The deterministic criteria used to assess model predictive performance.

<p>The deterministic criteria used to assess model predictive performance.</p

Sensor placement.

<p>(A) a sensor attached on the user forearm measuring forearm (FA) IMU, GSR and fingertip PPG signals; (B) a sensor attached on the upper arm measuring upper-arm (UA) IMU and 2-channel EMG signals.</p

Simulated target-reaching in virtual reality with user control input.

<p>Tasks with known indices of difficulty (IDs) were associated with varied distances (D), as defined by Fitts’ law.</p

Summary table showing the aggregated 10-fold cross-validation results based on PLS-R regression.

<p>Summary table showing the aggregated 10-fold cross-validation results based on PLS-R regression.</p

Pearson correlation coefficient with <i>p</i>-value of candidate features extracted from multichannel measures.

<p>Pearson correlation coefficient with <i>p</i>-value of candidate features extracted from multichannel measures.</p

Overall results of human response for all reaching tasks with different difficulty indices (IDs).

<p>(A) EMG muscle activity, (B) EEG-based cognition, (C) galvanic skin conductance variance and heart rate response, (D) movement of end-effector in task space, (E) and (F) user limb motion on both forearm (FA) and upper arm (UA). Black lines are connecting mean values of corresponding measures, error bars illustrate the variances in a 95% confidence interval.</p

Instrumentation for experiments.

<p>Subjects interacted with the virtual task by controlling a robotic interface (i.e., haptic device). Physiological response (e.g., EEG, GSR, EMG) and user kinematic movements were recorded from wireless inertial measurement units (IMUs) on the upper and forearm, as well as encoder readings from the haptic device.</p

All end-effector trajectories in task space controlled by a typical subject.

<p>Different colors denote target-reaching tasks with different indices of difficulty.</p

Path straight deviation (<i>PathStrDev</i>) and path efficiency (<i>PathEff</i>) metrics.

<p>These measures are obtained from end-effector trajectories in the task space.</p

Chemical Inhibition Method to Synthesize Highly Crystalline Prussian Blue Analogs for Sodium-Ion Battery Cathodes

The nucleation rate plays a critical role in the synthesis of Prussian blue analogs. Rapid precipitation may lead to a large number of vacancies and a large amount of interstitial water in the material, resulting in poor electrochemical performance in batteries. Hence, sodium citrate is used to compete with [Fe­(CN)₆]^4– to slow down the coordination rates of Ni²⁺ and Mn²⁺ ions with ferrous cyanide ions. The feasibility of the experiment is also confirmed by theoretical analysis. Benefiting from stable crystal structure and the removal of interstitial water, the as-prepared Na₂Ni_<i>x</i>Mn_<i>y</i>Fe­(CN)₆ sample exhibits a high reversible capacity of 150 mA h g^–1. In addition, a high rate performance of 77 mA h g^–1 is achieved at a current density of 1600 mA g^–1. Most noteworthy, the Coulombic efficiency and specific capacity gradually increase in the first few cycles, which can be ascribed to the formation of a passivation layer on the surface of the electrode. Continuous testing in an electrolyte solution of 1 M NaPF₆ dissolved in sulfone reveals that the presence of a passivation film is very important for the stability of the electrode