Miracle-dz/UniFAR-FTUs huggingface dataset:
An e-cient factorization for the noisy MAX ⁄

D¶‡ez’s algorithm for the noisy MAX is very e‐cient for polytrees, but when the network has loops it has to be combined with local conditioning, a suboptimal propagation algorithm. Other algorithms, based on several factorizations of the conditional probability of the noisy MAX, are not as e‐cient for polytrees, but can be combined with general propagation algorithms, such as clustering or variable elimination, which are more e‐cient for networks with loops. In this paper we propose a new factorization of the noisy MAX that amounts to D¶‡ez’s algorithm in the case of polytrees and at the same time is more e‐cient than previous factorizations when combined with either variable elimination or clustering.
International Migration and Poverty: a Cross Country Analysis

The objective of the paper is to empirically investigate the effect of migration on poverty in origin countries, using data from a cross country analysis. Moreover, the research aims to indirect ascertain whether migrants are selected in terms of welfare levels, through the comparison of the effects of international migration on different income quintiles of the population. The relationship between migration and poverty is as well analysed for different sizes of the network of relatives and friends, in order to cast some light on the importance of the network effect. To proxy the level of international migration, the variable stock of migrants is computed from a new data set, personally constructed, which contains bi-lateral information on the number of migrants produced by 149 origin nations and resident in 23 OECD destinations.
THE EFFECT OF COMPETENCE AND PROFESSIONAL SKEPTICISM ON FRAUD DETECTION SKILLS

This study aims to examine the effect of professional competence and skepticism on fraud detection skills. The survey was conducted on auditors at 25 Inspectorates in South Sulawesi Province. Data were collected from 118 respondents using purposive sampling. The method of analysis using SEM. The results showed that professional competence and skepticism had an effect on fraud detection skills. Competence affects the attitude of professional skepticism. Competence affects fraud detection skills through professional skepticism. Competent auditors are able to apply professional skepticism better to detect fraud. They are more skeptical and sensitive to the symptoms of fraud.
Machine Learning in Predicting Tooth Loss: A Systematic Review and Risk of Bias Assessment

Predicting tooth loss is a persistent clinical challenge in the 21st century. While an emerging field in dentistry, computational solutions that employ machine learning are promising for enhancing clinical outcomes, including the chairside prognostication of tooth loss. We aimed to evaluate the risk of bias in prognostic prediction models of tooth loss that use machine learning. To do this, literature was searched in two electronic databases (MEDLINE via PubMed; Google Scholar) for studies that reported the accuracy or area under the curve (AUC) of prediction models. AUC measures the entire two-dimensional area underneath the entire receiver operating characteristic (ROC) curves. AUC provides an aggregate measure of performance across all possible classification thresholds. Although both development and validation were included in this review, studies that did not assess the accuracy or validation of boosting models (AdaBoosting, Gradient-boosting decision tree, XGBoost, LightGBM, CatBoost) were excluded. Five studies met criteria for inclusion and revealed high accuracy; however, models displayed a high risk of bias. Importantly, patient-level assessments combined with socioeconomic predictors performed better than clinical predictors alone. While there are current limitations, machine-learning-assisted models for tooth loss may enhance prognostication accuracy in combination with clinical and patient metadata in the future.
Contrasting continental patterns of adaptive population divergence in a holarctic fungus

