Miracle-dz/UniFAR-FTUs huggingface dataset:
BERT-ATTACK: Adversarial Attack against BERT Using BERT

Adversarial attacks for discrete data (such as text) has been proved significantly more challenging than continuous data (such as image), since it is difficult to generate adversarial samples with gradient-based methods. Currently, the successful attack methods for text usually adopt heuristic replacement strategies on character or word level, which remains challenging to find the optimal solution in the massive space of possible combination of replacements, while preserving semantic consistency and language fluency. In this paper, we propose \textbf{BERT-Attack}, a high-quality and effective method to generate adversarial samples using pre-trained masked language models exemplified by BERT. We turn BERT against its fine-tuned models and other deep neural models for downstream tasks. Our method successfully misleads the target models to predict incorrectly, outperforming state-of-the-art attack strategies in both success rate and perturb percentage, while the generated adversarial samples are fluent and semantically preserved. Also, the cost of calculation is low, thus possible for large-scale generations.
Slowly rotating black holes in Einsteinian cubic gravity

We construct slowly rotating black-hole solutions of Einsteinian cubic gravity (ECG) in four dimensions with flat and AdS asymptotes. At leading order in the rotation parameter, the only modification with respect to the static case is the appearance of a non-vanishing $g_{t\phi}$ component. Similarly to the static case, the order of the equation determining such component can be reduced twice, giving rise to a second-order differential equation which can be easily solved numerically as a function of the ECG coupling. We study how various physical properties of the solutions are modified with respect to the Einstein gravity case, including its angular velocity, photon sphere, photon rings, shadow, and innermost stable circular orbits (in the case of timelike geodesics).
Solar slow magneto-acoustic-gravity waves: an erratum correction and a revisited scenario

Slow waves are commonly observed on the entire solar atmosphere. Assuming a thin flux tube approximation, the cut-off periods of slow-mode magneto-acoustic-gravity waves that travel from the photosphere to the corona were obtained in Costa et al. (2018). In that paper, however, a typo in the specific heat coefficient at constant pressure $c_{\mathrm{p}}$ value led to an inconsistency in the cut-off calculation, which is only significant at the transition region. Due to the abrupt temperature change in the region, a change of the mean atomic weight (by a factor of approximately two) also occurs, but is often overlooked in analytical models for simplicity purposes. In this paper, we revisit the calculation of the cut-off periods of magneto-acoustic-gravity waves in Costa et al. (2018) by considering an atmosphere in hydrostatic equilibrium with a temperature profile, with the inclusion of the variation of the mean atomic weight and the correction of the inconsistency aforementioned. In addition, we show that the cut-off periods obtained analytically are consistent with the corresponding periods measured in observations of a particular active region.
Existence and regularity theorems of one-dimensional Brakke flows

Given a closed countably $1$-rectifiable set in $\mathbb R^2$ with locally finite $1$-dimensional Hausdorff measure, we prove that there exists a Brakke flow starting from the given set with the following regularity property. For almost all time, the flow locally consists of a finite number of embedded curves of class $W^{2,2}$ whose endpoints meet at junctions with angles of either 0, 60 or 120 degrees.
Multiagent Persistent Monitoring of Targets With Uncertain States

We address the problem of persistent monitoring, where a finite set of mobile agents has to persistently visit a finite set of targets. Each of these targets has an internal state that evolves with linear stochastic dynamics. The agents can observe these states, and the observation quality is a function of the distance between the agent and a given target. The goal is then to minimize the mean squared estimation error of these target states. We approach the problem from an infinite horizon perspective, where we prove that, under some natural assumptions, the covariance matrix of each target converges to a limit cycle. The goal, therefore, becomes to minimize the steady-state uncertainty. Assuming that the trajectory is parameterized, we provide tools for computing the steady-state cost gradient. We show that, in 1-D (one dimensional) environments with bounded control and nonoverlapping targets, when an optimal control exists it can be represented using a finite number of parameters. We also propose an efficient parameterization of the agent trajectories for multidimensional settings using Fourier curves. Simulation results show the efficacy of the proposed technique in 1-D, 2-D, and 3-D scenarios.
The MUSTANG Galactic Plane Survey (MGPS90) Pilot

