Miracle-dz/UniFAR-FTUs huggingface dataset:
The Websky extragalactic CMB simulations

We present a new pipeline for the efficient generation of synthetic observations of the extragalactic microwave sky, tailored to large ground-based CMB experiments such as the Simons Observatory, Advanced ACTPol, SPT-3G, and CMB-S4. Such simulated observations are a key technical challenge in cosmology because of the dynamic range and accuracy required. The first part of the pipeline generates a random cosmological realization in the form of a dark matter halo catalog and matter displacement field, as seen from a given position. The halo catalog and displacement field are modeled with ellipsoidal collapse dynamics and Lagrangian perturbation theory, respectively. In the second part, the cosmological realization is converted into a set of intensity maps over the range 10–103 GHz using models based on existing observations and hydrodynamical simulations. These maps include infrared emission from dusty star forming galaxies (CIB), Comptonization of CMB photons by hot gas in groups and clusters through the thermal Sunyaev-Zel'dovich effect (tSZ), Doppler boosting by Thomson scattering of the CMB by bulk flows through the kinetic Sunyaev-Zel'dovich effect (kSZ), and weak gravitational lensing of primary CMB anisotropies by the large-scale distribution of matter in the universe. After describing the pipeline and its implementation, we present the Websky maps, created from a realization of the cosmic web on our past light cone in the redshift interval 0<z<4.6 over the full-sky and a volume of ∼ 600 (Gpc/h)3 resolved with ∼1012 resolution elements. The Websky maps and halo catalog are publicly available at https://mocks.cita. utoronto.ca/websky.
Simple and Effective Prevention of Mode Collapse in Deep One-Class Classification

Anomaly detection algorithms find extensive use in various fields. This area of research has recently made great advances thanks to deep learning. A recent method, the deep Support Vector Data Description (deep SVDD), which is inspired by the classic kernel-based Support Vector Data Description (SVDD), is capable of simultaneously learning a feature representation of the data and a data-enclosing hypersphere. The method has shown promising results in both unsupervised and semi-supervised settings. However, deep SVDD suffers from hypersphere collapse—also known as mode collapse—, if the architecture of the model does not comply with certain architectural constraints, e.g. the removal of bias terms. These constraints limit the adaptability of the model and in some cases, may affect the model performance due to learning suboptimal features. In this work, we consider two regularizers to prevent hypersphere collapse in deep SVDD. The first regularizer is based on injecting random noise via the standard cross-entropy loss. The second regularizer penalizes the minibatch variance when it becomes too small. Moreover, we introduce an adaptive weighting scheme to control the amount of penalization between the SVDD loss and the respective regularizer. Our proposed regularized variants of deep SVDD show encouraging results and outperform a prominent state-of-the-art method on a setup where the anomalies have no apparent geometrical structure.
Propagating Magnetic Droplet Solitons as Moveable Nanoscale Spin-Wave Sources with Tunable Direction of Emission

Magnetic droplets are strongly nonlinear and localized spin-wave solitons that can be formed in current-driven nanocontacts. Here, we propose a simple way to launch droplets in an inhomogeneous nanoscopic waveguide. We use the drift motion of a droplet and show that in a system with broken translational symmetry, the droplet acquires a linear momentum and propagates. We find that the droplet velocity can be tuned via the strength of the break in symmetry and the size of the nanocontact. In addition, we demonstrate that the launched droplet can propagate up to several micrometers in a realistic system with reasonable damping. Finally, we demonstrate how an annihilating droplet delivers its momentum to a highly nonreciprocal spin-wave burst with a tunable wave vector with nanometer wavelengths. Such a propagating droplet can be used as a moveable spin-wave source in nanoscale magnonic networks. The presented method enables full control of the spin-wave emission direction, which can largely extend the freedom to design integrated magnonic circuits with a single spin-wave source.
Voronoi volume function: a new probe of cosmology and galaxy evolution

