Miracle-dz/UniFAR-FTUs huggingface dataset:
Exploring Reading Engagement in English as an International Language (EIL) Materials

The popularity of English as an International Language has been rapidly growing, contributing EIL materials to have become more widespread in learning. This study discusses students’ reading engagement and their perception of EIL materials, which aims to (1) investigate students’ engagement in reading EIL materials, (2) explore student perception of EIL materials, and (3) explore the relationship between students’ level of reading engagement and their perception of EIL materials. 113 undergraduate students at one private college who use English as a medium for their instruction were participated in this study. A mixed-method study which Reading Engagement Questionnaire and EIL Perception Questionnaire were adopted and constructed to explore the findings and an interview protocol was designed to triangulate with the questionnaires’ findings. The study revealed that students engaged in reading EIL materials in a neutral level and perceived EIL materials positively. Students possessed all four constructs of reading engagement in EIL materials: competence-related beliefs, task values, behavioral engagement in reading texts, and engaged readers. Furthermore, students perceived positively with four principles of EIL: current status of English, varieties of English, strategies for multilingual/multicultural communication and English reader’s identities. Interestingly, there was a positive relationship between students’ reading engagement and their perception of EIL materials.
Approximate predictive likelihood

SUMMARY A predictive likelihood is given which approximates both Bayes and maximum likeli- hood predictive inference by expansion of a posterior likelihood. This synthesizes and extends previous results and is widely applicable. The approximation usually differs from exact Bayes posterior predictive density by Op(n-2), and from exact predictive likelihood by Op(n-1), but does not depend on the availability of prior information and is applicable when exact predictive likelihood cannot be found. The results are applied to the prediction Various treatments of the likelihood function form the basis of parametric inference, but until recently few non-Bayesian attempts have been made to define versions of it suitable for prediction. However Lauritzen (1974), Hinkley (1979), and more recently Butler (1986) have proposed rather similar definitions of predictive likelihood based on the idea of conditioning on the value of a sufficient statistic. Unfortunately they apply only when sufficiency provides a genuine reduction of the data. Moreover, even if for a given problem an exact predictive likelihood exists, the calculations needed to derive it can be onerous. This paper provides approximations to Hinkley-Lauritzen predictive likelihood accur- ate to Op(n-1) in many cases, which are applicable in situations where maximum likelihood estimation is regular. They also apply to problems which admit no exact predictive likelihood because sufficiency provides no real reduction of the data. The approximations are derived from a posterior predictive density and may if prior informa- tion is available be regarded as Bayesian procedures. Their construction requires only the repeated maximization of a likelihood and evaluation of the observed information matrix at the maximum, and is fast and accurate using usual numerical maximization methods. There is a close connexion with the approximations to posterior moments and marginal densities given by Tierney & Kadane (1986), who suggest the same approxima- tion as used here but give no detailed results for prediction. Section 2 of this paper shows how Laplace's method for integrals may be applied to a posterior predictive density to yield approximate predictive likelihood. Section 3 discusses a connection with conditional inference: essentially the same approximation
Methods for determining the CO2 removal capacity of enhanced weathering in agronomic settings

Recent analysis by the IPCC suggests that, across an array of scenarios, both GHG emissions reductions and various degrees of carbon removal will be required to achieve climate stabilization at a level that avoids the most dangerous climate changes in the future. Among a large number of options in the realm of natural climate solutions, atmospheric carbon dioxide removal (CDR) via enhanced silicate weathering (EW) in global working lands could, in theory, achieve billions of tons of CO2 removal each year. Despite such potential, however, scientific verification and field testing of this technology are still in need of significant advancement. Increasing the number of EW field trials can be aided by formal presentation of effective study designs and methodological approaches to quantifying CO2 removal. In particular, EW studies in working lands require interdisciplinary “convergence” research that links low temperature geochemistry and agronomy. Here, drawing on geologic and agronomic literature, as well as demonstration-scale research on quantifying EW, we provide an overview of (1) existing literature on EW experimentation as a CO2 removal technique, (2) agronomic and geologic approaches to studying EW in field settings, (3) the scientific bases and tradeoffs behind various techniques for quantifying CO2 removal and other relevant methodologies, and (4) the attributes of effective stakeholder engagement for translating scientific research in action. In doing so, we provide a guide for establishing interdisciplinary EW field trials, thereby advancing the verification of atmospheric CO2 in working lands through the convergence of geochemistry and agronomy.
Modelling the Accuracy Rates of Spatial Relational Reasoning Problems: An Analysis Facilitating ACT-R and PRISM Theory

