Miracle-dz/UniFAR-FTUs huggingface dataset:
AGILE Observations of Two Repeating Fast Radio Bursts with Low Intrinsic Dispersion Measures

We focus on two repeating fast radio bursts (FRBs) recently detected by the CHIME/FRB experiment in 2018–2019 (Source 1: 180916.J0158+65, and Source 2: 181030.J1054+73). These sources have low excess dispersion measures ( and , respectively), implying relatively small maximal distances. They were repeatedly observed by AGILE in the MeV–GeV energy range. We do not detect prompt emission simultaneously with these repeating events. This search is particularly significant for the submillisecond and millisecond integrations obtainable by AGILE. The sources are constrained to emit a MeV-fluence in the millisecond range below corresponding to an isotropic energy near erg for a distance of 150 Mpc (applicable to Source 1). We also searched for γ-ray emission for time intervals up to 100 days, obtaining 3σ upper limits (ULs) for the average isotropic luminosity above 50 MeV, (5–10) . For a source distance near 100 kpc (possibly applicable to Source 2), our ULs imply , and 2 . Our results are significant in constraining the high-energy emission of underlying sources such as magnetars, or other phenomena related to extragalactic compact objects, and show the prompt emission to be lower than the peak of the 2004 magnetar outburst of SGR 1806-20 for source distances less than about 100 Mpc.
Modelling the Canes Venatici I dwarf spheroidal galaxy

The aim of this work is to find a progenitor for Canes Venatici I (CVn I), under the assumption that it is a dark matter free object that is undergoing tidal disruption. With a simple point mass integrator, we searched for an orbit for this galaxy using its current position, position angle, and radial velocity in the sky as constraints. The orbit that gives the best results has the pair of proper motions μα = −0.099 mas yr−1 and μδ = −0.147 mas yr−1, that is, an apogalactic distance of 242.79 kpc and a perigalactic distance of 20.01 kpc. Using a dark matter free progenitor that undergoes tidal disruption, the best-fitting model matches the final mass, surface brightness, effective radius, and velocity dispersion of CVn I simultaneously. This model has an initial Plummer mass of 2.47 × 107 M⊙ and a Plummer radius of 653 pc, producing a remnant after 10 Gyr with a final mass of 2.45 × 105 M⊙, a central surface brightness of 26.9 mag arcsec−2, an effective radius of 545.7 pc, and a velocity dispersion with the value 7.58 km s−1. Furthermore, it is matching the position angle and ellipticity of the projected object in the sky.
Speculative trading, prospect theory and transaction costs

A speculative agent with prospect theory preference chooses the optimal time to purchase and then to sell an indivisible risky asset to maximise the expected utility of the round-trip profit net of transaction costs. The optimisation problem is formulated as a sequential optimal stopping problem, and we provide a complete characterisation of the solution. Depending on the preference and market parameters, the optimal strategy can be “buy and hold”, “buy low, sell high”, “buy high, sell higher” or “no trading”. Behavioural preference and market friction interact in a subtle way which yields surprising implications on the agent’s trading patterns. For example, increasing the market entry fee does not necessarily curb speculative trading, but instead may induce a higher reference point under which the agent becomes more risk-seeking and in turn is more likely to trade.
Quasinormal modes and spectroscopy of a Schwarzschild black hole surrounded by a cloud of strings in Rastall gravity

