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- Adam M Guss
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By engineering the Serine Integrase Assisted Genome Engineering (SAGE) genetic toolkit in an industrial strain of Aspergillus niger, we have established its proof of principle for applicability in Eukaryotes.

System and method for part porosity monitoring of additively manufactured components using machining
In additive manufacturing, choice of process parameters for a given material and geometry can result in porosities in the build volume, which can result in scrap.

We present a comprehensive muti-technique approach for systematic investigation of enzymes generated by wastewater Comamonas species with hitherto unknown functionality to wards the depolymerization of plastics into bioaccessible products for bacterial metabolism.

Faults in the power grid cause many problems that can result in catastrophic failures. Real-time fault detection in the power grid system is crucial to sustain the power systems' reliability, stability, and quality.

Water heaters and heating, ventilation, and air conditioning (HVAC) systems collectively consume about 58% of home energy use.

Detection of gene expression in plants is critical for understanding the molecular basis of plant physiology and plant responses to drought, stress, climate change, microbes, insects and other factors.

This technology identifies enzymatic routes to synthesize amide oligomers with defined sequence to improve polymerization of existing materials or enable polymerization of new materials. Polymers are generally composed of one (e.g. Nylon 6) or two (e.g.

The technologies described provides for the upcycling of mixed plastics to muonic acid and 3-hydroxyacids.

Sensing of additive manufacturing processes promises to facilitate detailed quality inspection at scales that have seldom been seen in traditional manufacturing processes.

This invention is for bacterial strains that can utilize lignocellulose sugars. This will improve the efficiency of bioproduct formation in these strains and reduce the greenhouse-gas emission of an industrial bi