Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysis of Mathematical Literacy in Solving PISA Problems based on Students' mathematical Ability

The purpose of this study was to analyze mathematical literacy skills in solving PISA problems in terms of students' abilities. This research is a qualitative research. The research subjects included 3 grade VIII students of SMP Negeri 5 Kendari. Determination of subjects based on the results of the initial test, then grouped and assigned one subject each from the high, medium and low ability groups. Data collection techniques used include initial tests, mathematical literacy tests and interviews. Data analysis includes data reduction, data presentation and conclusion drawing. The results showed that the mathematical literacy skills of high-ability subjects and moderate-ability subjects were able to write down all facts and formulate problems with appropriate verbal descriptions, use appropriate strategies at the completion stage and carry out certain rules or formula calculations and write and verbally describe an illustration. through the relationships of the facts that exist to draw a conclusion correctly. While the subject of low ability, unable to write down the facts completely and not correctly formulating the problem, unable to choose the right strategy to solve problems and carry out calculations both in writing and verbally, and unable to make conclusions.
Cognitive Analyses for Interface Design Using Dual N-Back Tasks for Mental Workload (MWL) Evaluation

In the manufacturing environments of today, human–machine systems are constituted with complex and advanced technology, which demands workers’ considerable mental workload. This work aims to design and evaluate a Graphical User Interface developed to induce mental workload based on Dual N-Back tasks for further analysis of human performance. This study’s contribution lies in developing proper cognitive analyses of the graphical user interface, identifying human error when the Dual N-Back tasks are presented in an interface, and seeking better user–system interaction. Hierarchical task analysis and the Task Analysis Method for Error Identification were used for the cognitive analysis. Ten subjects participated voluntarily in the study, answering the NASA-TLX questionnaire at the end of the task. The NASA-TLX results determined the subjective participants’ mental workload proving that the subjects were induced to different levels of mental workload (Low, Medium, and High) based on the ANOVA statistical results using the mean scores obtained and cognitive analysis identified redesign opportunities for graphical user interface improvement.
Boundary Layer Development in Axial Compressors and Turbines: Part 3 of 4— LP Turbines

This is Part Three of a four-part paper. It begins with Section 11.0 and continues to describe the comprehensive experiments and computational analyses that have led to a detailed picture of boundary layer development on airfoil surfaces in multistage turbomachinery. In this part, we present the experimental evidence that we used to construct the composite picture for LP turbines that was given in the discussion in Section 5.0 of Part 1. We present and interpret the data from the surface hot-film gages and the boundary layer surveys for the baseline operating condition. We then show how this picture changes with variations in Reynolds number, airfoil loading, and nozzle-nozzle clocking.
Association between Migraine and Workplace Social Support in the Social Context of China: Using a Validated Chinese Version of the DCSQ

Background: Workplace social support might have a protective function against migraine in the social context of China, as close co-worker relationships and collectivism are acknowledged as work values in Chinese society. Objectives: This paper aimed to analyse the association between migraine and workplace social support. The validity and reliability of the Chinese version of the Support scale of the Demand-Control-Support Questionnaire (DCSQ) used were also determined. Methods: Following international guidelines, this study was carried out in two stages. Stage I involved translations and pilot testing to assess content and face validity of the Chinese version of the DCSQ Support scale. Stage II was a cross-sectional survey (N = 677 bank employees) to evaluate structural validity, internal consistency and test-retest reliability of the Support scale, as well as to examine the association between workplace social support and a migraine-positive diagnosis. Results: A high level of social support in the workplace was associated with a 74% decreased likelihood of migraine (adjusted OR = 0.26, 95%CI: 0.14–0.46). Of the six aspects of workplace social support, co-worker support had the greatest protective effect (adjusted OR = 0.49, 95% CI: 0.39–0.60). The Chinese version of the DCSQ Support scale established satisfactory content and face validity (I-CVIs ≥ 0.78; S-CVIAVE ≥ 0.90). Confirmatory factor analysis verified its one-dimensional theoretical factor, with adequate internal consistency (Cronbach’s α 0.98; item-total correlations ≥ 0.80) and test-retest reliability (weighted Kappa coefficients 0.81–0.87; percentages agreement 85.23–88.92%). Conclusions: In the Chinese social context, workplace social support could protect against migraine, with the strongest benefit coming from co-workers. This study also provides a Chinese-language DCSQ Support scale as a valid and reliable instrument for measuring workplace social support.
Attitudes about refugees and immigrants arriving in the United States: a conjoint experiment

