Abstract: Methods, systems, and apparatus, including computer programs encoded on a storage device, for electric grid modeling using surfel data are enclosed. An electric grid wire identification method includes: obtaining a set of surface elements (surfels), wherein each surfel of the set of surfels represents a portion of a surface of an object in a geographic region; selecting, based on one or more surfel attributes, one or more surfels of the set of surfels that each represent a portion of a surface of an electric grid wire; generating a representation of the electric grid wire from the selected one or more surfels; and adding the representation of the electric grid wire to a virtual model of the electric grid. Obtaining the set of surfels can include obtaining ranging data of the geographic region; and generating the set of surfels from the ranging data.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for receiving, from one of two or more sensors of a device that independently determine whether an aircraft takeoff has likely occurred, an indication that the aircraft takeoff has likely occurred; activating, based on receiving the indication that the aircraft takeoff has likely occurred, an airplane mode of the device; receiving, while the device is in the airplane mode and from one of two or more other sensors of the device that independently determine that an aircraft flight is likely not occurring, an indication that the aircraft flight is likely not occurring; and deactivating, based on receiving the indication that the aircraft flight is likely not occurring, the airplane mode of the device. The indication that the aircraft takeoff has likely occurred may include acceleration data indicating an acceleration of the device in three dimensions.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for developing electrical grid mapping. One of the methods includes obtaining a computer model of an electric power grid; generating a network graph representation of the computer model, wherein nodes of the network graph represent grid assets of the computer model and edges of the network graph represent wires connecting the grid assets; generating an initial prediction of links between nodes in the network graph by adding at least one edge to the network graph to obtain an over-connected graph; applying the over-connected network graph as input to a machine learning model to obtain an annotated network graph, the machine learning model configured to identify edges as positive links and negative links, and apply annotations to the edges indicating whether each edge is a positive or negative link; and updating the model based on the annotated network graph.

Abstract: In some embodiments, techniques for creating fabricable segmented designs for physical devices are provided. A proposed segmented design is determined based on a design specification. The proposed segmented design includes a plurality of segments that each includes an indication of a material for the segment. The proposed segmented design also includes lattice members and lattice voids. A size of the lattice members and a size of the lattice voids are greater than a size of the segments and are greater than or equal to at least one of a minimum feature width and a minimum feature spacing of a fabrication system Performance of the proposed segmented design is simulated. One or more lattice members and lattice voids are chosen to change to improve the performance of the proposed segmented design.

Abstract: Some techniques relate to projecting aptamer representations into an embedding space and clustering the representations. A cluster-specific binding metric can be defined for each cluster based on aptamer-specific binding metrics of aptamers associated with the cluster. A subset of the clusters can be selected based on the cluster-specific binding metrics. Identifications of aptamers assigned to the subset of clusters can then be output.

Abstract: A multi-dimensional latent space (defined by an Encoder model) corresponds to projections of sequences of aptamers. An architecture of the Encoder model, a hyperparameter of the Encoder model, or a characteristic of a training data set used to train the Encoder model was selected using an assessment of an encoding-efficiency of the Encoder model that is based on: a predicted extents to which representations in an embedding space are indicative of specific aptamer sequences to which a probability distribution of the embedding space differs from a probability distribution of a source space that represents individual base-pairs; generating projections in the latent space using representations of aptamers and the Encoder model; identifying one or more candidate aptamers for the particular target using the projections and the Decoder model; and outputting an identification of the one or more candidate aptamers.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for governing phenotypic outcomes in plants. One method includes obtaining a model input comprising time series data, wherein the time series data comprises, for each previous time point of one or more previous time points, at least one of i) first multi-omics data corresponding to a plant at the previous time point, or ii) phenotypic data corresponding to the plant at the previous time point; and processing the model input using a machine learning model to obtain a model output that comprises, for each future time point of one or more of future time points, a prediction of at least one of i) a phenotype of the plant at the future time point, or ii) second multi-omics data corresponding to the plant at the future time point.

Abstract: Methods described herein include receiving data from flowing a plurality of aptamers over a sample of tumor cells randomly affixed to a surface of a microfluidic device. The tumor cells may include one or more unknown tumor subtypes of cells. The plurality of aptamers may include a plurality of aptamer families. Each aptamer family of the plurality of aptamer families may be determined to bind to at least one possible subtype of the tumor cells. The data may include a measure of binding affinity of each aptamer family to the tumor cells. The method may include analyzing the measure of the binding affinity of each aptamer family to the tumor cells. The analyzing may include classifying the binding affinity. The method may also include determining one or more aptamer families that characterize the one or more unknown tumor subtypes of cells based on the classifying.

Abstract: An optical communication system includes an optical transmitter and one or more processors. The optical transmitter is configured to output an optical signal, and includes an average-power-limited optical amplifier, such as an erbium-doped fiber amplifier (EDFA). The one or more processors are configured to receive optical signal data related to a received power for a communication link from a remote communication system and determine that the optical signal data is likely to fall below a minimum received power within a time interval. In response to the determination, the one or more processors are configured to determine a duty cycle of the optical transmitter based on a minimum on-cycle length and a predicted EDFA output power and operate the optical transmitter using the determined duty cycle to transmit an on-cycle power that is no less than the minimum required receiver power for error-free operation of the communication link.