11 Understanding the population processes and genetic mechanisms that 12 give rise to new species remains one of the most elusive goals of mod- 13 ern evolutionary biology. In the hyperdiverse and ecologically important 14 Fungi, the process of speciation is virtually unknown, including for the 15 more than 20,000 species of obligate ectomycorrhizal mutualists that 16 play essential roles in ecosystem function. We investigated patterns of 17 genome-wide diﬀerentiation in the ectomycorrhizal porcini mushroom 18 Boletus edulis , a globally distributed species complex with broad eco- 19 logical amplitude. By whole genome sequencing 160 individuals from 20 across the Northern Hemisphere, we identiﬁed 792,923 SNPs and used 21 these to elucidate the demographic and adaptive processes shaping 22 global population diﬀerentiation. We show that B. edulis exhibits deeply 23 contrasting patterns of genomic divergence between continents, with 24 multiple lineages being present across North America, while a single 25 lineage dominates Europe over a vast geographic scale. These geograph- 26 ical lineages are inferred to have diverged between 2.66 and 1.62 million 27 years ago, corresponding to a period of climatic upheaval and the onset 28 of glaciation during the Pliocene-Pleistocene boundary. High levels of 29 genomic diﬀerentiation were observed among lineages despite evidence of 30 substantial and ongoing introgression. Furthermore, genome scans, demo- 31 graphic inference and ecological niche models all suggest that genomic 32 diﬀerentiation is maintained by environmental adaptation and not phys- 33 ical isolation. Our study uncovers striking diﬀerences on a truly global 34 scale and emphasizes the importance of local adaptation and ecologically 35 mediated divergence, rather than prezygotic barriers such as allopa- 36 try or genomic incompatibility in population diﬀerentiation in Fungi. 37
ICEEMDAN-Based Transfer Entropy between Global Commodity Classes and African Equities

We examine the information transfer dynamics between global commodity and African equity markets to test their efficiency levels in a denoised transfer entropy approach. Our findings in the short- and medium-term scales lend support to the alternative hypothesis of market efficiency, whereas the transfer entropies at the long-term scale lend support to the efficient market hypothesis and the long-term market efficiency. Investing in a single commodity results in high uncertainty when the return pattern (history) of African equities is acknowledged. Similarly, investing in any single African equity results in high return uncertainty whilst accounting for the history of commodity markets’ returns. Short-term traders could monitor the loopholes in the market efficiency levels between global commodities and African equities to take advantage of arbitrage when needed, whilst long-term investors are assured of efficient market dynamics between global commodity markets and African equities. Regulation of markets may need to strategically incorporate news items as they fall due to either market.
CN Zeeman and dust polarization in a high-mass cold clump

We report on the young massive clump (G35.20w) in W48 that previous molecular line and dust observations have revealed to be in the very early stages of star formation. Based on virial analysis, we find that a strong field of 1640 μ G is required to keep the clump in pressure equilibrium. We performed a deep Zeeman effect measurement of the 113 GHz CN (1−0) line towards this clump with the IRAM 30 m telescope. We combine simultaneous fitting of all CN hyperfines with Monte Carlo simulations for a large range in realization of the magnetic field to obtain a constraint on the line-of-sight field strength of −687 ± 420 μ G. We also analyze archival dust polarization observations towards G35.20w. A strong magnetic field is implied by the remarkably ordered field orientation that is perpendicular to the longest axis of the clump. Based on this, we also estimate the plane-of-sky component of the magnetic field to be ~740 μ G. This allows for a unique comparison of the two orthogonal measurements of magnetic field strength of the same region and at similar spatial scales. The expected total field strength shows no significant conflict between the observed field and that required for pressure equilibrium. By producing a probability distribution for a large range in field geometries, we show that plane-of-sky projections are much closer to the true field strengths than line-of-sight projections. This can present a significant challenge for Zeeman measurements of magnetized structures, even with ALMA. We also show that CN molecule does not suffer from depletion on the observed scales in the predominantly cold and highly deuterated core in an early stage of high-mass star formation and is thus a good tracer of the dense gas.
Challenges faced by English majors when writing research papers

: The purpose of the study is to figure out some common challenges English majors encounter when writing their research papers. The participants are 53 English majors at Tra Vinh University. The questionnaire is the only instrument focusing on students’ obstacles: preparing for conducting a research paper, writing the introduction, writing the literature review, identifying the research methodology, analyzing the data, and giving recommendations. The findings reveal that the participants face some difficulties including identifying a research topic, searching materials, recognizing the significance of the paper, selecting appropriate theoretical background, choosing and summarizing related studies, using correct style of citation, deciding the appropriate statistical tool for data analysis, using appropriate formulas for calculating the collected data, interpreting data clearly and concisely, and comparing the findings of the present study to those of related studies. From the findings above, some recommendations are suggested to assist students in overcoming their issues.
$\ell_p$ Slack Norm Support Vector Data Description

