Social Networking for Learning in Higher Education: Capitalising on Social Capital

YesThis study explores the evolution of student-led social networking groups initiated and sustained by a cohort of undergraduate students over a 3-year time frame. The study contributes to this growing area of research by exploring the impact of peer-led, peer-supported informal learning through social media networks. Social capital is a useful lens through which to understand the findings, and particularly in interpreting descriptions of the evolution of the group over time. The findings suggest that students build bridging social capital to support the transition into higher education, form relationships and learn collaboratively through a large cohort-based Facebook group. Over time, this form of social capital and the use of the Facebook group declines due to a lack of perceived reciprocity and an increased perception of competitiveness amongst peers. However, there is accompanied by a subsequent rise in the building of bonding social capital between closer peer relationships facilitated through the use of various WhatsApp groups. The findings have implications for considering how social networking might support the student journey towards more nuanced, more personalised collaborative learning and a move towards more self-directed learning

Variable expressivity of a novel mutation in the SCN1A gene leading to an autosomal dominant seizure disorder

AbstractMutations in the SCN1A gene can cause a variety of dominantly inherited epilepsy syndromes. Severe phenotypes usually result from loss of function mutations, whereas missense mutations cause a milder phenotype by altering the sodium channel activity. We report on a novel missense variant (p.Val1379Leu) in the SCN1A gene segregating in an autosomal dominant pattern in a family exhibiting a variable epilepsy phenotype ranging from generalized epilepsy with febrile seizures during infancy to a well controlled seizure disorder in adulthood. This report supports the importance of SCN1A mutation analysis in families in which seizure disorders segregate in an autosomal dominant fashion

Effective potential and stability of the rigid membrane

The calculation of the effective potential for fixed-end and toroidal rigid $p$-branes is performed in the one-loop as well as in the $1/d$ approximations. The analysis of the involved zeta-functions (of inhomogeneous Epstein type) which appear in the process of regularization is done in full detail. Assymptotic formulas (allowing only for exponentially decreasing errors of order $\leq 10^{-3}$) are found which carry all the dependences on the basic parameters of the theory explicitly. The behaviour of the effective potential (specified to the membrane case $p=2$) is investigated, and the extrema of this effective potential are obtained.Comment: 15 PAGE

Transfer learning for galaxy morphology from one survey to another

© 2018 The Author(s). Published by Oxford University Press on behalf of the Royal Astronomical Society.Deep Learning (DL) algorithms for morphological classification of galaxies have proven very successful, mimicking (or even improving) visual classifications. However, these algorithms rely on large training samples of labelled galaxies (typically thousands of them). A key question for using DL classifications in future Big Data surveys is how much of the knowledge acquired from an existing survey can be exported to a new dataset, i.e. if the features learned by the machines are meaningful for different data. We test the performance of DL models, trained with Sloan Digital Sky Survey (SDSS) data, on Dark Energy survey (DES) using images for a sample of $\sim$5000 galaxies with a similar redshift distribution to SDSS. Applying the models directly to DES data provides a reasonable global accuracy ($\sim$ 90%), but small completeness and purity values. A fast domain adaptation step, consisting in a further training with a small DES sample of galaxies ($\sim$500-300), is enough for obtaining an accuracy > 95% and a significant improvement in the completeness and purity values. This demonstrates that, once trained with a particular dataset, machines can quickly adapt to new instrument characteristics (e.g., PSF, seeing, depth), reducing by almost one order of magnitude the necessary training sample for morphological classification. Redshift evolution effects or significant depth differences are not taken into account in this study.Peer reviewedFinal Accepted Versio

Measurement of conversion coefficients in normal and triaxial strongly deformed bands in Lu167

Internal conversion coefficients have been measured for transitions in both normal deformed and triaxial strongly deformed bands in Lu167 using the Gammasphere and ICE Ball spectrometers. The results for all in-band transitions are consistent with E2 multipolarity. Upper limits are determined for the internal conversion coefficients for linking transitions between TSD Band 2 and TSD Band 1, the nw=1 and nw=0 wobbling bands, respectively

Multiple band structures in Ta169

Rotational structures in the Ta169 nucleus were studied via the Sn124(V51, 6n) reaction. These data were obtained as a side channel of an experiment focusing on Ta171, but the sensitivity provided by the Gammasphere spectrometer proved sufficient for a significant extension of the level scheme of this rare-earth nucleus. Over 170 new transitions and four new band structures were placed in Ta169, including the intruder πi13/2 structure. Linking transitions between all of the sequences were identified, and the relative excitation energies between the different configurations were determined for the first time. The rotational sequences were interpreted within the framework of the cranked shell model