We study the Voronoi volume function (VVF) – the distribution of cell volumes (or inverse local number density) in the Voronoi tessellation of any set of cosmological tracers (galaxies/haloes). We show that the shape of the VVF of biased tracers responds sensitively to physical properties such as halo mass, large-scale environment, substructure, and redshift-space effects, making this a hitherto unexplored probe of both primordial cosmology and galaxy evolution. Using convenient summary statistics – the width, median, and a low percentile of the VVF as functions of average tracer number density – we explore these effects for tracer populations in a suite of N-body simulations of a range of dark matter models. Our summary statistics sensitively probe primordial features such as small-scale oscillations in the initial matter power spectrum (as arise in models involving collisional effects in the dark sector), while being largely insensitive to a truncation of initial power (as in warm dark matter models). For vanilla cold dark matter (CDM) cosmologies, the summary statistics display strong evolution and redshift-space effects, and are also sensitive to cosmological parameter values for realistic tracer samples. Comparing the VVF of galaxies in the Galaxies & Mass Assembly (GAMA) survey with that of abundance-matched CDM (sub)haloes tentatively reveals environmental effects in GAMA beyond halo mass (modulo unmodelled satellite properties). Our exploratory analysis thus paves the way for using the VVF as a new probe of galaxy evolution physics as well as the nature of dark matter and dark energy.
Into the Ly α jungle: exploring the circumgalactic medium of galaxies at z ∼ 4−5 with MUSE

We present a study of the galaxy environment of nine strong H i + C iv absorption line systems (16.2 < log(N(HI)) < 21.2) spanning a wide range in metallicity at z ∼ 4−5, using MUSE integral field and X-Shooter spectroscopic data collected in a z ≈ 5.26 quasar field. We identify galaxies within a 250 kpc and ±1000 km s−1 window for six out of the nine absorption systems, with two of the absorption line systems showing multiple associated galaxies within the MUSE field of view. The space density of Ly α emitting galaxies (LAEs) around the H i and C iv systems is ≈10−20 times the average sky density of LAEs given the flux limit of our survey, showing a clear correlation between the absorption and galaxy populations. Further, we find that the strongest C iv systems in our sample are those that are most closely aligned with galaxies in velocity space, i.e. within velocities of ±500 km s−1. The two most metal-poor systems lie in the most dense galaxy environments, implying we are potentially tracing gas that is infalling for the first time into star-forming groups at high redshift. Finally, we detect an extended Ly α nebula around the z ≈ 5.26 quasar, which extends up to ≈50 kpc at the surface brightness limit of 3.8 × 10−18 erg s−1 cm−2 arcsec−2. After scaling for surface brightness dimming, we find that this nebula is centrally brighter, having a steeper radial profile than the average for nebulae studied at z ∼ 3 and is consistent with the mild redshift evolution seen from z ≈ 2.
A Formal Development Cycle for Security Engineering in Isabelle

In this paper, we show a security engineering process based on a formal notion of refinement fully formalized in the proof assistant Isabelle. This Refinement-Risk Cycle focuses on attack analysis and security refinement supported by interactive theorem proving. Since we use a fully formalized model of infrastructures with actors and policies we can support a novel way of formal security refinement for system specifications. This formal process is built practically as an extension to the Isabelle Infrastructure framework with attack trees. We define a formal notion of refinement on infrastructure models. Thanks to the formal foundation of Kripke structures and branching time temporal logic in the Isabelle Infrastructure framework, these stepwise transformations can be interleaved with attack tree analysis thus providing a fully formal security engineering framework. The process is illustrated on an IoT healthcare case study introducing GDPR requirements and blockchain.
Sporadic and intense accretion in a 1 Myr-old brown dwarf candidate

