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In this article, the equivalent elastic modulus of the resin-impregnated Nomex honeycomb core is derived by considering the bending and stretching deformation of the honeycomb wall, based on the Euler beam theory. The elastic modulus obtained by the proposed theoretical method is proved to be in good accordance with both the experimental results and numerical results. Furthermore, the effect of the geometric parameters on the equivalent mechanical properties of the honeycomb core is discussed using a dimensionless method.

Over the past few decades, nanotechnology has developed rapidly and has been applied to various fields. Gold nanoclusters (AuNCs), which are composed of several hundred atoms, are a new type of nanomaterial. AuNCs are often synthesized using ligands or templates. The interaction between the gold atoms and the groups of the ligands or templates results in unexpected physical and chemical properties. In recent studies, natural proteins have often been used as templates to synthesize AuNCs. The unique structure of natural proteins endows AuNCs with biological functions, such as biocompatibility and enzymatic activity. The unique properties of these natural protein-AuNCs have been verified and applied in various fields. In this article, the synthetic strategies used to produce AuNCs have been divided into two categories: animal-derived and plant-derived protein synthesis. The protein types and synthesis strategies used in the current mainstream research are reviewed, and their applications in detection and biological imaging are summarized. Finally, the problems and future development directions of AuNCs synthesized from natural proteins are discussed, laying a foundation for the biological application of protein-AuNCs.

This paper tackles current challenges in network security analysis by proposing an innovative information gain-based feature selection algorithm and leveraging visualization techniques to develop a network security log data visualization system. The system’s key functions include raw data collection for firewall logs and intrusion detection logs, data preprocessing, database management, data manipulation, data logic processing, and data visualization. Through statistical analysis of log data and the construction of visualization models, the system presents analysis results in diverse graphical formats while offering interactive capabilities. Seamlessly integrating data generation, processing, analysis, and display processes, the system demonstrates high accuracy, precision, recall, F1 score, and real-time performance metrics, reaching 98.3%, 92.1%, 97.5%, 98.1%, and 91.2%, respectively, in experimental evaluations. The proposed method significantly enhances real-time prediction capabilities of network security status and monitoring efficiency of network devices, providing a robust security assurance tool.

As composite materials are playing more important role in advanced aircraft structures,the change of mechanical properties of composites during service is of significant importance for the overall safety of the aircraft.In order to achieve the goal of fatigue evaluation and life prediction of composite components of aircraft based on guided wave in-situ detection,firstly,the fatigue evolution law of composite materials is studied from the perspectives of macroscopic phenomenology and microscopic physics.Then,the potential of guided wave phase velocity and mode conversion phenomenon for fatigue characterization is discussed through analyzing the guided wave field.At the same time,a deep learning framework is constructed to extract fatigue evolution features from the guided wave field in a data-driven manner.Finally,a fatigue evolution model based on the Bayesian model averaging method is proposed to predict the residual fatigue life of the composite specimen.The results show that,by extracting and analyzing the guided wave propagating features,the fatigue state of composite materials can be accurately characterized.Combining the Bayesian model averaging method and the confidence interval criterion,the goal of residual life prediction before specimen fatigue failure is achieved.

The data filling, mathematical calculations and statistical operations for property management are realised by a system development tool that adopts the browser/server (B/S) architecture, Java, as the development language and a framework that adopts Spring MVC mode; additionally, the MySQL database is used, the source code and database interaction process use the Mybatis framework and the front-end display uses the VUE.js framework.. Functional modules include the following elements: owner information, real estate information, engineering equipment, personnel management and lease management. The system has passed the functional test, if it has been in trial operation for 1 year in multiple residential communities and has the characteristics of simple operation, stable operation and strong scalability, among others.

Honeycomb sandwich panels have become more and more widely used in the aerospace field, and the fatigue problems that occur during their application have become increasingly prominent. At present, there is little research on the fatigue of honeycomb sandwich panels, and the test methods used in the study are also very different. Under different test methods, the fatigue process of Nomex honeycomb sandwich panels varies greatly. This article mainly reviews the research progress of the fatigue of honeycomb sandwich panels. The purpose is to compare the fatigue damage process of honeycomb sandwich panels under different test methods and summarize the similarities and differences of the fatigue performance of honeycomb sandwich panels. By introducing the fatigue test method, fatigue damage process, fatigue life prediction method and fatigue life curve of honeycomb sandwich panel, the research direction of the fatigue of honeycomb sandwich panel is proposed.