ABSTRACT From 2013 to 2018, the global refugee population increased by about 50 per cent. Although public opinion toward refugees plays a key role in shaping related policies, scholarly research on this topic remains limited. Using original data from a nationally representative conjoint survey experiment conducted in 2019, we examine whether US citizens’ attitudes toward refugees are distinct from their attitudes toward other types of immigrants to the US, and how applicant attributes shape American citizens’ preferences about admission of foreigners. We find that immigrant and refugee reasons (as defined by law) for migrating to the US affect attitudes, with refugee reasons garnering greater support. The labels “immigrant” and “refugee” on their own have smaller effects, in general, but can be salient in combination with other characteristics. We also find marked effects of newcomers’ characteristics, especially country of origin, profession, gender and religion.
Exploring the universal nature of electrical percolation exponents by genetic algorithm fitting with general effective medium theory

This paper considers the nature of the electromagnetic response of percolating conductor–insulator composites in the critical region near the percolation threshold. It is demonstrated how the filler fraction and frequency dependence of the complex permittivity for these composites can be matched to McLachlan's general effective medium theory using a genetic algorithm fitting process to obtain values for the percolation threshold, percolation exponents, s and t, and the filler particle conductivity. Good estimates of these parameters can be obtained from broadband permittivity spectra of, as few as, two composite formulations. The use of genetic algorithm techniques enables the uniqueness of the fit parameters to be considered, as the genetic algorithm method is robust in terms of finding globally optimum solutions. It was hypothesized that non-universal exponents could be offset by ambiguity in the filler conductivity. For example, contact resistance effects could reduce filler conductivities below their bulk values. The genetic algorithm technique employed is described and it is demonstrated that the best fit values for fit parameters are unique. Thus, confidence can be placed in non-universal values of the percolation exponents.
Well-Log Information-Assisted High-Resolution Waveform Inversion Based on Deep Learning

The high-resolution waveform inversion for seismic velocities is gaining increasing interest as we start to deal with complex structures. Although full waveform inversion (FWI) has been used for several years, obtaining high-resolution velocity models still presents many obstacles, such as the high computational cost and the limited bandwidth of the data. Thus, we propose a deep learning (DL)-based algorithm to build high-resolution velocity models using low-resolution velocity models, migration images, and well-log velocities as inputs. The well information, specifically, helps enhance the resolution with ground-truth information, especially around the well. These three inputs are fed to an improved neural network, a variant of U-Net, as three channels to predict the corresponding true velocity models, which serve as labels in the training. The incorporation of well velocities from several locations is crucial for improving the resolution of the output model. Numerical experiments on complex models demonstrate the robust performance of this network and the crucial role that well information plays, especially in generalizing the approach to models that differ from the trained ones and achieving superior performance compared with FWI.
Constraining Type Ia Supernova Progenitors

