Miracle-dz/UniFAR-FTUs huggingface dataset:
Optical and Near-Infrared Spectroscopy of Cygnus A

We present optical and near-infrared spectroscopy of the luminous radio galaxy Cygnus A (3C 405). Optical (∼6700–9300 Å) observations were obtained of the central region, including the region where most emission lines are strongest, about 1. ″5 northwest of the nucleus. However, high-ionization lines ([Ar XI] and [Fe XI]), as well as an unidentified feature at ∼7608 Å, are stronger in the continuum-dominated southeast component. We detect the near-infrared Ca triplet in absorption, and we use it to obtain a new determination of the redshift and velocity dispersion of the stellar component of Cygnus A. The infrared (∼1.9–2.5 μm) spectrum of the nucleus shows emission from [Si VI], [S XI], and possibly [Si XI]. A number of molecular hydrogen transitions were also detected; their ratios favor X-ray heating from the nuclear source over other possible origins (e.g., shocks) as the most likely excitation mechanism. We see no evidence for broad-line wings on the Paα line profile, confirming that the broad-line region in Cygnus A remains heavily obscured at 2 μm.
Constrained extended Kalman filter for improving Bayesian inference of vocal function from laryngeal high-speed videoendoscopy

Bayesian estimation based on an extended Kalman filter and a muscle-controlled biomechanical model of the vocal folds has demonstrated a viable, appealing method for obtaining physiologically relevant measures of glottal function (e.g., subglottal pressure, activation of laryngeal muscles, and vocal fold collision pressure) from synchronized recordings of calibrated high-speed videoendoscopy and oral airflow. In practice, the simultaneous recording of these signals is a cumbersome, uncomfortable procedure for patients. To simplify the experimental procedure while maintaining sufficient accuracy, we introduce a constrained Bayesian scheme that suitably incorporates physiological information about the subglottal pressure and uses the glottal area waveform as the sole observation. The proposed constrained extended Kalman filter produces reliable glottal airflow estimates compared to in-lab obtained waveforms, yielding root-mean-square errors lower than 63 mL/s, a performance similar to previous studies. These initial results provide advancement for the clinical assessment of vocal function.
Self-Supervised Learning IoT Device Features With Graph Contrastive Neural Network for Device Classification in Social Internet of Things

Device Classification (DC) is one of the critical network management means in the Internet of Things (IoT). Most machine learning-driven DC methods are implemented in two steps: firstly, extracting device features, and then training the classifier. Thus, for the same classifier, the quality of device features plays a decisive role. However, for one thing, these methods usually merely consider device traffic or device attributed features, ignoring the complex relationship between devices in Social IoT. For another thing, these features fed to the classifier are often selected manually without automatic learning. These two factors seriously affect the performance and flexibility of the algorithm. To address the above issues, we propose a novel Graph Contrastive Neural Network-based algorithm for DC dubbed GCNNDC. Specifically, based on the complex relationship between heterogeneous objects in Social IoT and the attribute information of the device itself, we first construct four kinds of homogeneous device-device attributed networks as the input of the neural network. Then, we train a novel GCNN model to learn informative device features in a self-supervised learning fashion. Finally, we leverage the features to train a classifier to complete the DC task. Experimental results on real-world IoT network dataset demonstrate the superiority of GCNNDC.
Incorporating the Effects of 3D Radiative Transfer in the Presence of Clouds into Two-Stream Multilayer Radiation Schemes

