Statistical coverage for supersymmetric parameter estimation: a case study with direct detection of dark matter

Models of weak-scale supersymmetry offer viable dark matter (DM) candidates. Their parameter spaces are however rather large and complex, such that pinning down the actual parameter values from experimental data can depend strongly on the employed statistical framework and scanning algorithm. In frequentist parameter estimation, a central requirement for properly constructed confidence intervals is that they cover true parameter values, preferably at exactly the stated confidence level when experiments are repeated infinitely many times. Since most widely-used scanning techniques are optimised for Bayesian statistics, one needs to assess their abilities in providing correct confidence intervals in terms of the statistical coverage. Here we investigate this for the Constrained Minimal Supersymmetric Standard Model (CMSSM) when only constrained by data from direct searches for dark matter. We construct confidence intervals from one-dimensional profile likelihoods and study the coverage by generating several pseudo-experiments for a few benchmark sets of pseudo-true parameters. We use nested sampling to scan the parameter space and evaluate the coverage for the benchmarks when either flat or logarithmic priors are imposed on gaugino and scalar mass parameters. The sampling algorithm has been used in the configuration usually adopted for exploration of the Bayesian posterior. We observe both under- and over-coverage, which in some cases vary quite dramatically when benchmarks or priors are modified. We show how most of the variation can be explained as the impact of explicit priors as well as sampling effects, where the latter are indirectly imposed by physicality conditions. For comparison, we also evaluate the coverage for Bayesian credible intervals, and observe significant under-coverage in those cases.Comment: 30 pages, 5 figures; v2 includes major updates in response to referee's comments; extra scans and tables added, discussion expanded, typos corrected; matches published versio

Quantifying impacts of short-term plasticity on neuronal information transfer

Short-term changes in efficacy have been postulated to enhance the ability of synapses to transmit information between neurons, and within neuronal networks. Even at the level of connections between single neurons, direct confirmation of this simple conjecture has proven elusive. By combining paired-cell recordings, realistic synaptic modelling and information theory, we provide evidence that short-term plasticity can not only improve, but also reduce information transfer between neurons. We focus on a concrete example in rat neocortex, but our results may generalise to other systems. When information is contained in the timings of individual spikes, we find that facilitation, depression and recovery affect information transmission in proportion to their impacts upon the probability of neurotransmitter release. When information is instead conveyed by mean spike rate only, the influences of short-term plasticity critically depend on the range of spike frequencies that the target network can distinguish (its effective dynamic range). Our results suggest that to efficiently transmit information, the brain must match synaptic type, coding strategy and network connectivity during development and behaviour.Comment: Accepted for publication in Phys Rev E. 42 pages in referee format, 9 figure

The study of reproductive outcome and the health of offspring of UK veterans of the Gulf war: methods and description of the study population

BACKGROUND: The aim of this study is to determine whether Gulf war veterans and their partners are at increased risk of adverse reproductive events and whether their children have increased risk of serious health problems. Methods and response to the study are reported here. METHODS: This was a retrospective cohort study of reproduction among UK Gulf war veterans, with a comparison cohort of Armed Service personnel who were not deployed to the Gulf. Reproductive history and details of children's health was collected by means of a validated postal questionnaire. A separate study of non-responders was conducted. RESULTS: Questionnaires were returned by a total of 25,084 Gulf war veterans (24,379 men) and 19,003 (18,439 men) subjects in the comparison group. After adjusting for undelivered mail the response rate was 53% for Gulf war veterans and 42% for non-Gulf veterans among men, 72% and 60% among women. Data from the non-responder study suggests that failure to respond to the main survey was largely unrelated to reproduction. 11,155 (46%) male Gulf war veterans and 7,769 (42%) male non-Gulf war veterans had conceived, or attempted to conceive, since the Gulf war. They reported 16442 and 11517 pregnancies respectively in that period. For women, 313 (44%) Gulf veterans and 235 (42%) non-Gulf veterans reported 484 and 377 pregnancies respectively conceived since the Gulf war. CONCLUSIONS: This survey enabled collection of information on a range of reproductive outcomes from veterans of the Gulf war and a suitably matched comparison cohort. Although the response rate for men was disappointing, selection bias related to reproduction does not appear to be strong in these data

