Miracle-dz/UniFAR-FTUs huggingface dataset:
GLACE survey: Galaxy activity in ZwCl0024+1652 cluster from strong optical emission lines

Although ZwCl0024+1652 galaxy cluster at z ∼ 0.4 has been thoroughly analysed, it lacks a comprehensive study of star formation and nuclear activity of its members. With GaLAxy Cluster Evolution (GLACE) survey, a total of 174 H α emission-line galaxies (ELGs) were detected, most of them having [N ii]. We reduced and analysed a set of [O iii] and H β tunable filter (TF) observations within GLACE survey. Using H α priors, we identified [O iii] and H β in 35 (∼20 per cent) and 59 (∼34 per cent) sources, respectively, with 21 of them having both emission lines, and 20 having in addition [N ii]. Applying BPT-NII diagnostic diagram, we classified these ELGs into 40 per cent star-forming (SF), 55 per cent composites, and 5 per cent LINERs. Star formation rate (SFR) measured through extinction corrected H α fluxes increases with stellar mass (M*), attaining its peak at $\mathrm{\mathit{ M}}_{*}\sim 10^{9.8}\, \mathrm{M}_\odot$. We observed that the cluster centre to ∼ 1.3 Mpc is devoid of SF galaxies and AGN. Our results suggest that the star formation efficiency declines as the local density increases in the cluster medium. Moreover, the SF and AGN fractions drop sharply towards high-density environments. We observed a strong decline in SF fraction in high M*, confirming that star formation is highly suppressed in high-mass cluster galaxies. Finally, we determined that SFR correlates with M* while specific SFR (sSFR) anticorrelates with M*, both for cluster and field. This work shows the importance and strength of TF observations when studying ELGs in clusters at higher redshifts. We provide with this paper a catalogue of ELGs with H β and/or [O iii] lines in ZwCl0024+1652 cluster.
A Primal-Dual Framework for Decentralized Stochastic Optimization

We consider the decentralized convex optimization problem, where multiple agents must cooperatively minimize a cumulative objective function, with each local function expressible as an empirical average of data-dependent losses. State-of-the-art approaches for decentralized optimization rely on gradient tracking, where consensus is enforced via a doubly stochastic mixing matrix. Construction of such mixing matrices is not straightforward and requires coordination even prior to the start of the optimization algorithm. This paper puts forth a primal-dual framework for decentralized stochastic optimization that obviates the need for such doubly stochastic matrices. Instead, dual variables are maintained to track the disagreement between neighbors. The proposed framework is flexible and is used to develop decentralized variants of SAGA, L-SVRG, SVRG++, and SEGA algorithms. Using a unified proof, we establish that the oracle complexity of these decentralized variants is $O(1/\epsilon)$, matching the complexity bounds obtained for the centralized variants. Additionally, we also present a decentralized primal-dual accelerated SVRG algorithm achieving $O(1/\sqrt{\epsilon})$ oracle complexity, again matching the bound for the centralized accelerated SVRG. Numerical tests on the algorithms establish their superior performance as compared to the variance-reduced gradient tracking algorithms.
Minimax Regret for Stochastic Shortest Path with Adversarial Costs and Known Transition

We study the stochastic shortest path problem with adversarial costs and known transition, and show that the minimax regret is $\widetilde{O}(\sqrt{DT^\star K})$ and $\widetilde{O}(\sqrt{DT^\star SA K})$ for the full-information setting and the bandit feedback setting respectively, where $D$ is the diameter, $T^\star$ is the expected hitting time of the optimal policy, $S$ is the number of states, $A$ is the number of actions, and $K$ is the number of episodes. Our results significantly improve upon the existing work of (Rosenberg and Mansour, 2020) which only considers the full-information setting and achieves suboptimal regret. Our work is also the first to consider bandit feedback with adversarial costs. Our algorithms are built on top of the Online Mirror Descent framework with a variety of new techniques that might be of independent interest, including an improved multi-scale expert algorithm, a reduction from general stochastic shortest path to a special loop-free case, a skewed occupancy measure space, %the usage of log-barrier with an increasing learning rate schedule, and a novel correction term added to the cost estimators. Interestingly, the last two elements reduce the variance of the learner via positive bias and the variance of the optimal policy via negative bias respectively, and having them simultaneously is critical for obtaining the optimal high-probability bound in the bandit feedback setting.
Graph-based open-ended survey on concerns related to COVID-19

