprived patients can achieve similar improvements in OKS to less deprived patients following UKR.

LEVEL OF EVIDENCE: 2b - retrospective cohort study of prognosis.

Joint Optimization of Area Spectral Efficiency and Delay over PPP Interfered Ad-Hoc Networks

To evaluate the performance of the co-channel transmission based communication, we propose a new metric for area spectral efficiency (ASE) of interference limited ad-hoc network by assuming that the nodes are randomly distributed according to a Poisson point processes (PPP). We introduce a utility function, U = ASE/delay and derive the optimal ALOHA transmission probability p and the SIR threshold τ that jointly maximize the ASE and minimize the local delay. Finally, numerical results have been conducted to confirm that the joint optimization based on the U metric achieves a significant performance gain compared to conventional systems.

Avoiding Negligence and Profusion: The failure of the Joint-Stock form in the Anglo-Indian Tea Trade, 1840-1870

In the 19th century, firms operating in the Anglo-Indian tea trade were organised using a variety ownership forms including the partnership, joint-stock and a combination of the two known as the Managing agency. Faced with both an increasing need for fixed capital and high agency costs caused by the distance between owners and managers, the firms adapted and increasingly adopted the hybrid managing agency model to overcome these problems. Using new data from Calcutta and Bengal Commercial Registers and detailed case studies of the Assam Company and Gillanders, Arbuthnot and Co, this paper demonstrates that British entrepreneurs did not see the choice of ownership as a dichotomy or firm boundaries as fixed, but instead innovatively drew on the strengths of different forms of ownership to compete and grow successfully.

Statistical Tests for Joint Analysis of Performance Measures

Recently there has been an increasing interest in the development of new methods using Pareto optimality to deal with multi-objective criteria (for example, accuracy and architectural complexity). Once one has learned a model based on their devised method, the problem is then how to compare it with the state of art. In machine learning, algorithms are typically evaluated by comparing their performance on different data sets by means of statistical tests. Unfortunately, the standard tests used for this purpose are not able to jointly consider performance measures. The aim of this paper is to resolve this issue by developing statistical procedures that are able to account for multiple competing measures at the same time. In particular, we develop two tests: a frequentist procedure based on the generalized likelihood-ratio test and a Bayesian procedure based on a multinomial-Dirichlet conjugate model. We further extend them by discovering conditional independences among measures to reduce the number of parameter of such models, as usually the number of studied cases is very reduced in such comparisons. Real data from a comparison among general purpose classifiers is used to show a practical application of our tests.

Fibre laser joining of highly dissimilar materials: Commercially pure Ti and PET hybrid joint for medical device applications

Laser transmission joining (LTJ) is growing in importance, and has the potential to become a niche technique for the fabrication of hybrid plastic-metal joints for medical device applications. The possibility of directly joining plastics to metals by LTJ has been demonstrated by a number of recent studies. However, a reliable and quantitative method for defining the contact area between the plastic and metal, facilitating calculation of the mechanical shear stress of the hybrid joints, is still lacking. A new method, based on image analysis using ImageJ, is proposed here to quantify the contact area at the joint interface. The effect of discolouration on the mechanical performance of the hybrid joints is also reported for the first time. Biocompatible polyethylene terephthalate (PET) and commercially pure titanium (Ti) were selected as materials for laser joining using a 200 W CW fibre laser system. The effect of laser power, scanning speed and stand-off distance between the nozzle tip and top surface of the plastic were studied and analysed by Taguchi L9 orthogonal array and ANOVA respectively. The surface morphology, structure and elemental composition on the PET and Ti surfaces after shearing/peeling apart were characterized by SEM, EDX, XRD and XPS.