Relational reasoning involves evaluating relations between representations. Spatial relational reasoning problems have long been used in psychology to study deductive inference abilities. Research incorporating such tasks has resulted in findings of a variety of effects and reasons as to why some problems are more difficult than others. Computational accounts of the relational reasoning of spatial information offer valuable insights, such as how individuals may construct a mental model to infer conclusions and why some cognitive strategies might be preferred over others. However, many of these accounts either fail to incorporate or remain general to the impact of other factors affecting the difficulty of these reasoning problems, such as the effects of working memory errors. This thesis aims to investigate how the different types of memory errors of omission and commission may be computationally modelled to provide a theoretically unifying account of qualitatively different cognitive reasoning processes and quantitatively different accuracy rates on experimental measurements of spatial relational reasoning problems. Our models demonstrate that modelling memory errors of omission and commission in Python ACT-R based on PRISM theory produces a similar negative relationship of a decrease in accuracy rates with each increase of premise and dimensionality complexity per question as found in the relational reasoning experimental literature. Our results highlight the need for future modelling to consider individual differences in participant micro-strategy preferences, how reasoning processes may be affected by different memory errors, and how future measures may be constructed to better address raised concerns. MODELLING ACCURACY RATES OF SPATIAL RELATIONAL REASONING 3
Changes in Physical Activity and Health Indicators among Koreans during the COVID-19 Pandemic: Comparison between 2019 and 2020

This study aimed to compare the changes in physical activity (PA), chronic disease, and mental health indicators of Koreans before and after the COVID-19 outbreak, using raw data from more than 400,000 representative samples from the 2019–2020 Community Health Survey by the Korea Centers for Disease Control and Prevention, and to explore the correlations among them. We used two-way ANOVA to analyze changes and differences in PA and obesity levels. We assessed the influence of gender and recurrent PA using chi-square tests for mental health status and chronic disease. Finally, we performed a correlation analysis to determine the relationships among PA days, mental health, and chronic disease. The results showed that, compared to the levels before the COVID-19 period, moderate-intensity (Days: 1.415~1.217; Time: 114.688~107.321) and high-intensity (Days: 0.798~0.671; Time: 112.866~106.110) PA significantly decreased in Koreans during the COVID-19 period, while low-intensity (Time: 60.305~61.735) PA increased. Before and during the COVID-19 period, men (18,436 (8.1%)~16,124 (7.0%)) performed PA more regularly than women (13,207 (5.8%)~9382 (4.1%)). Compared to the number of regular PA participants before the COVID-19 period, regular PA participants (male, female) decreased from 31,643 (13.8%) to 25,506 (11.1%) during the COVID-19 period. Compared with the levels before the COVID-19 period, the experience rates of stress (3.1%~2.6%), depression (0.8%~0.6%), HBP (3.0%~2.2%), and diabetes (1.2%~0.9%) significantly changed under different levels of conventional PA intervention. In addition, the obesity rate during the COVID-19 period (23.957) was higher than it was before COVID-19 (23.477). During the COVID-19 period, the PA of Koreans was greatly restricted, but low-intensity PA was maintained and increased. PA is an effective activity for maintaining mental health and for preventing and reducing chronic diseases. Recommendations for appropriate intensity or a combination of high-, moderate-, and low-intensity PA should be based on the health status of Koreans to help them maintain mental health and to reduce the risk of chronic diseases during COVID-19 social distancing.
Does the Chronic Stress of Everyday Discrimination or Race Itself Better Predict AD Onset Risk?

