Miracle-dz/UniFAR-FTUs huggingface dataset:
ALMA captures feeding and feedback from the active galactic nucleus in NGC 613

We report ALMA observations of CO(3–2) emission in the Seyfert/nuclear starburst galaxy NGC 613, at a spatial resolution of 17 pc, as part of our NUclei of GAlaxies (NUGA) sample. Our aim is to investigate the morphology and dynamics of the gas inside the central kiloparsec, and to probe nuclear fueling and feedback phenomena. The morphology of CO(3–2) line emission reveals a two-arm trailing nuclear spiral at r ≲ 100 pc and a circumnuclear ring at a radius of ∼350 pc that is coincident with the star-forming ring seen in the optical images. Also, we find evidence for a filamentary structure connecting the ring and the nuclear spiral. The ring reveals two breaks into two winding spiral arms corresponding to the dust lanes in the optical images. The molecular gas in the galaxy disk is in a remarkably regular rotation, however the kinematics in the nuclear region are very skewed. The nuclear spectrum of CO and dense gas tracers HCN(4–3), HCO+(4–3), and CS(7–6) show broad wings up to ±300 km s−1, associated with a molecular outflow emanating from the nucleus (r ∼ 25 pc). We derive a molecular outflow mass Mout = 2 × 106 M⊙ and a mass outflow rate of Ṁout = 27 M⊙ yr−1. The molecular outflow energetics exceed the values predicted by AGN feedback models: the kinetic power of the outflow corresponds to PK, out = 20%LAGN and the momentum rate is Ṁoutv ∼ 400LAGN/c. The outflow is mainly boosted by the AGN through entrainment by the radio jet, but given the weak nuclear activity of NGC 613, we might be witnessing a fossil outflow resulting from a previously strong AGN that has now faded. Furthermore, the nuclear trailing spiral observed in CO emission is inside the inner Lindblad resonance ring of the bar. We compute the gravitational torques exerted in the gas to estimate the efficiency of the angular momentum exchange. The gravity torques are negative from 25 to 100 pc and the gas loses its angular momentum in a rotation period, providing evidence for a highly efficient inflow towards the center. This phenomenon shows that the massive central black hole has significant dynamical influence on the gas, triggering the inflowing of molecular gas to feed the black hole.
Language-integrated provenance by trace analysis

Language-integrated provenance builds on language-integrated query techniques to make provenance information explaining query results readily available to programmers. In previous work we have explored language-integrated approaches to provenance in and . However, implementing a new form of provenance in a language-integrated way is still a major challenge. We propose a self-tracing transformation and trace analysis features that, together with existing techniques for type-directed generic programming, make it possible to define different forms of provenance as user code. We present our design as an extension to a core language for Links called TLinks, give examples showing its capabilities, and outline its metatheory and key correctness properties.
CraftAssist Instruction Parsing: Semantic Parsing for a Minecraft Assistant

We propose a large scale semantic parsing dataset focused on instruction-driven communication with an agent in Minecraft. We describe the data collection process which yields additional 35K human generated instructions with their semantic annotations. We report the performance of three baseline models and find that while a dataset of this size helps us train a usable instruction parser, it still poses interesting generalization challenges which we hope will help develop better and more robust models.
Adaptive Task Allocation for Asynchronous Federated Mobile Edge Learning

This paper proposes a scheme to efficiently execute distributed learning tasks in an asynchronous manner while minimizing the gradient staleness on wireless edge nodes with heterogeneous computing and communication capacities. The designed approach considered in this paper ensures that all devices work for a certain duration that covers the time for data/model distribution, learning iterations, model collection and global aggregation. The resulting problem is an integer non-convex program with quadratic equality constraints as well as linear equality and inequality constraints. Because the problem is NP-hard, we relax the integer constraints in order to solve it efficiently with available solvers. Analytical bounds are derived using the KKT conditions and Lagrangian analysis in conjunction with the suggest-and-improve approach. Results show that our approach reduces the gradient staleness and can offer better accuracy than the synchronous scheme and the asynchronous scheme with equal task allocation.
Fairness-Aware Ranking in Search & Recommendation Systems with Application to LinkedIn Talent Search

