An overview of traumatic brain injury in adults

The epidemiology of traumatic brain injury (TBI) in high-income countries is changing, with falls in older adults as one of the leading causes. Disability after TBI results largely from cognitive, emotional and behavioural problems, as well as physical impairments. The consequences are long term and far-reaching, affecting not only the survivor and carers, but also incurring major socioeconomic costs to society. TBI is a heterogeneous disease, which has different causes, severity and encompasses a spectrum of pathological features. In part one of this two-part series, the author provides an overview of the different pathophysiological features of TBI. Part two will focus on management of adult patients with a severe TBI (Glasgow Coma Scale score ≤8) who require critical care, based on current evidence

Severe traumatic brain injury in adults: a review of critical care management

This second of a two-part review on traumatic brain injury (TBI) describes management for adult patients with a severe TBI (post-resuscitation Glasgow Coma Scale score ≤ 8) who require critical care based on evidence and recommendations. Evidence-based, standardised practice aims to limit secondary injury in patients with TBI. Critical care management is based on maintaining optimal physiology to minimise secondary injury in the early acute phase. The aim is to save lives and improve the quality of outcome for survivors

Iterative synchronisation and DC-offset estimation using superimposed training

In this paper, we propose a new iterative approach for superimposed training (ST) that improves synchronisation, DC-offset estimation and channel estimation. While synchronisation algorithms for ST have previously been proposed in [2],[4] and [5], due to interference from the data they performed sub-optimally, resulting in channel estimates with unknown delays. These delay ambiguities (also present in the equaliser) were estimated in previous papers in a non-practical manner. In this paper we avoid the need for estimation of this delay ambiguity by iteratively removing the effect of the data “noise”. The result is a BER performance superior to all other ST algorithms that have not assumed a-priori synchronisation

Internet information on birth options after caesarean compared to the RCOG patient information leaflet : a web survey

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An Evaluation of MIRU-VNTR Analysis and Spoligotyping for Genotyping of M. Bovis Isolates and a Comparison on RFLP Typing

Common strain typing methods for differentiation of Mycobacterium bovis isolates include restriction endonuclease analysis (REA), restriction fragment length polymorphism (RFLP) analysis, spoligotyping and more recently, mycobacterial interspersed repetitive unit-variable-number tandem repeat (MIRU-VNTR) typing. MIRU-VNTR and spoligotyping were evaluated in this study and these typing methods were compared with RFLP typing. A total of 386 M. bovis isolates from cattle, badgers and deer in the Republic of Ireland that had previously been typed by IS6110, polymorphic GC-rich sequence (PGRS) and direct repeat (DR) RFLP were included in the study. An initial panel of VNTR loci was established to analyse the first 60 isolates to determine that six VNTR loci (QUB 11a, QUB 11b, ETR A, 4052, MIRU 26 and 1895) displayed the greatest degree of discrimination between strains. Analysis of these six VNTR loci and spoligotyping was performed on all 386 isolates. RFLP was the method that gave the greatest differentiation of strains with a Hunter Gaston discriminatory index (HGDI) of 0.927, the HGDI recorded for MIRU-VNTR was marginally lower at 0.918 and spoligotyping was the least discriminatory method with a HGDI of 0.7. The HGDI for VNTR (6 loci) and spoligotyping was 0.933, however when 4 VNTR loci were used a comparable HGDI of 0.93 was recorded. Spoligotype SB0140 represented approximately 50% of the isolates. Within the group of isolates represented by SB0140 there was a high level of diversity between RFLP and MIRU-VNTR typescompared to groups represented by other spoligotypes. The most common MIRU-VNTR types within the SB0140 group were widely distributed geographically which limited their usefulness for tracing geographic spread of infection. However, the less common MIRU-VNTR types with the SB0140 group were largely concentrated in defined geographic areas. A combination of spoligotyping and MIRUVNTR typing offered advantages over MIRU-VNTR typing alone. In a combined spoligotyping and MIRU-VNTR typing protocol the number of VNTR loci could be reduced to four (QUB 11a, QUB 11b, ETR A and 4052) while maintaining a high level of strain differentiation

Channel estimation and symbol detection for block transmission using data-dependent superimposed training

We address the problem of frequency-selective channel estimation and symbol detection using superimposed training. The superimposed training consists of the sum of a known sequence and a data-dependent sequence that is unknown to the receiver. The data-dependent sequence cancels the effects of the unknown data on channel estimation. The performance of the proposed approach is shown to significantly outperform existing methods based on superimposed training (ST)

Block synchronisation for joint channel and DC-offset estimation using data-dependent superimposed training

In this paper, we propose a new (single-step) block synchronisation algorithm for joint channel and DC-offset estimation for data-dependent superimposed training (DDST). While a (two-step) block synchronisation algorithm for DDST has previously been proposed in [5], due to interference from the information-bearing data it performed sub-optimally, resulting in channel estimates with unknown delays. These delay ambiguities (also present in the equaliser) were then estimated in [5] in a non-practical manner. In this paper we avoid the need for estimation of this delay ambiguity by exploiting the special structure of the channel output’s cyclic mean vector. The result is a BER performance superior to the DDST synchronisation algorithm first published in [5]

Clinical prediction models to inform individualized decision-making in subfertile couples : a stratified medicine approach

Funding This work was supported by a Chief Scientist Office Postdoctoral Training Fellowship in Health Services Research and Health of the Public Research (Ref PDF/12/06). The views expressed in this paper represent the views of the authors and not necessarily the views of the funding body.Peer reviewedPostprin