Abstract: A noncontact, multi-wavelength time-resolved laser speckle contrast imaging (MTR-LSCI) technique provides for continuous, fast and high-resolution 2D mapping of tissue blood flow (BF) and tissue blood oxygen saturation (StO2) at different depths of target tissue. MTR-LSCI illuminates the tissue with picosecond-pulsed, coherent, widefield light at least at two different wavelengths in the near-infrared range (600-1100 nm) and synchronizes a high-resolution, gated single-photon avalanche diode (SPAD) camera to capture BF and StO2 maps at different depths of target tissue, wherein the imaging depth depends on light propagation inside a tissue volume, captured by the time-gated camera. The reconstruction of BF and StO2 maps can be dramatically expedited by incorporating highly parallelized computation and convolution functions. The performance of MTR-LSCI was evaluated using head-simulating phantoms with known properties and in-vivo rodents with varied hemodynamic challenges to the brain.

Abstract: A semiconductor package having a fillet is provided. The semiconductor package includes a trace disposed within a solder mask that has a top surface. A first die is over the solder mask and mechanically couples with the trace. A first adhesive is between the trace and the first die where sides of the first die and the first adhesive define a die edge. The semiconductor package includes a fillet adjacent the die edge and a second die above the first die. The semiconductor package also includes a second adhesive having a bottom surface where the second adhesive is between the first die and the second die. The solder mask top surface, the first die surface, and the second adhesive bottom surface define a cavity where the fillet is within the cavity at the die edge.

Abstract: Apparatuses, systems, and techniques to process neural networks. In at least one embodiment, neural network graph data is organized for processing. In at least one embodiment, for example, neural network graph data is organized based, at least in part, on one or more sparsity constraints.

Abstract: Apparatuses, systems, and techniques are presented to generate digital reconstructions of physical objects. In at least one embodiment, one or more first neural networks are used to generate a three-dimensional (3D) model having a first level of detail, and one or more second neural networks are used to modify the 3D model to have a second level of detail.

Abstract: Apparatuses, systems, and techniques to evaluate neural networks. In at least one embodiment, neural networks are evaluated using one or more other neural networks. In at least one embodiment, two or more neural networks are caused to generate consistent results from first input information and caused to generate inconsistent results from second input information.

Abstract: Apparatuses, systems, and techniques to generate an image. In at least one embodiment, one or more neural networks are to generate a second image based, at least in part, on a first image and information indicating zero or more differences between the first and second image.

Abstract: Exemplary systems and methods are disclosed for allocating resources in a breeding pipeline to multiple origins. One exemplary method includes accessing a data structure including data representative of multiple origins, in which the data includes, for each of the multiple origins, a trait performance expression or genotypic component information. The exemplary method further includes determining a resource allocation, which allocates n resources among the multiple origins based on a probability associated with the trait performance expressions and/or the genotypic components for the origins, and then allocating the n resources in the breeding pipeline for the multiple origins, based on the determined resource allocation.

Abstract: Apparatuses, systems, and techniques to modify tensors based on processor requirements. In at least one embodiment, input tensors and weight tensors are modified to meet processing resource requirements.

Abstract: A light-emitting device includes a circuit carrier board having a short side and a long side, a plurality of light-emitting units on the circuit carrier board for emitting three or more color lights, and a light-transmitting glue layer on the circuit carrier board and covering the plurality of light-emitting units. The short side is shorter than the long side. The plurality of light-emitting units include a first light-emitting unit. The first light-emitting unit has a light exit surface, a first sidewall, and a second sidewall. The first sidewall faces the short side and has a first included angle with the light exit surface, and the second sidewall faces the long side and has a second included angle with the light exit surface. The first included angle is between 85 to 95 degrees, and the second included angle is less than 85 degrees or greater than 105 degrees.

Abstract: Exemplary systems and methods are disclosed for allocating resources in a breeding pipeline to multiple origins. One exemplary method includes accessing a data structure including data representative of multiple origins, in which the data includes, for each of the multiple origins, a trait performance expression or genotypic component information. The exemplary method further includes determining a resource allocation, which allocates n resources among the multiple origins based on a probability associated with the trait performance expressions and/or the genotypic components for the origins, and then allocating the n resources in the breeding pipeline for the multiple origins, based on the determined resource allocation.

Abstract: A display device includes a first light-emitting module and a second light-emitting module. Each light-emitting module has a substrate, a plurality of LED dies arranged on the substrate, a reflective layer on the substrate, and a light-transmissive layer. The light-transmissive layer covers the substrate, the plurality of LED dies, and the reflective layer. Both the light-transmissive layer of the first module and the light-transmissive layer of the second module have rough uppermost surfaces. The first light-emitting module has a first reflectivity, the second light-emitting module has a second reflectivity, and a standard deviation between the first reflectivity and the second reflectivity is not greater than 0.5.

