Externally bonded reinforcements are commonly and widely used in civil engineering objects made of concrete to increase the structure load capacity or to minimize the negative effects of long-term operation and possible defects. The quality of adhesive bonding between a strengthened structure and steel or composite elements is essential for effective reinforcement; therefore, there is a need for non-destructive diagnostics of adhesive joints. The aim of this paper is the detection of debonding defects in adhesive joints between concrete beams and steel plates using the modal analysis approach. The inspection was based on modal shapes and their further processing with the use of continuous wavelet transform (CWT) for precise debonding localization and imaging. The influence of the number of wavelet vanishing moments and the mode shape interpolation on damage imaging maps was studied. The results showed that the integrated modal analysis and wavelet transform could be successfully applied to determine the exact shape and position of the debonding in the adhesive joints of composite beams.
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http://dx.doi.org/10.3390/ma14113014 | DOI Listing |
J Phys Chem B
January 2025
Department of Physiology and Biophysics, Weill Cornell Medical College, New York, New York 10065, United States.
ModeHunter is a modular Python software package for the simulation of 3D biophysical motion across spatial resolution scales using modal analysis of elastic networks. It has been curated from our in-house Python scripts over the last 15 years, with a focus on detecting similarities of elastic motion between atomic structures, coarse-grained graphs, and volumetric data obtained from biophysical or biomedical imaging origins, such as electron microscopy or tomography. With ModeHunter, normal modes of biophysical motion can be analyzed with various static visualization techniques or brought to life by dynamics animation in terms of single or multimode trajectories or decoy ensembles.
View Article and Find Full Text PDFCardiovasc Diagn Ther
December 2024
The First Affiliated Hospital, Department of Cardiology, Hengyang Medical School, University of South China, Hengyang, China.
Background And Objective: Radiomics is an emerging technology that facilitates the quantitative analysis of multi-modal cardiac magnetic resonance imaging (MRI). This study aims to introduce a standardized workflow for applying radiomics to non-ischemic cardiomyopathies, enabling clinicians to comprehensively understand and implement this technology in clinical practice.
Methods: A computerized literature search (up to August 1, 2024) was conducted using PubMed to identify relevant studies on the roles and workflows of radiomics in non-ischemic cardiomyopathy.
Physiol Meas
January 2025
Academy of Military Science of the People's Liberation Army, Beijing, 100073, CHINA.
Objective: Humanity faces many health challenges, among which respiratory diseases are one of the leading causes of human death. Existing AI-driven pre-diagnosis approaches can enhance the efficiency of diagnosis but still face challenges. For example, single-modal data suffer from information redundancy or loss, difficulty in learning relationships between features, and revealing the obscure characteristics of complex diseases.
View Article and Find Full Text PDFBackground: Mild Cognitive Impairment (MCI) is the prodromal stage of dementia, including Alzheimer's Disease (AD). Early identification and accurate assessment of MCI are critical for clinical trial enrichment as well as the early intervention of AD. Digital makers offered a unique opportunity for ecologically valid and affordable early detection approaches.
View Article and Find Full Text PDFAlzheimers Dement
December 2024
Department of Neurobiology, Care Sciences and Society, Center for Alzheimer Research, Karolinska Institutet, Stockholm, Sweden.
Background: Detecting early stages of Alzheimer's disease (AD) remains a crucial yet complex challenge. While recent interest has surged in detecting biomarkers linked with the disease preclinical phase, a comprehensive understanding of the concomitant peripheral biological pathways before the potential disease onset is necessary. We aim to explore the associations between the 18F-MK6240 tau PET tracer with plasma inflammatory markers, other AT(X)N biomarkers and episodic memory.
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