Emotional Climate Recognition in Conversations using Peers' Speech-based Bispectral Features and Affect Dynamics.

Emotion recognition in conversations using artificial intelligence (AI) has recently gained a lot of attention, as it can provide additional emotion cues that can be correlated with human social behavior. An extension towards an AI-based emotional climate (EC) recognition, i.e.

Classification of children with ADHD through task-related EEG recordings via Swarm-Decomposition-based Phase Locking Value.

Attention Deficit/Hyperactivity Disorder (ADHD) is a common neurodevelopmental disorder mainly affecting children. ADHD children brain activity is reported to present alterations from neurotypically developed children, yet establishment of an EEG biomarker, which is of high importance in clinical practice and research, has not been achieved. In this work, task-related EEG recordings from 61 ADHD and 60 age-matched non-ADHD children are analyzed to examine the underlying Cross-Frequency Coupling phenomena.

Digital Health Technologies for Long-term Self-management of Osteoporosis: Systematic Review and Meta-analysis.

Background: Osteoporosis is the fourth most common chronic disease worldwide. The adoption of preventative measures and effective self-management interventions can help improve bone health. Mobile health (mHealth) technologies can play a key role in the care and self-management of patients with osteoporosis.

In-depth evaluation of commercially available human vascular smooth muscle cells phenotype: Implications for vascular tissue engineering.

In vitro research on vascular tissue engineering has extensively used isolated primary human or animal smooth muscle cells (SMC). Research programs that lack such facilities tend towards commercially available primary cells sources. Here, we aim to evaluate the capacity of commercially available human SMC to maintain their contractile phenotype, and determine if dedifferentiation towards the synthetic phenotype occurs in response to conventional cell culture and passaging without any external biochemical or mechanical stimuli.

A spatiotemporal characterization method for the dynamic cytoskeleton.

The significant gap between quantitative and qualitative understanding of cytoskeletal function is a pressing problem; microscopy and labeling techniques have improved qualitative investigations of localized cytoskeleton behavior, whereas quantitative analyses of whole cell cytoskeleton networks remain challenging. Here we present a method that accurately quantifies cytoskeleton dynamics. Our approach digitally subdivides cytoskeleton images using interrogation windows, within which box-counting is used to infer a fractal dimension (Df ) to characterize spatial arrangement, and gray value intensity (GVI) to determine actin density.