Putting Piezoelectric Sensors into Fano Resonances

Piezoelectric resonance sensors are widely used in chemical and biological sensing applications. They operate by detecting the resonant frequency shift of piezoelectric resonators caused by the deposition of analytes on their surfaces. To detect minute changes in analytes, resonators require a high quality factor (Q factor). Traditionally, methods ...

Fiber Optics-Based Surface Enhanced Raman Spectroscopy Sensors for Rapid Multiplex Detection of Foodborne Pathogens in Raw Poultry

Fiber Optics-Based Surface Enhanced Raman Spectroscopy Sensors for Rapid Multiplex Detection of Foodborne Pathogens in Raw Poultry Academic Background Foodborne illnesses are a significant global public health challenge, with Salmonella being one of the leading pathogens causing such diseases. In the United States alone, Salmonella results in 1.35 ...

Fabrication and In Vivo Testing of a Sub-mm Duckbill Valve for Hydrocephalus Treatment

Fabrication and In Vivo Testing of a Sub-mm Duckbill Valve for Hydrocephalus Treatment Academic Background Hydrocephalus is a complex pathological condition characterized by the accumulation of cerebrospinal fluid (CSF) in the cranium due to an imbalance between CSF production and absorption. This accumulation leads to increased intracranial pressu...

Ultrahigh-Field Animal MRI System with Advanced Technological Update

Technological Updates in Ultrahigh-Field Animal MRI Systems Academic Background Animal magnetic resonance imaging (MRI) systems play a crucial role in preclinical research, typically offering superior imaging performance compared to conventional human MRI systems. However, achieving high performance in these systems is challenging due to the multif...

Robust Self-Supervised Denoising of Voltage Imaging Data Using CellMincer

Academic Background Voltage imaging is a powerful technique for studying neuronal activity, but its effectiveness is often constrained by low signal-to-noise ratios (SNR). Traditional denoising methods, such as matrix factorization, impose rigid assumptions about noise and signal structures, while existing deep learning approaches fail to fully cap...