Abstract: An example hydraulic tool includes: a fluid reservoir; a pump; an electric motor; a cylinder; a piston; a first trigger button; a second trigger button; and a controller configured to perform operations comprising: receiving a first signal when the first trigger button is triggered, responsively, causing the electric motor to rotate in a first rotational direction, thereby: (i) causing the pump to provide fluid to the cylinder, and (ii) causing the piston to move in a first linear direction, thereafter, receiving a second signal when the second trigger button is triggered, and responsively to the second signal, causing the electric motor to rotate in a second rotational direction opposite the first rotational direction, thereby: (i) opening a fluid path from the cylinder to the fluid reservoir, and (ii) causing the piston to move in a second linear direction opposite the first linear direction.

Abstract: Vehicles according to at least some embodiments of the disclosure include a sensor, and a computing device comprising at least one hardware processing unit. The computing device is programmed to perform operations comprising capturing an image with the sensor, identifying an object in the image, and in response to an accuracy of the identification meeting a first criterion, pre-loading a braking system of the autonomous vehicle. In some aspects, the computing device may predict that an object not currently within a path of the vehicle has a probability of entering the path of the vehicle that meets a second criterion. When the probability of entering the path meets the second criterion, some of the disclosed embodiments may pre-load the braking system.

Abstract: A simulated environment includes a motion control system. The motion control system may comprise a suspension structure, a housing slidably engaged to the suspension structure such that the suspension controller translates in a planar manner relative to the suspension structure. A rotary component may be rotatably attached to the housing. A plurality of winches may be attached to the rotary component, the plurality of winches having cables to allow longitudinal movement of the cables parallel to a force of gravity.

Abstract: A simulated environment includes a motion control system. The motion control system comprises a suspension structure, a housing slidably engaged to the suspension structure such that the suspension controller translates in a planar manner relative to the suspension structure. A rotary component is rotatably attached to the housing. A plurality of winches are attached to the rotary component, the plurality of winches having cables to allow longitudinal movement of the cables parallel to a force of gravity.

Abstract: Vehicles according to at least some embodiments of the disclosure include a sensor, and a computing device comprising at least one hardware processing unit. The computing device is programmed to perform operations comprising capturing an image with the sensor, identifying an object in the image, and in response to an accuracy of the identification meeting a first criterion, pre-loading a braking system of the autonomous vehicle. In some aspects, the computing device may predict that an object not currently within a path of the vehicle has a probability of entering the path of the vehicle that meets a second criterion. When the probability of entering the path meets the second criterion, some of the disclosed embodiments may pre-load the braking system.

Abstract: Various examples are directed to systems and methods for operating a vehicle comprising a tractor and a trailer attached for pulling behind the tractor. A center-of-mass system may determine a mass of the trailer and a tractor understeer. The center-of-mass system may determine the tractor understeer using steering input data describing a steering angle of the tractor and yaw data describing a yaw of the tractor. The center-of-mass system may determine a load center of mass using the tractor understeer and a mass of the trailer. The center-of-mass system may further determine that the load center of mass transgresses a center-of-mass threshold and send an alert message indicating that the load transgresses the load center-of-mass threshold.

Abstract: Vehicles according to at least some embodiments of the disclosure include a sensor, and a computing device comprising at least one hardware processing unit. The computing device is programmed to perform operations comprising capturing an image with the sensor, identifying an object in the image, and in response to an accuracy of the identification meeting a first criterion, pre-loading a braking system of the autonomous vehicle. In some aspects, the computing device may predict that an object not currently within a path of the vehicle has a probability of entering the path of the vehicle that meets a second criterion. When the probability of entering the path meets the second criterion, some of the disclosed embodiments may pre-load the braking system.

Abstract: The present invention discloses novel crystalline forms of (1R,3R)-3-(cyanomethyl)-3-(4-(6-(1-methyl-1H-pyrazol-4-yl)pyrazolo[1,5-a]pyrazin-4-yl)-1H-pyrazol-1-yl)cyclobutane-1-carbonitrile, Form 1 anhydrous free base and Form 2 monohydrate, pharmaceutical composition containing them, preparations thereof and uses thereof.

Abstract: An exemplary airport tug is configured to navigate an airport facility autonomously. The exemplary airport tug may comprise a coupling portion configured to engage with a receiving portion of an aircraft, one or more sensors configured to collect sensor data descriptive of environmental conditions in a vicinity of the airport tug, a memory storing instructions, and one or more processors communicatively coupled to the memory and configured to execute the instructions to perform a process comprising: monitoring, based on the sensor data, the environmental conditions in the vicinity of the airport tug; and directing, based on the monitoring of the environmental conditions and while the coupling portion is engaged to the receiving portion, autonomous movement of the airport tug to transport the aircraft from a starting position to a designated delivery position for the aircraft at the airport facility.

Abstract: One variation of a method for delivering a digital medicine experience to a user includes: loading the digital medicine experience at a sensory immersion vessel; calculating a target value of a bioindicator of the physiological state of the user, the target value of the bioindicator corresponding to a target physiological state of the user; at an initial time, rendering sensory representations of a set of elements in a multi-sensory virtual environment within the sensory immersion vessel at an initial progression rate; at a time during the digital medicine experience, succeeding the initial time, measuring a value of the bioindicator; calculating a progression rate through the digital medicine experience based on a difference between the value of the bioindicator and the target value of the bioindicator; and at a second time succeeding the time, rendering sensory representations of the set of elements in the multi-sensory virtual environment at the progression rate.

