Yoxas/statistical_literacy huggingface dataset:
We explored the home learning environments of 173 Mexican preschool children (aged 3-6 years) in relation to their numeracy performance. Parents indicated the frequency of their formal home numeracy and literacy activities, and their academic expectations for children's numeracy and literacy performance. Children completed measures of early numeracy skills. Mexican parent-child dyads from families with either high- or low-socioeconomic status (SES) participated. Low-SES parents (n = 99) reported higher numeracy expectations than high-SES parents (n = 74), but similar frequency of home numeracy activities. In contrast, high-SES parents reported higher frequency of literacy activities. Path analyses showed that operational (i.e., advanced) numeracy activities were positively related to children's numeracy skills in the high- but not in the low-SES group. These findings improve the understanding of the role of the home environment in different contexts and provide some insights into the sources of the variable patterns of relations between home learning activities and children's numeracy outcomes. They also suggest that SES is a critical factor to consider in research on children's home numeracy experiences.
We explored the structural and functional changes of the healthy hemisphere of the brain after surgery in children with intracranial space-occupying lesions. We enrolled 32 patients with unilateral intracranial space-occupying lesions for brain imaging and cognitive assessment. Voxel-based morphometry and surface-based morphometry analyses were used to investigate the structural images of the healthy hemisphere. Functional images were analyzed using regional homogeneity, amplitude of low-frequency fluctuations, and fractional-amplitude of low-frequency fluctuations. Voxel-based morphometry and surface-based morphometry analysis used the statistical model built into the CAT 12 toolbox. Paired t-tests were used for functional image and cognitive test scores. For structural image analysis, we used family-wise error correction of peak level (p < 0.05), and for functional image analysis, we use Gaussian random-field theory correction (voxel p < 0.001, cluster p < 0.05). We found an increase in gray matter volume in the healthy hemisphere within six months postoperatively, mainly in the frontal lobe. Regional homogeneity and fractional-amplitude of low-frequency fluctuations also showed greater functional activity in the frontal lobe. The results of cognitive tests showed that psychomotor speed and motor speed decreased significantly after surgery, and reasoning increased significantly after surgery. We concluded that in children with intracranial space-occupying lesions, the healthy hemisphere exhibits compensatory structural and functional effects within six months after surgery. This effect occurs mainly in the frontal lobe and is responsible for some higher cognitive compensation. This may provide some guidance for the rehabilitation of children after brain surgery.
We have prepared thousands of future STEM faculty around the world to adopt evidence-based instructional practices through their participation in two massive open online courses (MOOCs) and facilitated in-person learning communities. Our novel combination of asynchronous online and coordinated, structured face-to-face learning community experiences provides flexible options for STEM graduate students and postdoctoral fellows to pursue teaching professional development. A total of 14,977 participants enrolled in seven offerings of the introductory course held 2014-2018, with 1,725 participants (11.5% of enrolled) completing the course. Our results of high levels of engagement and learning suggest that leveraging the affordances of educational technologies and the geographically clustered nature of this learner demographic in combination with online flexible learning could be a sustainable model for large scale professional development in higher education. The preparation of future STEM faculty makes an important difference in establishing high-quality instruction that meets the diverse needs of all undergraduate students, and the initiative described here can serve as a model for increasing access to such preparation.
We have shown that use of Team-based learning (TBL) in a first-year Infectious Diseases (ID) course improved final examination and course performance. Therefore, we implemented TBL in the second-year Women's Health (WH) course to improve acquisition of course content. We hypothesized that prior experience with TBL in the first-year of medical school would lead to a strong correlation between TBL performance in the first and second years. Our study is a retrospective review of student TBL and final examination performance in the ID and WH courses. The ID course has weekly TBL exercises that cover all course material, while the WH course has one TBL that covers a small portion of the course material. Final examination and TBL individual readiness assurance test (iRAT) scores in the ID and WH courses from three classes (n = 226) were obtained with institutional review board approval. Statistical analyses were performed including comparisons of means and correlation studies. Average WH iRAT scores were significantly higher than ID iRAT scores (9.19 vs. 7.40,p < 0.01), and iRAT scores in both courses were highly correlated (r = 0.35,p < 0.01). When stratifying students based on WH course performance, in struggling students, iRAT but not final examination scores were higher in the WH course than the ID course (8.73 vs. 7.00,p < 0.01 and 82.45 vs. 80.51,p > 0.05, respectively). Our results suggest that prior experience with TBL improves TBL iRAT scores, especially in struggling students. Prior TBL experience is also associated with consistent iRAT performance between first- and second-year courses in high performing students.
