Investigating cognitive-physical task interaction during self-paced cycling: a Granger Causality study.

Self-pacing physical exercise is thought to rely on high-order cognitive processing (e.g., attentional control to monitor afferent cardiovascular feedback for exercise goals).

Do Power Meter Data Depend on the Device on Which They Are Collected? Comparison of Eleven Different Recordings.

This study evaluated the influence of cycle computers on the accuracy of power and cadence data. The research was divided into three phases: (1) a graded exercise test (GXT) at different constant loads to record power and cadence data; (2) a self-paced effort lasting 1 min to measure mean maximal power output (MMP); and (3) a short all-out effort. Eight cyclists completed the GXT, ten participated in the 1-min test, and thirty participated in the sprint effort.

Unlocking Security for Comprehensive Electroencephalogram-Based User Authentication Systems.

With recent significant advancements in artificial intelligence, the necessity for more reliable recognition systems has rapidly increased to safeguard individual assets. The use of brain signals for authentication has gained substantial interest within the scientific community over the past decade. Most previous efforts have focused on identifying distinctive information within electroencephalogram (EEG) recordings.

Filling the gaps on root hair development under salt stress and phosphate starvation using current evidence coupled with a meta-analysis approach.

Population expansion is a global issue, especially for food production. Meanwhile, global climate change is damaging our soils, making it difficult for crops to thrive and lowering both production and quality. Poor nutrition and salinity stress affect plant growth and development.