Multi-function sensing applications based on high Q-factor multi-Fano resonances in an all-dielectric metastructure.

A multi-function sensor based on an all-dielectric metastructure for temperature and refractive index sensing simultaneously is designed and analyzed in this paper. The structure is composed of a periodic array of silicon dimers placed on the silicon dioxide substrate. By breaking the symmetry of the structure, the ideal bound states in the continuum can be converted to the quasi-bound states in the continuum, and three Fano resonances are excited in the near-infrared wavelength. Combining with the electromagnetic field distributions, the resonant modes of three Fano resonances are analyzed as magnetic dipole, magnetic toroidal dipole, and electric toroidal dipole, respectively. The proposed sensor exhibits an impressive maximal Q-factor of 9352, with a modulation depth approaching 100%. Our investigation into temperature and refractive index sensing properties reveals a maximum temperature sensitivity of 60 pm/K. Regarding refractive index sensing, the sensitivity and figure of merit are determined to be 279.5 nm/RIU and 2055.1 RIU-1, respectively. These findings underscore the potential of the all-dielectric metastructure for simultaneous multi-parameter measurements. The sensor's versatility suggests promising applications in biological and chemical sensing.

Decision-making ability limitations and brain neural activity changes in healthcare workers after mild COVID-19.

Studies have demonstrated that the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) extensively affects brain function. Although cognitive dysfunction is considered a common manifestation in COVID-19 patients during the recovery period, the potential changes in decision-making ability, are not yet clear. Decision-making functions are essential to the work of healthcare workers. However, there is a lack of a multidimensional assessment of its functioning in COVID-19 cases. Here, we used tests combined with the resting-state functional magnetic resonance imaging (rs-fMRI) stabilization feature amplitude of low-frequency fluctuations (ALFF) to explore decision-making behavior and brain neural activity changes in healthcare workers after mild COVID-19. Participants were divided into the SARS-CoV-2 infected group (SI, n = 41) and healthy controls (HC, n = 42). All participants underwent a series of neuropsychological tests. They performed the Iowa Gambling Task (IGT) and the Game of Dice Task (GDT), followed by fMRI (n = 20) to assess their decision-making ability under ambiguous and risky conditions and changes in brain neural activity. The SI group performed worse in verbal memory than the HC group. Furthermore, the SI group performed worse in the IGT, whereas no significant difference was observed in the GDT. In addition, rs-fMRI showed enhanced spontaneous neural activity in the postcentral gyrus and inferior parietal lobe in the SI group compared to the HC group.

Attentional impairment and altered brain activity in healthcare workers after mild COVID-19.

Severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) is highly transmissible and pathogenic. Patients with mild cases account for the majority of those infected with coronavirus disease 2019 (COVID-19). Although there is evidence that many patients with COVID-19 have varying degrees of attentional impairment, little is known about how SARS-COV-2 affects attentional function. This study included a high-risk healthcare population divided into groups of healthcare workers (HCWs) with mild COVID-19 (patient group, n = 45) and matched healthy HCWs controls (HC group, n = 42), who completed general neuropsychological background tests and Attention Network Test (ANT), and underwent resting-state functional magnetic resonance imaging (rs-fMRI) using amplitude of low-frequency fluctuation (ALFF) to assess altered brain activity; Selective impairment occurred in orienting and executive control networks, but not in alert network, in the patient group, and widespread cognitive impairment encompassing general attention, memory, and executive dysfunction. Moreover, the patient group had significantly lower ALFF values in the left superior and left middle frontal gyri than the HC group. SARS-COV-2 infection may have led to reduced brain activity in the left superior and left middle frontal gyri, thus impairing attentional orienting and executive control networks, which may explain the development of attentional deficits after COVID-19.

Prevalence and risk factors of psychotic symptoms in middle-aged patients with first-episode drug-naïve major depressive disorder: A large-scale cross-sectional study.

BACKGROUND: Psychotic symptoms are common in patients with major depressive disorder (MDD). However, few studies have assessed the incidence of comorbid psychotic symptoms in first-episode drug naïve (FEDN) MDD patients. The present study aimed to evaluate the prevalence and risk factors of psychotic symptoms in a large sample of middle-aged Chinese patients with FEDN MDD. METHODS: 813 middle-aged (age range 35 to 65 years) outpatients with FEDN MDD were recruited. The 17-item Hamilton Rating Scale for Depression (HAMD), the 14-item Hamilton Anxiety Rating Scale (HAMA), and the positive subscales of the Positive and Negative Syndrome Scale (PANSS) were used to assess patient anxiety, depression and psychotic symptoms, respectively. RESULTS: The prevalence of psychotic symptoms in middle-aged patients with FEND MDD was 10.95 %. Multivariate logistic regression analysis showed that HAMA score, HAMD score, TSH, TC and BMI levels were significant predictors of psychotic symptoms in MDD middle-aged patients. The HAMA score and HAMD score predicted psychotic symptoms for both male and female middle-aged patients with MDD, while higher TSH, TC and BMI levels were correlated with psychotic symptoms only in female MDD patients. Furthermore, combining the HAMA score, HAMD score, and TSH could differentiate between psychotic major depression (PMD) and nonpsychotic major depression (NPMD) in middle-aged patients. CONCLUSIONS: Psychotic symptoms among middle-aged patients with MDD can be identified by integrating clinical and biological variables as early as possible during the first time see a doctor.

Molecular Simulation to Explore the Dissolution Behavior of Sulfur in Carbon Disulfide.

Soluble sulfur (S8) and insoluble sulfur (IS) have different application fields, and molecular dynamics simulation can reveal their differences in solubility in solvents. It is found that in the simulated carbon disulfide (CS2) solvent, soluble sulfur in the form of clusters mainly promotes the dissolution of clusters through van der Waals interaction between solvent molecules (CS2) and S8, and the solubility gradually increases with the increase in temperature. However, the strong interaction between polymer chains of insoluble sulfur in the form of polymer hinders the diffusion of IS into CS2 solvent, which is not conducive to high-temperature dissolution. The simulated solubility parameter shows that the solubility parameter of soluble sulfur is closer to that of the solvent, which is consistent with the above explanation that soluble sulfur is easy to dissolve.