Chris J. Lee

Background and Objective: While the most notable impacts of the coronavirus disease 2019 (COVID-19) pandemic have arguably been felt in the healthcare industry, there have been repercussions across virtually every vertical, including animal agriculture. Disruptions caused by the pandemic, including those related to regulatory responses, led to significant shortages in animal protein. Industry professionals are exploring environmental disinfection technologies that can reduce the presence of pathogens in food production plants. A fundamental point of differentiation among the options is their ability to be operated continuously in occupied settings, such as livestock/poultry production facilities. This review examines Dry Hydrogen Peroxide (DHP), a continuously operating technology, and its efficacy against pathogens in the context of suitability for optimizing food safety and processing in animal agriculture. Methods: This review examines peer-reviewed research pertaining to DHP published between January 2019 and September 2022. These findings were supplemented by pertinent lab reports and observational findings describing DHP’s efficacy against key foodborne pathogens and potential impact on chicken egg hatch rate and mortality. Key Content and Findings: The materials reviewed indicate DHP’s efficacy against a wide range of pathogens commonly present in clinical and animal agriculture settings. Additional observational evidence suggests a potential enhancement of poultry production outcomes, providing direction for future investigation. Conclusions: The identification of effective environmental disinfection technologies that can be integrated into food production facilities requires evaluation of all aspects of system operation. DHP is a technology that appears to be well-suited to this industry, offering an automated, continuous strategy for reduction of pathogens that impact humans and livestock/poultry alike.

Reviewer Acknowledgements for Computer and Information Science, Vol. 16, No. 2, 2023

Reviewer Acknowledgements for Computer and Information Science, Vol. 15, No. 2, 2022

Reviewer acknowledgements for International Education Studies, Vol. 15, No. 2, 2022.

Reviewer Acknowledgements for Computer and Information Science, Vol. 15, No. 1, 2022

A position sensing glove called SmartScan, which creates a 3D virtual model of a real object, is presented. The data from the glove is processed by a volume minimization algorithm to validate the position sensor data. This allows only data from the object’s surface to be retained. The data validation algorithm allows the user to progressively improve an image by repeatedly moving their hand over the object. In addition, the user can choose their own balance between feature resolution and invalid data rejection. The SmartScan glove is tested on a foot model and is shown to be robust against motion artifacts, having a mean accuracy of 2.9 mm (compared to a 3D model generated from optical imaging) without calibration.

In this work, a technique for hydrogen diffusion measurements through thin films is proposed and demonstrated. A yttrium film, which changes its refractive index upon hydrogen absorption, is used as an optical sensor to detect hydrogen. The yttrium sensor is coated with a thin (up to 12 nm) layer of test material and exposed to atomic hydrogen. To ensure that the calculated diffusion constant is not artificially changed by surfaces processes, the test layer is coated with palladium. Hydrogen diffusion through test layers of Si, Al, Ag, Ru, Mo, Al₂O₃ and SiO₂ were measured and compared with existing data. The hydrogenation time (time to form YH₂) was found to exponentially scale with the enthalpy of hydrogen solution in the test material. Comparison between measured diffusion coefficients for different film thicknesses, as well as previously reported results, highlights the strong dependence of the diffusion constant on sample fabrication conditions, and hydrogen exposure conditions. It is concluded that diffusion through thin films can be reliably compared only when specimen form and exposure conditions are the same. The relevance of this study for applications is discussed.

The design, fabrication, and characterization of a low profile shear-force sensor for gait analysis is presented. An analytical model is used to estimate the behavior of the sensor. The sensor response is linear within the modeled range and has a predicted sensitivity of 0.012 pF/N, which is confirmed using a 3D FEM model of the electrical properties of the sensor. The capacitive sensor has a measured sensitivity of 0.0006 pF/N (x-axis) and 0.0003 pF/N (y-axis). When considering the readout electronics, this translates to a voltage/force sensitivity of 9.8 mV/N (x-axis) and 5.2 mV/N (y-axis). The range of the sensor was found to be more than 24 N. The 3D printed sensor is cylindrical with a footprint of ∼3 cm2 and a height of just 3.6 mm, making it suitable for in-sole shear-force measurements.

The structural changes in Ru-coated Y films during hydrogenation were studied in this work. In situ XRD data were used to show that the Y to YH₂ transition requires significant hydrogen loading of the Y lattice. By comparing the XRD data with the in situ spectroscopic ellipsometry data, an effective medium model for the transition was obtained. This model describes the Y to YH₂ transition well. The YH₂ to YH₃ transition is also described by an effective medium model, however, with reduced accuracy around the midpoint of the transition. By comparing the YH₂ and YH₃ crystal sizes, we show that these deviations may be due to a surface plasmon resonance. The improved understanding of the ellipsometry measurements is important for optical hydrogen sensing applications.