How Prepared are UK Medical Graduates for Practice? Final report from a programme of research commissioned by the General Medical Council

This programme of research aimed to understand the extent to which current UK medical graduates are prepared for practice. Commissioned by the General Medical Council, we conducted: (1) A Rapid Review of the literature between 2009 and 2013; (2) narrative interviews with a range of stakeholders; and (3) longitudinal audio-diaries with Foundation Year 1 doctors. The Rapid Review (RR) resulted in data from 81 manuscripts being extracted and mapped against a coding framework (including outcomes from Tomorrow's Doctors (2009) (TD09)). A narrative synthesis of the data was undertaken. Narrative interviews were conducted with 185 participants from 8 stakeholder groups: F1 trainees, newly registered trainee doctors, clinical educators, undergraduate and postgraduate deans and foundation programme directors, other healthcare professionals, employers, policy and government and patient and public representatives. Longitudinal audio-diaries were recorded by 26 F1 trainees over 4 months. The data were analysed thematically and mapped against TD09. Together these data shed light onto how preparedness for practice is conceptualised, measured, how prepared UK medical graduates are for practice, the effectiveness of transition interventions and the currently debated issue of bringing full registration forward to align with medical students’ graduation. Preparedness for practice was conceptualised as both a long- and short-term venture that included personal readiness as well as knowledge, skills and attitudes. It has mainly been researched using self-report measures of generalised incidents that have been shown to be problematic. In terms of transition interventions: assistantships were found to be valuable and efficacious for proactive students as team members, shadowing is effective when undertaken close to employment/setting of F1 post and induction is generally effective but of inconsistent quality. The August transition was highlighted in our interview and audio-diary data where F1s felt unprepared, particularly for the step-change in responsibility, workload, degree of multitasking and understanding where to go for help. Evidence of preparedness for specific tasks, skills and knowledge was contradictory: trainees are well prepared for some practical procedures but not others, reasonably well prepared for history taking and full physical examinations, but mostly unprepared for adopting an holistic understanding of the patient, involving patients in their care, safe and legal prescribing, diagnosing and managing complex clinical conditions and providing immediate care in medical emergencies. Evidence for preparedness for interactional and interpersonal aspects of practice was inconsistent with some studies in the RR suggesting graduates were prepared for team working and communicating with colleagues and patients, but other studies contradicting this. Interview and audio-diary data highlights concerns around F1s preparedness for communicating with angry or upset patients and relatives, breaking bad news, communicating with the wider team (including interprofessionally) and handover communication. There was some evidence in the RR to suggest that graduates were unprepared for dealing with error and safety incidents and lack an understanding of how the clinical environment works. Interview and audio-diary data backs this up, adding that F1s are also unprepared for understanding financial aspects of healthcare. In terms of being personally prepared, RR, interview and audio diary evidence is mixed around graduates’ preparedness for identifying their own limitations, but all data points to graduates’ difficulties in the domain of time management. In terms of personal and situational demographic factors, the RR found that gender did not typically predict perceptions of preparedness, but graduates from more recent cohorts, graduate entry students, graduates from problem based learning courses, UK educated graduates and graduates with an integrated degree reported feeling better prepared. The longitudinal audio-diaries provided insights into the preparedness journey for F1s. There seems to be a general development in the direction of trainees feeling more confident and competent as they gain more experience. However, these developments were not necessarily linear as challenging circumstances (e.g. new specialty, new colleagues, lack of staffing) sometimes made them feel unprepared for situations where they had previously indicated preparedness.

Search for the Return of Activity in Active Asteroid 176P/LINEAR

We present the results of a search for the reactivation of active asteroid 176P/LINEAR during its 2011 perihelion passage using deep optical observations obtained before, during, and after that perihelion passage. Deep composite images of 176P constructed from data obtained between 2011 June and 2011 December show no visible signs of activity, while photometric measurements of the object during this period also show no significant brightness enhancements similar to that observed for 176P between 2005 November and 2005 December when it was previously observed to be active. An azimuthal search for dust emission likewise reveals no evidence for directed emission (i.e., a tail, as was previously observed for 176P), while a one-dimensional surface brightness profile analysis shows no indication of a spherically symmetric coma at any time in 2011. We conclude that 176P did not in fact exhibit activity in 2011, at least not on the level on which it exhibited activity in 2005, and suggest that this could be due to the devolatization or mantling of the active site responsible for its activity in 2005.

