Abstract: A trained machine learning model(s) is used to determine scores (e.g., trust scores) for user accounts registered with a video game service, and the scores are used to match players together in multiplayer video game settings. In an example process, a computing system may access data associated with registered user accounts, provide the data as input to the trained machine learning model(s), and the trained machine learning model(s) generates the scores as output, which relate to probabilities of players behaving, or not behaving, in accordance with a particular behavior while playing a video game in multiplayer mode. Thereafter, subsets of logged-in user accounts executing a video game can be assigned to different matches based at least in part on the scores determined for those logged-in user accounts, and the video game is executed in the assigned match for each logged-in user account.

Abstract: Described herein are, among other things, techniques, devices, and systems for generating one or more trained machine-learning models used for generating content-item recommendations. Also described herein are techniques, devices, and systems for applying a consumption history of a particular user to the trained model(s) to generate score data indicating a correlation between each content-item title and the consumption history, as well as modifying this score data using one or more biasing factors for generating result data. In addition, the techniques, devices, and systems may use this result data, along with received user input, for determining an order in which to present one or more content items to the user. For example, this may include determining which content items to recommend to a user and in which order to do so.

Abstract: Described herein are, among other things, techniques, devices, and systems for generating one or more trained machine-learning models. Also described herein are techniques, devices, and systems for applying a consumption history of a particular user to the trained model(s) to generate score data indicating a correlation between each content-item title and the consumption history. The techniques then determine a ranked list of content items having a highest correlation to the consumption history, which may be used to retrieve videos associated with the most-correlated content items for generating a compilation video composed of these retrieved videos.

Abstract: The present disclosure relates, in general, to improved processes for the preparation of 4-{8-amino-3-[(2S)-1-(but-2-ynoyl)pyrrolidin-2-yl]imidazo[1,5-a]pyrazin-1-yl}-N-(pyridin-2-yl)-benzamide, particularly large-scale processes for manufacturing 4-{8-amino-3-[(2S)-1-(but-2-ynoyl)pyrrolidin-2-yl]imidazo[1,5-a]pyrazin-1-yl}-N-(pyridin-2-yl)benzamide and intermediates used in such processes.

Abstract: A system for tissue dissection and retraction is disclosed herein. A tissue dissection assembly generally comprises an elongate body shaft, an actuation member movable relative to the elongate body shaft, and at least one dissector arm member having at least a first end attached to the elongate body shaft, wherein the at least one dissector arm member is adapted to reconfigure within a plane from a low profile to an expanded profile when urged via the actuation member, and wherein the at least one dissector arm is further adapted to dissect tissue within the plane. In use, the assembly dissects tissue within the plane typically by advancing the elongate body shaft into the tissue region where the dissector arm member or members are then reconfigured within the plane from its low profile to its expanded profile to thereby dissect the tissue region along the plane.

Abstract: Various implementations directed to composite skid member with varying cross-sections are provided. In one implementation, an aircraft landing gear assembly may include two composite skid members configured to contact the ground, where each composite skid member includes a first cross-section and a second cross-section, and where the first cross-section is different than the second cross-section. The aircraft landing gear assembly may also include two cross members configured to couple to a fuselage of an aircraft and configured to interconnect the two composite skid members.

Abstract: A system (100) for handling sheets of flexible material comprises: a plurality of releasable connectors (20) supported on a main carrier (110). The releasable connectors (20) are individually addressable so that when actuated a connector lifts or releases a sheet of flexible material. One or more end adjustment means is provided to vary at least one of: the orientation and/or the location of the connectors (20), with respect to a surface defined in three dimensions, such that in use the sheet of flexible material is placed in a precise user selected position on the three dimensional surface without the material creasing or wrinkling. An advantage of the present invention is that previously actuators were able to orient grippers to be normal to the surface of a cylinder; whereas the provision of parallel, flexible strips enables active surfaces to be positioned normal to the surface of complex surface, such as that defined by a cone.

Abstract: A pad for a railway rail fastening assembly, the pad being configured for placement between a rail and an underlying foundation, such as slab track or a sleeper, wherein a cross-section of the pad comprises: a second resilient layer configured to face a railway rail; an intermediate rigid layer; and a first resilient layer configured to face an underlying foundation. The rigid layer is provided between and is integrally formed with the first and second resilient layers. An edge of the pad comprises at least one ear that extends beyond a central region of the pad, the rigid layer extending into the ear with the ear being configured to resist rail roll.

Abstract: Techniques are described for automatically reducing cheating in an interactive execution environment, such as to perform automated operations to detect and stop use of cheat software in an online game environment, and to restrict subsequent access to the online game environment for users who are identified as using cheat software. The techniques may include using deep learning techniques to train one or more models to classify particular types of gameplay actions as being unauthorized if cheat software use is detected, including to determine a likelihood of whether a separate cheat detection decision system would decide that particular gameplay actions are authorized or not authorized if the additional cheat detection decision system assesses those gameplay actions, and then using the trained model(s) and in some cases the additional cheat detection decision system for the cheat software detection and prevention.

Abstract: Described herein are, among other things, techniques, devices, and systems for generating one or more trained machine-learning models. Also described herein are techniques, devices, and systems for applying a consumption history of a particular user to the trained model(s) to generate score data indicating a correlation between each content-item title and the consumption history. The techniques then determine a ranked list of content items having a highest correlation to the consumption history, which may be used to retrieve videos associated with the most-correlated content items for generating a compilation video composed of these retrieved videos.

