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Infections of the central nervous system (CNS) are potentially life-threatening and can cause serious morbidity. We evaluated the clinical value of metagenomic next-generation sequencing (mNGS) in the diagnosis of infectious encephalitis and meningitis and explored the factors affecting the results of mNGS. Patients with suspected cases of encephalitis or meningitis who presented in Northern Jiangsu People's Hospital from 1 March 2018 to 30 September 2022 were collected. Demographic, historical, and clinical information were obtained, and cerebrospinal fluid (CSF) samples were treated with mNGS. The pathogen was identified using National Center for Biotechnology Information (NCBI) GenBank sequence data. Ninety-six patients were screened and finally 90 subjects enrolled. Of the 90 enrolled cases, 67 (74.4%) were diagnosed with central nervous system infections, which included 48 cases (71.6%) of viral infection, 11 (12.2%) of bacterial infection, 5 (7.5%) of mycobacterium tuberculosis, 2 (3.0%) of fungal infection, and 1 (1.5%) of rickettsia infection. From these cases, mNGS identified 40 (44.4%) true-positive cases, 3 (3.3%) false-positive case, 22 (24.4%) true-negative cases, and 25 (27.8%) false-negative cases. The sensitivity and specificity of mNGS were 61.5% and 88%, respectively. mNGS of CSF could show a higher positive rate in patients with marked CSF abnormalities, including elevated protein concentrations and monocyte counts. mNGS of CSF is an effective method for detecting infectious encephalitis and meningitis, and the results should be analyzed combined with conventional microbiological testing results. [ABSTRACT FROM AUTHOR]

Summary: This article focuses on the fast finite‐time adaptive tracking control for non‐strict feedback stochastic nonlinear systems. Random disturbances with constraints have rarely been considered in previous studies of fast finite‐time stabilization problems. The corresponding extension of the adaptive fast finite‐time stabilization mechanism to stochastic nonlinear systems with full‐state constraints is one of the innovations of this article. First, neural networks and barrier Lyapunov functions are utilized to handle the problems arising from the unknown nonlinear terms and the state constraints, respectively. Second, an adaptive fast finite‐time tracking control scheme for stochastic systems is designed based on the backstepping technique and a fast finite‐time control strategy, which allows all signals of the closed‐loop system to be bounded. Meanwhile, the designed controller guarantees a fast convergence of the tracking error to a small neighborhood of the origin under full‐state constraints. Finally, two examples are given to illustrate the feasibility of the proposed method. [ABSTRACT FROM AUTHOR]

It is necessary to identify takeover behavior patterns of conditional autonomous driving. In this paper, using driving simulations, takeover request lead time (5 s and 10 s) and nondriving-related tasks (working task and entertainment task) are designed to study the takeover behavior pattern in crash scenarios. Through driving simulation experiment, the number of takeover behavior patterns is eleven and the number of first takeover behaviors is three. Results showed that the first takeover behavior has a significant impact on the first takeover reaction time, speed, lateral offset, and minimum TTC, but the first takeover behavior has no significant effect on the takeover correct time. The takeover request lead time (TORlt) has a significant impact on the pattern and the first takeover behavior, while the non-driving-related task (NDRT) has no significant effect on the pattern and the first takeover behavior. In addition, this paper constructs a maps of takeover operation behavior, which more intuitively shows the behavior changes during a takeover. [ABSTRACT FROM AUTHOR]

Background: Static shear wave elastography (SWE) is used to detect breast lesions, but slice and plane selections result in discrepancies.Objective: To evaluate the intraobserver reproducibility of continuous SWE, and whether quantitative elasticities in orthogonal planes perform better in the differential diagnosis of breast lesions.Method: One hundred and twenty-two breast lesions scheduled for ultrasound-guided biopsy were recruited. Continuous SWE scans were conducted in orthogonal planes separately. Quantitative elasticities and histopathology results were collected. Reproducibility in the same plane and diagnostic performance in different planes were evaluated.Results: The maximum and mean elasticities of the hardest portion, and standard deviation of whole lesion, had high inter-class correlation coefficients (0.87 to 0.95) and large areas under receiver operation characteristic curve (0.887 to 0.899). Without loss of accuracy, sensitivities had increased in orthogonal planes compared with single plane (from 73.17% up to 82.93% at most). Mean elasticity of whole lesion and lesion-to-parenchyma ratio were significantly less reproducible and less accurate.Conclusion: Continuous SWE is highly reproducible for the same observer. The maximum and mean elasticities of the hardest portion and standard deviation of whole lesion are most reliable. Furthermore, the sensitivities of the three parameters are improved in orthogonal planes without loss of accuracies. [ABSTRACT FROM AUTHOR]