Miracle-dz/UniFAR-FTUs huggingface dataset:
Using angular momentum maps to detect kinematically distinct galactic components

In this work, we introduce a physically motivated method of performing disc/spheroid decomposition of simulated galaxies, which we apply to the eagle sample. We make use of the healpix package to create Mollweide projections of the angular momentum map of each galaxy’s stellar particles. A number of features arise on the angular momentum space which allows us to decompose galaxies and classify them into different morphological types. We assign stellar particles with angular separation of less/greater than 30° from the densest grid cell on the angular momentum sphere to the disc/spheroid components, respectively. We analyse the spatial distribution for a subsample of galaxies and show that the surface density profiles of the disc and spheroid closely follow an exponential and a Sérsic profile, respectively. In addition discs rotate faster, have smaller velocity dispersions, are younger and are more metal rich than spheroids. Thus, our morphological classification reproduces the observed properties of such systems. Finally, we demonstrate that our method is able to identify a significant population of galaxies with counter-rotating discs and provide a more realistic classification of such systems compared to previous methods.
Dying of the Light: An X-Ray Fading Cold Quasar at z ∼ 0.405

Cold quasars are a rare subpopulation observed to host unobscured, X-ray luminous active galactic nuclei (AGN) while also retaining a cold gas supply fueling high star formation rates. These objects are interpreted as AGN early in their evolution. We present new SOFIA HAWC+ far-infrared observations, far-ultraviolet to far-infrared (FUV–FIR) photometry, and optical spectroscopy to characterize the accretion and star formation behavior in a cold quasar at z ∼ 0.405 (CQ 4479). CQ 4479 is a starburst galaxy with a predominantly young stellar population and a high gas mass fraction of ∼50%–70%. The AGN component has yet to become the dominant component of the FIR emission. We also find AGN bolometric luminosity that varies as a function of observation method and AGN region probed. Finally, we identify a candidate outflow feature corroborating the hypothesis that cold quasars have energetic feedback. This object presents an intriguing look into the early stages of AGN feedback and probes the rare phase where an AGN and cold gaseous component coexist.
Pedestrian Motion Tracking by Using Inertial Sensors on the Smartphone

Inertial Measurement Unit (IMU) has long been a dream for stable and reliable motion estimation, especially in indoor environments where GPS strength limits. In this paper, we propose a novel method for position and orientation estimation of a moving object only from a sequence of IMU signals collected from the phone. Our main observation is that human motion is monotonous and periodic. We adopt the Extended Kalman Filter and use the learning-based method to dynamically update the measurement noise of the filter. Our pedestrian motion tracking system intends to accurately estimate planar position, velocity, heading direction without restricting the phone’s daily use. The method is not only tested on the self-collected signals, but also provides accurate position and velocity estimations on the public RIDI dataset, i.e., the absolute transmit error is 1.28m for a 59-second sequence.
IDA: Improved Data Augmentation Applied to Salient Object Detection

In this paper, we present an Improved Data Aug-mentation (IDA) technique focused on Salient Object Detection (SOD). Standard data augmentation techniques proposed in the literature, such as image cropping, rotation, flipping, and resizing, only generate variations of the existing examples, providing a limited generalization. Our method combines image inpainting, affine transformations, and the linear combination of different generated background images with salient objects extracted from labeled data. Our proposed technique enables more precise control of the object’s position and size while preserving background information. The background choice is based on an inter-image optimization, while object size follows a uniform random distribution within a specified interval, and the object position is intra-image optimal. We show that our method improves the segmentation quality when used for training state-of-the-art neural networks on several famous datasets of the SOD field. Combining our method with others surpasses traditional techniques such as horizontal-flip in 0.52% for F-measure and 1.19% for Precision. We also provide an evaluation in 7 different SOD datasets, with 9 distinct evaluation metrics and an average ranking of the evaluated methods.
The birth of Romanian BERT

