Modeling a Pandemic: Investigating Student Learning about Disease Spread in the Context of Agent-Based Modeling

The COVID-19 pandemic has highlighted a need for students to learn about public health issues, including the transmission of disease and methods for the prevention of epidemics. This study presents data from a project focused on developing computational microworlds to help middle school students learn about these topics. The microworld is designed to help students model and test their ideas about how a disease spreads through a population and how an epidemic can be prevented. I employed a lab-based case study approach to conduct one-on-one 1.5-hour interviews through Zoom with four middle-school students (ages 12-14). During the interview, the student was asked questions about the spread and prevention of disease and then invited to model and test their ideas in the microworld. This study presents an analysis of students’ pre and post instructional knowledge of disease spread and prevention, which they shared while constructing their initial and later models. I present student ideas in categories of disease transmission, recovery from disease, and disease protection strategies. The paper also analyzes students’ knowledge refinement through the building, testing, and debugging of a disease spread and prevention model. I model student refinement of thinking through steps of building initial models and predicting results, testing initial models, making sense of the results, debugging and retesting models, observing final models, and explaining results, resulting in three types of thinking shifts, and two types of thinking refinements. My findings suggest middle school students can learn about strategies for disease prevention through computational modeling

Investigating Student Learning About Disease Spread and Prevention in the Context of Agent-Based Computational Modeling

The COVID-19 pandemic has highlighted a need to help students learn about public health issues, including the transmission of disease and methods for the prevention of epidemics. This study presents data from a project aimed at developing a computational modeling microworld to help middle school students learn about the spread of disease. The microworld is meant to help students model and test their ideas about how a disease spreads through a population and how an epidemic can be prevented. I employed a lab-based case study approach to conduct one-on-one 1.5-hour interviews through Zoom with four middle school students (ages 12-14). During the interview, the student was asked questions about the spread and prevention of disease and then invited to model and test their ideas in the microworld. I conducted a micro genetic analysis to produce a temporal decomposition of students’ trajectory of thinking with respect to disease prevention and protection strategies. We model student refinement of thinking through steps of building initial models and predicting results, testing initial models and making sense of the results, debugging and retesting models, observing final models, and explaining results. Our findings suggest adolescents can learn about strategies for disease prevention through computational modeling. https://youtu.be/7BavA-rB4g

Evaluating the influence of environmental R&D on the SO2 intensity in China: evidence from dynamic spatial Durbin model analysis

Green technology is a significant means to improve the environment and achieve sustainable development goals. According to the data of Chinese provincial panel from 2000 to 2016, our study investigated the spatial effect of environmental research and development (R&D) activities on SO2 intensity using the dynamic spatial Durbin model. First, SO2 intensity in China was shown to have obvious spatial correlation, strong path dependence, and spatial agglomeration features of ‘high-high’ as well as ‘low-low’. Second, both in the short- and long-term, environmental R&D activities had an essential negative influence on local SO2 intensity, but no significant effect on SO2 intensity in the neighbouring areas, indicating that the SO2 intensity reduction effect of environmental R&D activities was confined to local areas. Moreover, the long-term effect of environmental R&D activities on SO2 intensity was not enhanced, indicating that China’s existing green technology is insufficient, which hinders the spillover influences of environmental R&D activities. Third, the short- as well as long-term effects of practical-type R&D on SO2 intensity were significantly negative, indicating that practical-type R&D can effectively reduce SO2 intensity. Inventiontype R&D had a significant negative effect on local SO2 intensity, but no significant effect on neighbouring areas

Two weight inequality for Hankel form on weighted Bergman spaces induced by doubling weights

The boundedness of the small Hankel operator $h_f^\nu(g)=P_\nu(f\bar{g})$, induced by an analytic symbol $f$ and the Bergman projection $P_\nu$ associated to $\nu$, acting from the weighted Bergman space A^p_\om to $A^q_\nu$ is characterized on the full range $0<p,q<\infty$ when $\omega,\nu$ belong to the class $\mathcal{D}$ of radial weights admitting certain two-sided doubling conditions. Certain results obtained are equivalent to the boundedness of bilinear Hankel forms, which are in turn used to establish the weak factorization $A_{\eta}^{q}=A_{\omega}^{p_{1}}\odot A_{\nu}^{p_{2}}$, where $1<q,p_{1},p_{2}<\infty$ such that $q^{-1}=p_{1}^{-1}+p_{2}^{-1}$ and $\widetilde{\eta}^{\frac{1}{q}}\asymp\widetilde{\omega}^{\frac{1}{p_{1}}}\widetilde{\nu}^{\frac{1}{p_{2}}}$. Here $\widetilde{\tau}(r)=\int_r^1\tau(t)\,dt/(1-t)$ for all $0\le r<1$

Possibility of generating the Λc3^3_{\Lambda_c}H in the quark-delocalization color-screening model

We probe the existence of the $^3_{\Lambda_c}$H where the $N\Lambda_c$ potentials are derived from the quark-delocalization color-screening model (QDCSM). The $N\Lambda_c$ system is studied and the $N\Lambda_c$ scattering length so as the effective range are obtained in the QDCSM. We construct effective Gaussian-type $N\Lambda_c$ potentials which reproduce the $N\Lambda_c$ scattering data given by the QDCSM. By solving the $NN\Lambda_c$ three body Schr\"odinger equation with the Gaussian expansion method, we calculate the energies of the $^3_{\Lambda_c}$H with isospin $I=0$, $J^P=1/2^+$ and $I=0$, $J^P=3/2^+$ under different color screening parameter $\mu$. The $J^P=1/2^+$ and $J^P=3/2^+$ states are both bound when the color screening parameter $\mu$ is set to 1.0 or 1.2, where the $J^P=1/2^+$ state is bound by $0.08\sim0.85$ MeV and the $J^P=3/2^+$ state is bound by $0.15\sim1.31$ MeV with respect to the deuteron-$\Lambda_c$ threshold.Comment: 7 pages, 6 gigure