Context. Studying the accretion process in very low-mass objects has important implications for understanding their formation mechanism. Many nearby late-M dwarfs that have previously been identified in the field are in fact young brown dwarf members of nearby young associations. Some of them are still accreting. They are therefore excellent targets for further studies of the accretion process in the very low-mass regime at different stages. Aims. We aim to search for accreting young brown dwarf candidates in a sample of 85 nearby late-M dwarfs. Methods. Using photometric data from DENIS, 2MASS, and WISE, we constructed the spectral energy distribution of the late- M dwarfs based on BT-Settl models to detect infrared excesses. We then searched for lithium and Hα emission in candidates that exhibit infrared excesses to confirm their youth and the presence of accretion. Results. Among the 85 late-M dwarfs, only DENIS-P J1538317−103850 (M5.5) shows strong infrared excesses in WISE bands. The detection of lithium absorption in the M5.5 dwarf and its Gaia trigonometric parallax indicate an age of ~1 Myr and a mass of 47 MJ. The Hα emission line in the brown dwarf shows significant variability that indicates sporadic accretion. This 1 Myr-old brown dwarf also exhibits intense accretion bursts with accretion rates of up to 10−7.9 M⊙ yr−1. Conclusions. Our detection of sporadic accretion in one of the youngest brown dwarfs might imply that sporadic accretion at early stages could play an important role in the formation of brown dwarfs. Very low-mass cores would not be able to accrete enough material to become stars, and thus they end up as brown dwarfs.
Forecasting football matches by predicting match statistics

This paper considers the use of observed and predicted match statistics as inputs to forecasts for the outcomes of football matches. It is shown that, were it possible to know the match statistics in advance, highly informative forecasts of the match outcome could be made. Whilst, in practice, match statistics are clearly never available prior to the match, this leads to a simple philosophy. If match statistics can be predicted pre-match, and if those predictions are accurate enough, it follows that informative match forecasts can be made. Two approaches to the prediction of match statistics are demonstrated: Generalised Attacking Performance (GAP) ratings and a set of ratings based on the Bivariate Poisson model which are named Bivariate Attacking (BA) ratings. It is shown that both approaches provide a suitable methodology for predicting match statistics in advance and that they are informative enough to provide information beyond that reflected in the odds. A long term and robust gambling profit is demonstrated when the forecasts are combined with two betting strategies.
All that Glitters is not Bitcoin – Unveiling the Centralized Nature of the BTC (IP) Network

Blockchains are typically managed by peer-to-peer (P2P) networks providing the support and substrate to the so-called distributed ledger (DLT), a replicated, shared, and syn-chronized data structure, geographically spread across multiple nodes. The Bitcoin (BTC) blockchain is by far the most well-known DLT, used to record transactions among peers, based on the BTC digital currency. In this paper we focus on the network side of the BTC P2P network, analyzing its nodes from a purely network measurements-based approach. We present a BTC crawler able to discover and track the BTC P2P network through active measurements, and use it to analyze its main properties. Through the combined analysis of multiple snapshots of the BTC network as well as by using other publicly available data sources on the BTC network and DLT, we unveil the BTC P2P network, locate its active nodes, study their performance, and track the evolution of the network over the past two years. Among other relevant findings, we show that (i) the size of the BTC network has remained almost constant during the last 12 months – since the major BTC price drop in early 2018, (ii) most of the BTC P2P network resides in US and EU countries, and (iii) despite this western network locality, most of the mining activity and corresponding revenue is controlled by major mining pools located in China. By additionally analyzing the distribution of BTC coins among independent BTC entities (i.e., single BTC addresses or groups of BTC addresses controlled by the same actor), we also conclude that (iv) BTC is very far from being the decentralized and uncontrolled system it is so much advertised to be, with only 4.5% of all the BTC entities holding about 85% of all circulating BTC coins.
Selection of highly-accreting quasars

