Abstract: A priority based prefetch by a memory controller is disclosed. A prefetch of data of a low priority master is suspended when a data request associated with a high priority master indicated by a master identification is to be performed. The suspension includes storing a saved state of the prefetch, performing the prefetch of data of the high priority master, and resuming the prefetch of data of the low priority master when the prefetch of data of the high priority master is completed.

Abstract: A column includes a stack assembly including stacked electrochemical cells and interconnects, a ceramic frame surrounding the stack assembly, a first spring assembly located inside of the ceramic frame over the stack assembly and configured to apply a load to the stack assembly, and including a first rod plate and a first ceramic spring, a second spring assembly located inside of the ceramic frame between first spring assembly and the stack assembly and configured to apply a load to the stack assembly, and including a second rod plate and a second ceramic spring, and a first dome plate located between the first ceramic spring and the second ceramic spring.

Abstract: A column includes a stack assembly including stacked electrochemical cells and interconnects, a ceramic frame surrounding the stack assembly, a first spring assembly located inside of the ceramic frame over the stack assembly and configured to apply a load to the stack assembly, and including a first rod plate and a first ceramic spring, a second spring assembly located inside of the ceramic frame between first spring assembly and the stack assembly and configured to apply a load to the stack assembly, and including a second rod plate and a second ceramic spring, and a first dome plate located between the first ceramic spring and the second ceramic spring.

Abstract: Thermal interface materials systems, assemblies formed therefrom, and methods of manufacture thereof are provided. A system includes a thermal interface material (TIM) layer and a first adhesive layer disposed over the TIM layer. The TIM layer includes a first polymer component and liquid metal droplets dispersed through the first polymer component. The TIM layer exhibits a storage modulus of 104 Pa to 107 Pa.

Abstract: A method of determining the accuracy of a test performed by a diagnostic laboratory system includes obtaining one or more first measurements during a first operation of the test performed by the diagnostic laboratory system. One or more second measurements are obtained during a second operation of the test performed by the diagnostic laboratory system. The first measurements and the second measurements are collectively analyzed using a trained model that calculates an uncertainty score for the test based on learned correlations between the first operation and the second operation. The uncertainty score may be used to determine whether the test results can be relied upon or whether the test should be rerun. Other methods and systems are disclosed.

Abstract: Systems and methods for performing one or more medical analysis tasks are provided. 1) patient data comprising mutational data of a patient and 2) an initial PPI (protein-protein interaction) graph are received. A patient-specific PPI graph for the patient is generated based on the mutational data and the initial PPI graph. One or more medical analysis tasks for the patient are performed using a machine learning based network based on the patient data and the patient-specific PPI graph. Results of the medical analysis task are output.

Abstract: A method of characterizing a specimen to be analyzed in an automated diagnostic analysis system provides a segmentation determination and/or an HILN (hemolysis, icterus, lipemia, normal) determination of the specimen while providing characterization training updates based on the accuracy and/or confidence in the determinations. The method includes identifying an incorrect or low confidence segmentation or HILN determination, forwarding the incorrect or low confidence determination from the HILN network to a database, and providing one or more training images to the HILN network based on the incorrect or low confidence determination. Quality check modules and systems configured to carry out the method are also described, as are other aspects.

Abstract: Systems and methods for automatically navigating a medical image acquisition device are provided. 1) An initial image depicting a current position of a medical image acquisition device and 2) at least one of a target image depicting a target position of the medical image acquisition device or text-based instructions for navigating to the target position of the medical image acquisition device are received. Features are extracted from the at least one of the target image or the text-based instructions respectively using at least one of a machine learning based image encoder or a machine learning based text encoder. The machine learning based image encoder and the machine learning based text encoder are trained to generate corresponding features for training target images and training text-based instructions for same target positions.

Abstract: A method of determining the accuracy of a test performed by a diagnostic laboratory system includes obtaining one or more first measurements during a first operation of the test performed by the diagnostic laboratory system. One or more second measurements are obtained during a second operation of the test performed by the diagnostic laboratory system. The first measurements and the second measurements are collectively analyzed using a trained model that calculates an uncertainty score for the test based on learned correlations between the first operation and the second operation. The uncertainty score may be used to determine whether the test results can be relied upon or whether the test should be rerun. Other methods and systems are disclosed.

Abstract: A treating chemistry distribution system for a plurality of treating chemistry devices. The treating chemistry distribution system has a treating chemistry hub, a treating chemistry manifold, and a water line. The treating chemistry hub has a set of treating chemistry modules.

Abstract: Systems and methods for performing a medical imaging analysis task are provided. One or more input medical images of a patient are received. The one or more input medical images are encoded into embeddings using a machine learning based encoder network. A medical imaging analysis task is performed based on the embeddings. Results of the medical imaging analysis task are output.

