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Imaging of cellular immune response in human skin

This patent application describes methods for non-invasive, label-free imaging of the cellular immune response in human skin using a nonlinear optical imaging system.

System And Method For Tomographic Fluorescence Imaging For Material Monitoring

Volumetric additive manufacturing and vat-polymerization 3D printing methods rapidly solidify freeform objects via photopolymerization, but problematically raises the local temperature in addition to degree-of-conversion (DOC). The generated heat can critically affect the printing process as it can auto-accelerate the polymerization reaction, trigger convection flows, and cause optical aberrations. Therefore, temperature measurement alongside conversion state monitoring is crucial for devising mitigation strategies and implementing process control. Traditional infrared imaging suffers from multiple drawbacks such as limited transmission of measurement signal, material-dependent absorptions, and high background signals emitted by other objects. Consequently, a viable temperature and DOC monitoring method for volumetric 3D printing doesn’t exist.To address this opportunity, UC Berkeley researchers have developed a tomographic imaging technique that detects the spatiotemporal evolution of temperature and DOC during volumetric printing. The invention lays foundations for the development of volumetric measurement systems that uniquely resolve both temperature and DOC in volumetric printing.This novel Berkeley measurement system is envisaged as an integral tool for existing manufacturing technologies, such as computed axial lithography (CAL, Tech ID #28754), and as a new research tool for commercial biomanufacturing, general fluid dynamics, and more.

System And Method For Noise-Enabled Static Imaging Using Event Cameras

Dynamic Vision Sensors (DVS), also known as event cameras or neuromorphic sensors, enable extremely high temporal resolution and dynamic range compared to traditional sensors. However, DVS pixels only capture changes in intensity, which discards all static information. To overcome this issue, an additional photosensor array is needed either (1) in a two-sensor system or (2) combined into a single sensor with two-pixel technologies (DAVIS346). In both cases, the resulting system is bulkier, more complex to design, and more expensive to manufacture. UC Berkeley researchers have developed an event-based imaging system that can capture static intensity, thereby eliminating the need of such two-pixel technologies by extracting underlying static intensity information directly from DVS pixels. The researchers have also demonstrated the feasibility of this approach through the analysis of noise statistics in event cameras.

Hot Forming of Curved Mirrors Without the Need for a Mandrel

Large format active or deformable mirrors can enable optical applications that are difficult to achieve with more conventional-sized deformable mirrors. In particular, adaptive secondary mirrors (ASMs) can be integrated into telescopes and provide adaptive optics corrections. However, making facesheets for ASMs is challenging. Current facesheet fabrication processes are costly and risky. Hot forming approaches for forming curved facesheets have been developed, but these methods typically require a mold for the facesheet to slump into.

(SD2022-180) Method of viral nanoparticle functionalization for therapy and imaging applications

Plant viral nanoparticles (plant VNPs) are promising biogenetic nanosystems for the delivery of therapeutic, immunotherapeutic, and diagnostic agents. The production of plant VNPs is simple and highly scalable through molecular farming in plants. Some of the important advances in VNP nanotechnology include genetic modification, disassembly/reassembly, and bioconjugation. Although effective, these methods often involve complex and time-consuming multi-step protocols.

Modular Piezoelectric Sensor Array with Beamforming Channels for Ultrasound Imaging

Researchers at the University of California, Davis have developed a large area sensor array for ultrasound imaging systems that utilizes high-bandwidth piezoelectric sensors and modular design elements.

High-Frequency Imaging and Data Transmission Using a Re-configurable Array Source with Directive Beam Steering

Researchers at the University of California, Davis have developed a reconfigurable radiator array that produces a high frequency directed beam via uninterrupted, scalable, electronic beam steering.

(SD2021-087) Bioinspired Wet Adhesives: Suction discs for adhesion to rough, delicate, and wet surfaces

Adhesion involves highly complex and hierarchical structures in nature, and by understanding the biological intricacies of such adhesive structures, one can improve engineered adhesives. The role of reversible adhesion in both the natural world and in engineering is to temporarily bind to a surface, providing the opportunity to detach and re-attach as needed. In nature, animals use attachment to enhance their fitness.  In robotics, reversible adhesion enables improved manipulation and locomotion by managing contact at the interface between the robot and its environment.

