Miracle-dz/UniFAR-FTUs huggingface dataset:
The soft state of the black hole transient source MAXI J1820+070: emission from the edge of the plunge region?

The Galactic black hole X-ray binary MAXI J1820+070 had a bright outburst in 2018 when it became the second brightest X-ray source in the sky. It was too bright for X-ray CCD instruments such as XMM–Newton and Chandra, but was well observed by photon-counting instruments such as Neutron star Inner Composition Explorer (NICER) and Nuclear Spectroscopic Telescope Array(NuSTAR). We report here on the discovery of an excess-emission component during the soft state. It is best modelled with a blackbody spectrum in addition to the regular disc emission, modelled as either diskbb or kerrbb. Its temperature varies from about 0.9 to 1.1 keV, which is about 30–80 per cent higher than the inner disc temperature of diskbb. Its flux varies between 4 and 12 per cent of the disc flux. Simulations of magnetized accretion discs have predicted the possibility of excess emission associated with a non-zero torque at the innermost stable circular orbit (ISCO) about the black hole, which, from other NuSTAR studies, lies at about 5 gravitational radii or about 60 km (for a black hole, mass is $8\, {\rm M}_{\odot }$). In this case, the emitting region at the ISCO has a width varying between 1.3 and 4.6 km and would encompass the start of the plunge region where matter begins to fall freely into the black hole.
Machine Translation System Selection from Bandit Feedback

Adapting machine translation systems in the real world is a difficult problem. In contrast to offline training, users cannot provide the type of fine-grained feedback typically used for improving the system. Moreover, users have different translation needs, and even a single user's needs may change over time. In this work we take a different approach, treating the problem of adapting as one of selection. Instead of adapting a single system, we train many translation systems using different architectures and data partitions. Using bandit learning techniques on simulated user feedback, we learn a policy to choose which system to use for a particular translation task. We show that our approach can (1) quickly adapt to address domain changes in translation tasks, (2) outperform the single best system in mixed-domain translation tasks, and (3) make effective instance-specific decisions when using contextual bandit strategies.
Sample canonical correlation coefficients of high-dimensional random vectors: Local law and Tracy–Widom limit

Consider two random vectors $\mathbf C_1^{1/2}\mathbf x \in \mathbb R^p$ and $\mathbf C_2^{1/2}\mathbf y\in \mathbb R^q$, where the entries of $\mathbf x$ and $\mathbf y$ are i.i. d. random variables with mean zero and variance one, and $\mathbf C_1$ and $\mathbf C_2$ are $p \times p$ and $q\times q$ deterministic population covariance matrices. With $n$ independent samples of $(\mathbf C_1^{1/2}\mathbf x,\mathbf C_2^{1/2}\mathbf y)$, we study the sample correlation between these two vectors using canonical correlation analysis. We denote by $S_{xx}$ and $S_{yy}$ the sample covariance matrices for $\mathbf C_1^{1/2}\mathbf x$ and $\mathbf C_2^{1/2}\mathbf y$, respectively, and $S_{xy}$ the sample cross-covariance matrix. Then the sample canonical correlation coefficients are the square roots of the eigenvalues of the sample canonical correlation matrix $\cal C_{XY}:=S_{xx}^{-1}S_{xy}S_{yy}^{-1}S_{yx}$. Under the high-dimensional setting with ${p}/{n}\to c_1 \in (0, 1)$ and ${q}/{n}\to c_2 \in (0, 1-c_1)$ as $n\to \infty$, we prove that the largest eigenvalue of $\mathcal C_{XY}$ converges to the Tracy-Widom distribution as long as we have $\lim_{s \rightarrow \infty}s^4 [\mathbb{P}(\vert x_{ij} \vert \geq s)+ \mathbb{P}(\vert y_{ij} \vert \geq s)]=0$. This extends the result in [16], which established the Tracy-Widom limit of the largest eigenvalue of $\mathcal C_{XY}$ under the assumption that all moments are finite. Our proof is based on a linearization method, which reduces the problem to the study of a $(p+q+2n)\times (p+q+2n)$ random matrix $H$. In particular, we shall prove an optimal local law on its inverse $G:=H^{-1}$, i.e the resolvent. This local law is the main tool for both the proof of the Tracy-Widom law in this paper, and the study in [22,23] on the canonical correlation coefficients of high-dimensional random vectors with finite rank correlations.
Fighting Fire with Light: A Case for Defending DDoS Attacks Using the Optical Layer