This paper presents a new method for representing the important effects of horizontal radiation transport through cloud sides in two-stream radiation schemes. Ordinarily, the radiative transfer equations are discretized separately for the clear and cloudy regions within each model level, but here terms are introduced that represent the exchange of radiation laterally between regions and the resulting coupled equations are solvedforeach layer.This approachmay be takenwith boththe direct incoming shortwave radiation,which is governed by Beer’s law, and the diffuse shortwave and longwave radiation, governed by the two-stream equations. The rate of lateral exchange is determined by the area of cloud ‘‘edge. ’’ The validity of the method is demonstrated by comparing with rigorous 3D radiative transfer calculations in the literature for two cloud types in which the 3D effect is strong, specifically cumulus and aircraft contrails. The 3D effect on shortwave cloud radiative forcing varies between around 225% and around 1100%, depending on solar zenith angle. Even with an otherwise very simplistic representation of the cloud, the new scheme exhibits good agreement with the rigorous calculations in the shortwave, opening the way for efficient yet accurate representation of this important effect in climate models.
Genome-Wide Analysis of lncRNA and mRNA Expression in the Uterus of Laying Hens during Aging

Eggshell plays an essential role in preventing physical damage and microbial invasions. Therefore, the analysis of genetic regulatory mechanisms of eggshell quality deterioration during aging in laying hens is important for the biosecurity and economic performance of poultry egg production worldwide. This study aimed to compare the differences in the expression profiles of long non-coding RNAs (lncRNAs) and mRNAs between old and young laying hens by the method of high-throughput RNA sequencing to identify candidate genes associated with aging in the uterus of laying hens. Overall, we detected 176 and 383 differentially expressed (DE) lncRNAs and mRNAs, respectively. Moreover, functional annotation analysis based on the Gene Ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) databases revealed that DE-lncRNAs and DE-mRNAs were significantly enriched in “phosphate-containing compound metabolic process”, “mitochondrial proton-transporting ATP synthase complex”, “inorganic anion transport”, and other terms related to eggshell calcification and cuticularization. Through integrated analysis, we found that some important genes such as FGF14, COL25A1, GPX8, and GRXCR1 and their corresponding lncRNAs were expressed differentially between two groups, and the results of quantitative real-time polymerase chain reaction (qPCR) among these genes were also in excellent agreement with the sequencing data. In addition, our study found that TCONS_00181492, TCONS_03234147, and TCONS_03123639 in the uterus of laying hens caused deterioration of eggshell quality in the late laying period by up-regulating their corresponding target genes FGF14, COL25A1, and GRXCR1 as well as down-regulating the target gene GPX8 by TCONS_01464392. Our findings will provide a valuable reference for the development of breeding programs aimed at breeding excellent poultry with high eggshell quality or regulating dietary nutrient levels to improve eggshell quality.
Exploring listening-related fatigue in children with and without hearing loss using self-report and parent-proxy measures

Children with hearing loss appear to experience greater fatigue than children with normal hearing (CNH). Listening-related fatigue is often associated with an increase in effortful listening or difficulty in listening situations. This has been observed in children with bilateral hearing loss (CBHL) and, more recently, in children with unilateral hearing loss (CUHL). Available tools for measuring fatigue in children include general fatigue questionnaires such as the child self-report and parent-proxy versions of the PedsQLTM-Multidimensional Fatigue Scale (MFS) and the PROMIS Fatigue Scale. Recently, the Vanderbilt Fatigue Scale (VFS-C: child self-report; VFS-P: parent-proxy report) was introduced with a specific focus on listening-related fatigue. The aims of this study were to compare fatigue levels experienced by CNH, CUHL and CBHL using both generic and listening-specific fatigue measures and compare outcomes from the child self-report and parent-proxy reports. Eighty children aged 6–16 years (32 CNH, 19 CUHL, 29 CBHL), and ninety-nine parents/guardians (39 parents to CNH, 23 parents to CUHL, 37 parents to CBHL), completed the above fatigue questionnaires online. Kruskal-Wallis H tests were performed to compare fatigue levels between the CNH, CUHL and CBHL. To determine the agreement between parent-proxy and child self-report measures, Bland-Altman 95% limits of agreement were performed. All child self-report fatigue measures indicated that CBHL experience greater fatigue than CNH. Only the listening-specific tool (VFS-C) was sufficiently able to show greater fatigue in CUHL than in CNH. Similarly, all parent-proxy measures of fatigue indicated that CBHL experience significantly greater fatigue than CNH. The VFS-P and the PROMIS Fatigue Parent-Proxy also showed greater fatigue in CUHL than in CNH. Agreement between the parent-proxy and child self-report measures were found within the PedsQL-MFS and the PROMIS Fatigue Scale. Our results suggest that CBHL experience greater levels of daily-life fatigue compared to CNH. CUHL also appear to experience more fatigue than CNH, and listening-specific measures of fatigue may be better able to detect this effect. Further research is needed to understand the bases of fatigue in these populations and to clarify whether fatigue experienced by CBHL and CUHL is comparable in nature and degree.
Machine Learning Identification of Obstructive Sleep Apnea Severity through the Patient Clinical Features: A Retrospective Study