Abstract: Exemplary systems and methods are disclosed for allocating resources in a breeding pipeline to multiple origins. One exemplary method includes accessing a data structure including data representative of multiple origins, in which the data includes, for each of the multiple origins, a trait performance expression or genotypic component information. The exemplary method further includes determining a resource allocation, which allocates n resources among the multiple origins based on a probability associated with the trait performance expressions and/or the genotypic components for the origins, and then allocating the n resources in the breeding pipeline for the multiple origins, based on the determined resource allocation.

Abstract: Methods, apparatus, systems and articles of manufacture for generating a three-dimensional (3D) model for 3D scene reconstruction are disclosed. An example apparatus includes a 3D scene generator to generate a 3D model for digital image scene reconstruction based on a trained generative model and a digital image captured in a real environment. An image simulator is to generate a simulated image based on the 3D model, the simulated image corresponding to the captured image. A discriminator is to apply a discriminative model to the simulated image to determine whether the simulated image is simulated.

Abstract: Apparatuses, systems, and techniques to transform data sets, such as matrices representing layers of neural networks, to increase sparsity and/or other characteristics of said data sets to improve performance in computations, such as neural network computations. In at least one embodiment, one or more subsets of data in one or more sets of data are rearranged as part of a process to increase sparsity in said one or more sets of data to satisfy one or more one or more structural sparsity constraints.

Abstract: Exemplary systems and methods are disclosed for allocating resources in a breeding pipeline to multiple origins. One exemplary method includes accessing a data structure including data representative of multiple origins, in which the data includes, for each of the multiple origins, a trait performance expression or genotypic component information. The exemplary method further includes determining a resource allocation, which allocates n resources among the multiple origins based on a probability associated with the trait performance expressions and/or the genotypic components for the origins, and then allocating the n resources in the breeding pipeline for the multiple origins, based on the determined resource allocation.

Abstract: Methods, apparatus, systems and articles of manufacture for generating a three-dimensional (3D) model for 3D scene reconstruction are disclosed. An example apparatus includes a 3D scene generator to generate a 3D model for digital image scene reconstruction based on a trained generative model and a digital image captured in a real environment. An image simulator is to generate a simulated image based on the 3D model, the simulated image corresponding to the captured image. A discriminator is to apply a discriminative model to the simulated image to determine whether the simulated image is simulated.

Abstract: Computing devices, computer-readable storage media, and computer-implemented methods are disclosed for prediction of capacity. In a central tier, central-tier benchmark values are generated from benchmark testing performed on different test configurations in a reference execution environment. In a deployment tier, deployment-tier benchmark values are generated from benchmark testing performed on a baseline deployed configuration in many execution environments. A sizing model is learned from the central-tier benchmark values to predict execution platform requirements given a set of workload input parameters. A performance model is learned from the deployment-tier and the central-tier benchmark values to predict a performance delta value reflecting relative performance between a particular execution environment and the reference execution environment. The performance delta value is used to adjust predicted execution platform requirements to tailor the prediction to a particular execution environment.

Abstract: An electron spectroscopy system and method are disclosed. In another aspect, an ultrabright and ultrafast angle-resolved electron spectroscopy system is provided. A further aspect of the present system employs an electron gun, a radio frequency cavity and multiple spectrometers. Yet another aspect uses spectrometers in an aligned manner to deflect and focus electrons emitted by the electron gun. Moreover, an ultrafast laser is coupled to an electron spectroscopy system. A bunch of monochromatic electrons have their energy compressed and reoriented in an additional aspect of the present system. A further aspect of the present electron spectroscopy system employs adaptive and/or adjustable optics to optimize both time and energy compression. Another aspect provides at least two RF lenses or cavities, one before a specimen and one after the specimen.

Abstract: A blood leakage warning device for dialysis patient is applied to cover an injection site, comprising a cover absorber, two detection modules, a control module and an alarm module. The cover absorber is used for absorbing blood leakage. The two detection modules are disposed on the cover absorber at intervals. The control module is electrically connected to the two detection modules to detect whether the cover absorber absorbs the blood. The alarm module is electrically connected to the control module. The alarm module issues an alarm when the cover absorber absorbs the blood.

Abstract: An electron spectroscopy system and method are disclosed. In another aspect, an ultrabright and ultrafast angle-resolved electron spectroscopy system is provided. A further aspect of the present system employs an electron gun, a radio frequency cavity and multiple spectrometers. Yet another aspect uses spectrometers in an aligned manner to deflect and focus electrons emitted by the electron gun. Moreover, an ultrafast laser is coupled to an electron spectroscopy system. A bunch of monochromatic electrons have their energy compressed and reoriented in an additional aspect of the present system. A further aspect of the present electron spectroscopy system employs adaptive and/or adjustable optics to optimize both time and energy compression. Another aspect provides at least two RF lenses or cavities, one before a specimen and one after the specimen.