The transfer of graphics to a product's surface is a widely known technology. Printing, engraving, and etching are used every day in production processes with countless types of materials. This paper deals with quality control for laser engraving on surfaces with variable dimensions via optical sensors. The engraving process, apart from colour changes, can induce volume and moisture changes, which lead to dimension changes in some materials. Natural materials and biomaterials are among the ones most affected. Combined with the porous and inhomogeneous structure of such a material, it can be difficult to measure the quality of graphic transfer, especially for shaded products. The quality control of laser-engraved photographs on thin layers of wood veneer was selected as a suitable problem to solve. A complex method for the quality measurement of the specified production was designed and tested. We used an affine transformation to determine the system behaviour and to determine the transfer function of material changes during the production process. Moreover, there is a possibility to compensate the image deformation of the engraved product.
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http://dx.doi.org/10.3390/s22166030 | DOI Listing |
EXCLI J
November 2024
Second Department of Neurology, National and Kapodistrian University of Athens, School of Medicine, "Attikon" University Hospital, Athens, Greece.
Since the outbreak of the COVID-19 pandemic, there has been a global surge in patients presenting with prolonged or late-onset debilitating sequelae of SARS-CoV-2 infection, colloquially termed long COVID. This narrative review provides an updated synthesis of the latest evidence on the neurological manifestations of long COVID, discussing its clinical phenotypes, underlying pathophysiology, while also presenting the current state of diagnostic and therapeutic approaches. Approximately one-third of COVID-19 survivors experience prolonged neurological sequelae that persist for at least 12-months post-infection, adversely affecting patients' quality of life.
View Article and Find Full Text PDFJ Orthop Traumatol
January 2025
Department of Orthopedics, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China.
Background: The objective of this review is to evaluate the methodological quality of meta-analyses and observe the consistency of the evidence they generated to provide comprehensive and reliable evidence for the clinical use of three-dimensional (3D) printing in surgical treatment of fracture.
Methods: We searched three databases (PubMed, Embase, and Web of Science) up until August 2024. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) standards were adhered to in this review.
Quant Imaging Med Surg
January 2025
Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Currently, radiologists must interpret large quantities of images and identify diseases on a daily basis. The minimization of errors is crucial for high-quality diagnostic imaging and optimal patient care. Brain imaging is frequently used in clinical practice; however, radiologists are prone to overlook some regions in brain imaging and make perceptual errors, thus leading to missed diagnoses.
View Article and Find Full Text PDFBMC Bioinformatics
January 2025
Institute for Human Genetics, University Medical Center Johannes Gutenberg University, 55131, Mainz, Germany.
Background: Tissue clearing combined with light-sheet microscopy is gaining popularity among neuroscientists interested in unbiased assessment of their samples in 3D volume. However, the analysis of such data remains a challenge. ClearMap and CellFinder are tools for analyzing neuronal activity maps in an intact volume of cleared mouse brains.
View Article and Find Full Text PDFSci Rep
January 2025
Wollega University, Nekemte, Ethiopia.
This research paper presents an advanced AI-driven hybrid power quality management system for electrical railways that addresses critical challenges in 25 kV AC traction networks through a novel integration of single-phase PV-UPQC with ANN-Lyapunov control architecture. The system effectively manages voltage unbalance exceeding 2%, high THD, voltage variations of ± 10%, and poor power factor through a dual-approach methodology combining ANN-based reference signal generation with Lyapunov optimization, enabling dynamic parameter tuning and real-time load adaptation. MATLAB/Simulink simulations validate the system's superior performance, demonstrating significant improvements, including voltage unbalance reduction from 1.
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