We present a framework for quantifying and mitigating algorithmic bias in mechanisms designed for ranking individuals, typically used as part of web-scale search and recommendation systems. We first propose complementary measures to quantify bias with respect to protected attributes such as gender and age. We then present algorithms for computing fairness-aware re-ranking of results. For a given search or recommendation task, our algorithms seek to achieve a desired distribution of top ranked results with respect to one or more protected attributes. We show that such a framework can be tailored to achieve fairness criteria such as equality of opportunity and demographic parity depending on the choice of the desired distribution. We evaluate the proposed algorithms via extensive simulations over different parameter choices, and study the effect of fairness-aware ranking on both bias and utility measures. We finally present the online A/B testing results from applying our framework towards representative ranking in LinkedIn Talent Search, and discuss the lessons learned in practice. Our approach resulted in tremendous improvement in the fairness metrics (nearly three fold increase in the number of search queries with representative results) without affecting the business metrics, which paved the way for deployment to 100% of LinkedIn Recruiter users worldwide. Ours is the first large-scale deployed framework for ensuring fairness in the hiring domain, with the potential positive impact for more than 630M LinkedIn members.
ConfigCrusher: White-Box Performance Analysis for Configurable Systems

In configurable software systems, stakeholders are often interested in knowing how configuration options influence the performance of a system to facilitate, for example, the debugging and optimization processes of these systems. There are several black-box approaches to obtain this information, but they usually require a large number of samples to make accurate predictions, whereas the few existing white-box approaches impose limitations on the systems that they can analyze. This paper proposes ConfigCrusher, a white-box performance analysis that exploits several insights of configurable systems. ConfigCrusher employs a static data-flow analysis to identify how configuration options may influence control-flow decisions and instruments code regions corresponding to these decisions to dynamically analyze the influence of configuration options on the regions' performance. Our evaluation using $10$ real-world configurable systems shows that ConfigCrusher is more efficient at building performance models that are similar to or more accurate than current state-of-the-art black-box and white-box approaches. Overall, this paper showcases the benefits and potential of white-box performance analyses to outperform black-box approaches and provide additional information for analyzing configurable systems.
Modeling and Fabrication of Micro FET Pressure Sensor with Circuits

This paper presents the simulation, fabrication and characterization of a micro FET (field effect transistor) pressure sensor with readout circuits. The pressure sensor includes 16 sensing cells in parallel. Each sensing cell that is circular shape is composed of an MOS (metal oxide semiconductor) and a suspended membrane, which the suspended membrane is the movable gate of the MOS. The CoventorWare is used to simulate the behaviors of the pressure sensor, and the HSPICE is employed to evaluate the characteristics of the circuits. The pressure sensor integrated with circuits is manufactured using the commercial 0.35 μm CMOS (complementary metal oxide semiconductor) process and a post-process. In order to obtain the suspended membranes, the pressure sensor requires a post-CMOS process. The post-process adopts etchants to etch the sacrificial layers in the pressure sensors to release the suspended membranes, and then the etch holes in the pressure sensor are sealed by LPCVD (low pressure chemical vapor deposition) parylene. The pressure sensor produces a change in current when applying a pressure to the sensing cells. The circuits are utilized to convert the current variation of the pressure sensor into the voltage output. Experimental results show that the pressure sensor has a sensitivity of 0.032 mV/kPa in the pressure range of 0-500 kPa.
Team Handball Experts Outperform Recreational Athletes in Hand and Foot Response Inhibition: A Behavioral Study

Inhibition is a central component of human behavior. It enables flexible and adaptive behavior by suppressing prepotent motor responses. In former studies, it has been shown that sport athletes acting in dynamic environments exhibit superior motor inhibitory control based on sensory stimuli. So far, existing studies have corroborated this in manual motor response settings only. Therefore, this study addresses the effector specificity of the inhibition benefit in elite athletes compared to physically active controls. A sport-unspecific stop-signal task has been adapted for hand as well as feet usage and 30 elite handball players as well as 30 controls were tested. A repeated-measures ANOVA with the two factors “effector” (hands, feet) and “group” (expert, recreational athletes) was conducted. Our results suggest no group differences in two-choice response times, but a convincing superiority of handball players in inhibitory control (i.e., shorter stop-signal reaction times), predominantly when responding with their hands, with weaker differential effects when responding with their feet. This suggests that motor inhibition might be a comprehensive performance characteristic of sport athletes acting in dynamic environments, detectable predominantly in eye-hand coordination tasks.
Modelling the tightest relation between galaxy properties and dark matter halo properties from hydrodynamical simulations of galaxy formation

We investigate how a property of a galaxy correlates most tightly with a property of its host dark matter halo, using state-of-the-art hydrodynamical simulations of galaxy formation: EAGLE, Illustris, and IllustrisTNG. Unlike most of the previous work, our analyses focus on all types of galaxies, including both central and satellite galaxies. We find that the stellar mass of a galaxy at the epoch of the peak circular velocity with an evolution correction gives the tightest such correlation to the peak circular velocity Vpeak of the galaxy’s underling dark matter halo. The evolution of galaxy stellar mass reduces rather than increases scatter in such a relation. We also find that one major source of scatter comes from star stripping due to the strong interactions between galaxies. Even though, we show that the size of scatter predicted by hydrodynamical simulations has a negligible impact on the clustering of dense Vpeak-selected subhalo from simulations, which suggests that even the simplest subhalo abundance matching (SHAM), without scatter and any additional free parameter, can provide a robust prediction of galaxy clustering that can agree impressively well with the observations from the Sloan Digital Sky Survey (SDSS) main galaxy survey.
Is Socioeconomic Status Associated With Biological Aging as Measured by Telomere Length?

