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Update of the list of qualified presumption of safety (QPS) recommended microbiological agents intentionally added to food or feed as notified to EFSA 24: Suitability of taxonomic units notified to EFSA until March 2026

EFSA Journal, Volume 24, Issue 7, July 2026.
Abstract The Qualified Presumption of Safety (QPS) process was developed to provide a harmonised safety assessment approach to support EFSA Scientific Panels and Units. The QPS approach assesses the taxonomic identity, body of knowledge and safety of microorganisms intentionally added to the food and feed chain.
EFSA Panel on Biological Hazards (BIOHAZ), Ana Allende, Avelino Alvarez‐Ordóñez, Valeria Bortolaia, Sara Bover‐Cid, Alessandra De Cesare, Wietske Dohmen, Laurent Guillier, Liesbeth Jacxsens, Maarten Nauta, Lapo Mughini‐Gras, Jakob Ottoson, Luisa Peixe, Fernando Perez‐Rodriguez, Panagiotis Skandamis, Elisabetta Suffredini, Marianne Chemaly, Pier Sandro Cocconcelli, Pablo Salvador Fernández Escámez, Miguel Prieto Maradona, Amparo Querol, Lolke Sijtsma, Ingvar Sundh, Fulvio Barizzone, Marta Bisaschi, Sandra Correia, Lieve Herman   +26 more
wiley   +1 more source

Acceleration of Image Classification and Object Tracking by the Intel Neural Compute Stick 2 with Power Efficiency Evaluation on Raspberry Pi 4B. [PDF]

Sensors (Basel)
Gao T, Suto J.
europepmc   +1 more source

Handbook of Establishing and Maintaining Oxygen‐Free Atmospheres

Advanced Engineering Materials, Volume 28, Issue 12, 17 June 2026.
This study presents a practical framework for creating oxygen‐free atmospheres at ambient pressure using silane‐doped inert gases. The results show that ultra‐low oxygen levels and strongly reduced water content can be achieved through controlled silane dosing, drying systems, and sensor monitoring.
Sascha Jan Zimmermann, René Gustus, Lienhard Wegewitz, Wolfgang Maus‐Friedrichs   +3 more
wiley   +1 more source

Time course measurements of leaf elevation angles during shade avoidance response in <i>Arabidopsis thaliana</i> using <i>Raspberry Pi</i> computers and computer vision technique. [PDF]

MicroPubl Biol
Kim BB.
europepmc   +1 more source

A Raspberry Pi-Based Traumatic Brain Injury Detection System for Single-Channel Electroencephalogram. [PDF]

Sensors (Basel), 2021
Dhillon NS, Sutandi A, Vishwanath M, Lim MM, Cao H, Si D.   +5 more
europepmc   +1 more source

Optimizing success rate with Nonlinear Mapping Control in a high-performance raspberry Pi-based light source target tracking system. [PDF]

PLoS One
Zhou G, Zhang B, Li Q, Zhao Q, Zhang S.
europepmc   +1 more source

Enhancing cotton whitefly (Bemisia tabaci) detection and counting with a cost-effective deep learning approach on the Raspberry Pi. [PDF]

Plant Methods
Feng Z, Wang N, Jin Y, Cao H, Huang X, Wen S, Ding M.   +6 more
europepmc   +1 more source

DATIV-Remote Enhancement of Smart Aerosol Measurement System Using Raspberry Pi-Based Distributed Sensors. [PDF]

Sensors (Basel)
Hasanuzzaman G, Buchwald T, Schunk C, Egbers C, Schröder A, Hampel U.   +5 more
europepmc   +1 more source

Raspberry PI-based GLSL code testing system

Метою даної кваліфікаційної роботи бакалавра є проектування та реалізація системи тестування GLSL коду на базі Raspberry PI. У кваліфікаційній роботі бакалавра спроектовано архітектуру системи тестування GLSL коду на базі Raspberry PI, розроблено ...
Muzychuk, Andriy, Музичук, Андрій Андрійович   +1 more
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