Abstract: A system (100) for managing incoming calls in a user's mobile device (3) while using a user's virtual reality, VR, device (1), comprising a user's mobile device (3) comprising a SIM card associated to a Mobile Subscriber Integrated Services Digital Number, MSISDN, the SIM card associated to a mobile carrier from an IP Multimedia. Subsystem, IMS, network (6), a user's virtual reality, VR, device (1) comprising computing means (2) to perform a pairing process between the mobile device (3) and the user's VR device (1) and managing incoming calls, an authentication module (4) configured to authenticate the user's mobile device (3), wherein authenticate means that the VR user (A) is in possession of the user's mobile device (3) comprising the SIM card; and a Web Real Time Communications Gateway, WebRTC GW(5) connected to the IMS network (6) of the mobile carrier and configured to translate IMS signaling into WebRTC signaling.

Abstract: The present invention relates to a microscope for quantitative measurements of the wavefront, comprising: means for the illumination of a sample (T); an objective lens (2); an ordered two-dimensional arrangement of lenses (3), with a spacing p? greater than 500 ?m and a relative aperture of less than 10; an image sensor (4) located in a capture space (Ec) to receive the light scattered by the sample (T), and to acquire spatial and angular information on the object wavefront associated therewith; and a computational entity to perform a computational reconstruction of the object wavefront from the spatial and angular information. Other aspects of the invention relate to a method, a computer program and a product incorporating the same, adapted for the performance of the functions of the computational entity of the microscope, as well as to a module and a kit for a microscope.

Abstract: A method is disclosed for generating a 3D printing file containing an object model of a part having a body and an integral electronic component. To generate the 3D printing file, a processor receives at least one geometry specification of the part to be printed and at least one component performance property of the electronic component to be printed integral to the part. An object model is determined by the processor in accordance with the at least one geometry specification of a part to be printed, the at least one component performance property of an electronic component to be printed, and at least one material property of an electronic component printing material of a 3D printer. The 3D printing file is generated by the processor and comprises the object model.

Abstract: There is provided reduced power consumption in devices that use at least two identities for communications. A method comprises aligning (1302) a plurality of paging occasions across at least two identities of a communication device. The aligning is performed via requesting and receiving (1306) from a communication network a paging occasion for the communication device with at least two identities using at least one of the identities.

Abstract: The disclosure notably relates to computer-implemented method for learning a neural network configured for inference, from a freehand drawing representing a 3D shape, of a solid CAD feature representing the 3D shape. The method includes providing a dataset including freehand drawings each representing a respective 3D shape, and learning the neural network based on the dataset. The method forms an improved solution for inference, from a freehand drawing representing a 3D shape, of a 3D modeled object representing the 3D shape.

Abstract: A computer-implemented method for predicting whether a molecule will be a good mosquito repellent is disclosed. The method includes obtaining a machine-learned prediction model obtained by transfer learning. The model has been trained using a first, larger training dataset for an odour prediction task and with a second, smaller training dataset for predicting whether a molecule would function as a mosquito repellent. The method further includes obtaining input data that describes a chemical structure of a selected molecule, providing the input data that describes the chemical structure of the selected molecule as input to the machine-learned prediction model, receiving prediction data descriptive of whether the selected molecule would be a good mosquito repellent as an output of the machine-learned sensory prediction model and providing the prediction data as output.

Abstract: Use of simple acyclic polyamines for the treatment of parasites of the family Trypanosomatidae The present invention provides the use of certain single acyclic polyamines of Formula (I), attached to heterocycles, for the treatment of leishmaniasis and trypanosomiasis. All the compounds studied show antiparasitic activity against Leishmania species, comparable or superior to that of the active ingredient of the drug commonly used to treat this disease, but with a macrophage toxicity similar to or, in most cases, lower than that of the commercial reference compound, and with higher selectivity indices against strains representative of the three clinical forms of the disease: cutaneous, mucocutaneous and visceral. The compounds show ability to inhibit parasite superoxide dismutase, generally at concentrations lower than those required to inhibit human superoxide dismutase. All this supports its usefulness for treating leishmaniasis and also trypanosomiasis.

Abstract: A method for processing a radiological image, in digital format includes at least one radiological anomaly detected using a convolutional neural network that has been trained to detect radiological anomalies on radiological examinations, the radiological image being characterized by the intensity of each of its pixels, and by at least one radiological anomaly influence map that assigns, for each pixel of the radiological image, a value representative of the proportion to which the pixel had an influence on the detection result of the radiological anomaly, which method is computer-implemented and comprises the steps of: normalizing the radiological anomaly influence maps to give normalized radiological anomaly influence maps; fusing the normalized radiological anomaly influence maps to give a single fused influence map; carrying out improvement processing on the image, using an intensity histogram, wherein the contribution of each pixel in the computing of the intensity histogram is weighted by the fused influ

Abstract: Various examples are directed to systems and methods for deploying a cloud environment to a cloud hyperscaler infrastructure. A software tool may receive a description of a cloud environment element to be included in a cloud environment. The software tool may determine that the description of the cloud environment element is consistent with cloud environment security guideline data and add the cloud environment element to cloud environment description data. A security concept document may be generated for the cloud environment. The software tool may generate deployment code comprising executable code describing the cloud environment and submit the deployment code to create the cloud environment at the cloud hyperscaler infrastructure.