Abstract: Methods, systems, and apparatus for an infrared and visible imaging system. In some implementations, Image data from a visible-light camera is obtained. A position of a device is determined based at least in part on the image data from the visible-light camera. An infrared camera is positioned so that the device is in a field of view of the infrared camera, with the field of view of the infrared camera being narrower than the field of view of the visible-light camera. Infrared image data from the infrared camera that includes regions representing the device is obtained. Infrared image data from the infrared camera that represents the device is recorded. Position data is also recorded that indicates the location and pose of the infrared camera when the infrared image data is acquired by the infrared camera.

Abstract: Methods, systems, and apparatus for receiving a request for a damage propensity score for a parcel, receiving imaging data for the parcel, wherein the imaging data comprises street-view imaging data of the parcel, extracting, by a machine-learned model including multiple classifiers, characteristics of vulnerability features for the parcel from the imaging data, determining, by the machine-learned model and from the characteristics of the vulnerability features, a damage propensity score for the parcel, and providing a representation of the damage propensity score for display.

Abstract: A computer-implemented method for modeling fabrication constraints of a fabrication process is described. The method includes receiving training data including pre-fabrication structures and post-fabrication, training a fabrication constraint model by optimizing parameters of the fabrication constraint model based on the training data to model the fabrication constraints of the fabrication process, receiving an input design corresponding to a physical device, and generating a fabricability metric of the input design via the fabrication constraint model. The fabricability metric is related to a probabilistic certainty that the input design is fabricable by the fabrication process determined by the fabrication constraint model.

Abstract: In some embodiments, a method for optimal parallel execution of a simulation of a design is provided. A computing device extracts one or more features from the design. The computing device provides at least the one or more features as inputs to one or more machine learning models to determine one or more predictions of execution times. The computing device determines an optimum execution architecture based on the one or more predictions of execution times. The computing device distributes portions of the design for simulation based on the optimum execution architecture. In some embodiments, one or more machine learning models are trained to generate outputs for predicting an optimal parallel execution architecture for simulation of a design.

Abstract: Methods and systems, including computer programs encoded on computer-storage media, for controlling a system for growing seaweed are described. Some implementations of a method include forming a substrate loop inoculated with seaweed spores; arranging the substrate loop about a pulley; submerging the substrate loop to grow the seaweed; determining, using a seaweed farm controller, that the seaweed has grown to a pre-determined size; and based on the determination that the seaweed has grown to a pre-determined size: providing instructions to the pulley to feed a section of the substrate loop to a harvesting unit; providing instructions to the harvesting unit to separate the seaweed attached to the section of the substrate loop; providing instructions to a cleaning unit to clean the section of the substrate loop that is freed from seaweed; and providing instructions to a seeding unit to inoculate the cleaned section of substrate loop with seaweed spores.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for determining turbidity of water using machine learning. One of the methods includes obtaining, by a camera, an image of water; detecting, using a blob detector, a plurality of blobs in the image that represent particles suspended in the water; determining a distribution of the plurality of blobs; determining, from the distribution of the plurality of blobs, a measurement associated with turbidity of the water; and providing a signal associated with the measurement.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a storage device, for electric grid asset detection are enclosed. An electric grid asset detection method includes: obtaining overhead imagery of a geographic region that includes electric grid wires; identifying the electric grid wires within the overhead imagery; and generating a polyline graph of the identified electric grid wires. The method includes replacing curves in polylines within the polyline graph with a series of fixed lines and endpoints; identifying, based on characteristics of the fixed lines and endpoints, a location of a utility pole that supports the electric grid wires; detecting an electric grid asset from street level imagery at the location of the utility pole; and generating a representation of the electric grid asset for use in a model of the electric grid.

Abstract: A method for controlling a sensor subsystem, the method including receiving one or more metrics representing one or more characteristics of livestock, including one or more livestock objects, contained in an enclosure and monitored by one or more sensors coupled to a winch subsystem. The method further includes determining a position to move the one or more sensors based on the metrics and determining an instruction that includes information related to a movement of the one or more sensors. The method further includes sending the instruction to the winch subsystem to change the position of the one or more sensors.

Abstract: Techniques for processing ore include the steps of causing an imaging capture system to record a plurality of images of a stream of ore fragments en route from a first location in an ore processing facility to a second location in the ore processing facility; correlating the plurality of images of the stream of ore fragments with at least one or more characteristics of the ore fragments using a machine learning model that includes a plurality of ore parameter measurements associated with the one or more characteristics of the ore fragments; determining, based on the correlation, at least one of the one or more characteristics of the ore fragments; and generating, for display on a user computing device, data indicating the one or more characteristics of the ore fragments or data indicating an action or decision based on the one or more characteristics of the ore fragments.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer-storage media, for controlling an aquaculture feeding system are described. In some implementations, a method includes determining, using a feeding system controller, that a feeding system has transitioned from a first state to a second state, and based on the transition from the first to the second state providing, using the feeding system controller, instructions to a dosing system to set a feed rate of the dosing system, and providing, using the feeding system controller, instructions to a blower operatively coupled to the dosing system to set a flow rate of the blower.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer-storage media, for obtaining initial parameters for ultrasonic transducers around a calibration target. The calibration target can include a fish-shaped structure, sensors placed at different locations of the fish-shaped structure, a processor that receives sensor values from the sensors, and a transmitter that outputs sensor data from the calibration target based on the sensor values. The calibration target can be fixed at a particular position relative to the ultrasonic transducers by a filament coupled to both the calibration target and a support structure. Sensor data can be obtained from the calibration target at the particular position relative to the ultrasonic transducers, and relative locations of the sensors can be determined. Parameters for the ultrasonic transducers around the calibration target can be adjusted based on the sensor data and the respective locations of the sensors.