Objectives: To evaluate the role of clinical scores assessing the risk of disease severity in patients with clinical suspicion of obstructive sleep apnea syndrome (OSA). The hypothesis was tested by applying artificial intelligence (AI) to demonstrate its effectiveness in distinguishing between mild–moderate OSA and severe OSA risk. Methods: A support vector machine model (SVM) was developed from the samples included in the analysis (N = 498), and they were split into 75% for training (N = 373) with the remaining for testing (N = 125). Two diagnostic thresholds were selected for OSA severity: mild to moderate (apnea–hypopnea index (AHI) ≥ 5 events/h and AHI < 30 events/h) and severe (AHI ≥ 30 events/h). The algorithms were trained and tested to predict OSA patient severity. Results: The sensitivity and specificity for the SVM model were 0.93 and 0.80 with an accuracy of 0.86; instead, the logistic regression full mode reported a value of 0.74 and 0.63, respectively, with an accuracy of 0.68. After backward stepwise elimination for features selection, the reduced logistic regression model demonstrated a sensitivity and specificity of 0.79 and 0.56, respectively, and an accuracy of 0.67. Conclusion: Artificial intelligence could be applied to patients with symptoms related to OSA to identify individuals with a severe OSA risk with clinical-based algorithms in the OSA framework.
Narrow-band nonlinear sea waves

Probabilistic description of nonlinear waves with a narrow-band spectrum is simplified to a form in which each realization of the surface displacement becomes an amplitude-modulated Stokes wave with a mean frequency and random phase. Under appropriate conditions this simplification provides a convenient yet rigorous means of describing nonlinear effects on sea surface properties in a semiclosed or closed form. In particular, it is shown that surface displacements are non-Gaussian and skewed, as was previously predicted by the Gram-Charlier approximation; that wave heights are Rayleigh distributed, just as in the linear case; and that crests are non-Rayleigh.
The Effectiveness of Educational Robots in Improving Learning Outcomes: A Meta-Analysis

Numerous studies have been conducted to investigate the potential effect of educational robots, but what appears to be missing is an up-to-date and thorough review of the learning effectiveness of educational robots and the various influencing factors. In this study, a meta-analysis was conducted to systematically synthesize studies’ findings on the effects of educational robots on students’ learning outcomes. After searching for randomized studies describing educational robots interventions to improve learning outcomes, 34 effect sizes described in 17 articles met the selection criteria. The results of our work evidence a moderate but significantly positive effect of educational robots on learning outcomes (g = 0.57, 95% CI [0.49, 0.65], p < 0.00001). Moreover, moderator analyses were conducted to investigate important factors relating to the variation of the impact, including educational level and assessment type. Based on the findings of this study, we provide researchers and practitioners with insights into what characteristics of educational robot interventions appear to benefit students’ learning outcomes and how pedagogical approaches can be applied in various educational settings to guide the design of future educational robot interventions.
AGB stellar evolution and symbiotic stars

Une annalyse des donnees publiees sur les pertes de masse et les periodes des etoiles Mira et des sources OH/IR montre une bonne correlation entre le taux de perte de masse et la periode et une transition reguliere des etoiles Mira aux sources OH/IR. Les variables symbiotiques s'amassent dans la zone de transition ou les etoiles Mira se transforment en sources OH/IR et ou l'accroissement des pertes de masse est a son niveau le plus raide. La geante rouge dans ces systemes symbiotiques est dans le meme etat d'evolution que les sources OH/IR a courtes periodes
Deterioration in Heat Transfer to Fluids at Supercritical Pressure and High Heat Fluxes

