Abstract: Methods and systems are described for performing spectroscopic measurement of at least one analyte of interest in an inhomogeneous sample using a spectroscopic system. This generally involves generating and aiming an illumination beam which forms a focal region having focal region size S upon a surface or within a volume of the sample where there is relative motion between the sample and the focal region at a relative speed V; selecting a desired ratio between an exposure time E for a detector of the spectroscopic system and a transit time T for a particle of the at least one analyte of interest to traverse the focal region; acquiring one or more spectral data sets corresponding to spectra for a region of the sample within the focal region; and analyzing the one or more spectral data sets to generate one or more corresponding analytical results.

Abstract: Provided is a process including: receiving a tank-nearly-full message indicating that a tank at an oil or gas related facility is or will be ready for a truck to unload and transport fluid accumulating in the tank; in response to the tank-nearly-full message, creating a tank-run record; sending a description of the tank-run to a mobile device of a driver of an oilfield truck; receiving, from the mobile device of the driver of the oilfield truck, a tank-run claimed message indicating that the driver will drive to the oil or gas related facility and transport at least some of the fluid accumulating in the tank; and after the tank-run claimed message, performing steps including: confirming that the tank-run has not yet been claimed; after the confirmation, designating the tank-run as claimed by the driver; and sending confirmation to the mobile device of the driver.

Abstract: Methods and devices are described herein for a) injecting/delivering fluid to and/or draining/removing fluid from the eye. One of the devices may comprise a probe including a main body having a distal end portion; a needle that extends and retracts from an exit location on a side surface of the distal end portion, the needle having a needle conduit; and one or more probe conduits for moving the fluid through the probe, the one or more probe conduits being fluidically coupled to the needle conduit. During use, a portion of the side surface having the exit location is placed adjacent to a surface of the eye and the needle is extended to penetrate into the eye, and the fluid is injected or drained through the needle conduit.

Abstract: Computerized methods and apparatuses, including computer program products, for guided workflow processing include a server computing device which determines a guided workflow transaction path based upon input received from a first client device. The server initiates a transaction based upon the transaction path, including capturing data elements associated with a user of a second client device. The server stores the captured data elements, including a transaction identification token and a state of the transaction path. The server receives a request to continue the transaction from the second client device and retrieves the data elements. The server generates a user interface form based upon the state of the transaction path and displays the user interface form on the second client device. The server processes the transaction based upon input received from the second client device via the user interface form.

Abstract: Provided is a process, including: receiving, via the network interface, from a remote user device, a command to change a state of the fluid-handling device to a target state; translating the received command into a translated command operative to cause a local controller of the fluid-handling device to drive the fluid-handling equipment to the target state, the local controller being responsive to the command and feedback from the fluid-handling device indicative of whether the fluid-handling device is in the target state; and sending the translated command to the local controller

Abstract: A generative neural network control system controls a generative neural network by modifying the intermediate latent space in the generative neural network. The generative neural network includes multiple layers each generating a set of activation values. An initial layer (and optionally additional layers) receives an input latent vector, and a final layer outputs an image generated based on the input latent vector. The data that is input to each layer (other than the initial layer) is referred to as data in an intermediate latent space. The data in the intermediate latent space includes activation values (e.g., generated by the previous layer or modified using various techniques) and optionally a latent vector. The generative neural network control system modifies the intermediate latent space to achieve various different effects when generating a new image.

Abstract: A message-oriented method that includes receiving a first message that includes first sensor data obtained by a first sensor, wherein the first message is associated with a first publishing identifier such that the first sensor is configured to obtain the first sensor data. The method further includes one or more computer systems that are subscribed to the first publishing identifier and providing the first message that includes the first sensor data to a first computer system of the one or more computer systems and the first computer system is disposed at a first fluid handling site, the first computer system being configured to provide control of at least one fluid handling component.

Abstract: Provided is a process, including: receiving, via the network interface, from a remote user device, a command to change a state of the fluid-handling device to a target state; translating the received command into a translated command operative to cause a local controller of the fluid-handling device to drive the fluid-handling equipment to the target state, the local controller being responsive to the command and feedback from the fluid-handling device indicative of whether the fluid-handling device is in the target state; and sending the translated command to the local controller.

Abstract: Provided is a process including: receiving a tank-nearly-full message indicating that a tank at an oil or gas related facility is or will be ready for a truck to unload and transport fluid accumulating in the tank; in response to the tank-nearly-full message, creating a tank-run record; sending a description of the tank-run to a mobile device of a driver of an oilfield truck; receiving, from the mobile device of the driver of the oilfield truck, a tank-run claimed message indicating that the driver will drive to the oil or gas related facility and transport at least some of the fluid accumulating in the tank; and after the tank-run claimed message, performing steps including: confirming that the tank-run has not yet been claimed; after the confirmation, designating the tank-run as claimed by the driver; and sending confirmation to the mobile device of the driver.

