Miracle-dz/UniFAR-FTUs huggingface dataset:
Postprandial glycemic and circulating SCFA concentrations following okara- and biovalorized okara-containing biscuit consumption in middle-aged and older adults: a crossover randomized controlled trial.

Okara is a high-fiber food by-product that can be biotransformed with Rhizopus oligosporus to improve its nutritional value and palatability. This research aims to assess postprandial changes in glycemic-related and lipid-related outcomes in middle-aged and older Singaporeans following okara- and biovalorized okara-containing biscuit consumption. Fifteen participants (58 ± 6 years old, mean ± SD) completed the randomized crossover study. Participants were provided control (C), okara (AOK)-, and biovalorized okara (RO)-containing biscuits in separate 4 h mixed meal tolerance tests. Serum glucose and insulin, insulin indices, serum short-chain fatty acids (SCFA) and lipid-lipoprotein panels, and sensory analysis were assessed. Glucose-stimulated insulin secretion was significantly lower for RO than for C (p: 0.035) while log insulin incremental area under the curve (AUC) was significantly lower for AOK compared to that for C (p: 0.023). The estimated insulin sensitivity index and estimated metabolic clearance rate were significantly higher for AOK compared to that for C (p: 0.025 and 0.016 respectively). Normalized AUC for total SCFA was significantly higher for RO compared to that for C (p: 0.038). Normalized AUC for LDL-cholesterol was significantly higher for AOK than for C (p: 0.010). No significant difference was noted for glucose, total cholesterol, HDL-cholesterol, and triglyceride concentrations. RO had greater flavor and overall liking than AOK (p: 0.007 and 0.017 respectively). Biscuits incorporated with okara or biovalorized okara can attenuate postprandial insulin responses. RO offered a greater SCFA response than C, indicating improved SCFA concentrations upon consumption of okara improved with fermentation. The trial was registered under https://www.clinicaltrials. gov (NCT03978104, 25 May 2019).
Health and Well-Being of Church Musicians during the COVID-19 Pandemic—Experiences of Health and Work-Related Distress from Musicians of the Evangelical Lutheran Church in Finland

Earlier research has revealed contrasting gender results in standardized mortality ratios (SMR) for cancers and cardiovascular diseases of Finnish church musicians compared with the general population. In order to better understand the SMRs, our study examined gender differences in health and work-related experiences of church musicians with special focus on experienced stress and burnout on the one hand, and work engagement and mental well-being on the other. The data were collected by a questionnaire including both standardized measures and open-ended questions. Statistical methods (mostly χ2 tests) were used for examining gender differences in the measures, and the open-ended questions were analyzed using theory-driven content analysis. The two sets of data complemented each other. Analyses of the standardized measures showed that church musicians have more burnout and distress than the general population but the results were not gendered. However, the open-ended questions revealed clearly higher distress in females than in males. Based on the contrast between the measures and the open-ended questions, we raise the question about how well females who have distressing work can recognize the stress factors and change them, especially if distress becomes a “normal state”.
A Systematic Literature Review on Latest Keystroke Dynamics Based Models

The purpose of this study is to conduct a comprehensive evaluation and analysis of the most recent studies on the implications of keystroke dynamics (KD) patterns in user authentication, identification, and the determination of useful information. Another aim is to provide an extensive and up-to-date survey of the recent literature and potential research directions to understand the present state-of-the-art methodologies in this particular domain that are expected to be beneficial for the KD research community. From January 1st, 2017 to March 13th, 2022, the popular six electronic databases have been searched using a search criterion (“keystroke dynamics” OR “typing pattern”) AND (“authentication” OR “verification” OR “identification”). With this criterion, a total of nine thousand three hundred forty-eight results, including duplicates, were produced. However, one thousand five hundred forty-seven articles have been chosen after removing duplicates and preliminary screening. Due to insufficient information, only one hundred twenty-seven high-quality quantitative research articles have been included in the article selection process. We compared and summarised several factors with multiple tables to comprehend the various methodologies, experimental settings, and findings. In this study, we have identified six unique KD-based designs and presented the status of findings toward an effective solution in authentication, identification, and prediction. We have also discovered considerable heterogeneity across studies in each KD-based design for desktops and smartphones separately. Finally, this paper found a few open research challenges and provided some indications for a deeper understanding of the issues and further study.
The Interaction Effects of School Location and Teaching Experience on Self-Efficacy Perceived by the Primary Science Teachers Towards Integrated Stream Teaching

