Relational Operant Skills Training Increases Standardized Matrices Scores in Adolescents: A Stratified Active-Controlled Trial

In recent years, small-scale studies have suggested that we may be able to substantially strengthen children's general cognitive abilities and intelligence quotient (IQ) scores using a relational operant skills training program (SMART). Only one of these studies to date has included an active Control Condition, and that study reported the smallest mean IQ rise. The present study is a larger stratified active-controlled trial to independently test the utility of SMART training for raising Non-verbal IQ (NVIQ) and processing speed. We measured personality traits, NVIQs, and processing speeds of a cohort of school pupils (aged 12–15). Participants were allocated to either a SMART intervention group or a Scratch computer coding control group, for a period of 3 months. We reassessed pupils’ NVIQs and processing speeds after the 3-month intervention. We observed a significant mean increase in the SMART training group’s (final nexp = 43) NVIQs of 5.98 points, while there was a nonsignificant increase of 1.85 points in the Scratch active-control group (final ncont = 27). We also observed an increase in processing speed across both conditions (final nexp = 70; ncont = 55) over Time. Our results suggest that relational skills training may be useful for improving performance on matrices tasks, and perhaps in future, accelerating children’s progression toward developmental milestones

Campus Mobility for the Future: The Electric Bicycle

Sustainable and practical personal mobility solutions for campus environments have traditionally revolved around the use of bicycles, or provision of pedestrian facilities. However many campus environments also experience traffic congestion, parking difficulties and pollution from fossil-fuelled vehicles. It appears that pedal power alone has not been sufficient to supplant the use of petrol and diesel vehicles to date, and therefore it is opportune to investigate both the reasons behind the continual use of environmentally unfriendly transport, and consider potential solutions. This paper presents the results from a year-long study into electric bicycle effectiveness for a large tropical campus, identifying barriers to bicycle use that can be overcome through the availability of public use electric bicycles

Eliminating ambiguities for quantum corrections to strings moving in AdS4×CP3AdS_4\times \mathbb{CP}^3

We apply a physical principle, previously used to eliminate ambiguities in quantum corrections to the 2 dimensional kink, to the case of spinning strings moving in $AdS_4\times \mathbb{CP}^3$, thought of as another kind of two dimensional soliton. We find that this eliminates the ambiguities and selects the result compatible with AdS/CFT, providing a solid foundation for one of the previous calculations, which found agreement. The method can be applied to other classical string "solitons".Comment: 18 pages, latex; references added, comments added at end of section 4, a few words changed; footnote added on page 1

Improved i-Vector Representation for Speaker Diarization

This paper proposes using a previously well-trained deep neural network (DNN) to enhance the i-vector representation used for speaker diarization. In effect, we replace the Gaussian Mixture Model (GMM) typically used to train a Universal Background Model (UBM), with a DNN that has been trained using a different large scale dataset. To train the T-matrix we use a supervised UBM obtained from the DNN using filterbank input features to calculate the posterior information, and then MFCC features to train the UBM instead of a traditional unsupervised UBM derived from single features. Next we jointly use DNN and MFCC features to calculate the zeroth and first order Baum-Welch statistics for training an extractor from which we obtain the i-vector. The system will be shown to achieve a significant improvement on the NIST 2008 speaker recognition evaluation (SRE) telephone data task compared to state-of-the-art approaches

On the Fermionic Frequencies of Circular Strings

We revisit the semiclassical computation of the fluctuation spectrum around different circular string solutions in AdS_5xS^5 and AdS_4xCP^3, starting from the Green-Schwarz action. It has been known that the results for these frequencies obtained from the algebraic curve and from the worldsheet computations sometimes do not agree. In particular, different methods give different results for the half-integer shifts in the mode numbers of the frequencies. We find that these discrepancies can be removed if one carefully takes into account the transition matrices in the spin bundle over the target space.Comment: 13 pages, 1 figur

Kaluza-Klein gauge and minimal integrable extension of OSp(4|6)/(SO(1,3) x U(3)) sigma-model

