Theory hypothesizes that the rate of decline in linkage disequilibrium (LD) as a function of distance between markers, measured by r(2), can be used to estimate effective population size (N(e)) and how it varies over time. The development of high-density genotyping makes feasible the application of this theory and has provided an impetus to improve predictions. This study considers the impact of several developments on the estimation of N(e) using both simulated and equine high-density single-nucleotide polymorphism data, when N(e) is assumed to be constant a priori and when it is not. In all models, estimates of N(e) were highly sensitive to thresholds imposed upon minor allele frequency (MAF) and to a priori assumptions on the expected r(2) for adjacent markers. Where constant N(e) was assumed a priori, then estimates with the lowest mean square error were obtained with MAF thresholds between 0.05 and 0.10, adjustment of r(2) for finite sample size, estimation of a [the limit for r(2) as recombination frequency (c) approaches 0] and relating N(e) to c (1 - c/2). The findings for predicting N(e) from models allowing variable N(e) were much less clear, apart from the desirability of correcting for finite sample size, and the lack of consistency in estimating recent N(e) (<7 generations) where estimates use data with large c. The theoretical conflicts over how estimation should proceed and uncertainty over where predictions might be expected to fit well suggest that the estimation of N(e) when it varies be carried out with extreme caution.

Introduction Medical education is committed to promoting empathic communication. Despite this, much research indicates that empathy actually decreases as students progress through medical school. In qualitative terms, relatively little is known about this changing student relationship with the concept of empathy for patients and how teaching affects it. This study explores that knowledge gap. Methods Adopting a constructivist paradigm, we utilised a research approach new to medical education: Love and Breakup Letter Methodology. A purposive sample of 20 medical students were asked to write love and break up letters to ‘empathy for patients’. The letters were prompts for the focus group discussions that followed. Forty letters and three focus group discussions were thematically analysed. Results The three major themes were: art and artifice; empathic burden; and empathy as a virtue. Students were uncomfortable with the common practice of faking empathic statements, a problem exacerbated by the need to ‘tick the empathy box’ during examinations. Students evolved their own empathic style, progressing from rote empathic statements towards phrases which suited their individual communication practice. They also learned non‐verbal empathy from positive clinician role‐modelling. Students reported considerable empathic burden. Significant barriers to empathy were reported within the hidden curriculum, including negative role‐modelling that socialises students into having less compassion for difficult patients. Students strongly associated empathy with virtue. Conclusions Medical education should address the problem of inauthentic empathy, including faking empathic s in assessments. Educators should remember the value of non‐verbal compassionate communication. The problems of empathic burden, negative role modelling and of finding empathy difficult for challenging patients may account for some of the empathy decline reported in quantitative research. Framing empathy as a virtue may help students utilise empathy more readily when faced with patients they perceive as challenging and may promote a more authentic empathic practice.

In everyday life, feelings are important to us, influencing our decision‐making and motivating our actions. This is equally true within medicine and medical education, where feelings influence key aspects such as clinical decision‐making, empathy, resilience, professional identity, reflection, team dynamics, career choices and questions of prejudice and bias. Feelings are therefore legitimate targets in medical education research, but asking research participants to talk openly about feelings can be challenging for participants and researchers alike. Within the disciple of User Experience (UX)—a relatively new research discipline used in the world of technology—researchers also seek to understand their customer's feelings, which are central to aspects of brand loyalty and choice of software platforms. UX researchers have developed innovative ways to explore feelings, in particular through the use of Love and Breakup Methodology (LBM)—participants are asked to write love and breakup letters to the product or app under study, and the letters are then used to guide the focus group discussion that follows. Methods: In this article, we describe the theoretical underpinnings of LBM, including ontological considerations. We also consider how LBM can be successfully used in medical education research and outline how we have adapted it in our own research studies and programme evaluations. Conclusions: Love and breakup letters are creative ways of understanding participants’ positive and negative emotions about the matter under study. LBM has been utilised extensively by UX researchers in technology, but has been little used in medical education. It has rich potential to enhance research approaches to aspects of medicine that are influenced by feelings, including empathy and resilience, team working and many other aspects of professional practice. Although principally a focus group research tool, it can be adapted to other approaches, including questionnaire surveys and individual interviews.

An 86% electron mobility improvement and over 20% bm.,a, enhancement were demonstrated for a 70nm strained-Si CMOS process fabricated on SiGe virtual substrates. Compared to a bulk-Si CMOS process, the strained8i process delivered 95% higher inverter peak-current and a 2.2 ps reduction in ring oscillator delay for the same drive current. Strained and bulk CMOS featured equivalent gate leakage through a 16A nitrided oxide, which remained the dominant leakage source despite dislocation-induced junction leakage observed on strained-Si wafen. Self-heating of strained3 CMOS due to the low thermal conductivity SiGe virtual substrate reduces Id..,., by 7% during DC operation.