Investigating Cortical Complexity in Mixed Dementia through Nonlinear Dynamic Analyses: A Resting-State EEG Study.

Objective: Dementia is a broad term referring to a decline in problem-solving abilities, language skills, memory, and other cognitive functions to a degree that it significantly disrupts everyday activities. The underlying cause of dementia is the impairment or loss of nerve cells and their connections within the brain. The particular symptoms experienced are contingent upon specific regions of the brain affected by this damage. In this research, we aimed to investigate the nonlinear dynamics of the mixed demented brain compared to healthy subjects using electroencephalogram (EEG) analysis. Method : For this purpose, EEG was recorded from 66 patients with mixed dementia and 65 healthy subjects during rest. After signal preprocessing, sample entropy and Katz fractal dimension analyses were applied to the preprocessed EEG data. Analysis of variance with repeated measures was utilized to compare the nonlinear dynamics of brain activity between dementia and healthy states and partial correlation analysis was employed to explore the relationship between EEG complexity measures and cognitive and neuropsychiatric symptoms of patients. Results: Based on repeated measures ANOVA, there was a significant main effect between groups for both Katz fractal dimension (F = 4.10, P = 0.01) and sample entropy (F = 4.81, P = 0.009) measures. Post hoc comparisons revealed that EEG complexity was significantly reduced in dementia mainly in the occipitoparietal and temporal areas (P < 0.05). MMSE scores were positively correlated with EEG complexity measures, while NPI scores were negatively correlated with EEG complexity measures, mainly in the occipitoparietal and temporal areas (P < 0.05). Moreover, using a KNN classifier, all significant complexity measures yielded the best classification performance with an accuracy of 98.05%, sensitivity of 97.03% and specificity of 99.16% in detecting dementia. Conclusion: This study demonstrated a unique dynamic system within the brain impacted by dementia that results in more predictable patterns of cortical activity mainly in the occipitoparietal and temporal areas. These abnormal patterns were associated with patients' cognitive capacity and neuropsychiatric symptoms.

CdIn2Se4@chitosan heterojunction nanocomposite with ultrahigh photocatalytic activity under sunlight driven photodegradation of organic pollutants.

This research focused on synthesizing a CdIn2Se4@Ch nanocomposite by doping CdIn2Se4 into chitosan using a photolysis assisted ultrasonic process. The aim was to enhance the photodegradation efficiency of ofloxacin and 2,4-dichlorophenoxyacetic acid under sunlight. The synthesized CdIn2Se4@Ch nanocomposite was investigated via different techniques, including XRD, XPS, FTIR, TEM, DSC, TGA, UV-Vis and PL. The study also investigated the influence of various reaction parameters, including the effects of inorganic and organic ions. The synthesized nanocomposite demonstrated exceptional efficiency, achieving 86 % and 95 % removal rates, with corresponding rate constants of 0.025 and 0.047 min-1. This performance surpasses that of CdIn2Se4 by approximately 1.35 and 2.25 times, respectively. The values of COD were decreased to 78 and 86 % for ofloxacin and 2,4-dichlorophenoxyacetic, while the TOC values decreased to 71 and 84 %, respectively, from their premier values. The improvement in performance is associated with the introduction of CdIn2Se4 into chitosan, resulting in the self-integration of Cd into the catalyst. This creates a localized accumulation point for electrons, enhancing the efficiency of charge separation and further reducing the surface charge of chitosan. Experimental evidence suggests that superoxide and hydroxyl radicals play a significant role in the photodegradation of pollutants. Additionally, the nanocomposite exhibits excellent stability and can be reused up to five times, indicating remarkable stability and reusability of the developed photocatalyst.

N2 reduction to NH3 on surfaces of Co-Al18P18, Ni-Al21N21, Fe-B24N24, Mn-B27P27, Ti-C60 and Cu-Si72 catalysts.

CONTEXT: The abilities of Co-Al18P18, Ni-Al21N21, Fe-B24N24, Mn-B27P27, Ti-C60 and Cu-Si72 as catalysts for N2-RR to create the NH3 are investigated by theoretical levels. The ∆Eadoption and ∆Eformation of Co-Al18P18, Ni-Al21N21, Fe-B24N24, Mn-B27P27, Ti-C60 and Cu-Si72 are investigated. The ∆Eadsorption of N2-RR intermediates and ΔGreaction of reaction steps of N2-RR on Co-Al18P18, Ni-Al21N21, Fe-B24N24, Mn-B27P27, Ti-C60 and Cu-Si72 are examined. In acceptable mechanisms, the *NN → *NNH step is potential limiting step and *NN → *NNH step in enzymatic mechanism is endothermic reaction. The ∆Greaction of *NHNH2 → *NH2NH2 step on Co-Al18P18, Ni-Al21N21, Fe-B24N24, Mn-B27P27, Ti-C60 and Cu-Si72 are -0.904, -0.928, -0.860, -0.882, -0.817 and -0.838 eV, respectively. The Co-Al18P18 and Ni-Al21N21 have the highest ∆Greaction values for reaction steps of N2-RR. Finally, it can be concluded that the Co-Al18P18, Ni-Al21N21, Fe-B24N24 and Mn-B27P2 have acceptable potential for N2-RR by acceptable pathways. METHODS: The structures of Co-Al18P18, Ni-Al21N21, Fe-B24N24, Mn-B27P27, Ti-C60 and Cu-Si72 and N2-RR intermediates are optimized by PW91PW91/6-311+G (2d, 2p) and M06-2X/cc-pVQZ as theoretical levels in GAMESS software. The convergence for force set displacement of Co-Al18P18, Ni-Al21N21, Fe-B24N24, Mn-B27P27, Ti-C60 and Cu-Si72 and N2-RR intermediates are 1.5 × 105 Hartree/Bohr and 6.0 × 10-5 Angstrom. The Opt = Tight and MaxStep = 30 are considered to optimize Co-Al18P18, Ni-Al21N21, Fe-B24N24, Mn-B27P27, Ti-C60 and Cu-Si72 and N2-RR intermediates. The frequencies of Co-Al18P18, Ni-Al21N21, Fe-B24N24, Mn-B27P27, Ti-C60 and Cu-Si72 and N2-RR intermediates are calculated.