At slightly supercritical pressure and in the neighborhood of the pseudo-critical temperature (defined as the temperature corresponding to the peak in specific heat at the operating pressure), the heat transfer coefficient between fluid and tube wall is strongly dependent on the heat flux. For large heat fluxes, a marked deterioration takes place in the heat transfer coefficient in the region where the bulk fluid temperature is below and the wall temperature above the pseudo-critical temperature. An analysis has been developed, based on the integration of the transport equations, to predict the deterioration in heat transfer at high heat fluxes, and the results have been compared with the previously available experimental results for steam. Experiments have been performed with carbon dioxide for additional comparison. Limits of safe operation in terms of the allowable heat flux for a particular flow rate have been determined both theoretically and experimentally. Experiments with twisted tape inserted in the test section to generate swirl have shown that the heat transfer rates can be improved by this method. Qualitative visual observations have been made of the flow under varying conditions of heat flux and flow rate.
Reports of practitioners’ use of public affairs faculty published research

ABSTRACT Using a unique dataset built around published papers in top quality public policy, public administration and program evaluation journals, we find that 29.7% of respondent authors indicate that the knowledge from their articles was used by policymakers or public administrators. These data are used to test for different patterns of use for policy vs management knowledge. Findings suggest that journal quality positively affects policy use but negatively affects management use and that topics suggested by practitioners affect management use but not policy use. The researchers’ degree of motivation to have their work used is important in both types of knowledge use. Overall, the results suggest there may be greater spillovers to practical use derived from standard academic publishing pursuits than generally believed.
Evolutions of Self-Rated Health and Social Interactions during the COVID-19 Pandemic Affected by Pre-Pandemic Conditions: Evidence from a Four-Wave Survey

The Coronavirus disease 2019 (COVID-19) pandemic has affected individuals’ self-rated health (SRH) and social interactions, but their evolution during the pandemic needs further investigation. The present study addressed this issue using longitudinal data from 13,887 observations of 4177 individuals obtained from a four-wave nationwide, population-based survey conducted between January and February 2019 (before the pandemic) and November 2022. We compared the evolutions of SRH and social interactions during the pandemic between individuals who interacted with others before the pandemic and those who did not. Three noteworthy findings were obtained. First, deterioration in SRH in response to the declared state of emergency was concentrated on individuals with no pre-pandemic interaction with others. Second, SRH generally improved during the pandemic, although the improvement was more remarkable among previously isolated individuals. Third, the pandemic has promoted social interactions among previously isolated individuals and reduced such chances among those who previously interacted with others. These findings underscore the importance of pre-pandemic social interactions as key determinants of responding to pandemic-related shocks.
Modelling of Catalytic Combustion in a Deformable Porous Burner Using a Fluid–Solid Interaction (FSI) Framework

The various concepts involved in the mathematical modeling of the fluid–solid interactions (FSIs) of catalytic combustion processes occurring within a porous burner are presented and discussed in this paper. The following aspects of them are addressed: (a) the relevant physical and chemical phenomena appearing at the interface between the gas and the catalytic surface; (b) a comparison of mathematical models; (c) a proposal of a hybrid two/three-field model, (d) an estimation of the interphase transfer coefficients; (e) a discussion of the proper constitutive equations and the closure relations; and (f) a generalization of the Terzaghi concept of stresses. Selected examples of application of the models are then presented and described. Finally, a numerical verification example is presented and discussed to demonstrate the application of the proposed model.
From an Operational to a Relational Conception of the Equal Sign. Third Graders' Developing Algebraic Thinking