The DDoS attack landscape is growing at an unprecedented pace. Inspired by the recent advances in optical networking, we make a case for optical layer-aware DDoS defense (O-LAD) in this paper. Our approach leverages the optical layer to isolate attack traffic rapidly via dynamic reconfiguration of (backup) wavelengths using ROADMs---bridging the gap between (a) evolution of the DDoS attack landscape and (b) innovations in the optical layer (e.g., reconfigurable optics). We show that the physical separation of traffic profiles allows finer-grained handling of suspicious flows and offers better performance for benign traffic in the face of an attack. We present preliminary results modeling throughput and latency for legitimate flows while scaling the strength of attacks. We also identify a number of open problems for the security, optical, and systems communities: modeling diverse DDoS attacks (e.g., fixed vs. variable rate, detectable vs. undetectable), building a full-fledged defense system with optical advancements (e.g., OpenConfig), and optical layer-aware defenses for a broader class of attacks (e.g., network reconnaissance).
Deep Reinforcement Learning with Linear Quadratic Regulator Regions

Practitioners often rely on compute-intensive domain randomization to ensure reinforcement learning policies trained in simulation can robustly transfer to the real world. Due to unmodeled nonlinearities in the real system, however, even such simulated policies can still fail to perform stably enough to acquire experience in real environments. In this paper we propose a novel method that guarantees a stable region of attraction for the output of a policy trained in simulation, even for highly nonlinear systems. Our core technique is to use "bias-shifted" neural networks for constructing the controller and training the network in the simulator. The modified neural networks not only capture the nonlinearities of the system but also provably preserve linearity in a certain region of the state space and thus can be tuned to resemble a linear quadratic regulator that is known to be stable for the real system. We have tested our new method by transferring simulated policies for a swing-up inverted pendulum to real systems and demonstrated its efficacy.
Systematic Synthesis and Design of Ultralow Threshold 2:1 Parametric Frequency Dividers

A new method is discussed for the systematic synthesis, design, and performance optimization of single-ended varactor-based 2:1 parametric frequency dividers (PFDs) exhibiting an ultralow-power threshold (<inline-formula> <tex-math notation="LaTeX">${P_{\mathrm{ th}}}$ </tex-math></inline-formula>). For the first time, it is analytically shown that the <inline-formula> <tex-math notation="LaTeX">${P_{\mathrm{ th}}}$ </tex-math></inline-formula>-value exhibited by any PFD can be expressed as an explicit closed-form function of the different impedances forming its network. Such a unique and unexplored property permits reliance on linear models, during PFD design and performance optimization. The validity of our analytical model has been verified, in a commercial circuit simulator, through the time- and frequency-domain algorithms. To demonstrate the effectiveness of our new synthesis approach, we also report on a lumped prototype of a 200:100 MHz PFD, realized on a printed circuit board (PCB). Although inductors with quality factors lower than 50 were used, the PFD prototype exhibits a <inline-formula> <tex-math notation="LaTeX">${P_{\mathrm{ th}}}$ </tex-math></inline-formula>-value lower than −15 dBm. Such a <inline-formula> <tex-math notation="LaTeX">${P_{\mathrm{ th}}}$ </tex-math></inline-formula>-value is the lowest one ever reported for passive varactor-based PFDs operating in the same frequency range.
When the disc’s away, the stars will play: dynamical masses in the nova-like variable KR Aur with a pinch of accretion