We obtain the solution of a static spherically symmetric black hole surrounded by a cloud of strings in Rastall gravity and study the influence of the parameter a associated with strings on the event horizon and the Hawking temperature. Through analyzing the black hole metric, we find that the static spherically symmetric black hole solution surrounded by a cloud of strings in Rastall gravity can be transformed into the static spherically symmetric black hole solution surrounded by quintessence in Einstein gravity when the parameter β of Rastall gravity is positive, which provides a possibility for the string fluid to be a candidate of dark energy. We use the method of Regge and Wheeler together with the high order WKB-Pade approximation to calculate the quasinormal mode frequencies of the odd parity gravitational perturbation and simultaneously apply the unstable null geodesics of black holes to compute the quasinormal mode frequencies at the eikonal limit for this black hole model. The results show that the increase of the parameter a makes the gravitational wave decay slowly in Rastall gravity. In addition, we utilize two methods, which are based on the adiabatic invariant integral and the periodic property of outgoing waves, respectively, to derive the area spectrum and entropy spectrum of the black hole model. The results show that the area spectrum and entropy spectrum are equidistant spaced. The former is the same as the case of Einstein gravity, while the latter is different, depending on the Rastall parameter β.
Graph Convolution Networks for Probabilistic Modeling of Driving Acceleration

The ability to model and predict ego-vehicle’s surrounding traffic is crucial for autonomous pilots and intelligent driver-assistance systems. Acceleration prediction is important as one of the major components of traffic prediction. This paper proposes novel approaches to the acceleration prediction problem. By representing spatial relationships between vehicles with a graph model, we build a generalized acceleration prediction framework. This paper studies the effectiveness of proposed Graph Convolution Networks, which operate on graphs predicting the acceleration distribution for vehicles driving on highways. We further investigate prediction improvement through integrating of Recurrent Neural Networks to disentangle the temporal complexity inherent in the traffic data. Results from simulation with comprehensive performance metrics support that our proposed networks outperform state-of-the-art methods in generating realistic trajectories over a prediction horizon.
Asset Price Bubbles in market models with proportional transaction costs

We study asset price bubbles in market models with proportional transaction costs $\lambda\in (0,1)$ and finite time horizon $T$ in the setting of [49]. By following [28], we define the fundamental value $F$ of a risky asset $S$ as the price of a super-replicating portfolio for a position terminating in one unit of the asset and zero cash. We then obtain a dual representation for the fundamental value by using the super-replication theorem of [50]. We say that an asset price has a bubble if its fundamental value differs from the ask-price $(1+\lambda)S$. We investigate the impact of transaction costs on asset price bubbles and show that our model intrinsically includes the birth of a bubble.
Heliospheric Structure as Revealed by the 3–88 keV H ENA Spectra

Energetic neutral atoms (ENAs) are an important tool for investigating the structure of the heliosphere. Recently, it was observed that fluxes of ENAs (with energy ≤55 keV) coming from the upwind and downwind regions of the heliosphere are similar in strength. This led the authors of these observations to hypothesize that the heliosphere is bubble-like rather than comet-like, meaning that it has no extended tail. We investigate the directional distribution of the ENA flux for a wide energy range (3–88 keV) including observations from IBEX (Interstellar Boundary Explorer), INCA (Ion and Neutral Camera, on board Cassini), and HSTOF (High-energy Suprathermal Time Of Flight sensor, on board the Solar and Heliospheric Observatory). An essential element is the model of pickup ion (PUI) acceleration at the termination shock proposed by Zank. We use state-of-the-art models of the global heliosphere, interstellar neutral gas density, and PUI distributions. The results, based on the “comet-like” model of the heliosphere, are close in flux magnitude to ENA observations by IBEX, HSTOF, and partly those by INCA (except for the 5.2–13.5 keV energy channel). We find that the ENA flux from the tail dominates at high energy (in agreement with HSTOF, but not INCA). At low energy, our comet-like model produces ENA fluxes of similar strength from the upwind and downwind directions—which, therefore, removes this as a compelling argument for a bubble-like heliosphere.
NICER observations of the Crab pulsar glitch of 2017 November

