Miracle-dz/UniFAR-FTUs huggingface dataset:
Online Gamified Quizzes in Undergraduate Mental Health Nursing Education: Thematic Analysis of Students’ Qualitative Views

The shortage of mental health nurses is a long-standing concern (Browne et al., 2013; Delaney & Shattell, 2012), and some undergraduate nursing students regard mental health nursing as an unpopular career trajectory (Happell & Gaskin, 2013; Jansen & Venter, 2015). Undergraduate mental health nursing education must transform to ensure adequate interest and retention of new graduate nurses. Educators of undergraduate nursing students may address negative attitudes towards mental health nursing by implementing novel teaching strategies that inspire interest. Even in the absence of discouraging presuppositions, garnering students’ interest and engagement in course content is a challenge for tertiary educators (Collaço, 2017). Challenges notwithstanding, it is an educator’s responsibility to implement dynamic learning strategies that facilitate the development of the knowledge and skills required by the curriculum. Research focussed on mental health nursing education has highlighted the importance of activities involving simulation, critical thinking, and consumer-oriented experiences (Goh et al., 2021; Lehr & Schlenger, 2016). Little has been reported in relation to the merits of gamified quizzes in undergraduate mental health nursing education. In corralling students’ focus and interest, electronic gamified mediums are emerging as a viable feature of teaching in both the classroom and online space. Electronic gamified activities are of particular significance in light of the COVID-19 pandemic, which has led to widespread adoption of distance learning, and dependence on computer-based mediums.
Theta burst stimulation versus high-frequency repetitive transcranial magnetic stimulation for poststroke dysphagia

Abstract Background: Repetitive transcranial magnetic stimulation (rTMS) of high-frequency (10 Hz) on suprahyoid motor cortex has been an evidence-based treatment for poststroke dysphagia. Intermittent theta burst stimulation (iTBS) can be performed in 3 minutes compared with 20 ± 5 minutes for 10 Hz rTMS. This study aimed to ensure the clinical efficacy, safety, and tolerability of iTBS compared with 10 Hz rTMS for patients with poststroke dysphagia. Method: In this randomized, double-blind, single-center, controlled trial, 47 participants were randomly assigned to iTBS (n = 24) and rTMS (n = 23) group. Each participant received iTBS or rTMS daily at suprahyoid motor cortex of affected hemisphere for 10 consecutive days. The outcomes were assessed at baseline, immediately, and 2 weeks after intervention, including water-swallowing test, standardized swallowing assessment, Mann assessment of swallowing ability, Murray Secretion Scale, Yale Pharyngeal Residue Severity Rating Scale, Penetration-Aspiration Scale, and motor evoked potential (MEP) of bilateral suprahyoid muscle. Results: There were no significant differences between groups. There was a significant improvement on all rating scales and MEP after rTMS and iTBS. No significant differences on water-swallowing test, Mann assessment of swallowing ability, standardized swallowing assessment, Murray Secretion Scale scores, and MEP were observed between groups. In particular, there was significant differences on Penetration-Aspiration Scale scores (viscous liquid: mean difference = 1.016; 95% CI: 0.32–1.71; effect size: 0.360; P = .005) and the residue rate of pyriform fossa (viscous liquid: mean difference = 0.732; 95% CI: 0.18–1.28; effect size: 0.248; P = .010) in between-group. Comparing the differences over the changes of all rating scales, only the residue rate of epiglottis valley between groups was found to be significantly different (dilute liquid: mean difference = –0.567; 95% CI: –0.98 to –0.15; P = .009). There was no severe adverse effect and high dropout rates in both groups. Conclusion: The clinical efficacy, safety, and tolerability of iTBS showed non-inferior to 10 Hz rTMS for patients with poststroke dysphagia. The present study can be used to improve the clinicians’ knowledge and clinical decision skills on iTBS and rTMS for poststroke dysphagia.
The effects of metformin and alendronate in attenuating bone loss and improving glucose metabolism in diabetes mellitus mice