2-D Polymer-Based Device for Serial X-Ray Crystallography

Researchers at the University of California, Davis have developed a single-use chip for the identification of protein crystals using X-ray based instruments.

Method For Mid-Infrared Imaging In Si-Based Cameras Through Non-Degenerate Two-Photon Absorption

Researchers at UCI have developed a novel method to combine common CCD (charge-coupled device) cameras with mid-infrared (MIR) technology in order to create an affordable and accessible spectroscopic camera for biochemical imaging.

Deep Learning Techniques For In Vivo Elasticity Imaging

Imaging the material property distribution of solids has a broad range of applications in materials science, biomechanical engineering, and clinical diagnosis. For example, as various diseases progress, the elasticity of human cells, tissues, and organs can change significantly. If these changes in elasticity can be measured accurately over time, early detection and diagnosis of different disease states can be achieved. Elasticity imaging is an emerging method to qualitatively image the elasticity distribution of an inhomogeneous body. A long-standing goal of this imaging is to provide alternative methods of clinical palpation (e.g. manual breast examination) for reliable tumor diagnosis. The displacement distribution of a body under externally applied forces (or displacements) can be acquired by a variety of imaging techniques such as ultrasound, magnetic resonance, and digital image correlation. A strain distribution, determined by the gradient of a displacement distribution, can be computed (or approximated) from measured displacements. If the strain and stress distributions of a body are both known, the elasticity distribution can be computed using the constitutive elasticity equations. However, there is currently no technique that can measure the stress distribution of a body in vivo. Therefore, in elastography, the stress distribution of a body is commonly assumed to be uniform and a measured strain distribution can be interpreted as a relative elasticity distribution. This approach has the advantage of being easy to implement. The uniform stress assumption in this approach, however, is inaccurate for an inhomogeneous body. The stress field of a body can be distorted significantly near a hole, inclusion, or wherever the elasticity varies. Though strain-based elastography has been deployed on many commercial ultrasound diagnostic-imaging devices, the elasticity distribution predicted based on this method is prone to inaccuracies.To address these inaccuracies, researchers at UC Berkeley have developed a de novo imaging method to learn the elasticity of solids from measured strains. Our approach involves using deep neural networks supervised by the theory of elasticity and does not require labeled data for the training process. Results show that the Berkeley method can learn the hidden elasticity of solids accurately and is robust when it comes to noisy and missing measurements.

Gigahertz Bandwidth Asic For Time-Resolved Frequency Domain Optical Metrology

Inventors from UC Irvine and Beckman Laser Institute have created a low-cost, compact technology for in vivo optical imaging of biological tissues.The technology has the ability to be adapted into a wearable device for bedside imaging in hospitals and clinics.

Real-Time Imaging in Low Light Conditions

Prof. Luat Vuong and colleagues from the University of California, Riverside have developed a method for imaging in low light and low signal-to-noise conditions. This technology works by using a dense neural network to reconstruct an object from intensity-only data and efficiently solves the inverse mapping problem without performing iterations with each image and without deep learning schemes. This network operates without learned stereotypes with low computational complexity, low reconstruction latency, decreased power consumption, and robust resistance to disturbances compared to current imaging technologies. Fig 1: Theoretical/simulation accuracy for multi-vortex arrays - 3,5,7 correspondingly using the dense single layer neural net, in comparison to convolutional NN and a single layer NN using conventional imaging. The SNR is provided for the conventional imaging scheme.  

Embedded Power Amplifier

Researchers at the University of California, Davis have developed an amplifier technology that boosts power output in order to improve data transmission speeds for high-frequency communications.

Polarization-Sensitive Optical Coherence Tomography Using a Polarization-Insensitive Detector

A polarization-sensitive optical coherence tomography (PS-OCT) is a common approach to non-invasively imaging in biomedical applications. The inventors have come up with a new way of creating a PS-OCT that is cheaper and simpler.

