Miracle-dz/UniFAR-FTUs huggingface dataset:
Effective Favor Exchange for Human-Agent Negotiation Challenge at IJCAI 2020

This document describes Pilot, our submission for Human-Agent Negotiation Challenge at IJCAI 2020. Pilot is a virtual human that participates in a sequence of three negotiations with a human partner. Our system is based on the Interactive Arbitration Guide Online (IAGO) negotiation framework. We leverage prior Affective Computing and Psychology research in negotiations to guide various key principles that define the behavior and personality of our agent. Pilot has been selected as one of the finalists for presentation at IJCAI.
Volatile components and antimicrobial activity of Citrus sinensis var. mosammi leaves oil

The hydro-distilled essential oil of Citrus sinensis var. mosammi was analyzed by Gas chromatography–mass spectrometry (GC-MS). Out of 18 components, 7 components were identified from their fragmentation pattern. Among the identified constituents, β-phyllendrene (27.544 %) was found as major component followed by 3 carene (7.630%), limonene (4.873%), β-pinene (3.278%), caryophyllene (3.154%), diethyltoluamide (2.339%) and a-pinene (1.298%). The essential oil of C. sinensis var. mosammi leaves had promising antimicrobial activity against the tested bacterial and fungal strains. The inhibition zones were measured after 48 and 96 h following disc diffusion method. The results indicated thatmaximum zone of inhibition was exhibited by Aspergillus ficcum (17 mm) andstaphylococcus aureus (16 mm) after a period of 96 h of incubation at 25°C in case of fungal and 37°C for bacterial strains, respectively. Key words: Gas chromatography–mass spectrometry (GC-MS), essential oil, zones of inhibition, antimicrobial activity and fragmentation pattern.
A Survey on Automated Log Analysis for Reliability Engineering

Logs are semi-structured text generated by logging statements in software source code. In recent decades, software logs have become imperative in the reliability assurance mechanism of many software systems, because they are often the only data available that record software runtime information. As modern software is evolving into a large scale, the volume of logs has increased rapidly. To enable effective and efficient usage of modern software logs in reliability engineering, a number of studies have been conducted on automated log analysis. This survey presents a detailed overview of automated log analysis research, including how to automate and assist the writing of logging statements, how to compress logs, how to parse logs into structured event templates, and how to employ logs to detect anomalies, predict failures, and facilitate diagnosis. Additionally, we survey work that releases open-source toolkits and datasets. Based on the discussion of the recent advances, we present several promising future directions toward real-world and next-generation automated log analysis.
A Self Contour-based Rotation and Translation-Invariant Transformation for Point Clouds Recognition

Recently, several direct processing point cloud models have achieved state-of-the-art performances for classification and segmentation tasks. However, these methods lack rotation robustness, and their performances degrade severely under random rotations, failing to extend to real-world applications with varying orientations. To address this problem, we propose a method named Self Contour-based Transformation (SCT), which can be flexibly integrated into a variety of existing point cloud recognition models against arbitrary rotations without any extra modifications. The SCT provides efficient and mathematically proved rotation and translation invariance by introducing Rotation and Translation-Invariant Transformation. It linearly transforms Cartesian coordinates of points to the self contour-based rotation-invariant representations while maintaining the global geometric structure. Moreover, to enhance discriminative feature extraction, the Frame Alignment module is further introduced, aiming to capture contours and transform self contour-based frames to the intra-class frame. Extensive experimental results and mathematical analyses show that the proposed method outperforms the state-of-the-art approaches under arbitrary rotations without any rotation augmentation on standard benchmarks, including ModelNet40, ScanObjectNN and ShapeNet.
Large-scale simulations of H and He reionization and heating driven by stars and more energetic sources