Background: To explore the anti-osteoporosis and anti-diabetes effects and potential underlying mechanisms of treatment with metformin and alendronate in diabetes mellitus mice. Methods: Eight-week-old C57 BL/KS db/db and db/+ female mice were evaluated according to the following treatment group for 12 weeks: control group, diabetes mellitus group, diabetes mellitus with metformin group, diabetes mellitus with Alendronate group, diabetes mellitus with metformin plus alendronate group. Glucose level, glucose tolerance test, bone mineral density, bone microarchitecture, bone histomorphometry, serum biomarkers, and qPCR analysis. Results: Combined metformin and alendronate can improve progression in glucose metabolism and bone metabolism, including blood glucose levels, blood glucose levels after 4 and 16 hours fasting, glucose tolerance test results, insulin sensitivity and reduces bone loss than the diabetes group. The use of alendronate alone can increase significantly serum glucagon-like peptide-1 levels than the diabetes group. The use of metformin alone can improve bone microstructure such as Tb.Sp and Tb.N of spine in diabetic mice. Conclusion: The combined use of alendronate and metformin has an anti-diabetes and anti-osteoporotic effect compared with diabetic mice, but they appear to act no obvious synergistically between alendronate and metformin.
Addressing selection bias in the UK Biobank neurological imaging cohort

The UK Biobank is a national prospective study of half a million participants between the ages of 40 and 69 at the time of recruitment between 2006 and 2010, established to facilitate research on diseases of aging. The imaging cohort is a subset of UK Biobank participants who have agreed to undergo extensive additional imaging assessments. However, Fry et al (2017) find evidence of "healthy volunteer bias" in the UK Biobank -- participants are less likely to smoke, be obese, consume alcohol daily than the target population of UK adults. Here we examine selection bias in the UK Biobank imaging cohort. We address two common misconceptions: first, that study size can compensate for bias in data collection, and second that selection bias does not affect estimates of associations, which are the primary interest of the UK Biobank. We introduce inverse probability weighting (IPW) as an approach commonly used in survey research that can be used to address selection bias in volunteer health studies like the UK Biobank. We discuss 6 such methods -- five existing and one novel --, assess relative performance in simulation studies, and apply them to the UK Biobank imaging cohort. We find that our novel method, BART for predicting the probability of selection combined with raking, performs well relative to existing methods, and helps alleviate selection bias in the UK Biobank imaging cohort.
Risk predictive tools of perioperative drug hypersensitivity reaction: A case-control study

Objective We aimed to determine the risk factors of perioperative drug hypersensitivity reaction (DHR) and develop a predictive score for use in clinical practice. Methods A case-control study was conducted in patients who underwent anesthesia at a tertiary hospital in Thailand, between 2015–2018. DHR cases were graded clinically from 1 to 4 according to the World Federation of Societies of Anesthesiologists by two anesthesiologists. Controls were randomly matched with cases (ratio 2:1) by age group and month and type of surgery. Patient and anesthesia-related factors and agents given intraoperatively were recorded. A risk score was derived from the coefficients of the significant predictors of the final multivariate logistic regression model. Risk scores, adjusted odds ratios (OR) for perioperative DHR and 95% confidence intervals (CI) were determined. Results Overall, 325 cases and 650 controls were recruited. The severity of DHR was grade 1 (72.9%), grade 2 (24%), and grade 3 (3.1%). Our risk predictive tools for perioperative DHR provided a sensitivity of 62% and specificity of 65%. Predictive scores of subgroups of moderate to severe DHR showed high specificity (80%) but low sensitivity (47%). Common predictors of overall DHR and moderate to severe DHR were history of drug allergy to 2 or more drug categories (score 2.5–3.5), being allergic to analgesics (score 2.5–4.0), and intraoperative morphine use (score of 1). The sole predictor of high-risk perioperative DHR (score ≥3.5) was airway management with an endotracheal tube intubation (OR 5.6, 95% CI 2.2–14.4) whereas history of allergic rhinitis (OR 11.7, 95% CI 1.3–105.1) was a predictor of high-risk moderate to severe DHR (score ≥2.5). Conclusions Our predictive tool for perioperative DHR provided a modest predictive ability. History of drug allergies, rhinitis, morphine use and endotracheal intubation were significant risk factors of DHR after adjusting for age and type of surgery.
A DG-IMEX Method for Two-moment Neutrino Transport: Nonlinear Solvers for Neutrino–Matter Coupling

