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  1. Involving students in scientific modeling practice is one of the most effective approaches to achieving the next generation science education learning goals. Given the complexity and multirepresentational features of scientific models, scoring student-developed models is time- and cost-intensive, remaining one of the most challenging assessment practices for science education. More importantly, teachers who rely on timely feedback to plan and adjust instruction are reluctant to use modeling tasks because they could not provide timely feedback to learners. This study utilized machine learn- ing (ML), the most advanced artificial intelligence (AI), to develop an approach to automatically score student- drawn models and their written descriptions of those models. We developed six modeling assessment tasks for middle school students that integrate disciplinary core ideas and crosscutting concepts with the modeling practice. For each task, we asked students to draw a model and write a description of that model, which gave students with diverse backgrounds an opportunity to represent their understanding in multiple ways. We then collected student responses to the six tasks and had human experts score a subset of those responses. We used the human-scored student responses to develop ML algorithmic models (AMs) and to train the computer. Validation using newmore »data suggests that the machine-assigned scores achieved robust agreements with human consent scores. Qualitative analysis of student-drawn models further revealed five characteristics that might impact machine scoring accuracy: Alternative expression, confusing label, inconsistent size, inconsistent position, and redundant information. We argue that these five characteristics should be considered when developing machine-scorable modeling tasks.« less
    Free, publicly-accessible full text available March 1, 2023
  2. Free, publicly-accessible full text available March 18, 2023
  3. Free, publicly-accessible full text available April 1, 2023
  4. With the increased prevalence of new SARS-CoV-2 variants of concern, such as Delta and Omicron, the COVID-19 pandemic has become an ongoing human health disaster, killing millions worldwide. SARS-CoV-2 invades its host through the interaction of its spike (S) protein with a host cell receptor, angiotensin-converting enzyme 2 (ACE2). In addition, heparan sulfate (HS) on the surface of host cells plays an important role as a co-receptor for this viral pathogen–host cell interaction. Our previous studies demonstrated that many sulfated glycans, such as heparin, fucoidans, and rhamnan sulfate have anti-SARS-CoV-2 activities. In the current study, a small library of sulfated glycans and highly negatively charged compounds, including pentosan polysulfate (PPS), mucopolysaccharide polysulfate (MPS), sulfated lactobionic acid, sulodexide, and defibrotide, was assembled and evaluated for binding to the S-proteins and inhibition of viral infectivity in vitro. These compounds inhibited the interaction of the S-protein receptor-binding domain (RBD) (wild type and different variants) with immobilized heparin, a highly sulfated HS, as determined using surface plasmon resonance (SPR). PPS and MPS showed the strongest inhibition of interaction of heparin and S-protein RBD. The competitive binding studies showed that the IC50 of PPS and MPS against the S-protein RBD binding to immobilized heparin wasmore »~35 nM and ~9 nM, respectively, much lower than the IC50 for soluble heparin (IC50 = 56 nM). Both PPS and MPS showed stronger inhibition than heparin on the S-protein RBD or spike pseudotyped lentiviral particles binding to immobilized heparin. Finally, in an in vitro cell-based assay, PPS and MPS exhibited strong antiviral activities against pseudotyped viral particles of SARS-CoV-2 containing wild-type or Delta S-proteins.« less
    Free, publicly-accessible full text available February 1, 2023
  5. The COVID-19 pandemic is a major human health concern. The pathogen responsible for COVID-19, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), invades its host through the interaction of its spike (S) protein with a host cell receptor, angiotensin-converting enzyme 2 (ACE2). In addition to ACE2, heparan sulfate (HS) on the surface of host cells also plays a significant role as a co-receptor. Our previous studies demonstrated that sulfated glycans, such as heparin and fucoidans, show anti-COVID-19 activities. In the current study, rhamnan sulfate (RS), a polysaccharide with a rhamnose backbone from a green seaweed, Monostroma nitidum, was evaluated for binding to the S-protein from SARS-CoV-2 and inhibition of viral infectivity in vitro. The structural characteristics of RS were investigated by determining its monosaccharide composition and performing two-dimensional nuclear magnetic resonance. RS inhibition of the interaction of heparin, a highly sulfated HS, with the SARS-CoV-2 spike protein (from wild type and different mutant variants) was studied using surface plasmon resonance (SPR). In competitive binding studies, the IC50 of RS against the S-protein receptor binding domain (RBD) binding to immobilized heparin was 1.6 ng/mL, which is much lower than the IC50 for heparin (~750 ng/mL). RS showed stronger inhibition than heparin onmore »the S-protein RBD or pseudoviral particles binding to immobilized heparin. Finally, in an in vitro cell-based assay, RS showed strong antiviral activities against wild type SARS-CoV-2 and the delta variant.« less
    Free, publicly-accessible full text available December 1, 2022
  6. Due to its high theoretical energy density and relative abundancy of active materials, the magnesium–sulfur battery has attracted research attention in recent years. A closely related system, the lithium-sulfur battery, can suffer from serious self-discharge behavior. Until now, the self-discharge of Mg–S has been rarely addressed. Herein, we demonstrate for a wide variety of Mg–S electrolytes and conditions that Mg–S batteries also suffer from serious self-discharge. For a common Mg–S electrolyte, we identify a multi-step self-discharge pathway. Covalent S 8 diffuses to the metal Mg anode and is converted to ionic Mg polysulfide in a non-faradaic reaction. Mg polysulfides in solution are found to be meta-stable, continuing to react and precipitate as solid magnesium polysulfide species during both storage and active use. Mg–S electrolytes from the early, middle, and state-of-the-art stages of the Mg–S literature are all found to enable the self-discharge. The self-discharge behavior is found to decrease first cycle discharge capacity by at least 32%, and in some cases up to 96%, indicating this is a phenomenon of the Mg–S chemistry that deserves focused attention.