Using evidence from the Health and Retirement Study, we explore racial disparities in Alzheimer’s Disease (AD) onset risk. From a stress process perspective, there is substantial evidence in the literature that everyday discrimination is a chronic strain for Black individuals that acts as a social determinant of illness. However, few studies have examined specific relationships between this social stressor, race, and AD onset risk. Using Cox Proportional Hazard Models, we examined racial differences in exposure and vulnerability to everyday discrimination. Findings suggest that everyday discrimination predicts AD onset risk, and Black individuals experience more frequent exposure to everyday discrimination as a chronic strain. However, contrary to the stress process model, Black respondents were not more vulnerable to the effect of everyday discrimination on AD onset risk. Racial bias from medical professionals during the diagnostic process and mortality selection bias may explain this effect. Overall, the results of this study provide further evidence that discrimination is a key factor in predicting AD while also considering that many racial minorities with high rates of this type of social stress may not receive an unbiased diagnosis and/or survive to late life to develop AD.
A Two-Dimensional Numerical Investigation of the interaction between Sea Breezes and Deep Convection over the Florida Peninsula

Abstract Deep convection initiated by sea breezes over the Florida peninsula is simulated using a two-dimensional nonhydrostatic model. Reasonable agreement is obtained between model results and observations for the three types of undisturbed days classified by Blanchard and Lopez. The convergence of the east and west coast sea breezes is the primary control on the timing and location of rapid convective development, and this is mainly determined by the low-level winds. The simulated convection is spatially concentrated and does not produce an extensive stratiform region. Sensitivity tests are performed for a variety of wind and thermodynamic profiles, and for different soil moisture contents. During the early stages of these simulations, small convective cells develop in between the sea-breeze fronts. As the outer cells at the sea-breeze fronts deepen these smaller cells are suppressed. Typically, during the midafternoon a new cell explosively develops in between the sea-breeze fronts and the outer cells.
Electron beam formation by small‐scale oblique inertial Alfvén waves

Particle-in-cell simulations reveal characteristics of small-scale nearly perpendicular nonlinear inertial Alfven waves in the electrostatic limit, during wave steepening and electron beam generation. These electrostatic inertial Alfven waves (ESIAW) propagate with only weak electron Landau damping for T i /T e >>1. Nonlinear amplitude initial conditions convectively steepen and evolve higher wavenumber structures similar in morphology and magnitude to previous results from a fluid-kinetic model. Shorter wavelength acoustic waves emergent during steepened ESIAW wave evolution are found to be instrumental in exciting cold electron beams possessing kinetic energies a few hundred times that of the thermal electron population. This mechanism is one possible explanation for suprathermal electron bursts observed in and near auroral inverted-V events.
Effects of radiative heat transfer on the structure of turbulent supersonic channel flow

The interaction between turbulence in a minimal supersonic channel and radiative heat transfer is studied using large-eddy simulation. The working fluid is pure water vapour with temperature-dependent specific heats and molecular transport coefficients. Its line spectra properties are represented with a statistical narrow-band correlated-k model. A grey gas model is also tested. The parallel no-slip channel walls are treated as black surfaces concerning thermal radiation and are kept at a constant temperature of 1000 K. Simulations have been performed for different optical thicknesses (based on the Planck mean absorption coefficient) and different Mach numbers. Results for the mean flow variables, Reynolds stresses and certain terms of their transport equations indicate that thermal radiation effects counteract compressibility (Mach number) effects. An analysis of the total energy balance reveals the importance of radiative heat transfer, compared to the turbulent and mean molecular heat transport.
Evaluation of Particle Yields in 30 GeV Proton-Carbon Inelastic Interactions for Estimating the T2K Neutrino Flux

