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1. A Comparison between Analog Ensemble and Convolutional Neural Network Empirical-Statistical Downscaling Techniques for Reconstructing High-Resolution Near-Surface Wind

   https://doi.org/10.3390/en15051718  

   Rozoff, Christopher M.; Alessandrini, Stefano (March 2022, Energies)

   Empirical-statistical downscaling (ESD) can be a computationally advantageous alternative to dynamical downscaling in representing a high-resolution regional climate. Two distinct strategies of ESD are employed here to reconstruct near-surface winds in a region of rugged terrain. ESD is used to reconstruct the innermost grid of a multiply nested mesoscale model framework for regional climate downscaling. An analog ensemble (AnEn) and a convolutional neural network (CNN) are compared in their ability to represent near-surface winds in the innermost grid in lieu of dynamical downscaling. Downscaling for a 30 year climatology of 10 m April winds is performed for southern MO, USA. Five years of training suffices for producing low mean absolute error and bias for both ESD techniques. However, root-mean-squared error is not significantly reduced by either scheme. In the case of the AnEn, this is due to a minority of cases not producing a satisfactory representation of high-resolution wind, accentuating the root-mean-squared error in spite of a small mean absolute error. Homogeneous comparison shows that the AnEn produces smaller errors than the CNN. Though further tuning may improve results, the ESD techniques considered here show that they can produce a reliable, computationally inexpensive method for reconstructing high-resolution 10 m winds over complex terrain. 

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2. A Co-Instructional Model to Develop High School CS Teachers in Historically Underrepresented Communities: Building Capacity with a Purpose

   https://doi.org/10.1145/3653666.3656067  

   Lapetina, Andrew; Hill, Richard; Yadav, Aman; Lachney, Michael; Allen_Kuyenga, Madison (May 2024, ACM)

   Many secondary school teachers in historically lower performing districts find themselves asked to teach CS without adequate training. They find themselves struggling to build a CS program without the environment necessary to foster student engagement and success. To improve educator preparedness, and transform school cultures, Innovating Detroit’s Robotics Agile Workforce (iDRAW) offers one year of co-instruction by a university instructor with a high school teacher to better prepare the teacher to provide rigorous CS instruction independently in future years. Reflections from this university co-instructor are contained, with insights into the preparation of CS teachers and initiation of CS courses in high schools in the future. 

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3. Internal-Distributed CDM ESD Protection

   https://doi.org/10.1109/EDTM50988.2021.9421054  

   Di, Mengfu; Pan, Zijin; Li, Cheng; Wang, Albert (January 2021, Proc. IEEE Electron Devices Technology and Manufacturing Conference (EDTM))

   CDM ESD protection is a major ESD protection design challenge for advanced ICs, often suffering from random design failures. It was recently reported that the traditional pad-based CDM ESD protection method is fundamentally faulty, contributing to design uncertainties in CDM ESD testing and field failures. This paper reports a novel internally distributed CDM ESD protection method to overcome this major design challenge, which was validated using an internal-CDM-protected oscillator IC implemented in a foundry 45nm SOI CMOS technology. ESD protection is required for all systems. 

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4. Using technology in representing practice to support preservice teachers’ quality questioning: The roles of noticing in improving practice

   Walkoe, J. and (January 2018, Journal of technology and teacher education)

   Calls for a “practice-based” approach to teacher education have become common in scholarship on teacher education, and preservice-teaching (PST) mathematics programs are increasingly heeding this call. Practice-based teacher education (PBTE) moves beyond standard approaches to teacher education in which PSTs learn about teaching in ways they are then expected to apply in practice and toward an approach that provides PSTs opportunities to gain experience in particular core practices in ways that approximate enactment in the classroom. A growing body of research suggests that teachers’ responses, including the questions they ask, can help students’ develop content knowledge and proficiency in mathematics and science practices in the classroom. However, despite evidence that PSTs can notice students’ thinking in various activities in their preparation programs, it is not clear that they are sufficiently well-prepared to propose quality responses before entering the classroom. In this paper, we describe two different approaches that we have taken to provide support for quality teacher questioning in the LessonSketch environment. From our results, we develop a hypothesis that a pedagogical approach that primes novices to notice model questioning can support a stance of focusing on the substance of students’ thinking and probing rather than guiding students’ thinking in their proposed questions. 

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5. Electrostatic Spray Disinfection Using Nano-Engineered Solution on Frequently Touched Surfaces in Indoor and Outdoor Environments

   Tanya Purwar 1, * (May 2022, International journal of environmental research and public health)

   Paul B. Tchounwou (Ed.)

   Abstract: The COVID-19 pandemic has resulted in high demand for disinfection technologies. However, the corresponding spray technologies are still not completely optimized for disinfection purposes. There are important problems, like the irregular coverage and dripping of disinfectant solutions on hard and vertical surfaces. In this study, we highlight two major points. Firstly, we discuss the effectiveness of the electrostatic spray deposition (ESD) of nanoparticle-based disinfectant solutions for systematic and long-lasting disinfection. Secondly, we show that, based on the type of material of the substrate, the effectiveness of ESD varies. Accordingly, 12 frequently touched surface materials were sprayed using a range of electrostatic spray system parameters, including ion generator voltage, nozzle spray size and distance of spray. It was observed that for most cases, the surfaces become completely covered with the nanoparticles within 10 s. Acrylic, Teflon, PVC, and polypropylene surfaces show a distinct effect of ESD and non-ESD sprays. The nanoparticles form a uniform layer with better surface coverage in case of electrostatic deposition. Quantitative variations and correlations show that 1.5 feet of working distance, an 80 μm spray nozzle diameter and an ion generator voltage of 3–7 kV ensures a DEF (differential electric field) that corresponds to an optimized charge-to-mass ratio, ensuring efficient coverage of nanoparticles. 

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