Alignments, additivity, and signature inversion in odd-odd Ta170: A comprehensive high-spin study

High-spin states (I 50) of the odd-odd nucleus Ta170 have been investigated with the Sn124(51V,5n) reaction. The resolving power of Gammasphere has allowed for the observation of eleven rotational bands (eight of which are new) and over 430 transitions (~350 of which are new) in this nucleus. Many interband transitions have been observed such that the relative spins and excitation energies of the 11 bands have been established. This is an unusual circumstance in an odd-odd study. Configurations have been assigned to most of these bands based upon features such as alignment properties, band crossings, B(M1)/B(E2) ratios, and the additivity of Routhians. A systematic study of the frequency at which normal signature ordering occurs in the πh9/2νi13/2 band has been performed and it is found that its trend is opposite to that observed in the πh11/2νi13/2 bands. A possible interpretation of these trends is discussed based on a proton-neutron interaction

Superluminous supernovae from the Dark Energy Survey

We present a sample of 21 hydrogen-free superluminous supernovae (SLSNe-I) and one hydrogen-rich SLSN (SLSN-II) detected during the five-year Dark Energy Survey (DES). These SNe, located in the redshift range 0.220 < z < 1.998, represent the largest homogeneously selected sample of SLSN events at high redshift. We present the observed g, r, i, z light curves for these SNe, which we interpolate using Gaussian processes. The resulting light curves are analysed to determine the luminosity function of SLSNe-I, and their evolutionary timescales. The DES SLSN-I sample significantly broadens the distribution of SLSN-I light-curve properties when combined with existing samples from the literature. We fit a magnetar model to our SLSNe, and find that this model alone is unable to replicate the behaviour of many of the bolometric light curves. We search the DES SLSN-I light curves for the presence of initial peaks prior to the main light-curve peak. Using a shock breakout model, our Monte Carlo search finds that 3 of our 14 events with pre-max data display such initial peaks. However, 10 events show no evidence for such peaks, in some cases down to an absolute magnitude of<−16, suggesting that such features are not ubiquitous to all SLSN-I events. We also identify a red pre-peak feature within the light curve of one SLSN, which is comparable to that observed within SN2018bsz

High-spin states in 179Au: Spectroscopy of shape-driving orbitals beyond the neutron midshell

Multiple band structures in 179Au are established from γ-ray spectroscopic measurements with Gammasphere at the Argonne Fragment Mass Analyzer. The yrast band, based on the 13/2+ proton, confirms the predicted drop in excitation energy of the prolate deformed band head as compared to the heavier isotopes. The implications for the prolate energy minimum in odd-mass Au nuclei beyond the neutron i13/2 midshell (N<102) are discussed

Measurement of the splashback feature around SZ-selected Galaxy clusters with DES, SPT, and ACT

We present a detection of the splashback feature around galaxy clusters selected using the Sunyaev–Zel’dovich (SZ) signal. Recent measurements of the splashback feature around optically selected galaxy clusters have found that the splashback radius, rsp, is smaller than predicted by N-body simulations. A possible explanation for this discrepancy is that rsp inferred from the observed radial distribution of galaxies is affected by selection effects related to the optical cluster-finding algorithms. We test this possibility by measuring the splashback feature in clusters selected via the SZ effect in data from the South Pole Telescope SZ survey and the Atacama Cosmology Telescope Polarimeter survey. The measurement is accomplished by correlating these cluster samples with galaxies detected in the Dark Energy Survey Year 3 data. The SZ observable used to select clusters in this analysis is expected to have a tighter correlation with halo mass and to be more immune to projection effects and aperture-induced biases, potentially ameliorating causes of systematic error for optically selected clusters. We find that the measured rsp for SZ-selected clusters is consistent with the expectations from simulations, although the small number of SZ-selected clusters makes a precise comparison difficult. In agreement with previous work, when using optically selected redMaPPer clusters with similar mass and redshift distributions, rsp is ∼2σ smaller than in the simulations. These results motivate detailed investigations of selection biases in optically selected cluster catalogues and exploration of the splashback feature around larger samples of SZ-selected clusters. Additionally, we investigate trends in the galaxy profile and splashback feature as a function of galaxy colour, finding that blue galaxies have profiles close to a power law with no discernible splashback feature, which is consistent with them being on their first infall into the cluster