Neutrino–matter interactions play an important role in core-collapse supernova (CCSN) explosions, as they contribute to both lepton number and/or four-momentum exchange between neutrinos and matter and thus act as the agent for neutrino-driven explosions. Due to the multiscale nature of neutrino transport in CCSN simulations, an implicit treatment of neutrino–matter interactions is desired, which requires solutions of coupled nonlinear systems in each step of the time integration scheme. In this paper, we design and compare nonlinear iterative solvers for implicit systems with energy-coupling neutrino–matter interactions commonly used in CCSN simulations. Specifically, we consider electron neutrinos and antineutrinos, which interact with static matter configurations through the Bruenn 85 opacity set. The implicit systems arise from the discretization of a nonrelativistic two-moment model for neutrino transport, which employs the discontinuous Galerkin (DG) method for phase-space discretization and an implicit–explicit (IMEX) time integration scheme. In the context of this DG-IMEX scheme, we propose two approaches to formulate the nonlinear systems: a coupled approach and a nested approach. For each approach, the resulting systems are solved with Anderson-accelerated fixed-point iteration and Newton’s method. The performance of these four iterative solvers has been compared on relaxation problems with various degrees of collisionality, as well as proto–neutron star deleptonization problems with several matter profiles adopted from spherically symmetric CCSN simulations. Numerical results suggest that the nested Anderson-accelerated fixed-point solver is more efficient than other tested solvers for solving implicit nonlinear systems with energy-coupling neutrino–matter interactions.
Human Leukocyte Antigen Homozygosity Contributes to Sensitization in Kidney Transplant Candidates

Background: Homozygosity for human leukocyte antigens (HLA) has been associated with adverse outcomes after viral infection as well as pregnancy-induced HLA sensitization. We sought to assess the relationship between HLA locus homozygosity and the level of HLA antibody sensitization. Methods: We measured sensitization using the calculated panel reactive antibody (CPRA) value for a large cohort of 147,461 patients added to the US OPTN/UNOS kidney transplant waitlist between December 2014 and December 2019. We used multinomial logistic modeling to compare 62,510 sensitized patients to 84,955 unsensitized controls. Results: We found that the number of homozygous HLA loci was strongly associated with the level of sensitization. Within highly- or extremely-sensitized candidates, women displayed a higher relative abundance of HLA homozygosity at multiple HLA loci as compared to men, with attenuation of this effect in Black candidates. In multinomial logistic modeling, the number of homozygous HLA loci was an independent predictor of sensitization and interacted with female sex but not with other factors associated with sensitization. Conclusions: This study shows that HLA homozygosity is an innate genetic factor that contributes to HLA sensitization, and enhances the effect of pregnancy-related sensitization.
Cryo-EM structures of amyloid-β 42 filaments from human brains

Description Hi-res view of human Aβ42 filaments Alzheimer’s disease is characterized by a loss of memory and other cognitive functions and the filamentous assembly of Aβ and tau in the brain. The assembly of Aβ peptides into filaments that end at residue 42 is a central event. Yang et al. used electron cryo–electron microscopy to determine the structures of Aβ42 filaments from human brain (see the Perspective by Willem and Fändrich). They identified two types of related S-shaped filaments, each consisting of two identical protofilaments. These structures will inform the development of better in vitro and animal models, inhibitors of Aβ42 assembly, and imaging agents with increased specificity and sensitivity. —SMH In Alzheimer’s disease and other conditions, two structurally related protofilaments form type I and type II Aβ42 filaments. Filament assembly of amyloid-β peptides ending at residue 42 (Aβ42) is a central event in Alzheimer’s disease. Here, we report the cryo–electron microscopy (cryo-EM) structures of Aβ42 filaments from human brains. Two structurally related S-shaped protofilament folds give rise to two types of filaments. Type I filaments were found mostly in the brains of individuals with sporadic Alzheimer’s disease, and type II filaments were found in individuals with familial Alzheimer’s disease and other conditions. The structures of Aβ42 filaments from the brain differ from those of filaments assembled in vitro. By contrast, in AppNL-F knock-in mice, Aβ42 deposits were made of type II filaments. Knowledge of Aβ42 filament structures from human brains may lead to the development of inhibitors of assembly and improved imaging agents.
Association Between Dietary Patterns and Dyslipidemia in Korean Women