Impact of offshore wind power forecast error in a carbon constraint electricity market

This paper investigates the impacts of offshore wind power forecast error on the operation and management of a pool-based electricity market in 2050. The impact from offshore wind power forecast errors of up to 2000 MW on system generation costs, emission costs, dispatch-down of wind, number of start-ups and system marginal price are analysed. The main findings of this research are an increase in system marginal prices of approximately 1% for every percentage point rise in the offshore wind power forecast error regardless of the average forecast error sign. If offshore wind power generates less than forecasted (−13%) generation costs and system marginal prices increases by 10%. However, if offshore wind power generates more than forecasted (4%) the generation costs decrease yet the system marginal prices increase by 3%. The dispatch down of large quantities of wind power highlights the need for flexible interconnector capacity. From a system operator's perspective it is more beneficial when scheduling wind ahead of the trading period to forecast less wind than will be generated.

Optimisation of Kinetic Parameters for an After-treatment Catalyst

Mathematical modelling has become an essential tool in the design of modern catalytic systems. Emissions legislation is becoming increasingly stringent, and so mathematical models of aftertreatment systems must become more accurate in order to provide confidence that a catalyst will convert pollutants over the required range of conditions. 
Automotive catalytic converter models contain several sub-models that represent processes such as mass and heat transfer, and the rates at which the reactions proceed on the surface of the precious metal. Of these sub-models, the prediction of the surface reaction rates is by far the most challenging due to the complexity of the reaction system and the large number of gas species involved. The reaction rate sub-model uses global reaction kinetics to describe the surface reaction rate of the gas species and is based on the Langmuir Hinshelwood equation further developed by Voltz et al. [1] The reactions can be modelled using the pre-exponential and activation energies of the Arrhenius equations and the inhibition terms. 
The reaction kinetic parameters of aftertreatment models are found from experimental data, where a measured light-off curve is compared against a predicted curve produced by a mathematical model. The kinetic parameters are usually manually tuned to minimize the error between the measured and predicted data. This process is most commonly long, laborious and prone to misinterpretation due to the large number of parameters and the risk of multiple sets of parameters giving acceptable fits. Moreover, the number of coefficients increases greatly with the number of reactions. Therefore, with the growing number of reactions, the task of manually tuning the coefficients is becoming increasingly challenging. 
In the presented work, the authors have developed and implemented a multi-objective genetic algorithm to automatically optimize reaction parameters in AxiSuite®, [2] a commercial aftertreatment model. The genetic algorithm was developed and expanded from the code presented by Michalewicz et al. [3] and was linked to AxiSuite using the Simulink add-on for Matlab. 
The default kinetic values stored within the AxiSuite model were used to generate a series of light-off curves under rich conditions for a number of gas species, including CO, NO, C_{3H8 and C3H6. These light-off curves were used to generate an objective function.} 
This objective function was used to generate a measure of fit for the kinetic parameters. The multi-objective genetic algorithm was subsequently used to search between specified limits to attempt to match the objective function. In total the pre-exponential factors and activation energies of ten reactions were simultaneously optimized. 
The results reported here demonstrate that, given accurate experimental data, the optimization algorithm is successful and robust in defining the correct kinetic parameters of a global kinetic model describing aftertreatment processes.

System level DSP synthesis using voltage overscaling, unequal error protection & adaptive quality tuning

In this paper, we propose a system level design approach considering voltage over-scaling (VOS) that achieves error resiliency using unequal error protection of different computation elements, while incurring minor quality degradation. Depending on user specifications and severity of process variations/channel noise, the degree of VOS in each block of the system is adaptively tuned to ensure minimum system power while providing "just-the-right" amount of quality and robustness. This is achieved, by taking into consideration system level interactions and ensuring that under any change of operating conditions only the "lesscrucial" computations, that contribute less to block/system output quality, are affected. The design methodology applied to a DCT/IDCT system shows large power benefits (up to 69%) at reasonable image quality while tolerating errors induced by varying operating conditions (VOS, process variations, channel noise). Interestingly, the proposed IDCT scheme conceals channel noise at scaled voltages. ©2009 IEEE.

An optimal algorithm for low power multiplierless FIR filter design using chebychev criterion

In this paper, we propose a novel finite impulse response (FIR) filter design methodology that reduces the number of operations with a motivation to reduce power consumption and enhance performance. The novelty of our approach lies in the generation of filter coefficients such that they conform to a given low-power architecture, while meeting the given filter specifications. The proposed algorithm is formulated as a mixed integer linear programming problem that minimizes chebychev error and synthesizes coefficients which consist of pre-specified alphabets. The new modified coefficients can be used for low-power VLSI implementation of vector scaling operations such as FIR filtering using computation sharing multiplier (CSHM). Simulations in 0.25um technology show that CSHM FIR filter architecture can result in 55% power and 34% speed improvement compared to carry save multiplier (CSAM) based filters.

