Abstract: The present application relates to particular anti-PAD4 (peptidyl arginine deiminase 4) antibodies, nucleic acids encoding the antibodies, vectors and host cells comprising the nucleic acids, and methods of making and using the antibodies.

Abstract: An electric air heater system including a first electric air heater module. The first electric air heater module including an outer casing having an inner surface, a first end, and a second end; a refractory insulation layer in tight communication with the outer casing; an inner cavity within the refractory insulation layer; and a plurality of tubes extending through the inner cavity from the first end to the second end, the plurality of tubes each having an exterior surface. Each tube is fixed relative to the outer casing at the first end, and each tube has an electrical connection disposed at the first end. The plurality of tubes is arranged into one or more bundles of tubes, where each bundle includes two or more tubes having a plurality of fins extending radially from the exterior surface, and a heating element axially through a hollow interior of the tube.

Abstract: Disclosed are antigen binding polypeptides and antigen binding polypeptide complexes (e.g., antibodies and antigen binding fragments thereof) having certain structural and/or functional features. Also disclosed are polynucleotides and vectors encoding such polypeptides and polypeptide complexes; host cells, pharmaceutical compositions and kits containing such polypeptides and polypeptide complexes; and methods of using such polypeptides and polypeptide complexes.

Abstract: This disclosure describes a system and method for generating images and location data of a subsurface object using existing infrastructure as a source. Many infrastructure objects (e.g., pipes, cables, conduits, wells, foundation structures) are constructed of rigid materials and have a known shape and location. Additionally these infrastructure objects can have exposed portions that are above or near the surface and readily accessible. A signal generator can be affixed to the exposed portion of the infrastructure object, which induces acoustic energy, or vibrations in the object. The object with affixed signal generator can then be used as a source in performing a subsurface imaging of subsurface objects, which are not exposed.

Abstract: This disclosure describes a system and method for generating images by performing TEM surveys using pre-existing infrastructure such as transmission lines, or power lines, and naturally occurring transients such as lightning strikes or load switching. A relatively inexpensive sensor array can be installed on overhead power lines (e.g., electrical transmission or sub-transmission lines) which can detect transients in the overhead power lines. Transients in the overhead power lines can cause the power lines to emit pulses of electromagnetic (EM) radiation, which propagate into the earth's subsurface. This sudden change in electromagnetic field in the subsurface can induce eddy currents, which in turn emit return EM radiation that can propagate back to the overhead power line and induce secondary voltage and current transients. The magnitude of these secondary transients, and their time delay from the original transient are influenced by the properties of the subsurface in which the eddy currents formed.

Abstract: In some implementations, a server may receive, from a user device and at a secure endpoint of an application programming interface, a set of structured data including a plurality of entries. The server may extract, from each entry, a corresponding partial string from a corresponding description string included in the entry, and may determine, for each partial string, a corresponding data structure in a database. The server may generate, for each entry, a standardized name and a location indicator based on the corresponding data structure, and may extract, for each data structure, an image corresponding to the data structure. Accordingly, the server may return, to the user device, a modified set of structured data including, for each entry, the standardized name, the location indicator, and the corresponding image.

Abstract: This disclosure describes a system and method for generating images and location data of a subsurface object using existing infrastructure as a source. Many infrastructure objects (e.g., pipes, cables, conduits, wells, foundation structures) are constructed of rigid materials and have a known shape and location. Additionally these infrastructure objects can have exposed portions that are above or near the surface and readily accessible. A signal generator can be affixed to the exposed portion of the infrastructure object, which induces acoustic energy, or vibrations in the object. The object with affixed signal generator can then be used as a source in performing a subsurface imaging of subsurface objects, which are not exposed.

Abstract: This disclosure describes a system and method for generating images by performing TEM surveys using pre-existing infrastructure such as transmission lines, or power lines, and naturally occurring transients such as lightning strikes or load switching. A relatively inexpensive sensor array can be installed on overhead power lines (e.g., electrical transmission or sub-transmission lines) which can detect transients in the overhead power lines. Transients in the overhead power lines can cause the power lines to emit pulses of electromagnetic (EM) radiation, which propagate into the earth's subsurface. This sudden change in electromagnetic field in the subsurface can induce eddy currents, which in turn emit return EM radiation that can propagate back to the overhead power line and induce secondary voltage and current transients. The magnitude of these secondary transients, and their time delay from the original transient are influenced by the properties of the subsurface in which the eddy currents formed.

Abstract: This disclosure describes a system and method for generating a subsurface model representing lithological characteristics and attributes of the subsurface of a celestial body or planet. By automatically ingesting data from many sources, a machine learning system can infer information about the characteristics of regions of the subsurface and build a model representing the subsurface rock properties. In some cases, this can provide information about a region using inferred data, where no direct measurements have been taken. Remote sensing data, such as aerial or satellite imagery, gravimetric data, magnetic field data, electromagnetic data, and other information can be readily collected or is already available at scale.

Abstract: Methods, systems, and apparatuses, including computer programs encoded on a computer storage medium, for machine learning classification based on separate processing of multiple views. In some implementations, a system obtains image data for multiple images showing different views of an object. A machine learning model is used to generate a separate output based on each the multiple images individually. The outputs for the respective images are combined to generate a combined output. A predicted characteristic of the object is determined based on the combined output. An indication of the predicted characteristic of the object is provided.

