Miracle-dz/UniFAR-FTUs huggingface dataset:
SWIFT J0503.7-2819: A nearly synchronous intermediate polar below the period gap?

Based on the X-ray observations from XMM-Newton and Swift, and optical observations from Transiting Exoplanet Survey Satellite (TESS) and AAVSO, we present temporal and spectral properties of probable intermediate polar SWIFT J0503.7-2819. The X-ray light curve shows two distinctive features, where possibly the second pole seems to be active during the middle of the XMM-Newton observations. Present analysis confirms and also refines the previously reported orbital period of SWIFT J0503.7-2819 as 81.65$\pm$0.04 min. The X-ray and optical variations of this target have been found to occur at the period of $\sim$ 65 min, which we propose as the spin period of the white dwarf (WD). The energy-dependent modulation at this period, which are due to the photoelectric absorption in the accretion flow, also assures this conjecture. Two temperature thermal plasma model well explains the X-ray spectra with temperatures of $\sim$ 150 eV and $\sim$ 18.5 keV, which is absorbed by a dense material with an average equivalent hydrogen column density of 3.8 $\times$ 10$^{22}$ cm$^{-2}$ that partially covers $\sim$ 27% of the X-ray source. An attempt is made to understand the accretion flow in this system using the present data of SWIFT J0503.7-2819. If the proposed spin period is indeed the actual period, then SWIFT J0503.7-2819 could be the first nearly synchronous intermediate polar below the period gap.
Training neural network ensembles via trajectory sampling

In machine learning, there is renewed interest in neural network ensembles (NNEs), whereby predictions are obtained as an aggregate from a diverse set of smaller models, rather than from a single larger model. Here, we show how to define and train a NNE using techniques from the study of rare trajectories in stochastic systems. We define an NNE in terms of the trajectory of the model parameters under a simple, and discrete in time, diffusive dynamics, and train the NNE by biasing these trajectories towards a small time-integrated loss, as controlled by appropriate counting fields which act as hyperparameters. We demonstrate the viability of this technique on a range of simple supervised learning tasks. We discuss potential advantages of our trajectory sampling approach compared with more conventional gradient based methods.
Black-body radiation-induced photodissociation and population redistribution of weakly bound states in H2 +

Molecular hydrogen ions in weakly bound states close to the first dissociation threshold are attractive quantum sensors for measuring the proton-to-electron mass ratio and hyperfine-induced ortho-para mixing. The experimental accuracy of previous spectroscopic studies relying on fast ion beams could be improved by using state-of-the-art ion trap setups. With the electric-dipole moment vanishing in H and preventing fast spontaneous emission, radiative lifetimes of the order of weeks are found. We include the effect of black-body radiation that can lead to photodissociation and rovibronic state redistribution to obtain effective lifetimes for trapped ion experiments. Rate coefficients for bound-bound and bound-continuum processes were calculated using adiabatic nuclear wave functions and nonadiabatic energies, including relativistic and radiative corrections. Effective lifetimes for the weakly bound states were obtained by solving a rate equation model and lifetimes in the range of 4–523 and >215 ms were found at room temperature and liquid nitrogen temperature, respectively. Black-body induced photodissociation was identified as the lifetime-limiting effect, which guarantees the purity of state-selectively generated molecular ion ensembles. The role of hyperfine-induced g/u-mixing, which allows pure rovibrational transitions, was found to be negligible. GRAPHICAL ABSTRACT
Katara: synthesizing CRDTs with verified lifting

Conflict-free replicated data types (CRDTs) are a promising tool for designing scalable, coordination-free distributed systems. However, constructing correct CRDTs is difficult, posing a challenge for even seasoned developers. As a result, CRDT development is still largely the domain of academics, with new designs often awaiting peer review and a manual proof of correctness. In this paper, we present Katara, a program synthesis-based system that takes sequential data type implementations and automatically synthesizes verified CRDT designs from them. Key to this process is a new formal definition of CRDT correctness that combines a reference sequential type with a lightweight ordering constraint that resolves conflicts between non-commutative operations. Our process follows the tradition of work in verified lifting, including an encoding of correctness into SMT logic using synthesized inductive invariants and hand-crafted grammars for the CRDT state and runtime. Katara is able to automatically synthesize CRDTs for a wide variety of scenarios, from reproducing classic CRDTs to synthesizing novel designs based on specifications in existing literature. Crucially, our synthesized CRDTs are fully, automatically verified, eliminating entire classes of common errors and reducing the process of producing a new CRDT from a painstaking paper proof of correctness to a lightweight specification.
A Versatile Agent for Fast Learning from Human Instructors