The COVID-19 pandemic is an unprecedented public health crisis with broad social and economic consequences. We conducted four surveys between April and August 2020 using the graph-based open-ended survey (GOS) framework, and investigated the most pressing concerns and issues for the general public in Japan. The GOS framework is a hybrid of the two traditional survey frameworks that allows respondents to post their opinions in a free-format style, which can subsequently serve as one of the choice items for other respondents, just as in a multiple-choice survey. As a result, this framework generates an opinion graph that relates opinions and respondents. We can also construct annotated opinion graphs to achieve a higher resolution. By clustering the annotated opinion graphs, we revealed the characteristic evolution of the response patterns as well as the interconnectedness and multi-faceted nature of opinions. Substantively, our notable finding is that “social pressure,” not “infection risk,” was one of the major concerns of our respondents. Social pressure refers to criticism and discrimination that they anticipate receiving from others should they contract COVID-19. It is possible that the collectivist nature of Japanese culture coupled with the government’s policy of relying on personal responsibility to combat COVID-19 explains some of the above findings, as the latter has led to the emergence of vigilantes. The presence of mutual surveillance can contribute to growing skepticism toward others as well as fear of ostracism, which may have negative consequences at both the societal and individual levels.
From Bag of Sentences to Document: Distantly Supervised Relation Extraction via Machine Reading Comprehension

Distant supervision (DS) is a promising approach for relation extraction but often suffers from the noisy label problem. Traditional DS methods usually represent an entity pair as a bag of sentences and denoise labels using multi-instance learning techniques. The bag-based paradigm, however, fails to leverage the inter-sentence-level and the entity-level evidence for relation extraction, and their denoising algorithms are often specialized and complicated. In this paper, we propose a new DS paradigm--document-based distant supervision, which models relation extraction as a document-based machine reading comprehension (MRC) task. By re-organizing all sentences about an entity as a document and extracting relations via querying the document with relation-specific questions, the document-based DS paradigm can simultaneously encode and exploit all sentence-level, inter-sentence-level, and entity-level evidence. Furthermore, we design a new loss function--DSLoss (distant supervision loss), which can effectively train MRC models using only $\langle$document, question, answer$\rangle$ tuples, therefore noisy label problem can be inherently resolved. Experiments show that our method achieves new state-of-the-art DS performance.
Graph Coloring with Quantum Annealing

We develop a heuristic graph coloring approximation algorithm that uses the D-Wave 2X as an independent set sampler and evaluate its performance against a fully classical implementation. A randomly generated set of small but hard graph instances serves as our test set. Our performance analysis suggests limited quantum advantage in the hybrid quantum-classical algorithm. The quantum edge holds over multiple metrics and suggests that graph problem applications are a good fit for quantum annealers.
Studies of vibrational relaxation in OCS and CF4 by pulsed photoacoustic techniques

We have used the pulsed photoacoustic technique to measure the effective collisional probabilities for relaxation of the lowest vibrational modes of OCS and CF4 by several collision partners. The measured probabilities at 300 K are OCS by OCS—(3.7±0.7)×10−4; He—(8.0±0.3) ×10−4; Ar—(0.96±0.3)×10−4; H2—(12.0±7.0)×10−4; D2—(12.9±2.5) ×10−4; N2—(2.5±0.5)×10−4; CO—(3.0±0.7)×10−4; CF4 by CF4—(3.4 ±0.2)×10−4; He—(8.6±1.0)×10−4; Ar—(1.6±0.2)×10−4. We also consider in some detail the acoustic waves generated by cylindrically symmetric laser excitation of a weakly absorbing gas in a cylindrical tube and how the signals produced by a microphone in the tube wall reflect the V‐R,T relaxation of the gas.
Cyber Autonomy: Automating the Hacker- Self-healing, self-adaptive, automatic cyber defense systems and their impact to the industry, society and national security

