Miracle-dz/UniFAR-FTUs huggingface dataset:
Agr2‐interacting Prod1‐like protein Tfp4 from Xenopus laevis is necessary for early forebrain and eye development as well as for the tadpole appendage regeneration

The Agr family genes, Ag1, Agr2, and Agr3, encode for the thioredoxin domain containing secreted proteins and are specific only for vertebrates. These proteins are attracting increasing attention due to their involvement in many physiological and pathological processes, including exocrine secretion, cancer, regeneration of the body appendages, and the early brain development. At the same time, the mode by which Agrs regulate intracellular processes are poorly understood. Despite that the receptor to Agr2, the membrane anchored protein Prod1, has been firstly discovered in Urodeles, and it has been shown to interact with Agr2 in the regenerating limb, no functional homologs of Prod1 were identified in other vertebrates. This raises the question of the mechanisms by which Agrs can regulate regeneration in other lower vertebrates. Recently, we have identified that Tfp4 (three‐fingers Protein 4), the structural and functional homolog of Prod1 in Anurans, interacts with Agr2 in Xenopus laevis embryos. In the present work we show by several methods that the activity of Tfp4 is essential for the tadpole tail regeneration as well as for the early eye and forebrain development during embryogenesis. These data show for the first time the common molecular mechanism of regeneration regulation in amphibians by interaction of Prod1 and Agr2 proteins.
Recidivism Among Justice-Involved Youth: Findings From JJ-TRIALS

Recidivism, and the factors related to it, remains a highly significant concern among juvenile justice researchers, practitioners, and policy makers. Recent studies highlight the need to examine multiple measures of recidivism as well as conduct multilevel analyses of this phenomenon. Using data collected in a National Institute on Drug Abuse (NIDA)-funded Juvenile Justice-Translational Research on Interventions for Adolescents in the Legal System (JJ-TRIALS) cooperative agreement, we examined individual- and site-level factors related to 1-year recidivism among probation youth in 20 sites in five states to answer research questions related to how recidivism rates differ across sites and the relationships between individual-level variables and a county-level concentrated disadvantage measure and recidivism. Our findings of large site differences in recidivism rates, and complex relationships between individual and county-level predictors of recidivism, highlight the need for more nuanced, contextually informed, multilevel approaches in studying recidivism among juveniles.
Beyond Incivility: Understanding Patterns of Uncivil and Intolerant Discourse in Online Political Talk

This article takes up the popular argument that much online discussion is toxic and hence harmful to democracy, and argues that the pervasiveness of incivility is not incompatible with democratically relevant political talk. Instead of focusing on the tone of political talk, scholars interested in understanding the extent to which digital platforms threaten democratic values should focus on expressions of intolerance. I demonstrate the validity of this conceptual model by investigating the discursive and contextual features associated with incivility and intolerance online in the context of public comments in two different platforms—news websites and Facebook. Results show that incivility and intolerance occur in meaningfully different discussion settings. Whereas incivility is associated with features that reveal meaningful discursive engagement, such as justified opinion expression and engagement with disagreement, intolerance is likely to occur in homogeneous discussions about minorities and civil society—exactly when it can hurt democracy the most.
Understanding of learning styles and teaching strategies towards improving the teaching and learning of mathematics

This study was conducted to analyse the influence of learning styles and teaching strategies on academic performance in mathematics. Surveys were conducted to 277 randomly selected grade 9 students and five purposively sample mathematics teachers. Findings reveal that most of the student-respondents have a combination of dependent, collaborative and independent learning styles. Multiple regression analysis indicates that among the learning styles, only the independent style has a significant influence on the academic performance of grade 9 students. Four teaching strategies including cooperative learning, deductive approach, inductive approach, and integrative approach, were found to have a significant influence on academic performance. By understanding the learning styles of students, teachers will be guided in designing different strategies to help students enhance learning for their improved performance in mathematics.
Modeling Gamma-Ray Light Curves with More Realistic Pulsar Magnetospheres

