Comprehensive Clustering Analysis and Profiling of COVID-19 Vaccine Hesitancy and Related Factors across U.S. Counties: Insights for Future Pandemic Responses.

This study employs comprehensive clustering analysis to examine COVID-19 vaccine hesitancy and related socio-demographic factors across U.S. counties, using the collected and curated data from Johns Hopkins University. Utilizing K-Means and hierarchical clustering, we identify five distinct clusters characterized by varying levels of vaccine hesitancy, MMR vaccination coverage, population demographics, and political affiliations. Principal Component Analysis (PCA) was conducted to reduce dimensionality, and key variables were selected based on their contribution to cumulative explained variance. Our analysis reveals significant geographic and demographic patterns in vaccine hesitancy, providing valuable insights for public health strategies and future pandemic responses. Geospatial analysis highlights the distribution of clusters across the United States, indicating areas with high and low vaccine hesitancy. In addition, multiple regression analyses within each cluster identify key predictors of vaccine hesitancy in corresponding U.S. county clusters, emphasizing the importance of socio-economic and demographic factors. The findings underscore the need for targeted public health interventions and tailored communication strategies to address vaccine hesitancy across the United States and, potentially, across the globe.

A Digital Image Correlation Technique for Laboratory Structural Tests and Applications: A Systematic Literature Review.

Digital image correlation (DIC) is an optical technique used to measure surface displacements and strains in materials and structures. This technique has demonstrated significant utility in structural examination and monitoring. This manuscript offers a comprehensive review of the contemporary research and applications that have leveraged the DIC technique in laboratory-based structural tests. The reviewed works encompass a broad spectrum of structural components, such as concrete beams, columns, pillars, masonry walls, infills, composite materials, structural joints, steel beams, slabs, and other structural elements. These investigations have underscored the efficacy of DIC as a metrological instrument for the precise quantification of surface deformation and strain in these structural components. Moreover, the constraints of the DIC technique have been highlighted, especially in scenarios involving extensive or complex test configurations. Notwithstanding these constraints, the effectiveness of the DIC methodology has been validated as a strain measurement instrument, offering numerous benefits such as non-invasive operation, full-field measurement capability, high precision, real-time surveillance, and compatibility with integration into other measurement instruments and methodologies.

Fracture Properties Evaluation of Cellulose Nanocrystals Cement Paste.

Due to the need for high-performance and sustainable building materials, the investigation of the determination of fracture toughness of cement paste using new and sustainable materials, such as cellulose nanocrystals (CNCs) is worthwhile. Contrary to other well-known nano-reinforcement particles, such as carbon nanotubes, CNCs are less toxic; therefore, they have less safety and environmental risks. Fracture behavior of cement paste has been studied intensively for a long time. However, the incorporation of new materials in the cement paste, such as cellulose nanocrystal materials (CNCs), has not been fully investigated. In this paper, the fracture behavior, compressive strength, and hydration properties of cement paste reinforced with cellulose nanocrystal particles were studied. At the age of 3, 7, and 28 days, a three-point bending moment test, and a calorimetry and thermogravimetric analysis, scanning electron microscopy (SEM), and energy dispersive x-ray spectroscopy (EDX) analysis were performed on the water-to-binder-weight ratio of 0.35 cement paste, containing 0.0%, 0.2%, and 1.0% volume cellulose nanocrystals. Results indicated that the fracture properties and compressive strength were improved for the sample containing 0.2% CNCs. Preliminary results indicate that CNCs can improve the fracture behavior of cementitious materials and can be considered as a renewable and sustainable material in construction.