Deep Learning-Based Feature Extraction of Acoustic Emission Signals for Monitoring Wear of Grinding Wheels.

Tool wear monitoring is a critical issue in advanced manufacturing systems. In the search for sensing devices that can provide information about the grinding process, Acoustic Emission (AE) appears to be a promising technology. The present paper presents a novel deep learning-based proposal for grinding wheel wear status monitoring using an AE sensor. The most relevant finding is the possibility of efficient feature extraction form frequency plots using CNNs. Feature extraction from FFT plots requires sound domain-expert knowledge, and thus we present a new approach to automated feature extraction using a pre-trained CNN. Using the features extracted for different industrial grinding conditions, t-SNE and PCA clustering algorithms were tested for wheel wear state identification. Results are compared for different industrial grinding conditions. The initial state of the wheel, resulting from the dressing operation, is clearly identified for all the experiments carried out. This is a very important finding, since dressing strongly affects operation performance. When grinding parameters produce acute wear of the wheel, the algorithms show very good clustering performance using the features extracted by the CNN. Performance of both t-SNE and PCA was very much the same, thus confirming the excellent efficiency of the pre-trained CNN for automated feature extraction from FFT plots.

Non-telecentric two-photon microscopy for 3D random access mesoscale imaging.

Diffraction-limited two-photon microscopy permits minimally invasive optical monitoring of neuronal activity. However, most conventional two-photon microscopes impose significant constraints on the size of the imaging field-of-view and the specific shape of the effective excitation volume, thus limiting the scope of biological questions that can be addressed and the information obtainable. Here, employing a non-telecentric optical design, we present a low-cost, easily implemented and flexible solution to address these limitations, offering a several-fold expanded three-dimensional field of view. Moreover, rapid laser-focus control via an electrically tunable lens allows near-simultaneous imaging of remote regions separated in three dimensions and permits the bending of imaging planes to follow natural curvatures in biological structures. Crucially, our core design is readily implemented (and reversed) within a matter of hours, making it highly suitable as a base platform for further development. We demonstrate the application of our system for imaging neuronal activity in a variety of examples in zebrafish, mice and fruit flies.

Two decades of neuroscience publication trends in Africa.

Neuroscience research in Africa remains sparse. Devising new policies to boost Africa's neuroscience landscape is imperative, but these must be based on accurate data on research outputs which is largely lacking. Such data must reflect the heterogeneity of research environments across the continent's 54 countries. Here, we analyse neuroscience publications affiliated with African institutions between 1996 and 2017. Of 12,326 PubMed indexed publications, 5,219 show clear evidence that the work was performed in Africa and led by African-based researchers - on average ~5 per country and year. From here, we extract information on journals and citations, funding, international coauthorships and techniques used. For reference, we also extract the same metrics from 220 randomly selected publications each from the UK, USA, Australia, Japan and Brazil. Our dataset provides insights into the current state of African neuroscience research in a global context.

LED Zappelin': An open source LED controller for arbitrary spectrum visual stimulation and optogenetics during 2-photon imaging.

Two-photon (2P) microscopy is a cornerstone technique in neuroscience research. However, combining 2P imaging with spectrally arbitrary light stimulation can be challenging due to crosstalk between stimulation light and fluorescence detection. To overcome this limitation, we present a simple and low-cost electronic solution based on an ESP32 microcontroller and a TLC5947 LED driver to rapidly time-interleave stimulation and detection epochs during scans. Implemented for less than $100, our design can independently drive up to 24 arbitrary spectrum LEDs to meet user requirements. We demonstrate the utility of our stimulator for colour vision experiments on the in vivo tetrachromatic zebrafish retina and for optogenetic circuit mapping in Drosophila.