Measuring Mental Workload Using ERPs Based on FIR,ICA, and MARA

Mental workload is considered to be strongly linked to human performance, and the ability to measure it accurately is key for balancing human health and work. In this study, brain signals were elicited by mental arithmetic tasks of varying difficulty to stimulate different levels of mental workload. In addition, a finite impulse response (FIR) filter, independent component analysis (ICA), and multiple artifact rejection algorithms (MARAs) were used to filter event-related potentials (ERPs). Then, the data consisting of ERPs, subjective ratings of mental workload, and task performance, were analyzed through the use of variance and Spearman’s correlation during a simulated computer task. We found that participants responded faster and performed better in the easy task condition, followed by the medium and high-difficulty conditions, which verifies the validity of the ERP filtering. Moreover, larger P2 and P3 waveforms were evoked as the task difficulty increased, and a higher task difficulty elicited a more enhanced N300. Correlation analysis revealed a negative relationship between the amplitude of P3 and the subjective ratings, and a positive relationship between the P3 amplitude and accuracy. The results presented in this paper demonstrate that a combination of FIR, ICA, and MARA methods can filter ERPs in the non-invasive real-time measurement of workload. Additionally, frontocentral P2, N3, and parietal P3 components showed differences between genders. The proposed measurement of mental workload can be useful for real-time identification of mental states and can be applied to human–computer interaction in the future.     

Anticipating Cutoff Diameters in Deterministic Lateral Displacement (DLD) Microfluidic Devices for an Optimized Particle Separation

Deterministic lateral displacement (DLD) devices enable to separate nanometer to micrometer‐sized particles around a cutoff diameter, during their transport through a microfluidic channel with slanted rows of pillars. In order to design appropriate DLD geometries for specific separation sizes, robust models are required to anticipate the value of the cutoff diameter. So far, the proposed models result in a single cutoff diameter for a given DLD geometry. This paper shows that the cutoff diameter actually varies along the DLD channel, especially in narrow pillar arrays. Experimental and numerical results reveal that the variation of the cutoff diameter is induced by boundary effects at the channel side walls, called the wall effect. The wall effect generates unexpected particle trajectories that may compromise the separation efficiency. In order to anticipate the wall effect when designing DLD devices, a predictive model is proposed in this work and has been validated experimentally. In addition to the usual geometrical parameters, a new parameter, the number of pillars in the channel cross dimension, is considered in this model to investigate its influence on the particle trajectories.     

Engineering carbon quantum dots for photomediated theranostics

Carbon quantum dots (CQDs) have emerged as potential alternatives to classical metal-based semiconductor quantum dots (QDs) due to the abundance of their precursors, their ease of synthesis, high biocompatibility, low cost, and particularly their strong photoresponsiveness, tunability, and stability. Light is a versatile, tunable stimulus that can provide spatiotemporal control. Its interaction with CQDs elicits interesting responses such as wavelength-dependent optical emissions, charge/electron transfer, and heat generation, processes that are suitable for a range of photomediated bioapplications. The carbogenic core and surface characteristics of CQDs can be tuned through versatile engineering strategies to endow specific optical and physicochemical properties, while conjugation with specific moieties can enable the design of targeted probes. Fundamental approaches to tune the responses of CQDs to photo-interactions and the design of bionanoprobes are presented, which enable biomedical applications involving diagnostics and therapeutics. These strategies represent comprehensive platforms for engineering multifunctional probes for nanomedicine, and the design of QD probes with a range of metal-free and emerging 2D materials.

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Building 2D quasicrystals from 5-fold symmetric corannulene molecules

Nano Research - The formation of long-range ordered aperiodic molecular films on quasicrystalline substrates is a new challenge that provides an opportunity for further surface functionalization....