Miracle-dz/UniFAR-FTUs huggingface dataset:
NCLS: Neural Cross-Lingual Summarization

Cross-lingual summarization (CLS) is the task to produce a summary in one particular language for a source document in a different language. Existing methods simply divide this task into two steps: summarization and translation, leading to the problem of error propagation. To handle that, we present an end-to-end CLS framework, which we refer to as Neural Cross-Lingual Summarization (NCLS), for the first time. Moreover, we propose to further improve NCLS by incorporating two related tasks, monolingual summarization and machine translation, into the training process of CLS under multi-task learning. Due to the lack of supervised CLS data, we propose a round-trip translation strategy to acquire two high-quality large-scale CLS datasets based on existing monolingual summarization datasets. Experimental results have shown that our NCLS achieves remarkable improvement over traditional pipeline methods on both English-to-Chinese and Chinese-to-English CLS human-corrected test sets. In addition, NCLS with multi-task learning can further significantly improve the quality of generated summaries. We make our dataset and code publicly available here: http://www.nlpr. ia.ac. cn/cip/dataset.htm.
Algorithm-Based Fault Tolerance for Parallel Stencil Computations

The increase in HPC systems size and complexity, together with increasing on-chip transistor density, power limitations, and number of components, render modern HPC systems subject to soft errors. Silent data corruptions (SDCs) are typically caused by such soft errors in the form of bit-flips in the memory subsystem and hinder the correctness of scientific applications. This work addresses the problem of protecting a class of iterative computational kernels, called stencils, against SDCs when executing on parallel HPC systems. Existing SDC detection and correction methods are in general either inaccurate, inefficient, or targeting specific application classes that do not include stencils. This work proposes a novel algorithm-based fault tolerance (ABFT) method to protect scientific applications that contain arbitrary stencil computations against SDCs. The ABFT method can be applied both online and offline to accurately detect and correct SDCs in 2D and 3D parallel stencil computations. We present a formal model for the proposed method including theorems and proofs for the computation of the associated check-sums as well as error detection and correction. We experimentally evaluate the use of the proposed ABFT method on a real 3D stencil-based application (HotSpot3D) via a fault-injection, detection, and correction campaign. Results show that the proposed ABFT method achieves less than 8% overhead compared to the performance of the unprotected stencil application. Moreover, it accurately detects and corrects SDCs. While the offline ABFT version corrects errors more accurately, it may incur a small additional overhead than its online counterpart.
Safe beginning for the Universe?

When general relativity is augmented by quadratic gravity terms, it becomes a renormalisable theory of gravity. This theory may admit a non-Gaussian fixed point as envisaged in the asymptotic safety program, rendering the theory trustworthy to energies up to the Planck scale and even beyond. We show that requiring physical solutions to have a finite action imposes a strong selection on big-bang-type universes. More precisely we find that, in the approach to zero volume, both anisotropies and inhomogeneities are suppressed while the scale factor is required to undergo accelerated expansion. This provides initial conditions which are favourable to the onset of an inflationary phase while also providing a suitable starting point for the second law of thermodynamics in the spirit of the Weyl curvature hypothesis.
Discovery of a New Stellar Subpopulation Residing in the (Inner) Stellar Halo of the Milky Way

We report the discovery of a unique collection of metal-poor giant stars that exhibit anomalously high levels of 28Si, clearly above typical Galactic levels. Our sample spans a narrow range of metallicities, peaking at −1.07 ± 0.06, and exhibits abundance ratios of [Si, Al/Fe] that are as extreme as those observed in Galactic globular clusters (GCs), and Mg is slightly less overabundant. In almost all the sources we used, the elemental abundances were redetermined from high-resolution spectra, which were reanalyzed assuming LTE. Thus, we compiled the main element families, namely, the light elements (C, N), α-elements (O, Mg, Si), iron-peak element (Fe), s-process elements (Ce, Nd), and the light odd-Z element (Al). We also provide dynamical evidence that most of these stars lie on tight (inner) halo-like and retrograde orbits passing through the bulge. Such kinds of objects have been found in present-day halo GCs, providing the clearest chemical signature of past accretion events in the (inner) stellar halo of the galaxy, possibly formed as the result of dissolved halo GCs. Their chemical composition is, in general, similar to that of typical GC populations, although several differences exist.
Does the pressure gradient in renal artery stenosis before and after percutaneous transluminal renal angioplasty predict initial and long-term outcome?

