This review presents critical evaluation of the key parameters that affect the extraction of targeted components, giving due consideration to safety and environmental aspects. The crucial aspects of the extraction technologies along with protocols and process parameters for designing unit operations have been emphasized. The parameters like solvent usage, substrate type, concentration, particle size, temperature, quality and storage of extract as well as stability of extraction have been elaborately discussed. The process optimization using mathematical and computational modeling highlighting information and communication technologies have been given importance aiming for a green and sustainable industry level scaleup. The findings indicate that the extraction processes vary significantly depending on the category of food and its structure. There is no single extraction method or universal set of process conditions identified for extracting all value-added products from respective sources. A comprehensive understanding of process parameters and their optimization as well as synergistic combination of multiple extraction processes can aid in enhancement of the overall extraction efficiency. Future efforts must be directed toward the design of integrated unit operations that cause minimal harm to the environment along with investigations on economic feasibility to ensure sustainable extraction systems.
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http://dx.doi.org/10.1016/j.fct.2022.113207 | DOI Listing |
Insights Imaging
January 2025
Department of Radiology, Radio-Oncology and Nuclear Medicine, Université de Montréal, Montreal, QC, Canada.
Objectives: To compare thoracolumbar fascia (TLF) shear strain between individuals with and without nonspecific low back pain (NSLBP), investigate its correlation with symptoms, and assess a standardized massage technique's impact on TLF shear strain.
Methods: Participants were prospectively enrolled between February 2021 and June 2022. Pre- and post-intervention TLF ultrasound and pain/disability questionnaires were conducted.
J Neurol
January 2025
Jacobs Comprehensive MS Treatment and Research Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA.
Background: Previous investigations on optical coherence tomography (OCT) in multiple sclerosis (MS) focused on generalizable macular and peri-papillary regions without considering the anatomic variations of the retinal layer thickness.
Objective: This study aimed to assess the utility of parafoveal retinal layer thickness measured by OCT, underscoring its relationships with clinical outcomes in MS.
Methods: In this cross-sectional study, 214 people with MS (pwMS) and 57 age- and sex-matched healthy controls (HCs) were enrolled.
Ophthalmol Ther
January 2025
Pediatric Ophthalmology and Strabismus Division, King Khaled Eye Specialist Hospital, Al Urubah Branche Rd., West Building 2nd Floor, 11462, Riyadh, Saudi Arabia.
Introduction: Persistent fetal vasculature (PFV) is a congenital anomaly associated with significant surgical challenges, including a high risk of postoperative retinal detachment (RD). This study aimed to evaluate the impact of surgical approach and axial length (AL) on RD risk and visual outcomes in pediatric PFV management.
Methods: A retrospective cohort study was conducted involving 76 eyes of 74 patients who underwent cataract surgery for PFV between 2014 and 2022.
Radiol Artif Intell
January 2025
From the Department of Radiology, University Hospital, LMU Munich, Marchioninistr 15,81377 Munich, Germany (T.W., J.D., M.I.); Department of Statistics, LMU Munich, Munich, Germany (T.W., D.R.); and Munich Center for Machine Learning, Munich, Germany (T.W., J.D., D.R., M.I.).
Purpose To investigate whether the computational effort of 3D CT-based multiorgan segmentation with TotalSegmentator can be reduced via Tucker decomposition-based network compression. Materials and Methods In this retrospective study, Tucker decomposition was applied to the convolutional kernels of the TotalSegmentator model, an nnU-Net model trained on a comprehensive CT dataset for automatic segmentation of 117 anatomic structures. The proposed approach reduced the floating-point operations (FLOPs) and memory required during inference, offering an adjustable trade-off between computational efficiency and segmentation quality.
View Article and Find Full Text PDFBr J Math Stat Psychol
January 2025
Research Group of Quantitative Psychology and Individual Differences, Faculty of Psychology and Educational Sciences, Katholieke Universiteit, Leuven, Belgium.
In various areas of science, researchers try to gain insight into important processes by jointly analysing different datasets containing information regarding common aspects of these processes. For example, to explain individual differences in personality, researchers collect, for the same set of persons, data regarding behavioural signatures (i.e.
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