A Profile Likelihood Analysis of the Constrained MSSM with Genetic Algorithms

The Constrained Minimal Supersymmetric Standard Model (CMSSM) is one of the simplest and most widely-studied supersymmetric extensions to the standard model of particle physics. Nevertheless, current data do not sufficiently constrain the model parameters in a way completely independent of priors, statistical measures and scanning techniques. We present a new technique for scanning supersymmetric parameter spaces, optimised for frequentist profile likelihood analyses and based on Genetic Algorithms. We apply this technique to the CMSSM, taking into account existing collider and cosmological data in our global fit. We compare our method to the MultiNest algorithm, an efficient Bayesian technique, paying particular attention to the best-fit points and implications for particle masses at the LHC and dark matter searches. Our global best-fit point lies in the focus point region. We find many high-likelihood points in both the stau co-annihilation and focus point regions, including a previously neglected section of the co-annihilation region at large m_0. We show that there are many high-likelihood points in the CMSSM parameter space commonly missed by existing scanning techniques, especially at high masses. This has a significant influence on the derived confidence regions for parameters and observables, and can dramatically change the entire statistical inference of such scans.Comment: 47 pages, 8 figures; Fig. 8, Table 7 and more discussions added to Sec. 3.4.2 in response to referee's comments; accepted for publication in JHE

The assessment of pain in older people: UK National Guidelines

We are facing a huge increase in the older population over the next 30 years. This brings an anticipated increase in the prevalence of chronic pain and with this comes the challenge of assessment of pain in many varied settings. Our first iteration of this document was published in 2007. But there has been a proliferation of literature and research since then, so we have developed a new set of guidelines. Different patterns and sites of pain were seen in men and women. Age differences suggest that pain prevalence increased with age up to 85 years and then decreased. The available studies on barriers and attitudes to pain management point towards an adherence to bio-medically orientated beliefs about pain, concern amongst clinicians in relation to activity recommendations, and a negative orientation in general towards patients with chronic painful conditions. A multidisciplinary approach to the assessment and treatment of pain is essential, but the assessment is a complex process which is hampered by many communication issues, including cognitive ability and socio-cultural factors. Such issues are part of the UK ageing population. Structured pain education should be implemented that provides all health professionals (whether professionally or non-professionally trained) with standardised education and training in the assessment and management of pain according to level of experience. Although subjective, patient self-report is the most valid and reliable indicator of pain and it may be necessary to ask questions about pain in different ways in order to elicit a response. A number of valid and reliable self-report measures are available and can be used even when moderate dementia exists. The Numerical Rating Scale or verbal descriptors can be used with people who have mild to moderate cognitive impairment. For people with severe cognitive impairment Pain in Advanced Dementia (PAINAD) and Doloplus-2 are recommended. PAINAD and Doloplus-2 scales continue to show positive results in terms of reliability and validity. There has been no recent evaluation of the Abbey pain scale although it is widely used throughout the UK. There is a need for more research into pain assessment using the collaborative role of the multidisciplinary team in all care settings. Self-report questionnaires of function are limited in their ability to capture the fluctuations in capacity and ability. The concentration on items of relevance to the population of interest means that issues of personal relevance can be obscured. Strong associations were seen between pain and depressed mood with each being a risk factor for the other. Additionally, loneliness and social isolation were associated with an increased risk of pain. Clinicians should be cognisant that social isolation and or depressive signs and symptoms may be indicators of pre-existing pain or a predictor of future pain onset. There are a number of evidence based guidelines on pain assessment in older people with or without cognitive impairment from around the world, including Australia and Europe

The National Early Warning Score and its subcomponents recorded within ±24 hours of emergency medical admission are poor predictors of hospital-acquired acute kidney injury

YesBackground: Hospital-acquired Acute Kidney Injury (H-AKI) is a common cause of avoidable morbidity and mortality. Aim: To determine if the patients’ vital signs data as defined by a National Early Warning Score (NEWS), can predict H-AKI following emergency admission to hospital. Methods: Analyses of emergency admissions to York hospital over 24-months with NEWS data. We report the area under the curve (AUC) for logistic regression models that used the index NEWS (model A0), plus age and sex (A1), plus subcomponents of NEWS (A2) and two-way interactions (A3). Likewise for maximum NEWS (models B0,B1,B2,B3). Results: 4.05% (1361/33608) of emergency admissions had H-AKI. Models using the index NEWS had the lower AUCs (0.59 to 0.68) than models using the maximum NEWS AUCs (0.75 to 0.77). The maximum NEWS model (B3) was more sensitivity than the index NEWS model (A0) (67.60% vs 19.84%) but identified twice as many cases as being at risk of H-AKI (9581 vs 4099) at a NEWS of 5. Conclusions: The index NEWS is a poor predictor of H-AKI. The maximum NEWS is a better predictor but seems unfeasible because it is only knowable in retrospect and is associated with a substantial increase in workload albeit with improved sensitivity.The Health Foundatio