The significant role of biofilms in pathogenicity has spurred research into preventing their formation and promoting their disruption, resulting in overlooked opportunities to develop biofilms as a synthetic biological platform for self-assembling functional materials. Here we present Biofilm-Integrated Nanofiber Display (BIND) as a strategy for the molecular programming of the bacterial extracellular matrix material by genetically appending peptide domains to the amyloid protein CsgA, the dominant proteinaceous component in Escherichia coli biofilms. These engineered CsgA fusion proteins are successfully secreted and extracellularly self-assemble into amyloid nanofibre networks that retain the functions of the displayed peptide domains. We show the use of BIND to confer diverse artificial functions to the biofilm matrix, such as nanoparticle biotemplating, substrate adhesion, covalent immobilization of proteins or a combination thereof. BIND is a versatile nanobiotechnological platform for developing robust materials with programmable functions, demonstrating the potential of utilizing biofilms as large-scale designable biomaterials.
Image blur is caused by a number of factors such as motion, defocus, capturing light over the non-zero area of the aperture and pixel, the presence of anti-aliasing filters on a camera sensor, and limited sensor resolution. We present an algorithm that estimates non-parametric, spatially-varying blur functions (i.e., point-spread functions or PSFs) at subpixel resolution from a single image. Our method handles blur due to defocus, slight camera motion, and inherent aspects of the imaging system. Our algorithm can be used to measure blur due to limited sensor resolution by estimating a sub-pixel, super-resolved PSF even for in-focus images. It operates by predicting a "sharp" version of a blurry input image and uses the two images to solve for a PSF. We handle the cases where the scene content is unknown and also where a known printed calibration target is placed in the scene. Our method is completely automatic, fast, and produces accurate results.
Vast potential exists for the development of novel, engineered platforms that manipulate biology for the production of programmed advanced materials. Such systems would possess the autonomous, adaptive, and self-healing characteristics of living organisms, but would be engineered with the goal of assembling bulk materials with designer physicochemical or mechanical properties, across multiple length scales. Early efforts toward such engineered living materials (ELMs) are reviewed here, with an emphasis on engineered bacterial systems, living composite materials which integrate inorganic components, successful examples of large-scale implementation, and production methods. In addition, a conceptual exploration of the fundamental criteria of ELM technology and its future challenges is presented. Cradled within the rich intersection of synthetic biology and self-assembling materials, the development of ELM technologies allows the power of biology to be leveraged to grow complex structures and objects using a palette of bio-nanomaterials.
The advent of inexpensive digital image sensors and the ability to create photographs that combine information from a number of sensed images are changing the way we think about photography. In this paper, we describe a unique array of 100 custom video cameras that we have built, and we summarize our experiences using this array in a range of imaging applications. Our goal was to explore the capabilities of a system that would be inexpensive to produce in the future. With this in mind, we used simple cameras, lenses, and mountings, and we assumed that processing large numbers of images would eventually be easy and cheap. The applications we have explored include approximating a conventional single center of projection video camera with high performance along one or more axes, such as resolution, dynamic range, frame rate, and/or large aperture, and using multiple cameras to approximate a video camera with a large synthetic aperture. This permits us to capture a video light field, to which we can apply spatiotemporal view interpolation algorithms in order to digitally simulate time dilation and camera motion. It also permits us to create video sequences using custom non-uniform synthetic apertures. *
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