Improved bioimpedance spectroscopy tissue classification through data augmentation from generative adversarial networks.

Bioimpedance spectroscopy is a tissue classification technique with many clinical applications. Similarly to other data-driven methods, it requires large amounts of data to accurately distinguish similar classes of tissue. Classifiers trained on small datasets typically suffer from over-fitting and lack the ability to generalise to previously unseen data.

Improved Configurations for 3D Acoustoelectric Tomography With a Minimal Number of Electrodes.

Objective: Acoustoelectric tomography (AET) is a hybrid imaging technique combining ultrasound and electrical impedance tomography (EIT). It exploits the acoustoelectric effect (AAE): an US wave propagating through the medium induces a local change in conductivity, depending on the acoustoelectric properties of the medium. Typically, AET image reconstruction is limited to 2D and most cases employ a large number of surface electrodes.

Inorganic Carbon Assimilation and Electrosynthesis of Platform Chemicals in Bioelectrochemical Systems (BESs) Inoculated with N1-H4.

The need for greener processes to satisfy the demand of platform chemicals together with the possibility of reusing CO from human activities has recently encouraged research on the set-up, optimization, and development of bioelectrochemical systems (BESs) for the electrosynthesis of organic compounds from inorganic carbon (CO, HCO). In the present study, we tested the ability of N1-4 (DSMZ 14923) to produce acetate and D-3-hydroxybutyrate from inorganic carbon present in a CO:N gas mix. At the same time, we tested the ability of a MR1 and PA1430/CO1 consortium to provide reducing power to sustain carbon assimilation at the cathode.