AUTONOMOUS VEHICLE SYSTEM

Sensor data is received from a plurality of sensors, where the plurality of sensors includes a first set of sensors and a second set of sensors, and at least a portion of the plurality of sensors are coupled to a vehicle. Control of the vehicle is automated based on at least a portion of the sensor data generated by the first set of sensors. Passenger attributes of one or more passengers within the autonomous vehicles are determined from sensor data generated by the second set of sensors. Attributes of the vehicle are modified based on the passenger attributes and the sensor data generated by the first set of sensors.

Systems, methods, and devices for electronic spectrum management

Methods for tracking a signal origin by a spectrum analysis and management device are disclosed. Signal characteristics of other known emitters are used for obtaining a position of an emitter of a signal of interest. In one embodiment, frequency difference of arrival technique is implemented. In another embodiment, time difference of arrival technique is implemented.

Ultrasonic surgical instrument with a carrier kart and reusable stage

A surgical instrument includes an end effector, a shaft assembly, a carrier, and a support structure. Shaft assembly extends proximally from the end effector. The shaft assembly defines a longitudinal axis. The carrier is configured to translate the end effector along the longitudinal axis. The carrier includes a carriage, an actuation driver, and an actuation assembly. The actuation driver is configured to rotate along an axis parallel to the longitudinal axis. The actuation assembly is operatively coupled with the actuation driver and the carriage. The support structure includes a supporting portion. The supporting portion is configured to reduce torsional forces exerted on the carriage as the actuation assembly transfers the rotation of the actuation driver into translation of a portion of the shaft assembly to actuate the end effector.

Methods of detecting analytes

Localized detection of RNA in a tissue sample that includes cells is accomplished on an array. The array include a number of features on a substrate. Each feature includes a different capture probe immobilized such that the capture probe has a free 3′ end. Each feature occupies a distinct position on the array and has an area of less than about 1 mm2. Each capture probe is a nucleic acid molecule, which includes a positional domain including a nucleotide sequence unique to a particular feature, and a capture domain including a nucleotide sequence complementary to the RNA to be detected. The capture domain can be at a position 3′ of the positional domain.

Enhancing specificity of analyte binding

Methods for enhancing specificity of an analyte binding moiety or probe oligonucleotide to an analyte are provided herein. For example, methods provided herein include blocking a capture binding domain, thereby preventing hybridization to the capture domain of the capture probe affixed to a substrate. Further methods include releasing the block from the capture binding domain, thereby allowing the capture binding domain to specifically bind to the capture domain of the capture probe on the substrate.

Spatial analysis of DNA methylation

Provided herein are methods of identifying a methylation status of an analyte in a biological sample. Also provided herein are methods that combine identifying the methylation status with spatial technology to identify the location of a methylation status in a biological sample.

System and method for characterizing properties of EM signals

A method and system are presented for determining properties of an electromagnetic waveform. The method comprises: providing measured parametric EM field data indicative of measured vector components of electric and magnetic fields of an EM waveform measured in at least one instance of time: providing reference data indicative of a plurality of reference data sets, each data set comprising: a reference steering vector parameters indicative of a certain respective direction of arrival (DO A), and a corresponding parametric EM field reference data including reference vector components of an electric and magnetic field pertaining to a wavefront propagating with the DO A of the corresponding reference steering vector parameters; determining a matching score between the measured parametric EM field data and the parametric EM field reference data of one or more of the reference data sets; and in case the matching score of a certain reference data set complies with a certain threshold condition, determining that said measured parametric EM field data corresponds to said EM waveform having a single EM wavefront thereby enabling to discriminate between measured EM waveforms having a single wavefront and measured EM waveforms having multiple wavefronts.

Systems, methods, and devices for automatic signal detection based on power distribution by frequency over time within a spectrum

Systems, methods and apparatus for automatic alarm management in a radio-frequency (RF) environment are disclosed. An apparatus calculates a power distribution by frequency of the RF environment in real time or near real time, including a first derivative and a second derivative of FFT data of the RF environment. The apparatus then creates a baseline based on the power distribution by frequency of the RF environment in a period of time, identifies at least one alarm situation based on a multiplicity of alarm triggering conditions by comparing the power distribution in real time or near real time to the baseline of the RF environment, identifies at least one signal based on the first derivative and the second derivative of FFT data in the at least one alarm situation, and sends at least one alarm comprising details of the at least one signal identified in the at least one alarm situation.

DETECTING SUPPLY CHAIN ISSUES IN CONNECTION WITH INVENTORY MANAGEMENT USING MACHINE LEARNING TECHNIQUES

Methods, apparatus, and processor-readable storage media for detecting supply chain issues in connection with inventory management using machine learning techniques are provided herein. An example computer-implemented method includes obtaining data pertaining to inventory items in connection with a supply chain; training machine learning techniques using the obtained data, wherein training the machine learning techniques comprises determining upper bounds and lower bounds for parameters related to the supply chain; detecting anomalies in audit data pertaining to at least one inventory item within the supply chain by processing the audit data using the machine learning techniques; generating a graph representing the supply chain based on the obtained data and the audit data; identifying at least one issue within the at least one supply chain by processing the graph in connection with the detected anomalies using graph algorithms; and performing an automated action based on the identified issue(s).

AUTONOMOUS VEHICLE SYSTEM

An apparatus comprising at least one interface to receive sensor data from a plurality of sensors of a vehicle; and one or more processors to autonomously control driving of the vehicle according to a path plan based on the sensor data; determine that autonomous control of the vehicle should cease; send a handoff request to a remote computing system for the remote computing system to control driving of the vehicle remotely; receive driving instruction data from the remote computing system; and control driving of the vehicle based on instructions included in the driving instruction data.