We hypothesize that children characterized by deprived factors have poorer health outcomes. We aim to identify clustering of determinants and estimate risk of early childhood diseases. This 1993-2019 longitudinal cohort study combines three Canadian pediatric cohorts and their families. Mothers and children are clustered using latent class analysis (LCA) by 16 indicators in three domains (maternal and newborn; socioeconomic status [SES] and neighbourhood; environmental exposures). Hazard ratios (HR) of childhood asthma, allergic rhinitis (AR), and eczema are quantified with Cox proportional hazard (PH) regression. Rate ratios (RR) of children's health services use (HSU) are estimated with Poisson regression. Here we report the inclusion of 15,724 mother-child pairs; our LCA identifies four mother-clusters. Classes 1 and 2 mothers are older (30-40 s), non-immigrants with university education, living in high SES neighbourhoods; Class 2 mothers have poorer air quality and less greenspace. Classes 3 and 4 mothers are younger (20-30 s), likely an immigrant/refugee, with high school-to-college education, living in lower SES neighborhoods with poorer air quality and less greenspace. Children's outcomes differ by Class, in comparison to Class 1. Classes 3 and 4 children have higher risks of asthma (HR 1.24, 95% CI 1.11-1.37 and HR 1.39, 95% CI 1.22-1.59, respectively), and similar higher risks of AR and eczema. Children with AR in Class 3 have 20% higher all-cause physician visits (RR = 1.20, 95% CI 1.10-1.30) and those with eczema have 18% higher all-cause emergency department visits (RR = 1.18, 95% CI 1.09-1.28) and 14% higher all-cause physician visits (RR = 1.14, 95% CI 1.09-1.19). Multifactorial-LCA mother-clusters may characterize associations of children's health outcomes and care, adjusting for interrelationships.
We hypothesized that reticence to address a groin mass may result in late presentation of testicular/paratesticular malignancy in early puberty through adolescence. Malignant testicular and paratesticular tumors (malignant germ cell tumors and rhabdomyosarcomas) diagnosed at our institution from 1994-2023 for patients aged 11-20 were included. Clinicopathologic features were recorded, and statistically analyzed. Eighty-five cases were identified. Patient ages ranged from 11 to 20 years (mean 17 years, median 16 years). The greatest tumor dimension ranged from 0.8 to 18.0 cm (mean 4.4 cm, median 3.5 cm). Ten tumors (11.8% of cases) were ≥10.0 cm. In the 11-13-year-old age group, 100% of tumors (3/3) were ≥10 cm. The proportion of tumors ≥10 cm was significantly higher in the 11-13-year-old age group than in either the 14-16-year-old (P<0.001) or 17-20-year-old (P<0.001) age groups. This adolescent cohort with malignant testicular and paratesticular tumors showed a high proportion (11.8%) of very large (≥10 cm) tumors. Although the reasons are unknown and likely multifactorial, this study suggests that adolescents, particularly the 11-13 year age group, are a vulnerable population.
We hypothesized that some metabolic factors, lifestyle factors, and socioeconomic factors may have a causal effect on pelvic organ prolapse (POP). We selected instruments from corresponding genome-wide association studies (GWAS), which identified independent single nucleotide polymorphisms strongly associated with 12 potential risk factors. Summary statistics for POP were derived from two GWAS datasets, serving for discovery and replication stage. The primary analysis involved the use of the inverse-variance weighting mendelian randomization (MR) method, with additional sensitivity MR analyses conducted. The univariable mendelian randomization (UVMR) analysis in both the discovery and replication stage provided evidence for significant causal effects between higher waist-to-hip ratio adjusted for body mass index (WHRadjBMI) levels, lower high-density lipoprotein cholesterol (HDL-C) levels, and lower educational attainment and higher POP risk, as well as a suggestive positive causal effect between triglycerides and POP. The multivariable mendelian randomization (MVMR) analysis showed that only HDL-C among the three blood lipid fractions could reduce the risk of POP. Mediation analysis indicated that HDL-C may partially mediate the effect of WHRadjBMI on POP risk, and the causal effect between educational attainment and POP may be mediated through WHRadjBMI and HDL-C. Our study's evidence supported a causal relationship between WHRadjBMI, triglycerides, HDL-C, educational attainment, and POP risk. This highlights that clinicians may guide the general female population to control obesity and blood lipid levels to reduce the risk of POP.
We introduce Chalkboard, a prototype tool for representing and displaying cell-signaling pathway knowledge, for carrying out simple qualitative reasoning over these pathways, and for generating quantitative biosimulation code. The design of Chalkboard has been driven by the need to quickly model and visualize alternative hypotheses about uncertain pathway knowledge. Chalkboard allows the biologists to test in silico the implications of various hypotheses. To fulfill this need, chalkboard includes (1) a rich ontology of pathway entities and interactions, which is ultimately informed by the basic chemistry and physics among molecules, and (2) a form of qualitative reasoning that computes causal chains and feedback loops within the network of entities and reactions. We demonstrate Chalkboard's capabilities in the domain of APP proteolysis, a pathway that plays a key role in the pathogenesis of Alzheimer's disease. In this pathway (as is common), information is incomplete and parts of the pathways are conjectural, rather than experimentally verified. With Chalkboard, we can carry out in silico perturbation experiments and explore the consequences of different conjectural connections and relationships in the network. We believe that pathway reasoning capabilities and in silico experiments will become a critical component of the hypothesis generation phase of modern biological research.
