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

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

Bloom Filter-Based Secure Data Forwarding in Large-Scale Cyber-Physical Systems

Cyber-physical systems (CPSs) connect with the physical world via communication networks, which significantly increases security risks of CPSs. To secure the sensitive data, secure forwarding is an essential component of CPSs. However, CPSs require high dimensional multiattribute and multilevel security requirements due to the significantly increased system scale and diversity, and hence impose high demand on the secure forwarding information query and storage. To tackle these challenges, we propose a practical secure data forwarding scheme for CPSs. Considering the limited storage capability and computational power of entities, we adopt bloom filter to store the secure forwarding information for each entity, which can achieve well balance between the storage consumption and query delay. Furthermore, a novel link-based bloom filter construction method is designed to reduce false positive rate during bloom filter construction. Finally, the effects of false positive rate on the performance of bloom filter-based secure forwarding with different routing policies are discussed

IgG4-related digestive diseases: diagnosis and treatment

IgG4-related digestive diseases encompass a group of chronic inflammatory disorders characterized by autoimmune reactions and fibrosis affecting multiple digestive organs. These diseases are identified by elevated serum levels of IgG4 and the presence of IgG4-positive plasma cell infiltration in the affected sites, along with storiform fibrosis, obliterative phlebitis, and eosinophilic infiltration. Although extensive research has been conducted, a comprehensive understanding of these conditions remains elusive. Current clinical diagnosis often relies on the application of integrated diagnostic criteria for IgG4-related diseases, combined with specific organ involvement criteria. Distinguishing them from malignancies poses considerable challenges. Moreover, further investigations are required to elucidate the underlying pathogenic mechanisms and explore potential therapeutic interventions. This review provides a systematic classification of IgG4-related digestive diseases while discussing their diagnostic strategies, clinical presentations, and treatment modalities. The comprehensive insights shared herein aim to guide clinicians in their practice and contribute to the advancement of knowledge in this field