We present simulations of cosmic reionization and reheating from $z=18$ to $z=5$, investigating the role of stars (emitting soft UV-photons), nuclear black holes (BHs, with power-law spectra), X-ray binaries (XRBs, with hard X-ray dominated spectra), and the supernova-associated thermal bremsstrahlung of the diffuse interstellar medium (ISM, with soft X-ray spectra). We post-process the hydrodynamical simulation Massive-Black II (MBII) with multifrequency ionizing radiative transfer. The source properties are directly derived from the physical environment of MBII, and our only real free parameter is the ionizing escape fraction $f_{\rm esc}$. We find that, among the models explored here, the one with an escape fraction that decreases with decreasing redshift yields results most in line with observations, such as of the neutral hydrogen fraction and the Thomson scattering optical depth. Stars are the main driver of hydrogen reionization and consequently of the thermal history of the intergalactic medium (IGM). We obtain $\langle x_{\rm HII} \rangle = 0.99998$ at $z=6$ for all source types, with volume averaged temperatures $\langle T \rangle \sim 20,000~{\rm K}$. BHs are rare and negligible to hydrogen reionization, but conversely they are the only sources which can fully ionize helium, increasing local temperatures by $\sim 10^4~{\rm K}$. The thermal and ionization state of the neutral and lowly ionized hydrogen differs significantly with different source combinations, with ISM and (to a lesser extent) XRBs, playing a significant role and, as a consequence, determining the transition from absorption to emission of the 21 cm signal from neutral hydrogen.
The Nickel Mass Distribution of Stripped-envelope Supernovae: Implications for Additional Power Sources

We perform a systematic study of the 56Ni mass (M Ni) of 27 stripped-envelope supernovae (SESNe) by modeling their light-curve tails, highlighting that use of “Arnett’s rule” overestimates M Ni for SESNe by a factor of ∼2. Recently, Khatami & Kasen presented a new model relating the peak time (t p) and luminosity (L p) of a radioactively powered supernova to its M Ni that addresses several limitations of Arnett-like models, but depends on a dimensionless parameter, β. Using observed t p, L p, and tail-measured M Ni values for 27 SESNe, we observationally calibrate β for the first time. Despite scatter, we demonstrate that the model of Khatami & Kasen with empirically calibrated β values provides significantly improved measurements of M Ni when only photospheric data are available. However, these observationally constrained β values are systematically lower than those inferred from numerical simulations, primarily because the observed sample has significantly higher (0.2–0.4 dex) L p for a given M Ni. While effects due to composition, mixing, and asymmetry can increase L p none can explain the systematically low β values. However, the discrepancy can be alleviated if ∼7%–50% of L p for the observed sample comes from sources other than radioactive decay. Either shock cooling or magnetar spin-down could provide the requisite luminosity. Finally, we find that even with our improved measurements, the M Ni values of SESNe are still a factor of ∼3 larger than those of hydrogen-rich Type II SNe, indicating that these supernovae are inherently different in terms of the initial mass distributions of their progenitors or their explosion mechanisms.
RBE with Non-Poisson Distribution of Radiation Induced Strand Breaks.

Postulating that increasing linear energy transfer (LET) causes non-random clustering of lethal lesions to deviate from the Poisson distribution, we employ a non-Poisson approach as a more flexible alternative that accounts for overdispersion of lethal lesions. Using non-homologous end-joining (NHEJ) pathway of double-strand break repair, a customized negative binomial (NB) distribution is used to describe the distribution of lethal events in a cell nucleus. The proposed model provides a novel, mechanistically based explanation for the measured values of the biological relevant quantities, such as model parameters and relative biological effectiveness (RBE) of the surviving cells, for various light ion types and LET values. The estimated quantities are compared with the predictions of several mechanism-inspired models and experimental data at medium and high LET values. The results examined are closer to the Microdosimetric-Kinetic model predictions for helium and carbon ions but progressively lower than trends predicted by the Local Effect Model and the Repair Misrepair-Fixation model in the large LET region. The results support the view that the limitation in the increase in RBE at high LET can be accounted for entirely, or, in large part, by clustering of lethal events to cause deviation from the Poisson distribution.
Testing gravity with cold atom interferometry: results and prospects

