Schizophrenia patients always show cognitive impairment, which is proved to be related to hypo-connectivity or hyper-connectivity. Further, individuals with an ultra-high risk for psychosis also show abnormal functional connectivity-related cognitive impairment, especially in the alpha rhythm. Thus, the identification of functional networks is essential to our understanding of the disorder. We investigated the resting-state functional connectivity of the alpha rhythm measured by electroencephalography (EEG) to reveal the relation between functional network and clinical symptoms. The participants included 28 patients with first-episode schizophrenia (FES), 28 individuals with ultra-high risk for psychosis (UHR), and 28 healthy controls (HC). After the professional clinical symptoms evaluation, all the participants were instructed to keep eyes closed for 3-min resting-state EEG recording. The 3-min EEG data were segmented into artefact-free epochs (the length was 3 s), and the functional connectivity of the alpha phase was estimated using the phase lag index (PLI), which measures the phase differences of EEG signals. The FES and UHR groups displayed increased resting-state PLI connectivity compared with the HC group [F(2,74) = 10.804, p < 0.001]. Significant increases in the global efficiency, the local efficiency, and the path length were found in the FES and UHR groups compared with those of the HC group. FES and UHR showed an increased degree of connectivity compared with HC. The degree of the left occipital lobe area was higher in the UHR group than in the FES group. The hypothesis of disconnection is confirmed. Furthermore, differences between the UHR and FES group were found, which is valuable for producing clinical significance before the onset of schizophrenia.

Traditional optimization algorithms for blind signal separation (BSS) are mainly based on the gradient, which requires the objective function to be continuous and differentiable, so the applications of these algorithms are very limited. Moreover, these algorithms have problems with the convergence speed and accuracy. To overcome these drawbacks, this paper presents a modified glowworm swarm optimization (MGSO) algorithm based on a novel step adjustment rule and then applies MGSO to BSS. Taking kurtosis of the mixed signals as the objective function of BSS, MGSO-BSS succeeds in separating the mixed signals in Matlab environment. The simulation results prove that MGSO is more effective in capturing the global optimum of the objective function of the BSS algorithm and has faster convergence speed and higher accuracy, compared with particle swarm optimization (PSO) and GSO.

Electrochemical synthesis of NH 3 from H 2 O and N 2 , as a sustainable alternative to the Haber−Bosch process, has attracted extensive attention. However, the achievement of effective NH 3 electrosynthesis remains challenging since N 2 features remarkable thermodynamic stability and ultralow solubility in aqueous electrolytes. Here, we prepare new-type Cr-based spinel oxides using coprecipitation and hydrothermal methods. The ternary spinel ZnCr 2−x Fe x O 4 phases are formed by substituting Fe 3+ ions for Cr 3+ ions at octahedral sites of ZnCr 2 O 4 . The introduction of Fe results in lattice expansion, lattice distortion, an increase in oxygen vacancies, and a remarkable change in the electronic structure, which further affect nitrogen chemisorption and activation properties. The asfabricated ZnCr 1.2 Fe 0.8 O 4 spinel has bifunctional active sites of Cr 3+ and Fe 3+ and exhibits large capacity and moderate strength of N 2 chemisorption. To break the N 2 solubility limit in the aqueous electrolytes for electrosynthesis of NH 3 , a novel two-step process of gas-phase N 2 adsorption and electroreduction is successfully developed. The catalyst has excellent catalytic performances with an ammonia formation rate of 29.26 μg h −1 cm −2 , the highest Faradaic efficiency of 18.41%, and long-term stability for 20 h. This study provides a new strategy for developing a highly efficient electrocatalyst for the electrosynthesis of NH 3 .

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