Integrated science, technology, engineering and mathematics (STEM) is expanded to integrated STrEAM, where the “r” denotes the amalgamation of reading and writing elements to bridge the gap between STEM disciplines. Since integrated STrEAM is a new approach, it is pivotal to gauge the teachers’ self-efficacy in executing integrated STrEAM teaching. Therefore, this cross-sectional survey design reports on the effect of school location and years of teaching experience on the self-efficacy of primary science teachers towards integrated STrEAM teaching. For this purpose, the STrEAM Teaching Self-Efficacy Scale (STSES) was administered to 200 primary science teachers throughout the nation. The STSES consists of five subscales: STrEAM instructional strategies self-efficacy, STrEAM classroom management self-efficacy, STrEAM community involvement self-efficacy, STrEAM student engagement self-efficacy, and STrEAM outcome expectancy. Data obtained from the STSES survey was analysed using two-way Multiple analysis of variance (MANOVA) to identify the effects of school location and years of teaching experience towards self-efficacy perceived by the primary science teachers towards integrated STrEAM teaching. The findings show that school location and years of teaching experience significantly affect the self-efficacy perceived by the primary science teachers towards integrated STrEAM teaching. School location and years of teaching experience also have a significant interaction effect (Wilks’ lambda = 0.860, F (15, 519) = 1.950, p < 0.005) on primary science teachers towards integrated STrEAM teaching. The finding of this study is resourceful for the STEM stakeholders and policy makers to design the STrEAM teaching materials for training the teachers.
Optically isotropic and monoclinic ferroelectric phases in Pb ( Zr 1 − x Ti x ) O 3 (PZT) single crystals near morphotropic phase boundary

We report the finding of unusual scale-dependent symmetry below the ferroelectric Curie temperature in the perovskite $\text{Pb}({\text{Zr}}_{1\ensuremath{-}x}{\text{Ti}}_{x}){\text{O}}_{3}$ single crystals of morphotropic phase boundary compositions. The crystals of tetragonal symmetry on submicrometer scale exhibit a macroscopic (optically determined) cubic symmetry. This peculiar optical isotropy is explained by the anomalously small size of tetragonal ferroelectric domains. Upon further cooling the crystals transform to the phase consisting of micrometer-sized domains of monoclinic symmetry.
Linking Processing Parameters and Rheology to Optimize Additive Manufacturing of k-Carrageenan Gel Systems

Additive manufacturing—in particular, three-dimensional (3D) printing—has been introduced since the late 1980s, offering a novel paradigm for engineering design and manufacturing, as it allows the fabrication of very complex structures. Additive manufacturing of hydrogels is a very popular method to produce scaffolds to be used in tissue engineering and other biomedical applications, as well as in other advanced technological areas. When printing a thermoreversible physical hydrogel, a subtle balance between thermal and rheological parameters exists. The characteristic times of the sol–gel transition, regulated by a well-defined thermal history, must be optimized with respect to the characteristic processing times. In this work, we use this thermo-rheological approach to the additive manufacturing of a physical hydrogel. A low-cost desktop 3D printer for thermoplastic polymers was suitably modified to print a 1.5 wt% solution of k-carrageenan. The thermal behavior of the printer was determined by performing experimental measurements of the temperature–time evolution during the different processing steps, from solution loading, to the extrusion of the incoming gel, to the final solidification stage. In parallel, linear viscoelastic oscillatory shear measurements were performed in a rotational rheometer under thermal histories as close as possible to those previously measured in the printing process. The comparison between the rheological results and the quality of printing under different thermal histories is presented and discussed, highlighting the main relations between rheological and processing behavior, which are helpful in the assessment and optimization of the printing conditions.
Predicting Quality of Life and Domestic Violence against Women During COVID-19 Quarantine Based on Resilience and Coping Styles

Background: Restrictive measures caused by the COVID-19 have exposed the families' structure to some critical issues such as reduced quality of life and increased domestic violence. For this reason, the study of psychological factors are essential in this regard. Objectives: The study aimed to predict the quality of life and violence against women during COVID-19 quarantine based on resilience and coping styles. Methods: This descriptive correlation study was conducted on all married women in Karaj from October 1 to November 30, 2020. A total of 241 people were randomly selected as the sample and answered the questionnaires about coping styles, quality of life, violence against women, and resilience scale. The data were analysized by Pearson correlation test and regression analysis. Results: There was a significant positive relationship between resilience, efficient coping style, and quality of life, as well as a significant negative relationship between inefficient coping style and quality of life (P < 0.01). A significant negative relationship was observed between coping style with domestic violence, as well as a significant positive relationship between dysfunctional coping style and domestic violence (P < 0.01). Resilience and effective coping style predicted the quality of life, domestic violence, and ineffective coping style of domestic violence against women (P < 0.01). Conclusions: According to the results, individual and psychological factors of people could play a significant role in the occurrence of violence and thus reduce their quality of life. In educational-therapeutic sessions, counselors and family therapists increased the quality of life and reduced violence by examining coping styles and resilience to use educational strategies in this area.
The Equation of State in Astrophysics: Neutron star crusts with magnetic fields