Large-scale pretrained language models have become ubiquitous in Natural Language Processing. However, most of these models are available either in high-resource languages, in particular English, or as multilingual models that compromise performance on individual languages for coverage. This paper introduces Romanian BERT, the first purely Romanian transformer-based language model, pretrained on a large text corpus. We discuss corpus com-position and cleaning, the model training process, as well as an extensive evaluation of the model on various Romanian datasets. We opensource not only the model itself, but also a repository that contains information on how to obtain the corpus, fine-tune and use this model in production (with practical examples), and how to fully replicate the evaluation process.
Estimating the treatment effect of the juvenile stay-at-home order on SARS-CoV-2 infection spread in Saline County, Arkansas

We investigate the treatment effect of the juvenile stay-at-home order (JSAHO) adopted in Saline County, Arkansas, from April 6 to May 7, in mitigating the growth of SARS-CoV-2 infection rates. To estimate the counterfactual control outcome for Saline County, we apply Difference-in-Differences and Synthetic Control design methodologies. Both approaches show that stay-at-home order (SAHO) significantly reduced the growth rate of the infections in Saline County during the period the policy was in effect, contrary to some of the findings in the literature that cast doubt on the general causal impact of SAHO with narrower scopes.
Eggs and larvae of Maurolicus muelleri (Gonostomatidae) and other fish eggs and larvae from two fjords in western Norway

Abstract The distribution and abundance of eggs and larvae of Maurolicus muelleri (Gmelin, 1788) in Masfjorden and Fensfjorden were investigated from April to September 1977, by means of the Bongo net 20. For each cruise the total number of M. muelleri eggs present in the spawning area was estimated and the total number of eggs spawned during this period was 9 × 1010 in Masfjorden and 58 × 1010 in Fensfjorden. The estimated stock sizes were 6 400 and 30 700 tons for Masfjorden and Fensfjorden respectively. Studies of fish eggs and larvae showed that 35 species were present in both fjords. Eggs of Brosme brosme, Microstomus kitt, Gaidropsarus sp. , and Ctenolabrus rupestris and larvae of Sebastes sp. and Benthosema glaciale were particularly abundant.
Diagnostics and clinical significance of Faecalibacterium prausnitzii

The human body contains over ten times more microbial cells than human cells, and over 100 times more microbial genes than human genes. All the microbes (bacteria, archaea and eukarya) residing in and on the human body are together referred to as the human microbiota. The microbial density is largest in the gastrointestinal tract and especially in the colon, where most of the residing microbes are anaerobic bacteria. Gut bacteria have many important tasks. They, for instance, protect against invading pathogens, participate in food digestion and take part in immune functions. Gut microbiota dysbiosis has been linked to various disorders such as obesity, asthma and inflammatory bowel disease (IBD). Faecalibacterium prausnitzii (F. prausnitzii) is one of the most abundant bacteria in a healthy human gut, and recent studies suggest this bacterium could be beneficial for gut health. The number of F. prausnitzii is significantly decreased in patients suffering from IBD. The aim of this study was to set up a practical method for quantifying F. prausnitzii from fecal samples, and to cultivate this obligatory anaerobe to enable antibiotic resistance testing. Two deoxyribonucleic acid (DNA) extraction protocols were compared to reveal the most suitable method for extracting F. prausnitzii DNA from feces. Quantitative polymerase chain reaction (qPCR) was compared with fluorescence in situ hybridization (FISH) to discover which method was more practical for studying F. prausnitzii abundance from fecal samples. GXT Stool Extraction Kit was found most effective and user-friendly method for extracting F. prausnitzii DNA from fecal samples. Best DNA quantity was gained when combining GXT Stool Extraction Kit with an extra homogenization with MO BIO homogenizer. qPCR with LightCycler automate was found to be the most useful method for analyzing F. prausnitzii abundance from feces. Fluorescence in situ hybridization (FISH) combined with fluorescence microscopy analysis was found extremely laborious and time-consuming when compared to qPCR. Because F. prausnitzii is an obligatory anaerobe with very strict growth requirements, the cultivation of the bacterium was challenging and the antibiotic resistance analysis could not be performed during the time scheduled for this study. In a small sample cohort (n = 27) included in this study, each of the fecal samples contained F. prausnitzii. The abundance of this particular bacterium in feces varied substantially between the subjects. The analysis of possible interrelationships between F. prausnitzii abundance and the clinical characteristics of the study subjects was excluded from this study due to small sample number. However, this preliminary study provides tools for quantifying the bacterium and assessing its clinical significance in future research.
Convex Shape and Rotation Model of Lucy Target (11351) Leucus from Lightcurves and Occultations