The NA61/SHINE (SPS Heavy Ion and Neutrino Experiment) experiment at the CERN SPS combines a rich physics program in various fields. One of its main purposes is to perform hadron production measurements in proton–carbon interactions targeted for an accurate neutrino flux prediction of the T2K experiment in Japan. T2K is a long baseline neutrino oscillation experiment at J-PARC, Japan, with the aim to precisely measure the νμ → νe appearance and νμ disappearance. To generate neutrinos, a high intensity 30 GeV proton beam impinging on a 90 cm long carbon target is used, whereby hadrons (π, K, etc) are produced, which decay into neutrinos (νμ,e). The neutrino flux is then measured 2.5 off-axis, both, in a near detector, located 280 m behind the target, and in the 295 km far away Super-Kamiokande detector (SK). Neutrino oscillations can be probed by comparing the neutrino flux measured at SK to the one predicted at SK. In order to predict the flux at SK one uses the near detector measurements and extrapolates them with the help of Monte Carlo (MC) predictions to SK. Up to now, these MC predictions depend on hadron production models of deficient predictive power. For more precise predictions, measurements of the hadron production off the carbon target are essential to tune the available MC codes. The aim of the NA61/SHINE measurements for T2K is to provide these hadro-production measurements. The NA61 detector is a large acceptance hadron spectrometer at the CERN SPS. Its main components represent four large volume time projection chambers (TPCs), which provide high momentum resolution and good particle identification (PID) via specific energy loss measurements. The PID capability of the TPCs is complemented through time-of-flight measurements of various detector arrays. Two carbon targets of different lengths are used, a 2 cm long target, the so called thin target, and a 90 cm long T2K replica target. The latter allows to study the full particle yield in the T2K target, including primary as well as higher order interactions, while the thin target allows to evaluate the primary particle production in proton–carbon collisions without distortions due to target reinteractions. The proton–carbon cross section measurements are not only important for determining the direct contribution–the largest one–to the neutrino flux in T2K, but are of great interest on their own right. During the pilot run in October 2007 approximately 660k events with the thin target and 230k events with the T2K replica target were registered with a 30 GeV proton beam. Upon successful completion of the test run, efforts were joined for the calibration and analysis of the thin target data to extract first results on the inclusive particle cross sections and the mean
Non‐linear analysis of stiffened plates using super elements

A new numerical technique for large deflection elasto-plastic analysis of stiffened plates is presented. The method uses super finite elements which are macro elements having analytical as well as the usual finite element shape functions, specially designed so that only one plate element per bay and one beam element per span are needed. The large deflection theory by von Karman and the von Mises yield criterion and associated flow rule are employed. The governing equations are derived using the principle of virtual work, integrated numerically using Gauss quadrature and solved by Newton–Raphson iteration. Numerical solutions are presented for simple beams and plates, and plates stiffened in one or two mutually perpendicular directions. Good approximations are obtained with only one-element representations of each plate bay or beam span with significant savings in computing time, costs and storage requirements as compared with using regular finite elements.
Primitive-chain Brownian simulations of entangled rubbers

We present a new multi-chain Brownian dynamics simulation of a polymeric network containing both crosslinks and slip-links (entanglements). We coarse-grain at the level of chain segments connecting consecutive nodes (cross- or slip-links). Affine displacement of nodes is not imposed; rather, their displacement as well as sliding of monomers through slip-links is governed by force balances. The stress-strain response in uniaxial extension is compared with the slip-link theories of Ball et al. (Polymer, 22 (1981) 1010) and Edwards and Vilgis (Polymer, 27 (1986) 483), and with the molecular-dynamics simulations of Grest et al. (J. Non-Cryst. Solids, 274 (2000) 139). Qualitative agreement both with the Mooney-Rivlin expression and with the stress upturn at large strains confirms the role of entanglements in explaining departure from the classical theory of phantom chain networks. However, quantitative agreement with data is satisfactory at low strains only, and the observed discrepancy at larger strains suggests possible refinements of the model. Additivity of free energy contributions of crosslinks and entanglements used in several molecular theories of rubber elasticity is confirmed by the simulation results.
Yield potentials of improved rice varieties for increased lowland rice production within the mankran watershed in Ghana