Abstract: A system and method of removing turbulence from an image of a time ordered sequence of image frames. The method comprises removing effects of turbulence from a first image of the sequence to create an initial corrected image frame; determining a number of iterations required to achieve a desired turbulence removal for a subsequent image in the sequence and satisfy a latency constraint and an available memory capacity; and determining, based on the number of required iterations, a minimum set of image frames required to remove turbulence from the subsequent image. The minimum set of image frames comprises: a number of image frames of the sequence, a number of image frames generated in an intermediate iteration of turbulence removal and the initial corrected image frame. The method further comprises using the minimum set of image frames to remove turbulence from the subsequent image of the sequence.

Abstract: A trained machine learning model(s) is used to determine scores (e.g., trust scores) for user accounts registered with a video game service, and the scores are used to match players together in multiplayer video game settings. In an example process, a computing system may access data associated with registered user accounts, provide the data as input to the trained machine learning model(s), and the trained machine learning model(s) generates the scores as output, which relate to probabilities of players behaving, or not behaving, in accordance with a particular behavior while playing a video game in multiplayer mode. Thereafter, subsets of logged-in user accounts executing a video game can be assigned to different matches based at least in part on the scores determined for those logged-in user accounts, and the video game is executed in the assigned match for each logged-in user account.

Abstract: An anchoring device for use in retaining a railway rail fastening clip having first and second leg portions and a rail-bearing portion therebetween. The anchoring device includes a base member, an opening in the base member configured to receive a fastening component for fastening the anchoring device to an underlying foundation, and first and second clip-retaining sides extending from said base member with the first clip-retaining side being spaced apart from the second clip-retaining side so as to define a space therebetween for receiving the rail-bearing portion of the clip. Each clip-retaining side comprising upper and lower clip contact walls defining a passageway for receiving one of the leg portions, wherein the leg portions contact the clip contact walls of the respective clip-retaining sides as the clip moves from a wedged position towards an engaged position where the rail-bearing portion of the clip bears on the rail.

Abstract: Various implementations directed to composite skid member with varying cross-sections are provided. In one implementation, an aircraft landing gear assembly may include two composite skid members configured to contact the ground, where each composite skid member includes a first cross-section and a second cross-section, and where the first cross-section is different than the second cross-section. The aircraft landing gear assembly may also include two cross members configured to couple to a fuselage of an aircraft and configured to interconnect the two composite skid members.

Abstract: Various implementations directed to composite skid members are provided. In one implementation, an aircraft landing gear assembly may include two skid members configured to contact the ground, where each skid member includes composite material manufactured using a pultrusion process. The aircraft landing gear assembly may also include a plurality of cross members configured to couple to a fuselage of an aircraft and configured to interconnect the two skid members.

Abstract: A trained machine learning model(s) is used to determine scores (e.g., trust scores) for user accounts registered with a video game service, and the scores are used to match players together in multiplayer video game settings. In an example process, a computing system may access data associated with registered user accounts, provide the data as input to the trained machine learning model(s), and the trained machine learning model(s) generates the scores as output, which relate to probabilities of players behaving, or not behaving, in accordance with a particular behavior while playing a video game in multiplayer mode. Thereafter, subsets of logged-in user accounts executing a video game can be assigned to different matches based at least in part on the scores determined for those logged-in user accounts, and the video game is executed in the assigned match for each logged-in user account.

Abstract: Described herein are, among other things, techniques, devices, and systems for generating one or more trained machine-learning models used for generating content-item recommendations. Also described herein are techniques, devices, and systems for applying a consumption history of a particular user to the trained model(s) to generate score data indicating a correlation between each content-item title and the consumption history, as well as modifying this score data using one or more biasing factors for generating result data. In addition, the techniques, devices, and systems may use this result data, along with received user input, for determining an order in which to present one or more content items to the user. For example, this may include determining which content items to recommend to a user and in which order to do so.

Abstract: Described herein are, among other things, techniques, devices, and systems for generating one or more trained machine-learning models. Also described herein are techniques, devices, and systems for applying a consumption history of a particular user to the trained model(s) to generate score data indicating a correlation between each content-item title and the consumption history. The techniques then determine a ranked list of content items having a highest correlation to the consumption history, which may be used to retrieve videos associated with the most-correlated content items for generating a compilation video composed of these retrieved videos.

Abstract: The present invention relates to analgesic treatments to reduce pain through use of an inhibitor of fatty-acid amide hydrolase pseudogene (FAAH-OUT).

Abstract: A system and method of removing turbulence from an image of a time ordered sequence of image frames. The method comprises removing effects of turbulence from a first image of the sequence to create an initial corrected image frame; determining a number of iterations required to achieve a desired turbulence removal for a subsequent image in the sequence and satisfy a latency constraint and an available memory capacity; and determining, based on the number of required iterations, a minimum set of image frames required to remove turbulence from the subsequent image. The minimum set of image frames comprises: a number of image frames of the sequence, a number of image frames generated in an intermediate iteration of turbulence removal and the initial corrected image frame. The method further comprises using the minimum set of image frames to remove turbulence from the subsequent image of the sequence.