We describe a teaching experiment about third grade studentsunderstanding of the equal sign and their initial forays into analyzing expressions. We used true/false and open number sentences in forms unfamiliar to the students to cause students to reconsider their conceptions of the equal sign. Our results suggest a sequence of three stages in the evolution of students' understanding of the equal sign with students progressing from a procedural/computational perspective to an analytic perspective. Our data show that as students deepened their conceptions about the equal sign they began to analyze expressions in ways that promoted algebraic thinking. We describe the essential elements of instruction that advanced this learning.
The Effect of Accentuation of Curve of Spee on Masticatory Efficiency—A Systematic Review and Meta-Analysis

Background: The appropriate alignment of the lower teeth is indicated by the Curve of Spee (COS), which can be observed in the sagittal profile view of human skulls. Graf Von Spee made the initial observation on this occlusal curvature. Through this systematic review and meta-analysis, we evaluated studies that looked at how COS affected masticatory activities. Methods: The databases PubMed-MEDLINE, Web of Science, Cochrane, and Scopus were all searched. A total of 12 documents were ultimately picked because they met the necessary inclusion and exclusion requirements. The data was then loaded into the RevMan 5 programme for meta-analysis after being chosen for information on the sample size, variables analyzed, and various aspects of the research. Results: The Curve of Spee was found to have a noticeable impact on both the masticatory efficiency as well as dentofacial alignment in the 12 studies that we selected for the review and meta-analysis. In addition, other occlusal curvatures such as the Curve of Monson and the Curve of Wilson were found to be of vital importance on a similar level to the COS. The meta-analysis further revealed that seven of the included clinical trials had mentioned the noticeable impact on masticatory efficiency. Conclusions: This study focused on the significance of the COS on force distribution in the oral cavity as well as the necessity of COS corrections after receiving full orthodontic care. Following orthodontic treatment, the COS, along with other occlusal curves such as the Curve of Wilson and the Curve of Monson, is essential in removing strains from the condyle, as well as the maxilla and mandible, which enhances masticatory effectiveness and lessens the overall strain on a patient’s oral cavity.
Phrasal verbs in European Parliament conference English: a corpus-based pedagogical list

ABSTRACT Phrasal verbs (PVs), comprising a lexical verb and an adverbial particle, are a notoriously difficult category of multiword units even for advanced learners of English because of their syntactic peculiarity and semantic complexity. Non-native professional interpreters have also been found to use PVs much less often than their native counterparts in simultaneous interpreting into English. This study aims to generate a pedagogical list containing the most frequent PVs and their major meanings for conference interpreting purposes. A corpus-based approach was adopted to identify PVs in a 724,054-word corpus comprising transcribed speeches interpreted into or held in English during the European Parliament plenary sessions. Out of a total of 461 PVs, 169 PVs crossed the lowest frequency threshold. They make up 87.07% of all PV occurrences in the corpus, suggesting the dominance of the top 1/3 of the PVs. Semantic analysis showed that the 169 PVs have a relatively small number of key meanings (two on average), and that the primary meanings play a dominant role. Available as an online supplemental material, the European Parliament Conference English Phrasal Verb Pedagogical List (The EP-CE PHaVE List) contains these most frequent 169 PVs, their major meanings, and example sentences extracted from the corpus.
Productivity of "Collisions Generate Heat" for Reconciling an Energy Model with Mechanistic Reasoning: A Case Study.

We observe teachers in professional development courses about energy constructing mechanistic accounts of energy transformations. We analyze a case in which teachers investigating adiabatic compression develop a model of the transformation of kinetic energy to thermal energy. Among their ideas is the idea that thermal energy is generated as a byproduct of individual particle collisions, which is represented in science education research literature as an obstacle to learning. We demonstrate that in this instructional context, the idea that individual particle collisions generate thermal energy is not an obstacle to learning, but instead is productive: it initiates intellectual progress. Specifically, this idea initiates the reconciliation of the teachers' energy model with mechanistic reasoning about adiabatic compression, and leads to a canonically correct model of the transformation of kinetic energy into thermal energy. We claim that the idea's productivity is influenced by features of our particular instructional context, including the instructional goals of the course, the culture of collaborative sense-making, and the use of certain representations of energy. I. Introduction