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Finite strip method (FSM) is a classical method to analyze the buckling of thin-walled members. The traditional FSM adopting trigonometric functions longitudinally can hardly analyze the members with spaced ribs along the longitudinal direction, while the compound strip method (CSM) can compensate for this shortcoming. Based on the CSM, the influence of utilizing plane elements and shell elements to respectively imitate stiffeners on buckling is investigated. Compared with the shell-element ribs, the plane-element ribs are prone to assembling the stiffener matrices with fewer degrees of freedom. But the shell-element ribs are more comprehensive as the out-plane displacement of ribs are taken into consideration. It is found that plane element ribs and shell element ribs have little difference on the buckling capacity of members. The buckling capacity has a small difference of mean absolute error (MAE) underneath 0.75% between the two types of CSMs, and the buckling capacity and modes are in good agreement with the finite element results. The buckling loads of the two types of CSMs are close to the FEM with a MEA less than 5%. The accuracy of the plane elements satisfies the predicted requirements, which helps to reduce the program computation and simplify the analysis complexity. The efficiency of analysis can be dramatically improved for fine meshing elements.

Purpose: This study aims to examine the risk factors for catheter-associated urinary tract infection (CAUTI) following radical hysterectomy for cervical cancer (CC). Furthermore, the study seeks to develop a visual model that can effectively assist physicians in improving their proficiency in diagnosing, treating, and preventing CAUTIs. Patients and Methods: 48 subjects who developed CAUTI postoperatively were assigned to the infection group. There were 443 cases who did not develop CAUTI, and a 1:1 propensity score matching (PSM) method was employed to match 48 cases for the non-infection group. Univariate logistic and multivariate stepwise regression analyses were used to analyze the risk factors for CAUTI following radical hysterectomy for CC. Subsequently, a nomogram-based model was developed, and its effectiveness was comprehensively assessed. Results: The incidence rate of CAUTI in 491 patients who underwent radical hysterectomy for CC was 9.76% (48/491). Multivariate stepwise regression analysis revealed that the duration of urinary catheterization, urinary leukocyte esterase, and positive urine culture were the independent risk factors for CAUTI after radical hysterectomy for CC (all β > 0, P < 0.05). A nomogram model incorporating these independent risk factors was constructed, and receiver operating characteristic (ROC) and decision curve analysis (DCA) curves were generated. The ROC curve exhibited an area under the curve value of 0.9035, 95% CI of 0.8352– 0.9718, specificity of 0.8214, sensitivity of 0.8571, accuracy of 0.8429, positive predictive value of 0.8780, and negative predictive value of 0.7931. Conclusion: The duration of urinary catheterization, urinary leukocyte esterase, and positive urine culture are independent risk factors for CAUTI after radical hysterectomy for CC. This nomogram-based model exhibits numerous advantages, including simplicity, user-friendliness, high diagnostic accuracy, and significant clinical value, which can provide assistance in early clinical diagnosis decision-making. [ABSTRACT FROM AUTHOR]

In the process of aluminum alloy reflector mirror processing, the structural defects of aluminum alloys present bottlenecks restricting the development of aluminum alloy reflector mirror processing technologies. Therefore, this study proposes an aluminum alloy reflector mirror processing method involving ultrasonic rolling and single-point diamond turning. The core idea of this method is to use ultrasonic rolling to pretreat the surface of the workpiece to refine the grains and increase the hardness, then perform single-point diamond turning to improve the optical reflection performance. In this study, an ultrasonic rolling cutting experiment was carried out, and the influence of the material preparation method on the microstructure and hardness of the workpiece was analyzed. An ultrasonic rolling single-point diamond turning experiment was carried out, and the influence of the material preparation method on the reflection performance of single-point diamond turning was studied. Results showed that compared with single-point diamond turning after ordinary milling, the ultrasonic rolling single-point diamond turning method has certain advantages in improving the surface reflection performance, with an increase of 5.116%. The method proposed in this study can provide new ideas for the high-quality processing of aluminum alloy reflector mirrors. [ABSTRACT FROM AUTHOR]

Mastering the high strain characteristics at cryogenics and constructing an accurate constitutive model are critical for establishing a cryogenic cutting simulation of Ti-6Al-4V alloy. The traditional constitutive model is inadequate for accounting for high and cryogenic conditions. In this paper, cryogenic split Hopkinson pressure bar (SHPB) experiments are conducted, specifically for Ti-6Al-4V alloy, to develop a modified Johnson–Cook (J–C) constitutive model that incorporates the cryogenic effect. A coupled two-dimensional orthogonal finite element simulation involving temperature displacement was conducted for the cryogenic cutting of Ti-6Al-4V alloy. This simulation was performed using ABAQUS, based on a modified J–C constitutive model subroutine. It was observed that the smallest discrepancy between the simulation results and the data from ice-fixed milling experiments was just 2.12%. The modified J–C constitutive model is more adept at simulating the chip morphology under cryogenic conditions. It was also found that cryogenic machining enhances the distribution of temperature and stress within the chip. For every 5°C reduction in processing temperature, the tool temperature diminishes by more than 2%. [ABSTRACT FROM AUTHOR]

Background: To identify risk factors for acquiring HAIs in COVID-19 patients and establish visual prediction model. Methods: Data was extracted from Xinglin Hospital Infection Monitoring System to analyze COVID-19 patients diagnosed between December 1, 2022, and March 1, 2023. Univariate and multivariate analyses were conducted to identify risk factors. Predictive signature was developed by selected variables from lasso, logistic regression, and their intersection and union. Models were compared using DeLong's t-tests. Likelihood ratio (LR) and Youden's index was used to evaluate the predictive performance. Nomogram was constructed using optimal variables ensemble, prediction accuracy was evaluated using AUC, DCA and calibration curve. Results: Total of 739 patients met the criteria, of which 53 (7.2%) were HAIs. NSAIDs, surgery, fungi and MDRO detected, hormone drugs and LYMR were independent risk factors. Lasso model screened seven variables, and logistic model identified six risk factors. Union model performed the best with the maximum of the Youden's index is 0.703, the sensitivity is 95.6%, the specificity is 74.7%, the LR is 3.778. The best AUC of union model is 0.953 (0.928– 0.978), and the accuracy is 87.5%. DCA indicated that the union model provided the best net benefits and calibration curve demonstrated good predictive agreement. Conclusions: HAIs prediction in COVID-19 patients is feasible and beneficial to improve prognosis. Physicians can use this nomogram to identify high-risk COVID-19 populations for HAIs and tailor follow-up strategies. [ABSTRACT FROM AUTHOR]