We study the gamma-ray emission patterns and light curves in dissipative pulsar magnetospheres. We produce the gamma-ray light curves by using the geometric method and the particle trajectory method. For the geometric method, assuming the gamma-ray emission originates in a finite-width layer along the last closed lines, we generate the gamma-ray light curves based on the uniform emissivity along the magnetic field lines in the comoving frame. For the particle trajectory method, we consider the spatial distribution of conductivity σ by assuming a very high conductivity within the light cylinder (LC) and a finite conductivity outside the LC. Assuming that all the γ-ray emission originates in the outer magnetosphere outside the LC, we generate the gamma-ray light curves by computing realistic particle trajectories and Lorentz factors, taking into account both the accelerating electric field and curvature radiation loss. Further, we compare the modeling light curves to the observed light curves at >0.1 GeV energies for the Vela pulsar. Our results show that the magnetosphere with the low σ value is preferred for the geometric method. However, the magnetosphere with a near force-free regime within the LC and a high σ value outside the LC is favored for the particle trajectory method. It is noted that the particle trajectory method uses the parallel electric fields that are self-consistent with the magnetic fields of the magnetosphere. We suggest that the results from the particle trajectory method are better supported on the physical ground.
Skeletal muscle Nur77 and NOR1 insulin responsiveness is blunted in obesity and type 2 diabetes but improved after exercise training

Obesity and type 2 diabetes (T2DM) are characterized by a blunted metabolic response to insulin, and strongly manifests in skeletal muscle insulin resistance. The orphan nuclear receptors, Nur77 and NOR1, regulate insulin‐stimulated nutrient metabolism where Nur77 and NOR1 gene expression is increased with acute aerobic exercise and acute insulin stimulation. Whether Nur77 or NOR1 are associated with the insulin‐sensitizing effects of chronic aerobic exercise training has yet to be elucidated. Fourteen lean healthy controls (LHC), 12 obese (OB), and 10 T2DM individuals (T2DM) underwent hyperinsulinemic‐euglycemic clamps with skeletal muscle biopsies. Muscle was analyzed for Nur77 and NOR1 gene and protein expression at basal and insulin‐stimulated conditions. Furthermore, a subcohort of 18 participants (OB, n = 12; T2DM, n = 6) underwent a 12‐week aerobic exercise intervention (85% HRmax, 60 min/day, 5 days/week). In response to insulin infusion, LHC increased protein expression of Nur77 (8.7 ± 3.2‐fold) and NOR1 (3.6 ± 1.1‐fold), whereas OB and T2DM remained unaffected. Clamp‐derived glucose disposal rates correlated with Nur77 (r2 = 0.14) and NOR1 (r2 = 0.12) protein expression responses to insulin, whereas age (Nur77: r2 = 0.22; NOR1: r2 = 0.25) and BMI (Nur77: r2 = 0.22; NOR1: r2 = 0.42) showed inverse correlations, corroborating preclinical data. In the intervention cohort, exercise improved Nur77 protein expression in response to insulin (PRE: −1.2 ± 0.3%, POST: 6.2 ± 1.5%). Also, insulin treatment of primary human skeletal muscle cells increased Nur77 and NOR1 protein. These findings highlight the multifactorial nature of insulin resistance in human obesity and T2DM. Understanding the regulation of Nur77 and NOR1 in skeletal muscle and other insulin‐sensitive tissues will create opportunities to advance therapies for T2DM.
Cardiac Screening to Mitigate the Risk of Sudden Cardiac Death in Middle Eastern and African Competitive Athletes. A Systematic Review