Vehicle Make and Model Identification

Prof. Bir Bhanu and his colleagues from the University of California, Riverside have developed a method for  analyzing real-time video feed of vehicles from a rear  view  perspective to identify the make and model of a vehicle. This method works by using a software system for detecting the Regions-of-Interest (ROIs) of moving vehicles and moving shadows, computing structural and other features and using a vehicle make and model database for vehicle identification. The system performs calculations based on factors found in all vehicles, so it is reliable regardless of vehicle color and type. The system is compatible with low resolution video feed, so it is able to analyze video feed in real-time. Thus, this technology holds potential for innovating fields like vehicle surveillance, vehicle security, class-based vehicle tolling, and traffic monitoring where reliable real-time video analysis is needed. Two Step alignment: (a) Target image (b) Query Image, (c) Vertical alignment cost (Hotter colors indicate higher cost) and solution (blue line), (d) Horizontal alignment alignment cost and so- lution, (e) Aligned query, (f) Query aligned with SIFTflow Cumulative match characteristic for top 20 retrievals demonstrating significant improvement over the baseline

Vibration Sensing and Long-Distance Sounding with THz Waves

UCLA researchers in the Department of Electrical and Computer Engineering have developed a terahertz (THz) detector that utilizes the micro-Doppler effect to detect vibrations and long-distance sounds.

Vehicle Logo Identification in Real-Time

Brief description not available

Design Of Task-Specific Optical Systems Using Broadband Diffractive Neural Networks

UCLA researchers in the Department of Electrical and Computer Engineering have developed a diffractive neural network that can process an all-optical, 3D printed neural network for deep learning applications.

High External-Efficiency Nanofocusing for Lens-Free Near-Field Optical Microscopy

Profs. Ruoxue Yan, Ming Liu, and their colleagues from the University of California, Riverside have developed a two-step sequential broadband nanofocusing technique with an external nanofocusing efficiency of ~50% over nearly all the visible range on a fibre-coupled nanowire scanning probe. By integrating this with a basic portable scanning tunneling microscope, the technology captured images with spatial resolution as low as one nanometer at high resolution. The high performance and vast versatility offered by this fibre-based nanofocusing technique allows for the easy incorporation of nano-optical microscopy into various existing measurement platforms.  Fig. 1: High-resolution NSOM mapping. a, scanning tunnelling microscope topographic image of single wall carbon nanotubes on a gold film. Top inset: cross-sectional profile along the dashed line. Bottom inset: the possible configurations of the bundle.  

Materials Platform for Flexible Emissivity Engineering

This materials platform enables flexible engineering of infrared (IR) emissivity and development of thermal radiation devices beyond the Stefan-Boltzmann law. The materials structure is based on thin films of vanadium oxide (VO2) with judiciously designed graded W doping across a thickness less than the skin depth of electromagnetic screening (~100 nm). The infrared emissivity can be engineered to decrease in an arbitrary manner from ~ 0.75 to ~ 0.35 over a temperature range up to 50 C near room temperature. The large range of emissivity tuning and flexible adjustability is beyond the capability of regular materials or structures. This invention provides a new platform for unprecedented manipulation of thermal radiation and IR signals with a wide variety of applications, such as:  The emissivity can be programmed to precisely counteract the T^4 dependence in the Stefan-Boltzmann law and achieve a temperature dependent thermal radiation. Such a design enables a mechanically flexible and power-free infrared camouflage, which is inherently robust and immune to drastic temporal fluctuation and spatial variation of temperature. By tailoring structure and composition, the materials platform can create a surface with robust and arbitrary IR temperature image, regardless of the actual temperature distribution on the targets. This design of infrared "decoy" not only passively conceals the real thermal activity of the object, but also intentionally fools the camera with a counterfeited image. The materials platform can achieve strong temperature dependence of reflectivity over a broad wavelength from near-IR to far-IR, which is promising for high-sensitivity remote temperature sensing by thermoreflectance imaging, or active reflectance modulation of IR signals. 

Simultaneous Acquisition Of Multiple Epi-Fluorescence Micrographs

UCSF researchers have developed a novel microscope system which allows multiple images of a single sample to be acquired simultaneously.  These images are structured and, when coupled with conventional structured illumination image processing methods, can provide video rate, super-resolution micrographs. 

Graphene Oxide Based Affinity Grids As Sample Supports For High- Resolution Cryo Electron Microscopy.

Inventors at UCSF have developed a novel and economical method to produce a new generation of Cryo-EM sample grids that bind purify and protect biomolecule samples.

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