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The evolution of antibiotic resistance in bacteria is a significant public health risk influenced by several factors. Switched systems can abstract the evolutionary aspects driven by antibiotic use in a given population. However, mathematical models are not perfect, and uncertain dynamics remain. Based on a set theory approach, our main result is the development of an algorithm to demonstrate the stabilizability of a robust invariant set for the uncertain switched system. The algorithm also provides a characterization of invariant regions for switched systems under perturbations. Our findings provide insights into how to incorporate uncertainties in switched systems. This paves the way for selecting antibiotics to tackle drug-resistant infections. 

STEM technician education programs face a world in which cutting-edge technologies are transforming existing industries and creating new ones at an unprecedented pace. In light of this, the NSF ATE project Preparing Technicians for the Future of Work conducted industry site interviews and regional convenings of academic partners and industry leaders representing a wide range of technical fields to learn how technology impacts technician job tasks and roles. Through these activities, the project identified three skill areas common across multiple technologies and deemed essential for future STEM technicians: data knowledge/analysis, advanced digital literacy, and business knowledge/processes. These “cross-disciplinary STEM core” skill sets and recommendations for integrating them into technical programs are described in A Framework for a Cross-Disciplinary STEM Core. To facilitate adoption of the Framework at a systemic level, the project is sharing an adoption toolkit with concrete steps a college can take, tools it can use with employers to prioritize STEM Core skill sets and faculty activities for identifying where prioritized skills are taught within existing program curriculum and instructional gaps where new cross-disciplinary skill sets could be easily integrated. 

Two regional universities have completed the first round of a three-year collaborative NSF Research Experience for Teachers grant focused on human-centered design and appropriate technology for developing countries. In this transformative research experience, teachers travel to global community partner sites to engage in learning projects aimed to enhance their understanding of engineering and intercultural awareness. Upon return from their immersion experience, the teachers complete an intensive, two-week curriculum development workshop. The teachers then pilot the resulting lesson(s) in their classroom, make revisions as necessary, and share their finalized curriculum with other STEM educators via the TeachEngineering website. Throughout the experience, teachers benefit professionally through integrated development activities and cultivate greater self-awareness and understanding of culture. First, this paper will summarize the project to date. Then, we present observations from participants’ reflections, semi-structured interview, and pre/post intercultural assessments. Next, we highlight the collaborative outreach and capacity-building efforts which resulted in a new community partner and immersion site. Finally, we discuss the unique opportunities and challenges associated with navigating international travel and immersion experiences during the COVID-19 pandemic. 

In this paper, we present improvements to the pointing accuracy of the South Pole Telescope (SPT) using machine learning. The ability of the SPT to point accurately at the sky is limited by its structural imperfections, which are impacted by the extreme weather at the South Pole. Pointing accuracy is particularly important during SPT participation in observing campaigns with the Event Horizon Telescope (EHT), which requires stricter accuracy than typical observations with the SPT. We compile a training dataset of historical observations of astronomical sources made with the SPT-3G and EHT receivers on the SPT. We train two XGBoost models to learn a mapping from current weather conditions to two telescope drive control arguments — one which corrects for errors in azimuth and the other for errors in elevation. Our trained models achieve root mean squared errors on withheld test data of 2[Formula: see text]14 in cross-elevation and 3[Formula: see text]57 in elevation, well below our goal of 5[Formula: see text] along each axis. We deploy our models on the telescope control system and perform further in situ test observations during the EHT observing campaign in April 2024. Our models result in significantly improved pointing accuracy: for sources within the range of input variables where the models are best trained, average combined pointing error improved 33%, from 15[Formula: see text]9 to 10[Formula: see text]6. These improvements, while significant, fall shy of our ultimate goal, but they serve as a proof of concept for the development of future models. Planned upgrades to the EHT receiver on the SPT will necessitate even stricter pointing accuracy which will be achievable with our methods. 

Abstract Superconducting on-chip filter banks provide a scalable, space saving solution to create imaging spectrometers at millimetre and submillimetre wavelengths. We present an easy to realise, lithographed superconducting filter design with a high tolerance to fabrication error. Using a capacitively coupled $$\lambda /2$$ λ / 2 microstrip resonator to define a narrow ( $$\lambda /\Delta \lambda = 300$$ λ / Δ λ = 300 ) spectral pass band, the filtered output of a given spectrometer channel directly connects to a lumped-element kinetic inductance detector. We show the tolerance analysis of our design, demonstrating $$<11\%$$ < 11 % change in filter quality factor to any one realistic fabrication error and a full filter-bank efficiency forecast to be 50% after accounting for fabrication errors and dielectric loss tangent. 

Neonicotinoids (NNs) are commonly found throughout the environment on surfaces such as seeds, soil, vegetation, and blowing dust particles. However, there is a paucity of data on the kinetics and oxidation products formed on contact with the atmosphere which limits understanding of their potentially far-reaching impacts. In this study, in situ attenuated total reflectance (ATR) FTIR spectroscopy was used to investigate the OH oxidation of thin films of three solid NNs, imidacloprid (IMD), dinotefuran (DNF) and clothianidin (CLD) at 295 ± 3 K. The experimentally measured reaction probabilities based on initial rates of NN loss are (1.6 ± 0.8) × 10 −2 for IMD, (1.5 ± 0.6) × 10 −2 for DNF and (0.9 ± 0.2) × 10 −2 for CLD (±1 σ ), suggesting initial NN lifetimes with respect to OH of 10–17 days. The kinetics were interpreted using a multiphase kinetics model, KM-SUB, which showed that the OH uptake and reaction occurred primarily in the surface layer. Products identified by mass spectrometry included carbonyl-, alcohol- and olefin-containing species formed via hydrogen abstraction from aliphatic C–H groups. Additionally, carbonyl-containing desnitro and urea derivative products were observed from secondary reactions of the initially formed photodegradation products. Reaction with OH will contribute to NN loss both during the day as well as at night when there are non-photolytic sources of this radical. Thus, OH reactions with both the parent neonicotinoid and its photodegradation products should be considered in assessing their environmental impacts.