Abstract: A chemical mechanical polishing apparatus has a platen to support a polishing pad, a carrier head comprising a rigid housing and configured to hold a surface of a substrate against the polishing pad, a motor to generate relative motion between the platen and the carrier head so as to polish the substrate, an in-situ carrier head monitoring system including a sensor positioned to interact with the housing and to detect vibrational motion of the housing and generate signals based on the detected vibrational motion, and a controller. The controller is configured to generate a value for a carrier head status parameter based on received signals from the in-situ carrier head monitoring system, and change a polishing parameter or generate an alert based on the carrier head status parameter.

Abstract: In one embodiment, a system includes a sensor and an airflow generator coupled to an airflow guide configured to direct airflow from the airflow generator toward and past the sensor. The system includes one or more processors and a non-transitory computer readable storage media embodying instructions coupled to the one or more processors, the one or more processors operable to execute the instructions to acquire data about an operational state of the system, wherein the operational state is related to at least one air contaminant generated by the system; and to control the airflow from the airflow generator based on the data about the operational state of the system.

Abstract: Described herein are CD73 inhibitors and pharmaceutical compositions comprising said compounds. The subject compounds and compositions are useful for the treatment of cancer, infections, and neurodegenerative diseases.

Abstract: According to certain aspects, a computer-implemented method for operating an autonomous or semi-autonomous vehicle may be provided. With the customer's permission, an identity of a vehicle operator may be identified and a vehicle operator profile may be retrieved. Operating data regarding autonomous operation features operating the vehicle may be received from vehicle-mounted sensors. When a request to disable an autonomous feature is received, a risk level for the autonomous feature is determined and compared with a driver behavior setting for the autonomous feature stored in the vehicle operator profile. Based upon the risk level comparison, the autonomous vehicle retains control of vehicle or the autonomous feature is disengaged depending upon which is the safer driver—the autonomous vehicle or the vehicle human occupant. As a result, unsafe disengagement of self-driving functionality for autonomous vehicles may be alleviated.

Abstract: A chemical mechanical polishing system includes a platen to support a polishing pad having a polishing surface, a conduit having an inlet to be coupled to a gas source, and a dispenser coupled to the conduit and having a convergent-divergent nozzle suspended over the platen to direct gas from the gas source onto the polishing surface of the polishing pad.

Abstract: Methods and systems for calibrating simulated measurement signals generated by a parametric measurement model are described herein. Regression on real measurement signals is performed using a parametric model. The residual fitting error between the real measurement signals and simulated measurement signals generated by the parametric model characterizes the error of the parametric model at each set of estimated values of the one or more floating parameters. Simulated measurement signals are generated by the parametric model at specified values of the floating parameters. A residual fitting error associated with the simulated measurement signals generated at the specified values of the floating parameters is derived from the residual fitting errors calculated by the regression on the real measurement signals. The simulated measurement signals are calibrated by adding the residual fitting error to the uncalibrated, simulated measurement signals.

Abstract: Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a user equipment (UE) may measure a signal, transmitted by a base station, using a set of candidate beams. The UE may communicate, with the base station based at least in part on the measurement of the signal, using a first beam from the set of candidate beams. The UE may determine to switch the first beam based on a first value for a beam parameter associated with a second beam, from the set of candidate beams, satisfying a condition. The UE may measure, based at least in part on the determination to switch the first beam, the second beam to obtain a second value of the beam parameter. The UE may switch the first beam to the second beam if the second value satisfies a condition. Numerous other aspects are provided.

Abstract: Conventional high performance computer connections are electron-based systems, which require the memory packages to be as close as mechanically possible to the computation engine. Low power and high bandwidth communication, e.g. photonic, links can drastically change the architecture of high-performance computers by eliminating the bottlenecks in communication and augment existing memory systems to allow them to be both high capacity and high bandwidth simultaneously.

Abstract: A chemical mechanical polishing system includes a platen to support a polishing pad having a polishing surface, a source of coolant, a dispenser having one or more apertures suspended over the platen to direct coolant from the source of coolant onto the polishing surface of the polishing pad; and a controller coupled to the source of coolant and configured to cause the source of coolant to deliver the coolant through the nozzles onto the polishing surface during a selected step of a polishing operation.

Abstract: Inferential analysis includes: assessing risk of a cyber security failure in a computer network of an entity, using a computer agent configured to collect information from at least one accessible Internet elements, automatically determining, based on the assessed risk, a change or a setting to at least one element of policy criteria of a cyber security policy; and automatically recommending, based on the assessed risk, a computer network change to reduce the assessed risk.