Abstract: One variation of a method for delivering a digital medicine experience to a user includes: loading the digital medicine experience at a sensory immersion vessel; calculating a target value of a bioindicator of the physiological state of the user, the target value of the bioindicator corresponding to a target physiological state of the user; at an initial time, rendering sensory representations of a set of elements in a multi-sensory virtual environment within the sensory immersion vessel at an initial progression rate; at a time during the digital medicine experience, succeeding the initial time, measuring a value of the bioindicator; calculating a progression rate through the digital medicine experience based on a difference between the value of the bioindicator and the target value of the bioindicator; and at a second time succeeding the time, rendering sensory representations of the set of elements in the multi-sensory virtual environment at the progression rate.

Abstract: Systems and methods for integrating data related to aircraft operations such as data from flight logs, flight tracker, maintenance, connectivity, router into modules, for a specific aircraft that can be communicated to and displayed on a single device display in real-time. Systems and methods for integrating data related to aircraft operations into modules, that is both aircraft-specific (engine data, take-off and landing times) and personnel specific (i.e. crew scheduling, passenger manifestos), that includes a web-based interface which incorporates multiple data fields, and can display and communicate on devices, including but not limited to desktop computers, portable devices, such as smart phones, tablets and laptops.

Abstract: In example implementations, an apparatus is provided. The apparatus includes a plurality of power outputs, a logic controller and a single switch. Each one of the plurality of power outputs is communicatively coupled to a respective current/power sensor. The logic controller is communicatively coupled to the respective current/power sensor of each one of the plurality of power outputs. The single switch is communicatively coupled to the logic controller and the respective current/power sensor of each one of the plurality of power outputs. Power to each one of the plurality of power outputs is controlled by the logic controller via the single switch.

Abstract: A system for determining a goodness of a deep learning model comprises a memory coupled with a processor. The processor accesses a first set of vectors representative of images of a biological assay. The vectors of the first set of vectors are outputs of a first deep learning model. The processor creates a first distribution of a first plurality of pairwise comparisons of vectors, of the first set of vectors, which were generated from image pairs with similar cell perturbations. The processor creates a second distribution of a second plurality of pairwise comparisons of vectors, of the first set of vectors, which were generated from image pairs with dissimilar cell perturbations. The processor determines a difference between the first distribution and the second distribution and uses the difference to make a determination of goodness of the deep learning model as applied to the biological assay.

Abstract: A system for selecting CRISPR guides for knocking out one or more target genes in a target cell from a multiplicity of candidate guides comprises a memory and a processor. The processor determines whether the candidate guide meets a plurality of thresholds. The thresholds are associated with: a transcript support level; targeting a consensus sequence of a target gene; which exon of the target gene is targeted; targeting of a primary transcript, targeting of a common isoform; a precomputed prediction of editing outcomes; mapping to an expressed sequence; fraction of gene expression attributable to targeted transcripts; a common SNP overlap threshold; which exon of the target gene is targeted; overlap of a selected guide; predicted frameshift percentage; maximum and minimum GC content; off target score; where a coding sequence is targeted. In response to meeting the thresholds, the processor selects the candidate guide as a selected CRISPR guide.

Abstract: Vehicles according to at least some embodiments of the disclosure include a sensor, and a computing device comprising at least one hardware processing unit. The computing device is programmed to perform operations comprising capturing an image with the sensor, identifying an object in the image, and in response to an accuracy of the identification meeting a first criterion, pre-loading a braking system of the autonomous vehicle. In some aspects, the computing device may predict that an obj ect not currently within a path of the vehicle has a probability of entering the path of the vehicle that meets a second criterion. When the probability of entering the path meets the second criterion, some of the disclosed embodiments may pre-load the braking system.

Abstract: The present disclosure provides CRISPC-Cas systems for the creating mutated genes within cells within wells of an addressable well plate.

Abstract: Vehicles according to at least some embodiments of the disclosure include a sensor, and a computing device comprising at least one hardware processing unit. The computing device is programmed to perform operations comprising capturing an image with the sensor, identifying an object in the image, and in response to an accuracy of the identification meeting a first criterion, pre-loading a braking system of the autonomous vehicle. In some aspects, the computing device may predict that an object not currently within a path of the vehicle has a probability of entering the path of the vehicle that meets a second criterion. When the probability of entering the path meets the second criterion, some of the disclosed embodiments may pre-load the braking system.

Abstract: Systems and methods for exchanging clinical data among parties involved in a clinical trial. The system comprises a clinical data exchange controller, a first repository and a second repository. Repository configuration information comprises: a connection to a target repository, scope of capacities, and a rule set. Repository configuration information for the first repository is received at the first repository, and repository configuration information for the second repository is received at the second repository. When there is a change defined in the rule set happened in the first repository, a request for data transfer is sent to the clinical data exchange controller, and the clinical data exchange controller then transfers the data to the target repository based on the rule set.

Abstract: Various examples are directed to systems and methods for operating a vehicle comprising a tractor and a trailer attached for pulling behind the tractor. A center-of-mass system may determine a mass of the trailer and a tractor understeer. The center-of-mass system may determine the tractor understeer using steering input data describing a steering angle of the tractor and yaw data describing a yaw of the tractor. The center-of-mass system may determine a load center of mass using the tractor understeer and a mass of the trailer. The center-of-mass system may further determine that the load center of mass transgresses a center-of-mass threshold and send an alert message indicating that the load transgresses the load center-of-mass threshold.