Atom interferometers have been developed in the last three decades as new powerful tools to investigate gravity. They were used for measuring the gravity acceleration, the gravity gradient, and the gravity-field curvature, for the determination of the gravitational constant, for the investigation of gravity at microscopic distances, to test the equivalence principle of general relativity and the theories of modified gravity, to probe the interplay between gravitational and quantum physics and to test quantum gravity models, to search for dark matter and dark energy, and they were proposed as new detectors for the observation of gravitational waves. Here I describe past and ongoing experiments with an outlook on what I think are the main prospects in this field and the potential to search for new physics.
Variable stars in the field of intermediate-age open cluster NGC 559

This work presents the first long-term photometric variability survey of the intermediate-age open cluster NGC 559. Time-series V band photometric observations on 40 nights taken over more than three years with three different telescopes are analyzed to search for variable stars in the cluster. We investigate the data for the periodicity analysis and reveal 70 variable stars including 67 periodic variables in the target field, all of them are newly discovered. The membership analysis of the periodic variables reveal that 30 of them belong to the cluster and remaining 37 are identified as field variables. Out of the 67 periodic variables, 48 are short-period (P 1 day) variables. The variable stars have periodicity between 3 hours to 41 days and their brightness ranges from V = 10.9 to 19.3 mag. The periodic variables belonging to the cluster are then classified into different variability types on the basis of observational properties such as shape of the light curves, periods, amplitudes, as well as their positions in the Hertzsprung-Russell (H-R) diagram. As a result, we identify one Algol type eclipsing binary, one possible blue straggler star, 3 slowly pulsating B type stars, 5 rotational variables, 11 non-pulsating variables, 2 FKCOM variables and remaining 7 are characterized as miscellaneous variables. We also identify three Eclipsing Binary stars (EBs) belonging to the field star population. The PHOEBE package is used to analyse the light curve of all four EBs in order to determine the parameters of the binary systems such as masses, temperatures and radii.
A comparison of internal validation methods for validating predictive models for binary data with rare events

In clinical research, prediction models for binary data are frequently developed in logistic regression framework to predict the risk of patient’s health status such as death and illness. However, when the outcome is rare, the maximum likelihood (ML) based standard logistic regression has been reported to show poor predictive performance by providing overfitted model. To overcome this, penalized maximum likelihood (PML) based logistic models are being widely used in risk prediction, however, their predictive performance in validation settings is not well-documented. Several validation approaches, namely split-sample, crossvalidation, bootstrap validation and its two variants 0.632 and 0.632+, have been widely used to validate the performance of a prediction model, however, it is also unclear which one of these approaches best for estimating accurate predictive performance of a rare-outcome model. This paper focused on evaluating predictive performance of PML based logistic model in such validation settings in comparison with ML based standard model and identifying the effective validation method. An extensive simulation study was performed by creating several scenarios to reflect modeling in dataset with few events. The results revealed that PML based model showed better performance by reducing overfitting to some extent and increasing discriminatory ability over ML based model, irrespective of validation methods under study. Of the validation methods, regular bootstrap and its variants 0.632 and 0.632+, particularly 0.632+, performed well by providing nearly accurate and stable estimate of the true predictive performance. We also illustrated the methods applying them to cardiac data set with few events.
Use of home range behaviour to assess establishment in translocated giraffes