Abstract: One embodiment provides a computing device for remote experiential teambuilding activities. The computing device includes a communication circuitry and a user interface (UI). The communication circuitry is configured to couple to a remote computing device via a network. The remote computing device is associated with a remote participant. The UI is configured to receive a local user input from a local participant, and to provide at least one of a local device output or a remote device output to the local participant. The local user input, local device output and remote device output are related to a selected experiential activity.

Abstract: Methods and systems for cross-platform user profiling based on disparate datasets using machine learning models. Specifically, the system may monitor native asset data of an asset corresponding to a cross-platform profile, wherein the cross-platform profile comprises a profile linked to an account, for a user, that is used across multiple assets. The system may detect, using a machine learning model, an incident of the user based on telemetry data extracted from the native asset data. The system may update a status of the cross-platform profile based on the incident. The system may generate for presentation, in a user interface for the account, the status of cross-platform profile and reconstructed asset data based on the incident.

Abstract: Inferential analysis includes: assessing risk of a cyber security failure in a computer network of an entity, using a computer agent configured to collect information from at least one accessible Internet elements, automatically determining, based on the assessed risk, a change or a setting to at least one element of policy criteria of a cyber security policy; and automatically recommending, based on the assessed risk, a computer network change to reduce the assessed risk.

Abstract: Inferential analysis includes: assessing risk of a cyber security failure in a computer network of an entity, using a computer agent configured to collect information from at least one accessible Internet elements; automatically determining, based on the assessed risk, a change or a setting to at least one element of policy criteria of a cyber security policy; and automatically recommending, based on the assessed risk, a computer network change to reduce the assessed risk.

Abstract: Methods and systems for detecting disparate incidents in processed data using a plurality of machine learning models. For example, the system may receive native asset data. The system may extract telemetry data from the native asset data. The system may input the first feature input into a first machine learning model, wherein the first machine learning model is trained to detect known incidents of a first type in a first set of labeled telemetry data. The system may then detect a first incident based on a first output from the first machine learning model, wherein the first incident is a first event in an asset related to the user's behavior.

Abstract: Inferential analysis includes: assessing risk of a cyber security failure in a computer network of an entity, using a computer agent configured to collect information from at least one accessible Internet elements; automatically determining, based on the assessed risk, a change or a setting to at least one element of policy criteria of a cyber security policy; and automatically recommending, based on the assessed risk, a computer network change to reduce the assessed risk.

Abstract: Various embodiments of the present technology include methods of assessing risk of a cyber security failure in a computer network of an entity. Some embodiments involve using continual or periodic data collecting to improve inferential analysis, as well as obtaining circumstantial or inferential information from social networks. Machine learning may be used to improve predicitive capabilities. Some embodiments allow for identification of an entity from circumstantial or inferential information based on the machine learning and comparative analyses.

Abstract: Various embodiments of the present technology include methods of assessing risk of a cyber security failure in a computer network of an entity. Some embodiments involve using continual or periodic data collecting to improve inferential analysis, as well as obtaining circumstantial or inferential information from social networks. Machine learning may be used to improve predicitive capabilities. Some embodiments allow for identification of an entity from circumstantial or inferential information based on the machine learning and comparative analyses.

Abstract: Various embodiments disclosed include, for each entity in a portfolio, receiving entity data indicative of attributes of an entity, determining the received entity data for at least some entities is missing a portion of the entity data required to perform a cyber risk analysis; and synthesizing the missing portion. The method may further include comparing the received entity data and synthesized missing portion for each of the entities to each other; locating clusters of similar entity data shared between two or more of the entities; and calculating a cyber risk score representing how different the entities are to one another based on the entity data that are not shared between entities. Some embodiments include comparing entities that are missing some entity data to entities which have complete entity data, and generating a synthesized portfolio by selecting entities having complete entity data to replace the entities that are missing entity data.

Abstract: Various embodiments of the present technology include methods of assessing risk of a cyber security failure in a computer network of an entity. Some embodiments involve using continual or periodic data collecting to improve inferential analysis, as well as obtaining circumstantial or inferential information from social networks. Machine learning may be used to improve predicitive capabilities. Some embodiments allow for identification of an entity from circumstantial or inferential information based on the machine learning and comparative analyses.