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    NAVETTE DE SUPPORT ET D'ECLAIRAGE D'AU MOINS UN OBJET, NOTAMMENT UN OEUF AVIAIRE, ET MACHINE COMPRENANT AU MOINS UNE TELLE NAVETTE
    1.
    发明公开
    NAVETTE DE SUPPORT ET D'ECLAIRAGE D'AU MOINS UN OBJET, NOTAMMENT UN OEUF AVIAIRE, ET MACHINE COMPRENANT AU MOINS UNE TELLE NAVETTE 审中-公开

    公开(公告)号：EP4427586A1

    公开(公告)日：2024-09-11

    申请号：EP24161003.9

    申请日：2024-03-01

    申请人： Unista

    发明人： BONICEL, Frédéric ,  BARREAU, Frédéric ,  FORGET, Anthony

    IPC分类号： A01K43/00 ,  G01N33/08

    CPC分类号： A01K43/00 ,  G01N33/085

    摘要： L'invention concerne une navette (1) et une machine comprenant au moins une telle navette (1), laquelle navette (1) comprend : - un ensemble de maintien dont un socle (2) comporte au moins une cavité inférieure apte à recevoir une région d'extrémité inférieure d'un objet (O) et dont une bride (4) supportée par le socle (2) comporte, en regard de la cavité inférieure, une cavité supérieure apte à recevoir une région d'extrémité supérieure de l'objet (O), en utilisation, l'ensemble de maintien (2-4) étant configuré pour occuper une position de maintien en position de l'objet (O) ; - au moins un dispositif d'éclairage situé dans l'une des cavités supérieure et inférieure ; - des moyens de connexion électrique comportant un ensemble connecteur électrique (70) accessible depuis l'extérieur du socle (2) et un ensemble conducteur d'électricité formant un chemin électrique entre l'ensemble connecteur électrique (70) et le ou chaque dispositif d'éclairage.

    METHOD FOR REDUCING PATHOGENS IN POULTRY HATCHERY OPERATIONS
    3.
    发明公开
    METHOD FOR REDUCING PATHOGENS IN POULTRY HATCHERY OPERATIONS 审中-实审

    公开(公告)号：EP4403914A2

    公开(公告)日：2024-07-24

    申请号：EP24179130.0

    申请日：2018-02-02

    申请人： Zoetis Services LLC

    发明人： WILLIAMS, Christopher John

    IPC分类号： G01N33/08

    CPC分类号： A01K43/00 ,  A01K41/06 ,  G01N33/085 ,  A01K45/007

    摘要： A pathogen reduction tool implementing a method of processing eggs at a poultry hatchery is provided. Such a method includes setting a production quantity of avian eggs in a setter incubator, the eggs being maintained in a plurality of egg flats. The avian eggs are removed from the setter incubator on a predetermined day of incubation, such predetermined day being during about day nine to day twelve of incubation. Subsequent to removal of the avian eggs from the setter incubator, the avian eggs are subjected to an egg detection system on the predetermined day to determine which of the avian eggs are viable and non-viable. The non-viable avian eggs are removed from the egg flats on the predetermined day. The viable avian eggs remaining in the egg flats post-inspection by the egg detection system are incubated through hatch.

    DIRECT INFERENCE BASED ON UNDERSAMPLED MRI DATA OF INDUSTRIAL SAMPLES
    6.
    发明公开
    DIRECT INFERENCE BASED ON UNDERSAMPLED MRI DATA OF INDUSTRIAL SAMPLES 审中-公开

    公开(公告)号：EP4202427A1

    公开(公告)日：2023-06-28

    申请号：EP21217638.2

    申请日：2021-12-23

    申请人： Orbem GmbH

    发明人： Coello Uribe, Jorge Eduardo ,  Kudielka, Guido ,  Gómez Damián, Pedro Agustín ,  Laparidou, Maria ,  Molina Romero, Miguel

    IPC分类号： G01N24/08 ,  G01R33/56 ,  G01R33/561 ,  G06T7/00 ,  B07C5/344 ,  G01N33/08 ,  G01R33/483

    摘要： Method for automated non-invasive identification of a predetermined feature in a multitude of industrial samples (102) of a predefined sample type, the method comprising the steps of: a) conveying an industrial sample (102) of the predefined sample type into an MRI scanner (106), b) recording in an MRI measurement for at least one slice or at least a partial volume of the industrial sample undersampled MRI data (300), comprising: - undersampled raw MRI data, comprising a multitude of time dependent signals for different phases, and/or - processed MRI data, obtained from processing undersampled raw MRI data, and c) analysing the undersampled MRI data (300) with an inference module (200) for identifying a predetermined feature of the industrial sample (102) using a machine learning module (204) that is trained for identifying the predetermined feature in industrial samples (102) of the predefined sample type from undersampled MRI data (300), wherein the inference module (200) comprises a memory (202) storing the machine learning module (204) and a processor (206) for controlling the inference module (200), wherein the inference module (200) is configured to provide the undersampled MRI data (300) as an input to the machine learning module (200) and to analyse the undersampled MRI data (300) using the machine learning module (204), wherein the machine learning module (204) is trained for identifying the predetermined feature in industrial samples (102) of the predefined sample type using a training set (302) comprising undersampled MRI data (300) of different training samples of the predefined sample type, wherein a fraction of the training samples comprises the predetermined feature and a fraction of the training samples does not comprise the predetermined feature.