Abstract: A brownfield security gateway is configured to support a trusted execution environment (TEE) that employs cryptographic and physical security—which forms a trusted cyber physical system—to protect sensitive transmissions on route to a controllable device. The gateway may be implemented with a System on Chip (SoC) that utilizes an application layer gateway to filter content within a transmission. When the application layer gateway authorizes the transmission, the transmission is forwarded to a trusted peripheral device that is configured with communication transport protocols, and the trusted peripheral device transfers the transmission to the controllable device. The trusted peripheral device and the controllable device are physically protected by, for example, protected distribution systems. Accordingly, the trusted peripheral device functions as a gateway between the SoC and the controllable device.

Abstract: A system is disclosed that includes an image sensor, a depth sensor, and at least one processor. The image sensor acquires images within a first field-of-view. The depth sensor includes a plurality of photosensitive cells that acquires distance information within a second field-of-view. The second field-of-view at least partially overlaps the first field-of-view. The at least one processor is programmed to transition from a first mode of operation to a second mode of operation in response to satisfaction of a specified criteria based on object information associated with the distance information for an object within the second field-of-view.

Abstract: Use of diverse biomass feedstock in a process for the recovery of target C5 and C6 alditols and target glycols via staged hydrogenation and hydrogenolysis processes is disclosed. Particular alditols of interest include, but are not limited to, xylitol and sorbitol. Various embodiments of the present invention synergistically improve overall recovery of target alditols and/or glycols from a mixed C5/C6 sugar stream without needlessly driving total recovery of the individual target alditols and/or glycols. The result is a highly efficient, low complexity process having enhanced production flexibility, reduced waste and greater overall yield than conventional processes directed to alditol or glycol production.

Abstract: The present disclosure provides new and innovative devices, methods, and apparatuses for discerning the presence and characteristics of objects that are passing in front of an indicia decoding device. In an example, a device comprises a 2D imaging assembly, a depth imaging assembly, and a processing device configured to analyze data from the depth imaging assembly to determine a number of items that are in a field of view of the depth imaging assembly during a period of time, analyze data from the 2D imaging assembly to determine a number of indicia that are present in a field of view of the 2D imaging assembly during at least a portion of the period of time, compare the number of indicia with the number of items, output a determination as to whether the number of indicia matches the number of items, and responsive to determining that the number of indicia does not match the number of items, transmit a message to an alert module.

Abstract: The present disclosure provides new and innovative systems, methods, and apparatuses for detecting non-decode events in indicia scanning settings.

Abstract: A system for performing interbody fusion surgery including an expandable intervertebral spacer and specialized instruments for choosing the correct size of implant, implanting the device within the intervertebral space, and for delivery of bone graft or bone substitute to the interior of the implant.

Abstract: Multiple x-ray images of a skeletal portion are acquired, from which 3D image data of the skeletal portion is generated. First and second x-ray images of a tool and the skeletal portion are acquired from respective first and second views, the first and second views each being similar to a view of one of the multiple x-ray images. During the acquisition of the multiple images the tool was (i) not visible in the multiple images, or (ii) disposed at a different location than the location in which the tool is disposed during the acquisition of the first and second images. A computer processor registers the first and second images to the 3D image data, identifies a location of the tool within the first and second images, and determines the location of the tool with respect to the 3D image data. Other applications are also described.

Abstract: The invention provides a colon cleansing solution comprising: a) 300 to 800 mmol per litre ascorbate anion provided by a mixture of: (i) ascorbic acid and (ii) one or more salts of ascorbic acid the components (i) and (ii) being present in a molar ratio of from 1:4.5 to 1:7.0; and b) 10 to 200 g per litre polyethylene glycol. The invention also provides methods and kits associated with, or making use of the solutions, and compositions for the preparation of the solutions.

Abstract: Disclosed herein are compositions that comprise engineered polynucleotides, pharmaceutical compositions comprising the same, methods of making the same, and methods of treatment comprising the compositions that comprise the engineered polynucleotides.

Abstract: Secure methods, systems, and media for generating and verifying user credentials are provided. In some embodiments, the method comprises: receiving, from a user device, a request for access to a service that requires valid user credentials; determining an aspect of the user credentials that is to be satisfied to grant access to the requested service; transmitting, to the user device, a request for information related to the aspect of the user credential; receiving, from the user device, information related to the aspect of the user credential, wherein the information has been signed using a key associated with the user device; verifying the key used to sign the information by the user device; in response to verifying the key used to sign the information, determining whether the aspect of the user credential has been satisfied based on the received information; and, in response to determining that the aspect of the user credential has been satisfied, granting access to the service.