The properties of plasma in neutron star crusts with strong magnetic fields B — 10 10 — 10 13 G are reviewed: thermodynamic properties (equation of state, entropy, specific heat), transport properties (electron thermal and electrical conductivity of degenerate electron gas, radiative thermal con ductivity of very surface nondegenerate layers) and neutrino energy losses. Classical effects of electron Larmor rotation in a magnetic field are con sidered as well as quantum effects of the electron motion (Landau levels). The influence of the magnetic fields on density and temperature profiles in the surface layers of neutron stars and on neutron star cooling is briefly discussed.
A Sentence Prediction Approach Incorporating Trial Logic Based on Abductive Learning

Sentencing prediction is an important direction of artificial intelligence applied to the judicial field. The purpose is to predict the trial sentence for the case based on the description of the case in the adjudication documents. Traditional methods mainly use neural networks exclusively, which are trained on a large amount of data to encode textual information and then directly regress or classify out the sentence. This shows that machine learning methods are effective, but are extremely dependent on the amount of data. We found that there is still external knowledge such as laws and regulations that are not used. Moreover, the prediction of sentences in these methods does not fit well with the trial process. Thus, we propose a sentence prediction method that incorporates trial logic based on abductive learning, called SPITL. The logic of the trial is reflected in two aspects: one is that the process of sentence prediction is more in line with the logic of the trial, and the other is that external knowledge, such as legal texts, is utilized in the process of sentence prediction. Specifically, we establish a legal knowledge base for the characteristics of theft cases, translating relevant laws and legal interpretations into first-order logic. At the same time, we designed the process of sentence prediction according to the trial process by dividing it into key circumstance element identification and sentence calculation. We fused the legal knowledge base as weakly supervised information into a neural network through the combination of logical inference and machine learning. Furthermore, a sentencing calculation method that is more consistent with the sentencing rules is proposed with reference to the Sentencing Guidelines. Under the condition of the same training data, the effect of this model in the experiment of responding to the legal documents of theft cases was improved compared with state-of-the-art models without domain knowledge. The results are not only more accurate as a sentencing aid in the judicial trial process, but also more explanatory.
Selecting massive variables using an iterated conditional modes/medians algorithm

: Empirical Bayes methods are designed in selecting massive variables, which may be inter-connected following certain hierarchical structures, because of three attributes: taking prior information on model pa- rameters, allowing data-driven hyperparameter values, and free of tuning parameters. We propose an iterated conditional modes/medians (ICM/M) algorithm to implement empirical Bayes selection of massive variables, while incorporating sparsity or more complicated a priori information. The it- erative conditional modes are employed to obtain data-driven estimates of hyperparameters, and the iterative conditional medians are used to esti- mate the model coeﬃcients and therefore enable the selection of massive variables. The ICM/M algorithm is computationally fast, and can easily extend the empirical Bayes thresholding, which is adaptive to parameter sparsity, to complex data. Empirical studies suggest competitive perfor- mance of the proposed method, even in the simple case of selecting massive regression predictors.
Construction and Analysis of Urban Traffic Noise Prediction Model Based on PSO Algorithm and BRF Network Structure

Due to the current nonlinear traffic noise and changing natural environment, accurate prediction of traffic noise has become a major challenge. In order to improve the accuracy of traffic noise prediction, this paper constructs a short-term traffic noise prediction model based on PSO algorithm and BRF network structure. The model can predict the noise state of future traffic according to historical traffic information. Particle swarm optimization (PSO) network is used for short-term traffic prediction to deal with the problems of low accuracy and long-time consumption. A BRF (one-dimensional convolution)-PSO short-term traffic noise prediction model is proposed. BRF method is used to extract the spatial features of traffic noise and compared with PCA (principal component analysis)-PSO model and PSO model. The results show that the prediction accuracy of BRF-PSO model is 2% higher than that of PCA-PSO model and 6% higher than that of PSO model, which proves the effectiveness of BRF-PSO model. This study provides a technical reference for the short-term traffic noise prediction of intelligent city and the effective improvement of urban traffic environment.
Host–Virus Interactions in Japanese Encephalitis Virus

Japanese encephalitis (JE) is a mosquito-borne zoonotic disease that causes severe brain inflammation. The JE virus envelope protein domain III (JEV-ED3) plays a critical role in activating receptor binding and membrane fusion. This communication briefly describes, in a computational approach, how structural changes within the JEV-ED3 mutant epitopes suppress their antibody neutralization function. The simulated results demonstrate that mutant Ser40Lys acts as an antibody neutralization escape while Asp41Arg may play the role of an escape mutant. Additionally, an examination of the double mutants on JEV-ED3 suggests that these mutants may qualify as stronger neutralizing escape agents than their single variants. The structural analysis of this work helps to identify the proper antiviral target sequences and specific monoclonal antibodies for the JEV-ED3 escape mutants.
Finite Element Assessment of a Hybrid Proposal for Hip Stem, from a Standardized Base and Different Activities