Abstract: A metal powder having a composition including the following elements, expressed in content by weight: 6.5%?Si?10%, 4.5%?Nb?10%, 0.2%?B?2.0%, 0.2%?Cu?2.0%, C?2% and optionally containing Ni?10 wt % and/or Co?10 wt % and/or Cr?7 wt % and/or Zr as a substitute for any part of Nb on a one-to-one basis and/or Mo as a substitute for any part of Nb on a one-to-one basis and/or P as a substitute for any part of Si on a one-to-one basis, the balance being Fe and unavoidable impurities resulting from the elaboration, the metal powder having a microstructure including at least 5% in area fraction of an amorphous phase, the balance being made of crystalline ferritic phases with a grain size below 20 ?m and possible precipitates, the metal powder having a mean sphericity SPHT of at least 0.80.

Abstract: A computer-implemented method for forming a dataset configured for learning a neural network. The neural network is configured for inference, from a freehand drawing representing a 3D shape, of a solid CAD feature representing the 3D shape. The method includes generating one or more solid CAD feature includes each representing a respective 3D shape. The method also includes, for each solid CAD feature, determining one or more respective freehand drawings each representing the respective 3D shape, and inserting in the dataset, one or more training samples. Each training sample includes the solid CAD feature and a respective freehand drawing. The method forms an improved solution for inference, from a freehand drawing representing a 3D shape, of a 3D modeled object representing the 3D shape.

Abstract: The disclosure notably relates to a computer-implemented method for learning a neural network configured for inference, from a discrete geometrical representation of a 3D shape, of an editable feature tree representing the 3D shape. The editable feature tree includes a tree arrangement of geometrical operations applied to leaf geometrical shapes. The method includes obtaining a dataset including discrete geometrical representations each of a respective 3D shape, and obtaining a candidate set of leaf geometrical shapes. The method also includes learning the neural network based on the dataset and on the candidate set. The candidate set includes at least one continuous subset of leaf geometrical shapes. The method forms an improved solution for digitization.

Abstract: The present disclosure provides systems and methods for predicting olfactory properties of a molecule. One example method includes obtaining a machine-learned graph neural network trained to predict olfactory properties of molecules based at least in part on chemical structure data associated with the molecules. The method includes obtaining a graph that graphically describes a chemical structure of a selected molecule. The method includes providing the graph as input to the machine-learned graph neural network. The method includes receiving prediction data descriptive of one or more predicted olfactory properties of the selected molecule as an output of the machine-learned graph neural network. The method includes providing the prediction data descriptive of the one or more predicted olfactory properties of the selected molecule as an output.

Abstract: The disclosure notably relates to a computer-implemented method for forming a dataset configured for learning a neural network. The neural network is configured for inference, from a discrete geometrical representation of a 3D shape, of an editable feature tree representing the 3D shape. The editable feature tree comprises a tree arrangement of geometrical operations applied to leaf geometrical shapes. The method includes obtaining respective data pieces, and inserting a part of the data pieces in the dataset each as a respective training sample. The respective 3D shape of each of one or more first data pieces inserted in the dataset is identical to the respective 3D shape of respective one or more second data pieces not inserted in the dataset. The method forms an improved solution for digitization.

Abstract: The disclosure notably relates to a computer-implemented method for generating a structured three-dimensional (3D) model from a mesh. The method includes obtaining a mesh that comprises faces, each face of the mesh including a normal and principal curvature values; computing a distribution of the principal curvatures values over the whole mesh by counting the number of occurrences of discretized curvature values; identifying in the computed distribution one or more dominant ranges of principal curvature values; for each identified dominant range, computing one or more regions of the mesh that includes faces belonging to the identified dominant range; for each computed region, detecting a primitive type by using the curvatures values of all faces of the region and identifying parameters of the detected primitive by using the mesh surface of the region.

Abstract: The disclosure notably relates to a computer-implemented method for extracting a feature tree from a mesh. The method includes providing a mesh, computing a geometric and adjacency graph of the provided mesh, wherein each node of the graph represents one region of the mesh and comprises a primitive type and parameters of the region, each connection between two nodes is an intersection between the respective surfaces of the regions represented by the two connected nodes. The method also includes instantiating for each node of the graph, a surface based on the identified primitive type and parameters of the region.

Abstract: Process of refrigeration induced by an external stimulus comprising the application of an external stimulus selected among hydrostatic pressure, uniaxial pressure, electric field and illumination with light, to an organic-inorganic hybrid material of crystalline structure with hexagonal packing, of formula ABX3 (I), where A is a given monovalent organic cation or a given mixture of monovalent organic cations or a given mixture of monovalent organic cations and monovalent inorganic cations, B is a given divalent metal cation, a given mixture of divalent metal cations, or a given 50/50% atomic mixture of a monovalent cation and a trivalent cation, and X is a halide anion or a mixture thereof. A device with cooling capacity induced by an external stimulus, comprising the above organic-inorganic hybrid material.