Context. The Crab pulsar underwent its largest timing glitch on 2017 Nov. 8. The event was discovered at radio wavelengths, and was followed at soft X-ray energies by observatories, such as XPNAV and NICER. Aims. This work aims to compare the glitch behavior at the two wavelengths mentioned above. Preliminary work in this regard has been done by the X-ray satellite XPNAV. NICER with its far superior sensitivity is expected to reveal much more detailed behavior. Methods. NICER has accumulated more than 301 kilo seconds of data on the Crab pulsar, equivalent to more than 3.3 billion soft X-ray photons. These data were first processed using the standard NICER analysis pipeline. Then the arrival times of the X-ray photons were referred to the solar system’s barycenter. Then specific analysis was done to study the specific behavior outlined in the following sections, while taking dead time into account. Results. The variation of the rotation frequency of the Crab pulsar and its time derivative during the glitch is almost exactly similar at the radio and X-ray energies. The following properties of the Crab pulsar remain essentially constant before and after the glitch: the total X-ray flux; the flux, widths, and peaks of the two components of its integrated profile; and the soft X-ray spectrum. There is no evidence for giant pulses at X-ray energies. However, the timing noise of the Crab pulsar shows quasi sinusoidal variation before the glitch, with increasing amplitude, which is absent after the glitch. Conclusions. Even the strongest glitch in the Crab pulsar appears not to affect all but one of the properties mentioned above, at either frequency. The fact that the timing noise appears to change due to the glitch is an important clue to unravel as this is still an unexplained phenomenon.
The Chemical Signatures of Planetary Engulfment Events in Binary Systems

Planetary engulfment events involve the chemical assimilation of a planet into a star’s external layer. This can cause a change in the chemical pattern of the stellar atmosphere in a way that mirrors the composition of the rocky object engulfed, with the refractory elements being more abundant than the volatiles. Due to these stellar chemical changes, planetary engulfment events can render the process of chemical tagging potentially inaccurate. A line-by-line differential analysis of twin stars in wide binary systems allows us to test the chemical homogeneity of these associations with typical individual stellar Fe i uncertainties of 0.01 dex and eventually unveil chemical anomalies that could be attributed to planetary engulfment events. Out of the 14 systems analyzed here, we report the discovery of the most chemically inhomogeneous system to date (HIP 34407/HIP 34426). The median difference in abundances of refractory elements within the pair is 0.19 dex and the trend between the differential abundances and condensation temperature suggests that the anomaly is likely due to a planetary engulfment event. Within our sample, five other chemically anomalous systems are found.
PhotoTwinVR: An Immersive System for Manipulation, Inspection and Dimension Measurements of the 3D Photogrammetric Models of Real-Life Structures in Virtual Reality

Photogrammetry is a science dealing with obtaining reliable information about physical objects using their imagery description. Recent advancements in the development of Virtual Reality (VR) can help to unlock the full potential offered by the digital 3D-reality models generated using the state-of-art photogrammetric technologies. These models are becoming a viable alternative for providing high-quality content for such immersive environment. Simultaneously, their analyses in VR could bring added-value to professionals working in various engineering and non-engineering settings and help in extracting useful information about physical objects. However, there is little research published to date on feasible interaction methods in the VR-based systems augmented with the 3D photogrammetric models, especially concerning gestural input interfaces. Consequently, this paper presents the PhotoTwinVR -- an immersive, gesture-controlled system for manipulation and inspection of 3D photogrammetric models of physical objects in VR. Our system allows the user to perform basic engineering operations on the model subjected to the off-line inspection process. An observational study with a group of three domain-expert participants was completed to verify its feasibility. The system was populated with a 3D photogrammetric model of an existing pipe-rack generated using a commercial software package. The participants were asked to carry out a survey measurement of the object using the measurement toolbox offered by PhotoTwinVR. The study revealed a potential of such immersive tool to be applied in practical real-words cases of off-line inspections of pipelines.
Neutral Hydrogen Observations of Low Surface Brightness Galaxies around M101 and NGC 5485