ABSTRACT Rice production in Ghana is limited by low varietal choices, which puts farmers at a disadvantage in meeting the market demand for consumers. The objectives of this study were to (i) assess the yield potentials of improved rice varieties developed by the Africa Rice Center (AfricaRice), and (ii) to allow farmers to select improved varieties of their choice based on growth and yield, as observed in the field, in order to ensure a high adoption rate, increase productivity and food security. Two seasons (i.e. 2020 major and 2020–2021 minor) field experiments were conducted at two lowland within the Mankran watershed in the Ashanti region of Ghana. The experiment comprised thirteen (13) improved varieties and two local checks and was conducted using recommended good agronomic practices. The key findings of the study showed that growth and yield parameters vary significantly between varieties across locations. The biplot analysis showed that varieties FARO 66, SAHEL 317, and Amankwatia are the best in the major season while WITA 9, GT 11, ARS-957-BGJ-171-15-D-B, NERICA L36, and AGRA were the best in the minor season at both locations. Farmers’ preference for the varieties was based not only on growth and yield but on resistance to lodging, pests, and diseases. In conclusion, the best performing varieties have demonstrated yield potential which is about 92% higher than the yield of the local checks and can be recommended for adoption by farmers. Future breeding programs on these varieties should include the most preferred attributes by farmers in this study. GRAPHICAL ABSTRACT
Entropy and Potential Temperature

Abstract The theoretical investigations presented in this paper show that the various definitions of potential temperatures, such as the potential temperature of dry air and of moist air, the equivalent potential temperature, the liquid water potential temperature, the ice-liquid water potential temperature and the wet equivalent potential temperature can be unified by one single definition. This general potential temperature is named the entropy temperature as it is a measure of entropy. The entropy state function for a system of cloudy air and the entropy budget are presented and discussed. For each of the potential temperatures the respective thermodynamic equation for which the potential temperature is an integral of the form, θ = constant, is reviewed on the basis of the entropy concept. As one result, it is found that the ice-liquid water potential temperature θil is only an integral of the corresponding thermodynamic equation if saturation or chemical equilibrium between water vapor and liquid wate.
Selectively coated photonic crystal fiber for highly sensitive fluorescence detection

The authors investigate the potential of hollow core photonic crystal fibers (HCPCFs) for highly sensitive fluorescence detection by selectively coating the central hole of a HCPCF with fluorophores. After studying the influence of reabsorption and intermolecular effects on the emission, they show that dye concentrations down to 10−9M can be detected using only nanoliter sample volumes. The results indicate that HCPCF are well suited for sensing applications involving internal emission or scattering processes, such as fluorescence based gas sensing or surface-enhanced Raman scattering, and may be integrated into compact optical devices.
The effect of gravity on the meniscus accumulation phenomenon in a tube

It is well known that when a suspension of noncolloidal, neutrally buoyant rigid particles is drawn into an empty tube, the inward shear-induced migration of the particles results in a continuously growing packed layer of particles at the advancing meniscus. For non-neutrally buoyant suspensions, however, gravity perpendicular to the flow direction modifies the fully developed concentration profile and can lead to depletion of particles at the meniscus. This accumulation/depletion phenomenon was studied experimentally as a function of the buoyancy number Nb, the ratio of gravitational to viscous forces. The rate of accumulation or depletion was used to determine the area average concentration as a function of Nb and the feed concentration. These results are in good agreement with the profiles calculated theoretically using the suspension balance model of Nott and Brady [J. Fluid Mech. 275, 157 (1994)] coupled with the anisotropic constitutive equations of Zarraga et al. [J. Rheol. 44, 185 (2000)].