Abstract: A method of training a sample container identification network of a diagnostic laboratory system includes obtaining a plurality of data subsets, wherein each data subset is smaller than a full training data set used to train the sample container identification network and includes a plurality of images of one or more sample containers. The sample container identification network is trained on each of the plurality of data subsets to generate a plurality of trained sample container identification networks. Each of the trained sample container identification networks are testing using testing data that includes test images of sample containers, wherein the testing includes identifying the sample containers in the test images. A core data set is selected from one of the plurality of data subsets based on the testing. the core data set for use in training a deployed sample container identification network. Other methods and systems are disclosed.

Abstract: A method of characterizing a specimen as containing hemolysis, icterus, or lipemia is provided. The method includes capturing one or more images of the specimen, wherein the one or more images include a serum or plasma portion of the specimen. Pixel data is generated by capturing the image. The pixel data of the one or more images of the specimen is processed using a first network executing on a computer to predict a classification of the serum or plasma portion, wherein the classification comprises hemolysis, icterus, and lipemia. The predicted classification is verified using one or more verification networks. Quality check modules and specimen testing apparatus adapted to carry out the method are described, as are other aspects.

Abstract: Hermetic thermocouple harnesses for solid oxide electrochemical systems include a harness having a feedthrough washer including two metal disks with holes circumferentially disposed about the disks and a braze alloy layer between the disks. Thermocouples are fed through the feedthrough washer, and induction brazing is used to seal and bind the disks and the thermocouples together. The feedthrough washer is welded to the base of the hotbox, forming a hermetic seal while allowing the thermocouples to extend between the interior and exterior of the hotbox. A second harness includes a main body, a top tube, and a sealant end having holes. Thermocouples extend from the interior of the hotbox, through the top tube, main body, and through the holes of the sealant to the exterior of the hotbox. Clearance between the thermocouples and their respective holes are closed with glass seals, and the top tube is filled with putty.

Abstract: A method of training a model of a diagnostic apparatus includes providing one or more first tube assemblies of a first type and one or more second tube assemblies of a second type in a diagnostic apparatus; capturing one or more first images of at least a portion of each of the one or more first tube assemblies and the second tube assemblies using the imaging device. Training the model includes identifying tube assemblies of the first type and tube assemblies of the second type based on the one or more first images and the one or more second images. Tubes assemblies of the first type are grouped into a first group and tube assemblies of the second type are grouped into a second group. Other methods and apparatus are disclosed.

Abstract: An integrated circuit (IC), including a functional circuit and a security system, is disclosed. The functional circuit generates a request packet for an indirect memory access of a memory. The security system validates the functional circuit based on a security attribute and a functional identifier of the functional circuit. Based on the request packet and the validation of the functional circuit, the security system identifies an instruction sequence associated with the indirect memory access. Further, the security system determines a type of the indirect memory access based on the instruction sequence, and validates the type of the indirect memory access based on the security attribute and the request packet. Based on the validation of the type of the indirect memory access, the instruction sequence is executed, thereby facilitating the indirect memory access for the functional circuit.

Abstract: A method of synthesizing an image of a tube assembly includes capturing an image of the tube assembly, wherein the capturing generates a captured image. The captured image is decomposed into a plurality of features in latent space using a trained image decomposition model. One or more of the features in the latent space is manipulated into one or more manipulated features. A synthesized tube assembly image is generated with at least one of the manipulated features using a trained image composition model. Other methods and systems are disclosed.

Abstract: A method of identifying a tube type. The method includes capturing one or more pixelated images of a cap affixed to a tube; identifying a color of one or more pixels of the pixilated image of the cap; identifying one or more gradients of a dimension of the cap; and identifying the tube type based at least on: the color of the one or more pixels, and the one or more gradients of a dimension of the cap. Apparatus adapted to carry out the method are disclosed as are other aspects.

Abstract: A method of determining the accuracy of a test performed by a diagnostic laboratory system includes obtaining one or more first measurements during a first operation of the test performed by the diagnostic laboratory system. One or more second measurements are obtained during a second operation of the test performed by the diagnostic laboratory system. The first measurements and the second measurements are collectively analyzed using a trained model that calculates an uncertainty score for the test based on learned correlations between the first operation and the second operation. The uncertainty score may be used to determine whether the test results can be relied upon or whether the test should be rerun. Other methods and systems are disclosed.

Abstract: Systems and methods for performing one or more medical imaging analysis tasks using a vision-language model are provided. One or more input medical images are received. Image embeddings are extracted from the one or more input medical images. One or more medical imaging analysis tasks are performed based on the image embeddings extracted from the one or more input medical images using a trained vision-language model. Results of the one or more medical imaging analysis tasks are output.