In recent years, a myriad of superlative works on intelligent robotics policies have been done, thanks to advances in machine learning. However, inefficiency and lack of transfer ability hindered algorithms from pragmatic applications, especially in human-robot collaboration, when few-shot fast learning and high flexibility become a wherewithal. To surmount this obstacle, we refer to a ”Policy Pool”, containing pre-trained skills that can be easily accessed and reused. An agent is employed to govern the ”Policy Pool” by unfolding requisite skills in a flexible sequence, contingent on task specific predilection. This predilection can be automatically interpreted from one or few human expert demonstrations. Under this hierarchical setting, our algorithm is able to pick up a sparse-reward, multi-stage knack with only one demonstration in a Mini-Grid environment, showing the potential for instantly mastering complex robotics skills from human instructors. Additionally, the innate quality of our algorithm also allows for lifelong learning, making it a versatile agent.
Entropic Descent Archetypal Analysis for Blind Hyperspectral Unmixing

In this paper, we introduce a new algorithm based on archetypal analysis for blind hyperspectral unmixing, assuming linear mixing of endmembers. Archetypal analysis is a natural formulation for this task. This method does not require the presence of pure pixels (i.e., pixels containing a single material) but instead represents endmembers as convex combinations of a few pixels present in the original hyperspectral image. Our approach leverages an entropic gradient descent strategy, which (i) provides better solutions for hyperspectral unmixing than traditional archetypal analysis algorithms, and (ii) leads to efficient GPU implementations. Since running a single instance of our algorithm is fast, we also propose an ensembling mechanism along with an appropriate model selection procedure that make our method robust to hyper-parameter choices while keeping the computational complexity reasonable. By using six standard real datasets, we show that our approach outperforms state-of-the-art matrix factorization and recent deep learning methods. We also provide an open-source PyTorch implementation: https://github.com/inria-thoth/EDAA.
SEER: Safe Efficient Exploration for Aerial Robots using Learning to Predict Information Gain

We address the problem of efficient 3-D exploration in indoor environments for micro aerial vehicles with limited sensing capabilities and payload/power constraints. We develop an indoor exploration framework that uses learning to predict the occupancy of unseen areas, extracts semantic features, samples viewpoints to predict information gains for different exploration goals, and plans informative trajectories to enable safe and smart exploration. Extensive experimentation in simulated and real-world environments shows the proposed approach outperforms the state-of-the-art exploration framework by 24% in terms of the total path length in a structured indoor environment and with a higher success rate during exploration.
Vanilla feedforward neural networks as a discretization of dynamic systems

Deep learning has made significant applications in the field of data science and natural science. Some studies have linked deep neural networks to dynamic systems, but the network structure is restricted to the residual network. It is known that residual networks can be regarded as a numerical discretization of dynamic systems. In this paper, we back to the classical network structure and prove that the vanilla feedforward networks could also be a numerical discretization of dynamic systems, where the width of the network is equal to the dimension of the input and output. Our proof is based on the properties of the leaky-ReLU function and the numerical technique of splitting method to solve differential equations. Our results could provide a new perspective for understanding the approximation properties of feedforward neural networks.
Parallel Reinforcement Learning Simulation for Visual Quadrotor Navigation

