Long-wave infrared (LWIR) imaging is widely used in night vision and thermal target recognition, but often suffers from noise and blurred edges. Here, we present a distributed Bragg reflector–liquid crystal (DBR-LC) framework for reconfigurable optical preprocessing of LWIR images. By combining the angle-dependent phas...
Abstract Pasture nutritive value is an important indicator of production efficiency in grazing systems. Remote sensing using unmanned aerial vehicles (UAVs) equipped with multispectral sensors could be an alternative to estimate pasture nutritional value through vegetation indices (VIs) and monitor animal feeding behav...
Guilherme Lobato Menezes, R.R. Mantovani, Maria Elisa Montes et al.· Journal of Animal Science· 0 citations
Transcatheter mitral valve interventions including transcatheter edge-to-edge repair and transcatheter mitral valve replacement have emerged as vital therapies for secondary mitral regurgitation (SMR) in patients at high or prohibitive surgical risk. Advanced multimodality imaging is central to patient selection, proce...
O. Chehab, R. Capasso, Victoria Delgado et al.· Circulation Cardiovascular I...· 0 citations
Can local physical learning destroy the conducting structure needed to define its own task? We study the Euclidean projected conductance-gradient flow of a finite passive resistor network with two fixed-potential terminals, one output, and one interior scalar target, under an explicit prune-and-continue convention for...
Oleg Dolgikh· Zenodo (CERN European Organi...· 0 citations
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Monitoring landings in data-scarce fisheries is hampered by short, noisy series and multi-year reporting gaps. We benchmark Echo State Networks (ESNs) against SARIMA, LightGBM, and LSTM models and against naïve and seasonal-naïve persistence, for one-step-ahead forecasting of the monthly landings (1993–2023) of the sha...
Diego Restrepo-Leal, Mario C. Cruz-Mercado, Jairo Altamar et al.· Applied Sciences· 0 citations
Background . The growing availability of large prokaryotic genomic datasets presents an opportunity to discover new metabolic pathways and enzymatic reactions useful for industrial or synthetic biological applications. Efforts to identify new enzyme functions in this vast number of sequences cannot be achieved without...
Mark Stam, Jordan Langlois, Céline Chevalier et al.· Peer Community Journal· 0 citations
Abstract
AI-native sixth-generation (6G) infrastructure will increasingly execute network, commercial and public-service actions through autonomous agents distributed across terminals, edges and clouds. Yet a conventional digital signature can authenticate a message without proving that the message was produced under a...
Murali Krishna Pasupuleti· International Journal of Aca...· 0 citations
Every finite bipartite simple graph occurs as a vertex-induced unrooted subgraph of the principal graph of an irreducible finite-depth inclusion of hyperfinite type II1 factors. For part sizes m and n, an explicit neighborhood-multiplicity parameter q gives index q3^n, with q at most m+1, and depth at most four. The se...
Alper Ferudun· Zenodo (CERN European Organi...· 0 citations
Abstract This dataset and software repository presents the formal implementation and theoretical framework of the Slot-Based Technical Taxonomy Model (N-Slot Engine). Evolving from a baseline 3-slot architecture (Header + Core + Modifier), this framework introduces deterministic 6-slot and 9-slot positional grammar sch...
Donald Sobaski· Zenodo (CERN European Organi...· 0 citations
Jennifer Neville did not want to go into computer science—but that’s exactly where she landed. Neville discusses the starts and stops that led to her professional sweet spot and her work identifying “surprising failures” making it hard for AI to handle complexity. The post What AI gets wrong and what failure teaches us appeared first on Microsoft Research.
MIT News · Artificial Intelligence· news.mit.eduOct 2, 2026