Abstract: An analyzer system for in vitro diagnostics includes a sample handler module having a robot arm that delivers samples from drawers into carriers on a linear synchronous motor automation track. Samples are delivered via the automation track to individual track sections associated with individual analyzer modules. Analyzer modules aspirate sample portions directly from the sample carriers and perform analysis thereon.

Abstract: A system for performing interbody fusion surgery including an expandable intervertebral spacer and specialized instruments for choosing the correct size of implant, implanting the device within the intervertebral space, and for delivery of bone graft or bone substitute to the interior of the implant.

Abstract: Identity systems, methods, and media for auditing and notifying users concerning verifiable claims are provided.

Abstract: A VCN process may receive, by a computing device, information associated with a set of value chain network entities of a value chain network, the information generated by at least one of: a set of sensors of the set of value chain network entities, a set of IoT devices configured to collect data relating to the set of value chain network entities, or a set of APIs configured to publish data relating to the set of value chain network entities. A VCN process may provide the information to a set of Artificial Intelligence (AI)-based learning models. A VCN process may determine a procurement action to be taken in the value chain network based upon, at least in part, an output of the set of AI-based learning models. A VCN process may execute the procurement action.

Abstract: A VCN process may receive information associated with a set of value chain network entities. A VCN process may provide the information to a first set of Artificial Intelligence (AI)-based learning models, wherein at least one member of the first set of AI-based learning models is trained to generate a prediction of future demand for an item. A VCN process may provide the information to a second set of AI-based learning models, wherein at least one member of the second set of AI-based learning models is trained to classify at least one of: an operating state, a fault condition, an operating flow, or a behavior of at least one value chain entity. A VCN process may determine a potential risk in the value chain network associated with the at least one value chain network entity based upon, at least in part, an output of the AI-based learning models.

Abstract: A VCN process may receive information associated with a value chain network. A VCN process may provide the information to a set of Artificial Intelligence (AI)-based learning models, wherein at least one member of the set of AI-based learning models is trained on a training data set of a set of value chain network entities operating data to classify at least one of: an operating state, a fault condition, an operating flow, or a behavior of at least one value chain entity of the set of value chain network entities. A VCN process may determine a task to be completed for the value chain network based upon, at least in part, on an output of the set of AI-based learning models. A VCN process may execute the task to facilitate an improvement in the value chain network.

Abstract: A VCN process may receive, by a value chain network digital twin, information associated with a value chain network. A VCN process may provide the information to a set of Artificial Intelligence (AI)-based learning models, wherein at least one member of the set of AI-based learning models is trained to classify at least one of: an operating state, a fault condition, an operating flow, or a behavior of the value chain network and at least one member of the set of AI-based learning models is trained to determine a task to be completed for the value chain network. A VCN process may provide at least one of an instruction for executing the task in the value chain network digital twin and a recommendation for executing the task in the value chain network digital twin.

Abstract: A VCN process may receive, by a computing device, information associated with a set of value chain network entities of a value chain network, the information generated by at least one of a set of sensors of the set of value chain network entities, a set of IoT devices configured to collect data relating to the set of value chain network entities, or a set of APIs configured to publish data relating to the set of value chain network entities. A VCN process may provide the information to a set of Artificial Intelligence (AI)-based learning models. A VCN process may determine a potential risk in the value chain based upon, at least in part, an output of the AI-based learning classification. A VCN process may execute an action to mitigate the potential risk in the value chain network.

Abstract: A VCN process may receive information associated with a value chain network. A VCN process may provide the information to a set of Artificial Intelligence (AI)-based learning models, wherein at least one member of the set of AI-based learning models is trained to classify at least one of: an operating state, a fault condition, an operating flow, or a behavior of the value chain network and at least one member of the set of AI-based learning models is trained on the training data set to determine, upon receiving the classification of the at least one of: the operating state, the fault condition, the operating flow, or the behavior, a task to be completed for the value chain network. A VCN process may provide a computer code instruction set to a machine to execute the task to facilitate an improvement in the operation of the value chain network.

Abstract: A VCN process may receive information associated with a value chain network. A VCN process may provide the information to a set of Artificial Intelligence (AI)-based learning models, wherein at least one member of the set of AI-based learning models is trained to classify at least one of: an operating state, a fault condition, an operating flow, or a behavior of the value chain network and at least one member of the set of AI-based learning models is trained on the training data set to determine, upon receiving the classification of the at least one of: the operating state, the fault condition, the operating flow, or the behavior, a task to be completed for the value chain network. A VCN process may configure a robotic process automation system to execute the task to facilitate an improvement in the value chain network.