Reinforcement learning (RL) is an agent-based approach for teaching robots to navigate within the physical world. Gathering data for RL is known to be a laborious task, and real-world experiments can be risky. Simulators facilitate the collection of training data in a quicker and more cost-effective manner. However, RL frequently requires a significant number of simulation steps for an agent to become skilful at simple tasks. This is a prevalent issue within the field of RL-based visual quadrotor navigation where state dimensions are typically very large and dynamic models are complex. Furthermore, rendering images and obtaining physical properties of the agent can be computationally expensive. To solve this, we present a simulation framework, built on AirSim, which provides efficient parallel training. Building on this framework, Ape-X is modified to incorporate parallel training of AirSim environments to make use of numerous networked computers. Through experiments we were able to achieve a reduction in training time from 3.9 hours to 11 minutes, for a toy problem, using the aforementioned framework and a total of 74 agents and two networked computers. Further details including a github repo and videos about our project, PRL4AirSim, can be found at https://sites.google. com/view/prl4airsim/home
Cumulus: A BFT-based Sidechain Protocol for Off-chain Scaling

Sidechain technology has been envisioned as a promising solution to accelerate today’s public blockchains in terms of scalability and interoperability. By relying on the mainchain for security, different sidechains can formulate their own rules to reach consensus. Although the literature has considered the possibility of using consensus protocols in the sidechain, so far a tailor-made consensus protocol for sidechains with high performance and formal security proof has not been attempted. To ﬁll this gap, we introduce Cumulus , a low over-head, highly efﬁcient, security provable sidechain protocol. Cumulus follows a BFT-based protocol and makes use of smart contracts to ensure that only one block proposed in the sidechain will be enforced on the mainchain in each round, thereby achieving consensus in an efﬁcient manner. We give a formal speciﬁcation of Cumulus which ensures safety and liveness without any online requirements of clients. For security analysis, we provide formal security deﬁnitions and proofs under Universally Composable Security (UCS) model. As proof of concept, we implement Cumulus and evaluate it in an Ethereum testnet.
THE γ-RAY DETECTED NARROW-LINE SEYFERT 1 GALAXY 1H 0323+342: SWIFT MONITORING AND SUZAKU SPECTROSCOPY

As a radio-loud narrow-line Seyfert 1 galaxy (NLS1) detected by Fermi/LAT in GeV γ-rays, 1H 0323+342 is a remarkable active galactic nucleus showing properties characteristic of both NLS1s and blazars. Here we present results of simultaneous X-ray and UV/optical monitoring observations on 1H 0323+342 taken with the UV/Optical Telescope and X-ray Telescope onboard the Swift satellite over six years from 2006. Overall, the object showed statistically correlated variations in both the UV and X-ray bands on timescales of years as well as on timescales of days. A deep Suzaku observation reveals X-ray variability on timescales as short as a few tens of thousand seconds, and an X-ray spectrum typical of Seyfert galaxies. The broadband spectral energy distribution, for which the data of UV and X-ray observations taken on 2009 July 26–27 were used, can be well modeled with a simple one-zone leptonic jet model plus accretion disk/corona emission. The latter is predominantly responsible for the UV/optical and X-ray (0.3–10 keV) emission and their observed variations. The correlated UV–X-ray variability on the timescale of days is consistent with reprocessing of the X-ray radiation by the accretion disk. The shortest timescale and large normalized excess variance of the X-ray variability detected with Suzaku suggest a relatively small black hole mass of the order of 10 7 M ⊙ ? > , consistent with the estimation based on the broad Hβ line in the optical.
Marine parasite in a freshwater wetland: new host and geographical records of Progrillotia dasyatidis (Cestoda: Trypanorhyncha) from Gasterosteus aculeatus (Actinopterygii: Gasterosteidae) in Bulgaria, with comments on its life-cycle

Abstract Plerocerci of the trypanorhynch cestode Progrillotia dasyatidis Beveridge, Neifar & Euzet, 2004 (Progrillotiidae) were isolated from the gallbladder of the three-spined stickleback Gasterosteus aculeatus from a small freshwater marsh in the Lake Atanasovsko Wetlands, a coastal area adjacent to the Black Sea coast, Bulgaria. The parasite was recorded in five out of 134 fish individuals studied (prevalence 3.73%, intensity 1–7, mean intensity 2.40 ± 1.17 and mean abundance 0.09 ± 0.06). A description of the plerocerci is presented, expanding data on intraspecific variation. The present report is the first record of P. dasyatidis from G. aculeatus (new host record) and from Bulgaria (new geographical record). Recording only plerocerci with evaginated scoleces in the sticklebacks is consistent with the hypothesis that teleosts are paratenic hosts and not intermediate hosts of P. dasyatidis.
Wechsler Intelligence Scale for Adults – Fourth Edition profiles of adults with autism spectrum disorder

