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A<sc>bstract</sc> The Energy Mover’s Distance (EMD) has seen use in collider physics as a metric between events and as a geometric method of defining infrared and collinear safe observables. Recently, the Spectral Energy Mover’s Distance (SEMD) has been proposed as a more analytically tractable alternative to the EMD. In this work, we obtain a closed-form expression for the Riemannian-likep= 2 SEMD metric between events, eliminating the need to numerically solve an optimal transport problem. Additionally, we show how the SEMD can be used to define event and jet shape observables by minimizing the distance between events and parameterized energy flows (similar to the EMD), and we obtain closed-form expressions for several of these observables. We also present the Specter framework, an efficient and highly parallelized implementation of the SEMD metric and SEMD-derived shape observables as an analogue of the previously-introduced Shaper for EMD-based computations. We demonstrate that computing the SEMD with Specter can be up to a thousand times faster than computing the EMD with standard optimal transport libraries. 

We surveyed 70 mobile app creators (34 professionals and 36 students learning mobile app creation) to understand their perceptions toward creativity and accessibility. We found mobile app creators who treated design constraints as creative constraints naturally included accessibility, but those with the freedom of unrestricted aesthetic design often disregarded accessibility. Our research suggests that we can change negative perceptions toward accessible design by making it an integrated part of the creative process. 

Abstract Emerging non-volatile memristor-based devices with resistive switching (RS) materials are being widely researched as promising contenders for the next generation of data storage and neuromorphic technologies. Titanium nitride (TiN_x) is a common industry-friendly electrode system for RS; however, the precise TiN_xproperties required for optimum RS performance is still lacking. Herein, using ion-assisted DC magnetron sputtering, we demonstrate the key importance not only of engineering the TiN_xbottom electrodes to be dense, smooth, and conductive, but also understoichiometric in N. With these properties, RS in HfO₂-based memristive devices is shown to be optimised for TiN_0.96. These devices have switching voltages ≤ ±1 V with promising device-to-device uniformity, endurance, memory window of ~40, and multiple non-volatile intermediate conductance levels. This study highlights the importance of precise tuning of TiN_xbottom electrodes to achieve robust performance of oxide resistive switching materials.