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Mathematical and computational modeling for organic and insect frass fertilizer production: A systematic review.
PLoS One
January 2025
Data Management, Modelling and Geo-Information Unit, International Centre of Insect Physiology and Ecology, Kenya.
Organic fertilizers have been identified as a sustainable agricultural practice that can enhance productivity and reduce environmental impact. Recently, the European Union defined and accepted insect frass as an innovative and emerging organic fertilizer. In the wider domain of organic fertilizers, mathematical and computational models have been developed to optimize their production and application conditions.
View Article and Find Full Text PDFPredicting vasovagal reactions to needles from video data using 2D-CNN with GRU and LSTM.
PLoS One
January 2025
Department of Cognitive Science and Artificial Intelligence, Tilburg University, Tilburg, The Netherlands.
When undergoing or about to undergo a needle-related procedure, most people are not aware of the adverse emotional and physical reactions (so-called vasovagal reactions; VVR), that might occur. Thus, rather than relying on self-report measurements, we investigate whether we can predict VVR levels from the video sequence containing facial information measured during the blood donation. We filmed 287 blood donors throughout the blood donation procedure where we obtained 1945 videos for data analysis.
View Article and Find Full Text PDFArtificial Intelligence for Optical Coherence Tomography in Glaucoma.
Transl Vis Sci Technol
January 2025
Glaucoma Service, Wills Eye Hospital, Philadelphia, PA, USA.
Purpose: The integration of artificial intelligence (AI), particularly deep learning (DL), with optical coherence tomography (OCT) offers significant opportunities in the diagnosis and management of glaucoma. This article explores the application of various DL models in enhancing OCT capabilities and addresses the challenges associated with their clinical implementation.
Methods: A review of articles utilizing DL models was conducted, including convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs), autoencoders, and large language models (LLMs).
Flexible Synaptic Memristors With Controlled Rigidity in Zirconium-Oxo Clusters for High-Precision Neuromorphic Computing.
Adv Sci (Weinh)
January 2025
School of Advanced Materials Science and Engineering, Sungkyunkwan University, Suwon, 16419, Republic of Korea.
Flexible memristors are promising candidates for multifunctional neuromorphic computing applications, overcoming the limitations of conventional computing devices. However, unpredictable switching behavior and poor mechanical stability in conventional memristors present significant challenges to achieving device reliability. Here, a reliable and flexible memristor using zirconium-oxo cluster (ZrOOH(OMc)) as the resistive switching layer is demonstrated.
View Article and Find Full Text PDFForensic sex classification by convolutional neural network approach by VGG16 model: accuracy, precision and sensitivity.
Int J Legal Med
January 2025
Centro de Estatística e Aplicações Universidade de Lisbao, CEAUL, Faculdade de Ciências da Universidade de Lisboa no Bloco C6 - Piso 4, Lisboa, 1749-016, Portugal.
Introduction: In the reconstructive phase of medico-legal human identification, the sex estimation is crucial in the reconstruction of the biological profile and can be applied both in identifying victims of mass disasters and in the autopsy room. Due to the inherent subjectivity associated with traditional methods, artificial intelligence, specifically, convolutional neural networks (CNN) may present a competitive option.
Objectives: This study evaluates the reliability of VGG16 model as an accurate forensic sex prediction algorithm and its performance using orthopantomography (OPGs).
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