Abstract Aim In this study, we have compared 229 Wechsler Adults Intelligence Scale – Fourth Edition (WAIS-IV) cognitive profiles of different severity adults with autism spectrum disorder to verify the impact of several variables including sex, age, level of education and autism severity level in an Italian sample. Moreover, we wanted to find out the optimal cut points for the major intelligence quotients in order to discriminate autism severity levels. Methods Participants were recruited from two National Health System Center in two different Italian regions and were assessed with gold-standard instruments as a part of their clinical evaluation. According to DSM-5, cognitive domains were also measured with multi-componential tests. We used the Italian adaptation of WAIS-IV. We checked our hypotheses using linear regression models and receiver operating characteristics (ROC) curves. Results Our results showed that age and level of education have a strong impact on Verbal Comprehension (VCI) and Working Memory Indexes (WMI). Gender differences are relevant when considering the VCI and Processing Speed index (PSI) in which women obtained the best performance. These differences are still relevant when considering cut points of ROC because 69 resulted to be the optimal cut point for women, 65 for men. Conclusions Few conclusions can be assumed only examining Full Scale Intelligence Quotient (FSIQ) scores as it includes many different information about broader cognitive abilities. Looking deeper at main indexes and their subtests findings are consistent with previous research on the disorder (moderate correlations of FSIQ, Perceptual Reasoning index, WMI and PSI with the participants’ age), while other results are unforeseen (no effect of sex found on FSIQ score) or novel (significant effect of education on VCI and WMI). Using an algorithm predicting optimal cut point for discriminating through autism severity levels can help clinicians to better label and quantify the required help a person may need, a test cannot replace diagnostic and clinical evaluation by experienced clinicians.
Reproductive status affects isotopic niches of Miniopterus natalensis in northeastern South Africa

The Natal long-fingered bat, Miniopterus natalensis, is an insectivorous, regional migrating species that exhibits sex-specific migration patterns. We explored the variability of isotopic niches using δ13C and δ15N ratios in fur from female and male bats in different reproductive states: pregnant, reproductive (but not pregnant at the time of this study), and nonreproductive females; nonscrotal and scrotal males using Bayesian standard ellipse areas and generalized linear models. Reproductive status was an informative predictor for the observed variation of both δ13C and δ15N ratios. Pregnant females displayed the highest mean δ13C and δ15N ratios and were distinct from other reproductive states. Reproductive females exhibited significantly higher δ15N ratios than nonreproductive females or nonscrotal and scrotal males, which may reflect state-dependent foraging and/or higher metabolic stress. Scrotal males displayed the lowest mean δ13C and δ15N ratios. Nonscrotal males exhibited the broadest isotopic niche, whereas reproductive females had the narrowest isotopic niche. Differences in isotopic niche sizes between the different reproductive groups may relate to variable individual feeding behavior and/or geographically different foraging areas/migratory stopover sites at individual and intraspecific levels in M. natalensis. This suggests that group-living, cave-dwelling bats may employ individual foraging specialization to facilitate coexistence in the broader geographic landscape.
Trees, owls, worms, and crevices: which habitat factors predict local woodrat demographics?

