Magnetotransport near a quantum critical point in a simple metal

We use geometric considerations to study transport properties, such as the conductivity and Hall coefficient, near the onset of a nesting-driven spin density wave in a simple metal. In particular, motivated by recent experiments on vanadium-doped chromium, we study the variation of transport coefficients with the onset of magnetism within a mean-field treatment of a model that contains nearly nested electron and hole Fermi surfaces. We show that most transport coefficients display a leading dependence that is linear in the energy gap. The coefficient of the linear term, though, can be small. In particular, we find that the Hall conductivity $\sigma_{xy}$ is essentially unchanged, due to electron-hole compensation, as the system goes through the quantum critical point. This conclusion extends a similar observation we made earlier for the case of completely flat Fermi surfaces to the immediate vicinity of the quantum critical point where nesting is present but not perfect.Comment: 11 pages revtex, 4 figure

A deep neural network application for improved prediction of HbA1c in type 1 diabetes

HbA1c is a primary marker of long-term average blood glucose, which is an essential measure of successful control in type 1 diabetes. Previous studies have shown that HbA1c estimates can be obtained from 5- 12 weeks of daily blood glucose measurements. However, these methods suffer from accuracy limitations when applied to incomplete data with missing periods of measurements. The aim of this work is to overcome these limitations improving the accuracy and robustness of HbA1c prediction from time series of blood glucose. A novel data-driven HbA1c prediction model based on deep learning and convolutional neural networks is presented. The model focuses on the extraction of behavioral patterns from sequences of self-monitored blood glucose readings on various temporal scales. Assuming that subjects who share behavioral patterns have also similar capabilities for diabetes control and resulting HbA1c, it becomes possible to infer the HbA1c of subjects with incomplete data from multiple observations of similar behaviors. Trained and validated on a dataset, containing 1543 real world observation epochs from 759 subjects, the model has achieved the mean absolute error of 4.80±0.62 mmol/mol, median absolute error of 3.81±0.58 mmol/mol and R2 of 0.71±0.09 on average during the 10 fold cross validation. Automatic behavioral characterization via extraction of sequential features by the proposed convolutional neural network structure has significantly improved the accuracy of HbA1c prediction compared to the existing methods

Facilitator, Functionary, Friend or Foe? Studying the Role of iPads within Learning Activities Across a School Year

We present the findings from a longitudinal study of iPad use in a Primary school classroom. While tablet devices have found their way into classroom environments, we still lack in depth and long-term studies of how they integrate into everyday classroom activities. Our findings illustrate in-classroom tablet use and the broad range of learning activities in subjects such as maths, languages, social sciences, and even physical education. Our observations expand current models on teaching and learning supported by tablet technology. Our findings are child-centred, focusing on three different roles that tablets can play as part of learning activities: Friend, Functionary, and Facilitator. This new perspective on in-classroom tablet use can facilitate critical discussions around the integration and impact of these devices in the educational context, from a design and educational point of view

Metabolome-wide association study on ABCA7 indicates a role of ceramide metabolism in Alzheimer’s disease

Genome-wide association studies (GWASs) have identified genetic loci associated with the risk of Alzheimer’s disease (AD), but the molecular mechanisms by which they confer risk are largely unknown. We conducted a metabolome-wide association study (MWAS) of AD-associated loci from GWASs using untargeted metabolic profiling (metabolomics) by ultraperformance liquid chromatography–mass spectrometry (UPLC-MS). We identified an association of lactosylceramides (LacCer) with AD-related single-nucleotide polymorphisms (SNPs) in ABCA7 (P = 5.0 × 10−5 to 1.3 × 10−44). We showed that plasma LacCer concentrations are associated with cognitive performance and genetically modified levels of LacCer are associated with AD risk. We then showed that concentrations of sphingomyelins, ceramides, and hexosylceramides were altered in brain tissue from Abca7 knockout mice, compared with wild type (WT) (P = 0.049–1.4 × 10−5), but not in a mouse model of amyloidosis. Furthermore, activation of microglia increases intracellular concentrations of hexosylceramides in part through induction in the expression of sphingosine kinase, an enzyme with a high control coefficient for sphingolipid and ceramide synthesis. Our work suggests that the risk for AD arising from functional variations in ABCA7 is mediated at least in part through ceramides. Modulation of their metabolism or downstream signaling may offer new therapeutic opportunities for AD