This paper sets the context for the urgency for cyber autonomy, and the current gaps of the cyber security industry. A novel framework proposing four phases of maturity for full cyber autonomy will be discussed. The paper also reviews new and emerging cyber security automation techniques and tools, and discusses their impact on society, the perceived cyber security skills gap/shortage and national security. We will also be discussing the delicate balance between national security, human rights and ethics, and the potential demise of the manual penetration testing industry in the face of automation.
Residential Exposure and Risk Levels to Ambient Formaldehyde and Acetaldehyde According to Distance from Industrial Area in Metropolitan City

The present study evaluated residential exposure to atmospheric formaldehyde and acetaldehyde according to distance from the a dyeing industry complex (DIC). This purpose was achieved by measuring concurrently the outdoor air concentrations in residences near the DIC and a certain distance away, plus the outdoor air concentrations at two industrial areas within the DIC boundary. Formaldehyde concentrations (median values of 24.3 and 22.5 μg/m 3 in IS1 and IS2, respectively) were higher than acetaldehyde concentrations (median values of 7.4 and 7.3 μg/m 3 in IS1 and IS2, respectively) at both sites. However, there was no significant difference in the industrial outdoor air concentrations of both formaldehyde and acetaldehyde between the two sites. In addition, the median formaldehyde concentration from the residential site near the DIC (RS1) was about 1.5 times higher than that from the residential site far away from the DIC(RS2), and the median acetaldehyde concentration from RS1 was about 1.3 times higher than that from RS2. It is noteworthy that the mean or median risk as well as these maximum risks are well above the USEPA's permissible risk level of 10 -6 from environmental exposure. This suggests that appropriate management for formaldehyde and acetaldehyde is necessary in order to decrease risk of the residents of study areas, regardless of the distance from the DIC.
Discourse Parsing of Contentious, Non-Convergent Online Discussions

Online discourse is often perceived as polarized and unproductive. While some conversational discourse parsing frameworks are available, they do not naturally lend themselves to the analysis of contentious and polarizing discussions. Inspired by the Bakhtinian theory of Dialogism, we propose a novel theoretical and computational framework, better suited for non-convergent discussions. We redefine the measure of a successful discussion, and develop a novel discourse annotation schema which reflects a hierarchy of discursive strategies. We consider an array of classification models -- from Logistic Regression to BERT. We also consider various feature types and representations, e.g., LIWC categories, standard embeddings, conversational sequences, and non-conversational discourse markers learnt separately. Given the 31 labels in the tagset, an average F-Score of 0.61 is achieved if we allow a different model for each tag, and 0.526 with a single model. The promising results achieved in annotating discussions according to the proposed schema paves the way for a number of downstream tasks and applications such as early detection of discussion trajectories, active moderation of open discussions, and teacher-assistive bots. Finally, we share the first labeled dataset of contentious non-convergent online discussions.
Self-organization in systems of anisotropic particles

