Miracle-dz/UniFAR-FTUs huggingface dataset:
Basic biology education in high school and acceptance of genetically modified food in Japan

While many types of genetically modified (GM) food have become more available worldwide, the acceptance of GM food continues to be low. To increase this acceptance, various educational interventions have been conducted; however, conflicts remain about the safety and acceptability of GM food among laypeople, experts, and policymakers in several countries. Thus, this study aimed to clarify whether basic biology education influences Japanese people’s acceptance of GM food. We examined this idea by comparing individual experiences of high school biology education based on curriculum and proficiency level. We distributed online questionnaires to 1,594 people in Japan; 1,122 valid responses (70.4%) were obtained. Results showed that the acceptance rates of GM vegetables, fish, and meat were 33.6%, 29.0%, and 29.1%, respectively. Comparing the biology knowledge test scores according to different high school biology education levels (i.e., non-learners, basic, and advanced levels) showed no significant differences between the three age groups (20s, 30s, and 40s), which corresponded to different curricula (p = 0.90); however, there were significant differences between the high school biology education levels (p<0.01). Using logistic regression analysis, we then examined the effect of high school biology education on acceptance of GM food. The results showed no significant differences between different high school biology education levels but significantly lower acceptance by the 30s and 40s groups compared with the 20s group (p<0.05). This suggests that basic biology education alone is not sufficient to change people’s attitudes toward GM foods. These generational differences suggest factors other than high school biology curriculum affect different generations’ acceptance of GM foods. Overall, high school biology education did not directly affect acceptance of GM foods, although those who received a higher level of education had an increased knowledge of GM foods.
A smart repair embedded memetic algorithm for 2D shape matching problems

Shape representation plays a major role in any shape optimization exercise. The ability to identify a shape with good performance is dependent on both the flexibility of the shape representation scheme and the efficiency of the optimization algorithm. In this article, a memetic algorithm is presented for 2D shape matching problems. The shape is represented using B-splines, in which the control points representing the shape are repaired and subsequently evolved within the optimization framework. The underlying memetic algorithm is a multi-feature hybrid that combines the strength of a real coded genetic algorithm, differential evolution and a local search. The efficiency of the proposed algorithm is illustrated using three test problems, wherein the shapes were identified using a mere 5000 function evaluations. Extension of the approach to deal with problems of unknown shape complexity is also presented in the article.
Differences in Tsimane children’s growth outcomes and associated determinants as estimated by WHO standards vs. within-population references

Anthropometric measures are commonly converted to age stratified z-scores to examine variation in growth outcomes in mixed-age and sex samples. For many study populations, z-scores will differ if calculated from World Health Organization (WHO) growth standards or within-population references. The specific growth reference used may influence statistical estimates of growth outcomes and their determinants, with implications for biological inference. We examined factors associated with growth outcomes in a sample of 152 Tsimane children aged 0–36 months. The Tsimane are a subsistence-scale population in the Bolivian Amazon with high rates of infectious disease and growth faltering. To examine the influence of growth reference on statistical inferences, we constructed multiple plausible models from available infant, maternal, and household attributes. We then ran identical models for height-for-age (HAZ), weight-for-age (WAZ), and weight-for-height (WHZ), with z-scores alternately calculated from WHO and robust Tsimane Lambda-Mu-Sigma growth curves. The distribution of WHO relative to Tsimane HAZ scores was negatively skewed, reflecting age-related increases in lower HAZ. Standardized coefficients and significance levels generally agreed across WHO and Tsimane models, although the strength and significance of specific terms varied in some models. Age was strongly, negatively associated with HAZ and WAZ in nearly all WHO, but not Tsimane models, resulting in consistently higher R2 estimates. Age and weaning effects were confounded in WHO models. Biased estimates of determinants associated with WHO HAZ may be more extreme in small samples and for variables that are strongly age-patterned. Additional methodological considerations may be warranted when applying WHO standards to within-population studies, particularly for populations with growth patterns known to systematically deviate from those of the WHO reference sample.
An Idea of Interactive Japanese Language M-Learning Application to Support Listening and Speaking Exercise

Advances in the mobile devices technology introduce a new learning model called mobile learning (m-learning). In the context of Indonesian higher education, Japanese language is not only one of the most favourite foreign language but also considered to be a difficult foreign language to learn. This fact brings up many m-learning applications were developed to help learners to learn Japanese language independently. Popular Japanese m-learning applications only focus on enhancing vocabulary, writing and reading ability. Although enhancing vocabulary and reading ability are important, training Japanese speaking is also essential in fundamental Japanese learning. This paper presents the concept of speaking input in m-learning application to provide the new interaction for learners as an alternative Japanese language learning tool. The main objective is to investigate the feasibility of the speaking method to support m-learning implementation. The proposed application is expected to provide listening and speaking practice intuitively. Experimental results show that the overall functionality of proposed application is feasible for future implementation with 81.0 usability score.
The empirical structure of narrative identity: The initial Big Three.

