Yoxas/statistical_literacy huggingface dataset:
Mapping skills between different codes to represent numerical information, such as number symbols (i.e., verbal number words and written digits) and non-symbolic quantities, are important in the development of the concept of number. The aim of the current study is to investigate children's mapping skills by incorporating another numerical code that emerges at early stages in development, finger patterns. Specifically, the study investigates (i) the order in which mapping skills develop and the association with young children's understanding of cardinality; and (ii) whether finger patterns are processed similarly to symbolic codes or rather as non-symbolic quantities. Preschool children (3-year-olds, N = 113, Mage = 40.8 months, SDage = 3.6 months; 4-year-olds, N = 103, Mage = 52.9 months, SDage = 3.4 months) both cardinality knowers and subset-knowers, were presented with twelve tasks that assessed the mappings between number words, Arabic digits, finger patterns, and quantities. The results showed that children's ability to map symbolic numbers precedes the understanding that such symbols reflect quantities, and that children recognize finger patterns above their cardinality knowledge, suggesting that finger patterns are symbolic in essence. RESEARCH HIGHLIGHTS: Children are more accurate in mapping between finger patterns and symbols (number words and Arabic digits) than in mapping finger patterns and quantities, indicating that fingers are processed holistically as symbolic codes. Children can map finger patterns to symbols above their corresponding cardinality level even in subset-knowers. Finger patterns may play a role in the process by which children learn to map symbols to quantities. Fingers patterns' use in the classroom context may be an adequate instructional and diagnostic tool.
Mapping the neurobiology of meditation has been bolstered by functional MRI (fMRI) research, with advancements in ultra-high field 7 Tesla fMRI further enhancing signal quality and neuroanatomical resolution. Here, we utilize 7 Tesla fMRI to examine the neural substrates of meditation and replicate existing widespread findings, after accounting for relevant physiological confounds. In this feasibility study, we scanned 10 beginner meditators (N = 10) while they either attended to breathing (focused attention meditation) or engaged in restful thinking (non-focused rest). We also measured and adjusted the fMRI signal for key physiological differences between meditation and rest. Finally, we explored changes in state mindfulness, state anxiety and focused attention attributes for up to 2 weeks following the single fMRI meditation session. Group-level task fMRI analyses revealed significant reductions in activity during meditation relative to rest in default-mode network hubs, i.e., antero-medial prefrontal and posterior cingulate cortices, precuneus, as well as visual and thalamic regions. These findings survived stringent statistical corrections for fluctuations in physiological responses which demonstrated significant differences (p < 0.05/n, Bonferroni controlled) between meditation and rest. Compared to baseline, State Mindfulness Scale (SMS) scores were significantly elevated (F(3,9) = 8.16, p < 0.05/n, Bonferroni controlled) following the fMRI meditation session, and were closely maintained at 2-week follow up. This pilot study establishes the feasibility and utility of investigating focused attention meditation using ultra-high field (7 Tesla) fMRI, by supporting widespread evidence that focused attention meditation attenuates default-mode activity responsible for self-referential processing. Future functional neuroimaging studies of meditation should control for physiological confounds and include behavioural assessments.
Marked spatiotemporal variabilities in mosquito infection of arboviruses, exemplified by the transmission of West Nile virus (WNV) in America, require adaptive strategies for mosquito sampling, pool screening and data analyses. Currently there is a lack of reliable and consistent measures of risk exposure, which may compromise comparison of surveillance data. Based on quantitative reasoning, we critically examined fundamental issues regarding mosquito sampling design and estimation of transmission intensity. Two surveillance strategies were proposed, each with a distinct focus, i.e. targeted surveillance for detection of low rates of mosquito infection and extensive surveillance for evaluation of risk exposure with high levels of mosquito infection. We strongly recommend the use of indicators embodying both mosquito abundance and infection rates as measures of risk exposure. Aggregation of surveillance data over long periods of time and across broad areas obscures patterns of focal arboviral transmission. We believe that these quantitative issues, once addressed by mosquito surveillance programs, can improve the epidemiological intelligence of arbovirus transmission.
Markov chains are a class of probabilistic models that have achieved widespread application in the quantitative sciences. This is in part due to their versatility, but is compounded by the ease with which they can be probed analytically. This tutorial provides an in-depth introduction to Markov chains and explores their connection to graphs and random walks. We use tools from linear algebra and graph theory to describe the transition matrices of different types of Markov chains, with a particular focus on exploring properties of the eigenvalues and eigenvectors corresponding to these matrices. The results presented are relevant to a number of methods in machine learning and data mining, which we describe at various stages. Rather than being a novel academic study in its own right, this text presents a collection of known results, together with some new concepts. Moreover, the tutorial focuses on offering intuition to readers rather than formal understanding and only assumes basic exposure to concepts from linear algebra and probability theory. It is therefore accessible to students and researchers from a wide variety of disciplines.
