Cognitive amplify-and-forward relay networks with beamforming under primary user power constraint over Nakagami-m fading channels

In this paper, we analyze the performance of cognitive amplify-and-forward (AF) relay networks with beamforming under the peak interference power constraint of the primary user (PU). We focus on the scenario that beamforming is applied at the multi-antenna secondary transmitter and receiver. Also, the secondary relay network operates in channel state information-assisted AF mode, and the signals undergo independent Nakagami-m fading. In particular, closed-form expressions for the outage probability and symbol error rate (SER) of the considered network over Nakagami-m fading are presented. More importantly, asymptotic closed-form expressions for the outage probability and SER are derived. These tractable closed-form expressions for the network performance readily enable us to evaluate and examine the impact of network parameters on the system performance. Specifically, the impact of the number of antennas, the fading severity parameters, the channel mean powers, and the peak interference power is addressed. The asymptotic analysis manifests that the peak interference power constraint imposed on the secondary relay network has no effect on the diversity gain. However, the coding gain is affected by the fading parameters of the links from the primary receiver to the secondary relay network

Changing policy and legislation in special and inclusive education: a perspective from Northern Ireland

It is now 15 years since the signing of the 1998 Belfast (or ‘Good Friday’) Peace Agreement which committed all participants to exclusively democratic and peaceful means of resolving differences, and towards a shared and inclusive society defined by the principles of respect for diversity, equality and the interdependence of people. In particular, it committed participants to the protection and vindication of the human rights of all. This is, therefore, a precipitous time to undertake a probing analysis of educational reforms in Northern Ireland associated with provision in the areas of inclusion and special needs education. Consequently, by drawing upon analytical tools and perspectives derived from critical policy analysis, this article, by Ron Smith from the School of Education, Queen’s University Belfast, discusses the policy cycle associated with the proposed legislation entitled Every School a Good School: the way forward for special educational needs and inclusion. It examines how this policy text structures key concepts such as ‘inclusion’, ‘additional educational needs’ and ‘barriers to learning’, and how the proposals attempt to resolve the dilemma of commonality and difference. Conceived under direct rule from Westminster (April 2006), issued for consultation when devolved powers to a Northern Ireland Assembly had been restored, and with the final proposals yet to be made public, this targeted educational strategy tells a fascinating story of the past, present and likely future of special needs education in Northern Ireland. Before offering an account of this work, it is placed within some broader ecological frameworks.

Simultaneously uncovering the patterns of brain regions involved in different story reading subprocesses

Story understanding involves many perceptual and cognitive subprocesses, from perceiving individual words, to parsing sentences, to understanding the relationships among the story characters. We present an integrated computational model of reading that incorporates these and additional subprocesses, simultaneously discovering their fMRI signatures. Our model predicts the fMRI activity associated with reading arbitrary text passages, well enough to distinguish which of two story segments is being read with 74% accuracy. This approach is the first to simultaneously track diverse reading subprocesses during complex story processing and predict the detailed neural representation of diverse story features, ranging from visual word properties to the mention of different story characters and different actions they perform. We construct brain representation maps that replicate many results from a wide range of classical studies that focus each on one aspect of language processing and offer new insights on which type of information is processed by different areas involved in language processing. Additionally, this approach is promising for studying individual differences: it can be used to create single subject maps that may potentially be used to measure reading comprehension and diagnose reading disorders.

Autism and ABA: Best Practice in America and the Way Forward for Europe.

According to recent estimates, 1 in each 68 new-borns will be diagnosed with an Autism Spectrum Disorder (ASD) in the USA (Centers for Disease Control and Prevention, 2014), while 1 in every 29 children will be diagnosed with ASD in the UK (Dillenburger, Jordan, McKerr, & Keenan, 2015). Individuals diagnosed with ASD share a set of characteristics at varying levels of severity: impairments in social communication skills and presence of restricted interests and repetitive behaviours (American Psychiatric Association, 2013).Notwithstanding these figures, little effort has been placed in European countries’ policies for reaching an early diagnosis. This has a detrimental effect on future prognosis for children with ASD, since research has clearly shown that when evidence-based interventions are accessed early in life, they can lead to great improvements on the overall functioning of children with ASD, including significant gains in social communication and reduction of inappropriate behaviours (Dawson, Rogers, Munson, Smith, Winter, Greenson, Donaldson, & Varley, 2009).Additionally, when looking at the services available for children with ASD and their families in Europe, it seems that not much improvement has been made in the last decades. Traditional eclectic approaches and a wealth of non-scientific methods seem to be available and often recommended by public bodies, while state-funded evidence-based interventions are not offered as part of the education or health system. Given that there is a wealth of evidence on the effectiveness of interventions based on the science of ABA, it seems that specific action is required to correct the situation, respecting children’s right to effective treatment and inclusion.In the present paper, these issues are fully discussed and recommendations for best practice are offered.