Conservation translocation is a management technique employed to introduce, re-introduce or reinforce wild animal and plant populations. Giraffe translocations are being conducted throughout Africa, but the lack of effective post-translocation monitoring limits our ability to assess translocation outcomes. One potential indicator of translocation success is the establishment of characteristic movement and home range behaviour in the new location. We analysed the post-translocation movement patterns of six Global Positioning System-collared Angolan giraffes (Giraffa camelopardalis angolensis) in three regions of Namibia. We estimated home range size with minimum convex polygon (MCP) and adaptive local convex hull estimators, and assessed home range behaviour with the localizing tendency model and a home range Monte Carlo bootstrap analysis. Four of the six giraffes appeared to establish home ranges, indicating short-term translocation success. The other two giraffes exhibited long-distance linear movements throughout the observation period, suggesting they did not establish home ranges. Home range sizes varied greatly among regions. Our results suggest monitoring translocated animals for the establishment of characteristic movement behaviour could be a useful early indicator of translocation success. Resume La translocation a des fins de conservation est une technique de gestion employee pour introduire, reintroduire ou renforcer des populations sauvages de plantes ou d'animaux. Des translocations de girafes ont lieu dans toute l'Afrique, mais le manque de suivi apres ces translocations limite nos possibilites d'en evaluer les resultats. Un indicateur possible du succes d'une translocation est l’etablissement de deplacements et de comportements territoriaux caracteristiques au nouvel endroit. Nous avons analyse le schema des deplacements apres translocation de six girafes d'Angola (Giraffa camelopardalis angolensis) equipees de collier GPS dans trois regions de Namibie. Nous avons estime la taille de leur domaine vital avec la methode du polygone convexe minimum et des estimations du polygone convexe adaptees a la situation locale et nous avons evalue le comportement territorial avec le modele de tendance de localisation et une analyse de bootstrap (inference statistique) de Monte Carlo. Quatre des six girafes semblaient etablir un domaine vital, ce qui indique une reussite rapide de la translocation. Les deux autres ont presente de longs deplacements lineaires pendant toute la periode d'observation, ce qui suggere qu'elles n'ont pas etabli de territoire. La taille des domaines viataux variait beaucoup selon les regions. Nos resultats suggerent que le suivi, chez des animaux deplaces, de l’etablissement d'un comportement de deplacement caracteristique pourrait etre un indicateur precoce utile du succes d'une translocation.
A comparative study of satellite galaxies in Milky Way-like galaxies from HSC, DECaLS, and SDSS

We conduct a comprehensive and statistical study of the luminosity functions (LFs) for satellite galaxies, by counting photometric galaxies from HSC, DECaLS and SDSS around isolated central galaxies (ICGs) and galaxy pairs from the SDSS/DR7 spectroscopic sample. Results of different surveys show very good agreement. The satellite LFs can be measured down to $M_V\sim-10$, and for central primary galaxies as small as $8.5<\log_{10}M_\ast/M_\odot<9.2$ and $9.2<\log_{10}M_\ast/M_\odot<9.9$, which implies there are on average 3--8 satellites with $M_V<-10$ around LMC-mass ICGs. The bright end cutoff of satellite LFs and the satellite abundance are both sensitive to the magnitude gap between the primary and its companions, indicating galaxy systems with larger magnitude gaps are on average hosted by less massive dark matter haloes. By selecting primaries with stellar mass similar to our MW, we discovered that i) the averaged satellite LFs of ICGs with different magnitude gaps to their companions and of galaxy pairs with different colour or colour combinations all show steeper slopes than the MW satellite LF; ii) there are more satellites with $-15<M_V<-10$ than those in our MW; iii) there are on average 1.5 to 2.5 satellites with $M_V<-16$ around ICGs, consistent with our MW. Thus the MW and its satellite system are atypical of our sample of MW-mass systems. In consequence, our MW is not a good representative of other MW-mass galaxies. Strong cosmological implications based on only MW satellites await additional discoveries of fainter satellites in extra-galactic systems. Interestingly, the MW satellite LF is typical among other MW-mass systems within 40~Mpc in the local Universe, perhaps implying the Local Volume is an under-dense region.
An Increase in Small-planet Occurrence with Metallicity for Late-type Dwarf Stars in the Kepler Field and Its Implications for Planet Formation