It has been hypothesized that one way in which lower socioeconomic status (SES) affects health is by increasing the rate of biological aging. A widely used marker of biological aging is telomere length. Telomeres are structures at the ends of chromosomes that erode with increasing cell proliferation and genetic damage. We aimed to identify, through systematic review and meta-analysis, whether lower SES (greater deprivation) is associated with shorter telomeres. Thirty-one articles, including 29 study populations, were identified. We conducted 3 meta-analyses to compare the telomere lengths of persons of high and low SES with regard to contemporaneous SES (12 study populations from 10 individual articles), education (15 study populations from 14 articles), and childhood SES (2 study populations from 2 articles). For education, there was a significant difference in telomere length between persons of high and low SES in a random-effects model (standardized mean difference (SMD) = 0.060, 95% confidence interval (CI): 0.002, 0.118; P = 0.042), although a range of sensitivity analyses weakened this association. There was no evidence for an association between telomere length and contemporaneous SES (SMD = 0.104, 95% CI: −0.027, 0.236; P = 0.119) or childhood SES (SMD = −0.037, 95% CI: −0.143, 0.069; P = 0.491). These results suggest weak evidence for an association between SES (as measured by education) and biological aging (as measured by telomere length), although there was a lack of consistent findings across the SES measures investigated here.
Relation Discovery with Out-of-Relation Knowledge Base as Supervision

Unsupervised relation discovery aims to discover new relations from a given text corpus without annotated data. However, it does not consider existing human annotated knowledge bases even when they are relevant to the relations to be discovered. In this paper, we study the problem of how to use out-of-relation knowledge bases to supervise the discovery of unseen relations, where out-of-relation means that relations to discover from the text corpus and those in knowledge bases are not overlapped. We construct a set of constraints between entity pairs based on the knowledge base embedding and then incorporate constraints into the relation discovery by a variational auto-encoder based algorithm. Experiments show that our new approach can improve the state-of-the-art relation discovery performance by a large margin.
On McQuillan's "tautological inequality" and the Weyl-Ahlfors theory of associated curves

In 1941, L. Ahlfors gave another proof of a 1933 theorem of H. Cartan on approximation to hyperplanes of holomorphic curves in P^n. Ahlfors' proof built on earlier work of H. and J. Weyl (1938), and proved Cartan's theorem by studying the associated curves of the holomorphic curve. This work has subsequently been reworked by H. -H. Wu in 1970, using differential geometry, M. Cowen and P. A. Griffiths in 1976, further emphasizing curvature, and by Y. -T. Siu in 1987 and 1990, emphasizing meromorphic connections. This paper gives another variation of the proof, motivated by successive minima as in the proof of Schmidt's Subspace Theorem, and using McQuillan's "tautological inequality. " In this proof, essentially all of the analysis is encapsulated within a modified McQuillan-like inequality, so that most of the proof primarily uses methods of algebraic geometry, in particular flag varieties. A diophantine conjecture based on McQuillan's inequality is also posed.
Improved Hard Example Mining by Discovering Attribute-based Hard Person Identity

In this paper, we propose Hard Person Identity Mining (HPIM) that attempts to refine the hard example mining to improve the exploration efficacy in person re-identification. It is motivated by following observation: the more attributes some people share, the more difficult to separate their identities. Based on this observation, we develop HPIM via a transferred attribute describer, a deep multi-attribute classifier trained from the source noisy person attribute datasets. We encode each image into the attribute probabilistic description in the target person re-ID dataset. Afterwards in the attribute code space, we consider each person as a distribution to generate his view-specific attribute codes in different practical scenarios. Hence we estimate the person-specific statistical moments from zeroth to higher order, which are further used to calculate the central moment discrepancies between persons. Such discrepancy is a ground to choose hard identity to organize proper mini-batches, without concerning the person representation changing in metric learning. It presents as a complementary tool of hard example mining, which helps to explore the global instead of the local hard example constraint in the mini-batch built by randomly sampled identities. Extensive experiments on two person re-identification benchmarks validated the effectiveness of our proposed algorithm.
Efficient approximate unitary t-designs from partially invertible universal sets and their application to quantum speedup