Married adolescents contribute to poor maternal health indicators in many low-and middle-income countries, where restrictive social norms hinder access to, and utilisation of maternal health services. Addressing these barriers is key to improving health outcomes of young mothers and their children. This study assessed married young women's knowledge of obstetric danger signs and perceptions of the need to attend obstetric services. A cross sectional descriptive design, interviewing 1624 randomly selected married young women aged 12-25 years. Data were collected in early 2017 using an interviewer-administered questionnaire on mobile phones, and exported into a statistical software for analysis. We found low levels of knowledge of danger signs, especially those pertaining to the post-partum period. Respondents' age, literacy and household wealth were significantly associated with knowledge of danger signs across the continuum of care. Awareness of danger signs during delivery, was strongly associated with perceptions of need for antenatal care (odds ratio[OR]= 2.269; p 0.05), and delivery in a health facility (OR = 1.883; P 0.05). Most respondents believed they must wait for their husband's approval to attend a health facility when in labour. Our findings show that the low levels of knowledge of obstetric danger signs, low perceptions of the importance of facility delivery, and the need to obtain husband's permission before seeking care, are highly contextualised and reflect the socio-cultural and economic circumstances of married young women in northern Nigeria. Interventions must consider these cultural context, and include a strong male-involvement component.
Mass casualty incident (MCI) triage simulation is an increasingly useful tool for teaching triage systems to medical students, trainees, and hospital staff. MCI simulation in the prehospital setting has not yet been studied in this population. We aimed to assess the effectiveness of a prehospital MCI simulation in medical students, residents, and fellows. Our primary outcome was knowledge of the components of the triage algorithms used in MCI response. Our secondary outcome was each participant's confidence level if required to assist with or lead a MCI response. This was an observational study with pre-post surveys. We recruited 30 medical students, 14 emergency medicine (EM) residents, and four pediatric EM fellows to fill out a survey before and after a 3-h simulation session practicing the START and JumpSTART algorithms on two prehospital MCI scenarios. Overall, all groups demonstrated significant improvement in knowledge of triage colors, information needed to assign a triage color, pediatric airway management during a MCI, and indications for breaths-first CPR. They also demonstrated significant increase in confidence both in assisting with and in leading a MCI response. Simulated practice triaging patients in prehospital MCI scenarios improves knowledge of triage algorithms and increases confidence in assisting with or leading a MCI response in medical trainees.
Mass school shootings have created fear in the American public. The results of this fear have been the hardening of schools, lockdowns, and active shooter drills, yet the mass shootings have not ended. The goal of this study was to analyze the mental health awareness of K-12 public schools teachers in Texas with a goal to identify the connections between mental health awareness and school safety. Data were used from an archival database of K-12 teacher responses in the 2020 Texas Educators' Needs Assessment Regarding School Safety and Victims Services to assess the current state of student mental health concerns and the connection of these concerns to school safety. This needs assessment included one mixed methods survey that was collected from Texas K-12 educators and Texas educators working in higher education in 2020. The original study included 25,161 usable responses (6.1%). For the purpose of this study, only K-12 teacher responses were used in the analysis. The K-12 teacher participants (n = 19,888) included the following institutional levels: (a) special setting, 2,919 (14.7%); (b) elementary school, 6,813 (34.3%); (c) middle/intermediate school, 4,189 (21.1%); (d) high school, 5,864 (29.5%); and (e) district level, 103 (0.5%). A total of 8,053 participant's qualitative responses and 10 of the original quantitative survey questions from the archival data were used to identify all findings in the study. Collected qualitative and quantitative participant responses' outlined a need to improve student mental health by strengthening the focus on supporting all stakeholders (e.g., teachers, parents, counselors, and students) in mental health awareness and education. Participant comments focused on the lack of training, counselor support, and community support regarding the mental health needs of their students. Recommendations to improve student mental health that were developed from this study identified key goals in school counselor role and responsibility to student mental health, increased involvement of community agencies, and improvement to in-school mental health counseling. Final recommendations of this study were focused on the need to improve student mental health if stakeholders want to develop a positive school environment. The failure to build an environment that is focused on student mental health will continue to affect the goal to improve overall school safety.
