Miracle-dz/UniFAR-FTUs huggingface dataset:
The Impact of Problem-Based Learning Electronics Module Integrated with STEM on Students' Critical Thinking Skills

: One of the goals of learning physics is to help students develop their critical thinking skills. Preliminary studies conducted at SMAN 1 Pacitan show that the learning process is still teacher-centered with the lecture method and providing practice questions. Such a learning process causes the development of student's critical thinking skills to be less well-stimulated. Using e-modules in physics learning is expected to be a new solution to stimulate students' critical thinking skills. This research aims to determine the impact of Problem-Based learning physics electronic module integrated with STEM on students' critical thinking skills. The research method uses a quasi-experimental technique with a one-group pretest-posttest design. Data analysis used the N-gain test to determine the increase in students' critical thinking skills and the t-test to determine the effect of problem-based learning electronic module integrated with STEM on students' critical thinking skills. The sample was selected using a purposive sampling strategy. The samples involved were 34 students of class XI MIPA Senior High School Pacitan. The test was conducted to collect data on students' critical thinking skills. Research data was collected using an essay test of critical thinking skills totaling twelve valid questions with a reliability coefficient 0.70. Before the N-gain test was carried out, the normality, homogeneity, and t-test were first carried out. In the normality test, the data is normally distributed. In the homogeneity test, the data is homogeneous. Based on the paired sample t-test, it shows that there is a significant difference between pretest and posttest critical thinking skills with a sig. (2-tailed) <0.05, which indicates that the problem-based learning electronic module integrated with STEM has a positive effect on students' critical thinking skills. By acquiring an N-Gain score of 0.76 in the high category, the PBL physics electronic module integrated with STEM on mechanical wave characteristics material can improve students' critical thinking skills.
Bistatic 3D Electromagnetic Scattering from a Right-angle Dihedral at Arbitrary Orientation and Position

A method is created to extend a bistatic 3D electromagnetic scattering solution for a dihedral at a given orientation and position to the case of arbitrary orientation and position. Results produced using this method are compared to shooting and bouncing rays (SBR) and method of moments (MoM) predictions, as well as measured data for applicable cases. The model in this thesis shows excellent agreement in magnitude and phase with SBR predictions. It also shows good agreement in magnitude with MoM predictions. Small phase differences between model and MoM data occur due to differences in the underlying scattering solution and the more exact MoM prediction. The model accurately predicts bistatic scattering from a dihedral at arbitrary orientation and position and is computationally more efficient than SBR and MoM methods.
Sugar Starvation Disrupts Lipid Breakdown by Inducing Autophagy in Embryonic Axes of Lupin (Lupinus spp.) Germinating Seeds

Under nutrient deficiency or starvation conditions, the mobilization of storage compounds during seed germination is enhanced to primarily supply respiratory substrates and hence increase the potential of cell survival. Nevertheless, we found that, under sugar starvation conditions in isolated embryonic axes of white lupin (Lupinus albus L.) and Andean lupin (Lupinus mutabilis Sweet) cultured in vitro for 96 h, the disruption of lipid breakdown occurs, as was reflected in the higher lipid content in the sugar-starved (-S) than in the sucrose-fed (+S) axes. We postulate that pexophagy (autophagic degradation of the peroxisome—a key organelle in lipid catabolism) is one of the reasons for the disruption in lipid breakdown under starvation conditions. Evidence of pexophagy can be: (i) the higher transcript level of genes encoding proteins of pexophagy machinery, and (ii) the lower content of the peroxisome marker Pex14p and its increase caused by an autophagy inhibitor (concanamycin A) in -S axes in comparison to the +S axes. Additionally, based on ultrastructure observation, we documented that, under sugar starvation conditions lipophagy (autophagic degradation of whole lipid droplets) may also occur but this type of selective autophagy seems to be restricted under starvation conditions. Our results also show that autophagy occurs at the very early stages of plant growth and development, including the cells of embryonic seed organs, and allows cell survival under starvation conditions.
Binary pressure-sensitive paint measurements using miniaturised, colour, machine vision cameras

Recent advances in machine vision technology and capability have led to machine vision cameras becoming applicable for scientific imaging. This study aims to demonstrate the applicability of machine vision colour cameras for the measurement of dual-component pressure-sensitive paint (PSP). The presence of a second luminophore component in the PSP mixture significantly reduces its inherent temperature sensitivity, increasing its applicability at low speeds. All of the devices tested are smaller than the cooled CCD cameras traditionally used and most are of significantly lower cost, thereby increasing the accessibility of such technology and techniques. Comparisons between three machine vision cameras, a three CCD camera, and a commercially available specialist PSP camera are made on a range of parameters, and a detailed PSP calibration is conducted in a static calibration chamber. The findings demonstrate that colour machine vision cameras can be used for quantitative, dual-component, pressure measurements. These results give rise to the possibility of performing on-board dual-component PSP measurements in wind tunnels or on real flight/road vehicles.
How hot is the molecular gas in the Galactic Center?

