The development of glassy nanocomposites, xFe-(1−x) (0.5 [Formula: see text]–0.4 CdO–0.1 ZnO) is particularly important not only for exploring their microstructures using x-ray diffraction, FT-IR, and UV–Vis techniques but also for exploring their electrical conduction mechanism in terms of hopping of small polarons. The presence of various nanophases, such as ZnO, CdO, Cd9.5Zn0.5, ZnV, and Zn3V2O8, have been identified and the size of estimated nanocrystallites is found to decrease with more incorporation of the Fe content in the compositions. As the value of lattice strain increases with the increase of the Fe content in the compositions, the present system becomes more and more unstable, which may be favorable for better electrical transport phenomena via the polaron hopping process. Electrical conductivity of the system has been analyzed using modified correlated barrier hopping model, Almond–West formalism, and the alternating-current conductivity scaling. Experimental data reveal that both optical photon and acoustical phonon transitions are responsible for the entire electrical conduction process. Polaron hopping is expected to be of percolation type, which has been validated from an estimated range of frequency exponents. All experimental data have been used to frame a schematic model to explore the conduction mechanism inside the present glassy system.

This paper proposes a scheme for assessing the alertness levels of an individual using simultaneous acquisition of multimodal physiological signals and fusing the information into a single metric for quantification of alertness. The system takes electroencephalogram, high-speed image sequence, and speech data as inputs. Certain parameters are computed from each of these measures as indicators of alertness and a metric is proposed using a fusion of the parameters for indicating alertness level of an individual at an instant. The scheme has been validated experimentally using standard neuropsychological tests, such as the Visual Response Test (VRT), Auditory Response Test (ART), a Letter Counting (LC) task, and the Stroop Test. The tests are used both as cognitive tasks to induce mental fatigue as well as tools to gauge the present degree of alertness of the subject. Correlation between the measures has been studied and the experimental variables have been statistically analyzed using measures such as multivariate linear regression and analysis of variance. Correspondence of trends obtained from biomarkers and neuropsychological measures validate the usability of the proposed metric.

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Continuous and repetitive performance of a task is likely to induce a drop in alertness levels of an individual. Changes in Electroencephalogram (EEG) have been proposed in literature as a marker of alertness during repeated performance of a cognitive task set. The present paper investigates the increase in fatigue levels and resultant drop in alertness of subjects during continuous performance of cognitive tasks by analyzing changes in energy of EEG frequency bands. The trends reflected in the EEG parameters correspond to a gradual increase in fatigue levels of subjects with increase in cognitive loading.

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