Development and application of simulation modelling for orthopaedic elective resource planning in England

Objectives This study aimed to develop a simulation model to support orthopaedic elective capacity planning. Methods An open-source, generalisable discrete-event simulation was developed, including a web-based application. The model used anonymised patient records between 2016 and 2019 of elective orthopaedic procedures from a National Health Service (NHS) Trust in England. In this paper, it is used to investigate scenarios including resourcing (beds and theatres) and productivity (lengths of stay, delayed discharges and theatre activity) to support planning for meeting new NHS targets aimed at reducing elective orthopaedic surgical backlogs in a proposed ring-fenced orthopaedic surgical facility. The simulation is interactive and intended for use by health service planners and clinicians. Results A higher number of beds (65–70) than the proposed number (40 beds) will be required if lengths of stay and delayed discharge rates remain unchanged. Reducing lengths of stay in line with national benchmarks reduces bed utilisation to an estimated 60%, allowing for additional theatre activity such as weekend working. Further, reducing the proportion of patients with a delayed discharge by 75% reduces bed utilisation to below 40%, even with weekend working. A range of other scenarios can also be investigated directly by NHS planners using the interactive web app. Conclusions The simulation model is intended to support capacity planning of orthopaedic elective services by identifying a balance of capacity across theatres and beds and predicting the impact of productivity measures on capacity requirements. It is applicable beyond the study site and can be adapted for other specialties

Field measurements of horizontal forward motion velocities of terrestrial dust devils: towards a proxy for ambient winds on Mars and Earth

Dust devils – convective vortices made visible by the dust and debris they entrain – are common in arid environments and have been observed on Earth and Mars. Martian dust devils have been identified both in images taken at the surface and in remote sensing observations from orbiting spacecraft. Observations from landing craft and orbiting instruments have allowed the dust devil translational forward motion (ground velocity) to be calculated, but it is unclear how these velocities relate to the local ambient wind conditions, for (i) only model wind speeds are generally available for Mars, and (ii) on Earth only anecdotal evidence exists that compares dust devil ground velocity with ambient wind velocity. If dust devil ground velocity can be reliably correlated to the ambient wind regime, observations of dust devils could provide a proxy for wind speed and direction measurements on Mars. Hence, dust devil ground velocities could be used to probe the circulation of the martian boundary layer and help constrain climate models or assess the safety of future landing sites. We present results from a field study of terrestrial dust devils performed in the southwest USA in which we measured dust devil horizontal velocity as a function of ambient wind velocity. We acquired stereo images of more than a hundred active dust devils and recorded multiple size and position measurements for each dust devil. We used these data to calculate dust devil translational velocity. The dust devils were within a study area bounded by 10 m high meteorology towers such that dust devil speed and direction could be correlated with the local ambient wind speed and direction measurements. Daily (10:00 to 16:00 local time) and two-hour averaged dust devil ground speeds correlate well with ambient wind speeds averaged over the same period. Unsurprisingly, individual measurements of dust devil ground speed match instantaneous measurements of ambient wind speed more poorly; a 20-minute smoothing window applied to the ambient wind speed data improves the correlation. In general, dust devils travel 10-20% faster than ambient wind speed measured at 10 m height, suggesting that their ground speeds are representative of the boundary layer winds a few tens of meters above ground level. Dust devil ground motion direction closely matches the measured ambient wind direction. The link between ambient winds and dust devil ground velocity demonstrated here suggests that a similar one should apply on Mars. Determining the details of the martian relationship between dust devil ground velocity and ambient wind velocity might require new in-situ or modelling studies but, if completed successfully, would provide a quantitative means of measuring wind velocities on Mars that would otherwise be impossible to obtain

The Structure of Interpretations in Family Therapy: A Video-Enhanced Exploration *

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/73991/1/j.1545-5300.2000.39204.x.pd