Miracle-dz/UniFAR-FTUs huggingface dataset:
Towards an Automated Information Extraction Model from Twitter Threads during Disasters

Social media plays a vital role as a communication source during large-scale disasters. The unstructured and informal nature of such short individual posts makes it difficult to extract useful information, often due to a lack of additional context. The potential of social media threads – sequences of posts – has not been explored as a source of adding context and more information to the initiating post. In this research, we explored Twitter threads as an information source and developed an information extraction model capable of extracting relevant information from threads posted during disasters. We used a crowdsourcing platform to determine whether a thread adds more information to the initial tweet and defined disaster-related information present in these threads into six themes – event reporting, location, time, intensity, casualty and damage reports, and help calls. For these themes, we created the respective thematic lexicons from WordNet. Moreover, we developed and compared four information extraction models trained on GloVe, word2vec, bag-of-words, and thematic bag-of-words to extract and summarize the most critical information from the threads. Our results reveal that 70 percent of all threads add information to the initiating post for various disaster-related themes. Furthermore, the thematic bag-of-words information extraction model outperforms the other algorithms and models for preserving the highest number of disaster-related themes.
RR LYRAE VARIABLES IN THE LOCAL GROUP DWARF GALAXY NGC 147

We investigate the RR Lyrae (RRL) population in NGC 147, a dwarf satellite galaxy of M31 (Andromeda). We used both Thuan–Gunn g-band ground-based photometry from the literature and Hubble Space Telescope Wide Field Planetary Camera 2 archival data in the F555W and F814W passbands to investigate the pulsation properties of RRL variable candidates in NGC 147. These data sets represent the two extreme cases often found in RRL studies with respect to the phase coverage of the observations and the quality of the photometric measurements. Extensive artificial variable star tests for both cases were performed. We conclude that neither data set is sufficient to confidently determine the pulsation properties of the NGC 147 RRLs. Thus, while we can assert that NGC 147 contains RRL variables, and therefore a population older than ∼10 Gyr, it is not possible at this time to use the pulsation properties of these RRLs to study other aspects of this old population. Our results provide a good reference for gauging the completeness of RRL variable detection in future studies.
Multiparticle Wannier states and Thouless pumping of interacting bosons

The study of topological effects in physics is a hot area of research, and only recently have researchers been able to address the important issues of topological properties of interacting quantum systems. But it is still a great challenge to describe multiparticle and interaction effects. Here, we introduce the multiparticle Wannier states for interacting systems with cotranslational symmetry, which provide an orthogonal basis for constructing effective Hamiltonians for the isolated bands. We reveal how the shift of multiparticle Wannier state relates to the Chern number of the multiparticle Bloch band and study the Thouless pumping of two interacting bosons in a one-dimensional superlattice. In addition to the Thouless pumping of bound states when two bosons move unidirectionally as a whole, we describe topologically resonant tunneling when two bosons move unidirectionally, one by the other, provided the neighboring-well potential bias matches the interaction energy. Our work creates a paradigm for multiparticle topological effects and provides a way to detect topological states in interacting multiparticle systems.
GALAXIES M32 AND NGC 5102 CONFIRM A NEAR-INFRARED SPECTROSCOPIC CHRONOMETER

We present near-infrared (NIR) IRTF/SpeX spectra of the intermediate-age galaxy M32 and the post-starburst galaxy NGC 5102. We show that features from thermally pulsing asymptotic giant branch (TP-AGB) and main-sequence turnoff (MSTO) stars yield similar ages to those derived from optical spectra. The TP-AGB can dominate the NIR flux of a coeval stellar population between ∼0.1 and ∼2 Gyr, and the strong features of (especially C-rich) TP-AGB stars are useful chronometers in integrated light studies. Likewise, the Paschen series in MSTO stars is strongly dependent on age and is an indicator of a young stellar component in integrated spectra. We define four NIR spectroscopic indices to measure the strength of absorption features from both C-rich TP-AGB stars and hydrogen features in main-sequence stars, in a preliminary effort to construct a robust chronometer that probes the contributions from stars in different evolutionary phases. By comparing the values of the indices measured in M32 and NGC 5102 to those in the Maraston stellar population synthesis models for various ages and metallicities, we show that model predictions for the ages of the nuclei of M32 and NGC 5102 agree with previous results obtained from integrated optical spectroscopy and color–magnitude diagram analysis of the giant branches. The indices discriminate between an intermediate-age population of ∼3–4 Gyr, a younger population of ≲1 Gyr, and can also detect the signatures of very young ≲100 Myr populations.
Accelerating Diversity Sampling for Deep Active Learning By Low-Dimensional Representations