We introduce the Weak-form Estimation of Nonlinear Dynamics (WENDy) method for estimating model parameters for non-linear systems of ODEs. Without relying on any numerical differential equation solvers, WENDy computes accurate estimates and is robust to large (biologically relevant) levels of measurement noise. For low dimensional systems with modest amounts of data, WENDy is competitive with conventional forward solver-based nonlinear least squares methods in terms of speed and accuracy. For both higher dimensional systems and stiff systems, WENDy is typically both faster (often by orders of magnitude) and more accurate than forward solver-based approaches. The core mathematical idea involves an efficient conversion of the strong form representation of a model to its weak form, and then solving a regression problem to perform parameter inference. The core statistical idea rests on the Errors-In-Variables framework, which necessitates the use of the iteratively reweighted least squares algorithm. Further improvements are obtained by using orthonormal test functions, created from a set of [Formula: see text] bump functions of varying support sizes.We demonstrate the high robustness and computational efficiency by applying WENDy to estimate parameters in some common models from population biology, neuroscience, and biochemistry, including logistic growth, Lotka-Volterra, FitzHugh-Nagumo, Hindmarsh-Rose, and a Protein Transduction Benchmark model. Software and code for reproducing the examples is available at https://github.com/MathBioCU/WENDy .
We introduce the Weak-form Estimation of Nonlinear Dynamics (WENDy) method for estimating model parameters for non-linear systems of ODEs. Without relying on any numerical differential equation solvers, WENDy computes accurate estimates and is robust to large (biologically relevant) levels of measurement noise. For low dimensional systems with modest amounts of data, WENDy is competitive with conventional forward solver-based nonlinear least squares methods in terms of speed and accuracy. For both higher dimensional systems and stiff systems, WENDy is typically both faster (often by orders of magnitude) and more accurate than forward solver-based approaches. The core mathematical idea involves an efficient conversion of the strong form representation of a model to its weak form, and then solving a regression problem to perform parameter inference. The core statistical idea rests on the Errors-In-Variables framework, which necessitates the use of the iteratively reweighted least squares algorithm. Further improvements are obtained by using orthonormal test functions, created from a set of C-infinity bump functions of varying support sizes. We demonstrate the high robustness and computational efficiency by applying WENDy to estimate parameters in some common models from population biology, neuroscience, and biochemistry, including logistic growth, Lotka-Volterra, FitzHugh-Nagumo, Hindmarsh-Rose, and a Protein Transduction Benchmark model. Software and code for reproducing the examples is available at (https://github.com/MathBioCU/WENDy).
We investigate actinide covalency effects in two [AnCptt3] (An = Th, U) complexes recently studied with pulsed electron paramagnetic resonance spectroscopy, using the Hyperion package to obtain relativistic hyperfine coupling constants from relativistic multiconfigurational wave functions. 1H and 13C HYSCORE simulations using the computed parameters show excellent agreement with the experimental data, highlighting the accuracy of modern relativistic ab initio methods. The extent of covalency indicated from the calculations on [ThCptt3] is in agreement with the original report based on traditional spectral fitting methods, while the covalency in [UCptt3] is found to be previously overestimated. The latter is due to the paramagnetic spin-orbit effect that arises naturally in a relativistic theory of hyperfine coupling and yet was not accounted for in the original study, thus highlighting the necessity of relativistic approaches for the interpretation of magnetic resonance data pertaining to actinides.
We investigate number and arithmetic learning among a Bolivian indigenous people, the Tsimane', for whom formal schooling is comparatively recent in history and variable in both extent and consistency. We first present a large-scale meta-analysis on child number development involving over 800 Tsimane' children. The results emphasize the impact of formal schooling: Children are only found to be full counters when they have attended school, suggesting the importance of cultural support for early mathematics. We then test especially remote Tsimane' communities and document the development of specialized arithmetical knowledge in the absence of direct formal education. Specifically, we describe individuals who succeed on arithmetic problems involving the number five-which has a distinct role in the local economy-even though they do not succeed on some lower numbers. Some of these participants can perform multiplication with fives at greater accuracy than addition by one. These results highlight the importance of cultural factors in early mathematics and suggest that psychological theories of number where quantities are derived from lower numbers via repeated addition (e.g., a successor function) are unlikely to explain the diversity of human mathematical ability.
