Reluctance Accelerator Efficiency Optimization via Pulse Shaping

Reluctance accelerators are used to apply linear forces to ferromagnetic projectiles via solenoids. Ef ciency increases for a single-stage reluctance accelerator were produced by manipulating the input current pulse supplied by a discharging capacitor. The development of a theoretical model allowed for the calculation of optimized pulse shapes. A digital pulsewidth modulated switching method was used to control the current pulse shape using an Arduino Uno microcontroller, which supplied signals to the gate of a MOSFET transistor that controlled the current to the system solenoid. An ef ciency increase of 5.7% was obtained for a reluctance accelerator with an optimized current pulse shape in comparison to a capacitor discharge with no pulse shapin

T2 mapping outperforms normalised FLAIR in identifying hippocampal sclerosis

Rationale Qualitatively, FLAIR MR imaging is sensitive to the detection of hippocampal sclerosis (HS). Quantitative analysis of T2 maps provides a useful objective measure and increased sensitivity over visual inspection of T2-weighted scans. We aimed to determine whether quantification of normalised FLAIR is as sensitive as T2 mapping in detection of HS. Method Dual echo T2 and FLAIR MR images were retrospectively analysed in 27 patients with histologically confirmed HS and increased T2 signal in ipsilateral hippocampus and 14 healthy controls. Regions of interest were manually segmented in all hippocampi aiming to avoid inclusion of CSF. Hippocampal T2 values and measures of normalised FLAIR Signal Intensity (nFSI) were compared in healthy and sclerotic hippocampi. Results HS was identified on T2 values with 100% sensitivity and 100% specificity. HS was identified on nFSI measures with 60% sensitivity and 93% specificity. Conclusion T2 mapping is superior to nFSI for identification of HS

Electromagnetic Induction Imaging of concealed metallic objects by means of resonating circuits

An electromagnetic induction system, suitable for 2D imaging of metallic samples of different electrical conductivities, has been developed. The system is based on a parallel LCR circuit comprising a ferrite-cored coil (7.8 mm x 9.5 mm, L=680 μH at 1 KHz), a variable resistor and capacitor. The working principle of the system is based on eddy current induction inside a metallic sample when this is introduced into the AC magnetic field created by the coil. The inductance of the LCR circuit is modified due to the presence of the sample, to an extent that depends on its conductivity. Such modification is known to increase when the system is operated at its resonant frequency. Characterizing different metals based on their values of conductivity is therefore possible by utilizing a suitable system operated at resonance. Both imaging and material characterization were demonstrated by means of the proposed electromagnetic induction technique. Furthermore, the choice of using a system with an adjustable resonant frequency made it possible to select resonances that allow magnetic-field penetration through conductive screens. Investigations on the possibility of imaging concealed metals by penetrating such shields have been carried out. A penetration depth of δ~3 mm through aluminium (Al) was achieved. This allowed concealed metallic samples- having conductivities ranging from 0.54 to 59.77 MSm-1 and hidden behind 1.5-mm-thick Al shields- to be imaged. Our results demonstrate that the presence of the concealed metallic objects can be revealed. The technique was thus shown to be a promising detection tool for security applications

Teaching and learning clinical reasoning: tutors' perceptions of change in their own clinical practice

BACKGROUND: Clinical reasoning is an important skill for all clinicians and historically has rarely been formally taught either at undergraduate or postgraduate level. Clinical reasoning is taught as a formal course in the fourth year of the undergraduate programme at Keele School of Medicine by tutors who are all practicing general practitioners. AIM: We aimed to explore the tutors' perceptions about how teaching on the course has impacted on their own consultation skills. DESIGN AND SETTING: All 11 course tutors who had taught on the course for at least one full academic year were invited to take part in recorded individual semi-structured interviews with an experienced, non-clinical, qualitative researcher. The data were analysed using qualitative methods. RESULTS: Eleven tutors participated, with a range of 7 to 32 years of clinical experience. They reported better decision-making, greater use of metacognition, more self-awareness, more reflective practice, more confidence and greater job satisfaction. They also reported positive impacts on their own knowledge and learning, and assumed concomitant benefits for their patients. CONCLUSION: All clinicians in this group perceived benefits on their consultation skills as a result of teaching clinical reasoning. There is a need to provide education, training and continuing professional development in cognitive consultation skills to students, trainees and established practitioners

