Abstract: A joint implant can include a proximal joint implant element having a proximal curved interface surface and a proximal base portion. The joint implant can also include a distal joint implant element coupled to the proximal joint implant element, having a distal curved interface surface facing the proximal curved interface surface, and a distal base portion. A first filament segment and a second filament segment can extend from the proximal joint implant element to the distal joint implant element. The second filament segment can cross the first filament segment at a location between the proximal joint implant element and the distal joint implant element. A proximal bone interface connector can be connected to the proximal base portion, and a distal bone interface connector can be connected to the distal base portion.

Abstract: In some examples, one or more processors of an aerial vehicle determine an update to a three-dimensional (3D) model corresponding to a scan target to scan according to a scan plan. Based at least on the update to the 3D model, the one or more processors determine a set of one or more uncovered points of the 3D model that are not covered by the scan plan. Additionally, the one or more processors determine an updated scan plan based at least on determining one or more poses to include in the scan plan for scanning the one or more uncovered points of the 3D model. The one or more processors, control the aerial vehicle to scan the scan target with the one or more image sensors according to the updated scan plan.

Abstract: A computer accesses a first symbolic expression for an output matrix as a function of an input matrix at a computing device comprising processing circuitry and memory. The computer computes a first Jacobian of the input matrix with respect to an input tangent space. The computer computes a second Jacobian of the output matrix with respect to the input matrix. The computer computes a third Jacobian of an output tangent space with respect to the input matrix. The computer applies symbolic matrix multiplication to the first Jacobian, the second Jacobian, and the third Jacobian to obtain a second symbolic expression for the output tangent space with respect to the input tangent space. The computer provides a representation of the second symbolic expression, the second symbolic expression representing a computed tangent-space Jacobian.

Abstract: A computer implemented method for operating a token management system includes: generating the first plurality of request messages; generating a first plurality of public tokens; augmenting each of the first plurality of request messages with one of the first plurality of public tokens, the augmenting resulting in a first plurality of augmented request messages; transmitting the first plurality of augmented request messages to the first plurality of market participants; generating a second plurality of public tokens based on the first plurality of public tokens; querying a database of financial messages for any financial messages including any of the second plurality of public tokens; and associating a plurality of financial messages including any of the second plurality of public tokens with each other.

Abstract: A fluid pump includes a housing. A delivery portion includes a delivery pump element disposed within the housing. A return portion includes a return pump element disposed within the housing. A motor is disposed within the housing that drives the delivery pump element and the return pump element via a drive shaft. The delivery portion is configured to deliver fluid from a reservoir to a drive unit. The return pump element is configured to deliver the fluid from a sump assembly of the drive unit to the reservoir.

Abstract: An anchor for an implantable device for arthroplasty can include a hollow anchor body defining an interior cannula space. A slot can extend along a length of the anchor body. The slot can provide an opening from the interior cannula space to an exterior of the anchor body. The slot can have a slot width that is smaller than an internal width dimension in the interior cannula space. The anchor can also include a rounded edge at a transition between the slot and at least one of an interior surface of the anchor body or an exterior surface of the anchor body.

Abstract: A flexible connector for an implantable device for arthroplasty can include a flexible central portion. A first anchoring portion can extend from a first end of the central portion. A second anchoring portion can extend from a second end of the central portion, opposite from the first end. The first anchoring portion and the second anchoring portion can each comprise a thickened portion located farther away from the central portion and a thinner portion, relative to the thickened portion, located nearer to the central portion than the thickened portion.

Abstract: Autonomous aerial navigation in low-light and no-light conditions includes using night mode obstacle avoidance intelligence and mechanisms for vision-based unmanned aerial vehicle (UAV) navigation to enable autonomous flight operations of a UAV in low-light and no-light environments using infrared data.

Abstract: A method includes receiving at an aspiration module of a pump assembly an input associated with a catheter parameter of a catheter coupled to the pump assembly. An aspiration profile associated with the catheter parameter is selected via the aspiration module from a list of preset aspiration profiles associated with different catheters and include upper and lower pressure limits, an aspiration speed, and an infusion speed. A first signal is sent to actuate the pump based on the aspiration profile to operate the pump in a first mode. A pressure signal is received at the aspiration module and a second signal is sent to actuate the pump based on the aspiration profile to operate the pump in a second mode, in which the pump is cycled between the aspiration speed and the infusion speed such that the catheter pressure cycles between the upper pressure limit and the lower pressure limit.

Abstract: A central database system trains and applies machine-learned models based on characteristics of one or more entities associated with the central database system. For instance, the central database system trains a machine-learned model configured to identify issues a target entity is likely to encounter based on training data identifying characteristics of historical entities and issues faced by the historical entities. Likewise, the central database system trains machine-learned models configured to predict actions that entities are likely to take in the future, and resources required to take those actions. The central database system can then perform one or more proactive actions or make one or more recommendations based on the predicted issues, the predicted future actions, and the predicted required resources.

Abstract: A central database system trains and applies machine-learned models based on characteristics of one or more entities associated with the central database system. For instance, the central database system trains a machine-learned model configured to identify issues a target entity is likely to encounter based on training data identifying characteristics of historical entities and issues faced by the historical entities. Likewise, the central database system trains machine-learned models configured to predict actions that entities are likely to take in the future, and resources required to take those actions. The central database system can then perform one or more proactive actions or make one or more recommendations based on the predicted issues, the predicted future actions, and the predicted required resources.

Abstract: A central database system trains and applies machine-learned models based on characteristics of one or more entities associated with the central database system. For instance, the central database system trains a machine-learned model configured to identify issues a target entity is likely to encounter based on training data identifying characteristics of historical entities and issues faced by the historical entities. Likewise, the central database system trains machine-learned models configured to predict actions that entities are likely to take in the future, and resources required to take those actions. The central database system can then perform one or more proactive actions or make one or more recommendations based on the predicted issues, the predicted future actions, and the predicted required resources.

Abstract: Autonomous aerial navigation in low-light and no-light conditions includes using night mode obstacle avoidance intelligence, training, and mechanisms for vision-based unmanned aerial vehicle (UAV) navigation to enable autonomous flight operations of a UAV in low-light and no-light environments using infrared data.

Abstract: A method includes receiving at an aspiration module of a pump assembly an input associated with a catheter parameter of a catheter coupled to the pump assembly. An aspiration profile associated with the catheter parameter is selected via the aspiration module from a list of preset aspiration profiles associated with different catheters and include upper and lower pressure limits, an aspiration speed, and an infusion speed. A first signal is sent to actuate the pump based on the aspiration profile to operate the pump in a first mode. A pressure signal is received at the aspiration module and a second signal is sent to actuate the pump based on the aspiration profile to operate the pump in a second mode, in which the pump is cycled between the aspiration speed and the infusion speed such that the catheter pressure cycles between the upper pressure limit and the lower pressure limit.