Aim: To evaluate whether measurement of mean pressure gradient (MPG) over a renal artery stenosis (RAS) before and after percutaneous transluminal renal angioplasty (PTRA) predicts initial and long-term outcome. Materials and methods: In our institution, PTRA has generally been performed in RAS patients with MPG > 10 mmHg. We related MPG before and after PTRA in 287 consecutive RAS patients (age 65± 14 years, 152 (53%) men) undergoing PTRA on 332 kidneys to blood pressures (BP), renal function and treatment during 4.1 ± 3.3 years of retrospective follow-up. The patients were divided into four groups according to MPG before PTRA: group A, MPG 0‐29 mmHg,n = 60 patients, 79 kidneys; group B, MPG 30‐59 mmHg, n = 48 patients, 57 kidneys; group C, MPG 60‐199 mmHg, n = 40 patients, 43 kidneys; group D, occlusive pressure without numerical value obtainable, n = 139 patients, 153 kidneys. Results: In groups A, B, and C, MPG before PTRA correlated with systolic BP (SBP) before PTRA, (r = 0.242; p = 0.0032) and with the reduction in SBP during follow-up (r = 0.243; p = 0.0034). MPG decreased from 38.7 ± 26.8 mmHg before PTRA to 1.3 ± 3.2 mmHg after PTRA ( p 10 mmHg. Whether PTRA is also indicated with MPG < 10 mmHg requires further evaluation. Residual MPG post PTRA predicts re-do but not the outcome of the intervention.
Sentence-Level Content Planning and Style Specification for Neural Text Generation

Building effective text generation systems requires three critical components: content selection, text planning, and surface realization, and traditionally they are tackled as separate problems. Recent all-in-one style neural generation models have made impressive progress, yet they often produce outputs that are incoherent and unfaithful to the input. To address these issues, we present an end-to-end trained two-step generation model, where a sentence-level content planner first decides on the keyphrases to cover as well as a desired language style, followed by a surface realization decoder that generates relevant and coherent text. For experiments, we consider three tasks from domains with diverse topics and varying language styles: persuasive argument construction from Reddit, paragraph generation for normal and simple versions of Wikipedia, and abstract generation for scientific articles. Automatic evaluation shows that our system can significantly outperform competitive comparisons. Human judges further rate our system generated text as more fluent and correct, compared to the generations by its variants that do not consider language style.
Moderate deviations for the range of a transient random walk. II

We obtain sharp upper and lower bounds for the moderate deviations of the volume of the range of a random walk in dimension five and larger. Our results encompass two regimes: a Gaussian regime for small deviations, and a stretched exponential regime for larger deviations. In the latter regime, we show that conditioned on the moderate deviations event, the walk folds a small part of its range in a ball-like subset. Also, we provide new path properties, in dimension three as well. Besides the key role Newtonian capacity plays in this study, we introduce two original ideas, of general interest, which strengthen the approach developed in \cite{AS}.
Pareto-Optima for a Generalized Ramsey Model

We consider a Ramsey model with several households with heterogeneous preferences who are able to borrow capital to each other. Since the capital constraints of one household then depends on the others' capital, one can no longer optimize each household's welfare individually. This problem formulation leads to a Pareto optimization problem. We consider existence and first order optimality conditions as well as some numerical results.
Towards Making a Dependency Parser See