We present atomic hydrogen (H i) observations using the Robert C. Byrd Green Bank Telescope along the lines of sight to 27 low surface brightness (LSB) dwarf galaxy candidates discovered in optical searches around M101. We detect H i reservoirs in five targets and place stringent upper limits on the remaining 22, implying that they are gas-poor. The distances to our H i detections range from 7 to 150 Mpc, demonstrating the utility of wide-bandpass H i observations as a follow-up tool. The systemic velocities of three detections are consistent with that of the NGC 5485 group behind M101, and we suggest that our 15 nondetections with lower distance limits from the optical are associated with and have been stripped by that group. We find that the gas richness of confirmed M101 satellites are broadly consistent with those of the Milky Way satellites, as well as with those of satellites around other hosts of comparable mass, when survey completeness is taken into account. This suggests that satellite quenching and gas stripping proceed similarly around halos of similar mass, in line with theoretical expectations.
Deriving star cluster parameters with convolutional neural networks. II. Extinction and cluster/background classification

Context. Convolutional neural networks (CNNs) have been established as the go-to method for fast object detection and classification of natural images. This opens the door for astrophysical parameter inference on the exponentially increasing amount of sky survey data. Until now, star cluster analysis was based on integral or resolved stellar photometry, which limit the amount of information that can be extracted from individual pixels of cluster images. Aims. We aim to create a CNN capable of inferring star cluster evolutionary, structural, and environmental parameters from multiband images and to demonstrate its capabilities in discriminating genuine clusters from galactic stellar backgrounds. Methods. A CNN based on the deep residual network (ResNet) architecture was created and trained to infer cluster ages, masses, sizes, and extinctions with respect to the degeneracies between them. Mock clusters placed on M 83 Hubble Space Telescope images utilizing three photometric passbands (F336W, F438W, and F814W) were used. The CNN is also capable of predicting the likelihood of the presence of a cluster in an image and quantifying its visibility (S/N). Results. The CNN was tested on mock images of artificial clusters and has demonstrated reliable inference results for clusters of ages ≲100 Myr, extinctions AV between 0 and 3 mag, masses between 3 × 103 and 3 × 105 M⊙, and sizes between 0.04 and 0.4 arcsec at the distance of the M 83 galaxy. Real M 83 galaxy cluster parameter inference tests were performed with objects taken from previous studies and have demonstrated consistent results.
Do Cookie Banners Respect my Choice? : Measuring Legal Compliance of Banners from IAB Europe’s Transparency and Consent Framework

As a result of the GDPR and the ePrivacy Directive, European users encounter cookie banners on almost every website. Many of such banners are implemented by Consent Management Providers (CMPs), who respect IAB Europe’s Transparency and Consent Framework (TCF). Via cookie banners, CMPs collect and disseminate user consent to third parties. In this work, we systematically study IAB Europe’s TCF and analyze consent stored behind the user interface of TCF cookie banners. We analyze the GDPR and the ePrivacy Directive to identify potential legal violations in implementations of cookie banners based on the storage of consent and detect such suspected violations by crawling 1 426 websites that contains TCF banners, found among 28 257 crawled European websites. With two automatic and semi-automatic crawl campaigns, we detect suspected violations, and we find that: 141 websites register positive consent even if the user has not made their choice; 236 websites nudge the users towards accepting consent by pre-selecting options; and 27 websites store a positive consent even if the user has explicitly opted out. Performing extensive tests on 560 websites, we find at least one suspected violation in 54% of them. Finally, we provide a browser extension to facilitate manual detection of suspected violations for regular users and Data Protection Authorities.
Multiple points of Gaussian random fields

This paper is concerned with the existence of multiple points of Gaussian random fields. Under the framework of Dalang et al. (2017), we prove that, for a wide class of Gaussian random fields, multiple points do not exist in critical dimensions. The result is applicable to fractional Brownian sheets and the solutions of systems of stochastic heat and wave equations.
Professional Development and Self-Efficacy of Texas Educators and the Teaching of English Language Learners