A robust empirical literature suggests that individual differences in the thematic and structural aspects of life narratives are associated with and predictive of psychological well-being. However, 1 limitation of the current field is the multitude of ways of capturing these narrative features, with little attention to overarching dimensions or latent factors of narrative that are responsible for these associations with well-being. In the present study we uncovered a reliable structure that accommodates commonly studied features of life narratives in a large-scale, multi-university collaborative effort. Across 3 large samples of emerging and midlife adults responding to various narrative prompts (N = 855 participants, N = 2,565 narratives), we found support for 3 factors of life narratives: motivational and affective themes, autobiographical reasoning, and structural aspects. We also identified a "functional" model of these 3 factors that reveals a reduced set of narrative features that adequately captures each factor. Additionally, motivational and affective themes was the factor most reliably related to well-being. Finally, associations with personality traits were variable by narrative prompt. Overall, the present findings provide a comprehensive and robust model for understanding the empirical structure of narrative identity as it relates to well-being, which offers meaningful theoretical contributions to the literature, and facilitates practical decision making for researchers endeavoring to capture and quantify life narratives. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
Evidence of item bias in a national flourishing measure for autistic youth

Flourishing is a positive health indicator that aligns with strengths‐based perspectives and measures within autism research. Flourishing indicators were recently included in the National Survey of Children's Health (NSCH) and have been used to evidence disparities in flourishing experienced by autistic children compared to non‐autistic peers. Yet, little has been done to examine the utility of standard flourishing items for this population. This study examined the NSCH caregiver‐reported flourishing items for measurement item bias. A cross‐sectional, representative sample of autistic and non‐autistic US children aged 6–17 years (n = 41,691) was drawn from the 2018–2019 NSCH public dataset. A confirmatory factor analysis using a multiple indicators and multiple causes model (MIMIC‐CFA) was conducted to (1) test for differential item functioning (DIF; i.e., measurement bias); and (2) estimate latent mean group differences after controlling for DIF. Findings supported a 3‐factor (social competence, school motivation, and behavioral control), 10‐item model structure consistent with past literature, yet measurement bias was evident for 6 of the 10 items. Persistent group differences, after accounting for DIF and covariates, indicates that caregivers of autistic children perceive their children are experiencing meaningfully lower flourishing outcomes compared to caregivers of non‐autistic children. However, evidence of measurement bias for items related to the social competence dimension calls into question the applicability of this measure for autistic children. Further interpretation of group differences and use of this measure should be approached with caution.
Challenges, Job Satisfiers, and Self-Care among Perinatal Nurses in the United States during the COVID-19 Pandemic

Abstract Purpose: To explore the perceived challenges, job satisfiers, and self-care of perinatal nurses in the United States during the COVID-19 pandemic. Study Design and Methods: In May of 2021, a cross-sectional survey was distributed online to members of the Association of Women's Health, Obstetric, and Neonatal Nurses and the National Association of Neonatal Nurses. We calculated descriptive statistics on respondent characteristics and applied conventional content analysis to free-text comments. Results: Perinatal nurses (N = 297) responded to three open-ended questions on their perceived challenges, job satisfiers, and self-care. Frequently reported challenges included changing guidelines and policies (n = 101, 34%), personal protective equipment as a barrier (n = 73, 24.6%), and visitor restrictions (n = 64, 21.5%). Frequently reported job satisfiers were provision of high-quality care (n = 137, 46.1%) and visitor restrictions (n = 77, 25.9%). Respondents reported using mental (n = 152, 51.2%) and physical (n = 145, 48.8%) self-care strategies and 12.8% (n = 38) reported using no self-care strategies. Clinical Implications: The ability to provide high-quality care was reported as a leading job satisfier. Poor communication of consistent, evidence-based guidelines, lack of personal protective equipment, and inadequate unit staffing were leading challenges. Visitor restrictions were a challenge and a job satisfier, suggesting opportunities to better include visitors as support people. Most respondents reported engaging in one or more types of self-care outside of the hospital setting. Future research is needed to examine strategies for self-care among perinatal nurses when at work in the hospital setting. Perinatal nurses, like other nurses in the United States and around the world, have faced many challenges in providing high quality nursing care during the COVID-19 pandemic. In this study, members of the Association of Women's Health, Obstetric, and Neonatal Nurses and the National Association of Neonatal Nurses participated in an online survey about their experiences during the pandemic. Ability to provide high-quality care was reported as a leading job satisfier, while poor communication of consistent, evidence-based guidelines, lack of personal protective equipment, and inadequate unit staffing were leading challenges. Visitor restrictions were a challenge and a job satisfier, suggesting opportunities to better include visitors as support people. This study adds important information about maternity nursing practice in the United States during the COVID-19 pandemic.
Contribution of Extracellular Membrane Vesicles To the Secretome of Staphylococcus aureus