Design methodology to trade off power, output quality and error resiliency: Application to color interpolation filtering

Power dissipation and tolerance to process variations pose conflicting design requirements. Scaling of voltage is associated with larger variations, while Vdd upscaling or transistor up-sizing for process tolerance can be detrimental for power dissipation. However, for certain signal processing systems such as those used in color image processing, we noted that effective trade-offs can be achieved between Vdd scaling, process tolerance and "output quality". In this paper we demonstrate how these tradeoffs can be effectively utilized in the development of novel low-power variation tolerant architectures for color interpolation. The proposed architecture supports a graceful degradation in the PSNR (Peak Signal to Noise Ratio) under aggressive voltage scaling as well as extreme process variations in. sub-70nm technologies. This is achieved by exploiting the fact that some computations are more important and contribute more to the PSNR improvement compared to the others. The computations are mapped to the hardware in such a way that only the less important computations are affected by Vdd-scaling and process variations. Simulation results show that even at a scaled voltage of 60% of nominal Vdd value, our design provides reasonable image PSNR with 69% power savings.

Low Complexity Spectral Analysis of Heart-Rate-Variability through a Wavelet based FFT

In this paper, a low complexity system for spectral analysis of heart rate variability (HRV) is presented. The main idea of the proposed approach is the implementation of the Fast-Lomb periodogram that is a ubiquitous tool in spectral analysis, using a wavelet based Fast Fourier transform. Interestingly we show that the proposed approach enables the classification of processed data into more and less significant based on their contribution to output quality. Based on such a classification a percentage of less-significant data is being pruned leading to a significant reduction of algorithmic complexity with minimal quality degradation. Indeed, our results indicate that the proposed system can achieve up-to 45% reduction in number of computations with only 4.9% average error in the output quality compared to a conventional FFT based HRV system.

Logic and Memory Design Based on Unequal Error Protection for Voltage-scalable, Robust and Adaptive DSP Systems

In this paper, we propose a system level design approach considering voltage over-scaling (VOS) that achieves error resiliency using unequal error protection of different computation elements, while incurring minor quality degradation. Depending on user specifications and severity of process variations/channel noise, the degree of VOS in each block of the system is adaptively tuned to ensure minimum system power while providing "just-the-right" amount of quality and robustness. This is achieved, by taking into consideration block level interactions and ensuring that under any change of operating conditions, only the "less-crucial" computations, that contribute less to block/system output quality, are affected. The proposed approach applies unequal error protection to various blocks of a system-logic and memory-and spans multiple layers of design hierarchy-algorithm, architecture and circuit. The design methodology when applied to a multimedia subsystem shows large power benefits ( up to 69% improvement in power consumption) at reasonable image quality while tolerating errors introduced due to VOS, process variations, and channel noise.

Quantitative Measurement of [Na+] and [K+] in Postmortem Human Brain Tissue Indicates Disturbances in Subjects with Alzheimer's Disease and Dementia with Lewy Bodies

Alzheimer’s disease (AD) is associated with significant disturbances in the homeostasis of Na+ and K+ ions as well as reduced levels of Na+/K+ ATPase in the brain. This study used ICP-MS to accurately quantify Na+ and K+ concentrations in human postmortem brain tissue. We analyzed parietal cortex (Brodmann area 7) from 28 cognitively normal age-matched controls, 15 cases of moderate AD, 30 severe AD, and 15 dementia with Lewy bodies (DLB). Associations were investigated between [Na+] and [K+] and a number of variables including diagnosis, age, gender, Braak tangle stage, amyloid-β (Aβ) plaque load, tau load, frontal tissue pH, and APOE genotype. Brains from patients with severe AD had significantly higher (26%; p<0.001) [Na+] (mean 65.43 ± standard error 2.91 mmol/kg) than controls, but the concentration was not significantly altered in moderate AD or DLB. [Na+] correlated positively with Braak stage (r=0.45; p<0.0001), indicating association with disease severity. [K+] in tissue was 10% lower (p<0.05) in moderate AD than controls. However, [K+] in severe AD and DLB (40.97±1.31 mmol/kg) was not significantly different from controls. There was a significant positive correlation between [K+] and Aβ plaque load (r=0.46; p=0.035), and frontal tissue pH (r=0.35; p=0.008). [Na+] was not associated with [K+] across the groups, and neither ion was associated with tau load or APOE genotype. We have demonstrated disturbances of both [Na+] and [K+] in relation to the severity of AD and markers of AD pathology, although it is possible that these relate to late-stage secondary manifestations of the disease pathology.

BER evaluation of a low complexity transmit diversity scheme and its application to MIMO-BICM

In this paper, we first provide a theoretical validation for a low-complexity transmit diversity algorithm which employs only one RF chain and a low-complexity switch for transmission. Our theoretical analysis is compared to the simulation results and proved to be accurate. We then apply the transmit diversity scheme to multiple-input and multiple-output (MIMO) systems with bit-interleaved coded modulation (BICM). © 2012 IEEE.