Abstract We present observational and theoretical studies constraining Type Ia supernova progenitors. First, we use a new observational technique to show that “prompt” SNe Ia that trace star-formation on cosmic timescales exhibit a significant delay time of 200-500 million years. This implies that either the majority of SNe Ia companion stars have main-sequence masses less than three solar masses, or that most SNe Ia arise from double-white dwarf binaries. Second we present a comprehensive study of white dwarf collisions as an avenue for creating SNe Ia. Using a smooth particle hydrodynamics code with a 13-isotope nuclear network, we show that several combinations of white dwarf masses and impact parameters produce enough 56Ni to result in luminosities ranging from those of sub-luminous to super-luminous SNe Ia, depending on the parameters of the collision. Finally, we conduct a simulation survey of double-degenerate white dwarf mergers with varying mass combinations. Unlike previous works, we do not add detonations by hand to our simulations, and we do not find any thermonuclear explosions during the mergers. Instead, all but one of our simulations forms a cold, degenerate core surrounded by a hot disk, while our least massive pair of stars forms only a hot disk. We characterize the remnants by core mass, rotational velocity, and half-mass radius, and discuss how we will evolve them further with simulations that incorporate dissipative processes. Such simulations may indeed lead to double-degenerate Type Ia explosions that occur many orbits after the mergers themselves.
Prediction of the Diurnal Variation of Summertime Precipitation Over the Sichuan Basin by a Regional Model

The nocturnal precipitation over the Sichuan Basin (SCB) exhibits obvious spatial variation, most of the existing numerical research of precipitation event over the SCB is based on case studies. In this study, the long‐term climatological evaluation of the prediction of diurnal spatio‐temporal evolution of precipitation and relevant physical mechanism over the SCB by 9 and 3 km operational numerical weather prediction model is carried out. It is found that the SWC‐WARMS model with 9 km grid spacing overestimates the summer precipitation, especially over the western slopes of the SCB. The northeastward timing delay of the precipitation peak over the SCB is well reproduced in the model, with predicted precipitation peaking at midnight over the southwestern SCB and in the early morning over the northeastern SCB. However, the predicted diurnal peak of precipitation appears 2–3 hr earlier than the observed peak. Increasing horizontal resolution to 3 km reduces the wet bias and improves the diurnal phase of precipitation. Compared to reanalysis, the predicted easterly anomalous wind appears earlier and the anomalous wind speed is stronger. Moreover, the predicted atmosphere is too unstable, which is associated with “warm below and cold above” vertical biases in temperature and wet biases in specific humidity. Thus, model precipitation peaks too early in the day over the SCB, and is overestimated. The weakening of the predicted southwesterly flow in the middle troposphere weakens the northeastward propagation of precipitation after midnight over the SCB. The most significant improvements are found for the diurnal variation of low‐level anomalous wind speed in the 3 km resolution model, contributing to a more realistic representation of precipitation over the SCB.
A HYBRID PSO-SA OPTIMIZING APPROACH FOR SVM MODELS IN CLASSIFICATION

Support vector machine (SVM) is a widely used tool in the field of image processing and pattern recognition. However, the parameters selection of SVMs is a dilemma in disease identification and clinical diagnosis. This paper proposed an improved parameter optimization method based on traditional particle swarm optimization (PSO) algorithm by changing the fitness function in the traditional evolution process of SVMs. Then, this PSO method was combined with simulated annealing global searching algorithm to avoid local convergence that traditional PSO algorithms usually run into. And this method has achieved better results which reflected in the receiver-operating characteristic curves in medical images classification and has gained considerable identification accuracy in clinical disease detection.
Positron sound waves and nonlinear Landau damping of intense transverse EM waves in an isotropic EPI plasma