We report the results of a pilot program for a Green Bank Telescope MUSTANG-2 Galactic Plane survey at 3 mm (90 GHz), MGPS90. The survey achieves a typical 1σ depth of 1–2 mJy beam−1 with a 9″ beam. We describe the survey parameters, quality assessment process, cataloging, and comparison with other data sets. We have identified 709 sources over seven observed fields selecting some of the most prominent millimeter-bright regions between 0 deg < ℓ < 50 deg (total area ≈7.5 deg 2). The majority of these sources have counterparts at other wavelengths. By applying flux selection criteria to these sources, we successfully recovered several known hypercompact H ii (HCH ii) regions but did not confirm any new ones. We identify 126 sources that have mm-wavelength counterparts but do not have cm-wavelength counterparts and are therefore candidate HCH ii regions; of these, 10 are morphologically compact and are strong candidates for new HCH ii regions. Given the limited number of candidates in the extended area in this survey compared to the relatively large numbers seen in protoclusters W51 and W49, it appears that most HCH ii regions exist within dense protoclusters. Comparing the counts of HCH ii to ultracompact H ii (UCH ii) regions, we infer the HCH ii region lifetime is 16%–46% that of the UCH ii region lifetime. We additionally separated the 3 mm emission into dust and free–free emission by comparing with archival 870 and 20 cm data. In the selected pilot fields, most (≳80%) of the 3 mm emission comes from plasma, either through free–free or synchrotron emission.
DIET: Lightweight Language Understanding for Dialogue Systems

Large-scale pre-trained language models have shown impressive results on language understanding benchmarks like GLUE and SuperGLUE, improving considerably over other pre-training methods like distributed representations (GloVe) and purely supervised approaches. We introduce the Dual Intent and Entity Transformer (DIET) architecture, and study the effectiveness of different pre-trained representations on intent and entity prediction, two common dialogue language understanding tasks. DIET advances the state of the art on a complex multi-domain NLU dataset and achieves similarly high performance on other simpler datasets. Surprisingly, we show that there is no clear benefit to using large pre-trained models for this task, and in fact DIET improves upon the current state of the art even in a purely supervised setup without any pre-trained embeddings. Our best performing model outperforms fine-tuning BERT and is about six times faster to train.
The Multiplanet System TOI-421: A Warm Neptune and a Super Puffy Mini-Neptune Transiting a G9 V Star in a Visual Binary

We report the discovery of a warm Neptune and a hot sub-Neptune transiting TOI-421 (BD-14 1137, TIC 94986319), a bright (V = 9.9) G9 dwarf star in a visual binary system observed by the Transiting Exoplanet Survey Satellite (TESS) space mission in Sectors 5 and 6. We performed ground-based follow-up observations—comprised of Las Cumbres Observatory Global Telescope transit photometry, NIRC2 adaptive optics imaging, and FIbre-fed Echellé Spectrograph, CORALIE, High Accuracy Radial velocity Planet Searcher, High Resolution Échelle Spectrometer, and Planet Finder Spectrograph high-precision Doppler measurements—and confirmed the planetary nature of the 16 day transiting candidate announced by the TESS team. We discovered an additional radial velocity signal with a period of five days induced by the presence of a second planet in the system, which we also found to transit its host star. We found that the inner mini-Neptune, TOI-421 b, has an orbital period of Pb = 5.19672 ± 0.00049 days, a mass of Mb = 7.17 ± 0.66 M⊕, and a radius of Rb = R⊕, whereas the outer warm Neptune, TOI-421 c, has a period of Pc = 16.06819 ± 0.00035 days, a mass of Mc = M⊕, a radius of Rc = R⊕, and a density of ρc = g cm−3. With its characteristics, the outer planet (ρc = g cm−3) is placed in the intriguing class of the super-puffy mini-Neptunes. TOI-421 b and TOI-421 c are found to be well-suited for atmospheric characterization. Our atmospheric simulations predict significant Lyα transit absorption, due to strong hydrogen escape in both planets, as well as the presence of detectable CH4 in the atmosphere of TOI-421 c if equilibrium chemistry is assumed.
Multidimensional Iterative Filtering: a new approach for investigating plasma turbulence in numerical simulations