Learning with Biased Complementary Labels

In this paper, we study the classification problem in which we have access to easily obtainable surrogate for true labels, namely complementary labels, which specify classes that observations do \textbf{not} belong to. Let $Y$ and $\bar{Y}$ be the true and complementary labels, respectively. We first model the annotation of complementary labels via transition probabilities $P(\bar{Y}=i|Y=j), i\neq j\in\{1,\cdots,c\}$, where $c$ is the number of classes. Previous methods implicitly assume that $P(\bar{Y}=i|Y=j), \forall i\neq j$, are identical, which is not true in practice because humans are biased toward their own experience. For example, as shown in Figure 1, if an annotator is more familiar with monkeys than prairie dogs when providing complementary labels for meerkats, she is more likely to employ "monkey" as a complementary label. We therefore reason that the transition probabilities will be different. In this paper, we propose a framework that contributes three main innovations to learning with \textbf{biased} complementary labels: (1) It estimates transition probabilities with no bias. (2) It provides a general method to modify traditional loss functions and extends standard deep neural network classifiers to learn with biased complementary labels. (3) It theoretically ensures that the classifier learned with complementary labels converges to the optimal one learned with true labels. Comprehensive experiments on several benchmark datasets validate the superiority of our method to current state-of-the-art methods.Comment: ECCV 2018 Ora

Automated hippocampal segmentation in patients with epilepsy: Available free online

Hippocampal sclerosis, a common cause of refractory focal epilepsy, requires hippocampal volumetry for accurate diagnosis and surgical planning. Manual segmentation is time-consuming and subject to interrater/intrarater variability. Automated algorithms perform poorly in patients with temporal lobe epilepsy. We validate and make freely available online a novel automated method

Asking the next generation: the implementation of pre-university students' ideas about physics laboratory preparation exercises

It was planned to introduce online pre-laboratory session activities to a first-year undergraduate physics laboratory course to encourage a minimum level of student preparation for experiments outside the laboratory environment. A group of 16 and 17 year old laboratory work-experience students were tasked to define and design a pre-laboratory activity based on experiments that they had been undertaking. This informed the structure, content and aims of the activities introduced to a first year physics undergraduate laboratory course, with the particular focus on practising the data handling. An implementation study showed how students could try to optimise high grades, rather than gain efficiency-enhancing experience if careful controls were not put in place by assessors. However, the work demonstrated that pre-university and first-year physics students can take an active role in developing scaffolding activities that can help to improve the performance of those that follow their footsteps

Magnetic Imaging through Metallic Enclosures

Security applications may require the ability to image through electromagnetic shields. This is for example the case when trafficking of illicit material involves cargo containers. Thus, suitable detection techniques are required to penetrate a ferromagnetic enclosure. We report on the demonstration of the ability of a system based on electromagnetic interrogation techniques to create magnetic images of metallic objects concealed within metallic enclosures. The penetrating power through single and double ferromagnetic enclosures was investigated. The instrument employs a driver Helmholtz-coil assembly and an array of 20 × 20 sensor coils. The sample objects were imaged via phase variation measurements between the driver and sensor coils, due to inductive coupling between the coils and the sample object

Recent population trends of African penguins Spheniscus demersus in Namibia

The African penguin Spheniscus demersus is endemic to southern Africa and is listed overall as “vulnerable”. Over the past century, however, the Namibian population has been severely reduced and is currently listed as “critically endangered”. Recent trends at Possession, Halifax, Ichaboe and Mercury islands, which account for 97% of the Namibian population, were examined using counts of moulting adults and active nests at peak breeding. Since 1996, the adult population has decreased at a rate of 2.6% per year. Since 1990, the breeding population has decreased by 3.7% per year. Mercury Island is the only Namibian breeding site where penguin numbers are increasing. Improving the conservation status of the species is critical. Better management strategies need to be identified and implemented.Keywords: African penguin, census methods, conservation management, Namibia, population estimates, population trends, Spheniscus demersusAfrican Journal of Marine Science 2001, 23: 429–43

Discrepancies in central review re-testing of patients with ER-positive and HER2-negative breast cancer in the OPTIMA prelim randomised clinical trial

BACKGROUND: There is limited data on results of central re-testing of samples from patients with invasive breast cancer categorised in their local hospital laboratories as oestrogen receptor (ER) positive and human epidermal growth factor receptor homologue 2 (HER2) negative. METHODS: The Optimal Personalised Treatment of early breast cancer usIng Multiparameter Analysis preliminary study (OPTIMA prelim) was the feasibility phase of a randomised controlled trial to validate the use of multiparameter assay-directed chemotherapy decisions in the UK National Health Service (NHS). Eligibility criteria included ER positivity and HER2 negativity. Central re-testing of receptor status was mandatory. RESULTS: Of the 431 patients tested centrally, discrepant results between central and local laboratory results were identified in only 19 (4.4%; 95% confidence interval 2.5–6.3%) patients (with 21 tumours). On central review, seven patients had cancers that were ER-negative (1.6%) and 13 (3.0%) patients with 15 tumours had HER2-positive disease, including one tumour discrepant for both biomarkers. CONCLUSIONS: Central re-testing of receptor status of invasive breast cancers in the UK NHS setting shows a high level of reproducibility in categorising tumours as ER-positive and HER2-negative, and raises questions regarding the cost effectiveness and clinical value of central re-testing in this sub-group of breast cancers in this setting