Observations and Modelling of the Pre-flare Period of the 29 March 2014 X1 Flare

On 29 March 2014, NOAA Active Region (AR) 12017 produced an X1 flare that was simultaneously observed by an unprecedented number of observatories. We have investigated the pre-flare period of this flare from 14:00 UT until 19:00 UT using joint observations made by the Interface Region Imaging Spectrometer (IRIS) and the Hinode Extreme Ultraviolet Imaging Spectrometer (EIS). Spectral lines providing coverage of the solar atmosphere from the chromosphere to the corona were analysed to investigate pre-flare activity within the AR. The results of the investigation have revealed evidence of strongly blue-shifted plasma flows, with velocities up to 200kms−1, being observed 40 minutes prior to flaring. These flows are located along the filament present in the active region and are both spatially discrete and transient. In order to constrain the possible explanations for this activity, we undertake non-potential magnetic field modelling of the active region. This modelling indicates the existence of a weakly twisted flux rope along the polarity inversion line in the region where a filament and the strong pre-flare flows are observed. We then discuss how these observations relate to the current models of flare triggering. We conclude that the most likely drivers of the observed activity are internal reconnection in the flux rope, early onset of the flare reconnection, or tether-cutting reconnection along the filament

The secret symmetries of the AdS/CFT reflection matrices

We find new twisted Yangian symmetries of the AdS/CFT reflection matrices for the Y=0 maximal giant graviton and D5-brane. These new symmetries originate from the known secret symmetries of the Yangian symmetry of the AdS/CFT S-matrix.Comment: 9 pages, v2: published versio

Predicting Fluid Intelligence of Children using T1-weighted MR Images and a StackNet

In this work, we utilize T1-weighted MR images and StackNet to predict fluid intelligence in adolescents. Our framework includes feature extraction, feature normalization, feature denoising, feature selection, training a StackNet, and predicting fluid intelligence. The extracted feature is the distribution of different brain tissues in different brain parcellation regions. The proposed StackNet consists of three layers and 11 models. Each layer uses the predictions from all previous layers including the input layer. The proposed StackNet is tested on a public benchmark Adolescent Brain Cognitive Development Neurocognitive Prediction Challenge 2019 and achieves a mean squared error of 82.42 on the combined training and validation set with 10-fold cross-validation. In addition, the proposed StackNet also achieves a mean squared error of 94.25 on the testing data. The source code is available on GitHub.Comment: 8 pages, 2 figures, 3 tables, Accepted by MICCAI ABCD-NP Challenge 2019; Added ND

Bayesian regression filter and the issue of priors

We propose a Bayesian framework for regression problems, which covers areas which are usually dealt with by function approximation. An online learning algorithm is derived which solves regression problems with a Kalman filter. Its solution always improves with increasing model complexity, without the risk of over-fitting. In the infinite dimension limit it approaches the true Bayesian posterior. The issues of prior selection and over-fitting are also discussed, showing that some of the commonly held beliefs are misleading. The practical implementation is summarised. Simulations using 13 popular publicly available data sets are used to demonstrate the method and highlight important issues concerning the choice of priors

On the reflection of magnon bound states

We investigate the reflection of two-particle bound states of a free open string in the light-cone AdS_5 x S^5 string sigma model, for large angular momentum J=J_56 and ending on a D7 brane which wraps the entire AdS_5 and a maximal S^3 of S^5. We use the superspace formalism to analyse fundamental and two-particle bound states in the cases of supersymmetry-preserving and broken-supersymmetry boundaries. We find the boundary S-matrices corresponding to bound states both in the bulk and on the boundary.Comment: 35 pages, v2: few typos and ref corrected, accepted for publication in JHE

Project evaluation “classroom of the future”

