Abstract: The present disclosure provides compounds useful for the inhibition of KRAS G12D. The compounds have a general Formula I: (I) wherein the variables of Formula I are defined herein. This disclosure also provides pharmaceutical compositions comprising the compounds, uses of the compounds, and compositions for treatment of, for example, cancer.

Abstract: A depth sensing device, situated above a threshold to a room, collects asynchronous, non-personally-identifiable data regarding a count of people entering and exiting across the threshold. Phase shift of modulated infrared light reflected from a light source to an object is measured and converted into depth data indicating the depth of the pixels therein. The depth data is used to classify detected objects as human, and to track their movement bi-directionally through the threshold. A running count of humans entering or exiting the room is streamed to a remote server, which aggregates data collected from a number of depth sensing devices. The server then makes that data available at various levels of visualization corresponding to different levels of a hierarchy of nested virtual spaces, such as a multi-entrance room, or a building. Entities that access this data may see a real-time, accurate count of humans currently occupying the virtual space, as well as historical data.

Abstract: A plurality of positional sensing devices are situated at regular intervals within an environment and collect data for tracking objects moving within the environment. Phase shift of modulated Doppler pulses reflected from the sensing devices to objects are measured and converted into positional data indicating positions of detected objects within the environment. Associated timestamp data is also collected by the positional sensing devices. The positional data and associated timestamp data is aggregated from the plurality of positional sensors, and the aggregated positional data and is clustered to determine point clouds which are associated with the detected objects. The clusters are tracked by tracklets that track the position of each cluster over time. Trajectories for each detected object are determined by connecting tracklets together that are associated with the same detected object.

Abstract: A plurality of positional sensing devices are situated at regular intervals within an environment and collect data for tracking objects moving within the environment. Phase shift of modulated Doppler pulses reflected from the sensing devices to objects are measured and converted into positional data indicating positions of detected objects within the environment. Associated timestamp data is also collected by the positional sensing devices. The positional data and associated timestamp data is aggregated from the plurality of positional sensors, and the aggregated positional data and is clustered to determine point clouds which are associated with the detected objects. The clusters are tracked by tracklets that track the position of each cluster over time. Trajectories for each detected object are determined by connecting tracklets together that are associated with the same detected object.

Abstract: A depth sensing device, situated above a threshold to a room, collects asynchronous, non-personally-identifiable data regarding a count of people entering and exiting across the threshold. Phase shift of modulated infrared light reflected from a light source to an object is measured and converted into depth data indicating the depth of the pixels therein. The depth data is used to classify detected objects as human, and to track their movement bi-directionally through the threshold. A running count of humans entering or exiting the room is streamed to a remote server, which aggregates data collected from a number of depth sensing devices. The server then makes that data available at various levels of visualization corresponding to different levels of a hierarchy of nested virtual spaces, such as a multi-entrance room, or a building. Entities that access this data may see a real-time, accurate count of humans currently occupying the virtual space, as well as historical data.

Abstract: A depth sensing device, situated above a threshold to a room, collects asynchronous, non-personally-identifiable data regarding a count of people entering and exiting across the threshold. Phase shift of modulated infrared light reflected from a light source to an object is measured and converted into depth data indicating the depth of the pixels therein. The depth data is used to classify detected objects as human, and to track their movement bi-directionally through the threshold. A running count of humans entering or exiting the room is streamed to a remote server, which aggregates data collected from a number of depth sensing devices. The server then makes that data available at various levels of visualization corresponding to different levels of a hierarchy of nested virtual spaces, such as a multi-entrance room, or a building. Entities that access this data may see a real-time, accurate count of humans currently occupying the virtual space, as well as historical data.