We obtained time-resolved optical photometry and spectroscopy of the nova-like variable KR Aurigae in the low state. The spectrum reveals a DAB white dwarf (WD) and a mid-M dwarf companion. Using the companion star’s i-band ellipsoidal modulation we refine the binary orbital period to be P = 3.906519 ± 0.000001 h. The light curve and the spectra show flaring activity due to episodic accretion. One of these events produced brightness oscillations at a period of 27.4 min, that we suggest to be related with the rotation period of a possibly magnetic WD at either 27.4 or 54.8 min. Spectral modelling provided a spectral type of M4–5 for the companion star and $T_{1}=27\, 148$ $\pm \, 496$ K, $\log \, g=8.90 \pm 0.07$, and $\log (\mathrm{He/H})= -0.79^{+0.07}_{-0.08}$ for the WD. By simultaneously fitting absorption- and emission-line radial velocity curves and the ellipsoidal light curve, we determined the stellar masses to be $M_1 = 0.94^{+0.15}_{-0.11}\, {\rm{M}_{\rm \odot}}$ and $M_2 = 0.37^{+0.07}_{-0.07}\,{\rm{M}_{\rm \odot}}$ for the WD and the M-dwarf companion, respectively, and an orbital inclination of $47^{+1^{\rm o}}_{-2^{\rm o}}$. Finally, we analyse time-resolved spectroscopy acquired when the system was at an i-band magnitude of 17.1, about 1.3 mag brighter than it was in the low state. In this intermediate state, the line profiles contain an emission S-wave delayed by ≃0.2 orbital cycle relative to the motion of the WD, similar to what is observed in SW Sextantis stars in the high state.
Multi-Branch Learning for Weakly-Labeled Sound Event Detection

There are two sub-tasks implied in the weakly-supervised SED: audio tagging and event boundary detection. Current methods which combine multi-task learning with SED requires annotations both for these two sub-tasks. Since there are only annotations for audio tagging available in weakly-supervised SED, we design multiple branches with different learning purposes instead of pursuing multiple tasks. Similar to multiple tasks, multiple different learning purposes can also prevent the common feature which the multiple branches share from overfitting to any one of the learning purposes. We design these multiple different learning purposes based on combinations of different MIL strategies and different pooling methods. Experiments on the DCASE 2018 Task 4 dataset and the URBAN-SED dataset both show that our method achieves competitive performance.
Multilingual Twitter Corpus and Baselines for Evaluating Demographic Bias in Hate Speech Recognition

Existing research on fairness evaluation of document classification models mainly uses synthetic monolingual data without ground truth for author demographic attributes. In this work, we assemble and publish a multilingual Twitter corpus for the task of hate speech detection with inferred four author demographic factors: age, country, gender and race/ethnicity. The corpus covers five languages: English, Italian, Polish, Portuguese and Spanish. We evaluate the inferred demographic labels with a crowdsourcing platform, Figure Eight. To examine factors that can cause biases, we take an empirical analysis of demographic predictability on the English corpus. We measure the performance of four popular document classifiers and evaluate the fairness and bias of the baseline classifiers on the author-level demographic attributes.
Monocular Direct Sparse Localization in a Prior 3D Surfel Map

In this paper, we introduce an approach to tracking the pose of a monocular camera in a prior surfel map. By rendering vertex and normal maps from the prior surfel map, the global planar information for the sparse tracked points in the image frame is obtained. The tracked points with and without the global planar information involve both global and local constraints of frames to the system. Our approach formulates all constraints in the form of direct photometric errors within a local window of the frames. The final optimization utilizes these constraints to provide the accurate estimation of global 6-DoF camera poses with the absolute scale. The extensive simulation and real-world experiments demonstrate that our monocular method can provide accurate camera localization results under various conditions.
Understanding the large inferred Einstein radii of observed low-mass galaxy clusters

We assess a claim that observed galaxy clusters with mass ${\sim}10^{14} \mathrm{\, M_\odot }$ are more centrally concentrated than predicted in lambda cold dark matter (ΛCDM). We generate mock strong gravitational lensing observations, taking the lenses from a cosmological hydrodynamical simulation, and analyse them in the same way as the real Universe. The observed and simulated lensing arcs are consistent with one another, with three main effects responsible for the previously claimed inconsistency. First, galaxy clusters containing baryonic matter have higher central densities than their counterparts simulated with only dark matter. Secondly, a sample of clusters selected because of the presence of pronounced gravitational lensing arcs preferentially finds centrally concentrated clusters with large Einstein radii. Thirdly, lensed arcs are usually straighter than critical curves, and the chosen image analysis method (fitting circles through the arcs) overestimates the Einstein radii. After accounting for these three effects, ΛCDM predicts that galaxy clusters should produce giant lensing arcs that match those in the observed Universe.
Bryan's Maximum Entropy Method - Diagnosis of a Flawed Argument and Its Remedy