Abstract Relativistically hot electron–positron–ion (EPI) plasmas in the presence of relativistic intense electromagnetic (EM) radiation that are not in thermal equilibrium are studied by following a modified plasma particle distribution function. By means of a kinetic description, soliton solution is obtained for a small amplitude EM wave, whereas for large amplitude EM waves a cusp soliton solution is obtained. A general expression of positron density oscillations is obtained for long wavelength in comparison with the Debye length of electrons, and is discussed for special cases. Dispersion relations for a new type of longitudinal waves with slow damping is formulated as a consequence of resonant wave–particle interaction, and the necessary conditions for the existence of positron sound waves are obtained. Furthermore, for ultrarelativistic electrons and non-relativistic positrons, quasi positron sound waves dispersion relation in the intermediate wave range is obtained. It is shown that the modulation of amplitude of relativistic EM waves leads to instability for the rare plasma. Finally, we have obtained the relativistic kinetic nonlinear Schrödinger equation (KNLS) with local and non-local nonlinearities. The KNLS equation depicts nonlinear Landau damping rates for intense EM waves, and these damping rates are also examined.
AN EMPIRICAL INVESTIGATION OF ONE VARIABLE SECTION PRE‐EQUATING1

Section Pre-Equating (SPE) is a method used to equate test forms that consist of multiple separately-timed sections. The unique contribution of SPE is that it does not require examinees to take two complete forms of the test. Instead, all of the old form and one or two sections of the new form are administered to each examinee. Missing data techniques are employed to estimate the necessary equating parameters. When a test has two variable sections, the estimation is fairly straightforward. When a test includes only one variable section, there is no simple way to obtain an estimate of the correlation between pairs of sections from the new test because no one group takes a pair of sections. This study was designed to utilize empirical data to evaluate several methods for obtaining reasonable values for these correlations. The methods for obtaining correlations that are evaluated are borrowing correlations from another population who have taken the same test at a different administration, borrowing correlations from another parallel test taken by the same population, and imputing the unknown partial correlations. This study explored the effect on equating of using each of these methods. The criterion for evaluating the one-variable-section test equatings was the equating obtained using a two variable section model. Comparison of the converted scores obtained using the three different methods for estimating correlations under a one-variable-section test model were consistent with one another. Results from this study also demonstrated that equating results obtained from a one-variable-section test model were very consistent with those obtained from a two-variable-section test model.
Carbapenemase-Producing Klebsiella pneumoniae in COVID-19 Intensive Care Patients: Identification of IncL-VIM-1 Plasmid in Previously Non-Predominant Sequence Types

During the COVID-19 pandemic, intensive care units (ICUs) operated at or above capacity, and the number of ICU patients coinfected by nosocomial microorganisms increased. Here, we characterize the population structure and resistance mechanisms of carbapenemase-producing Klebsiella pneumoniae (CP-Kpn) from COVID-19 ICU patients and compare them to pre-pandemic populations of CP-Kpn. We analyzed 84 CP-Kpn isolates obtained during the pandemic and 74 CP-Kpn isolates obtained during the pre-pandemic period (2019) by whole genome sequencing, core genome multilocus sequence typing, plasmid reconstruction, and antibiotic susceptibility tests. More CP-Kpn COVID-19 isolates produced OXA-48 (60/84, 71.4%) and VIM-1 (18/84, 21.4%) than KPC (8/84, 9.5%). Fewer pre-pandemic CP-Kpn isolates produced VIM-1 (7/74, 9.5%). Cefiderocol (97.3–100%) and plazomicin (97.5–100%) had the highest antibiotic activity against pandemic and pre-pandemic isolates. Sequence type 307 (ST307) was the most widely distributed ST in both groups. VIM-1-producing isolates belonging to ST307, ST17, ST321 and ST485, (STs infrequently associated to VIM-1) were detected during the COVID-19 period. Class 1 integron Int1-blaVIM-1-aac(6′)-1b-dfrB1-aadAI-catB2-qacEΔ1/sul1, found on an IncL plasmid of approximately 70,000 bp, carried blaVIM-1 in ST307, ST17, ST485, and ST321 isolates. Thus, CP-Kpn populations from pandemic and pre-pandemic periods have similarities. However, VIM-1 isolates associated with atypical STs increased during the pandemic, which warrants additional monitoring and surveillance.
Final report on the supplementary comparison EURAMET.EM-S26: inductance measurements of 100 mH at 1 kHz (EURAMET project 816)