We explore whether it is possible to leverage eye-tracking data in an RNN dependency parser (for English) when such information is only available during training - i.e. no aggregated or token-level gaze features are used at inference time. To do so, we train a multitask learning model that parses sentences as sequence labeling and leverages gaze features as auxiliary tasks. Our method also learns to train from disjoint datasets, i.e. it can be used to test whether already collected gaze features are useful to improve the performance on new non-gazed annotated treebanks. Accuracy gains are modest but positive, showing the feasibility of the approach. It can serve as a first step towards architectures that can better leverage eye-tracking data or other complementary information available only for training sentences, possibly leading to improvements in syntactic parsing.
KLEESpectre

Spectre-style attacks disclosed in early 2018 expose data leakage scenarios via cache side channels. Specifically, speculatively executed paths due to branch mis-prediction may bring secret data into the cache, which are then exposed via cache side channels even after the speculative execution is squashed. Symbolic execution is a well-known test generation method to cover program paths at the level of the application software. In this article, we extend symbolic execution with modeling of cache and speculative execution. Our tool KLEESPECTRE, built on top of the KLEE symbolic execution engine, can thus provide a testing engine to check for data leakage through the cache side channel as shown via Spectre attacks. Our symbolic cache model can verify whether the sensitive data leakage due to speculative execution can be observed by an attacker at a given program point. Our experiments show that KLEESPECTRE can effectively detect data leakage along speculatively executed paths and our cache model can make the leakage detection more precise.
Superimposed Coding-Based CSI Feedback Using 1-Bit Compressed Sensing

In a frequency division duplex massive multiple input multiple output system, the channel state information (CSI) feedback causes a significant bandwidth resource occupation. In order to save the uplink bandwidth resources, a 1-bit compressed sensing (CS)-based CSI feedback method assisted by superimposed coding (SC) is proposed. Using 1-bit CS and SC techniques, the compressed support-set information and downlink CSI (DL-CSI) are superimposed on the uplink user data sequence (UL-US) and fed back to base station. Compared with the standalone SC-based feedback, the proposed method is shown with analysis and simulation results to improve the UL-US’s bit error ratio and the DL-CSI’s accuracy, without acquiring exclusive uplink bandwidth resources for DL-CSI feedback.
Combining Spans into Entities: A Neural Two-Stage Approach for Recognizing Discontiguous Entities

In medical documents, it is possible that an entity of interest not only contains a discontiguous sequence of words but also overlaps with another entity. Entities of such structures are intrinsically hard to recognize due to the large space of possible entity combinations. In this work, we propose a neural two-stage approach to recognizing discontiguous and overlapping entities by decomposing this problem into two subtasks: 1) it first detects all the overlapping spans that either form entities on their own or present as segments of discontiguous entities, based on the representation of segmental hypergraph, 2) next it learns to combine these segments into discontiguous entities with a classifier, which filters out other incorrect combinations of segments. Two neural components are designed for these subtasks respectively and they are learned jointly using a shared encoder for text. Our model achieves the state-of-the-art performance in a standard dataset, even in the absence of external features that previous methods used.
Zariski Equisingularity and Lipschitz Stratification of a Family of Surface Singularities

We consider the generic Zariski equisingular families of surface, not necessarily isolated, singularities in $\mathbb{C}^3$. We show that a natural stratification of such a family given by the singular set and the generic family of polar curves provides a Lipschitz stratification in the sense of Mostowski. In particular, such families are bi-Lipschitz trivial by trivializations obtained by integrating Lipschitz vector fields.
Searching for signs of jet-driven negative feedback in the nearby radio galaxy UGC 05771

Hydrodynamical simulations predict that the jets of young radio sources can inhibit star formation in their host galaxies by injecting heat and turbulence into the interstellar medium (ISM). To investigate jet–ISM interactions in a galaxy with a young radio source, we have carried out a multiwavelength study of the z = 0.025 Compact Steep Spectrum radio source hosted by the early-type galaxy UGC 05771. Using Keck/OSIRIS observations, we detected H2 1–0 S(1) and [Fe ii] emission at radii of 100s of parsecs, which traces shocked molecular and ionized gas being accelerated outwards by the jets to low velocities, creating a ‘stalling wind’. At kpc radii, we detected shocked ionized gas using observations from the CALIFA survey, covering an area much larger than the pc-scale radio source. We found that existing interferometric radio observations fail to recover a large fraction of the source’s total flux, indicating the likely existence of jet plasma on kpc scales, which is consistent with the extent of shocked gas in the host galaxy. To investigate the star formation efficiency in UGC 05771, we obtained IRAM CO observations to analyse the molecular gas properties. We found that UGC 05771 sits below the Kennicutt–Schmidt relation, although we were unable to definitively conclude if direct interactions from the jets are inhibiting star formation. This result shows that jets may be important in regulating star formation in the host galaxies of compact radio sources.
Super-Earth masses sculpted by pebble isolation around stars of different masses

