Miracle-dz/UniFAR-FTUs huggingface dataset:
The seeds of star formation in the filamentary infrared-dark cloud G011.11-0.12

Context. Infrared-dark clouds (IRDCs) are the precursors to massive stars and stellar clusters. G011.11–0.12 is a well-studied filamentary IRDC, though, to date, the absence of far-infrared data with sufficient spatial resolution has limited the understanding of the structure and star-formation activity. Aims. We use Herschel to study the embedded population of young pre- and protostellar cores in this IRDC. Methods. We examine the cloud structure, which appears in absorption at short wavelength and in emission at longer wavelength. We derive the properties of the massive cores from the spectral energy distributions of bright far-infrared point sources detected with the PACS instrument aboard Herschel. Results. We report on the detection and characterization of pre- and protostellar cores in a massive filamentary infrared-dark cloud G011.11–0.12 using PACS. We characterize 18 cores directly associated with the filament, two of which have masses over 50 M� , making them the best candidates to become massive stars in G011.11−0.12. These cores are likely at various stages of protostar formation, showing elevated temperature (� T �∼ 22 K) with respect to the ambient gas reservoir. The core masses (� M �∼ 24 M� )a re small compared to that in the cold filament. The mean core separation is 0.9 pc, well in excess of the Jeans length in the filament. Conclusions. We confirm that star formation in IRDCs is underway and diverse, and IRDCs have the capability of forming massive stars and clusters.
Analysis of government agencies and stakeholders' twitter communications during the first surge of COVID-19 in Brazil.

BACKGROUND Official authorities are in charge of communicating with the public in a consistent and coherent manner. The impact of social media on managing the coronavirus 2019 (COVID-19) pandemic potentially influenced social behavior in Brazil. OBJECTIVE Using Twitter, this study analyzes communications about the COVID-19 pandemic from official agencies of the Brazilian government and key public sector decision-makers. METHOD We captured public Twitter messages about COVID-19 exchanged between authorities at the federal, state, and municipal levels of government. These messages were further classified into guidance and information messages or disinformation messages. Finally, through analysis of tweets and their frequency, we evidenced the level of information generated by the three levels of government. RESULTS Our analyses show an underestimation of the magnitude of the pandemic by Brazilian government authorities. None of the spheres of government anticipated the imminent health crisis, did not issue good recommendations and guidelines, and did not take preventive actions. CONCLUSION The lack of governmental actions and adequate guidance in Brazil has led to an explosive increase in infected people and deaths. Surprisingly, this was not due to technical or structural reasons. It resulted from conflicting communication strategies implemented by the federal, state, and municipal governments in attempts to minimize the effects of COVID-19 on their local health structures.
THE OPTICAL MICROVARIABILITY AND SPECTRAL CHANGES OF THE BL LACERTAE OBJECT S5 0716+714

We monitored the BL Lac object S5 0716+714 in the optical band during 2008 October and December and 2009 February with a best temporal resolution of about 5 minutes in the BVRI bands. Four fast flares were observed with amplitudes ranging from 0.3 to 0.75 mag. The source remained active during the whole monitoring campaign, showing microvariability in all days except for one. The overall variability amplitudes are ΔB ∼ 0. ͫ89, ΔV ∼ 0. ͫ80, ΔR ∼ 0. ͫ73, and ΔI∼ 0. ͫ51. Typical timescales of microvariability range from 2 to 8 hr. The overall V − R color index ranges from 0.37 to 0.59. Strong bluer-when-brighter chromatism was found on internight timescales. However, a different spectral behavior was found on intranight timescales. A possible time lag of ∼11 minutes between B and I bands was found on one night. The shock-in-jet model and geometric effects can be applied to explain the source's intranight behavior.
A Multiscenario Optimization Evolutionary Algorithm Based on Transfer Framework