Background: The prevalence of dyslipidemia among Korean women differs significantly according to menopausal status. This study aimed to identify major dietary patterns among Korean women and examine their associations with the prevalence of dyslipidemia and its components. Methods: This study recruited 6,166 women from the Cancer Screenee Cohort 2007–2019 from the National Cancer Center of Korea. Dietary patterns were identified using factor analysis. Multivariable logistic regression was performed to calculate odds ratios (ORs) and 95% confidence intervals (CIs) for the associations between dietary patterns and the prevalence of dyslipidemia and its components, including hypercholesterolemia, hypertriglyceridemia, hypo-high-density lipoprotein (HDL) cholesterol, and hyper-low-density lipoprotein (LDL) cholesterol. Stratification analyses were performed for the premenopausal and postmenopausal subgroups. Results: The factor analysis identified three main dietary patterns, including traditional, western, and prudent dietary patterns. Compared with those with the lowest pattern scores, those with the highest pattern scores of the traditional (OR = 1.32, 95% CI = 1.05–1.67) and western (OR = 1.40, 95% CI = 1.11–1.78) diets had a higher prevalence of hyper-LDL cholesterol. When accounting for menopausal status in the analysis, traditional (OR = 1.44, 95% CI = 1.10–1.89) and western (OR = 1.43, 95% CI = 1.09–1.88) diets were still associated with hyper-LDL cholesterol in postmenopausal women. Additionally, consumption of a traditional diet was associated with a decreased prevalence of hypertriglyceridemia (OR = 0.73, 95% CI = 0.54–0.99), and consumption of a western diet was associated with an increased prevalence of hypercholesterolemia (OR = 1.41, 95% CI = 1.11–1.79) but a reduced prevalence of hypo-HDL cholesterol (OR = 0.60, 95% CI = 0.36–0.99). However, the prudent dietary pattern was not significantly associated with dyslipidemia and its components in the group of all women or the subgroups according to menopausal status. Conclusion: There were significant associations between the traditional and western dietary patterns and hyper-LDL cholesterol in the entire group and postmenopausal subgroup of women. In the perspective of energy restriction, our findings recommend women not to eat either traditional or western diets excessively or too frequently. Menopause may induce the effect of both the traditional diet on triglyceride reduction and the western diet on increasing total cholesterol.
Community Acknowledgment

Volunteers in non-profit groups are a valuable workforce that contributes to economic development and supports people in need in the U.S. However, many non-profit groups face challenges including engaging and sustaining volunteer participation, as well as increasing visibility of their work in the community. To support non-profit groups' service, we explored how engaging community members in the volunteer-acknowledgment process may have an impact. We set up workstations and invited community members to write thank-you cards to volunteers in non-profit groups. We conducted 14 interviews with volunteers and community members, collected and analyzed 25 thank-you cards. We found that the acknowledgment activity can help circulate social goods through multiple stakeholders, that authenticity was valued in the acknowledgment process, and that non-profit groups intended to distribute, reuse, and publicize the acknowledgments to utilize them to a fuller extent. Our contributions include expanding knowledge on experiences, needs, and impact of community acknowledgment from different stakeholders, as well as presenting design opportunities.
Building a Pillowfort: Political Tensions in Platform Design and Policy

