A Learning Outcomes Assessment Analysis based on the Mathematical Modeling of RaschGSP Curve, GSM and MSM

This paper presents an educational praxis of classroom assessment in curriculum and learning outcomes of “Introduction to Education”, and constructs assessment tool and analyzes them based on the mathematical modeling, the former with Q Matrix and ISM (Interpretive Structural Modeling), the latter mainly with Nagai’s GSP (Grey S-P) Chart, RaschGSP Curve, GSM (Grey Structural Modeling) and MSM (Matrix Based Structure Modeling). It aims: (1) To use and implement numerical value as the code for processing data, (2) To analyze and diagnose based on raw numerical values, (3) To illustrate and explain in visual diagraph analysis. Moreover, it is worth mentioning that applying mathematical logic in educational research, and such tools are not in favor of the quantitative approach, rather claimed unique feature of math logic, in benefit to: (1) Interface qualitative contextual analysis and quantitative numerical characters as the whole, (2) Convert teaching-learning praxis into binary numerical data, (3) Address alternative interdisciplinary educational research

Grain Growth and Density Distribution of the Youngest Protostellar Systems

We present dust opacity spectral indexes (beta) of the youngest protostellar systems (so-called Class 0 sources), L1448 IRS 2, L1448 IRS 3, and L1157, obtained between 1.3 mm and 2.7 mm continua, using the Combined Array for Research in Millimeter-wave Astronomy (CARMA). The unprecedented compact configuration and image fidelity of CARMA allow a better detection of the dust continuum emission from Class 0 sources, with a less serious missing flux problem normally associated with interferometry. Through visibility-modeling at both 1.3 mm and 2.7 mm simultaneously, as well as image- and visibility-comparison, we show that beta of the three Class 0 sources are around or smaller than 1, indicating that dust grains have already significantly grown at the Class 0 stage. In addition, we find a radial dependence of beta, which implies faster grain growth in the denser central regions and/or dust segregation. Density distributions of the Class 0 sources are also addressed by visibility-modeling.Comment: 16 pages; to be published in Ap

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data