Abstract The molecular clouds in the Central Molecular Zone of our Galaxy (CMZ; inner ~200 pc) show systematically higher gas than dust temperatures (>50 K vs <30 K) in recent H2CO line and dust continuum surveys. This discrepancy is puzzling since gas and dust temperatures should become equal over short times at the high densities observed in these clouds. In deep H2CO(3–2) and (4–3) observations of seven clouds in the CMZ, we detected not only large temperature differences between the clouds but also large gradients within the clouds. Comparing the temperatures and the main H2CO lines at 218 and 291 GHz, we found a positive correlation between those two parameters, indicating that turbulence plays an important role in the heating of the gas. As a follow-up, we mapped the temperature tracers CH3CCH and CH3CN in these seven clouds to derive multiple temperature estimates and test the accuracy of high gas temperatures.
Experiences of family members of relatives admitted as state patients in a psychiatric hospital

Background: Family members play an important role in caring for state patients during their admission to a psychiatric hospital. They receive limited support from the multidisciplinary team because they do not have a relationship that will promote the families to verbalise their thoughts, rather the interaction that the multidisciplinary team and family members share is about the admitted state patient.Aim: This article explored and described the experiences of family members who have a relative admitted as a state patient in a psychiatric hospital. Based on the findings, specific recommendations were provided to facilitate the mental health of state patients’ family members in the future.Setting: The study was conducted in participants’ homes; only one interview took place in the psychiatric hospital when the family member came to meet the multidisciplinary team.Methods: The study employed a qualitative, exploratory and contextual research design. Family members’ lived experiences were explored using in-depth phenomenological interviews and later analysed.Results: The findings indicated family members experienced negative feelings, a sincere desire to support their relatives and a great need to share information and knowledge about mental illness.Conclusion: The study indicated that state patients’ family members’ mental health should be focused on to improve their understanding of mental illness.Contribution: The findings of this study call for collaboration between the family members, the police and multidisciplinary teams from the hospitals, the mental health awareness and counselling for families.
Apertureless near-field optical microscopy

We discuss the operating principles of the apertureless scanning near-field optical microscope (ASNOM), in which the probe acts as a rod antenna and its electromagnetic radiation plays the role of the registered signal. The phase and amplitude of the emitted wave vary depending on the ‘grounding conditions’ of the antenna tip at the sample point under study. Weak radiation from a tiny (2–15 μm long) tip is detected using optical homo- and heterodyning and the nonlinear dependence of the tip polarizability on the tip–surface distance. The lateral resolution of ASNOMs is determined by the tip curvature radius (1– 20 nm), regardless of the wavelength (500 nm–100 μm). ASNOMs are shown to be capable of providing a surface optical map with nanometer resolution and carrying out spectral- and time-resolved measurements at a selected point on the surface.
Prediction of nematic transition temperatures of quinoline-containing liquid crystalline compounds from molecular structure

ABSTRACT A quantitative structure–property relationship study was performed on 51 quinoline-containing liquid crystalline compounds to predict their nematic–isotropic transition temperatures using chemical structure-based descriptors calculated by CODESSA software. The descriptors were also analysed by using principal component analysis. Essentials accounting for a reliable model were all considered carefully during model construction and assessment process. Four variables were selected out by best multilinear regression and were used as inputs to perform the multiple linear regressions. The obtained model was validated both internally and externally. For the test set, it gave a predictive correlation coefficient (R) of 0.9914, root mean square error of 10.5253 and absolute average relative deviation of 5.2213%, respectively. The applicability domain was checked by the leverage approach to verify prediction reliability. In addition, model fit and regression diagnostics were done through the influence plot which reflects the hat values, studentised residuals and Cook’s distance statistics of each sample. The relationships between the descriptors and the nematic–isotropic transition temperature of compounds were discussed. The odd-even effect in the transition temperatures of mesogens in the same homologous series was also discussed. Graphical Abstract
MULTISCALE STATISTICS OF LAGRANGIAN AND EULERIAN ACCELERATION IN TURBULENT STRATIFIED SHEAR FLOWS

Direct numerical simulation data of homogeneous turbulence with shear and stratification are analyzed to study the La- grangian and Eulerian acceleration statistics. Richardson numbers from Ri = 0, corresponding to unstratified shear flow, to Ri = 1, corresponding to strongly stratified shear flow, are considered. The scale dependence of the acceleration statistics is studied using a wavelet-based approach. The probability density functions (pdfs) of both Lagrangian and Eulerian accelerations exhibit a strong and similar influence onRi. The extreme values for Lagrangian acceleration are weaker than those observed for the Eulerian acceleration. Similarly, the Lagrangian time-rate of change of fluctuating density is observed to have smaller extreme values than that of the Eulerian time-rate of change. Thus the time-rate of change of fluctuating density obtained at a fixed location is mainly due to advection of fluc- tuating density through this location. In contrast the time-rate of change of fluctuating density following a fluid particle is substantially smaller, and due to production and dissipation of fluctuating density.
Categorical Feature GAN for Imbalanced Intelligent Fault Diagnosis of Rotating Machinery