Within the framework of EURAMET, a comparison has been organized of measurements of self-inductance at 100 mH and 1 kHz. The comparison is identified as EUROMET.EM-S26. Two 100 mH inductance standards, encased in a thermostatic controlled enclosure, were circulated among the participants. The results from 10 out of 16 participants are in agreement with the reference values. A majority of the results agrees within ±50 µH/H. The participants reported four different methods to realize the traceability of the unit of inductance. The results from these different methods are in good agreement within the reported uncertainties. The results of this comparison have been linked to the results of the comparison EUROMET.EM-S20. The organization of this comparison has been a successful exercise of sharing the workload among four different institutes and can be an example to future comparisons. Main text. To reach the main text of this paper, click on Final Report. Note that this text is that which appears in Appendix B of the BIPM key comparison database kcdb.bipm. org/. The final report has been peer-reviewed and approved for publication by EUROMET, according to the provisions of the CIPM Mutual Recognition Arrangement (MRA).
FAKTOR-FAKTOR YANG MEMPENGARUHI KEPATUHAN WAJIB PAJAK DENGAN PREFERENSI RISIKO SEBAGAI VARIABEL MODERASI

Abstract - The tax target from the government has never been achieved, previous research has shown inconsistencies between researchers, and the economic sector has declined due to the COVID-19 pandemic. Whether the current state of the COVID-19 pandemic will produce consistent or inconsistent results if research is carried out on compliance with fulfilling obligations in paying taxes. The purpose of this study is to obtain empirical evidence regarding the effect of understanding tax regulations, tax sanctions, and service of tax officials on taxpayer compliance with risk preference as a moderating variable. This study used 104 samples through simple random sampling method. The data used is primary data in the form of questionnaires distributed to individual taxpayers in Jakarta. Data processing in this study using the Smart Pls3 program. The results showed that prior to moderating the understanding of tax regulations and services of tax officials had an effect on taxpayer compliance, while tax sanctions had no effect on taxpayer compliance. After moderating with the risk preference variable statistically resulted in the understanding of tax regulations, the service of the tax authorities strengthened even though it had very little effect on taxpayer compliance. Meanwhile, the tax sanctions variable could not predict positively on taxpayer compliance, meaning that the risk preference variable was not statistically proven to be able to moderate . From the empirical results above, it shows that the Directorate General of Taxes should focus more on providing education, socialization in an effort to increase the understanding of taxpayers so that awareness arises in paying taxes and participating in mutual cooperation in building the Indonesian nation to achieve mutual prosperity. Keywords: Risk Preference; Taxpayer Compliance; Tax Sanctions; Tax Service Officers; Understanding of Tax Regulations
Effects of spatial confinement and layer disorder in photoluminescence of GaAs1−xBix/GaAs heterostructures

The structural and optical properties of a set of high-quality GaAs1−xBix/GaAs quantum well (QW) heterostructures with Bi concentrations ranging from 3.5% to 6.7% are studied. The energies of the excitonic ground state transitions are determined as a function of Bi concentration and spatial confinement. The influence of material disorder on the optical properties of QWs is investigated. It is determined that trap-related luminescence responds differently to temperature changes depending on whether the Bi concentration is more or less than 5%. Below 5% it contributes significantly to the overall photoluminescence line shape whereas above 5%, it is insignificant.
Sparse scatterers imaging through approximated multitask compressive sensing strategies

In the framework of the multitask Bayesian compressive sensing (BCS) paradigm, two innovative approaches for the solution of coherent imaging problems are proposed within the first‐order Born approximation and the Rytov approximation.Selected numerical results are reported to compare the proposed techniques with state‐of‐the‐art BCS approaches as well as global optimization‐based methods. © 2013 Wiley Periodicals, Inc. Microwave Opt Technol Lett 55:1553–1558, 2013; View this article online at wileyonlinelibrary.com. DOI 10.1002/mop.27612