Abstract: A testing platform for evacuated tube high-temperature superconducting magnetic levitation (HTS maglev) under a high-speed operation state, including an evacuated tube, a supporting platform assembly, a model train and a gantry. The supporting platform assembly is arranged in the evacuated tube, and is provided with a permanent magnet track and a stator winding. A mover and a cryogenic dewar are arranged at a bottom of the model train, and multiple superconducting bulks are arranged in the cryogenic dewar. A side wall of the model train is made of a metal material. The gantry is arranged on the supporting platform assembly, and permanent magnets are arranged on upright posts of the gantry. A testing method using the testing platform is also provided.

Abstract: The present disclosure provides a solar cell and a preparation method thereof, belongs to the technical field of solar cells. The preparation method of a solar cell according to the present disclosure includes: forming a passivation structure on a contact silicon layer at a back side of a silicon substrate; where the back side is a side opposite to a light incident side; removing the passivation structure located at least part of an electrode region by laser to form a contact opening, melting at least part of the contact silicon layer at the contact opening by laser, and solidifying the molten contact silicon layer to form a re-solidified structure; where the electrode region is a region configured to form a back electrode; and electroplating to form a back electrode in the electrode region on the back side of the contact silicon layer.

Abstract: A method for reconstructing an image from emission data includes generating a compressed point-spread function matrix, generating an accumulated attenuation factor; and performing at least one image projection operation on an image matrix of the emission data using the compressed point-spread function matrix and the accumulated attenuation factor. The image projection operation can include rotating an image matrix and an exponential attenuation map to align with a selected viewing angle. An accumulated attenuation image is then generated from the rotated image matrix and rotated exponential attenuation map and a projection image is generated for each voxel by multiplying the accumulated attenuation image and point spread function matrix for each voxel. The rotating and multiplying operations can be performed on a graphics processing unit, which may be found in a commercially available video processing card, which are specifically designed to efficiently perform such operations.

Abstract: A method for electronically cleansing a virtual object formed from acquired image data converted to a plurality of volume elements is provided. The present method allows individual volume elements, or voxels, to represent more than one material type. The method includes defining a partial volume image model for volume elements representing a plurality of material types based, at least in part, on the measured intensity value of the volume element. The material mixture for each of the volume elements representing a plurality of material types can be estimated using the observed intensity values and the defined partial volume image model. The volume elements representing a plurality of material types can then be classified in accordance with the estimated material mixture. For electronic colon cleansing, the method includes removing at least one classification of volume elements when displaying the virtual object.

Abstract: A method for reconstructing an image from emission data includes generating a compressed point-spread function matrix, generating an accumulated attenuation factor; and performing at least one image projection operation on an image matrix of the emission data using the compressed point-spread function matrix and the accumulated attenuation factor. The image projection operation can include rotating an image matrix and an exponential attenuation map to align with a selected viewing angle. An accumulated attenuation image is then generated from the rotated image matrix and rotated exponential attenuation map and a projection image is generated for each voxel by multiplying the accumulated attenuation image and point spread function matrix for each voxel. The rotating and multiplying operations can be performed on a graphics processing unit, which may be found in a commercially available video processing card, which are specifically designed to efficiently perform such operations.

Abstract: A computer aided detection (CAD) method for detecting polyps within an identified mucosa layer of a virtual representation of a colon includes the steps of identifying candidate polyp patches in the surface of the mucosa layer and extracting the volume of each of the candidate polyp patches. The extracted volume of the candidate polyp patches can be partitioned to extract a plurality of features, of the candidate polyp patch, which includes at least one internal feature of the candidate polyp patch. The features can include density texture features, geometrical features, and morphological features of the polyp candidate volume. The extracted features of the polyp candidates are analyzed to eliminate false positives from the candidate polyp patches. Those candidates which are not eliminated are identified as polyps.

Abstract: A method for electronically cleansing a virtual object formed from acquired image data converted to a plurality of volume elements is provided. The present method allows individual volume elements, or voxels, to represent more than one material type. The method includes defining a partial volume image model for volume elements representing a plurality of material types based, at least in part, on the measured intensity value of the volume element. The material mixture for each of the volume elements representing a plurality of material types can be estimated using the observed intensity values and the defined partial volume image model. The volume elements representing a plurality of material types can then be classified in accordance with the estimated material mixture. For electronic colon cleansing, the method includes removing at least one classification of volume elements when displaying the virtual object.