Selecting diverse instances for annotation is one of the key factors of successful active learning strategies. To this end, existing meth-ods often operate on high-dimensional latent representations. In this work, we propose to use the low-dimensional vector of predicted probabilities instead, which can be seamlessly integrated into existing meth-ods. We empirically demonstrate that this considerably decreases the query time, i.e., time to select an instance for annotation, while at the same time improving results. Low query times are relevant for active learning researchers, which use a (fast) oracle for simulated annotation and thus are often constrained by query time. It is also practically relevant when dealing with complex annotation tasks for which only a small pool of skilled domain experts is available for annotation with a limited time budget. Our code is available at: https://github.com/ sobermeier/low-dim-div-sampling .
THE MAGELLANIC MOPRA ASSESSMENT (MAGMA). I. THE MOLECULAR CLOUD POPULATION OF THE LARGE MAGELLANIC CLOUD

We present the properties of an extensive sample of molecular clouds in the Large Magellanic Cloud (LMC) mapped at 11 pc resolution in the CO(1–0) line. Targets were chosen based on a limiting CO flux and peak brightness as measured by the NANTEN survey. The observations were conducted with the ATNF Mopra Telescope as part of the Magellanic Mopra Assessment. We identify clouds as regions of connected CO emission and find that the distributions of cloud sizes, fluxes, and masses are sensitive to the choice of decomposition parameters. In all cases, however, the luminosity function of CO clouds is steeper than dN/dL∝L−2, suggesting that a substantial fraction of mass is in low-mass clouds. A correlation between size and linewidth, while apparent for the largest emission structures, breaks down when those structures are decomposed into smaller structures. We argue that the correlation between virial mass and CO luminosity is the result of comparing two covariant quantities, with the correlation appearing tighter on larger scales where a size–linewidth relation holds. The virial parameter (the ratio of a cloud's kinetic to self-gravitational energy) shows a wide range of values and exhibits no clear trends with the CO luminosity or the likelihood of hosting young stellar object (YSO) candidates, casting further doubt on the assumption of virialization for molecular clouds in the LMC. Higher CO luminosity increases the likelihood of a cloud harboring a YSO candidate, and more luminous YSOs are more likely to be coincident with detectable CO emission, confirming the close link between giant molecular clouds and massive star formation.
From the Fourth Color to Spin-charge Separation - Neutrinos and Spinons

We introduce the spin-charge separation mechanism to the quark-lepton unification models which consider the lepton number as the fourth color. In certain finite-density systems, quarks and leptons are decomposed into spinons and chargons, which carry the spin and charge degrees of freedom respectively. Neutrinos can be related to the spinons with respect to the electric-charge and spin separation in the early universe or other circumstances. Some effective, probably universal couplings between the spinon sector and the chargon sector are derived and a phenomenological description for the chargon condensate is proposed. It is then demonstrated that the spinon current can induce vorticity in the chargon condensate, and spinon zero modes are trapped in the vortices, forming spinon-vortex bound states. In cosmology this configuration may lead to the emission of extremely high energy neutrinos when vortices split and reconnect.
Roche volume filling and the dissolution of open star clusters

