Abstract: The present disclosure relates to immunogenic formulations and their use for the treatment and prevention of T. cruzi infection, Chagas Disease, and chronic Chagas cardiomyopathy. In certain aspects, methods of producing antigen presenting cells comprising T. cruzi antigens are provided.

Abstract: A computer-implemented method for classifying an input data set within a data category using multiple data representation modes. The method includes identifying at least a first data representation source mode and a second data representation source mode; classifying the at least first data representation source mode via at least a first data recognition tool and the at least second data representation source mode via at least a second data recognition tool, the classifying including allocating a confidence factor for each data representation source mode in the data category; and combining outputs of the classifying into a single output confidence score by using a weighted fusion of the allocated confidence factors.

Abstract: A computer-implemented method and system are disclosed for classifying an input data set within a data category using multiple data recognition tools. The method includes identifying at least a first attribute and a second attribute of the data category; classifying the at least first attribute via at least a first data recognition tool and the at least second attribute via at least a second data recognition tool, the classifying including: allocating a confidence factor for each of the at least first and second attributes that indicates a presence of each of the at least first and second attributes in the input data set; and combining outputs of the classifying into a single output confidence score by using a weighted fusion of the allocated confidence factors.

Abstract: An exemplary detection apparatus includes a housing having one or more sensors of one or more sensor types, an optional port for detachably mounting one or more of the sensors, and an optional motive system associated with a mode of transport for movement in an area of interest. A sensor circuit receives a signal originating from the one or more sensors, identifies the signal, optionally processes the signal data, and packages the raw signal data or processed signal data, as applicable, for transmission over a network. A control circuit establishes communication with the network for sending or receiving sensor data to/from other devices connected to the network, and controls the motive system for moving the apparatus to locations in the area of interest.

Abstract: A computer-implemented method and system are disclosed for classifying an input data set within a data category using multiple data recognition tools. The method includes identifying at least a first attribute and a second attribute of the data category; classifying the at least first attribute via at least a first data recognition tool and the at least second attribute via at least a second data recognition tool, the classifying including: allocating a confidence factor for each of the at least first and second attributes that indicates a presence of each of the at least first and second attributes in the input data set; and combining outputs of the classifying into a single output confidence score by using a weighted fusion of the allocated confidence factors.

Abstract: A computer-implemented method for classifying an input data set within a data category using multiple data representation modes. The method includes identifying at least a first data representation source mode and a second data representation source mode; classifying the at least first data representation source mode via at least a first data recognition tool and the at least second data representation source mode via at least a second data recognition tool, the classifying including allocating a confidence factor for each data representation source mode in the data category; and combining outputs of the classifying into a single output confidence score by using a weighted fusion of the allocated confidence factors.

Abstract: Methods and computer program products for analyzing tissue are provided. The tissue is exposed to light at the appropriate wavelengths for inducing fluorescence. Images of the fluorescing tissue are taken at two or more depths within the tissue. The PSD function is determined for each image at a different depth within the tissue. A characteristic of each PSD function determined is compared, and it is determined whether or not the tissue exhibits a pre-cancerous characteristic.