U uvjetima sve veće informatizacije društva, kada znanja postaju osnovni proizvodni resurs, od institucije škole očekuje se da zauzme ulogu predvodnika promjena. Obrazovni sustav mora biti osjetljiv i adaptabilan kako bi postao generator promjena i stalni pratitelj boljeg i kvalitetnijeg rada škole te obrazovanja kao cjeline. Danas se sve više naglašava potreba za obrazovanjem zasnovanom na metodama koje koriste informacijske i komunikacijske tehnologije zbog čega je naše istraživanje bilo usmjereno na procjenu stupnja iskorištenosti suvremenih nastavih sredstava i kvaliteta nastave u “Učionici budućnosti” gimnazije Frana Galovića u Koprivnici. Istraživanje je provedeno na 52 nastavnika navedene škole s ciljem ocjene trenutnog stanja u vezi sa stupnjem korištenja informacijskih tehnologija u nastavi te efektima njihove primjene. To je tek preliminarno istraživanje koje otvara mogućnosti za daljnja istraživanja o suvremenim metodama poučavanja baziranim na korištenju novih informacijskih tehnologija. Dobiveni rezultati upućuju na promišljanje o uspješnosti i kvaliteti korištenja informacijske i komunikacijske tehnologije, praćenje napretka te nude prijedloga od strane nastavnika za njihov daljnji razvoj.In terms of increasing computerization of society, where knowledge is becoming a basic production resource, it is expected that the school as an educational institution takes a leading role in these changes. The education system must be responsive and adaptive to become a generator of change and constant companion of a high quality school work and education as a whole. Today, the need for education based on methods that use information and communication technology is more and more emphasized, which is why our research was focused on evaluating the degree of utilization of modern means of teaching and the quality of teaching in the “classroom of the future” of the Gymnasium Fran Galović in Koprivnica. The study involved 52 teachers of the mentioned school in order to evaluate the current situation in relation to the degree of use of information technology in teaching and the effects of their use. It is only a preliminary study that opens up opportunities for further research in modern teaching methods based on the use of new information technologies. The results indicate reflection on the success and quality of the information and communication technology, tracking progress and offer suggestions from teachers for their further development

Yangian symmetry of boundary scattering in AdS/CFT and the explicit form of bound state reflection matrices

The reflection matrices of multi magnon bound states are obtained explicitely by exploiting the Yangian symmetry of boundary scattering on the Y=0 maximal giant graviton brane.Comment: 13 page

Reflection algebra, Yangian symmetry and bound-states in AdS/CFT

We present the `Heisenberg picture' of the reflection algebra by explicitly constructing the boundary Yangian symmetry of an AdS/CFT superstring which ends on a boundary with non-trivial degrees of freedom and which preserves the full bulk Lie symmetry algebra. We also consider the spectrum of bulk and boundary states and some automorphisms of the underlying algebras.Comment: 31 page, 8 figures. Updated versio

Optimal measurement of visual motion across spatial and temporal scales

Sensory systems use limited resources to mediate the perception of a great variety of objects and events. Here a normative framework is presented for exploring how the problem of efficient allocation of resources can be solved in visual perception. Starting with a basic property of every measurement, captured by Gabor's uncertainty relation about the location and frequency content of signals, prescriptions are developed for optimal allocation of sensors for reliable perception of visual motion. This study reveals that a large-scale characteristic of human vision (the spatiotemporal contrast sensitivity function) is similar to the optimal prescription, and it suggests that some previously puzzling phenomena of visual sensitivity, adaptation, and perceptual organization have simple principled explanations.Comment: 28 pages, 10 figures, 2 appendices; in press in Favorskaya MN and Jain LC (Eds), Computer Vision in Advanced Control Systems using Conventional and Intelligent Paradigms, Intelligent Systems Reference Library, Springer-Verlag, Berli

Bounded Rational Decision-Making with Adaptive Neural Network Priors

Bounded rationality investigates utility-optimizing decision-makers with limited information-processing power. In particular, information theoretic bounded rationality models formalize resource constraints abstractly in terms of relative Shannon information, namely the Kullback-Leibler Divergence between the agents' prior and posterior policy. Between prior and posterior lies an anytime deliberation process that can be instantiated by sample-based evaluations of the utility function through Markov Chain Monte Carlo (MCMC) optimization. The most simple model assumes a fixed prior and can relate abstract information-theoretic processing costs to the number of sample evaluations. However, more advanced models would also address the question of learning, that is how the prior is adapted over time such that generated prior proposals become more efficient. In this work we investigate generative neural networks as priors that are optimized concurrently with anytime sample-based decision-making processes such as MCMC. We evaluate this approach on toy examples.Comment: Published in ANNPR 2018: Artificial Neural Networks in Pattern Recognitio