Chloride is an essential cofactor in the oxygen-evolution reaction that takes place in photosystem II (PSII). The oxygen-evolving complex (OEC) is oxidized in a linear four-step photocatalytic cycle in which chloride is required for the OEC to advance beyond the S2 state. Here, using density functional theory, we compare the energetics and spin configuration of two different states of the Mn4CaO5 cluster in the S2 state: state A with Mn1(3+) and B with Mn4(3+) with and without chloride. The calculations suggest that model B with an S = 5/2 ground state occurs in the chloride-depleted PSII, which may explain the presence of the EPR signal at g = 4.1. Moreover, we use multiconformer continuum electrostatics to study the effect of chloride depletion on the redox potential associated with the S1/S2 and S2/S3 transitions.

Structural changes induced by radiation damage in X-ray crystallography hinder the ability to understand the structure/function relationship in chemical reactions. Serial femtosecond crystallography overcomes this problem by exposing the sample to very short and intense laser pulse leading to measurement before destruction. Here we use molecular modeling to map the radiation damage during the 10–50 fs to the intensity, the energy and the time duration of the laser pulse on the oxygen-evolving complex (OEC) of photosystem II. In the model, the nuclei move classically in a fully quantum potential created by electron density under the effect of strong laser pulse in the Ehrenfest dynamics regime. The results show that the Mn-Mn and Mn-Ca distances are less affected by radiation damage due to the their heavy masses, while one μ-oxo bridge (O5) moves significantly. The radiation damage may induce conformational changes of the water ligands but only bond elongation for the amino acids ligands. These effects are relatively intensity independent from 1016 to 1017 W/cm2, but changes increase dramatically if the beam intensity is increased to 1018 W/cm2. In addition, the self amplified spontaneous emission (SASE) nature of the laser beam does not affect the dynamics of the ions.

Detecting the cognitive profiles of learners is an important step towards personalized and adaptive learning. Electroencephalograms (EEG) have been used to detect the subject’s emotional and cognitive states. In this paper, an approach for detecting two cognitive skills, focused attention and working memory, using EEG signals is proposed. The proposed approach consists of the following main steps: first, subjects undergo a scientifically-validated cognitive assessment test that stimulates and measures their full cognitive profile while putting on a 14-channel wearable EEG headset. Second, the scores of focused attention and working memory are extracted and encoded for a classification problem. Third, the collected EEG data are analyzed and a total of 280 time- and frequency-domain features are extracted. Fourth, several classifiers were trained to correctly classify and predict three levels (low, average, and high) of the two cognitive skills. The classification accuracies that were obtained on 86 subjects were 84% and 81% for the focused attention and working memory, respectively. In comparison with similar approaches, the obtained results indicate the generalizability and suitability of the proposed approach for the detection of these two skills. Thus, the presented approach can be used as a step towards adaptive learning where real-time adaptation is to be done according to the predicted levels of the measured cognitive skills.

In this study, the synthesis, characterization and testing of new polymeric–metal oxide nanocomposites for enzymatic glucose biosensors were performed.