Researchers at the University of California, Davis and the USDA Agricultural Research Service (ARS) have developed RNAi-based compositions and methods that enhance miticide efficacy to control resistant Varroa destructor mites.

Researchers at the University of California, Davis have developed a protein-based composition and method that protects bioactive bacteria from thermal and osmotic stress during dehydration to maintain viability and shelf life.

Researchers at the University of California, Davis have developed a method that uses phenolic-rich agro-industrial residues to protect and stabilize beneficial microbes for improved shelf life and bioactivity.

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Researchers at the University of California, Davis have developed an engineered thermostable lipase capable of efficiently degrading polyurethane plastics at elevated temperatures.

Traditional air quality monitoring often lacks the resolution to pinpoint specific emission sources within a city, leaving "hyperlocal" pollution spikes undetected. To address this, researchers at UC Berkeley have developed INFE²R, a sophisticated method for detecting and refining airborne pollutant emissions at a neighborhood scale. The system utilizes a Weather Research and Forecasting (WRF) module to generate high-resolution meteorological inputs, which are then processed through a Stochastic Time Inverted Lagrangian Transport (STILT) module to create a source-receptor transfer matrix. By combining prior emission estimates with a cross-dimensional assimilation of both fixed and mobile sensor measurements, the platform employs Bayesian inversion to generate highly accurate posterior emission estimates. This allows for a granular understanding of how pollutants move and accumulate in specific urban localities.

Traditional 3D printing methods rely on layer-by-layer deposition, which often limits speed and introduces structural weaknesses. Computed Axial Lithography (CAL) revolutionized the field by using projected light to cure entire volumes at once, but it was previously constrained by the size of the illumination field. UC Berkeley researchers have advanced this technology with a Helical Cone Beam CAL system. By combining a rotating target volume with a synchronized translation mechanism, the system projects patterned cone beams in a helical path through radiation-reactive material. This allows for continuous printing of much larger objects than traditional CAL and even enables "inner printing"—the fabrication of new structures inside or around existing solid objects.

Converting voice identity in real-time while maintaining perfect linguistic clarity and emotional nuance is a significant hurdle in speech synthesis. Researchers at UC Berkeley have developed a system for real-time voice style conversion that transforms a source speaker's speech to match the timbre, accent, and emotion of a target speaker. The technology utilizes a content extraction network with conformer blocks and a unique low-dimensional quantization method—using fewer than 100 levels—to preserve linguistic fidelity. By extracting continuous representations before quantization, the system maintains higher speech quality than traditional discrete methods. A diffusion-based generation network then creates a mel-spectrogram conditioned on these features and a target style embedding, which is finally converted to audio via a vocoder. The system is designed for streaming operation through the use of chunked-causal attention mechanisms, enabling near-instantaneous transformation.