Objective The study aims to review the literature regarding abnormalities predisposing to Sudden Cardiac Death (SCD) in young Middle Eastern and African competitive athletes between the years 2009–2019 and aims to assess cardiac pre-participation screening methods. Methods A PubMed search was performed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The search targeted articles that reported the prevalence of cardiac abnormalities found in Middle Eastern and African athletes, and it also focused on comparing cardiac screening methods for assessment of athletes. Results our studies fell within the inclusion criteria and were included in the study. Results identified a shortage in the literature regarding prevalence rates of SCD in the Middle East and Africa. Additionally, there seems to be a lack of ethnicity-specific cardiac pre-participation screening programs in the region. Nevertheless, the prevalence of SCD-related abnormalities (HCM, ARVC, etc …) ranged from 0.47 to 4.29%. Included studies conveyed only male athletes with no reports on the female athletic population. Conclusion The present study highlights a need to develop an efficient cardiac pre-participation screening program specific to Arab and African athletes due to their high false-positive rates in contrast to Caucasian athletes. Significant evidence proves that an adequate cardiac screening program can prevent SCD in young competitive athletes. Therefore, it is imperative that future studies highlight the prevalence of abnormalities directly related to SCD in order to create a valid screening program that can be implemented in the region to mitigate the risk of shocking events.
Decomposing information into copying versus transformation

In many real-world systems, information can be transmitted in two qualitatively different ways: by copying or by transformation. Copying occurs when messages are transmitted without modification, e.g., when an offspring receives an unaltered copy of a gene from its parent. Transformation occurs when messages are modified systematically during transmission, e.g., when non-random mutations occur during biological reproduction. Standard information-theoretic measures do not distinguish these two modes of information transfer, although they may reflect different mechanisms and have different functional consequences. Starting from a few simple axioms, we derive a decomposition of mutual information into the information transmitted by copying and by transformation. Our decomposition applies whenever the source and destination of the channel have the same set of outcomes, so that a notion of message identity exists, although generalizations to other kinds of channels and similarity notions are explored. Furthermore, copy information can be interpreted as the minimal work needed by a physical copying process, relevant to better understand the physics of replication. We use the proposed decomposition to explore a model of amino acid substitution rates. Our results apply to any system in which the fidelity of copying, rather than simple predictability, is of critical relevance.
To thine own test be true: HIV self‐testing and the global reach for the undiagnosed

Copyright © 2019 World Health Organization; licensed by IAS. This is an open access article distributed under the terms of the Creative Commons Attribution IGO License https://creativecommons.org/licenses/by/3.0/igo/legalcode which permits unrestricted use, distribution and reproduction in any medium, provided that the original work is properly cited. In any reproduction of this article there should not be any suggestion that WHO or the article endorse any specific organization or products. The use of the WHO logo is not permitted. This notice should be preserved along with the article’s URL.
Fully numerical Hartree‐Fock and density functional calculations. II. Diatomic molecules

We present the implementation of a variational finite element solver in the HelFEM program for benchmark calculations on diatomic systems. A basis set of the form $\chi_{nlm}(\mu,\nu,\phi)=B_{n}(\mu)Y_{l}^{m}(\nu,\phi)$ is used, where $(\mu,\nu,\phi)$ are transformed prolate spheroidal coordinates, $B_{n}(\mu)$ are finite element shape functions, and $Y_{l}^{m}$ are spherical harmonics. The basis set allows for an arbitrary level of accuracy in calculations on diatomic molecules, which can be performed at present with either nonrelativistic Hartree--Fock (HF) or density functional (DF) theory. Hundreds of DFs at the local spin-density approximation (LDA), generalized gradient approximation (GGA) and the meta-GGA level can be used through an interface with the Libxc library; meta-GGA and hybrid DFs aren't available in other fully numerical diatomic program packages. Finite electric fields are also supported in HelFEM, enabling access to electric properties. We introduce a powerful tool for adaptively choosing the basis set by using the core Hamiltonian as a proxy for its completeness. HelFEM and the novel basis set procedure are demonstrated by reproducing the restricted open-shell HF limit energies of 68 diatomic molecules from the $1^{\text{st}}$ to the $4^{\text{th}}$ period with excellent agreement with literature values, despite requiring \emph{orders of magnitude} fewer parameters for the wave function. Then, the electric properties of the BH and N2 molecules under finite field are studied, again yielding excellent agreement with previous HF limit values for energies, dipole moments, and dipole polarizabilities, again with much more compact wave functions than what were needed in the literature references. Finally, HF, LDA, GGA, and meta-GGA calculations of the atomization energy of N2 are performed, demonstrating the superb accuracy of the present approach.
Constraining the Dimensionality of SN Ia Spectral Variation with Twins