At its core a $t$-design is a method for sampling from a set of unitaries in a way which mimics sampling randomly from the Haar measure on the unitary group, with applications across quantum information processing and physics. We construct new families of quantum circuits on $n$-qubits giving rise to $\varepsilon$-approximate unitary $t$-designs efficiently in $O(n^3t^{12})$ depth. These quantum circuits are based on a relaxation of technical requirements in previous constructions. In particular, the construction of circuits which give efficient approximate $t$-designs by Brandao, Harrow, and Horodecki (F.G.S.L Brandao, A.W Harrow, and M. Horodecki, Commun. Math. Phys. (2016). ) required choosing gates from ensembles which contained inverses for all elements, and that the entries of the unitaries are algebraic. We reduce these requirements, to sets that contain elements without inverses in the set, and non-algebraic entries, which we dub partially invertible universal sets. We then adapt this circuit construction to the framework of measurement based quantum computation(MBQC) and give new explicit examples of $n$-qubit graph states with fixed assignments of measurements (graph gadgets) giving rise to unitary $t$-designs based on partially invertible universal sets, in a natural way. We further show that these graph gadgets demonstrate a quantum speedup, up to standard complexity theoretic conjectures. We provide numerical and analytical evidence that almost any assignment of fixed measurement angles on an $n$-qubit cluster state give efficient $t$-designs and demonstrate a quantum speedup.
DynComm R Package - Dynamic Community Detection for Evolving Networks

Nowadays, the analysis of dynamics in networks represents a great deal in the Social Network Analysis research area. To support students, teachers, developers, and researchers in this work we introduce a novel R package, namely DynComm. It is designed to be a multi-language package, that can be used for community detection and analysis on dynamic networks. The package introduces interfaces to facilitate further developments and the addition of new and future developed algorithms to deal with community detection in evolving networks. This new package has the goal of abstracting the programmatic interface of the algorithms, whether they are written in R or other languages, and expose them as functions in R.
Numerical methods for a system of coupled Cahn-Hilliard equations

Abstract In this work, we consider a system of coupled Cahn-Hilliard equations describing the phase separation of a copolymer and a homopolymer blend. We propose some numerical methods to approximate the solution of the system which are based on suitable combinations of existing schemes for the single Cahn-Hilliard equation. As a verification for our experimental approach, we present some tests and a detailed description of the numerical solutions’ behaviour obtained by varying the values of the system’s characteristic parameters.
Thread Progress Equalization: Dynamically Adaptive Power-Constrained Performance Optimization of Multi-Threaded Applications

Dynamically adaptive multi-core architectures have been proposed as an effective solution to optimize performance for peak power constrained processors. In processors, the micro-architectural parameters or voltage/frequency of each core can be changed at run-time, thus providing a range of power/performance operating points for each core. In this paper, we propose Thread Progress Equalization (TPEq), a run-time mechanism for power constrained performance maximization of multithreaded applications running on dynamically adaptive multicore processors. Compared to existing approaches, TPEq (i) identifies and addresses two primary sources of inter-thread heterogeneity in multithreaded applications, (ii) determines the optimal core configurations in polynomial time with respect to the number of cores and configurations, and (iii) requires no modifications in the user-level source code. Our experimental evaluations demonstrate that TPEq outperforms state-of-the-art run-time power/performance optimization techniques proposed in literature for dynamically adaptive multicores by up to 23 percent.
Maximum likelihood (ML) estimators for scaled mutation parameters with a strand symmetric mutation model in equilibrium

With the multiallelic parent-independent mutation-drift model, the equilibrium proportions of alleles are known to be Dirichlet distributed. A special case is the biallelic model, in which the proportions are beta distributed. A sample taken from these models is then Dirichlet-multinomially or beta-binomially distributed, respectively. Maximum likelihood (ML) estimators for the mutation parameters of the biallelic parent-independent mutation model are available via an expectation maximization algorithm. Assuming small scaled mutation rates, the distribution of a sample of size $M$ can be expanded in a Taylor series of first order. Then the ML estimators for the two parameters in the biallelic model can be expressed using the site frequency spectrum. In this article, we go beyond parent-independent mutation and analyse a strand-symmetric mutation model with six scaled mutation parameters that deviates from parent independent mutation and, generally, from detailed balance. We derive ML estimators for these six parameters assuming mutation-drift equilibrium and small scaled mutation rates. This is the first time that ML estimators are provided for a mutation model more complex than parent-independent mutation.