From direct N-body simulations we find that the dynamical evolution of star clusters is strongly influenced by the Roche volume filling factor. We present a parameter study of the dissolution of open star clusters with different Roche volume filling factors and different particle numbers. We study both Roche volume underfilling and overfilling models and compare with the Roche volume filling case. We find that in the Roche volume overfilling limit of our simulations two-body relaxation is no longer the dominant dissolution mechanism but the changing cluster potential. We call this mechanism “mass-loss driven dissolution” in contrast to “two-body relaxation driven dissolution” which occurs in the Roche volume underfilling regime. We have measured scaling exponents of the dissolution time with the two-body relaxation time. In this experimental study we find a decreasing scaling exponent with increasing Roche volume filling factor. The evolution of the escaper number in the Roche volume overfilling limit can be described by a log-logistic differential equation. We report the finding of a resonance condition which may play a role for the evolution of star clusters and may be calibrated by the main periodic orbit in the large island of retrograde quasiperiodic orbits in the Poincare surfaces of section. We also report on the existence of a stability curve which may be of relevance with respect to the structure of star clusters. (© 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)
Testing nonlocal gravity with Lunar Laser Ranging

We study the impact of the limit on |Ġ|/G from Lunar Laser Ranging on “nonlocal gravity”, i.e. on models of the quantum effective action of gravity that include nonlocal terms relevant in the infrared, such as the “RR” and “RT” models proposed by our group, and the Deser-Woodard (DW) model. We elaborate on the analysis of Barreira et al. [1] and we confirm their findings that (under plausible assumptions such as the absence of strong backreaction from non-linear structures), the RR model is ruled out. We also show that the mechanism of “perfect screening for free” suggested for the DW model actually does not work and the DW model is also ruled out. In contrast, the RT model passes all phenomenological consistency tests and is still a viable candidate.
The SED of the nearby H i-massive LIRG HIZOA J0836–43: from the NIR to the radio domain

Abstract HIZOA J0836–43 is one of the most H i-massive galaxies in the local (z < 0.1) Universe. Not only are such galaxies extremely rare, but this “coelacanth” galaxy exhibits characteristics – in particular its active, inside-out stellar disk-building – that appear more typical of past (z ~ 1) star formation, when large gas fractions were more common. Unlike most local giant H i galaxies, it is actively star forming. Moreover, the strong infrared emission is not induced by a merger event or AGN, as is commonly found in other local LIRGs. The galaxy is suggestive of a scaled-up version of local spiral galaxies; its extended star formation activity likely being fueled by its large gas reservoir and, as such, can aid our understanding of star formation in systems expected to dominate at higher redshifts. The multi-wavelength imaging and spectroscopic observations that have led to these deductions will be presented. These include NIR (JHK) and MIR (Spitzer; 3 – 24μm) imaging and photometry, MIR spectroscopy, ATCA H i-interferometry and Mopra CO line emission observations. But no optical data, as the galaxy is heavily obscured due to its location in Vela behind the Milky Way.
Particle Flow Analysis on Mechanical Characteristics of Rock with Two Pre-Existing Fissures

Many research results show that under any stress state the rock mass is most likely to crack, swell, bifurcate, and infiltrate from the fissure tip, resulting in rock engineering instability and failure. In order to study the influence of double fissure angles on rock mechanical characteristics, five rock numerical models with different fissure angles were established by numerical simulation software. Uniaxial compression tests were carried out, and the variation characteristics of rock stress, strain, failure, microcrack, and acoustic emission (AE) were recorded. The test results show that: With increases in the fissure angles, the elastic modulus of rock increased, while the peak strength decreased first and then increased. The number of microcracks in rock was greater at 15° and 75° than at other angles. The microcracks in rock were mainly tensile cracks, and relatively few were shear cracks. The angles of microcracks were mostly concentrated between 0 and 180°, most of which were between 60 and 110°. The failure of rock was relatively light when the fissure angle was15° or 75°, but it produced more and smaller fragments, and the failure was the most serious when the fissure angle was 30°. The angles of the fissures affected the maximum number of AE events, the strain values for the initial AE event, and the maximal AE event. This research can provide some reference for disasters caused by rocks with pre-existing fissures.
Bose-Fermi cancellations without supersymmetry

