Recurrence plot embeddings as short segment nonlinear features for multimodal speaker identification using air, bone and throat microphones.

Speech is produced by a nonlinear, dynamical Vocal Tract (VT) system, and is transmitted through multiple (air, bone and skin conduction) modes, as captured by the air, bone and throat microphones respectively. Speaker specific characteristics that capture this nonlinearity are rarely used as stand-alone features for speaker modeling, and at best have been used in tandem with well known linear spectral features to produce tangible results. This paper proposes Recurrent Plot (RP) embeddings as stand-alone, non-linear speaker-discriminating features.

HES1 promoter activation dynamics reveal the plasticity, stemness and heterogeneity in neuroblastoma cancer stem cells.

Notch signaling and its downstream gene target HES1 play a critical role in regulating and maintaining cancer stem cells (CSCs), similar to as they do during embryonic development. Here, we report a unique subclass of Notch-independent Hes-1 (NIHes-1)-expressing CSCs in neuroblastoma. These CSCs maintain sustained HES1 expression by activation of HES1 promoter region upstream of classical CBF-1 binding sites, thereby completely bypassing Notch receptor-mediated activation.

Deep learning approach to detect seizure using reconstructed phase space images.

Epilepsy is a chronic neurological disorder that affects the function of the brain in people of all ages. It manifests in the electroencephalogram (EEG) signal which records the electrical activity of the brain. Various image processing, signal processing, and machine-learning based techniques are employed to analyze epilepsy, using spatial and temporal features.