SNe Ia continue to play a key role in cosmological measurements. Their interpretation over a range in redshift requires a rest-frame spectral energy distribution model. For practicality, these models are parameterized with a limited number of parameters and are trained using linear or nonlinear dimensionality reduction. This work focuses on the related problem of estimating the number of parameters underlying SN Ia spectral variation (the dimensionality). I present a technique for using the properties of high-dimensional space and the counting statistics of “twin” SNe Ia to estimate this dimensionality. Applying this method to the supernova pairings from Fakhouri et al. shows that a modest number of parameters (three to five, not including extinction) explain those data well. The analysis also finds that the intrinsic parameters are approximately Gaussian-distributed. The limited number of parameters hints that improved SED models are possible that may enable substantial reductions in SN cosmological uncertainties with current and near-term data sets.
Sexual Function and Quality of Life in a Cohort of Brazilian Users of Two Kind of Intrauterine Contraceptives

Abstract Objective To compare sexual function and quality of life (QOL) among intrauterine contraceptive (copper-intrauterine device [Cu-IUD] or the 52-mg 20 µg/day levonorgestrel-releasing intrauterine system [LNG-IUS]) users. Methods This was part of a cross-sectional study. Women aged between 18 and 49 years old, in a heterosexual relationship, reporting sexual intercourse in the previous 4 weeks, using Cu-IUD (Group 1) or LNG-IUS (Group 2) responded to a questionnaire with sociodemographic information, to the Female Sexual Function Index (FSFI), to the World Health Organization QOL Questionnaire Abbreviated Version (WHOQOL-BREF), and to a questionnaire about the contraceptive method used. The Student t-test, the Pearson χ2 test or the Fisher exact test, and the Mann-Whitney test were used for the analysis. For the adjusted comparison, we have used the analysis of covariance (ANCOVA). A multiple regression analyzing factors related to FSFI ≤ 26.55 was done. Significance was established at p < 0.05. Results A total of 347 women in Group 1 (mean age of 32.3 ± 7.5 years old) and of 298 in Group 2 (mean age of 32.7 ± 6.4 years old) completed the questionnaires. Most women had ≥ 8 years of schooling, were in a monogamous relationship, and had had ≤ 2 pregnancies. A total of 122 Cu-IUD and of 87 LNG-IUS users scored ≤ 26.55 on the FSFI. Significant lower scores in physical, environmental, and overall QOL domains in the WHOQOL-BREF questionnaire were found in Group 1. More women using the Cu-IUD were not satisfied with the method. Conclusion We did not find significant differences in sexual function; there was a lower score in some domains of QOL among women who used the Cu-IUD. It was not possible to ensure that those differences were related to the contraceptive method.
Hartogs domains and the Diederich–Fornæss index

We study a geometric property of the boundary on Hartogs domains which can be used to find upper and lower bounds for the Diederich-Forn{\ae}ss Index. Using this, we are able to show that under some reasonable hypotheses on the set of weakly pseudoconvex points, the Diederich-Forn{\ae}ss Index for a Hartogs domain is equal to one if and only if the domain admits a family of good vector fields in the sense of Boas and Straube. We also study the analogous problem for a Stein neighborhood basis, and show that under the same hypotheses if the Diederich-Forn{\ae}ss Index for a Hartogs domain is equal to one then the domain admits a Stein neighborhood basis.
A Channel Measurement Campaign for mmWave Communication in Industrial Settings