With the continuing growth of the school aged population of English language learners, schools must provide instruction in the English language and in the various content areas in order for the English language learners to be academically successful. The growth rate of English language learners has greatly outpaced the professional development teachers have received to teach them. A lack of sufficient, quality professional development can impact the teachers’ self-efficacy which can result in the teachers having lower confidence in their knowledge and ability to be effective. Teachers with lower self-efficacy are not as effective in their instruction. The purpose of this study was to explore the professional development and self-efficacy of Texas teachers as they relate to English language learners.
Factorized Multimodal Transformer for Multimodal Sequential Learning

The complex world around us is inherently multimodal and sequential (continuous). Information is scattered across different modalities and requires multiple continuous sensors to be captured. As machine learning leaps towards better generalization to real world, multimodal sequential learning becomes a fundamental research area. Arguably, modeling arbitrarily distributed spatio-temporal dynamics within and across modalities is the biggest challenge in this research area. In this paper, we present a new transformer model, called the Factorized Multimodal Transformer (FMT) for multimodal sequential learning. FMT inherently models the intramodal and intermodal (involving two or more modalities) dynamics within its multimodal input in a factorized manner. The proposed factorization allows for increasing the number of self-attentions to better model the multimodal phenomena at hand; without encountering difficulties during training (e.g. overfitting) even on relatively low-resource setups. All the attention mechanisms within FMT have a full time-domain receptive field which allows them to asynchronously capture long-range multimodal dynamics. In our experiments we focus on datasets that contain the three commonly studied modalities of language, vision and acoustic. We perform a wide range of experiments, spanning across 3 well-studied datasets and 21 distinct labels. FMT shows superior performance over previously proposed models, setting new state of the art in the studied datasets.
Parallel Distributed Logistic Regression for Vertical Federated Learning without Third-Party Coordinator

Federated Learning is a new distributed learning mechanism which allows model training on a large corpus of decentralized data owned by different data providers, without sharing or leakage of raw data. According to the characteristics of data dis-tribution, it could be usually classified into three categories: horizontal federated learning, vertical federated learning, and federated transfer learning. In this paper we present a solution for parallel dis-tributed logistic regression for vertical federated learning. As compared with existing works, the role of third-party coordinator is removed in our proposed solution. The system is built on the pa-rameter server architecture and aims to speed up the model training via utilizing a cluster of servers in case of large volume of training data. We also evaluate the performance of the parallel distributed model training and the experimental results show the great scalability of the system.
The skeletal benefits of calcium- and vitamin D 3 -fortified milk are sustained in older men after withdrawal of supplementation:

Background: In a previous 2-y randomized controlled trial, we showed that calcium- and vitamin D3–fortified milk stopped or slowed bone loss at several clinically relevant skeletal sites in older men. Objective: The present study aimed to determine whether the skeletal benefits of the fortified milk were sustained after withdrawal of the supplementation. Design:One hundred nine men50 y old who had completed a 2-y fortified milk trial were followed for an additional 18 mo, during which no fortified milk was provided. Bone mineral density (BMD) of the total hip, femoral neck, lumbar spine, and forearm was measured by using dual-energy X-ray absorptiometry. Results: Comparison of the mean changes from baseline between thegroups(adjustedforbaselineage,BMD,totalcalciumintake,and change in weight) showed that the net beneficial effects of fortified milk on femoral neck and ultradistal radius BMD at the end of the intervention (1.8% and 1.5%, respectively; P 0.01 for both) were sustained at 18-mo follow-up (P 0.05 for both). The nonsignificantbetween-groupdifferencesatthetotalhip(0.8%;P0.17)also persisted at follow-up (0.7%; P 0.10), but there were no lasting benefitsatthelumbarspine.Theaveragetotaldietarycalciumintake in the milk supplementation group at follow-up approximated recommended amounts for Australian men 50 y old (1000 mg/d) but did not differ significantly from that in the control subjects (1021 versus 890 mg/d). Conclusion: Supplementation with calcium- and vitamin D3–fortified milk for 2 y may provide some sustained benefits for BMD in older men after withdrawal of supplementation. Am J Clin Nutr 2008;87:771–7.