Stabilization diagrams to distinguish physical modes and spurious modes for structural parameter identification

A novel clustering stabilization diagram combined with self adaptive differential evolution algorithm is proposed to identify the modal parameters of civil engineering structures. Compared with the traditional stabilization diagram, the clustering diagram has drawn more attention because it can distinguish physical and spurious modes due to its automatic performance. In this paper, a self adaptive differential evolution algorithm is proposed to optimize the initial clustering centers so as to improve the clustering stabilization diagram. Moreover, this paper presents a new idea that the modal assurance criterion (MAC) composed of mode shapes is selected as the Y-axis to replace the model orders or damping ratios in existing stabilization diagrams. The results of a benchmark test of bridge Z24 and the numerical simulation of a continuous beam and a cable-stayed bridge demonstrate the advantages of the proposed approaches and the reliability of detecting the modal parameters

A Pairwise Likelihood Augmented Estimator for the Cox Model Under Left-Truncation

Survival data collected from prevalent cohorts are subject to left-truncation and the analysis is challenging. Conditional approaches for left-truncated data under the Cox model are inefficient as they typically ignore the information in the marginal likelihood of the truncation times. Length-biased sampling methods can improve the estimation efficiency but only when the stationarity assumption of the disease incidence holds, i.e., the truncation distribution is uniform; otherwise they may generate biased estimates. In this paper, we propose a semi-parametric method for the Cox model under general left-truncation, where the truncation distribution is unspecified. Our approach is to make inference based on the conditional likelihood augmented with a pairwise likelihood which eliminates the unspecified truncation distribution, yet retains the information about the regression coefficients and the baseline hazard function in the marginal likelihood. An iterative algorithm is provided to solve for the regression coefficients and the baseline hazard simultaneously. The proposed estimator is consistent and asymptotically normal with a closed-form consistent variance estimator. Simulations show a substantial efficiency gain in both the regression coefficients and the cumulative baseline hazard over the conditional approach estimator. Even when the stationarity assumption holds, our estimator results in better efficiency than some length-biased sampling estimators. An application to the analysis of a chronic kidney disease cohort study illustrates the utility of the method

Application effect of dual disease management theory in patients with alcoholic cardiomyopathy and heart failure

This paper explores the effect of application of dual disease management theory in the discharge readiness service for patients with alcoholic cardiomyopathy and heart failure. A retrospective study of 70 male patients with heart failure due to alcoholic cardiomyopathy was conducted. All patients were admitted in the hospital from September 2021 to September 2022. The control group was identified through an odd number, and the even number was the observation group, with 35 cases in each group. The control group received routine nursing care, and the observation group received a nursing model based on dual disease management theory, developed on the basis of the control group. The assessment criteria including the discharge readiness, binary coping score, self-efficacy score, self-care ability score and nursing compliance were compared between the two groups. The discharge readiness, patient and caregiver support coping score, self-efficacy and self-care ability scores of the observation group improved, compared to those of the control group, the difference was statistically significant (p < 0.05). The nursing compliance of the observation group was 91.4 %, statistically significantly higher (p < 0.05), compared to that of the control group (71.4%). The findings in this paper suggest that dual disease management theory applicable to the routine nursing can improve the nursing compliance and self-efficacy of patients with alcoholic cardiomyopathy and heart failure and self-care ability. Therefore, the dual management theory can effectively contribute to improving the level of patient support, response and patient care compliance

Feature Proliferation -- the "Cancer" in StyleGAN and its Treatments

Despite the success of StyleGAN in image synthesis, the images it synthesizes are not always perfect and the well-known truncation trick has become a standard post-processing technique for StyleGAN to synthesize high-quality images. Although effective, it has long been noted that the truncation trick tends to reduce the diversity of synthesized images and unnecessarily sacrifices many distinct image features. To address this issue, in this paper, we first delve into the StyleGAN image synthesis mechanism and discover an important phenomenon, namely Feature Proliferation, which demonstrates how specific features reproduce with forward propagation. Then, we show how the occurrence of Feature Proliferation results in StyleGAN image artifacts. As an analogy, we refer to it as the" cancer" in StyleGAN from its proliferating and malignant nature. Finally, we propose a novel feature rescaling method that identifies and modulates risky features to mitigate feature proliferation. Thanks to our discovery of Feature Proliferation, the proposed feature rescaling method is less destructive and retains more useful image features than the truncation trick, as it is more fine-grained and works in a lower-level feature space rather than a high-level latent space. Experimental results justify the validity of our claims and the effectiveness of the proposed feature rescaling method. Our code is available at https://github. com/songc42/Feature-proliferation.Comment: Accepted at ICCV 202

Di-μ-sulfato-κ4 O:O′-bis­[diaqua­(1H-imidazo[4,5-f][1,10]phenanthroline-κ2 N 7,N 9)cobalt(II)] dihydrate

In the centrosymmetric dinuclear title compound, [Co2(SO4)2(C13H8N4)2(H2O)4]·2H2O, the CoII atom is coord­in­ated by two N atoms from two 1H-imidazo[4,5-f][1,10]phenanthroline ligands, two O atoms from two sulfate anions and two O atoms from water mol­ecules in a distorted octa­hedral geometry. The Co⋯Co separation is 5.1167 (7) Å. The coordinated and uncoordinated water mol­ecules engage in N—H⋯O and O—H⋯O hydrogen-bonding inter­actions