The Effects of an Inclusive Badminton Program on Static Postural Control for Individuals with Intellectual and Developmental Disabilities.

The purpose of the study was to examine static postural control/balance in young adults with intellectual and developmental disabilities (IDD) and typically developing (TD) young adults before, during, and after an inclusive badminton intervention. Eight participants (four IDD-BADM and four TD-BADM) participated in a 12-week inclusive badminton intervention, with the other eight participants as matched controls (four IDD-CONTR and four TD-CONTR) (74.19 kg ± 9.

Physiological and Subjective Measures of Anxiety with Repeated Exposure to Virtual Construction Sites at Different Heights.

Background: Occupational workers at altitudes are more prone to falls, leading to catastrophic outcomes. Acrophobia, height-related anxiety, and affected executive functions lead to postural instabilities, causing falls. This study investigated the effects of repeated virtual height exposure and training on cognitive processing and height-related anxiety.

Impact of Sub-Clinical and Clinical Compression Socks on Postural Stability Tasks among Individuals with Ankle Instability.

Compression socks are used by a very diverse group of individuals and may potentially have a greater impact on physically diminished or impaired individuals as opposed to healthy individuals. The purpose of this study was to compare the effects of sub-clinical (SC) and clinical (CL) compression socks among healthy (CON), copers (COP), and individuals with chronic ankle instability (CAI). Postural stability was evaluated in 20 participants (11 males and 9 females) using Balance Tracking System Balance platform (BTrackS™) during the modified clinical test of sensory integration in balance (mCTSIB) and limits of stability (LOS) tests.

Symmetry-aware reservoir computing.

We demonstrate that matching the symmetry properties of a reservoir computer (RC) to the data being processed dramatically increases its processing power. We apply our method to the parity task, a challenging benchmark problem that highlights inversion and permutation symmetries, and to a chaotic system inference task that presents an inversion symmetry rule. For the parity task, our symmetry-aware RC obtains zero error using an exponentially reduced neural network and training data, greatly speeding up the time to result and outperforming artificial neural networks.

Next generation reservoir computing.

Reservoir computing is a best-in-class machine learning algorithm for processing information generated by dynamical systems using observed time-series data. Importantly, it requires very small training data sets, uses linear optimization, and thus requires minimal computing resources. However, the algorithm uses randomly sampled matrices to define the underlying recurrent neural network and has a multitude of metaparameters that must be optimized.

Forecasting chaotic systems with very low connectivity reservoir computers.

We explore the hyperparameter space of reservoir computers used for forecasting of the chaotic Lorenz '63 attractor with Bayesian optimization. We use a new measure of reservoir performance, designed to emphasize learning the global climate of the forecasted system rather than short-term prediction. We find that optimizing over this measure more quickly excludes reservoirs that fail to reproduce the climate.

Rapid time series prediction with a hardware-based reservoir computer.

Reservoir computing is a neural network approach for processing time-dependent signals that has seen rapid development in recent years. Physical implementations of the technique using optical reservoirs have demonstrated remarkable accuracy and processing speed at benchmark tasks. However, these approaches require an electronic output layer to maintain high performance, which limits their use in tasks such as time-series prediction, where the output is fed back into the reservoir.

Identification of a TBHQ-Interfering Peak in Crude Canola Oil Using AOCS Official Method Ce 6-86 and its Chromatographic Resolution.

AOCS Official Method Ce 6-86 "Antioxidants, Liquid Chromatographic Method" was originally developed to confirm the correct antioxidant was added at the specified concentration to refined oils. Today, this method is increasingly utilized to validate that antioxidants are absent from oil products. False positive results can have a significant impact on the ability to sell products in specific markets and can impart additional business expenditures for conclusive secondary analyses.