We show that adjoint QCD features very strong Bose-Fermi cancellations in the large-N limit, despite the fact that it is manifestly nonsupersymmetric. The difference between the bosonic and fermionic densities of states in large-N adjoint QCD turns out to have a “two-dimensional” scaling ∼exp(lE) for large energies E in finite spatial volume, where l is a length scale associated with the curvature of the spatial manifold. In particular, all Hagedorn growth cancels, and so does the growth exp(V1/4E3/4) expected in a standard local four-dimensional theory in spatial volume V. In these ways, large-N adjoint QCD, a manifestly nonsupersymmetric theory, acts similarly to supersymmetric theories. We also show that at large-N the vacuum energy of multiflavor adjoint QCD is non-negative and exponentially small compared to the UV cutoff with several natural regulators.
SPARSE AUTOENCODERS TO ENHANCE SPEECH RECOGNITION

Starting from a state-of-the-art Lattice-Free Maximum Mutual Information (LF-MMI) speech recognition system as baseline, we investigate the use of shallow sparse autoencoders to further process LF-MMI acoustic model outputs (i.e., LF-MMI senone likelihoods) to produce more reliable phone or senone likelihoods. The sparse and overcomplete autoencoders investigated here are shown to project the LF-MMI senone likelihoods to a high-dimensional sparse space. Detailed analysis of this representation space shows that the encodings obtained from the autoencoder are indeed sparse and capable of improving clas-siﬁcation performance. Motivated by this, we then exploit the resulting high-dimensional sparse representations to train a new acoustic model. Different combinations of the available acoustic models are explored. In particular, it is shown that combining the senone likelihoods from the acoustic model trained on the high-dimensional sparse encodings and from the acoustic model in the baseline system leads to promising improvements in the recognition performance on Augmented Multiparty Inter-action (AMI) data set for both Individual Head-mounted Micro-phone (IHM) and Single-Distant Microphone (SDM) tasks.
On the non-Gaussian errors in high-z supernovae type Ia data

The nature of random errors in any data set is Gaussian, which is a well established fact according to the Central Limit Theorem. Supernovae type Ia data have played a crucial role in major discoveries in cosmology. Unlike in laboratory experiments, astronomical measurements cannot be performed in controlled situations. Thus, errors in astronomical data can be more severe in terms of systematics and non-Gaussianity compared to those of laboratory experiments. In this paper, we use the Kolmogorov-Smirnov statistic to test non-Gaussianity in high-z supernovae data. We apply this statistic to four data sets, i.e., Gold data (2004), Gold data (2007), the Union2 catalog and the Union2.1 data set for our analysis. Our results show that in all four data sets the errors are consistent with a Gaussian distribution.
SDSS J102623.61+254259.5: the second most distant blazar at z = 5.3

The radio-loud quasar SDSS J102623.61+254259.5, at a redshift z = 5.3, is one of the most distant radio-loud objects. Since its radio flux exceeds 100 mJy at a few GHz, it is also one of the most powerful radio-loud sources. We propose that this source is a blazar, i.e. we are seeing its jet at a small viewing angle. This claim is based on the spectral energy distribution of this source, and especially on its strong and hard X-ray spectrum, as seen by Swift, very typical of powerful blazars. Observations by the Gamma-Ray Burst Optical/Near-Infrared Detector (GROND) and by the Wide-field Infrared Survey Explorer (WISE) allow us to establish the thermal nature of the emission in the near-IR–optical band. Assuming that this is produced by a standard accretion disc, we derive that it emits a luminosity of Ld≃ 9 × 1046 erg s−1 and that the black hole has a mass between 2 and 5 billion solar masses. This poses interesting constraints on the mass function of heavy (>109 M⊙) black holes at high redshifts.
Simulating the main stages of chalcopyrite leaching and bioleaching in ferrous ions solution: An electrochemical impedance study with a modiﬁed carbon paste electrode Minerals

