13 research outputs found

    Extraction of physicochemical properties from the fluorescence spectrum with 1D convolutional neural networks : application to olive oil

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    One of the main challenges for olive oil producers is the ability to assess oil quality regularly during the production cycle. The quality of olive oil is evaluated through a series of parameters that can be determined, up to now, only through multiple chemical analysis techniques. This requires samples to be sent to approved laboratories, making the quality control an expensive, time-consuming process, that cannot be performed regularly and cannot guarantee the quality of oil up to the point it reaches the consumer. This work presents a new approach that is fast and based on low-cost instrumentation, and which can be easily performed in the field. The proposed method is based on fluorescence spectroscopy and one-dimensional convolutional neural networks and allows to predict five chemical quality indicators of olive oil (acidity, peroxide value, UV spectroscopic parameters K270 and K232, and ethyl esters) from one single fluorescence spectrum obtained with a very fast measurement from a low-cost portable fluorescence sensor. The results indicate that the proposed approach gives exceptional results for quality determination through the extraction of the relevant physicochemical parameters. This would make the continuous quality control of olive oil during and after the entire production cycle a reality

    Compact optical fluorescence sensor for food quality control using artificial neural networks: application to olive oil

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    https://spie.org/photonics-europe/presentation/Compact-optical-fluorescence-sensor-for-food-quality-control-using-artificial/12139-80?enableBackToBrowse=true Aufgezeichnet und für TN als Video on demand abrufbar Eine Autorin zuviel aufgenommen? Martos, Vanessa

    Adapting UK Biobank imaging for use in a routine memory clinic setting: The Oxford Brain Health Clinic

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    The Oxford Brain Health Clinic (BHC) is a joint clinical-research service that provides memory clinic patients and clinicians access to high-quality assessments not routinely available, including brain MRI aligned with the UK Biobank imaging study (UKB). In this work we present how we 1) adapted the UKB MRI acquisition protocol to be suitable for memory clinic patients, 2) modified the imaging analysis pipeline to extract measures that are in line with radiology reports and 3) explored the alignment of measures from BHC patients to the largest brain MRI study in the world (ultimately 100,000 participants). Adaptations of the UKB acquisition protocol for BHC patients include dividing the scan into core and optional sequences (i.e., additional imaging modalities) to improve patients’ tolerance for the MRI assessment. We adapted the UKB structural MRI analysis pipeline to take into account the characteristics of a memory clinic population (e.g., high amount of white matter hyperintensities and hippocampal atrophy). We then compared the imaging derived phenotypes (IDPs) extracted from the structural scans to visual ratings from radiology reports, non-imaging factors (age, cognition) and to reference distributions derived from UKB data. Of the first 108 BHC attendees (August 2020-November 2021), 92.5 % completed the clinical scans, 88.0 % consented to use of data for research, and 43.5 % completed the additional research sequences, demonstrating that the protocol is well tolerated. The high rates of consent to research makes this a valuable real-world quality research dataset routinely captured in a clinical service. Modified tissue-type segmentation with lesion masking greatly improved grey matter volume estimation. CSF-masking marginally improved hippocampal segmentation. The IDPs were in line with radiology reports and showed significant associations with age and cognitive performance, in line with the literature. Due to the age difference between memory clinic patients of the BHC (age range 65–101 years, average 78.3 years) and UKB participants (44–82 years, average 64 years), additional scans on elderly healthy controls are needed to improve reference distributions. Current and future work aims to integrate automated quantitative measures in the radiology reports and evaluate their clinical utility

    D-2 Physiognomy, Art, and Artifice in The Rape of Lucrece and The Devil’s Law-Case

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    Critics have noted two predominant, competing attitudes toward art in the Renaissance. For some, art was problematic because its artifice obfuscated reality. For others, art elevated humankind by allowing artists to create, like God. Early modern artistic treatises, however, reveal that artists also valued art because of its physiognomic ability. In other words, they believed that art could communicate the painted individual’s true nature, attitude, and perhaps even secrets, especially through the face, a theory about art literary critics largely overlook. But even as artists acknowledged art’s epistemological power, they also faced the potential idealization undertaken in any artistic endeavor, especially portraits, works of art most likely to signify physiognomically. These varied approaches to and ideas about art also appear in Renaissance literature. While many texts consider the status of art, in William Shakespeare’s poem The Rape of Lucrece, the titular protagonist directly articulates and confronts the tension between art as physiognomic communicator and artificial epistemological obstructer, with a particular focus on the overlooked role of physiognomy and art. A similar interrogation of art’s illuminative vs. deceptive status occurs in John Webster’s drama The Devil’s Law-Case. Yet Webster’s text takes into account something Lucrece does not, the important role gender plays in both the creation and reception of art. Thus, by carefully considering the characterization of art in both The Rape of Lucrece and The Devil’s Law-Case, we can examine the importance of physiognomy and gender, respectively, to Renaissance art’s complicated status
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