The Maximum Entropy Method (MEM) is a popular data analysis technique based on Bayesian inference, which has found various applications in the research literature. While the MEM itself is well-grounded in statistics, I argue that its state-of-the-art implementation, suggested originally by Bryan, artificially restricts its solution space. This restriction leads to a systematic error often unaccounted for in contemporary MEM studies. The goal of this paper is to carefully revisit Bryan’s train of thought, point out its flaw in applying linear algebra arguments to an inherently nonlinear problem, and suggest possible ways to overcome it.
Observational constraints on dark matter decaying via gravity portals

Global symmetry can guarantee the stability of dark matter particles (DMps). However, the nonminimal coupling between dark matter (DM) and gravity can destroy the global symmetry of DMps, which in turn leads to their decay. Under the framework of nonminimal coupling between scalar singlet dark matter (ssDM) and gravity, it is worth exploring to what extent the symmetry of ssDM is broken. It is suggested that the total amount of decay products of ssDM cannot exceed current observational constraints. Along these lines, the data obtained with satellites such as Fermi-LAT and AMS-02 can limit the strength of the global symmetry breaking of ssDM. Since the mass of many well--motivated DM candidates may be in the GeV--TeV range, we determine a reasonable parameter range for the lifetime in this range. We find that when the mass of the ssDM is around the electroweak scale (246 GeV), the corresponding 3--$\sigma$ lower limits of the lifetime of ssDM is $5.3\times10^{26}$ s. Our analysis of ssDM around the typical electroweak scale contains the most abundant decay channels of all mass range, so the analysis of the behaviour of ssDM under the influence of gravity is more comprehensive.
On the Multiplicative Decomposition of Heterogeneity in Continuous Assemblages

A system's heterogeneity (equivalently, \textit{diversity}) amounts to the effective size of its event space, and can be quantified using the Renyi family of indices (also known as Hill numbers in ecology or Hannah-Kay indices in economics), which are indexed by an elasticity parameter $q \geq 0$. Importantly, under these indices, the heterogeneity of a composite system (the $\gamma$-heterogeneity) is decomposable into heterogeneity arising from variation \textit{within} and \textit{between} component subsystems (the $\alpha$- and $\beta$-heterogeneities, respectively). Since the average heterogeneity of a component subsystem should not be greater than that of the pooled assemblage, we require that $\alpha \leq \gamma$. There exists a multiplicative decomposition for Renyi heterogeneity of composite systems with discrete event spaces, but less attention has been paid to decomposition in the continuous setting. This paper therefore describes multiplicative decomposition of the Renyi heterogeneity for continuous mixture distributions under parametric and non-parametric pooling assumptions. We show that under non-parametric pooling (where $\gamma$-heterogeneity must typically be estimated numerically), the multiplicative decomposition holds such that $\gamma\geq\alpha$ for all values of the elasticity parameter $q > 0$, and $\beta$-heterogeneity amounts to the discrete number of distinct mixture components in the system. Conversely, under parametric pooling (as in a Gaussian mixed-effects model), which facilitates efficient analytical computation of $\gamma$-heterogeneity, we show that the $\gamma \geq \alpha$ condition holds only at $q=1$. By providing conditions under which the decomposability axiom of heterogeneity measurement holds, our findings further advance the understanding of heterogeneity measurement in non-categorical systems.
New features in the JHU generator framework

We present an extension of the JHUGen and MELA framework, which includes an event generator and library for the matrix element analysis. It enables simulation, optimal discrimination, reweighting techniques, and analysis of a bosonic resonance and the triple and quartic gauge boson interactions with the most general anomalous couplings. The new features, which become especially relevant at the current stage of LHC data taking, are the simulation of gluon fusion and vector boson fusion in the off-shell region, associated $ZH$ production at NLO QCD including the $gg$ initial state, and the simulation of a second spin-zero resonance. We also quote translations of the anomalous coupling measurements into constraints on dimension-six operators of an effective field theory. Some of the new features are illustrated with projections for experimental measurements with the full LHC and HL-LHC datasets.
An efficient algorithm for Elastic I‐optimal design of generalized linear models