The secretome of Staphylococcus aureus includes soluble molecules and nano-sized extracellular membrane vesicles (MVs). The protein composition of both the secretome and MVs includes cytoplasmic and membrane proteins, as well as exoproteins, some cell wall-associated proteins, and glycopolymers. ABSTRACT The microbial secretome modulates how the organism interacts with its environment. Included in the Staphylococcus aureus secretome are extracellular membrane vesicles (MVs) that consist of cytoplasmic and membrane proteins, as well as exoproteins, some cell wall-associated proteins, and glycopolymers. The extent to which MVs contribute to the diverse composition of the secretome is not understood. We performed a proteomic analysis of MVs purified from the S. aureus strain MRSA252 along with a similar analysis of the whole secretome (culture supernatant) before and after depletion of MVs. The MRSA252 secretome was comprised of 1,001 proteins, of which 667 were also present in MVs. Cell membrane-associated proteins and lipoteichoic acid in the culture supernatant were highly associated with MVs, followed by cytoplasmic and extracellular proteins. Few cell wall-associated proteins were contained in MVs, and capsular polysaccharides were found both in the secretome and MVs. When MVs were removed from the culture supernatant by ultracentrifugation, 54 of the secretome proteins were significantly depleted in abundance. Proteins packaged in MVs were characterized by an isoelectric point that was significantly higher than that of proteins excluded from MVs. Our data indicate that the generation of S. aureus MVs is a mechanism by which lipoteichoic acid, cytoplasmic, and cell membrane-associated proteins are released into the secretome. IMPORTANCE The secretome of Staphylococcus aureus includes soluble molecules and nano-sized extracellular membrane vesicles (MVs). The protein composition of both the secretome and MVs includes cytoplasmic and membrane proteins, as well as exoproteins, some cell wall-associated proteins, and glycopolymers. How the MV cargo differs from the protein composition of the secretome has not yet been addressed. Although the compositions of the secretome and MVs were strikingly similar, we identified 54 proteins that were specifically packaged in MVs. Proteins highly associated with MVs were characterized by their abundance in the secretome, an association with the bacterial membrane, and a basic isoelectric point. This study deepens our limited understanding about the contribution of MVs to the secretome of S. aureus.
Searching for analogues, how long must we wait?

A three-way relationship is derived between the size of a library ( M years) of historical atmospheric data, the distance between an arbitrarily picked state of the atmosphere and its nearest neighbor (or analogue), and the size of the spatial domain, as measured by the number of spatial degrees of freedom ( N ). It is found that it would take a library of order 10 30 years to find 2 observed flows that match to within current observational error over a large area such as the Northern Hemisphere. Obviously, with only 10–100 years of data, the probability of finding natural analogous is very small, unless one is satisfied with analogy over small areas or in just 2 of 3 degrees of freedom as represented, for instance, by 2 or 3 leading empirical orthogonal modes. We further propose the notion that analogues can be constructed by combining a number of observed flow patterns. We have found at least one application where linearly constructed analogues are conclusively better at specifying US surface weather from concurrent 700 mb geopotential height than natural analogues are. DOI: 10.1034/j.1600-0870.1994. t01-2-00006.x
Feasibility of A Smartwatch Platform to Assess Ecological Mobility: Real-time Online Assessment and Mobility Monitor (ROAMM).

BACKGROUND Early detection of mobility decline is critical to prevent subsequent reductions in quality of life, disability, and mortality. However, traditional approaches to mobility assessment are limited in their ability to capture daily fluctuations that align with sporadic health events. We aim to describe findings from a pilot study of our Real-time Online Assessment and Mobility Monitor (ROAMM) smartwatch application, which uniquely captures multiple streams of data in real-time in ecological settings. METHODS Data come from a sample of 31 participants (Mage=74.7, 51.6% female) who used ROAMM for approximately two weeks. We describe the usability and feasibility of ROAMM, summarize prompt data using descriptive metrics, and compare prompt data with traditional survey-based questionnaires or other established measures. RESULTS Participants were satisfied with ROAMM's function (87.1%) and ranked the usability as "above average. " Most were highly engaged (average adjusted compliance = 70.7%) and the majority reported being "likely" to enroll in a two-year study (77.4%). Some smartwatch features were correlated with their respective traditional measurements (e.g., certain GPS-derived life-space mobility features (r=0.50-0.51, p<0.05) and ecologically-measured pain (r=0.72, p=0.01)), but others were not (e.g., ecologically-measured fatigue). CONCLUSION ROAMM was usable, acceptable, and effective at measuring mobility and risk factors for mobility decline in our pilot sample. Additional work with a larger and more diverse sample is necessary to confirm associations between smartwatch-measured features and traditional measures. By monitoring multiple data streams simultaneously in ecological settings, this technology could uniquely contribute to the evolution of mobility measurement and risk factors for mobility loss.
CLEAN Based on Spatial Source Coherence

