It is an important means to study the electrical activity of the brain's nerve cells by exploring physiological information of the EEGs from the frequency domain. The gravity frequency is one of the global parameters with using this method. We used the multitaper spectrum method (MTM) spectrum estimation method of good performance to calculate the EEG spectrum and its gravity frequency of subjects under vigilance and vigilance decrement state. The results showed that the gravity frequency of vigilance state was higher than that of vigilance decrement state, the gravity frequency became smaller along with the vigilance decrement, and the location of the gravity frequency shifted to the left in the spectrum. Finally, the monitoring curve of the gravity frequency was acquired by designing an algorithm, and it was used to online monitoring vigilance operators.
Algorithms ; Brain ; physiology ; Electroencephalography ; Humans

Lung cancer is one of the malignant tumors with the highest incidence and mortality rate worldwide and has a poor prognosis. With the popularization of thin layer CT, more and more early lung cancers are being detected. In recent years, thoracoscopic technology and robotic surgery technology have been innovated, and multiple adjuvant therapies such as chemotherapy, targeted therapy and immunotherapy have progressed rapidly, providing lung cancer patients with multiple treatment options. However, the prognosis of lung cancer patients has not been significantly improved, which is related to the overall poor prognosis of lung cancer patients on the one hand, and the urgent need to find effective predictive markers for patients' prognosis, to accurately screen patients, and to carry out targeted treatment in order to improve patients' prognosis on the other hand. In this paper, we review the progress of tertiary lymphoid structures (TLSs) in lung cancer and discuss the prognostic predictive value of TLSs in lung cancer and their feasibility as biomarkers for adjuvant therapy.

Objective To investigate the association between gallstones (GS) and metabolic syndrome (MS) in southern Xinjiang, China, and to provide experience for the prevention and control of metabolic diseases in southern Xinjiang. Methods The patients with GS who visited First Division Hospital, Second Division Korla Hospital, and Third Division Hospital of Xinjiang Production and Construction Corps from March 2015 to March 2019 were enrolled as case group, and cluster sampling was used to select the individuals who underwent physical examination in Third Division 51st Regiment Hospital during the same period of time were enrolled as control group. According to inclusion and exclusion criteria, 1140 cases were enrolled in each group after 1∶ 1 matching based on age and sex. The t -test was used for comparison of continuous data between two groups, and the chi-square test was used for comparison of categorical data between two groups; a logistic regression analysis was used to investigate the influencing factors for GS. Dummy variables were included by logistic regression to evaluate multiplicative interaction between MS components, and the parameter estimate and covariance matrix of the logistic regression model and interaction calculation table were used to calculate and evaluate additive interaction between MS components. Results The risk of GS in MS patients was 2.33 times that in non-MS patients (odds ratio [ OR ]=2.33, 95% confidence interval [ CI ]: 1.86-2.92). In addition, the components of MS also increased the risk of GS, including blood glucose ( OR =2.94, 95% CI : 2.36-3.68), blood pressure ( OR =1.50, 95% CI : 1.26-1.80), blood lipids ( OR =1.48, 95% CI : 1.25-1.75), and body mass index ( OR =1.44, 95% CI : 1.21-1.70). After adjustment for multiple factors, the risk of GS gradually increased with the increase in the number of metabolic abnormalities, i.e., one abnormality ( OR =1.55, 95% CI : 1.22-1.99), two abnormalities ( OR =2.13, 95% CI : 1.66-2.72), three abnormalities ( OR =3.48, 95% CI : 2.59-4.69), and four abnormalities ( OR =4.65, 95% CI : 2.79-7.84). No additive or multiplicative interaction was found between MS components. Conclusion GS is closely associated with MS in southern Xinjiang, and the risk of GS gradually increases with the increase in MS components. No additive or multiplicative interaction is found between GS and MS components.