The support vector data description (SVDD) approach serves as a de facto standard for one-class classification where the learning task entails inferring the smallest hyper-sphere to enclose target objects while linearly penalising any errors/slacks via an $\ell_1$-norm penalty term. In this study, we generalise this modelling formalism to a general $\ell_p$-norm ($p\geq1$) slack penalty function. By virtue of an $\ell_p$ slack norm, the proposed approach enables formulating a non-linear cost function with respect to slacks. From a dual problem perspective, the proposed method introduces a sparsity-inducing dual norm into the objective function, and thus, possesses a higher capacity to tune into the inherent sparsity of the problem for enhanced descriptive capability. A theoretical analysis based on Rademacher complexities characterises the generalisation performance of the proposed approach in terms of parameter $p$ while the experimental results on several datasets confirm the merits of the proposed method compared to other alternatives.
THE MOUSE THAT ROARED: A SUPERFLARE FROM THE dMe FLARE STAR EV LAC DETECTED BY SWIFT AND KONUS-WIND

We report on a large stellar flare from the nearby dMe flare star EV Lac observed by the Swift and Konus-Wind satellites and the Liverpool Telescope. It is the first large stellar flare from a dMe flare star to result in a Swift trigger based on its hard X-ray intensity. Its peak fX from 0.3 to 100 keV of 5.3 × 10−8 erg cm−2 s−1 is nearly 7000 times larger than the star's quiescent coronal flux, and the change in magnitude in the white filter is ⩾4.7. This flare also caused a transient increase in EV Lac's bolometric luminosity (Lbol) during the early stages of the flare, with a peak estimated LX/Lbol ∼ 3.1. We apply flare loop hydrodynamic modeling to the plasma parameter temporal changes to derive a loop semi-length of l/R⋆ = 0.37 ± 0.07. The soft X-ray spectrum of the flare reveals evidence of iron Kα emission at 6.4 keV. We model the Kα emission as fluorescence from the hot flare source irradiating the photospheric iron, and derive loop heights of h/R⋆ = 0.1, consistent within factors of a few with the heights inferred from hydrodynamic modeling. The Kα emission feature shows variability on timescales of ∼200 s which is difficult to interpret using the pure fluorescence hypothesis. We examine Kα emission produced by collisional ionization from accelerated particles, and find parameter values for the spectrum of accelerated particles which can accommodate the increased amount of Kα flux and the lack of observed nonthermal emission in the 20–50 keV spectral region.
A Cyclic Cosmological Model Based on the f(ρ) Modified Theory of Gravity

We consider FLRW cosmological models for perfect fluid (with ρ as the energy density) in the frame work of the f(ρ) modified theory of gravity [V. N. Tunyak, Russ. Phys. J. 21, 1221 (1978); J. R. Ray, L. L. Smalley, Phys. Rev. D. 26, 2615 (1982)]. This theory, with total Lagrangian R-f(ρ), can be considered as a cousin of the F(R) theory of gravity with total Lagrangian F(R)-ρ. We can pick proper function forms f(ρ) to achieve, as the F(R) theory does, the following 4 specific goals, 1) producing a non-singular cosmological model (Ricci scalar and Ricci tensor curvature are bounded); 2) explaining the cosmic early inflation and late acceleration in a unified fashion; 3) passing the solar system tests; 4) unifying the dark matter with dark energy. In addition we also achieve goal number 5) unify the regular matter/energy with dark matter/energy in a seamless fashion. The mathematics is simplified because in the f(ρ) theory the leading terms in Einstein’s equations are linear in second order derivative of metric wrt coordinates but in the F(R) theory the leading terms are linear in fourth order derivative of metric wrt coordinates.
IETIF: Intelligent Energy-Aware Task Scheduling Technique in IoT/Fog Networks