Mass spectrometry (MS)-based proteomics workflows typically involve complex, multi-step processes, presenting challenges with sample losses, reproducibility, requiring substantial time and financial investments, and specialized skills. Here we introduce One-Tip, a proteomics methodology that seamlessly integrates efficient, one-pot sample preparation with precise, narrow-window data-independent acquisition (nDIA) analysis. One-Tip substantially simplifies sample processing, enabling the reproducible identification of >9000 proteins from ~1000 HeLa cells. The versatility of One-Tip is highlighted by nDIA identification of ~6000 proteins in single cells from early mouse embryos. Additionally, the study incorporates the Uno Single Cell Dispenser™, demonstrating the capability of One-Tip in single-cell proteomics with >3000 proteins identified per HeLa cell. We also extend One-Tip workflow to analysis of extracellular vesicles (EVs) extracted from blood plasma, demonstrating its high sensitivity by identifying >3000 proteins from 16 ng EV preparation. One-Tip expands capabilities of proteomics, offering greater depth and throughput across a range of sample types.
Mass spectrometry is routinely used for myriad applications in clinical, industrial, and research laboratories worldwide. Developments in the areas of ionization sources, high-resolution mass analyzers, tandem mass spectrometry, and ion mobility have significantly extended the repertoire of mass spectrometrists; however, for coordination compounds and supramolecules, mass spectrometry remains underexplored and arguably underappreciated. Here, the reader is guided through different tools of modern electrospray ionization mass spectrometry that are suitable for larger inorganic complexes. All steps, from sample preparation and technical details to data analysis and interpretation are discussed. The main target audience of this tutorial is synthetic chemists as well as technicians/mass spectrometrists with little experience in characterizing labile inorganic compounds.
Mass testing campaigns were proposed in France during the first wave of the COVID-19 pandemic to detect and isolate asymptomatic individuals infected by SARS-CoV-2. During mass testing in Saint-Étienne (February 2021), we performed a survey of the general population. We evaluated, on the scale of a city's population, the literacy level about SARS-CoV-2 transmission, barrier gesture respect, and isolation acceptability or possibility in case of SARS-CoV-2 infection. We used the validated CovQuest-CC questionnaire. Data were analyzed and correlated with volunteer characteristics and their SARS-CoV-2 screening results using multivariate analysis. In total, 4707 participants completed the CovQuest-CC questionnaire. Multivariate analysis revealed that female sex was a determinant of a higher score of knowledge about SARS-CoV-2 transmission (adjusted β coefficient=0.14, 95% CI 0.04-0.23; corrected P=.02). Older ages of 50-59 years (adjusted β coefficient=0.25, 95% CI 0.19-0.31; corrected P<.001) and ≥60 years (adjusted β coefficient=0.25, 95% CI 0.15-0.34; corrected P<.001) were determinants of a higher score on barrier gesture respect compared to ages 20-49 years considered as reference. Female sex was also a determinant of a higher score on barrier gesture respect (adjusted β coefficient=0.10, 95% CI 0.02-4.63; corrected P<.001). The knowledge score was correlated with the score on barrier gesture respect measures (adjusted β coefficient=0.03, 95% CI 0.001-0.004; corrected P=.001). Older ages of 50-59 years (adjusted β coefficient=0.21, 95% CI 0.13-0.29; corrected P<.001) and ≥60 years (adjusted β coefficient=0.25, 95% CI 0.1-0.38; corrected P<.001) were determinants of a higher score on isolation acceptability or possibility compared to the age of 20-49 years considered as reference. Finally, the knowledge score regarding SARS-CoV-2 transmission was significantly associated with a lower risk of RT-PCR (reverse transcriptase-polymerase chain reaction) positivity (adjusted odds ratio 0.80, 95% CI 0.69-0.94; corrected P<.03), implying that a 1-point increase in the knowledge score lowers the risk of positivity by 20% on average. This study identified factors associated with health literacy regarding SARS-CoV-2 infection in asymptomatic individuals in a large French city's population. We can confirm that in the context of the COVID-19 pandemic, the determinants of better health literacy are not the same as those in other contexts. It seems critical to obtain a more detailed understanding of the determinants of individual citizens' behavior, as part of a strategy to combat the large-scale spread of the virus. The harsh experience of this pandemic should teach us how to nurture research to structure customized interventions to encourage the adoption of ad hoc behaviors to engage citizens in adapting behaviors more favorable to their health.
Mass-casualty incidents have a significant global impact. Despite calls for improved disaster-preparedness training, most medical curriculums do not include formal disaster-medicine education. In 2021, the Medical Council of Canada introduced new disaster-medicine learning objectives. This article presents a mass-casualty-incident course for 3rd-year Canadian medical students. The course includes lectures, and a large-scale simulation of an explosion scene, field triage zone, and simulated emergency department (ED). The simulation incorporated "Dark-team-member" facilitators and 17 live actor and 8 mannequin patients with moulage. Pre-/post-event evaluation data was collected. One-hundred and twenty medical students participated in the course. Confidence in managing a real mass-casualty incident, on a scale from 1 to 10 (no-confidence to completely confident) significantly improved based on a Mann-Whitney U test, p < 0.05. Few formal medical student mass-casualty-incident courses exist. Combining "Dark-team-members" with live actors, imbedding clinician facilitators with medical students, and having a simulation with a continuous disaster scene to the ED are unique to this course. The methodology is presented for future replication.