To obtain higher resolution acoustic source plots from microphone array measurements, deconvolution techniques are becoming increasingly popular. Deconvolution algorithms aim at identifying Point Spread Functions (PSF)in source plots, and may therefore fall short when actual beam patterns of measured noise sources are not similar to synthetically obtained PSF's. To overcome this, a new version of the classical deconvolution method CLEAN is proposed here: CLEAN-SC. By this new method, which is based on spatial source coherence, side lobes can be removed of actually measured beam patterns. Essentially, CLEAN-SC iteratively removes the part of the source plot which is spatially coherent with the peak source. A feature of CLEAN-SC is its ability to extract absolute sound power levels from the source plots. The merits of CLEAN-SC were demonstrated using array measurements of airframe noise on a scale model of the Airbus A340 in the 8 ×6 m2 closed test section of DNW-LLF.
Statistical Prediction of Tropical Cyclone Motion over the Southwest Indian Ocean

Abstract The derivation of a system of regression equations for the prediction of tropical cyclone motion over the Southwest Indian Ocean is described. The equations use the same predictors that are typically used as storm selection criteria by analog models. In this sense, the prediction model simulates an analog forecast. To complete the simulation, a method is described whereby the prediction errors (residuals) of the development data are used to construct equi-probability ellipses similar to those used by analog models. Testing the prediction equations on three years of independent data for the years 1970, 1971 and 1972 indicates a forecast accuracy closely approximating that realized by a similar system of prediction equations in operational use in the Atlantic.
Health-related quality of life in gout, psoriatic arthritis, rheumatoid arthritis and ankylosing spondylitis, results from a cross-sectional survey in Western Sweden

Objectives Inflammatory joint diseases (IJDs) substantially affect health-related quality of life (HRQoL). We aimed to compare HRQoL between patients with gout, psoriatic arthritis (PsA), rheumatoid arthritis (RA), and ankylosing spondylitis (AS): (i) overall; (ii) stratified by sex; and (iii) between women and men with the same IJD diagnosis. Method A survey including the RAND36-Item Health Survey for assessing HRQoL was sent to patients with a diagnosis of gout, PsA, RA, or AS, registered at a rheumatology clinic or primary care centre during 2015–2017. HRQoL was compared across IJDs. Because of age differences between diagnoses, age-matched analyses were performed. Results In total, 2896/5130 (56.5%) individuals responded to the questionnaire. Of these, 868 had gout, 699 PsA, 742 RA, and 587 AS. Physical component summary (PCS) scores were more affected than mental component summary (MCS) scores for all diagnoses (PCS range: 39.7–41.2; MCS range: 43.7–48.9). Patients with gout reported better PCS scores than patients with PsA, RA, and AS, who reported similar scores in age-matched analysis. MCS scores were close to normative values for the general population and similar across IJDs. When comparing women and men with respective IJDs, women reported worse PCS (range, all IJDs: 34.5–37.4 vs 37.5–42.5) and MCS (PsA: 44.0 vs 46.8; RA: 46.1 vs 48.7) scores. Conclusion We found that patients with gout reported better PCS scores than patients with other IJDs, for whom the results were similar. Women reported overall worse PCS and MCS scores than men.
Comprehensive structural characterization of the human AAA+ disaggregase CLPB in the apo- and substrate-bound states reveals a unique mode of action driven by oligomerization

The human AAA+ ATPase CLPB (SKD3) is a protein disaggregase in the mitochondrial intermembrane space (IMS) and functions to promote the solubilization of various mitochondrial proteins. Loss-of-function CLPB mutations are associated with a few human diseases with neutropenia and neurological disorders. Unlike canonical AAA+ proteins, CLPB contains a unique ankyrin repeat domain (ANK) at its N-terminus. How CLPB functions as a disaggregase and the role of its ANK domain are currently unclear. Herein, we report a comprehensive structural characterization of human CLPB in both the apo- and substrate-bound states. CLPB assembles into homo-tetradecamers in apo-state and is remodeled into homo-dodecamers upon substrate binding. Conserved pore-loops (PLs) on the ATPase domains form a spiral staircase to grip and translocate the substrate in a step-size of 2 amino acid residues. The ANK domain is not only responsible for maintaining the higher-order assembly but also essential for the disaggregase activity. Interactome analysis suggests that the ANK domain may directly interact with a variety of mitochondrial substrates. These results reveal unique properties of CLPB as a general disaggregase in mitochondria and highlight its potential as a target for the treatment of various mitochondria-related diseases.