Abstract: A supercapacitor comprising at least one cell formed of two electrodes of opposite polarity. The cell is formed from a positive electrode and a negative electrode made of activated carbon, between which an electrolyte composition is arranged comprising at least one nitrile solvent, at least one salt and also comprising at least one additive from the family of phosphazenes having at least one fluorine atom. One of the compositions comprises acetonitrile, a tetramethylammonium tetrafluoroborate salt and an additive, hexafluorocyclotriphosphazene at a concentration of 1 to 10%.

Abstract: Apparatuses, systems, and techniques to enhance video are disclosed. In at least one embodiment, one or more neural networks are used to create a higher resolution video using upsampled frames from a lower resolution video.

Abstract: The present invention relates to an extract of algae from the order of ulvales, in particular an extract of green algae of the Ulva type, for its use for modulating the immune response in a human being or an animal, in particular for stimulating the immune response with view to infections. It also relates to the non-therapeutic use of an extract of green algae of the Ulva type for modulating the immune response.

Abstract: Systems and methods for automated segmentation of anatomical structures (e.g., heart). Convolutional neural networks (CNNs) may be employed to autonomously segment parts of an anatomical structure represented by image data, such as 3D MRI data. The CNN utilizes two paths, a contracting path and an expanding path. In at least some implementations, the expanding path includes fewer convolution operations than the contracting path. Systems and methods also autonomously calculate an image intensity threshold that differentiates blood from papillary and trabeculae muscles in the interior of an endocardium contour, and autonomously apply the image intensity threshold to define a contour or mask that describes the boundary of the papillary and trabeculae muscles. Systems and methods also calculate contours or masks delineating the endocardium and epicardium using the trained CNN model, and anatomically localize pathologies or functional characteristics of the myocardial muscle using the calculated contours or masks.

Abstract: Systems and methods for automated segmentation of anatomical structures, such as the human heart. The systems and methods employ convolutional neural networks (CNNs) to autonomously segment various parts of an anatomical structure represented by image data, such as 3D MRI data. The convolutional neural network utilizes two paths, a contracting path which includes convolution/pooling layers, and an expanding path which includes upsampling/convolution layers. The loss function used to validate the CNN model may specifically account for missing data, which allows for use of a larger training set. The CNN model may utilize multi-dimensional kernels (e.g., 2D, 3D, 4D, 6D), and may include various channels which encode spatial data, time data, flow data, etc. The systems and methods of the present disclosure also utilize CNNs to provide automated detection and display of landmarks in images of anatomical structures.

Abstract: Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) are commonly used to assess patients with known or suspected pathologies of the lungs and liver. In particular, identification and quantification of possibly malignant regions identified in these high-resolution images is essential for accurate and timely diagnosis. However, careful quantitative assessment of lung and liver lesions is tedious and time consuming. This disclosure describes an automated end-to-end pipeline for accurate lesion detection and segmentation.

Abstract: A supercapacitor comprising at least one cell formed of two electrodes of opposite polarity. The cell is formed from a positive electrode and a negative electrode made of activated carbon, between which an electrolyte composition is arranged comprising at least one nitrile solvent, at least one salt and also comprising at least one additive from the family of phosphazenes having at least one fluorine atom. One of the compositions comprises acetonitrile, a tetramethylammonium tetrafluoroborate salt and an additive, hexafluorocyclotriphosphazene at a concentration of 1 to 10%.

Abstract: A magnetometer is provided which measures an ambient magnetic field having a frequency range of interest. An optical pumping source emits in the direction of a cell filled with an atomic gas a light beam linearly polarised in a polarisation direction. A parametric resonance excitation circuit induces in the cell a radiofrequency magnetic field having two components orthogonal to the polarisation direction and each oscillating at its own oscillation frequency. A parametric resonance detection circuit performs synchronous detection at an inter-harmonic of oscillation frequencies of an electrical signal outputted by a photodetector arranged to receive the light beam having passed through the cell. A zero-field servo-control circuit generates from the synchronous detection a compensation magnetic field opposite to a component of the ambient magnetic field oriented in the polarisation direction.

Abstract: According to one aspect of the invention, there is proposed a capacitive radiofrequency MicroElectroMechanical System or capacitive RF MEMS comprising a metallic membrane suspended above an RF transmission line and resting on ground planes, and exhibiting a lower face, an upper face opposite to the lower face and a first layer comprising a refractory metallic material at least partially covering the upper face of the membrane so as to prevent the heating of the membrane.

Abstract: Systems and methods for automated segmentation of anatomical structures (e.g., heart). Convolutional neural networks (CNNs) may be employed to autonomously segment parts of an anatomical structure represented by image data, such as 3D MRI data. The CNN utilizes two paths, a contracting path and an expanding path. In at least some implementations, the expanding path includes fewer convolution operations than the contracting path. Systems and methods also autonomously calculate an image intensity threshold that differentiates blood from papillary and trabeculae muscles in the interior of an endocardium contour, and autonomously apply the image intensity threshold to define a contour or mask that describes the boundary of the papillary and trabeculae muscles. Systems and methods also calculate contours or masks delineating the endocardium and epicardium using the trained CNN model, and anatomically localize pathologies or functional characteristics of the myocardial muscle using the calculated contours or masks.