Nowadays, with the advent of various communication technologies such as the internet of things (IoT), a large volume of data is produced that needs to be processed in real-time. Fog computing is an appropriate solution to address the requirements of different types of IoT applications. In most cases, IoT applications consist of a set of dependent tasks that can be separately processed in a heterogeneous fog environment. Scheduling these tasks in a fog environment is an NP-hard problem that needs a vast amount of time and computation resources to solve, making it infeasible for real-time applications. In addition, reducing response time and energy consumption in fog computing is an essential issue that should be taken into account in task scheduling algorithms. To address these challenges, we aim to propose a multiobjective task scheduling model to jointly improve energy efficiency and response time. To solve the model, we also propose an intelligent solution named IETIF which combines and leverages the benefits of simulated annealing and NSGA-III algorithms. Simulation results show that IETIF outperforms the state-of-the-art methods in terms of energy consumption, response time, and speedup.
Dominant currency and exchange market pressure

The dominant currency paradigm proposes a theoretical framework that embodies a key stylized fact: exports and imports of peripheral economies are invoiced in a dominant currency, namely the US dollar or euro, instead of their respective national currency. This paper extends the analysis by empirically showing that movements in a dominant currency have wide macroeconomic effects, including debt sustainability in the periphery. Using a novel dataset for twelve emerging markets, the paper finds that a positive shock (appreciation) to the trade-weighted US dollar or the euro elicits strong foreign exchange pressure (shortage) in the periphery. Appreciation of the dominant currency also leads to the peripheral economy’s economic growth contraction, expansion of external debt, and wider financial intermediation spread. The paper also finds evidence supporting previous work showing high exchange rate pass-through given a depreciation of the peripheral currency. Between the two dominant currencies, the US dollar produces stronger effects on the macroeconomic variables of emerging markets.
Board characteristics and firm performance - Evidence from Chinese private listed firms In Fulfillment of the Requirements

: The purpose of this research is to examine the impact of board characteristics and firm performance in Chinese private listed firms. I use the regression analysis to test the effects of the board meeting, board size, board independence, managerial shareholding, directors without remuneration and chairman’s shareholding ratio on firm performance. Based on the sample of the 4023 firm-year observations from 447 private listed firms in China from 2010 to 2018, the results show that the firm performance is negatively associated with board meeting frequency and positively related managerial shareholding. I also find the percentage of independent directors has no relationship with firm performance. However, the findings cannot provide evidence that board size, director without remuneration and chairman’s shareholding ratio would affect firm performance. These findings provide some implications for future research on the effectiveness of board directors on private listed firm performance.
Does Education Matter for Income Inequality? Evidence from Sub-Saharan Africa

The issue of income equality has become of great concern on a global scale. Since the 2008 global financial crisis, economists and other socioeconomic analysts have observed the state of the income and wealth gap between the top ten percent rich and the lower forty percent poor of populations, and its far-reaching impact on the lives of ordinary people. Income inequality has become a global challenge and the effects are felt in both developed and developing countries. The socioeconomic disparity between the rich and poor is pronounced in developing countries, and recent trends of growing inequality are being observed in developed countries. This research examines the effect of education on income inequality and GDP per capita, using a panel dataset of 18 selected sub-Saharan countries for the period from 1994 to 2015. The panel models are estimated, using the fixed effects, random effects and generalised methods of moments estimation techniques. The results show that the relationship of education and its impact on income inequality is dependent on the level of education being assessed. High resource input in tertiary education increases income inequality, while high resource input in lower educational levels reduces income inequality. Overall, increases in government expenditure on education lead to increase in inequality and a fall in GDP per capita. These results show possible inefficiencies in the allocation of educational resources in sub-Saharan countries during the period of investigation. Government spending on education does not reduce inequality or boost income unless it is done efficiently. To reduce income inequality and increase average income, educational resources must be efficiently allocated with priority given to the educational levels of the highest proportions of the population.
ON THE STAR FORMATION EFFICIENCY OF TURBULENT MAGNETIZED CLOUDS