Multiscenario optimization problems involve multiple scenarios to be optimized simultaneously, where each scenario corresponds to a multiobjective optimization problem with specific operating conditions. The goal is to find a group of public compromised optimal solutions (PCOSs) achieving compromised optimal in every scenario. This type of optimization problems widely exists in real-world applications, but the research on it is few. In this article, a Multiscenario Optimization Evolutionary Algorithm based on a transfer framework is proposed. In one iteration, for each scenario, its knee solutions are recognized as its transfer candidates and are used to construct a constraint hyperplane, which determines whether transfer candidates from other scenarios can be the transferable solutions in this underlying scenario. Then, among all transfer candidates, those accepted by all scenarios are identified as the PCOSs and stored in archive. Afterwards, the archive updating process is applied to guarantee the optimality of solutions in archive and control the size of archive. Finally, each scenario’s accepted transferable solutions are utilized in its offspring generation, thus achieving information transfer between different scenarios. Experimental results on a group of benchmark functions verify the superiority of the proposed design in terms of both optimality and computational efficiency over existing approaches.
Just in Time to Flip Your Classroom.

With advocates like Sal Khan and Bill Gates,1 flipped classrooms are attracting an increasing amount of media and research attention.2 We had heard Khan's TED talk and were aware of the concept of inverted pedagogies in general. Yet it really hit home when we accidentally flipped our classroom. Our objective was to better prepare our students for class. We set out to effectively move some of our course content outside of class and decided to tweak the Just-in-Time Teaching approach (JiTT). 3 To our surprise, this tweak—which we like to call the flip-JiTT—ended up completely flipping our classroom. What follows is narrative of our experience and a procedure that any teacher can use to extend JiTT to a flipped classroom.
Spin Nematic Phase in S=1 Triangular Antiferromagnets(Condensed matter: electronic structure and electrical, magnetic, and optical properties)

Spin nematic order is investigated for an S =1 spin model on a triangular lattice with bilinear–biquadratic interactions. We particularly studied an antiferro nematic order phase with a three-sublattice structure, and magnetic properties are calculated at zero temperature by bosonization. Two types of bosonic excitations are found and we calculated dynamic and static spin correlations. One is a gapless excitation with linear energy dispersion around k ∼ 0 , and this leads to a finite spin susceptibility at T =0 and would have a specific heat C ( T ) ∼ T 2 at low temperatures. These behaviors can explain many of the characteristic features of a recently discovered spin liquid state in the triangular magnet, NiGa 2 S 4 .
Undergraduate Research EFL Students’ Experiences in Building ePortfolios

High-impact practices (HIPs) have been adopted by many universities around the world to enhance student learning. The aim of this qualitative study was to analyzed how building ePortfolios may impact student learning experience via weekly reflections. A total of 47 senior undergraduate English as a foreign language (EFL) students enrolled in research projects shared reflections about their research experiences via the development of ePortfolios. Data analysis was carried out through deductive coding of the transcribed focus groups and weekly reflections. Findings suggest that the participants used their ePortfolios to improve their writing skills and increase their knowledge. Students were able to track their progress and felt more engaged in learning. They also showed appreciation to the feedback provided by their instructors on their reflections. However, the students shared some challenges they faced while developing their ePortfolios. Despite these challenges, there was a positive impact of ePortfolios on students’ learning experiences. Implications and further directions for research are discussed.
SELECTION AND MID-INFRARED SPECTROSCOPY OF ULTRALUMINOUS STAR-FORMING GALAXIES AT z ∼ 2

Starting from a sample of 24 μm sources in the Extended Groth Strip, we use 3.6–8 μm color criteria to select ultraluminous infrared galaxies (ULIRGs) at z ∼ 2. Spectroscopy from 20–38 μm of 14 objects verifies their nature and gives their redshifts. Multi-wavelength data for these objects imply stellar masses >1011 M☉ and star formation rates ⩾410 M☉ yr−1. Four objects of this sample observed at 1.6 μm (rest-frame visible) with Hubble Space Telescope/WFC3 show diverse morphologies, suggesting that multiple formation processes create ULIRGs. Of the 14 objects, 4 show signs of active galactic nuclei, but the luminosity appears to be dominated by star formation in all cases.
Start of injection timing effect on performance and exhaust emissions of a combustion engine powered by a diesel-oleic acid methyl ester biodiesel blend