Abstract: Systems and methods for automated segmentation of anatomical structures (e.g., heart). Convolutional neural networks (CNNs) may be employed to autonomously segment parts of an anatomical structure represented by image data, such as 3D MRI data. The CNN utilizes two paths, a contracting path and an expanding path. In at least some implementations, the expanding path includes fewer convolution operations than the contracting path. Systems and methods also autonomously calculate an image intensity threshold that differentiates blood from papillary and trabeculae muscles in the interior of an endocardium contour, and autonomously apply the image intensity threshold to define a contour or mask that describes the boundary of the papillary and trabeculae muscles. Systems and methods also calculate contours or masks delineating the endocardium and epicardium using the trained CNN model, and anatomically localize pathologies or functional characteristics of the myocardial muscle using the calculated contours or masks.

Abstract: Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) are commonly used to assess patients with known or suspected pathologies of the lungs and liver. In particular, identification and quantification of possibly malignant regions identified in these high-resolution images is essential for accurate and timely diagnosis. However, careful quantitative assessment of lung and liver lesions is tedious and time consuming. This disclosure describes an automated end-to-end pipeline for accurate lesion detection and segmentation.

Abstract: Ionic liquids comprising the association of a cation have the following formula (I), in which —R1 is an acyclic hydrocarbonated group, n is a whole number between 0 and 3, and m is a whole number between 1 and 4, and an anion selected from a nitrate anion, a phosphate anion or an imidide anion.

Abstract: Electrolytes comprising at least one lithium salt and at least two ionic liquids, at least one of which is an ionic liquid resulting from the association of at least one cation complying with the following formula (I): In which: R1 is an acyclic hydrocarbon group; n is an integer ranging from 0 to 3; m is an integer ranging from 1 to 4; and at least one Y anion.

Abstract: An optical pumping and isotropic measurement magnetometer. The magnetometer is all-optical in the sense that resonance between Zeeman sub-levels is induced by modulating the intensity or the frequency of the pump beam. Resonance is detected either using the pump beam itself or an unmodulated probe beam. The pump beam is linearly polarised and its polarisation direction is kept constant relative to the direction of the magnetic field to be measured, so that a measurement independent of the orientation of the field can be made.

Abstract: A magnetometer including a detector configured to measure the amplitude of an output signal at an oscillation frequency to deduce a component of a magnetic field to be measured starting from the value of a resonance gradient, including a main excitation source outputting a measurement signal oscillating at a main oscillation frequency and a secondary excitation source outputting a reference signal with known amplitude oscillating at a secondary oscillation frequency, the detector being configured to measure the output signal amplitude at a harmonic of the secondary oscillation frequency and to deduce said resonance gradient. The invention also applies to a network of magnetometers and a method of measuring a magnetic field without slaving and compensation of fluctuations of the resonance gradient.

Abstract: A device for measuring an electric field in a conducting medium, including: two electrodes separated by a volume of an insulating material; a current measurement device; a voltage measurement device; and a switch enabling to alternately connect the current measurement device and the voltage measurement device between the electrodes.

Abstract: Systems and methods for automated segmentation of anatomical structures, such as the human heart. The systems and methods employ convolutional neural networks (CNNs) to autonomously segment various parts of an anatomical structure represented by image data, such as 3D MRI data. The convolutional neural network utilizes two paths, a contracting path which includes convolution/pooling layers, and an expanding path which includes upsampling/convolution layers. The loss function used to validate the CNN model may specifically account for missing data, which allows for use of a larger training set. The CNN model may utilize multi-dimensional kernels (e.g., 2D, 3D, 4D, 6D), and may include various channels which encode spatial data, time data, flow data, etc. The systems and methods of the present disclosure also utilize CNNs to provide automated detection and display of landmarks in images of anatomical structures.

Abstract: Systems and methods for automated segmentation of anatomical structures (e.g., heart). Convolutional neural networks (CNNs) may be employed to autonomously segment parts of an anatomical structure represented by image data, such as 3D MRI data. The CNN utilizes two paths, a contracting path and an expanding path. In at least some implementations, the expanding path includes fewer convolution operations than the contracting path. Systems and methods also autonomously calculate an image intensity threshold that differentiates blood from papillary and trabeculae muscles in the interior of an endocardium contour, and autonomously apply the image intensity threshold to define a contour or mask that describes the boundary of the papillary and trabeculae muscles. Systems and methods also calculate contours or masks delineating the endocardium and epicardium using the trained CNN model, and anatomically localize pathologies or functional characteristics of the myocardial muscle using the calculated contours or masks.

Abstract: Systems and methods for automated segmentation of anatomical structures (e.g., heart). Convolutional neural networks (CNNs) may be employed to autonomously segment parts of an anatomical structure represented by image data, such as 3D MRI data. The CNN utilizes two paths, a contracting path and an expanding path. In at least some implementations, the expanding path includes fewer convolution operations than the contracting path. Systems and methods also autonomously calculate an image intensity threshold that differentiates blood from papillary and trabeculae muscles in the interior of an endocardium contour, and autonomously apply the image intensity threshold to define a contour or mask that describes the boundary of the papillary and trabeculae muscles. Systems and methods also calculate contours or masks delineating the endocardium and epicardium using the trained CNN model, and anatomically localize pathologies or functional characteristics of the myocardial muscle using the calculated contours or masks.