The problem of imbalanced data amounts between the samples of healthy and faulty conditions degrades the performance of traditional intelligent diagnosis methods for rotating machinery. This article explores a data generation approach to improve the diagnostic performance of key components in the rotating machinery. A new generative adversarial network (GAN) model, called categorical feature GAN (CFGAN), is proposed to generate sufficient synthetic samples for the minority faulty conditions so as to rebalance the datasets. The main contribution is that the quality of the synthetic samples is ensured by considering both consistency and diversity with the real samples, which conduces to machinery fault diagnosis. Specifically, latent categorical features are first learned from the real fault samples via the proposed CFGAN, which is an integration model of autoencoder (AE) and auxiliary classifier GAN (ACGAN). Then, synthetic categorical features are produced by interpolation among the learned categorical features followed by slight noise addition. Finally, synthetic samples are generated using the synthetic categorical features through the generator of the CFGAN. In addition, Wasserstein distance (WD) is applied to the CFGAN to avoid mode collapse in training. Because categorical features rather than random noise are used to generate samples and the interpolation is performed in the feature space instead of the noisy data space, the consistency of the synthetic samples is improved as compared to the traditional methods. The diversity is ensured by the use of diverse synthetic categorical features and the WD. Two machinery datasets under varying imbalance ratios confirmed that the proposed CFGAN model can synthesize high-quality samples and has better generalization capability over the existing data generation methods in machinery fault diagnosis.
A parallel partition of unity method for the unsteady Stokes equations

Purpose The purpose of this paper is to propose a parallel partition of unity method to solve the time-dependent Stokes problems. Design/methodology/approach This paper solved the time-dependent Stokes equations using the finite element method and the partition of unity method. Findings The proposed method in this paper obtained the same accuracy as the standard Galerkin method, but it, in general, saves time. Originality/value Based on a combination of the partition of unity method and the finite element method, the authors, in this paper, propose a new parallel partition of unity method to solve the unsteady Stokes equations. The idea is that, at each time step, one need to only solve a series of independent local sub-problems in parallel instead of one global problem. Numerical tests show that the proposed method not only reaches the same convergence orders as the fully discrete standard Galerkin method but also saves ample computing time.
Methods for including multiphysics feedback in Monte Carlo reactor physics calculations

The ability to model and simulate nuclear reactors during steady state and transient conditions is important for designing efficient and safe nuclear power systems. The accurate simulation of a nuclear reactor is particularly challenging because the multiple physical processes within the reactor are tightly coupled, which requires that the numerical methods used to resolve each physical process can accurately and efficiently transfer and utilize data from other applications. Monte Carlo methods are desirable for solving the neutron transport equation required in reactor analysis because of the inherent accuracy of the method, but the Computational Solid Geometry (CSG) representation of the physical geometry makes it difficult to accurately and efficiently perform multiphysics reactor analyses with other applications that utilize finite element or finite volume representations. To address this limitation, a multiphysics coupling framework that minimizes the need for spatial discretization in the Monte Carlo geometry is presented in this thesis. The coupling framework uses Functional Expansion Tallies to transfer multiphysics information from the Monte Carlo application to other multiphysics tools. Additionally, the coupling framework uses a modified method for transporting neutrons through spatially continuous total macroscopic cross section distributions in order to incorporate continuous multiphysics feedback fields such as fuel temperature and coolant density into the Monte Carlo simulation. It has been shown that separable Zernike and Legendre Function Expansion Tallies can effectively reconstruct a continuous distribution of fission power density. Additionally, using a prototypical three-dimensional Light Water Reactor pin cell, the method used to transport neutrons through a continuously varying fuel temperature and coolant density distribution was shown to be 1.7 times faster than a comparable discretized simulation with volume-averaged properties, while still providing a high level of accuracy. Finally, in order to make the overall multiphysics coupling scheme useful for reactor analyses, a novel spatially continuous depletion methodology was developed and investigated. With the spatially continuous depletion methodology, number densities can be represented as a linear combination of polynomials, and those polynomial representations can be integrated through time to predict reactor operation. The spatially continuous depletion methodology was able to accurately predict the eigenvalue and number density distributions in a two-dimensional LWR pin cell depletion containing Gd-157 from a 2 weight percent GdO2 and seven other nuclides in the depletion matrix. Analyses of the spatially continuous depletion methodology showed that significant reductions in the number of tallied values could be achieved if polynomial representations were optimized for each nuclide reaction rate. From the depletion
The effects of HeartMath Heart Lock‐In on elementary students' HRV and self‐reported emotion regulation skills