We report new photometric lightcurve observations of the Lucy Mission target (11351) Leucus acquired during the 2017, 2018, and 2019 apparitions. We use these data in combination with stellar occultations captured during five epochs to determine the sidereal rotation period, the spin axis orientation, a convex shape model, the absolute scale of the object, its geometric albedo, and a model of the photometric properties of the target. We find that Leucus is a prograde rotator with a spin axis located within a sky-projected radius of 3° (1σ) from J2000 Ecliptic coordinates (λ = 208°, β = +77°) or J2000 Equatorial Coordinates (R.A. = 248°, decl. = +58°). The sidereal period is refined to Psid = 445.683 ± 0.007 h. The convex shape model is irregular, with maximum dimensions of 60.8, 39.1, and 27.8 km. The convex model accounts for global features of the occultation silhouettes, although minor deviations suggest that local and global concavities are present. We determine a geometric albedo of pV = 0.043 ± 0.002. The derived phase curve supports a D-type classification for Leucus.
Evidence for Complex Fixed Points in Pandemic Data

Mathematical models used in epidemiology to describe the diffusion of infectious diseases often fail to reproduce the recurrent appearance of exponential growth in the number of infections (waves). This feature requires a time-modulation of some parameters of the model. Moreover, epidemic data show the existence of a region of quasi-linear growth (strolling period) of infected cases extending in between waves. We demonstrate that this constitutes evidence for the existence of near time-scale invariance that is neatly encoded via complex fixed points in the epidemic Renormalization Group approach. As a result, we obtain the first consistent mathematical description of multiple wave dynamics and its inter-wave strolling regime. Our results are tested and calibrated against the COVID-19 pandemic data. Because of the simplicity of our approach that is organized around symmetry principles, our discovery amounts to a paradigm shift in the way epidemiological data are mathematically modelled. We show that the strolling period is crucial in controlling the emergence of the next wave, thus encouraging the maintenance of (non)pharmaceutical measures during the period following a wave.
On the Capacity Enlargement of Gaussian Broadcast Channels With Passive Noisy Feedback

It is well known that the capacity region of an average transmit power constrained Gaussian Broadcast Channel (GBC) with independent noise realizations at the receivers is enlarged by the presence of causal noiseless feedback. When the noise variances at the receivers are identical, even passive feedback via independent memoryless Gaussian links can lead to a capacity region enlargement. The last fact remains true even when the feedback noise variance is very high, and available only from one of the receivers. While such capacity enlargements are feasible for several other feedback models in the Gaussian BC setting, it is also known that feedback does not change the capacity region for physically degraded broadcast channels. In this paper, we consider a two user GBC with independent noise realizations at the receivers, where the feedback links from the receivers are corrupted by independent additive Gaussian noise processes. We investigate the set of four noise variances, two forward and two feedback, for which no capacity enlargement is possible. A sharp characterization of this region is derived, i.e., any quadruple outside the presented region will lead to a capacity enlargement, whereas quadruples inside will leave the capacity region unchanged. Our results lead to the conclusion that when the forward noise variances are different, too noisy a feedback from one of the receivers alone is not always beneficial for enlarging the capacity region, be it from the stronger user or the weaker one, in sharp contrast to the case of equal forward noise variances.
Comments on old and recent experiments of "stickiness" of a soft solid to a rough hard surface

