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  1. Free, publicly-accessible full text available September 15, 2023
  2. The ability to exert self-control varies within and across taxa. Some species can exert self-control for several seconds whereas others, such as large-brained vertebrates, can tolerate delays of up to several minutes. Advanced self-control has been linked to better performance in cognitive tasks and has been hypothesized to evolve in response to specific socio-ecological pressures. These pressures are difficult to uncouple because previously studied species face similar socio-ecological challenges. Here, we investigate self-control and learning performance in cuttlefish, an invertebrate that is thought to have evolved under partially different pressures to previously studied vertebrates. To test self-control, cuttlefish were presented with a delay maintenance task, which measures an individual's ability to forgo immediate gratification and sustain a delay for a better but delayed reward. Cuttlefish maintained delay durations for up to 50–130 s. To test learning performance, we used a reversal-learning task, whereby cuttlefish were required to learn to associate the reward with one of two stimuli and then subsequently learn to associate the reward with the alternative stimulus. Cuttlefish that delayed gratification for longer had better learning performance. Our results demonstrate that cuttlefish can tolerate delays to obtain food of higher quality comparable to that of some large-brained vertebrates.
  3. Bannister, Julie ; Mohanty, Nihar (Ed.)
    A method for automated creation and optimization of multistep etch recipes is presented. Here we demonstrate how an automated model-based process optimization approach can cut the cost and time of recipe creation by 75% or more as compared with traditional experimental design approaches. Underlying the success of the method are reduced-order physics-based models for simulating the process and performing subsequent analysis of the multi dimensional parameter space. SandBox Studio™ AI is used to automate the model selection, model calibration and subsequent process optimization. The process engineer is only required to provide the incoming stack and experimental measurements for model calibration and updates. The method is applied to the optimization of a channel etch for 3D NAND devices. A reduced-order model that captures the physics and chemistry of the multistep reaction is automatically selected and calibrated. A mirror AI model is simultaneously and automatically created to enable nearly instantaneous predictions across the large process space. The AI model is much faster to evaluate and is used to make a Quilt™, a 2D projection of etch performance in the multidimensional process parameter space. A Quilt™ process map is then used to automatically determine the optimal process window to achieve the target CDs.
  4. Free, publicly-accessible full text available June 1, 2023
  5. Abstract Proton radioactivity was discovered exactly 50 years ago. First, this nuclear decay mode sets the limit of existence on the nuclear landscape on the neutron-deficient side. Second, it comprises fundamental aspects of both quantum tunnelling as well as the coupling of (quasi)bound quantum states with the continuum in mesoscopic systems such as the atomic nucleus. Theoretical approaches can start either from bound-state nuclear shell-model theory or from resonance scattering. Thus, proton-radioactivity guides merging these types of theoretical approaches, which is of broader relevance for any few-body quantum system. Here, we report experimental measurements of proton-emission branches from an isomeric state in 54m Ni, which were visualized in four dimensions in a newly developed detector. We show that these decays, which carry an unusually high angular momentum, ℓ = 5 and ℓ = 7, respectively, can be approximated theoretically with a potential model for the proton barrier penetration and a shell-model calculation for the overlap of the initial and final wave functions.
    Free, publicly-accessible full text available December 1, 2022