Self-organization in systems of anisotropic particles William Leneal Miller III This dissertation presents studies on self-organization in soft matter systems. A wide variety of systems is studied, with the goal of understanding both the nonequilibrium and the equilibrium properties of this important process. In Chapter 2, we study the self-assembly of asymmetric Janus colloidal particles. We identify and systematically describe the e ect of the ratio of hydrophobic to hydrophilic surface area on the nonequilibrium processes and structure formation. In Chapter 3, we examine systems of hard, aspherical particles. We demonstrate that the thermodynamics of self-organization of a system of these aspherical particle (either a system of identical particles or a polydisperse system of di erent-shaped particles) is well-predicted by a simple relationship between the crystallization pressure and two measures of particle asphericity borrowed from other elds. In Chapter 4, we shift focus to systems of soft particles in two dimensions and on the surface of a sphere. Soft particles are particles with a nite interaction potential at zero distance; such particles exhibit a surprisingly large variety of ordered structures at equilibrium. A similar phenomenon is seen when the study is extended to soft particles on the surface of a sphere. In Chapter 5, we study the free energy of two-component polymer brush systems in which polymers of di erent length are patterned in alternating stripes of speci ed widths on the surface of a cylinder. We present the dependence of the free energy on the polymer lengths and stripe width and a qualitative explanation of its functional form. Finally, in Chapter 6, we approach the reverse self-assembly problem. That is, we describe an algorithm for answering the reverse (and much more di cult) question, Given a speci c desired target self-assembled structure, what interparticle interactions will yield a system which will self-assemble into that structure? We also describe a new model of interparticle interaction which should be able to generate interparticle interaction geometries with a high degree of exibility.
A geometric framework for pitch estimation on acoustic musical signals

This paper presents a geometric approach to pitch estimation (PE) – an important problem in music information retrieval (MIR), and a precursor to a variety of other problems in the field. Though there exist a number of highly accurate methods, both mono-pitch estimation and multi-pitch estimation (particularly with unspecified polyphonic timbre) prove computationally and conceptually challenging. A number of current techniques, while incredibly effective, are not targeted towards eliciting the underlying mathematical structures that underpin the complex musical patterns exhibited by acoustic musical signals. Tackling the approach from both theoretical and experimental perspectives, we present a novel framework, a basis for further work in the area, and results that (while not state of the art) demonstrate relative efficacy. The framework presented in this paper opens up a completely new way to tackle PE problems and may have uses both in traditional analytical approaches as well as in the emerging machine learning (ML) methods that currently dominate the literature.
At the edge of a one-dimensional jellium

We consider a one-dimensional classical Wigner jellium, not necessarily charge neutral, for which the electrons are allowed to exist beyond the support of the background charge. The model can be seen as a one-dimensional Coulomb gas in which the external field is generated by a smeared background on an interval. It is a true one-dimensional Coulomb gas and not a one-dimensional log-gas. We first observe that the system exists if and only if the total background charge is greater than the number of electrons minus one. Moreover we obtain a R\'enyi-type probabilistic representation for the order statistics of the particle system beyond the support of the background. Furthermore, for various backgrounds, we show convergence to point processes, at the edge of the support of the background. In particular, this provides asymptotic analysis of the fluctuations of the right-most particle. Our analysis reveals that these fluctuations are not universal, in the sense that depending on the background, the tails range anywhere from exponential to Gaussian-like behavior, including for instance Tracy-Widom-like behavior.
Workshop Report: Developing Pollution Source Tracking for Recreational and Shellfish Waters

Traditional methods, such as the detection of total and fecal coliforms, and more recently enterococci, that are used to detect fecal pollution levels do not identify the source of the pollution. Despite a significant volume of research in this field, at present there is no common methodology to identify sources of fecal contamination affecting bathing and shellfish waters in Europe.
Self‐Assembly and Fluorescent Modification of Hydroxyapatite Nanoribbon Spherulites

Hydroxyapatite nanoribbon spherulites have been successfully synthesized, with the bioactive eggshell membrane as directing template and in the presence of ethylenediamine, in a one-step reaction under mild conditions. The spherulites are about 2.5 μm in diameter and the extended nanoribbon about 1.1 μm long. The spherulites were modified with fluorescein to obtain a fluorescent probe material with strong luminescence. (© Wiley-VCH Verlag GmbH & Co. KGaA, 69451 Weinheim, Germany, 2005)
Active Learning: Problem Settings and Recent Developments

