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Confirmation of the unexpected occurrence of bitterness-inducing cucurbitacins in edible unripe melons by a two-step workflow based on liquid chromatography with combined UV and high-resolution MS detection.
Food Chem
December 2024
Dipartimento di Chimica; Centro Interdipartimentale SMART.
Plant metabolites known as cucurbitacins are known to impart an unpleasant bitter taste to edible fruits and even lead to severe health complications after the ingestion of relatively high amounts. In this study, an analytical method based on reversed phase liquid chromatography with combined detection by UV spectroscopy and atmospheric pressure chemical ionization high-resolution single/tandem mass spectrometry was applied to confirm the occurrence of four cucurbitacins (B, D, and R, and 23,24-dihydro cucurbitacin B) previously inferred in unexpectedly bitter-tasting fruits of an Italian variety (Scopatizzo) of unripe melon (Cucumis melo L.), known for the sweetness of its fruits.
View Article and Find Full Text PDFNeurocontrol for fixed-length trajectories in environments with soft barriers.
Neural Netw
December 2024
Department of Electrical and Computer Engineering, University of Alabama, Tuscaloosa, 35401, AL, US.
In this paper we present three neurocontrol problems where the analytic policy gradient via back-propagation through time is used to train a simulated agent to maximise a polynomial reward function in a simulated environment. If the environment includes terminal barriers (e.g.
View Article and Find Full Text PDF[Impact of artificial intelligence on the evolution of clinical practices in oncology: Focus on language models].
Bull Cancer
January 2025
Centre Léon-Bérard, Centre de recherche en cancérologie de Lyon, Lyon, France. Electronic address:
Artificial intelligence (AI) is addressing many expectations for healthcare practitioners and patients in oncology. It has the potential to deeply transform medical practices as we know them today: improving early diagnosis by analysing large quantities of medical data, refining personalised treatment plans and optimising patient follow-up. AI also makes it easier to identify new biomarkers and predict responses to therapies, reducing margins of error and speeding up clinical decisions.
View Article and Find Full Text PDFRevisiting the problem of learning long-term dependencies in recurrent neural networks.
Neural Netw
November 2024
Oak Ridge National Laboratory, Oak Ridge, TN, USA.
Recurrent neural networks (RNNs) are an important class of models for learning sequential behavior. However, training RNNs to learn long-term dependencies is a tremendously difficult task, and this difficulty is widely attributed to the vanishing and exploding gradient (VEG) problem. Since it was first characterized 30 years ago, the belief that if VEG occurs during optimization then RNNs learn long-term dependencies poorly has become a central tenet in the RNN literature and has been steadily cited as motivation for a wide variety of research advancements.
View Article and Find Full Text PDFBand edge modulation for high-performance LL-SAW resonators on LiNbO/SiC by introducing an ultra-thin intermediate oxide layer.
Ultrasonics
February 2025
State Key Laboratory of Materials for Integrated Circuits,Shanghai Institute of Microsystem and Information Technology, Shanghai 200050, China; Center of Materials Science and Optoelectronics Engineering, University of Chinese Academy of Science, Beijing 100190, China. Electronic address:
With the exploding demand of rapid information transmission, high-frequency acoustic filtering devices are becoming an immediate need. Longitudinal leaky surface acoustic wave (LL-SAW) devices with unique advantages can be a promising platform. In this paper, we introduce a 100 nm intermediate oxide layer into the X-cut lithium niobate on silicon carbide (LiNbO/SiC) to improve the in-band performance of LL-SAW resonators.
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