Social media platforms make trade-offs in their design and policy decisions to attract users and stand out from other platforms. These decisions are influenced by a number of considerations, e.g. what kinds of content moderation to deploy or what kinds of resources a platform has access to. Their choices play into broader political tensions; social media platforms are situated within a social context that frames their impact, and they can have politics through their design that enforce power structures and serve existing authorities. We turn to Pillowfort, a small social media platform, to examine these political tensions as a case study. Using a discourse analysis, we examine public discussion posts between staff and users as they negotiate the site's development over a period of two years. Our findings illustrate the tensions in navigating the politics that users bring with them from previous platforms, the difficulty of building a site's unique identity and encouraging commitment, and examples of how design decisions can both foster and break trust with users. Drawing from these findings, we discuss how the success and failure of new social media platforms are impacted by political influences on design and policy decisions.
Let's Think Together! Assessing Shared Mental Models, Performance, and Trust in Human-Agent Teams

An emerging research agenda in Computer-Supported Cooperative Work focuses on human-agent teaming and AI agent's roles and effects in modern teamwork. In particular, one understudied key question centers around the construct of team cognition within human-agent teams. This study explores the unique nature of team dynamics in human-agent teams compared to human-human teams and the impact of team composition on perceived team cognition, team performance, and trust. In doing so, a mixed-method approach, including three team composition conditions (all human, human-human-agent, human-agent-agent), completed the team simulation NeoCITIES and completed shared mental model, trust, and perception measures. Results found that human-agent teams are similar to human-only teams in the iterative development of team cognition and the importance of communication to accelerating its development; however, human-agent teams are different in that action-related communication and explicitly shared goals are beneficial to developing team cognition. Additionally, human-agent teams trusted agent teammates less when working with only agents and no other humans, perceived less team cognition with agent teammates than human ones, and had significantly inconsistent levels of team mental model similarity when compared to human-only teams. This study contributes to Computer-Supported Cooperative Work in three significant ways: 1) advancing the existing research on human-agent teaming by shedding light on the relationship between humans and agents operating in collaborative environments, 2) characterizing team cognition development in human-agent teams; and 3) advancing real-world design recommendations that promote human-centered teaming agents and better integrate the two.
Black Lives, Green Books, and Blue Checks

The Negro Motorist Green Book was a publication that offered resources for the Black traveler from 1936 to 1966. More than a directory of Black-friendly businesses, it also offered articles that provided insights for how best to travel safely, engagement with readers through contests and invitations for readers to share travel stories, and even civil rights advocacy. Today, a contemporary counterpart to the Green Book is Black Twitter, where people share information and advocate for their community. By conducting qualitative open coding on a subset of Green Book editions as well as tweets from Black Twitter, we explore similarities and overlapping characteristics such as safety, information sharing, and social justice. Where they diverge exposes how spaces like Black Twitter have evolved to accommodate the needs of people in the Black diaspora beyond the scope of physical travel and into digital spaces. Our research points to ways that the Black community has shifted from the physical to the digital space, expanding how it supports itself, and the potential for research to strengthen throughlines between the past and the present in order to better see the possibilities of the future.
Weather radar echo prediction method based on recurrent convolutional neural network

The emergence of strong convective weather has caused serious threats to people’s lives and production activities, and also caused serious damage to the ecological environment. Because this kind of weather has a short duration and a small impact area, it is difficult to be accurate predicted. Doppler weather radar is one of the devices that can sample strong convective weather continuously for a long time, and plays an extremely important role in the detection and prediction of severe weather. The prediction of radar echo intensity by using deep learning methods has largely improved the prediction accuracy of strong convective weather, but the prediction of radar echo shape change is not yet ideal, so the trend of strong convective weather cannot be accurately judged. This paper proposes a weather radar echo prediction method based on cyclic convolutional neural network, which is called the EDD model, its design was inspired by the RU_Net families of deep learning models. The feature fusion layer was added to the neural network, thus ensuring that the feature matrix contains more feature parameters and improving the problem of inaccurate prediction of radar echo shape change due to insufficient information during upsampling. The EDD model is trained using Doppler weather radar echo maps, and the experimental results show that the EDD model used in this paper can improve the prediction accuracy of radar echo intensity and make good predictions of radar echo shape changes, thus helping meteorologists to make more accurate judgments on the occurrence, development and change trends of strong convective weather.