In supervised learning, acquiring labeled training data for a predictive model can be very costly, but acquiring a large amount of unlabeled data is often quite easy. Active learning is a method of obtaining predictive models with high precision at a limited cost through the adaptive selection of samples for labeling. This paper explains the basic problem settings of active learning and recent research trends. In particular, research on learning acquisition functions to select samples from the data for labeling, theoretical work on active learning algorithms, and stopping criteria for sequential data acquisition are highlighted. Application examples for material development and measurement are introduced.
Towards molecular frame photoelectron angular distributions in polyatomic molecules from lab frame coherent rotational wavepacket evolution

A theory and method for a matrix-based reconstruction of molecular frame (MF) photoelectron angular distributions (MFPADs) from laboratory frame (LF) measurements (LFPADs) is developed and basic applications are explored. As with prior studies of MF reconstruction, the experimental side of this protocol is based upon time-resolved LF measurements in which a rotational wavepacket is prepared and probed as a function of time via photoionization, followed by a numerical reconstruction routine. In contrast to other methodologies, the protocol presented here does not require determination of the photoionization matrix elements, and consequently takes the relatively simple numerical form of a matrix equation. Significantly, this simplicity allows the successful reconstruction of MFPADs for nonlinear polyatomic molecules with D nh point group symmetry. We numerically demonstrate this scheme for two realistic molecular photoionization cases: N2 and C2H4. This new technique is expected to be generally applicable to a broad range of MF reconstruction problems involving photoionization of polyatomic molecules.
Analysis of a viscoelastic phase separation model

A new model for viscoelastic phase separation is proposed, based on a systematically derived conservative two-fluid model. Dissipative effects are included by phenomenological viscoelastic terms. By construction, the model is consistent with the second law of thermodynamics. We study well-posedness of the model in two space dimensions, i.e., existence of weak solutions, a weak-strong uniqueness principle, and stability with respect to perturbations, which are proven by means of relative energy estimates. Our numerical simulations based on the new viscoelastic phase separation model are in good agreement with physical experiments. Furthermore, a good qualitative agreement with mesoscopic simulations is observed.
A Topological Method for Comparing Document Semantics

Comparing document semantics is one of the toughest tasks in both Natural Language Processing and Information Retrieval. To date, on one hand, the tools for this task are still rare. On the other hand, most relevant methods are devised from the statistic or the vector space model perspectives but nearly none from a topological perspective. In this paper, we hope to make a different sound. A novel algorithm based on topological persistence for comparing semantics similarity between two documents is proposed. Our experiments are conducted on a document dataset with human judges’ results. A collection of state-of-the-art methods are selected for comparison. The experimental results show that our algorithm can produce highly human-consistent results, and also beats most state-of-the-art methods though ties with NLTK.
The ultraluminous X-ray source bubble in NGC 5585

Some ultraluminous X-ray sources (ULXs) are surrounded by collisionally ionized bubbles, larger and more energetic than supernova remnants: they are evidence of the powerful outflows associated with super-Eddington X-ray sources. We illustrate the most recent addition to this class: a huge (350 pc x 220 pc in diameter) bubble around a ULX in NGC 5585. We modelled the X-ray properties of the ULX (a broadened-disc source with L_X ~ 2-4 x 10^{39} erg/s) from Chandra and XMM-Newton, and identified its likely optical counterpart in Hubble Space Telescope images. We used the Large Binocular Telescope to study the optical emission from the ionized bubble. We show that the line emission spectrum is indicative of collisional ionization. We refine the method for inferring the shock velocity from the width of the optical lines. We derive an average shock velocity ~125 km/s, which corresponds to a dynamical age of ~600,000 years for the bubble, and an average mechanical power P_w ~ 10^{40} erg/s; thus, the mechanical power is a few times higher than the current photon luminosity. With Very Large Array observations, we discovered and resolved a powerful radio bubble with the same size as the optical bubble, and a 1.4-GHz luminosity ~10^{35} erg/s, at the upper end of the luminosity range for this type of source. We explain why ULX bubbles tend to become more radio luminous as they expand while radio supernova remnants tend to fade.