Turbulent space and astrophysical plasmas exhibit a complex dynamics, which involves nonlinear coupling across different temporal and spatial scales. There is growing evidence that impulsive events, such as magnetic reconnection instabilities, lead to a spatially localized enhancement of energy dissipation, thus speeding up the energy transfer at small scales. Capturing such a diverse dynamics is challenging. Here, we employ the Multidimensional Iterative Filtering (MIF) method, a novel technique for the analysis of non-stationary multidimensional signals. Unlike other traditional methods (e.g. based on Fourier or wavelet decomposition), MIF does not require any previous assumption on the functional form of the signal to be identified. Using MIF, we carry out a multiscale analysis of Hall-magnetohydrodynamic (HMHD) and hybrid particle-in-cell (HPIC) numerical simulations of decaying plasma turbulence. The results assess the ability of MIF to spatially identify and separate the different scales (the MHD inertial range, the sub-ion kinetic and the dissipation scales) of the plasma dynamics. Furthermore, MIF decomposition allows localized current structures to be detected and their contribution to the statistical and spectral properties of turbulence to be characterized. Overall, MIF arises as a very promising technique for the study of turbulent plasma environments.
Heavy element evolution in the inner regions of the Milky Way

We present results for the evolution of the abundances of heavy elements (O, Mg, Al, Si, K, Ca, Cr, Mn, Ni and Fe) in the inner Galactic regions ($R_{GC} < 4$kpc). We adopt a detailed chemical evolution model already tested for the Galactic bulge and compare the results with APOGEE data. We start with a set of yields from the literature which are considered the best to reproduce the abundance patterns in the solar vicinity. We find that in general the predicted trends nicely reproduce the data but in some cases either the trend or the absolute values of the predicted abundances need to be corrected, even by large factors, in order to reach the best agreement. We suggest how the current stellar yields should be modified to reproduce the data and we discuss whether such corrections are reasonable in the light of the current knowledge of stellar nucleosynthesis. However, we also critically discuss the observations. Our results suggest that Si, Ca, Cr and Ni are the elements for which the required corrections are the smallest, while for Mg and Al moderate modifications are necessary. On the other hand, O and K need the largest corrections to reproduce the observed patterns, a conclusion already reached for solar vicinity abundance patterns, with the exception of oxygen. For Mn we apply corrections already suggested in previous works. \end{abstract}
Scale Symmetry in the Universe

Scale symmetry is a fundamental symmetry of physics that seems however not to be fully realized in the universe. Here, we focus on the astronomical scales ruled by gravity, where scale symmetry holds and gives rise to a truly scale invariant distribution of matter, namely it gives rise to a fractal geometry. A suitable explanation of the features of the fractal cosmic mass distribution is provided by the nonlinear Poisson–Boltzmann–Emden equation. An alternative interpretation of this equation is connected with theories of quantum gravity. We study the fractal solutions of the equation and connect them with the statistical theory of random multiplicative cascades, which originated in the theory of fluid turbulence. The type of multifractal mass distributions so obtained agrees with results from the analysis of cosmological simulations and of observations of the galaxy distribution.
Train No Evil: Selective Masking for Task-guided Pre-training