Basing upon experience from performing double-dimensional reduction of the D=11 supermembrane on AdS_4 x S^7 background to Type IIA superstring on AdS_4 x CP^3 we introduce Kaluza-Klein (partial) kappa-symmetry gauge as a vanishing condition of the contribution to the D=11 supervielbein components tangent to D=10 space-time proportional to the differential of the coordinate parametrizing compact 11-th space-time dimension, that is identified with the supermembrane world-volume compact dimension. For AdS_4 x S^7 supermembrane Kaluza-Klein gauge removes half Grassmann coordinates associated with 8 space-time supersymmetries, broken by the AdS_4 x CP^3 superbackground, by imposing D=3 (anti-)Majorana condition on them. The consideration relies on the realization of osp(4|8) isometry superalgebra of the AdS_4 x S^7 superbackground as D=3 N=8 superconformal algebra. Requiring further vanishing of the D=10 dilaton leaves in the sector of broken supersymmetries just two Grassmann coordinates organized into D=3 (anti-)Majorana spinor that defines minimal SL(2,R)-covariant extension of the OSp(4|6)/(SO(1,3)x U(3)) sigma-model. Among 4 possibilities of such a minimal extension we consider in detail one, that corresponds to picking out D=3 Majorana coordinate related to broken Poincare supersymmetry, and show that the AdS_4 x CP^3 superstring equations of motion in this partial kappa-symmetry gauge are integrable. Also the relation between the OSp(4|6)/(SO(1,3) x U(3)) sigma-model and the AdS_4 x CP^3 superstring is revisited.Comment: LaTeX, 22 pages; v2: minor improvements in the text, typos corrected, references adde

Outcomes from COVID-19 across the range of frailty: excess mortality in fitter older people

Purpose: Our aim was to quantify the mortality from COVID-19 and identify any interactions with frailty and other demographic factors. / Methods: Hospitalised patients aged ≥ 70 were included, comparing COVID-19 cases with non-COVID-19 controls admitted over the same period. Frailty was prospectively measured and mortality ascertained through linkage with national and local statutory reports. / Results: In 217 COVID-19 cases and 160 controls, older age and South Asian ethnicity, though not socioeconomic position, were associated with higher mortality. For frailty, differences in effect size were evident between cases (HR 1.02, 95% CI 0.93–1.12) and controls (HR 1.99, 95% CI 1.46–2.72), with an interaction term (HR 0.51, 95% CI 0.37–0.71) in multivariable models. / Conclusions: Our findings suggest that (1) frailty is not a good discriminator of prognosis in COVID-19 and (2) pathways to mortality may differ in fitter compared with frailer older patients

Towards More Accurate Automatic Sleep Staging via Deep Transfer Learning.

BACKGROUND: Despite recent significant progress in the development of automatic sleep staging methods, building a good model still remains a big challenge for sleep studies with a small cohort due to the data-variability and data-inefficiency issues. This work presents a deep transfer learning approach to overcome these issues and enable transferring knowledge from a large dataset to a small cohort for automatic sleep staging. METHODS: We start from a generic end-to-end deep learning framework for sequence-to-sequence sleep staging and derive two networks as the means for transfer learning. The networks are first trained in the source domain (i.e. the large database). The pretrained networks are then finetuned in the target domain (i.e. the small cohort) to complete knowledge transfer. We employ the Montreal Archive of Sleep Studies (MASS) database consisting of 200 subjects as the source domain and study deep transfer learning on three different target domains: the Sleep Cassette subset and the Sleep Telemetry subset of the Sleep-EDF Expanded database, and the Surrey-cEEGrid database. The target domains are purposely adopted to cover different degrees of data mismatch to the source domains. RESULTS: Our experimental results show significant performance improvement on automatic sleep staging on the target domains achieved with the proposed deep transfer learning approach. CONCLUSIONS: These results suggest the efficacy of the proposed approach in addressing the above-mentioned data-variability and data-inefficiency issues. SIGNIFICANCE: As a consequence, it would enable one to improve the quality of automatic sleep staging models when the amount of data is relatively small

Two-loop Integrability of Planar N=6 Superconformal Chern-Simons Theory

Bethe ansatz equations have been proposed for the asymptotic spectral problem of AdS_4/CFT_3. This proposal assumes integrability, but the previous verification of weak-coupling integrability covered only the su(4) sector of the ABJM gauge theory. Here we derive the complete planar two-loop dilatation generator of N=6 superconformal Chern-Simons theory from osp(6|4) superconformal symmetry. For the osp(4|2) sector, we prove integrability through a Yangian construction. We argue that integrability extends to the full planar two-loop dilatation generator, confirming the applicability of the Bethe equations at weak coupling. Further confirmation follows from an analytic computation of the two-loop twist-one spectrum.Comment: 45 pages, v2: typos in (D.9) fixed, reference added, many small change

Weakly coupled N=4 Super Yang-Mills and N=6 Chern-Simons theories from u(2|2) Yangian symmetry

In this paper we derive the universal R-matrix for the Yangian Y(u(2|2)), which is an abstract algebraic object leading to rational solutions of the Yang-Baxter equation on representations. We find that on the fundamental representation the universal R-matrix reduces to the standard rational R-matrix R = R_0(1 + P/u), where the scalar prefactor is surprisingly simple compared to prefactors one finds e.g. for sl(n) R-matrices. This leads precisely to the S-matrix giving the Bethe Ansatz of one-loop N = 4 Super Yang-Mills theory and two-loop N = 6 Chern-Simons theory.Comment: 16 page