In this paper, the mean velocity profiles and the multi-layer division of the turbulent boundary layer (TBL) are studied for the entire adverse pressure gradient (APG) region before separation. By asymptotic expansions of the mean velocity, the difference in the APG effect between the inner and outer regions and the problems of directly matching the mean velocity are demonstrated. The wall law of the overlapping region, i.e., the log-pressure law, is derived from the perspective of turbulent transport in combination with the results of matching the Reynolds shear stress. The results show that it is applicable in the entire APG region, thus answering the questions of the existence of the log law, the slope of the log law, and the breakdown of the log law. A new half-power law is then proposed after reconsidering the self-similarity of the outer region. This law is believed to be valid only in the outer region of larger APGs and is only an approximate self-similar law compared to the wall law in the inner region. Furthermore, a multi-layer division of APG TBLs is presented to form a complete framework for describing the mean flow of APG TBLs. In particular, the basis of the division and the specific range of each layer are specified, where the range of the overlapping region involves the definition of a critical Reynolds number. [ABSTRACT FROM AUTHOR]

Ultra-precision machining has higher requirements for the performance of abrasive tools, but the traditional grinding wheel has some problems such as irregular grain arrangement, limited chip space, and high grinding temperature. Therefore, a structured grinding wheel suitable for ultra-precision machining is proposed. In this study, the laser cladding method and ultrasonic vibration technology were combined to study the preparation process of a structured grinding wheel. Firstly, the quality evaluation system of the printing layer was established, and the shape coefficient and dilution rate were used to evaluate the laser cladding quality. The effects of laser power, sweep speed, powder feeding speed, and ultrasonic power on the shape coefficient and dilution rate of the printing layer were analyzed by single-factor experiments. The level range of each factor in the orthogonal experiment was established to optimize the process parameters. The surface morphology was observed, and the influence of ultrasonic vibration on the morphology was analyzed. The structured grinding wheel was prepared according to the optimized parameters. [ABSTRACT FROM AUTHOR]

Background: Socioeconomic status (SES) plays a crucial role in blood pressure (BP) control. SES may influence BP control through obesity indices, such as body mass index (BMI) and waist circumference (WC). This study aimed to understand the relationships between SES and BP control in the elderly hypertensive population, and to determine whether BMI and WC mediate the relationship between SES and BP control. Methods: The study was conducted in Jia County, Henan Province, China, from 1 July to 31 August 2023. The 18,963 hypertensive people over 65 years old who were included in the National Basic Public Health Service Program were investigated. The study utilized questionnaire surveys to collect data on participants' demographic characteristics, disease history, lifestyle behaviors, antihypertensive medication, and measured height, weight, and blood pressure. SES was indexed by participants' self-reported educational level, family income, and occupation, and categorized into low, medium, and high groups by using latent category analysis (LCA). Logistic regression models were used to analyze the associations between SES and BP control. Obesity indicators, represented by BMI and WC, were included in mediation models to examine the indirect effects of BMI/WC on the association between SES and BP control. Results: The mean age of 17,234 participants was 73.4 years and 9888 (57.4%) of the participants were female. The LCA results indicated the number of participants in low SES, middle SES, and high SES groups were 7760, 8347, and 1127, respectively. Compared with the low SES group, the odds ratios (ORs) and 95% confidence intervals (CIs) for the association of BP control with middle SES and high SES were 1.101 (1.031, 1.175), and 1.492 (1.312, 1.696). This association was similarly found in the subsequent subgroup analyses (p < 0.05). Compared with low SES, our findings further suggested that BMI (indirect effects: 95% CIs: −0.004–−0.001; p < 0.001) and WC (indirect effects: 95% CIs: −0.003–−0.001; p = 0.020) play a suppressing role in the association between high SES and BP control. Conclusions: Our study indicated that the elderly hypertensive population with high SES may have a better result for BP control. However, we found that BMI/WC plays a suppressing role in this association. This indicated that despite the better BP control observed in elderly hypertensive populations with high SES, BMI and WC might undermine this beneficial relationship. Therefore, implementing strategies for obesity prevention is an efficient way to maintain this beneficial association between high SES and BP control. [ABSTRACT FROM AUTHOR]