Industry 4.0 relies heavily on wireless technologies. Energy efficiency and device cost have played a significant role in the initial design of such wireless systems for industry automation. However, high reliability, high throughput, and low latency are also key for certain sectors such as the manufacturing industry. In this sense, existing wireless solutions for industrial settings are limited. Emerging technologies such as millimeter-wave (mmWave) communication are highly promising to address this bottleneck. Still, the propagation characteristics at such high frequencies in harsh industrial settings are not well understood. Related work in this area is limited to isolated measurements in specific scenarios. In this work, we carry out an extensive measurement campaign in highly representative industrial environments. Most importantly, we derive the statistical link-level distributions of the channel parameters of widely accepted mmWave channel model of IEEE 802.11 ad that fit these environments. This model can be beneficial to understand the performance of mmWave systems in typical industrial settings. Beyond analyzing and discussing the insights, with this article we also share our extensive dataset with the community.
General Probabilistic Surface Optimization and Log Density Estimation

In this paper we contribute a novel algorithm family, which generalizes many unsupervised techniques including unnormalized and energy models, and allows us to infer different statistical modalities (e.g. data likelihood and ratio between densities) from data samples. The proposed unsupervised technique, named Probabilistic Surface Optimization (PSO), views a model as a flexible surface which can be pushed according to loss-specific virtual stochastic forces, where a dynamical equilibrium is achieved when the pointwise forces on the surface become equal. Concretely, the surface is pushed up and down at points sampled from two different distributions. The averaged up and down forces become functions of these two distribution densities and of force magnitudes defined by the loss of a particular PSO instance. Upon convergence, the force equilibrium imposes an optimized model to be equal to various statistical functions depending on the used magnitude functions. Furthermore, this dynamical-statistical equilibrium is extremely intuitive and useful, providing many implications and possible usages in probabilistic inference. We connect PSO to numerous existing statistical works which are also PSO instances, and derive new PSO-based inference methods as demonstration of PSO exceptional usability. Likewise, based on the insights coming from the virtual-force perspective we analyze PSO stability and propose new ways to improve it. Finally, we present new instances of PSO, termed PSO-LDE, for data log-density estimation and also provide a new NN block-diagonal architecture for increased surface flexibility, which significantly improves estimation accuracy. Both PSO-LDE and the new architecture are combined together as a new density estimation technique. In our experiments we demonstrate this technique to be superior over state-of-the-art baselines in density estimation task for multimodal 20D data.
Federated Learning Of Out-Of-Vocabulary Words

We demonstrate that a character-level recurrent neural network is able to learn out-of-vocabulary (OOV) words under federated learning settings, for the purpose of expanding the vocabulary of a virtual keyboard for smartphones without exporting sensitive text to servers. High-frequency words can be sampled from the trained generative model by drawing from the joint posterior directly. We study the feasibility of the approach in two settings: (1) using simulated federated learning on a publicly available non-IID per-user dataset from a popular social networking website, (2) using federated learning on data hosted on user mobile devices. The model achieves good recall and precision compared to ground-truth OOV words in setting (1). With (2) we demonstrate the practicality of this approach by showing that we can learn meaningful OOV words with good character-level prediction accuracy and cross entropy loss.
Video Relationship Reasoning Using Gated Spatio-Temporal Energy Graph

Visual relationship reasoning is a crucial yet challenging task for understanding rich interactions across visual concepts. For example, a relationship \{man, open, door\} involves a complex relation \{open\} between concrete entities \{man, door\}. While much of the existing work has studied this problem in the context of still images, understanding visual relationships in videos has received limited attention. Due to their temporal nature, videos enable us to model and reason about a more comprehensive set of visual relationships, such as those requiring multiple (temporal) observations (e.g., \{man, lift up, box\} vs. \{man, put down, box\}), as well as relationships that are often correlated through time (e.g., \{woman, pay, money\} followed by \{woman, buy, coffee\}). In this paper, we construct a Conditional Random Field on a fully-connected spatio-temporal graph that exploits the statistical dependency between relational entities spatially and temporally. We introduce a novel gated energy function parametrization that learns adaptive relations conditioned on visual observations. Our model optimization is computationally efficient, and its space computation complexity is significantly amortized through our proposed parameterization. Experimental results on benchmark video datasets (ImageNet Video and Charades) demonstrate state-of-the-art performance across three standard relationship reasoning tasks: Detection, Tagging, and Recognition.