The use of biodiesel as an alternative fuel can be a solution for reducing emissions from internal combustion engines. The present study aims to optimise the start of injection timing on the performance and emissions of biodiesel-fuelled engines. In this study, six starts of injection timings from −40° up to 0° were numerically investigated. The error of the numerical results did not exceed 10% which ensured the computational method validity. Based on the outcomes of the work, tuning a start of injection timing angle to −30° of the crankshaft angle before the top dead centre results in high performance and low emissions of engines fuelled by biodiesel. Overall, the results showed an increase of 65% in the brake torque (BT), a decrease of 28.57% in fuel consumption and an emission decline of 71% in the particulate matter with a start of injection timing angle of −30°.
Anomalous metastability in a temperature-driven transition

The Langer theory of metastability provides a description of the lifetime and properties of the metastable phase of the Ising model field-driven transition, describing the magnetic-field–driven transition in ferromagnets and the chemical-potential–driven transition of fluids. An immediate further step is to apply it to the study of a transition driven by the temperature, as the one exhibited by the two-dimensional Potts model. For this model, a study based on the analytical continuation of the free energy (Meunier J. L. and Morel A., Eur. Phys. J. B, 13 (2000) 341) predicts the anomalous vanishing of the metastable temperature range in the large-system-size limit, an issue that has been controversial since the eighties. By a GPU algorithm we compare the Monte Carlo dynamics with the theory. For temperatures close to the transition we obtain agreement and characterize the dependence on the system size, which is essentially different with respect to the Ising case. For smaller temperatures, we observe the onset of stationary states with non-Boltzmann statistics, not predicted by the theory.
A Comparative Study of Autoregressive Integrated Moving Average and Artificial Neural Networks Models

In this study, the forecasting capabilities of nonlinear models as Artificial Neural Networks and linear ARIMA models were compared. The comparison was conducted using the daily data of Nigeria’s All Share Index for 11 years. The empirical findings revealed ARIMA (1,1,2) model as the best fit for Nigeria’s All Share Index among other Box Jenkins models. This was supported by the most fit statistic test. Also, ANN model with three units in the hidden layer, two lags and the learning rate equal to 0.1, returned as the best fit for the Nigeria All Share Index forecasting. Furthermore, while comparing the performance of the two models, the RMSE of the ARIMA model equivalent to 0.0136 is higher than the RMSE of the ANN model (0.0048), indicating the efficiency of the ANN model. Thus, we can conclude from the above statistics that the ANN model is more efficient. As a result, the study recommends taking advantage of the high capacity of artificial neural networks as a forecasting technique in other fields, such as medical research, genetics research, industrial research, energy, and military research.
Association Of Inflammation Gene Polymorphism With Increased Risk Of Metabolic Syndrome In Tatar Ethnic Group

Background and objective — Chronic low-grade inflammation plays an important role in pathophysiology of metabolic syndrome (MetS). The aim of our study was to determine the associations of polymorphic variants of inflammation genes with MetS and serum levels of high-sensitivity C-reactive protein (hsCRP) and tumor necrosis factor-α (TNF-α) in Tatar patients (Bashkortostan). Methods — In our case-control cross-sectional study, 271 MetS patients and 327 healthy Tatars were genotyped for the SNPs in CRP, TNFA, LTA, TNFRSF1B genes. Results — TNFRSF1B (rs1061624) was associated with the MetS [odds ratio (OR)=0.49, рADJ=0.0034] and TNF-α level (p=0.033). TNFA (rs1800629) was associated with TNF-α (p=0.015), albuminuria (p=0.013). CRP (rs2794521) was associated with fasting (p=0.0096) and postprandial (p=0.01) insulin, HOMA-IR (homeostasis model assessment of insulin resistance, p=0.0019), hsCRP (p=0.036), waist-hip ratio (WHR, p=0.007), body mass index (BMI, p=0.039). The participants having the C-C haplotype of CRP rs2794521-rs1130864 were more common among MetS patients (OR=1.99, p=0.032). T-T haplotype in CRP was associated with hsCRP (p=0.0043), low-density lipoprotein cholesterol (p=0.025), HOMA-IR (p=0.00029), glycated hemoglobin (p=0.006), postprandial (p=0.0006) and fasting insulin (p=0.00031), WHR (p=0.00012), BMI (p=0.00024). Conclusions — The data confirms that the variants of inflammation genes CRP, TNFA, TNFRSF1B are associated with levels of TNF-α, hsCRP. Novel association of TNFRSF1B (rs1061624) with MetS had been identified.
Crash Severity Analysis With Cost-Sensitive Graph Convolutional Networks