The old asperity model of Fuller and Tabor had demonstrated almost 50 years ago surprisingly good correlation with respect to quite a few experiments on the pull-off decay due to roughness of rubber spheres against roughened Perspex plates. We revisit here some features of the Fuller and Tabor model in view of the more recent theories and experiments, finding good correlation can be obtained only at intermediate resolutions, as perhaps in stylus profilometers. In general we confirm the predictions of the Persson & Tosatti and Bearing Area Model of Ciavarella, as stickiness depends largely on the long wavelength content of roughness, and not the fine features. Therefore, multi-instruments measurements should hopefully not be needed.
The quotient criterion in equivariant cohomology for elementary $2$-abelian group actions

Let $G$ be a 2-elementary abelian group and $X$ be a manifold with a locally standard action of $G$. We provide a criterion to determine the syzygy order of the $G$-equivariant cohomology of $X$ with coefficients over a field of characteristic two using a complex associated to the cohomology of the face filtration of the manifold with corners $X/G$. This result is the real version of the quotient criterion for locally standard torus actions developed by M. Franz in arXiv:1205.4462z .
Detection of Change Points in Piecewise Polynomial Signals Using Trend Filtering

While many approaches have been proposed for discovering abrupt changes in piecewise constant signals, few methods are available to capture these changes in piecewise polynomial signals. In this paper, we propose a change point detection method, PRUTF, based on trend filtering. By providing a comprehensive dual solution path for trend filtering, PRUTF allows us to discover change points of the underlying signal for either a given value of the regularization parameter or a specific number of steps of the algorithm. We demonstrate that the dual solution path constitutes a Gaussian bridge process that enables us to derive an exact and efficient stopping rule for terminating the search algorithm. We also prove that the estimates produced by this algorithm are asymptotically consistent in pattern recovery. This result holds even in the case of staircases (consecutive change points of the same sign) in the signal. Finally, we investigate the performance of our proposed method for various signals and then compare its performance against some state-of-the-art methods in the context of change point detection. We apply our method to three real-world datasets including the UK House Price Index (HPI), the GISS surface Temperature Analysis (GISTEMP) and the Coronavirus disease (COVID-19) pandemic.
A Contraction Approach to Model-based Reinforcement Learning

Model-based Reinforcement Learning has shown considerable experimental success. However, a theoretical understanding of it is still lacking. To this end, we analyze the error in cumulative reward for both stochastic and deterministic transitions using a contraction approach. We show that this approach doesn't require strong assumptions and can recover the typical quadratic error to the horizon. We prove that branched rollouts can reduce this error and are essential for deterministic transitions to have a Bellman contraction. Our results also apply to Imitation Learning, where we prove that GAN-type learning is better than Behavioral Cloning in continuous state and action spaces.
Phylogenetic and biogeographical review of the Drepanocerina (Coleoptera: Scarabaeidae: Oniticellini)

A phylogenetic analysis of Drepanocerina based on 81 morphological characters was conducted using various analytical approaches (Maximum Parsimony, New Technology Search, Bayesian Inference, and Phylogenetic Networks Analysis). Twelve lineages ranked at the generic level were resolved, with full congruency among the four analytical methods. Results allowed to propose two new genera, which are herein described as Paraixodina gen. nov. and Epidrepanus gen. nov. In addition, the previously unknown Eodrepanus integriceps and Sinodrepanus similis females were identified and described. A biogeographic analysis was performed based on 14 geographic macro-areas, partitioning the subtribe and outgroup distributional ranges. Based on the inferred phylogeny and biogeography, an ancestral distribution and radiation scenario from the Central East Africa macroarea (Afrotropical Region) was proposed. The biogeographic implications of past and present-day relationships within Drepanocerina was discussed.
Efecto de la temperatura y salinidad del agua en la incubación de huevos de botete diana Sphoeroides annulatus Effects of temperature and salinity on the egg incubation of bullseye puffer fish Sphoeroides annulatus