We developed a pebble-driven core accretion model to study the formation and evolution of planets around stars in the stellar mass range of 0.08 M⊙–1 M⊙. By Monte Carlo sampling of the initial conditions, the growth and migration of a large number of individual protoplanetary embryos were simulated in a population synthesis manner. We tested two hypotheses for the birth locations of embryos: at the water ice line or log-uniformly distributed over entire protoplanetary disks. Two types of disks with different turbulent viscous parametersαtof 10−3and 10−4are also investigated to shed light on the role of outward migration of protoplanets. The forming planets are compared with the observed exoplanets in terms of mass, semimajor axis, metallicity, and water content. We find that gas giant planets are likely to form when the characteristic disk sizes are larger, the disk accretion rates are higher, the disks are more metal rich, and/or their stellar hosts are more massive. Our model shows that first, the characteristic mass of super-Earth is set by the pebble isolation mass. Super-Earth masses increase linearly with the mass of its stellar host, which corresponds to one Earth mass around a late M-dwarf star and 20 Earth masses around a solar-mass star. Second, the low-mass planets, up to 20 M⊕, can form around stars with a wide range of metallicities, while massive gas giant planets are preferred to grow around metal rich stars. Third, super-Earth planets that are mainly composed of silicates, with relatively low water fractions, can form from protoplanetary embryos at the water ice line in weakly turbulent disks where outward migration is suppressed. However, if the embryos are formed over a wide range of radial distances, the super-Earths would end up having a distinctive, bimodal composition in water mass. Altogether, our model succeeds in quantitatively reproducing several important observed properties of exoplanets and correlations with their stellar hosts.
Seeking edge-on galaxies with substantial extraplanar dust using a radiative transfer model: determination of the model parameter uncertainties for EON_10.477_41.954 (FGC 79)

We have revisited the target EON_10. 477_41. 954 in order to determine more accurately the uncertainties in the model parameters that are important for target classification (i.e. galaxies with or without substantial extraplanar dust). We performed a Markov chain Monte Carlo (MCMC) analysis for the 15 parameters of the three-dimensional radiative-transfer galaxy model we used previously for target classification. To investigate the convergence of the MCMC sampling – which is usually neglected in the literature but should not be – we monitored the integrated autocorrelation time (τint), and we achieved effective sample sizes >5650 for all the model parameters. The confidence intervals are unstable at the beginning of the iterations where the values of τint are increasing, but they become stable in later iterations where those values are almost constant. The final confidence intervals are ∼5–100 times larger than the nominal uncertainties used in our previous study (the standard deviation of three best-fitting results). Thus, those nominal uncertainties are not good proxies for the model-parameter uncertainties. Although the position of EON_10. 477_41. 954 in the target-classification plot (the scale height to diameter ratio of dust versus that of light source) decreases by about 20–30 per cent when compared to our previous study, its membership in the ‘high-group’ – i.e. among galaxies with substantial extraplanar dust – nevertheless remains unchanged.
Topological edge and corner states in a two-dimensional photonic Su-Schrieffer-Heeger lattice