In this article, a cost-sensitive graph convolutional networks (CSGCN) is proposed for crash severity analysis. To extract more complete data information, in addition to the original crash characteristics, CSGCN proposes to take the local neighborhood structure hidden among crashes as the input by defining a $k$-nearest neighbor graph, such that more robust model and significant crash contributing factors can be derived. Furthermore, to address the crash severity class imbalance issue, a cost-sensitive classification layer is developed in CSGCN, aiming to assign unequal cost values to crashes with different crash severity levels. Thereby, an unbiased classification hyperplane can be obtained, especially for estimating the relationship between crash influential factors and the minority but more severe crash severity level. In particular, in order to extract more discriminative crash feature representations, a cost-sensitive graph Laplacian regularisation layer is added to CSGCN. The crash dataset collected from Victorian from 2018 to 2019 is adopted for crash severity analysis. In comparison with 19 crash severity models, the proposed CSGCN can achieve at least 20.91% performance improvement in terms of the designed criterion of overall summary score. Moreover, the pseudo elasticity of the proposed CSGCN shows that the speed zone, accident time, heavy vehicles, road condition, run-off road and collision types are the most significant contributing factors to crash severity, providing implications to traffic engineers and policy makers for crash severity mitigation.
Resolving the mass–anisotropy degeneracy of the spherically symmetric Jeans equation – I. Theoretical foundation

A widely employed method for estimating the mass of stellar systems with apparent spherical symmetry is dynamical modelling using the spherically symmetric Jeans equation. Unfortunately this approach suffers from a degeneracy between the assumed mass density and the second order velocity moments. This degeneracy can lead to significantly different predictions for the mass content of the system under investigation, and thus poses a barrier for accurate estimates of the dark matter content of astrophysical systems. In a series of papers we describe an algorithm that removes this degeneracy and allows for unbiased mass estimates of systems of constant or variable mass-to-light ratio. The present contribution sets the theoretical foundation of the method that reconstructs a unique kinematic profile for some assumed free functional form of the mass density. The essence of our method lies in using flexible B-spline functions for the representation of the radial velocity dispersion in the spherically symmetric Jeans equation. We demonstrate our algorithm through an application to synthetic data for the case of an isotropic King model with fixed mass-to-light ratio, recovering excellent fits of theoretical functions to observables and a unique solution. The mass-anisotropy degeneracy is removed to the extent that, for an assumed functional form of the potential and mass density pair $(\Phi,\rho)$, and a given set of line-of-sight velocity dispersion $\sigma_{los}^2$ observables, we recover a unique profile for $\sigma_{rr}^2$ and $\sigma_{tt}^2$. Our algorithm is simple, easy to apply and provides an efficient means to reconstruct the kinematic profile.
Biases in the inferred mass-to-light ratio of globular clusters: no need for variations in the stellar mass function

