77 research outputs found
The Potential of a First LEGO League Robotics Program in Teaching 21st Century Skills: An Exploratory Study
Business and political leaders in the US call for schools to teach 21st century skills. In the meantime, researchers call for more research to develop curriculum that teach 21st century skills. In this study, the authors examine the experience of a First LEGO League (FLL) robotics team to explore the potential of FLL for teaching 21stcentury skills. We found that the program provided opportunities for learning many 21st century skills such as systems thinking, decision making, problem solving, teamwork, conflict resolution, flexibility, perseverance, and selfmanagement. We also found that instructional strategies such as modeling, coaching, scaffolding, examples and case studies were important in providing successful experience to children. For children to retain and transfer these 21stcentury skills, articulation and reflection are critical
Teachers’ Belief Changes in a Technology-Enhanced Pedagogical Laboratory
Preservice teachers who were enrolled in a technology integration course facilitated student-centered lessons to K-12 students in a pedagogical laboratory. A quantitative instrument, Teachers’ Beliefs Regarding Technology Use Survey (TBTUS), was employed to measure the impact of the pedagogical laboratory experience on preservice teachers’ beliefs regarding technology integration. The impact was largely insignificant. The qualitative data suggest that changes might be incremental and TBTUS might not be sensitive to the changes that occurred after 22-hour treatment, with only six hours of real teaching experience. Moreover, unlike vicarious experiences, personal teaching experiences may be different for each candidate, so they might have learned strategies that are unrelated to the beliefs that were measure
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Free-living human cells reconfigure their chromosomes in the evolution back to uni-cellularity
Cells of multi-cellular organisms evolve toward uni-cellularity in the form of cancer and, if humans intervene, continue to evolve in cell culture. During this process, gene dosage relationships may evolve in novel ways to cope with the new environment and may regress back to the ancestral uni-cellular state. In this context, the evolution of sex chromosomes vis-a-vis autosomes is of particular interest. Here, we report the chromosomal evolution in ~ 600 cancer cell lines. Many of them jettisoned either Y or the inactive X; thus, free-living male and female cells converge by becoming ‘de-sexualized’. Surprisingly, the active X often doubled, accompanied by the addition of one haploid complement of autosomes, leading to an X:A ratio of 2:3 from the extant ratio of 1:2. Theoretical modeling of the frequency distribution of X:A karyotypes suggests that the 2:3 ratio confers a higher fitness and may reflect aspects of sex chromosome evolution
Observation of superconductivity in the noncentrosymmetric nodal chain semimetal Ba5In4Bi5
The combination with superconductivity and topological nontrivial band
structure provides a promising route towards novel quantum states such as
topological superconductivity. Here, we report the first observation of
superconductivity (4.1 K) in Ba5In4Bi5 single crystal, a noncentrosymmetric
topological semimetal featuring nodal chain loops at the high-symmetry points R
and X. The magnetization, resistivity, and specific heat capacity measurements
reveal that Ba5In4Bi5 is a moderately coupled type-II Bardeen-Cooper-Schrieffer
superconductor. Bulk superconductivity is suggested from the magnetic
susceptibility and specific heat measurements. The results show that Ba5In4Bi5
provides a new platform for exploring the relationship of superconductivity and
topological nontrivial band topology
Characterization and fine mapping of a novel barley Stage Green-Revertible Albino Gene (HvSGRA) by Bulked Segregant Analysis based on SSR assay and Specific Length Amplified Fragment Sequencing
The Genome of Ganderma lucidum Provide Insights into Triterpense Biosynthesis and Wood Degradation
BACKGROUND: Ganoderma lucidum (Reishi or Ling Zhi) is one of the most famous Traditional Chinese Medicines and has been widely used in the treatment of various human diseases in Asia countries. It is also a fungus with strong wood degradation ability with potential in bioenergy production. However, genes, pathways and mechanisms of these functions are still unknown. METHODOLOGY/PRINCIPAL FINDINGS: The genome of G. lucidum was sequenced and assembled into a 39.9 megabases (Mb) draft genome, which encoded 12,080 protein-coding genes and ∼83% of them were similar to public sequences. We performed comprehensive annotation for G. lucidum genes and made comparisons with genes in other fungi genomes. Genes in the biosynthesis of the main G. lucidum active ingredients, ganoderic acids (GAs), were characterized. Among the GAs synthases, we identified a fusion gene, the N and C terminal of which are homologous to two different enzymes. Moreover, the fusion gene was only found in basidiomycetes. As a white rot fungus with wood degradation ability, abundant carbohydrate-active enzymes and ligninolytic enzymes were identified in the G. lucidum genome and were compared with other fungi. CONCLUSIONS/SIGNIFICANCE: The genome sequence and well annotation of G. lucidum will provide new insights in function analyses including its medicinal mechanism. The characterization of genes in the triterpene biosynthesis and wood degradation will facilitate bio-engineering research in the production of its active ingredients and bioenergy
Antisense expression of Gossypium barbadense UGD6 in Arabidopsis thaliana significantly alters cell wall composition
Leaf-trait relationships of Quercus liaotungensis along an altitudinal gradient in Dongling Mountain, Beijing
Desenvolvimento e implementação de um ambiente virtual de aprendizagem na área da saúde: uma experiência de pesquisa baseada em design
Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States
Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks
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