Context. The quasar class of extreme Population A (xA) (also known as super-Eddington accreting massive black holes, SEAMBHs) has been hailed as potential distance indicators for cosmology. Aims. The aim of this paper is to define tight criteria for their proper identification, starting from the main selection criterion RFeII > 1, and to identify potential intruders that do not meet the selection criteria, which nonetheless have been selected as xA because of the coarseness of automatic searches. The inclusion of the spurious xA sources may dramatically increase the dispersion in the Hubble diagram of quasars, which were obtained from virial luminosity estimates. Methods. We studied a sample of 32 low-z quasars that were originally selected from the seventh data release of the Sloan Digital Sky Survey as xA or SEAMBHs, which have been proved to be almost certainly misclassified sources. All of them show moderate to strong Fe II emission and the large majority show strong absorption features in their spectra which are typical of fairly evolved stellar populations. We performed a simultaneous fit of a host galaxy spectrum, active galactic nucleus (AGN) continuum, FeII template, and emission lines to spectra, using the fitting technique based on ULySS, the full spectrum fitting package. We derived the main accretion parameters (i.e., luminosity, black hole mass, and Eddington ratio) and investigate the relation between host galaxy properties and AGN. Results. For sources in our sample with spectral types that correspond to a relatively low Eddington ratio, we find an overall consistency between HβNC, [O III]λλ4959,5007 line shifts, and the mean stellar velocity obtained from the host galaxy fit (within ≲|60| km s−1). Only one source in our sample qualifies as a xA source. Conclusions. The correct classification of spectra that were contaminated by heavy absorption requires careful determination of the host galaxy spectrum. Contamination and misclassification are not usual in the identification of the xAs, nor at low z or at high z. We find a high fraction of host galaxy spectrum; in half of the sample this is even higher than 40%. When absorption lines are prominent, and the fraction of the host galaxy is high, host galaxy spectrum mimics FeII, which may result in a mistaken identification of FeII spectral features. We have identified several stellar absorption lines that, along with the continuum shape, may lead to an overestimate of RFeII, and therefore to the misclassification of sources as xA sources.
Smoothing and growth bound of periodic generalized Korteweg–De Vries equation

For generalized Korteweg–De Vries (KdV) models with polynomial nonlinearity, we establish a local smoothing property in [Formula: see text] for [Formula: see text]. Such smoothing effect persists globally, provided that the [Formula: see text] norm does not blow up in finite time. More specifically, we show that a translate of the nonlinear part of the solution gains [Formula: see text] derivatives for [Formula: see text]. Following a new simple method, which is of independent interest, we establish that, for [Formula: see text], [Formula: see text] norm of a solution grows at most by [Formula: see text] if [Formula: see text] norm is a priori controlled.
Variable stars in the Sh 2-170 H ii region

We present multi-epoch deep (∼20 mag) Ic-band photometric monitoring of the Sh 2-170 star-forming region to understand the variability properties of pre-main-sequence (PMS) stars. We report identification of 47 periodic and 24 non-periodic variable stars with periods and amplitudes ranging from ∼4 h to 18 d and from ∼0.1 to 2.0 mag, respectively. We have further classified 49 variables as PMS stars (17 Class ii and 32 Class iii) and 17 as main-sequence (MS)/field star variables. A larger fraction of MS/field variables (88 per cent) show periodic variability as compared to the PMS variables (59 per cent). The ages and masses of the PMS variable stars are found to be comparable with those of T-Tauri stars. Their variability amplitudes show an increasing trend with the near-IR/mid-IR excess. The period distribution of the PMS variables shows two peaks, one near ∼1.5 d and the other near ∼4.5 d. It is found that the younger stars with thicker discs and envelopes seem to rotate slower than their older counterparts. These properties of the PMS variables support the disc-locking mechanism. Both the period and amplitude of PMS stars show decrease with increasing mass probably due to the effective dispersal of circumstellar discs in massive stars. Our results favour the notion that cool spots on weak line T-Tauri stars are responsible for most of their variations, while hot spots on classical T-Tauri stars resulting from variable mass accretion from an inner disc contribute to their larger amplitudes and irregular behaviours.
Arcsine laws for random walks generated from random permutations with applications to genomics