From a study of the integrated light properties of 200 globular clusters (GCs) in M31, Strader et al. found that the mass-to-light ratios are lower than what is expected from simple stellar population (SSP) models with a `canonical' stellar initial mass function (IMF), with the discrepancy being larger at high metallicities. We use dynamical multi-mass models, that include a prescription for equipartition, to quantify the bias in the inferred dynamical mass as the result of the assumption that light follows mass. For a universal IMF and a metallicity dependent present day mass function we find that the inferred mass from integrated light properties systematically under estimates the true mass, and that the bias is more important at high metallicities, as was found for the M31 GCs. We show that mass segregation and a flattening of the mass function have opposing effects of similar magnitude on the mass inferred from integrated properties. This makes the mass-to-light ratio as derived from integrated properties an inadequate probe of the low-mass end of the stellar mass function. There is, therefore, no need for variations in the IMF, nor the need to invoke depletion of low-mass stars, to explain the observations. Finally, we find that the retention fraction of stellar-mass black holes (BHs) is an equally important parameter in understanding the mass segregation bias. We speculatively put forward to idea that kinematical data of GCs can in fact be used to constrain the total mass in stellar-mass BHs in GCs.
Thermal constraints on the reionization of hydrogen by Population II stellar sources

Measurements of the intergalactic medium (IGM) temperature provide a potentially powerful constraint on the reionization history due to the thermal imprint left by the photoionization of neutral hydrogen. However, until recently IGM temperature measurements were limited to redshifts 2 ≤z≤ 4.8, restricting the ability of these data to probe the reionization history at z > 6. In this work, we use recent measurements of the IGM temperature in the near-zones of seven quasars at z∼ 5.8–6.4, combined with a semi-numerical model for inhomogeneous reionization, to establish new constraints on the redshift at which hydrogen reionization completed. We calibrate the model to reproduce observational constraints on the electron scattering optical depth and the H i photoionization rate, and compute the resulting spatially inhomogeneous temperature distribution at z∼ 6 for a variety of reionization scenarios. Under standard assumptions for the ionizing spectra of Population II sources, the near-zone temperature measurements constrain the redshift by which hydrogen reionization was complete to be zr > 7.9 (6.5) at 68 (95) per cent confidence. We conclude that future temperature measurements around other high-redshift quasars will significantly increase the power of this technique, enabling these results to be tightened and generalized.
Spinodal nanodecomposition in magnetically doped semiconductors

T. Dietl, 2, 3 K. Sato, ∗ T. Fukushima, A. Bonanni, † M. Jamet, A. Barski, S. Kuroda, M. Tanaka, Pham Nam Hai, and H. Katayama-Yoshida Institute of Physics, Polish Academy of Sciences, PL-02-668 Warszawa, Poland Institute of Theoretical Physics, Faculty of Physics, University of Warsaw, PL-02-093 Warszawa, Poland WPI-Advanced Institute for Materials Research (WPI-AIMR), Tohoku University, Sendai 980-8577, Japan Graduate School of Engineering, Osaka University, Suita, Osaka 565-0871, Japan Graduate School of Engineering Science, Osaka University, Toyonaka, Osaka 560-8531, Japan Institut für Halbleiter-und-Festkörperphysik, Johannes Kepler University, A-4040 Linz, Austria Commissariat à l’Energie Atomique, INAC/SP2M-UJF, F-38054 Grenoble, France Institute of Materials Science, University of Tsukuba, Tsukuba, Ibaraki 305-8573, Japan Department of Electrical Engineering and Information Systems, The University of Tokyo, Tokyo 113-8656, Japan Department of Physical Electronics, Tokyo Institute of Technology, Tokyo 152-8552, Japan
ANALYSIS OF ADOLESCENT REPRODUCTIVE HEALTH KNOWLEDGE ON PREMARITAL SEXUAL ATTITUDE

Background : The lack of knowledge about adolescent reproductive health can affect adolescent attitudes about premarital sex which creates the risk of unhealthy sexual acts that affect reproductive health. This study aims to determine the effect of adolescent reproductive health knowledge on premarital sexual attitudes. Method : This study used an observational analytic survey method with a cross sectional approach. The sample was taken using Proportional Random Sampling with a sample of 60 respondents, namely 21 students of class X, 17 students of class XI and 22 students of class XII, then analyzed using the Spearman Rank Test. Results : The P-value is 0.021 < (α = 0.05), which means that there is a relationship between adolescent reproductive health knowledge and premarital sexual attitudes. Conclution : Adolescents who have good knowledge about reproductive health will have a positive attitude in preventing teenage pregnancy which is included in premarital sexual attitudes