We study the star formation efficiency (SFE) in simulations and observations of turbulent, magnetized, molecular clouds. We find that the probability density functions (PDFs) of the density and the column density in our simulations with solenoidal, mixed, and compressive forcing of turbulence, sonic Mach numbers of 3–50, and magnetic fields in the super- to the trans-Alfvénic regime all develop power-law tails of flattening slope with increasing SFE. The high-density tails of the PDFs are consistent with equivalent radial density profiles, ρ∝r−κ with κ ∼ 1.5–2.5, in agreement with observations. Studying velocity–size scalings, we find that all the simulations are consistent with the observed v∝ℓ1/2 scaling of supersonic turbulence and seem to approach Kolmogorov turbulence with v∝ℓ1/3 below the sonic scale. The velocity–size scaling is, however, largely independent of the SFE. In contrast, the density–size and column density–size scalings are highly sensitive to star formation. We find that the power-law slope α of the density power spectrum, P3D(ρ, k)∝kα, or equivalently the Δ-variance spectrum of the column density, σ2Δ(Σ, ℓ) ∝ ℓ−α, switches sign from α ≲ 0 for SFE ∼ 0 to α ≳ 0 when star formation proceeds (SFE > 0). We provide a relation to compute the SFE from a measurement of α. Studying the literature, we find values ranging from α = −1.6 to +1.6 in observations covering scales from the large-scale atomic medium, over cold molecular clouds, down to dense star-forming cores. From those α values, we infer SFEs and find good agreement with independent measurements based on young stellar object (YSO) counts, where available. Our SFE–α relation provides an independent estimate of the SFE based on the column density map of a cloud alone, without requiring a priori knowledge of star formation activity or YSO counts.
Spatiotemporal dynamics of multimode optical solitons Spatiotemporal dynamics of multimode optical solitons

: As optical ﬁber communications and ﬁber lasers approach fundamental limits there is considerable interest in multimode ﬁbers. In nonlinear science, they represent an exciting environment for complex nonlinear waves. As in single-mode ﬁber, solitons may be particularly important. Multimode solitons consist of synchronized, non-dispersive pulses in multiple spatial modes, which interact via the Kerr nonlinearity of the ﬁber. They are expected to exhibit novel spatiotemporal characteristics, dynamics and, like single-mode solitons, may provide a convenient intuitive tool for understanding more complex nonlinear phenomena in multimode ﬁbers. Here we explore experimentally and numerically basic properties and spatiotemporal behaviors of these solitons: their formation, ﬁssion, and Raman dynamics.
Attentional Moral Perception

Moral perceptualism is the view that perceptual experience is attuned to pick up on moral features in our environment, just as it is attuned to pick up on mundane features of an environment like textures, shapes, colors, pitches, and timbres. One important family of views that incorporate moral perception are those of virtue theorists and sensibility theorists. On these views, one central ability of the virtuous agent is her sensitivity to morally relevant features of situations, where this sensitivity is often spoken of in perceptual terms. However, sensibility theorists have often not been careful to specify how to understand their claims about moral sensibilities as perceptual. In this paper, we distinguish between what we call Attentional Moral Perception and Contentful Moral Perception. We argue that sensibility theorists should endorse Attentional Moral Perception, because it has very powerful empirical evidence in its favor, and it can play all of the explanatory roles that the sensibility theorist needs in her theory of moral sensibilities.
The Effect of COVID-19 Pandemic on Volatility Transmission Between the U.S. and Emerging Asia Stock Markets: A Case Study of Tiger Cub Economies

: The globalization in financial markets has highlighted the importance of a clear understanding of volatility transmission among equity markets in different countries. This paper looks into the effect of the COVID-19 pandemic on the volatility transmission between the U.S. stock market and five emerging equity markets called Tiger Cub economies in Southeast Asia. As the result of the dynamic conditional correlation GARCH (DCC-GARCH), the U.S. stock market’s volatility links positively to these smaller economies’ volatilities, and these linkages become stronger during the pandemic. We also find evidence of statistically significant co-volatility across five Tiger Cub markets. Due to the increase in financial globalization over the last few decades, the finding has relevant implications for policymakers, international investors, and portfolio managers.