Mastery of quantitative skills is increasingly critical for student success in life sciences, but few curricula adequately incorporate quantitative skills. Quantitative Biology at Community Colleges (QB@CC) is designed to address this need by building a grassroots consortium of community college faculty to 1) engage in interdisciplinary partnerships that increase participant confidence in life science, mathematics, and statistics domains; 2) generate and publish a collection of quantitative skills-focused open education resources (OER); and 3) disseminate these OER and pedagogical practices widely, in turn expanding the network. Currently in its third year, QB@CC has recruited 70 faculty into the network and created 20 modules. Modules can be accessed by interested biology and mathematics educators in high school, 2-year, and 4-year institutions. Here, we use survey responses, focus group interviews, and document analyses (principles-focused evaluation) to evaluate the progress in accomplishing these goals midway through the QB@CC program. The QB@CC network provides a model for developing and sustaining an interdisciplinary community that benefits participants and generates valuable resources for the broader community. Similar network-building programs may wish to adopt some of the effective aspects of the QB@CC network model to meet their objectives.
Materials exhibit an extraordinary range of visual appearances. Characterizing and quantifying appearance is important not only for basic research on perceptual mechanisms but also for computer graphics and a wide range of industrial applications. Although methods exist for capturing and representing the optical properties of materials and how they vary across surfaces (Haindl & Filip, 2013), the representations are typically very high-dimensional, and how these representations relate to subjective perceptual impressions of material appearance remains poorly understood. Here, we used a data-driven approach to characterizing the perceived appearance characteristics of 30 samples of wood veneer using a "visual fingerprint" that describes each sample as a multidimensional feature vector, with each dimension capturing a different aspect of the appearance. Fifty-six crowd-sourced participants viewed triplets of movies depicting different wood samples as the sample rotated. Their task was to report which of the two match samples was subjectively most similar to the test sample. In another online experiment, 45 participants rated 10 wood-related appearance characteristics for each of the samples. The results reveal a consistent embedding of the samples across both experiments and a set of nine perceptual dimensions capturing aspects including the roughness, directionality, and spatial scale of the surface patterns. We also showed that a weighted linear combination of 11 image statistics, inspired by the rating characteristics, predicts perceptual dimensions well.
Maternal and neonatal health are among the top prioritised agendas of global health care with due emphasis given to developing countries, where the burden is profound. Antenatal care accompanied by its recommended components is highly beneficial for both maternal health and birth outcome. The objective of this study was to identify the proportion of pregnant women who received adequate Antenatal care components and associated factors among Ethiopian women. We used a nation-wide data from Mini Ethiopian Demographic and Health Survey (MEDHS) of 2019. All women of age 15-49 and who had at least one ANC visit, who were either permanent residents of the selected households or visitors who slept in the household the night before the survey, were eligible to be interviewed. Since we utilised multilevel logistic regression model, the STATA output had two components, the fixed effect and the random effect. In our model, the fixed effect part was displayed by odds ratio while the random effect was addressed by variance and intra-cluster correlation (ICC). From the total women with at least one antenatal care (ANC) visit 55.41% (95% CI 53.60%, 57.20%) of them received adequate components of the care. In the final model after adjusting for the cluster and individual level variables, attending primary (AOR = 1.45; 95% CI: 1.15 to 1.84), secondary (AOR = 2.21; 95% CI: 1.51 to 3.24) and higher education (AOR = 2.42; 95% CI: 1.38 to 4.26) were significantly associated with higher odds of receiving adequate components of ANC. Similarly, wealth index of middle (AOR = 1.51; 95% CI: 1.06, 2.14), richer (AOR = 1.92; 95% CI: 1.32, 2.80), and richest (AOR = 3.86; 95% CI: 2.35, 6.33) compared to poorest index and having two or more ANC visits were significantly associated with receiving adequate components of ANC. On the other hand, being from Oromia region, from female headed household and protestant religion were negatively associated with receiving adequate components of ANC. The proportion of women who received adequate ANC component was much lower compared to the universal recommendation for every woman on ANC visit. Educational status, wealth index, number of ANC visit, region of residence and type of health facility were significantly associated with the odds of receiving adequate components of ANC. The government should pay attention to those without any formal education, encouraging pregnant women to receive the optimum number of ANC visits, and devising techniques to address those in poorest wealth index so that the proportion of adequate components of ANC will be increased.