Recently, pre-trained language models mostly follow the pre-training-then-fine-tuning paradigm and have achieved great performances on various downstream tasks. However, due to the aimlessness of pre-training and the small in-domain supervised data scale of fine-tuning, the two-stage models typically cannot capture the domain-specific and task-specific language patterns well. In this paper, we propose a selective masking task-guided pre-training method and add it between the general pre-training and fine-tuning. In this stage, we train the masked language modeling task on in-domain unsupervised data, which enables our model to effectively learn the domain-specific language patterns. To efficiently learn the task-specific language patterns, we adopt a selective masking strategy instead of the conventional random masking, which means we only mask the tokens that are important to the downstream task. Specifically, we define the importance of tokens as their impacts on the final classification results and use a neural model to learn the implicit selecting rules. Experimental results on two sentiment analysis tasks show that our method can achieve comparable or even better performance with less than 50\% overall computation cost, which indicates our method is both effective and efficient. The source code will be released in the future.
Binary black holes in young star clusters: the impact of metallicity

Young star clusters are the most common birth-place of massive stars and are dynamically active environments. Here, we study the formation of black holes (BHs) and binary black holes (BBHs) in young star clusters, by means of 6000 N-body simulations coupled with binary population synthesis. We probe three different stellar metallicities (Z=0.02, 0.002 and 0.0002) and two initial density regimes (density at the half-mass radius $\rho_{\rm h}\ge{}3.4\times10^4$ and $\ge{1.5\times10^2}$ M$_\odot$ pc$^{-3}$ in dense and loose star clusters, respectively). Metal-poor clusters tend to form more massive BHs than metal-rich ones. We find $\sim{}6$, $\sim{}2$, and $ 60$ M$_\odot$ at Z=0.0002, 0.002 and 0.02, respectively. In metal-poor clusters, we form intermediate-mass BHs with mass up to $\sim{}320$ M$_\odot$. BBH mergers born via dynamical exchanges (exchanged BBHs) can be more massive than BBH mergers formed from binary evolution: the former (latter) reach total mass up to $\sim{}140$ M$_\odot$ ($\sim{}80$ M$_\odot$). The most massive BBH merger in our simulations has primary mass $\sim{}88$ M$_\odot$, inside the pair-instability mass gap, and a mass ratio of $\sim{}0.5$. Only BBHs born in young star clusters from metal-poor progenitors can match the masses of GW170729, the most massive event in O1 and O2, and those of GW190412, the first unequal-mass merger. We estimate a local BBH merger rate density $\sim{}110$ and $\sim{}55$ Gpc$^{-3}$ yr$^{-1}$, if we assume that all stars form in loose and dense star clusters, respectively.
Photorespiration Enhances Acidification of the Thylakoid Lumen, Reduces the Plastoquinone Pool, and Contributes to the Oxidation of P700 at a Lower Partial Pressure of CO2 in Wheat Leaves

The oxidation of P700 in photosystem I (PSI) is a robust mechanism that suppresses the production of reactive oxygen species. We researched the contribution of photorespiration to the oxidation of P700 in wheat leaves. We analyzed the effects of changes in partial pressures of CO2 and O2 on photosynthetic parameters. The electron flux in photosynthetic linear electron flow (LEF) exhibited a positive linear relationship with an origin of zero against the dissipation rate (vH+) of electrochromic shift (ECS; ΔpH across thylakoid membrane), indicating that cyclic electron flow around PSI did not contribute to H+ usage in photosynthesis/photorespiration. The vH+ showed a positive linear relationship with an origin of zero against the H+ consumption rates in photosynthesis/photorespiration (JgH+). These two linear relationships show that the electron flow in LEF is very efficiently coupled with H+ usage in photosynthesis/photorespiration. Lowering the intercellular partial pressure of CO2 enhanced the oxidation of P700 with the suppression of LEF. Under photorespiratory conditions, the oxidation of P700 and the reduction of the plastoquinone pool were stimulated with a decrease in JgH+, compared to non-photorespiratory conditions. These results indicate that the reduction-induced suppression of electron flow (RISE) suppresses the reduction of oxidized P700 in PSI under photorespiratory conditions. Furthermore, under photorespiratory conditions, ECS was larger and H+ conductance was lower against JgH+ than those under non-photorespiratory conditions. These results indicate that photorespiration enhances RISE and ΔpH formation by lowering H+ conductance, both of which contribute to keeping P700 in a highly oxidized state.
Association between age and clinical characteristics and outcomes of COVID-19

