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Abstract To overcome the spatial resolution limit set by aperture-limited diffraction in traditional scanning transmission electron microscopy, microscopists have developed ptychography enabled by iterative phase retrieval algorithms and high-dynamic-range pixel array detectors. Current detector designs are limited by the data rate off chip, so a high-pixel-count detector has a proportionally lower frame rate than the few-segment detectors used for differential phase contrast (DPC) imaging. This slower acquisition speed leads to heightened vulnerability to scan noise, drift, and potential sample damage. This creates opportunities for repurposing fast segmented detectors for ptychography by trading a reduction in reciprocal space pixels for an increase in real space pixels. Here, we explore a strategy of oversampling in real space and instead apply detector pixel upsampling during the reconstruction process. We demonstrate the viability of achieving super-resolution ptychography on thin objects using only 2 × 2 detector pixels, surpassing the resolution of integrated DPC (iDPC) imaging. With optimization using simulated datasets and experiments on MoTe2/WSe2 bilayer moiré superlattices, we achieved super-resolution ptychography reconstructions under rapid acquisition conditions (37.5 pA, 1 μs dwell time), yielding over 50% improvements in contrast and information limit compared to annular dark field and iDPC imaging on the same detectors. 

We develop a mechanistic model that classifies individuals both in terms of epidemiological status (SIR) and vaccination attitude (Willing or Unwilling/Unable), with the goal of discovering how disease spread is influenced by changing opinions about vaccination. Analysis of the model identifies the existence and stability criteria for both disease-free and endemic disease equilibria. The analytical results, supported by numerical simulations, show that attitude changes induced by disease prevalence can destabilize endemic disease equilibria, resulting in limit cycles. 

Electronic cigarettes (ECs) emit many toxic substances, including metals, that can pose a threat to users and the environment. The toxicity of the emitted metals depends on their oxidation states. Hence, this study examines the oxidation states of metals observed in EC aerosols. X-ray photoelectron spectroscopy analysis of the filters that collected EC aerosols identified the oxidation states of five primary metals (based on surface sample analysis), including chromium(III) (close to 100%) under low power setting while a noticeable amount of chromium(VI) (15%) at higher power settings of the EC, and copper(II) (100%), zinc(II) (100%), nickel(II) (100%), lead(II) (65%), and lead(IV) (35%) regardless of power settings. This observation indicates that the increased temperature due to higher power settings could alter the oxidation states of certain metals. We noted that many metals were in their lesser toxic states; however, inhaling these metals may still pose health risks.