Abstract: A carbon dioxide (CO2) sequestration sensor system includes an underground sub-assembly including one or more sensors configured to detect at least one attribute associated with CO2 sequestration below a terranean surface; and an above-ground sub-assembly positionable on the terranean surface proximate the underground sub-assembly and including at least one controller communicably coupled to the one or more sensors.

Abstract: Methods, systems, apparatus, and computer-readable media for data band selection using machine learning. In some implementations, image data comprising information for each of multiple wavelength bands is obtained. A multi-layer neural network is trained using the image data to perform one or more classification or regression tasks. A proper subset of the wavelength bands is selected based on parameters of a layer of the trained multi-layer neural network, where the parameters were determined through training of the multi-layer neural network using the image data. Output is provided indicating that the selected wavelength bands are selected for the one or more classification or regression tasks.

Abstract: A system and method for automated lens adjustment for hyperspectral imaging is described. The system includes an image sensor and an electrically-controllable element arranged to set a spectral band for image capture by (i) selectively providing light for a selected spectral band or (ii) selectively filtering light to a selected spectral band. The system includes a tunable lens that is adjustable to change a focal length of the lens; and one or more data storage devices storing data that indicates different focus adjustment parameters corresponding to different spectral bands. The system includes a control system configured to perform operations including: selecting a spectral band; controlling the electrically-controllable element to set the spectral band for image capture; retrieving the focus adjustment parameter that corresponds to the spectral band; adjusting the lens based on the retrieved focus adjustment parameter; and capturing an image of the subject while the lens remains adjusted.

Abstract: This disclosure describes a system and method for generating a subsurface model representing lithological characteristics and attributes of the subsurface of a celestial body or planet. By automatically ingesting data from many sources, a machine learning system can infer information about the characteristics of regions of the subsurface and build a model representing the subsurface rock properties. In some cases, this can provide information about a region using inferred data, where no direct measurements have been taken. Remote sensing data, such as aerial or satellite imagery, gravimetric data, magnetic field data, electromagnetic data, and other information can be readily collected or is already available at scale.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for improved image segmentation using hyperspectral imaging. In some implementations, a system obtains image data of a hyperspectral image, the image data comprising image data for each of multiple wavelength bands. The system accesses stored segmentation profile data for a particular object type that indicates a predetermined subset of the wavelength bands designated for segmenting different region types for images of an object of the particular object type. The system segments the image data into multiple regions using the predetermined subset of the wavelength bands specified in the stored segmentation profile data to segment the different region types. The system provides output data indicating the multiple regions and the respective region types of the multiple regions.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for image segmentation and chemical analysis using machine learning. In some implementations, a system obtains a hyperspectral image that includes a representation of an object. The system segments the hyperspectral image to identify regions of a particular type on the object. The system generates a set of feature values derived from image data for different wavelength bands that is located in the hyperspectral image in the identified regions of the particular type. The system generates a prediction of a level of one or more chemicals in the object based on an output produced by a machine learning model in response to the set of feature values being provided as input to the machine learning model. The system provides data indicating the prediction of the level of the one or more chemicals in the object.

Abstract: Image data is obtained that indicates an extent to which one or more objects reflect, scatter, or absorb light at each of multiple wavelength bands, where the image data was collected while a conveyor belt was moving the object(s). The image data is preprocessed by performing an analysis across frequencies and/or performing an analysis across a representation of a spatial dimension. A set of feature values is generated using the image preprocessed image data. A machine-learning model generates an output using to the feature values. A prediction of an identity of a chemical in the one or more objects or a level of one or more chemicals in the object(s) is generated using the output. Data is output indicating the prediction of the identity of the chemical in the object(s) or the level of the one or more chemicals in at least one of the one or more objects.

Abstract: This disclosure describes a system and method for generating images and location data of a subsurface object using existing infrastructure as a source. Many infrastructure objects (e.g., pipes, cables, conduits, wells, foundation structures) are constructed of rigid materials and have a known shape and location. Additionally these infrastructure objects can have exposed portions that are above or near the surface and readily accessible. A signal generator can be affixed to the exposed portion of the infrastructure object, which induces acoustic energy, or vibrations in the object. The object with affixed signal generator can then be used as a source in performing a subsurface imaging of subsurface objects, which are not exposed.

Abstract: Methods, systems, apparatus, and computer-readable media for data band selection using machine learning. In some implementations, image data comprising information for each of multiple wavelength bands is obtained. A multi-layer neural network is trained using the image data to perform one or more classification or regression tasks. A proper subset of the wavelength bands is selected based on parameters of a layer of the trained multi-layer neural network, where the parameters were determined through training of the multi-layer neural network using the image data. Output is provided indicating that the selected wavelength bands are selected for the one or more classification or regression tasks.

Abstract: This disclosure describes a transportation matching system that manages the allocation of transportation providers by training and utilizing multiple machine-learning models to identify, allocate, and serve specific transportation providers with customized opportunities to relocate the transportation providers between geocoded areas in a geocoded region. For instance, the transportation matching system trains and utilizes an incremental provider model, a provider allocation model, and personalized provider behavioral models as well as a customized provider interface generator to satisfy anticipated transportation requests and improve transportation matching within a geocoded region.