Electrical stimulation treatment for facial palsy after revision pleomorphic adenoma surgery.

Surgery for pleomorphic adenoma recurrence presents a significant risk of facial nerve damage that can result in facial weakness effecting patients' ability to communicate, mental health and self-image. We report two case studies that had marked facial weakness after resection of recurrent pleomorphic adenoma and their progress with electrical stimulation. Subjects received electrical stimulation twice daily for 24 weeks during which photographs of expressions, facial measurements and Sunnybrook scores were recorded. Both subjects recovered good facial function demonstrating Sunnybrook scores of 54 and 64 that improved to 88 and 96, respectively. Neither subjects demonstrated adverse effects of treatment. We conclude that electrical stimulation is a safe treatment and may improve facial palsy in patients after resection of recurrent pleomorphic adenoma. Larger studies would be difficult to pursue due to the low incidence of cases

Suppressed-gap millimetre wave kinetic inductance detectors using DC-bias current

Funder: CSC Cambridge ScholarshipAbstract: In this study, we evaluate the suitability of using DC-biased aluminium resonators as low-frequency kinetic inductance detectors capable of operating in the frequency range of 50–120 GHz. Our analysis routine for supercurrent-biased resonators is based on the Usadel equations and gives outputs including density of states, complex conductivities, transmission line properties, and quasiparticle lifetimes. Results from our analysis confirm previous experimental observations on resonant frequency tuneability and retention of high quality factor. Crucially, our analysis suggests that DC-biased resonators demonstrate significantly suppressed superconducting density of states gap. Consequently these resonators have lower frequency detection threshold and are suitable materials for low-frequency kinetic inductance detectors

Statistical Approach to Raman Analysis of Graphene-Related Materials: Implications for Quality Control

A statistical method to determine the number of measurements required from nanomaterials to ensure reliable and robust analysis is described. Commercial products utilizing graphene are in their infancy and recent investigations of commercial graphene manufacture have attributed this to the lack of robust metrology and standards by which graphene and related carbon materials can be measured and compared. Raman spectroscopy is known to be a useful tool in carbon nanomaterial characterization, but to provide meaningful information, in particular for quality control or management, multiple spectra are needed. Herein we present a statistical method to quantify the number of different spectra or other microscale measurements that should be taken to reliably characterize a graphene material. We have recorded a large number of Raman measurements and studied the statistical convergence of these data sets. We use a graphical approach to monitor the change in summary statistics and a Monte Carlo based bootstrapping method of data analysis to computationally resample the data demonstrating the effects of underanalyzing a material; for example, graphene nanoplatelets may require over 500 spectra before information about the exfoliation efficiency, particle size, layer number, and chemical functionalization is accurately obtained