The generalized linear models (GLMs) are widely used in statistical analysis and the related design issues are undoubtedly challenging. The state‐of‐the‐art works mostly apply to design criteria on the estimates of regression coefficients. The prediction accuracy is usually critical in modern decision‐making and artificial intelligence applications. It is of importance to study optimal designs from the prediction aspects for GLMs. In this work, we consider Elastic I‐optimality as a prediction‐oriented design criterion for GLMs, and develop an efficient algorithm for such EI‐optimal designs. By investigating theoretical properties for the optimal weights of any set of design points and extending the general equivalence theorem to the EI‐optimality for GLMs, the proposed efficient algorithm adequately combines the Fedorov–Wynn algorithm and the multiplicative algorithm. It achieves great computational efficiency with guaranteed convergence. Numerical examples are conducted to evaluate the feasibility and computational efficiency of the proposed algorithm.
Application of computational chemistry for adsorption studies on metal–organic frameworks used for carbon capture

Abstract Computational chemistry is invaluable in calculating macroscopic and microscopic details of systems application in chemical industries which are involved in carbon capture through precombustion, post-combustion and oxy combustion technologies. This review discusses the role of computational chemistry for adsorption studies of metal–organic frameworks (MOFs) which can be utilized for carbon capture. Principles of quantum mechanics–molecular mechanics are used to devise the electrostatic charges and isotherm parameters on the MOFs. MOFs for carbon capture which can be compatible and which can withstand the severity in chemical industries can be effectively studied using grand canonical Monte Carlo simulation by selecting appropriate force fields. Since flue gases contain a host of other gases in addition to oxides of carbon, capture by MOFs has to be carefully modelled and the software useful for this study are mentioned in this review. The simulated adsorption isotherms should be compared with experimental adsorption isotherms to validate the study. The adsorption model for carbon dioxide adsorption on MOFs is generally reported to be type I reversible isotherm and the kinetics is in good agreement with pseudo-second-order kinetics. Graphical Abstract: Graphical Abstract
The Antiglycation Effect of Monomethyl Branched Chained Fatty Acid and Phytochemical Compounds and their Synergistic Effect on Obesity Related Colorectal Cancer Cell Panel

Abstract Background and aims: monomethyl branched chain fatty acids (mmBCFA) and phytochemicals including: Hydroxycitric Acid, Chlorogenic Acid and Piperine have been considered as an interesting agent for researches due to their role in diabetes and cancer. The present study examines the antiglycation effect of mmBCFA and phytochemicals and investigate their Synergistic effect on different colorectal cancer cell lines. Methods: This study was carried out by using murine monocyte-macrophage cell line and Methylglyoxal (MGO) to enhance the glycation process, furthermore to examine the antiproliferative effect of both the mmBCFA and phytochemicals we use Sulforhodamine B (SRB) assay against obesity related-colorectal cancer cell line panel. Results: Both phytochemicals and mmBCFA have a higher antiglycation effect than Aminoguanidine (AMG) significantly, moreover, all of the phytochemicals and mmBCFA have antiproliferative against SW620, CACO2 and SW480, nevertheless none of these agents was equipotent to Cisplatin, furthermore, the synergetic effect observed only when we co-incubate Piperine with mmBCFA. Conclusions: phytochemicals such as Hydroxycitric Acid, Chlorogenic Acid and Piperine and mmBCFA could be used as treatment to prevents the accumulation of advanced glycation end-products (AGEs) in diabetes. Furthermore, the co-incubation between these compounds can inhibit cancer growth, as alternative therapeutic strategy against obesity related-colorectal cancer.
Understanding the Conductive Carbon Additive on Electrode/Electrolyte Interface Formation in Lithium-Ion Batteries via in situ Scanning Electrochemical Microscopy

The role of conductive carbon additive on the electrode/electrolyte interface formation mechanism was examined in the low-potential (3.0–0 V) and high-potential (3.0–4.7 V) regions. Here the most commonly used conductive carbon Super P was used to prepared electrode with polyvinylidene fluoride binder without any active material. The dynamic process of interface formation was observed with in situ Scanning Electrochemical Microscopy. The electronically insulating electrode/electrolyte passivation layer with areal heterogeneity was formed after cycles in both potential regions. The low-potential interface layer is mainly composed of inorganic compounds covering the conductive carbon surface; While the electrode after high-potential sweep tends to lose its original carbon structure and has more organic species formed on its surface.