Augmented Reality (AR) glasses must be slim, lightweight, and energy-efficient to achieve widespread adoption. Beaming Displays present a promising solution by offloading active components, such as the power-supplied light engine, into the surrounding environment while leaving only passive elements, like the eyepiece, in the wearable device. However, existing approaches still struggle to achieve both a slim design and a wide tolerance for projection angles relative to the user’s head orientation. In this work, we introduce a design for light-receiving glasses using a diffractive waveguide with in-coupling and out-coupling gratings. Our approach expands the allowable range of incident angles while maintaining a compact, lightweight form factor. We developed a proof-of-concept prototype and demonstrated an incident angle tolerance of approximately 20-30 degrees range, overcoming the previous design of 5 degrees.

How animals process information, compute, and execute behaviors is a central question in neuroscience and computational biology. Predators attack prey by chasing or ambushing them, while prey respond with escaping or freezing. These behaviors are fundamental for survival. Uncovering functions of such behaviors requires an understanding not only of the implementation of neuronal circuits but also of the underlying algorithms and computation. However, how animals respond to predators or prey depending on whether they can detect them from a distance remains unclear. Here, we modeled and analyzed attack and defense behaviors with game theory. Using encounter probabilities to construct payoff matrices under a sensory-motor algorithm that lacked directional information, we identified the corresponding equilibrium behaviors for the agents (predators and prey). Different detection distances yielded distinct Nash equilibrium behaviors, representing a computational mechanism that can account for diverse attack and defense behaviors. The games based on interactions among multiple predators and prey were, in most cases, non-constant-sum and positive-sum games. Measured payoffs of Nash equilibrium behaviors indicated that the predators were able to increase their payoffs by attacking, and the prey were also able to increase their payoffs even in the presence of predators. These results suggest that each of the agents initiates attack and defense behaviors. Moreover, Nash equilibrium behaviors were also identified under a simpler non-sensory motor algorithm. Despite the similarity, the non-sensory motor algorithm and the sensory-motor algorithm had distinct adaptive significance. The sensory-motor algorithm produced substantially greater prey payoffs. By implementing these algorithms, agents interact in ways that give rise to payoff matrices from which various Nash equilibrium behaviors can be mathematically derived under different conditions. Furthermore, this approach offers an experimental framework for understanding behavioral evolution and suggests a possible difference in evolutionary mechanisms of attack and defense behaviors.

Fresnel zone aperture (FZA) lens-less camera is a class of computational imaging systems that employs an FZA as a coded mask instead of an optical lens. FZA lens-less camera can perform fast deconvolution reconstruction and realize the re-focusing function. However, the reconstructed image’s spatial resolution is restricted by diffraction when using the conventional method derived from the geometrical optics model. In a previous study, we quantitatively analyzed the diffraction propagation between mask and sensor. Then we proposed a color-channel synthesis reconstruction method based on wave-optics theory. This study proposed a novel image reconstruction method without distorting the color information, comprehensively synthesizing two images captured with different mask-sensor distances to mitigate the diffraction influence and improve the image resolution. The numerical simulation and optical experiment results confirm that the proposed method can improve the spatial resolution to about two times that of the conventional method based on the geometrical optics model.

Recently an algorithm to separate fluorescent and reflective components from a hyperspectral image has been reported, in which the important task of spectral unmixing of multiple fluorescent components was left unresolved. In this paper, we present the algorithm to simultaneously separate those components and unmix fluorophores (SSUF: Simultaneous Separation and Unmixing of Fluorescent components) from a single hyperspectral image. Two variants are introduced for the cases when fluorophore spectra are known and unknown. Experimental results confirm the validity of the proposed method.