While it is well-established that giant-planet occurrence rises rapidly with host star metallicity, it is not yet clear if small-planet occurrence around late-type dwarf stars depends on host star metallicity. Using the Kepler Data Release 25 planet candidate list and its completeness data products, we explore planet occurrence as a function of metallicity in the Kepler field’s late-type dwarf stellar population. We find that planet occurrence increases with metallicity for all planet radii Rp down to at least Rp ≈ 2 R⊕, and that in the range 2 R⊕ ≲ Rp ≲ 5 R⊕, planet occurrence scales linearly with metallicity Z. Extrapolating our results, we predict that short-period planets with Rp ≲ 2 R⊕ should be rare around early-M dwarf stars with [M/H] ≲ −0.5 or late-M dwarf stars with [M/H] ≲ +0.0. This dependence of planet occurrence on metallicity observed in the Kepler field emphasizes the need to control for metallicity in estimates of planet occurrence for late-type dwarf stars like those targeted by Kepler’s K2 extension and the Transiting Exoplanet Survey Satellite. We confirm the theoretical expectation that the small-planet occurrence–host star metallicity relation is stronger for low-mass stars than for solar-type stars. We establish that the expected solid mass in planets around late-type dwarfs in the Kepler field is comparable to the total amount of planet-making solids in their protoplanetary disks. We argue that this high efficiency of planet formation favors planetesimal accretion over pebble accretion as the origin of the small planets observed by Kepler around late-type dwarf stars.
The near-infrared companion to HD 94660 (=KQ Vel)

Context. The Bp star HD 94660 is a single-lined spectroscopic binary. Some authors have suggested that the unseen companion of at least 2 M⊙ may be a compact object. Aims. We intend to study this multiple system in detail, especially to learn more about the thus far unseen companion. Methods. We have collected and analyzed PIONIER (Precision Integrated-Optics Near-infrared Imaging ExpeRiment) H-band data from the Very Large Telescope Interferometer, TESS (Transiting Exoplanet Survey Satellite) visible photometric data, and X-ray observations with Chandra of HD 94660. Results. Using PIONIER, we were able to detect the companion to HD 94660, which is absent from high quality spectra at visible wavelengths, with a magnitude difference of 1.8 in the H band at a separation of 18.72 mas. The TESS light curve shows variations with a period of 2.1 d and also flaring. The Chandra spectrum is well described by emission from hot thermal plasma, yet it might include a nonthermal component. The X-ray properties are compatible with a magnetically active companion, while it is also possible that there might be some magnetospheric contributions from the primary. Conclusions. We can rule out that the companion to HD 94660 is a compact source. It is also very unlikely that this companion is a single star, as the estimated mass of more than 2 M⊙, the magnitude difference of 1.8 in the H band, and its nondetection in visible spectra are difficult to realize in a single object. One alternative could be a pair of late F stars, which would also be responsible for the detected photometric variations. Interferometric observations over the full binary orbit are necessary to determine the real mass of the companion and to add constraints on the overall geometry of the system.
Iterative Refinement in the Continuous Space for Non-Autoregressive Neural Machine Translation

We propose an efficient inference procedure for non-autoregressive machine translation that iteratively refines translation purely in the continuous space. Given a continuous latent variable model for machine translation (Shu et al., 2020), we train an inference network to approximate the gradient of the marginal log probability of the target sentence, using only the latent variable as input. This allows us to use gradient-based optimization to find the target sentence at inference time that approximately maximizes its marginal probability. As each refinement step only involves computation in the latent space of low dimensionality (we use 8 in our experiments), we avoid computational overhead incurred by existing non-autoregressive inference procedures that often refine in token space. We compare our approach to a recently proposed EM-like inference procedure (Shu et al., 2020) that optimizes in a hybrid space, consisting of both discrete and continuous variables. We evaluate our approach on WMT'14 En-De, WMT'16 Ro-En and IWSLT'16 De-En, and observe two advantages over the EM-like inference: (1) it is computationally efficient, i.e. each refinement step is twice as fast, and (2) it is more effective, resulting in higher marginal probabilities and BLEU scores with the same number of refinement steps. On WMT'14 En-De, for instance, our approach is able to decode 6.2 times faster than the autoregressive model with minimal degradation to translation quality (0.9 BLEU).
Classification of limit varieties of $\mathscr J$-trivial monoids

A variety of algebras is called limit if it is non-finitely based but all its proper subvarieties are finitely based. We present a new pair of limit varieties of monoids and show that together with the five limit varieties of monoids previously discovered by Jackson, Zhang and Luo and the first-named author, there are exactly seven limit varieties of $\mathscr J$-trivial monoids.