In this work, we present an electrochemical study using a carbon paste electrode modiﬁed with chalcopy- rite (CuFeS 2 ) in solution A of T&K medium with different ferrous ion concentrations, in the absence and presence of the bacterium Acidithiobacillus ferrooxidans . The aim was to evaluate the inﬂuence of ferrous ions and bacteria on the electrochemical behavior of chalcopyrite. Electrochemical impedance spectroscopy (EIS) was used to investigate the processes occurring at the electrode/solution interface in the different systems, considering the charge transfer reactions involving chalcopyrite and ferrous ions, the presence of a multicomponent layer, and diffusion. The main changes in the chalcopyrite response occurred before 67 h or 43 h of immersion, in the absence or presence of ferrous ions, respectively, indicating that the surface oxide layer present on chalcopyrite was dissolved faster in the presence of ferrous ions. The addition of bacteria decreased the charge transfer reaction resistance, especially when ferrous ions were present. In the presence of Fe 2+ , sulfur and jarosite were detected in the solid residues after leaching, while only jarosite was detected in the bioleaching experiment. The results suggested that ferrous ions accelerated the dissolution of chalcopyrite, and that overlayers including bioﬁlms did not halt chalcopyrite dissolution, indicating that there was no passivation. (cid:1) 2016 Elsevier Ltd. All rights reserved.
The mean ultraviolet spectrum of a representative sample of faint z ~ 3 Lyman alpha emitters

We discuss the rest-frame ultraviolet (UV) emission line spectra of a large (∼100) sample of low luminosity redshift z ∼ 3.1 Lyman alpha emitters (LAEs) drawn from a Subaru imaging survey in the SSA22 survey field. Our earlier work based on smaller samples indicated that such sources have high [O III]/[O II] line ratios possibly arising from a hard ionizing spectrum that may be typical of similar sources in the reionization era. With optical spectra secured from VLT/VIMOS, we re-examine the nature of the ionizing radiation in a larger sample using the strength of the high ionization diagnostic emission lines of CIII]λ1909, CIVλ1549, HEIIλ1640, and O III]λλ1661, 1666 A in various stacked subsets. Our analysis confirms earlier suggestions of a correlation between the strength of Ly α and CIII] emission and we find similar trends with broad-band UV luminosity and rest-frame UV colour. Using various diagnostic line ratios and our stellar photoionization models, we determine both the gas phase metallicity and hardness of the ionization spectrum characterized by ξion – the number of Lyman continuum photons per UV luminosity. We confirm our earlier suggestion that ξion is significantly larger for LAEs than for continuum-selected Lyman break galaxies, particularly for those LAEs with the faintest UV luminosities. We briefly discuss the implications for cosmic reionization if the metal-poor intensely star-forming systems studied here are representative examples of those at much higher redshift.
V346 Normae: first post-outburst observations of an FU Orionis star

We acknowledge support from an ERC Starting grant (Grant Agreement No. 639889), STFC Rutherford fellowship and grant (ST/J004030/1, ST/K003445/1), a NASA Sagan fellowship, Science Foundation Ireland grant (13/ERC/I2907), and NSF grant (AST 1311698).
Deep Cascade Learning for Optimal Medical Image Feature Representation

Cascade Learning (CL) is a new and alternative form of training a deep neural network in a layer-wise fashion. This varied training strategy results in different feature representations, advantageous due to the incremental complexity induced across layers of the network. We hypothesize that CL is inducing coarse-to-fine feature representations across layers of the network, differing from traditional end-to-end learning, advantageous for medical imaging applications. We use five different medical image classification tasks and a feature localisation task to show that CL is a superior learning strategy. We show that transferring cascade learned features from cascade trained models from a subset of ImageNet systematically outperforms transfer from traditional end-to-end training, often with statistical significance, but never worse. We demonstrate visually (using Grad-CAM saliency maps), numerically (using granulometry measures), and with error analysis that the features and also errors across the learning paradigms are different, motivating a combined approach, which we validate further improves performance. We find the features learned using CL are more closely aligned with medical expert labelled regions of interest on a large chest X-ray dataset. We further demonstrate other advantages of CL, such as robustness to noise and improved model calibration, which we suggest future work seriously consider as metrics to optimise, in addition to performance, prior to deployment in clinical settings.