Background: The study explores the challenges of handling multiblock data of different natures (process and NIR sensors) for on-line quality prediction in a full-scale plant scenario, namely a plant operating in continuous on an industrial scale and producing different grade Acrylonitrile Butadiene Styrene (ABS) products. This environment is an ideal scenario to evaluate the use of multiblock data analysis methods, which can enhance data interpretation, visualization, and predictive performances. In particular, a novel multiblock extension of Locally Weighted PLS has been proposed by the authors, namely Locally Weighted Multiblock Partial Least Squares (LW-MB-PLS). Response-Oriented Sequential Alternation (ROSA) has also been employed to evaluate the diverse block relevance for the prediction of two quality parameters associated with the polymer. Data are split in blocks both according to sensor type and different plant sections, and different models have been built by incremental addition of data blocks to evaluate if early estimation of product quality is feasible.
Results: ROSA method showed promising predictive performance for both quality parameters, highlighting the most influential plant sections through the selection of data blocks. The results suggested that both early and late-stage sensors play crucial roles in predicting product quality. A reasonable estimation of quality parameters before production completion has been achieved. On the other hand, the proposed LW-MB-PLS, while comparable in predictive performances, allowed reducing systematic prediction errors for specific products.
Significance: This study contributes valuable insights for continuous production processes, aiding plant operators and paving the way for advancements in online quality prediction and control. Furthermore, it is implemented as a locally weighted extension of MB-PLS.
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http://dx.doi.org/10.1016/j.aca.2024.342851 | DOI Listing |
Med Phys
January 2025
OncoRay - National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden - Rossendorf, Dresden, Germany.
Background: Patient-specific quality assurance (PSQA) is a crucial yet resource-intensive task in proton therapy, requiring special equipment, expertise and additional beam time. Machine delivery log files contain information about energy, position and monitor units (MU) of all delivered spots, allowing a reconstruction of the applied dose. This raises the prospect of phantomless, log file-based QA (LFQA) as an automated replacement of current phantom-based solutions, provided that such an approach guarantees a comparable level of safety.
View Article and Find Full Text PDFInfection
January 2025
Department of Infectious Diseases and Tropical Medicine, Hospital St. Georg, Leipzig, Germany.
Purpose: To analyze the associations between adherence to quality indicators (QIs) in the treatment of bloodstream infections caused by methicillin-susceptible Staphylococcus (S.) aureus (MSSA) and in-hospital mortality.
Methods: A retrospective observational study was conducted in patients admitted between 2019 and 2023 to Hospital St.
Med Phys
January 2025
Institute of Modern Physics, Chinese Academy of Sciences, Lanzhou, China.
Background: Online adaptive radiotherapy (OART) and rapid quality assurance (QA) are essential for effective heavy ion therapy (HIT). However, there is a shortage of deep learning (DL) models and workflows for predicting Monte Carlo (MC) doses in such treatments.
Purpose: This study seeks to address this gap by developing a DL model for independent MC dose (MCDose) prediction, aiming to facilitate OART and rapid QA implementation for HIT.
Environ Monit Assess
January 2025
Faculty of Water Supply and Environmental Engineering, Arba Minch University Water Technology Institute, P.O.B 21, Arba Minch, Ethiopia.
In developing nations, the biggest threat to public health is the quality of the water. The Kulfo River provides the majority demand of the domestic water and irrigation along its course; however, it is observed that wastes from anthropogenic and natural activities enter the river. Therefore, this study aimed to examine the pollution status by integrating conventional methods with benthic macroinvertebrates.
View Article and Find Full Text PDFComplement Ther Med
January 2025
Institute for Studies in Medicine History, Persian and Complementary Medicine, Iran University of Medical Science, Tehran, Iran; Department of Nutrition, School of Public Health, Iran University of Medical Sciences, Tehran, Iran; Student Research Committee, Iran University of Medical Sciences, Tehran, Iran. Electronic address:
Background: Conventional treatments for cardiometabolic diseases face limitations related to cost, efficacy, and side effects. Hibiscus sabdariffa (HS) is a common food product and a potential alternative. However, previous studies have shown inconsistent results and lacked assessments of result certainty, intervention safety, and subgroup analysis credibility.
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