Hypothesized reasons for the decline of many woodrat populations in the eastern United States include parasitism by raccoon roundworm (Baylisascaris procyonis; Ascaridida: Ascarididae), hard mast shortages, owl predation, and reductions in suitable structures (e.g., rock crevices) for nest construction. We investigated whether abundance and apparent survival of eastern woodrats (Neotoma floridana) within a successfully reintroduced metapopulation in southern Illinois could be predicted by factors underlying these hypothesized reasons for woodrat declines. We analyzed capture histories of 205 eastern woodrats from eight rock outcrop sites in summers of 2013 and 2014 to estimate local population size and apparent survival. We then used repeated-measures models to test how woodrat abundance and apparent survival were associated with availability of mast trees, owl abundance, risk of raccoon roundworm infection, and crevice availability. Mean monthly estimated woodrat abundance at sites ranged from 0.78 to 21.58 in 2013 and 0.48 to 18.08 in 2014, while monthly apparent survival ranged from 0.00 to 0.76 during the summers and 0.05 to 0.90 during the trapping intersession. Crevice availability was positively associated both with abundance and apparent survival of woodrats. Our results did not support the hypothesis that owls reduce woodrat populations because woodrat abundance was positively associated with owl abundance across sites. No raccoon roundworm eggs were found at any site. We conclude that crevice availability was the best predictor of woodrat population success in our study area, while owl abundance may be a proxy for other habitat variables or a response to woodrat abundance. Our findings suggest measures that could be taken to benefit woodrat survival and abundance.
Utilizing Interactive Technologies to Encourage Healthy Dietary Behavior

Practicing healthy habits in food intake is as important as having a healthy diet for both having a better quality of life as well as in avoiding various health issues. The purpose of this workshop is to provide an environment to discuss and enhance collaborations in the areas of eating detection, eating interruption minimization and healthy dietary feedback. The workshop plans to achieve this goal with design and brainstorming sessions, several invited talks and presentation sessions. In addition to publishing a magazine/ journal article which will provide information about the novel developments in the relevant areas of related research discussed in the workshop, we expect to inspire the participating HCI researchers in potential future collaborations in these areas of research.
Palm Happiness: A Location-Based Application to Promote Awareness of Everyday Happy Moments

There has been growing interest in the development of mobile applications aimed at promoting mental well-being. In this paper, we present one such application that was developed based on the three good things, a psychological intervention that aims to cultivate positive mental well-being and has been shown to help reduce depression and improve perceived happiness. The application combines a digitized version of the intervention with a location-based recommender system that can suggest nearby locations which could provide opportunities for users to experience positive emotions. The key characteristics of the ”good things” recorded by users are also visualized to help users better self-reflect on what made them happy in daily life. A preliminary evaluation of the system was carried out with 13 users, showing above average scores for usability, perspicuity,novelty as well as perceived usefulness and intention to use.
An upper bound for the Hales-Jewett number HJ(4,2)

We show that for $n$ at least $10^{11}$, any 2-coloring of the $n$-dimensional grid $[4]^n$ contains a monochromatic combinatorial line. This is a special case of the Hales-Jewett Theorem, to which the best known general upper bound is due to Shelah; Shelah's recursion gives an upper bound between $2 \uparrow \uparrow 7$ and $2 \uparrow \uparrow 8$ for the case we consider, and no better value was previously known.
$A_{\infty}$-modules and Calogero-Moser Spaces

We re-examine the bijective correspondence between the set of isomorphism classes of ideals of the first Weyl algebra and associated quiver varieties (Calogero-Moser spaces) \cite{BW1, BW2}. We give a new explicit construction of this correspondence based on the notion of $\A$-envelope of a rank one torsion-free $A_1$-module. Though perhaps less geometric than other methods, our approach is much simpler and seems more natural from the point of view of deformation theory.
Should we pursue SOTA in Computational Creativity?

Should we pursue a state-of-the-art in Computational Creativity? The activity of ‘SOTA-chasing’, or working towards beating performance standards achieved by the current state of the art, is typical in many research disciplines relevant to computational creativity such as Machine Learning or Natural Language Generation (SOTA). Computational Creativity (CC) research does not typically engage with SOTA-type benchmarks. Consequently, it becomes harder to objectively identify high-performing systems in a creative domain (area of creative application), despite our research efforts build- ing signiﬁcant bodies of work in several domains. This paper critically engages with the use of SOTA in other related disciplines and explores the idea of working with SOTA-based evaluation in CC. The paper offers recommendations for (careful) use of SOTA to invigo-rate and direct CC progress.