Mesenchymal stromal cells for treatment of the acute respiratory distress syndrome: The beginning of the story

In spite of decades of research, the acute respiratory distress syndrome (ARDS) continues to have an unacceptably high mortality and morbidity. Mesenchymal stromal cells (MSCs) present a promising candidate for the treatment of this condition and have demonstrated benefit in preclinical models. MSCs, which are a topic of growing interest in many inflammatory disorders, have already progressed to early phase clinical trials in ARDS. While a number of their mechanisms of effect have been elucidated, a better understanding of the complex actions of these cells may pave the way for MSC modifications, which might enable more effective translation into clinical practice.

Forward and backward least angle regression for nonlinear system identification

A forward and backward least angle regression (LAR) algorithm is proposed to construct the nonlinear autoregressive model with exogenous inputs (NARX) that is widely used to describe a large class of nonlinear dynamic systems. The main objective of this paper is to improve model sparsity and generalization performance of the original forward LAR algorithm. This is achieved by introducing a replacement scheme using an additional backward LAR stage. The backward stage replaces insignificant model terms selected by forward LAR with more significant ones, leading to an improved model in terms of the model compactness and performance. A numerical example to construct four types of NARX models, namely polynomials, radial basis function (RBF) networks, neuro fuzzy and wavelet networks, is presented to illustrate the effectiveness of the proposed technique in comparison with some popular methods.

A novel forward gene selection algorithm for microarray data

This paper investigates the gene selection problem for microarray data with small samples and variant correlation. Most existing algorithms usually require expensive computational effort, especially under thousands of gene conditions. The main objective of this paper is to effectively select the most informative genes from microarray data, while making the computational expenses affordable. This is achieved by proposing a novel forward gene selection algorithm (FGSA). To overcome the small samples' problem, the augmented data technique is firstly employed to produce an augmented data set. Taking inspiration from other gene selection methods, the L2-norm penalty is then introduced into the recently proposed fast regression algorithm to achieve the group selection ability. Finally, by defining a proper regression context, the proposed method can be fast implemented in the software, which significantly reduces computational burden. Both computational complexity analysis and simulation results confirm the effectiveness of the proposed algorithm in comparison with other approaches

Dual-Hop Cognitive Amplify-and-Forward Relaying Networks over η− μ Fading Channels

This paper presents a thorough performance analysis of dual-hop cognitive amplify-and-forward (AF) relaying networks under spectrum-sharing mechanism over independent non-identically distributed (i.n.i.d.) 􀀀 fading channels. In order to guarantee the quality-of-service (QoS) of primary networks, both maximum tolerable peak interference power Q at the primary users (PUs) and maximum allowable transmit power P at secondary users (SUs) are considered to constrain transmit power at the cognitive transmitters. For integer-valued fading parameters, a closed-form lower bound for the outage probability (OP) of the considered networks is obtained. Moreover, assuming arbitrary-valued fading parameters, the lower bound in integral form for the OP is derived. In order to obtain further insights on the OP performance, asymptotic expressions for the OP at high SNRs are derived, from which the diversity/coding gains and the diversity-multiplexing gain tradeoff (DMT) of the secondary network can be readily deduced. It is shown that the diversity gain and also the DMT are solely determined by the fading parameters of the secondary network whereas the primary network only affects the coding gain. The derived results include several others available in previously published works as special cases, such as those for Nakagami-m fading channels. In addition, performance evaluation results have been obtained by Monte Carlo computer simulations which have verified the accuracy of the theoretical analysis.

The inside story: A survey of social work students’ supervision and learning opportunities on placement

Practice learning accounts for half of the content of the Bachelor of Social Work degree course requirements in Northern Ireland in their field education programs and share a professional and ethical responsibility with practice teachers to provide appropriate learning environments to prepare students as competent and professional practitioners. The accreditation standards for practice learning require the placement to provide students with regular supervision and exposure to a range of learning strategies, but there is little research that actually identifies the types of placements offering this learning and the key activities provided. This paper builds on an Australian study and surveys social work students in two programs in Northern Ireland about their exposure a range of learning activities, how frequently they were provided and how it compares to what is required by the Northern Ireland practice standards. The results indicated that, although most students were satisfied with the supervision and support they received during their placement, the frequency of supervision and type of learning activities varied according to different settings, year levels and who provided the learning opportunities.

Introduction: Embodiment, Identity, and the Patient’s Story

This introduction looks at the links between medicine and narrative, arguing that patients’ stories have a valuable role to play in patient-centered healthcare. Two particular areas are addressed: first, the ways in which first-person expressions of embodied experience may contribute to medicine’s empathetic endeavor; and second, the lack of research to date into autopathography in the French-speaking world.