Globally, the rollout of COVID‐19 vaccine had been faced with a significant barrier in the form of vaccine hesitancy. This study adopts a multi‐stage perspective to explore the prevalence and determinants of COVID‐19 vaccine hesitancy, focusing on their dynamic evolutionary features. Guided by the integrated framework of the 3Cs model (complacency, confidence, and convenience) and the EAH model (environmental, agent, and host), this study conducted three repeated national cross‐sectional surveys. These surveys carried out from July 2021 to February 2023 across mainland China, targeted individuals aged 18 and older. They were strategically timed to coincide with three critical vaccination phases: universal coverage (stage 1), partial coverage (stage 2), and key population coverage (stage 3). From 2021 to 2023, the surveys examined sample sizes of 29 925, 6659, and 5407, respectively. The COVID‐19 vaccine hesitation rates increased from 8.39% in 2021 to 29.72% in 2023. Urban residency, chronic condition, and low trust in vaccine developer contributed to significant COVID‐19 vaccine hesitancy across the pandemic. Negative correlations between the intensity of vaccination policies and vaccine hesitancy, and positive correlations between vaccine hesitancy and long COVID, were confirmed. This study provides insights for designing future effective vaccination programs for emerging vaccine‐preventable infectious X diseases. [ABSTRACT FROM AUTHOR]

This paper presents an outer velocity scale and an inner scaling law of Reynolds shear stresses that are valid for the entire adverse pressure gradient (APG) region before separation, based on asymptotic expansions in turbulent boundary layers (TBLs). By reexamining the velocity defect and Reynolds shear stress in the outer region of TBLs, it is demonstrated that the pressure gradient effect can be included in asymptotic expansions. The mathematical requirements to be satisfied by the outer velocity scale are given. On this basis, we define a new outer velocity scale Uo, which is used in the mean momentum balance analysis over the entire APG region. The results show that there is a slowly evolving region of the Reynolds shear stress gradient in APG TBLs. We obtain a logarithmic decay law for the Reynolds stress gradient by asymptotic matching in this region, thus providing functional expressions for the total shear stress and total shear stress gradient in the inner region of TBLs. These expressions are valid for the entire APG region. Furthermore, we use the new velocity scale to determine three self-similar parameters in the momentum equation to discuss the conditions for approximate equilibrium. The changes in parameters point to changes in two physical properties of APG TBLs, the inertial force and turbulence production. [ABSTRACT FROM AUTHOR]

Aims and Objectives: To investigate whether chronic diseases are associated with higher COVID‐19 vaccine hesitancy and explore factors that influence COVID‐19 vaccine hesitancy in patients with chronic diseases. Background: Vaccine hesitancy has been acknowledged as one of the greatest hazards to public health. However, little information is available about COVID‐19 vaccine hesitancy among patients with chronic diseases who may be more susceptible to COVID‐19 infection, severe disease or death. Methods: From 6 to 9 August 2021, we performed an internet‐based cross‐sectional survey with 22,954 participants (14.78% participants with chronic diseases). Propensity score matching with 1:1 nearest neighbourhood was used to reduce confounding factors between patients with chronic diseases and the general population. Using a multivariable logistic regression model, the factors impacting COVID‐19 vaccine hesitancy were identified among patients with chronic diseases. Results: Both before and after propensity score matching, patients with chronic diseases had higher COVID‐19 vaccine hesitancy than the general population. In addition, self‐reported poor health, multiple chronic diseases, lower sociodemographic backgrounds and lower trust in nurses and doctors were associated with COVID‐19 vaccine hesitancy among patients with chronic diseases. Conclusions: Patients with chronic diseases were more hesitant about the COVID‐19 vaccine. Nurses should focus on patients with chronic diseases with poor health conditions, low socioeconomic backgrounds and low trust in the healthcare system. Relevance to Clinical Practice: Clinical nurses are recommended to not only pay more attention to the health status and sociodemographic characteristics of patients with chronic diseases but also build trust between nurses and patients by improving service levels and professional capabilities in clinical practice. Patient or Public Contribution: Patients or the public were not involved in setting the research question, the outcome measures, or the design or implementation of the study. However, all participants were invited to complete the digital informed consent and questionnaires. [ABSTRACT FROM AUTHOR]