We investigate the collisions of different alcohol molecules with hydrated nitric acid clusters using a molecular beam experiment and molecular dynamics simulations. The uptake cross sections σp for the molecules evaluated from the experiment are in excellent agreement with the simulations. This suggests that (i) the nontrivial assumptions implemented in the evaluation procedure of the experimental data are valid, and (ii) the simulations describe correctly the major processes in the molecule-cluster collisions. We observe that σp decreases with the increasing alkyl chain length of the alcohol, and also with the branching of the molecules that have the same mass but different structures. These systematic trends can be rationalized based on the accessibility of the hydrophilic OH group, which decreases with the increasing chain length and steric hindrance. The observed trends and their interpretation differ significantly from the simple model of hard-sphere collisions. The obtained data shall be beneficial not only for the fundamental understanding of the molecule-cluster collisions, but also in the modelling of atmospheric new-particle formation and aerosol growth.
We investigated 2018 gestational diabetes mellitus (GDM) prevalence estimates in three surveillance systems (National Vital Statistics System, State Inpatient Database, and Pregnancy Risk Assessment Monitoring Survey). We calculated GDM prevalence for jurisdictions represented in each system; a subset of data was analyzed for people 18-39 years old in 22 jurisdictions present in all three systems to observe dataset-specific demographics and GDM prevalence using comparable categories. GDM prevalence estimates varied widely by data system and within the data subset despite comparable demographics. Understanding the differences between GDM surveillance data systems can help researchers better identify people and places at higher risk of GDM.
We investigated associations between neighborhood racial/ethnic segregation and cognitive change. We used data (n = 1712) from the Multi-Ethnic Study of Atherosclerosis. Racial/ethnic segregation was assessed using Getis-Ord (Gi*) z-scores based on American Community Survey Census tract data (higher Gi* = greater spatial clustering of participant's race/ethnicity). Global cognition and processing speed were assessed twice, 6 years apart. Adjusted multilevel linear regression tested associations between Gi* z-scores and cognition. Effect modification by race/ethnicity, income, education, neighborhood socioeconomic status, and neighborhood social support was tested. Participants were on average 67 years old; 43% were White, 11% Chinese, 29% African American/Black, 17% Hispanic; 40% had high neighborhood segregation (Gi* > 1.96). African American/Black participants with greater neighborhood segregation had greater processing speed decline in stratified analyses, but no interactions were significant. Segregation was associated with greater processing speed declines among African American/Black participants. Additional follow-ups and comprehensive cognitive batteries may further elucidate these findings. A study of neighborhood racial/ethnic segregation and change in cognition. Study was based on a racially and geographically diverse, population-based cohort of older adults. Racial/ethnic segregation (clustering) was measured by the Getis-ord (Gi*) statistic. We saw faster processing speed decline among Black individuals in segregated neighborhoods.
We investigated cognitive profiles among diverse, middle-aged and older Hispanic/Latino adults in the Study of Latinos-Investigation of Neurocognitive Aging (SOL-INCA) cohort using a cross-sectional observational study design. Based on weighted descriptive statistics, the average baseline age of the target population was 56.4 years, slightly more than half were women (54.6%), and 38.4% reported less than a high school education. We used latent profile analysis of demographically adjusted z scores on SOL-INCA neurocognitive tests spanning domains of verbal memory, language, processing speed, and executive function. Statistical fit assessment indices combined with clinical interpretation suggested five profiles: (1) a Higher Global group performing in the average-to-high-average range across all cognitive and instrumental activity of daily living (IADL) tests (13.8%); (2) a Higher Memory group with relatively high performance on memory tests but average performance across all other cognitive/IADL tests (24.6%); (3) a Lower Memory group with relatively low performance on memory tests but average performance across all other cognitive/IADL tests (32.8%); (4) a Lower Executive Function group with relatively low performance on executive function and processing speed tests but average-to-low-average performance across all other cognitive/IADL tests (16.6%); and (5) a Lower Global group performing low-average-to-mildly impaired across all cognitive/IADL tests (12.1%). Our results provide evidence of heterogeneity in the cognitive profiles of a representative, community-dwelling sample of diverse Hispanic/Latino adults. Our analyses yielded cognitive profiles that may assist efforts to better understand the early cognitive changes that may portend Alzheimer's disease and related dementias among diverse Hispanics/Latinos. The present study characterized cognitive profiles among diverse middle-aged and older Hispanic/Latino adults.Latent profile analysis of neurocognitive test scores was the primary analysis conducted.The target population consists of middle-aged and older Hispanic/Latino adults enrolled in the Hispanic Community Health Study/Study of Latinos and ancillary Study of Latinos - Investigation of Neurocognitive Aging.