It is important to address social and emotional concerns early on, as they can adversely affect learning at all levels. The classroom is an ideal context for fostering healthy social and emotional development. For example, emotion regulation can be reinforced through simple daily practices within schools. The current applied research project was in collaboration with multiple community partners and assessed the effectiveness of a classroom ‐ based Heart-Math practice (Heart Lock ‐ In) on resting heart rate variability (HRV) and self ‐ reported emotional benefits in elementary students. This repeated ‐ measures study was conducted in central Alberta, Canada, in 2020 and involved obtaining pre – post HRV measurements from N = 24 grade five students who participated in a teacher ‐ led 5 ‐ min Heart Lock ‐ In (like loving ‐ kindness — radiating love to oneself and others) daily for 4 weeks. We hypothesized that the practice would increase resting HRV compared to a 4 ‐ week relaxation control. Qualitative questions were included to capture perceptions of the utility and impact of the practice. Univariate analysis of variance revealed that the HeartMath intervention significantly increased HRV compared to the relaxation control. Students reported enhanced emotional stability, feeling more positive about themselves, and improved interpersonal relationships. They expressed that the practice gives them better focus, which
Tenth-Graders’ Perceptions towards the Use of Google Classroom for Writing Class

The world of education today is closely related to the development of scientific and technological advances. Google Classroom is a useful platform to help the online learning process, especially in learning English. This study aims to determine students’ perceptions of using Google Classroom as a learning medium in writing class. This study used a quantitative descriptive research design. The research subjects were all tenth-grade students in one of the senior high schools in Wates, Central Java, Indonesia. The population of the study consisted of 385 students, but the researchers took a sample of 30% of the total from all tenth-grade students. The researcher used a questionnaire and interview as a data collection method. The researcher analyzed the data statistically by calculating the percentage of students’ answers using Microsoft Excel. This study finds that students have a positive perception of using Google Classroom in writing class. Moreover, it can be concluded that Google Classroom has a good influence in supporting learning for English Foreign Language students.
The impact of SARS-CoV-2 infection and vaccination on inflammatory arthritis: a cohort study

Objectives To investigate the effects of SARS-CoV-2 infection, as well as short- (within 48 hours) and long-term (within 30 days) adverse events (AEs) of SARS-CoV-2 vaccines, including arthritis flares in a large cohort of patients with inflammatory arthritis (IA). Methods A retrospective cohort study comprising 362 patients: 94 (26%) rheumatoid arthritis, 158 (43.6%) psoriatic arthritis and 110 (30.4%) ankylosing spondylitis; and 165 healthy controls (HC) to ascertain the prevalence and severity of SARS-CoV-2 infection in patients with IA, the rate of AEs associated with SARS-CoV-2 vaccines and disease flares within a month of the vaccination. All patients provided informed consent and data about SARS-CoV-2 infection and/or vaccination status. Results One-hundred-seventeen (32.3%) patients and 39 (23.6%) HC were affected by SARS-CoV-2 infection. Forty (34.2%) patients experienced an IA flare within one month of infection, of whom 3 (7.5%) needed to switch therapy. The prevalence of SARS-CoV-2 infection, disease severity, and hospitalization rate were not significantly different. At least one shot of SARS-CoV-2 vaccine was administered in 331 (91.4%) patients and 147 (89.1%) HC. Within 48 hours, 102 (30.8%) patients developed vaccine-related AEs; 52 (15.7%) patients with >1 vaccine dose experienced an IA flare-up, of whom 12 (23.1%) needed to switch therapy. Conclusions A significantly higher rate of IA flare was observed among patients who contracted SARS-CoV-2 infection vs. those without infection. Patients with IA experienced flares after SARS-CoV-2 vaccination, though it was not statistically significant.
Cross-contextual consistency of /s/ length and spectral quality in gay men’s speech

Previous literature on gay(-sounding) speech has shown that gay men tend to produce longer /s/ tokens with higher spectral centers of gravity (Munson & Babel (2010), Levon (2006, 2007), and Linville (1998)). The existing body of work, however, has only shown this difference using word-initial, non-cluster /s/ tokens or aggregate average values across all contexts. This study specifically investigates these questions in /sC/ clusters, both word-initally and -finally. Participants produced words in a carrier phrase containing either /s/ or an /s/-stop cluster, in either word-initial or word-final position (N = 16). To control for speech rate variation, /s/ tokens were measured with respect to participants’ syllable length. Preliminary findings show that gay speakers did in fact lengthen /s/ tokens in all contexts, at similar rates across cluster and singleton contexts. Significant differences between gay and straight men were found for both /s/-to-syllable ratio and spectral center of gravity at /s/ midpoin.