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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. [ABSTRACT FROM AUTHOR]

Reinforced concrete deep beams are a vital member of infrastructures such as bridges, shear walls, and foundation pile caps. Thousands of dollars and human lives are seriously threatened due to shear failure, which have developed in deep beams containing web openings. This paper investigates numerically the overall behavior of simply supported concrete deep beams reinforced with carbon fiber-reinforced polymer (CFRP) sheets through forty specimens grouped in four groups. The numerical analysis results agreed well with the experimental results in the literature, particularly the visual failure initiation with a failure load difference of nearly 7%. Finite element analyses indicated that the presence of an opening with considerable width reduced the failure load by about 71% compared to the corresponding solid specimens. In addition, the reinforced concrete deep beam samples started to behave differently when the (b/h) ratio increased more than (2.0). The findings showed that the compression stress strut pathway had been disrupted by the web opening leading to stress redistribution, and the structure will behave as two separate members. Thus, the upper web-opening part sustained the most stress, while the part under the web-opening did not show any stress concentration. The numerical stress distribution results showed that the attributed reason is that rebars and openings helped redirect the stresses to the compression strut. Using CFRP sheets with a width of more than 160 mm significantly improved the reinforced concrete deep beam with web-opening due to the increasing confinement to the upper part of the reinforced concrete deep beams with the opening. [ABSTRACT FROM AUTHOR]

The current study aimed to evaluate the influence of different sintering temperatures on the properties of copper aluminum oxide (CuAlO2) pellets synthesized from copper oxide (CuO) and aluminum hydroxide (Al(OH)3) for application in smart infrastructure systems. The pellets were sintered at 400 K, 1000 K, and 1300 K, in the presence of nitrogen gas flow to reduce the amount of oxygen availability. The CuAlO2 sintered nanoparticles were chemically analyzed by X-ray diffractometry, and the nanostructure of the materials was studied by scanning electron microscopy. The transmittance of the sintered materials was examined by ultraviolet/visible (UV/Vis) spectrophotometry, and 88% transparency was observed for the pellets sintered at 1300 K. Electrical conductivity was measured at 0.905 mS/cm, indicating a semiconducting behavior. [ABSTRACT FROM AUTHOR]

In an international setting of developing countries, applying advanced statistical estimation approaches such as the system generalized method of moments (GMM), two-stage least square (2SLS) regressions, and cluster analysis, this paper revisits the impact of macro-level governance quality and the corruption index on the economic growth rate. We use cross-country panel data for 40 sub-Saharan and the Middle Eastern and North African (MENA) countries over the period of 2009–2020. The empirical results document the positive and negative effects of the national governance index and the corruption index on the economic growth rate. Additionally, foreign direct investment and population have a positive impact on the economic growth rate and trade openness has a negative impact. The study evaluates the robustness of these associations through a series of tests. These findings have important policy implications for policymakers and regulators in developing countries. In particular, the study recommends the implementation of an anti-corruption campaign and improving country-level governance quality that could encourage increased foreign direct investment for an accelerated economic growth rate. These will further enhance accountability, transparency, the rule of law, social responsibility, the public voice, and government effectiveness. [ABSTRACT FROM AUTHOR]