The rapid outbreak of coronavirus disease 2019 (COVID-19) has been a matter of international concern as the disease is spreading fast [1, 2]. Considering that the contagious disease has led to an enormous impact globally, there is an urgent need to identify the risk populations with poor prognosis. Ageing is associated with certain changes in pulmonary physiology, pathology and function, during the period of lung infection. Therefore, age-related differences in responsiveness and tolerance become obvious and lead to worse clinical outcomes in elderly individuals [3]. Previous studies have mentioned that older COVID-19 patients are at an increased risk of death [4–7]. However, the age-related clinical characteristics, disease courses and outcomes other than death in COVID-19 patients remain unclear. Age significantly determined the clinical features and prognosis of COVID-19. The prognosis was worse in patients older than 60 years, calling for clinicians to pay more attention to patients of this age. https://bit.ly/34DTI05
Novel CYP19A1 Mutations Extend the Genotype-Phenotype Correlation and Reveal the Impact on Ovarian Function

Abstract Context The steroidogenic enzyme aromatase (CYP19A1) is required for estrogen biosynthesis from androgen precursors in the ovary and extragonadal tissues. The role of aromatase, and thus estrogens, is best illustrated by genetic variations of the CYP19A1 gene leading to aromatase deficiency or excess. Objective The objective of this work is to characterize novel CYP19A1 variants. Design, setting, and patients Variants causing aromatase deficiency were suspected in four 46,XX children of African and Indian origin by careful clinical phenotyping. Sequencing of the CYP19A1 gene identified novel variants. Minigene experiments, aromatase activity assay, and computational, and histological analysis were used to characterize the variants. Main outcome measure and results CYP19A1 variants were found in all patients: a deletion in intron 9 leading to p.P423_H503del, a delins variant at p.P154, and point variants p.V161D, p.R264C, p.R375C. Except for R264C, all variants showed a loss of function. Protein structure and dynamics studies were in line with functional assays. The 2 female patients with delins variants manifested with ambiguous genitalia at birth. Histologic investigation revealed normal ovarian tissue on one side and a streak gonad on the other. Two female patients presented with abnormal pubertal development and polycystic ovaries. Conclusion In girls, aromatase deficiency usually manifests at birth, but diagnosis may also be made because of abnormal pubertal development or ovarian torsion due to (poly)cystic ovaries. The ovary harboring CYP19A1 variants may present as streak gonad or appears normal at birth, but is then at very high risk to produce cysts with aging and is therefore prone to ovarian torsion.
Molecular Mechanism of Functional Ingredients in Barley to Combat Human Chronic Diseases

Barley plays an important role in health and civilization of human migration from Africa to Asia, later to Eurasia. We demonstrated the systematic mechanism of functional ingredients in barley to combat chronic diseases, based on PubMed, CNKI, and ISI Web of Science databases from 2004 to 2020. Barley and its extracts are rich in 30 ingredients to combat more than 20 chronic diseases, which include the 14 similar and 9 different chronic diseases between grains and grass, due to the major molecular mechanism of six functional ingredients of barley grass (GABA, flavonoids, SOD, K-Ca, vitamins, and tryptophan) and grains (β-glucans, polyphenols, arabinoxylan, phytosterols, tocols, and resistant starch). The antioxidant activity of barley grass and grain has the same and different functional components. These results support findings that barley grain and its grass are the best functional food, promoting ancient Babylonian and Egyptian civilizations, and further show the depending functional ingredients for diet from Pliocene hominids in Africa and Neanderthals in Europe to modern humans in the world. This review paper not only reveals the formation and action mechanism of barley diet overcoming human chronic diseases, but also provides scientific basis for the development of health products and drugs for the prevention and treatment of human chronic diseases.