l. guo

To assess the value of color Doppler ultrasonography (CDUS) in diagnosing carotid atherosclerotic plaque (CAP) in cerebral infarction (CI) patients.

Totally 100 CI patients in our hospital from March 2021 to March 2023 were included in the study group (SG), and another 98 patients who received physical examination at the same time were included in the control group (CG). CDUS was performed to determine the type, distribution and total detection rate of carotid atherosclerotic plaque, and to evaluate carotid blood flow parameters, carotid intima-media thickness (IMT) and stenosis degree in the two groups.

No significant difference of plaque in the proportion of external carotid artery (ECA), internal carotid artery (ICA), common carotid artery (CCA) and carotid artery bifurcation between the two groups (P>0.05). Relative to the CG, the detection rate of each type of carotid atherosclerotic plaque in the SG was significantly higher (P=0.03 and P<0.001), peak systolic flow velocity (PSV), minimum diastolic flow velocity (EDV), and resistance index (RI) of carotid blood flow were lower, and IMT was higher in the SG (P<0.05), and the proportion of mild, moderate and severe carotid artery stenosis in the SG were higher (P<0.01 and P<0.001).

CDUS can detect the distribution and quantity of plaques, determine the type and stability of plaques, and assess the carotid blood flow parameters and stenosis, which is valuable for the diagnosis of CAP in CI, and guides the formulation of clinical treatment plan.

To study the relationship between high-resolution computed tomography (HRCT) signs and the pathological subtypes and differentiation degree of lung adenocarcinoma.

We retrospectively reviewed HRCT images of 394 lung adenocarcinoma cases and compared the diversity of images among preinvasive lesions (PILs), minimally invasive adenocarcinoma (MIA) and invasive adenocarcinoma (IAC) and the differentiation degrees of IAC by Kruskal-Wallis and χ2 tests.

There were significant differences in the size, density and incidences of the pleura traction sign, spicule sign, lobulation sign, tumor vascular sign, bronchial cutoff sign, air bronchogram sign and cavity sign of PILs, MIA and IAC (χ2=2.172~247.077, P<0.05). The incidences of all these signs (except for the cavity sign) in IAC were higher than those in the other two groups (P<0.05). There were no significant differences in margin irregularity or vacuole signs among PILs, MIA and IAC (P>0.05). There were significant differences in the size, density, and incidences of margin irregularity, the pleura traction sign, the spicule sign, the lobulation sign, the tumor vascular sign, the bronchial cutoff sign and the cavity sign in the three differentiated subgroups (χ2=6.818~63.331, P<0.05).  No significant differences were found in the air bronchogram sign and vacuole sign among the three differentiated subgroups (P>0.05).

HRCT signs of lung adenocarcinoma are closely related to the pathological subtype and differentiation degree and have great value in helping predict tumor types and devise clinical treatment plans.

A novel Halbach permanent magnet array with rectangle section and trapezoid section is proposed and optimized in this paper. The analytical model of the premanent magnet segment is established based on the surface current method, which is numerically efficient and can be utilized to evaluate the magnetic field closely with the premanent magnet segment’s configurations. The analytical model of the Halbach array is acquired based on the superposition principle and coordinate transformation. The fundamental component of the magnetic flux density and the sinusoidal distortion rate are chosen as the optimization object. And the optimization is executed on the Halbach array with one specific set of dimensions by the genetic algorithm in global scale. The effectiveness of the optimization is validated by the finite element analysis. Compared to the traditional Halbach array with rectangle section, the magnetic field created by the optimized proposed Halbach array in this paper owns better performance.

This study proposed a novel method for system failure reasoning based on Bayesian networks to solve emergency airflow control system reliability problems. A system fault tree model was established to identify the logical relationship between the units, which was then transformed into a Bayesian network fault analysis model to determine network node states and the conditional probability table, as well as to carry out diagnostic reasoning on the system node branches. The reliability analysis of the model based on Netica Bayesian tool shows that the probability of system failure caused by substation communication node is the highest under normal conditions, and data monitoring and central station communication nodes have a greater impact on intelligent control. By predicting and diagnosing system faults, the optimization of system design is realized on the framework of Bayesian network to improve the reliability, and there by establishing a theoretical foundation for future disaster prevention research.