Abstract This paper showcases how the design process execution in a challenging environment where cost, time, and COVID-19 induced supply chain factors are significant considerations. The design process was executed in six phases: defining SMART (specific, measurable, attainable, relevant, time-bound) requirements, concept development, concept selection, risk reduction prototyping, final design, and verification testing. Defining SMART requirements is critical to quickly define the design scope which allows for a time-efficient and targeted approach during the subsequent phases. Positional accuracy and speed requirements were the most critical functional requirements. Next, we engaged in a concept development phase, which involved exploring existing designs and novel concepts, with input from subject matter experts familiar with the design space. Two concepts emerged as reasonable approaches: a direct-drive linear motor-based design and a lead-screw based design which were initially developed in parallel. To narrow down the design space, a concept selection phase was used to analyze the advantages and disadvantages of each concept, factoring in the weighted relative importance of each design requirement. The linear motor-based design was determined to best fit the design requirements and proceeded into risk reduction prototyping. Risk reduction prototyping involves design and creation of limited prototypes to learn the key limitations of a design with respect to the requirements, and iterate the deficient qualities in a short feedback loop. By leveraging readily available components a stage assembly representative of the final design was constructed and demonstrated that critical design requirements could be met. The final design was created and fabricated followed by verification testing to ensure the final stage design met the SMART requirements defined in the outset.

Rapid, simple, inexpensive, accurate, and sensitive point-of-care (POC) detection of viral pathogens in bodily fluids is a vital component of controlling the spread of infectious diseases. The predominant laboratory-based methods for sample processing and nucleic acid detection face limitations that prevent them from gaining wide adoption for POC applications in low-resource settings and self-testing scenarios. Here, we report the design and characterization of an integrated system for rapid sample-to-answer detection of a viral pathogen in a droplet of whole blood comprised of a 2-stage microfluidic cartridge for sample processing and nucleic acid amplification, and a clip-on detection instrument that interfaces with the image sensor of a smartphone. The cartridge is designed to release viral RNA from Zika virus in whole blood using chemical lysis, followed by mixing with the assay buffer for performing reverse-transcriptase loop-mediated isothermal amplification (RT-LAMP) reactions in six parallel microfluidic compartments. The battery-powered handheld detection instrument uniformly heats the compartments from below, and an array of LEDs illuminates from above, while the generation of fluorescent reporters in the compartments is kinetically monitored by collecting a series of smartphone images. We characterize the assay time and detection limits for detecting Zika RNA and gamma ray-deactivated Zika virus spiked into buffer and whole blood and compare the performance of the same assay when conducted in conventional PCR tubes. Our approach for kinetic monitoring of the fluorescence-generating process in the microfluidic compartments enables spatial analysis of early fluorescent "bloom" events for positive samples, in an approach called "Spatial LAMP" (S-LAMP). We show that S-LAMP image analysis reduces the time required to designate an assay as a positive test, compared to conventional analysis of the average fluorescent intensity of the entire compartment. S-LAMP enables the RT-LAMP process to be as short as 22 minutes, resulting in a total sample-to-answer time in the range of 17-32 minutes to distinguish positive from negative samples, while demonstrating a viral RNA detection as low as 2.70 × 102 copies per μl, and a gamma-irradiated virus of 103 virus particles in a single 12.5 μl droplet blood sample.

Traditional image classifiers suffer from the so called Background clutter problem, where they have to, simultaneously, localize and recognize an object of interest. In real-world video scenes, many objects appear at the same time and several objects of interest could be present. We decompose the problem into two stages. The first involves extracting a moving object from the video scene based on its coherent motion. This step makes no assumption about the nature of the object being tracked and extracted. We, then apply a classifier to the extracted object to determine if it falls into one of the classes of interest.

The development of the first fully integrated 4-channel fiber optic gyroscope is presented. The optical engine integrates the equivalent of more than 24 discrete optical components into a hybrid chip with a size of 67x11x3 mm. After the optical engine is spliced to fiber sensor coils, the performance of the gyroscope has been benchmarked to be equivalent to the performance of a navigation grade gyroscope fabricated with discrete components.

Flash Quantum Efficiency — a technique used to simultaneously measure full spectrum external quantum efficiency (EQE), Reflectance (R), and Transmittance (T), has been introduced in two prior publications [1,2]. The method uses a novel architecture to simultaneously modulate a bank of solid state lightsources and measure, in real time, the cell response to each wavelength. In this work we extend it to include two additional capabilities-automated spatial mapping and multi-junction measurements. Mapping throughput of 2400 sites per hour is demonstrated on single crystal silicon cells with a signal to noise ratio that is significantly higher than conventional QE. New inverted metamorphic cells are also used to develop and demonstrate a multi-junction FlashQE technique with total acquisition time of less than four seconds per triple-junction cell.