Abstract Implementation of topology on photonics has opened new functionalities of photonic systems such as topologically protected boundary modes. We theoretically present polarization-dependent topological properties in a 2D Su-Schrieffer-Heeger lattice by using a metallic nanoparticle array and considering the polarization degree of freedom. We demonstrate that when eigenmodes are polarized parallel to the plane of the 2D lattice, it supports longitudinal edge modes that are isolated from the bulk states and transverse edge modes that are overlapped with the bulk states. Also, the in-plane polarized modes support a second-order topological phase under an open boundary condition by breaking the four-fold rotational symmetry. This work will offer polarization-based multifunctionality in compact photonic systems that have topological features.
The little things matter: relating the abundance of ultrafaint satellites to the hosts’ assembly history

Ultrafaint dwarf galaxies ($M_\star \le 10^{5}\, {\rm M}_\odot$) are relics of an early phase of galaxy formation. They contain some of the oldest and most metal-poor stars in the Universe which likely formed before the epoch of hydrogen reionization. These galaxies are so faint that they can only be detected as satellites of the Milky Way. They are so small that they are not resolved in current cosmological hydrodynamic simulations. Here, we combine very high-resolution cosmological N-body simulations with a semi-analytic model of galaxy formation to study the demographics and spatial distribution of ultrafaint satellites in Milky Way-mass haloes. We show that the abundance of these galaxies is correlated with the assembly history of the host halo: at fixed mass, haloes assembled earlier contain, on average, more ultrafaint satellites today than haloes assembled later. We identify simulated galactic haloes that experience an ancient Gaia-Enceladus-Sausage-like and a recent LMC-like accretion event and find that the former occurs in 33 per cent of the sample and the latter in 9 per cent. Only 3 per cent experience both events and these are especially rich in ultrafaint satellites, most acquired during the ancient accretion event. Our models predict that the radial distribution of satellites is more centrally concentrated in early-forming haloes. Accounting for the depletion of satellites by tidal interactions with the central disc, we find a very good match to the observed radial distribution of satellites in the Milky Way over the entire radial range. This agreement is mainly due to the ability of our model to track ‘orphan’ galaxies after their subhaloes fall below the resolution limit of the simulation.
Adoption of improved sheep and goat husbandry practices in pudukottai district of Tamil Nadu

The study was conducted in Pudukkottai district of Tamil Nadu to evaluate the adoption of recommended sheep and goat husbandry practices by the livestock farmers. The study revealed that nearly 85 per cent of the participant farmers were in the medium and high level of adoption category. The extent of adoption of participant farmers was comparatively more than that of the nonparticipant farmers. The recommended practices namely Selection and purchase of quality animals, provision of shelter, feeding of colostrum to new born kids, feeding of crushed prosopis seeds and tamarind seeds, feeding of tree leaves in summer, deworming, vaccination and marketing of lambs at 8 months of age were the recommended practices adopted by majority of the participant farmers.
Intelligent Reflecting Surface Aided Multigroup Multicast MISO Communication Systems

Intelligent reflecting surface (IRS) has recently been envisioned to offer unprecedented massive multiple-input multiple-output (MIMO)-like gains by deploying large-scale and low-cost passive reflection elements. By adjusting the reflection coefficients, the IRS can change the phase shifts on the impinging electromagnetic waves so that it can smartly reconfigure the signal propagation environment and enhance the power of the desired received signal or suppress the interference signal. In this paper, we consider downlink multigroup multicast communication systems assisted by an IRS. We aim for maximizing the sum rate of all the multicasting groups by the joint optimization of the precoding matrix at the base station (BS) and the reflection coefficients at the IRS under both the power and unit-modulus constraint. To tackle this non-convex problem, we propose two efficient algorithms under the majorization–minimization (MM) algorithm framework. Specifically, a concave lower bound surrogate objective function of each user's rate has been derived firstly, based on which two sets of variables can be updated alternately by solving two corresponding second-order cone programming (SOCP) problems. Then, in order to reduce the computational complexity, we derive another concave lower bound function of each group's rate for each set of variables at every iteration, and obtain the closed-form solutions under these loose surrogate objective functions. Finally, the simulation results demonstrate the benefits in terms of the spectral and energy efficiency of the introduced IRS and the effectiveness in terms of the convergence and complexity of our proposed algorithms.