Choosing a suitable prosthesis to restore the functionality of the hip joint is a complex problem. The stem geometries, materials, and type of hip damage are critical factors for avoiding potential issues (aseptic loosening, fracture, and natural wear and tear). Comparing the available stems to select the best option is not straightforward because of the various loads and boundary conditions used in the tests, making the process difficult to compare the advantages and disadvantages among them. This work proposes stem assessment using a standardized base (generated from a literature review and ISO standards) to compare the stem geometries and present a new hybrid design to improve performance using the best qualities of the implants reported in the literature review. Sixteen hip prostheses were evaluated with the finite element method (FEM) using the same boundary and loading conditions through multi-objective analysis (von Mises stress and strain). Consequently, a hybrid geometry proposal was obtained by assessing specific points through the stem length (medial and lateral region) to define the cross-section (trapezoidal) and the new profile. The new hybrid implant proposal presented a stress reduction of 9.6% when compared to the reference implant P2-T (the implant with the best behavior) in the most critical activity (activity 4) using a titanium alloy. A similar stress reduction of 9.98% was obtained using ASTM F2996-13 and ISO 7206–4:2010(E) standards.
Understanding the reading practices of Fort Hare students

Universities world-wide are battling to offer access to far greater numbers than ever before. The University of Fort Hare, specifically, is also part of a troubled South African education system and is located in a disadvantaged, rural area. The main aim of this study was to understand Fort Hare students’ reading practices, as reported by the students themselves. This thesis used a framework of New Literacy Studies, which views student learning as a process of mastering discipline-specific, socially constructed norms and values, and sees the adopting of a literacy as including the adoption of an identity. Since discourse, in the NLS tradition, has been found to be a mediating mechanism in the social construction of identity, a critical discourse analysis was adopted to begin understanding aspects of Fort Hare students’ reading practices and the links between these and their identities. Critical realism is the ontological underpinning of this thesis. This means that the study aimed to identify the tendencies of certain mechanisms in this case, Discourses to affect students’ reading practices, by analysing interview transcripts of focus group discussions held with 30 students. Frameworks and tools provided by Fairclough and Gee were applied to interview data analysis. The ‘We blacks’ Discourse was one of one of the prominent Discourses that interviewees drew on when talking about their reading practices. It was closely allied to the ‘Resistance to reading’ Discourse, as participants explained that they tended to disregard books and did not enjoy reading for leisure. The ‘We blacks’ Discourse in this way homogenised class and other differences between black students, and indicated the ways in which their experiences were outside of academic Discourses. This Discourse served as a constraining mechanism for some, and indicated that those who used it tended not to identify with the academy. There was an evident link between the ‘We blacks’ Discourse, the ‘Resistance to reading’ Discourse and the ‘Better than us’ Discourse, in which students who enjoyed reading were called names for supposedly being conceited. Two opposing discourses (with a small ‘d’) emerged when students talked about literacy sponsors like parents and lecturers. Some used the ‘Our parents don’t chase us’ discourse to depict family members who were not encouraging, overlapping with the ‘We blacks’ Discourse. The contrasting ‘Go read anything’ discourse described more encouraging
Advances in Mass Spectrometers for Flyby Space Missions for the Analysis of Biosignatures and Other Complex Molecules

Spacecraft flybys provide access to the chemical composition of the gaseous envelope of the planetary object. Typical relative encounter velocities range from km/s to tens of km/s in flybys. For speeds exceeding about 5 km/s, modern mass spectrometers analyzing the rapidly encountering gas suffer from intrinsic hypervelocity impact-induced fragmentation processes causing ambiguous results when analyzing complex molecules. In this case, instruments use an antechamber, inside which the incoming species collide many times with the chamber wall. These collisions cause the desired deceleration and thermalization of the gas molecules. However, these collisions also dissociate molecular bonds, thus fragmenting the molecules, and possibly forming new ones precluding scientists from inferring the actual chemical composition of the sampled gas. We developed a novel time-of-flight mass spectrometer that handles relative encounter velocities of up to 20 km/s omitting an antechamber and its related fragmentation. It analyzes the complete mass range of m/z 1 to 1000 at an instance. This innovation leads to unambiguous analysis of complex (organic) molecules. Applied to Enceladus, Europa or Io, it will provide reliable chemical composition datasets for exploration of the Solar System to determine its status, origin and evolution.