The effects of different water temperatures (22, 25, 28 and 31oC) and salinities between 0 and 60 psu (with intervals of 5 psu) on egg incubation of the bullseye puffer (Sphoeroides annulatus) were evaluated in this study. The embryos could not develop at 22oC and the highest hatching rate for normal larvae was observed at 28oC. At 0, 50, 55 and 60 psu larvae were unable to develop. Highest hatching rates were obtained at 25, 30 and 35 psu. It was concluded that water temperature and salinity affects the incubation period, embryo development stage and larval survival of the bullseye puffer.
Inference for Large-Scale Linear Systems with Known Coefficients

This paper considers the problem of testing whether there exists a non‐negative solution to a possibly under‐determined system of linear equations with known coefficients. This hypothesis testing problem arises naturally in a number of settings, including random coefficient, treatment effect, and discrete choice models, as well as a class of linear programming problems. As a first contribution, we obtain a novel geometric characterization of the null hypothesis in terms of identified parameters satisfying an infinite set of inequality restrictions. Using this characterization, we devise a test that requires solving only linear programs for its implementation, and thus remains computationally feasible in the high‐dimensional applications that motivate our analysis. The asymptotic size of the proposed test is shown to equal at most the nominal level uniformly over a large class of distributions that permits the number of linear equations to grow with the sample size.
Lightweight Detection of a Small Number of Large Errors in a Quantum Circuit

Suppose we want to implement a unitary U, for instance a circuit for some quantum algorithm. Suppose our actual implementation is a unitary U~, which we can only apply as a black-box. In general it is an exponentially-hard task to decide whether U~ equals the intended U, or is significantly different in a worst-case norm. In this paper we consider two special cases where relatively efficient and lightweight procedures exist for this task.First, we give an efficient procedure under the assumption that U and U~ (both of which we can now apply as a black-box) are either equal, or differ significantly in only one k-qubit gate, where k=O(1) (the k qubits need not be contiguous). Second, we give an even more lightweight procedure under the assumption that U and U~ are Clifford circuits which are either equal, or different in arbitrary ways (the specification of U is now classically given while U~ can still only be applied as a black-box). Both procedures only need to run U~ a constant number of times to detect a constant error in a worst-case norm. We note that the Clifford result also follows from earlier work of Flammia and Liu, and da Silva, Landon-Cardinal, and Poulin.In the Clifford case, our error-detection procedure also allows us efficiently to learn (and hence correct) U~ if we have a small list of possible errors that could have happened to U; for example if we know that only O(1) of the gates of U~ are wrong, this list will be polynomially small and we can test each possible erroneous version of U for equality with U~.
Black Hole Mergers from Hierarchical Triples in Dense Star Clusters

Hierarchical triples are expected to be produced by the frequent binary-mediated interactions in the cores of globular clusters. In some of these triples, the tertiary companion can drive the inner binary to merger following large eccentricity oscillations, as a result of the eccentric Kozai–Lidov mechanism. In this paper, we study the dynamics and merger rates of black hole (BH) hierarchical triples, formed via binary–binary encounters in the CMC Cluster Catalog, a suite of cluster simulations with present-day properties representative of the Milky Way’s globular clusters. We compare the properties of the mergers from triples to the other merger channels in dense star clusters, and show that triple systems do not produce significant differences in terms of mass and effective spin distribution. However, they represent an important pathway for forming eccentric mergers, which could be detected by LIGO–Virgo/KAGRA (LVK), and future missions such as LISA and the DECi-hertz Interferometer Gravitational wave Observatory. We derive a conservative lower limit for the merger rate from this channel of 0.35 Gpc−3 yr−1 in the local universe and up to ∼9% of these events may have a detectable eccentricity at LVK design sensitivity. Additionally, we find that triple systems could play an important role in retaining second-generation BHs, which can later merge again in the core of the host cluster.