Abstract A classical result for the simple symmetric random walk with 2n steps is that the number of steps above the origin, the time of the last visit to the origin, and the time of the maximum height all have exactly the same distribution and converge when scaled to the arcsine law. Motivated by applications in genomics, we study the distributions of these statistics for the non-Markovian random walk generated from the ascents and descents of a uniform random permutation and a Mallows(q) permutation and show that they have the same asymptotic distributions as for the simple random walk. We also give an unexpected conjecture, along with numerical evidence and a partial proof in special cases, for the result that the number of steps above the origin by step 2n for the uniform permutation generated walk has exactly the same discrete arcsine distribution as for the simple random walk, even though the other statistics for these walks have very different laws. We also give explicit error bounds to the limit theorems using Stein’s method for the arcsine distribution, as well as functional central limit theorems and a strong embedding of the Mallows(q) permutation which is of independent interest.
Choosing the Right Return Distribution and the Excess Volatility Puzzle

Proponents of behavioral finance have identified several "puzzles" in the market that are inconsistent with rational finance theory. One such puzzle is the "excess volatility puzzle". Changes in equity prices are too large given changes in the fundamentals that are expected to change equity prices. In this paper, we offer a resolution to the excess volatility puzzle within the context of rational finance. We empirically show that market inefficiency attributable to the volatility of excess return across time is caused by fitting an improper distribution to the historical returns. Our results indicate that the variation of gross excess returns is attributable to poorly fitting the tail of the return distribution and that the puzzle disappears by employing a more appropriate distribution for the return data. The new distribution that we introduce in this paper that better fits the historical return distribution of stocks explains the excess volatility in the market and thereby explains the volatility puzzle. Failing to estimate the historical returns using the proper distribution is only one possible explanation for the existence of the volatility puzzle. However, it offers statistical models within the rational finance framework which can be used without relying on behavioral finance assumptions when searching for an explanation for the volatility puzzle.
THE INSTITUTE OF CERTIFIED PROFESSIONAL MANAGERS OF SRI LANKA The Institute of Certified Professional Managers of Sri Lanka

Development of women entrepreneurship in the SME sector has a crucial importance in a developing country like Bangladesh where women constitute half of the total population. The majority of them are underprivileged, under nourished, illiterate and poor. Hence, the development of women entrepreneurship has tremendous potentials for transforming the society through socioeconomic empowerment of the women. This potential is remained untapped in Bangladesh because of lower number of women entrepreneurs in business and economic activities. According to the Bangladesh Economic Review 2009, around six percent of the country’s $90 billion economy comes from SMEs, which is also the largest sector in terms of employment generation. But the women entrepreneurs are less than ten percent of the total entrepreneurs of the country. However, in the recent years, women entrepreneurship in small retail businesses of the country has been increasing which is a good sign for the positive growth of the economy. Therefore, for the development of women entrepreneurship in retail business sector of Bangladesh, identification of critical factors is highly important. These factors can be classified into three types such as, regulative, normative, and cognitive factors. This paper aims at identifying the critical factors related to the development of women entrepreneurship in the retail business sector of Bangladesh. For identifying the factors, 218 women entrepreneurs of retail businesses were interviewed with a structured questionnaire. Both descriptive and inferential statistics were used in this study. Structural Equation Modeling (SEM) was used to identify the relationships between the critical factors and the overall development of women entrepreneurship in the retail business of Bangladesh. The results show that for the development of retail business women entrepreneurs, regulative, normative and cognitive factors are important. Regulative factors such as rules and regulations of the Government and its implementation are critical significant factors for the development of retail business women entrepreneurs in Bangladesh. This study suggests that the government and the policy making organizations should come forward to overcome of normative and cognitive barriers of the women entrepreneurship in the retail business of Bangladesh.