Abstract: Provided is a surveillance system, including: a trailer having wheels, a mast, and a trailer towing coupler; a camera coupled to the mast; a cellular modem communicatively coupled to the camera and operative to transmit video captured by the camera; a command center server operative to remotely receive and store data describing operation of a fluid-handling device and to receive the transmitted video and send the video to a user in response to a request from a web browser of the user; a power storage device; and a solar panel coupled to the power storage device such that the solar panel charges the power storage device.

Abstract: Provided is a process, including: receiving, via the network interface, from a remote user device, a command to change a state of the fluid-handling device to a target state; translating the received command into a translated command operative to cause a local controller of the fluid-handling device to drive the fluid-handling equipment to the target state, the local controller being responsive to the command and feedback from the fluid-handling device indicative of whether the fluid-handling device is in the target state; and sending the translated command to the local controller

Abstract: A generative neural network control system controls a generative neural network by modifying the intermediate latent space in the generative neural network. The generative neural network includes multiple layers each generating a set of activation values. An initial layer (and optionally additional layers) receives an input latent vector, and a final layer outputs an image generated based on the input latent vector. The data that is input to each layer (other than the initial layer) is referred to as data in an intermediate latent space. The data in the intermediate latent space includes activation values (e.g., generated by the previous layer or modified using various techniques) and optionally a latent vector. The generative neural network control system modifies the intermediate latent space to achieve various different effects when generating a new image.

Abstract: An implantable blood pressure monitor has two or more elements configured to wrap at least part way around a blood vessel. Changes in pressure within the blood vessel may be sensed by detecting movements of the elements or forces applied to the elements. A blood pressure monitor may be implanted without surgery. The blood pressure monitor may transmit real time blood pressure information to a receiver by wireless data transmission.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for normalizing, compressing, and correlating vulnerabilities are disclosed. In one aspect, a method includes the actions of generating a first and second copy of a software target. The actions further include providing the first copy to a first scanning tool and the second copy to a second scanning tool. The actions further include receiving a first scanning tool output that identifies a first issue of the software target. The actions further include receiving a second scanning tool output that identifies a second issue of the software target. The actions further include determining that the first issue and the second issue are a same issue. The actions further include generating a combined issue of the first issue and the second issue. The actions further include outputting a notification that includes the combined issue.

Abstract: Provided is a process, including: receiving, via the network interface, from a remote user device, a command to change a state of the fluid-handling device to a target state; translating the received command into a translated command operative to cause a local controller of the fluid-handling device to drive the fluid-handling equipment to the target state, the local controller being responsive to the command and feedback from the fluid-handling device indicative of whether the fluid-handling device is in the target state; and sending the translated command to the local controller.

Abstract: Provided is a surveillance system, including: a trailer having wheels, a mast, and a trailer towing coupler; a camera coupled to the mast; a cellular modem communicatively coupled to the camera and operative to transmit video captured by the camera; a command center server operative to remotely receive and store data describing operation of a fluid-handling device and to receive the transmitted video and send the video to a user in response to a request from a web browser of the user; a power storage device; and a solar panel coupled to the power storage device such that the solar panel charges the power storage device.

Abstract: Provided is a process including: receiving a tank-nearly-full message indicating that a tank at an oil or gas related facility is or will be ready for a truck to unload and transport fluid accumulating in the tank; in response to the tank-nearly-full message, creating a tank-run record; sending a description of the tank-run to a mobile device of a driver of an oilfield truck; receiving, from the mobile device of the driver of the oilfield truck, a tank-run claimed message indicating that the driver will drive to the oil or gas related facility and transport at least some of the fluid accumulating in the tank; and after the tank-run claimed message, performing steps including: confirming that the tank-run has not yet been claimed; after the confirmation, designating the tank-run as claimed by the driver; and sending confirmation to the mobile device of the driver.

Abstract: Methods, systems, and non-transitory computer readable storage media are disclosed for utilizing a multi-stroke neural network for modifying a digital image via a plurality of generated stroke parameters in a single pass of the neural network. Specifically, the disclosed system utilizes an encoder neural network to generate an encoding of a digital image. The disclosed system then utilizes a decoder neural network that generates a sequence of stroke parameters for digital drawing strokes from the encoding in a single pass of the encoder neural network and decoder neural network. Additionally, the disclosed system utilizes a renderer neural network to render the digital drawing strokes on a digital canvas according to the sequence of stroke parameters. In additional embodiments, the disclosed system utilizes a balance of loss functions to learn parameters of the multi-stroke neural network to generate stroke parameters according to various rendering styles.

Abstract: A generative neural network control system controls a generative neural network by modifying the intermediate latent space in the generative neural network. The generative neural network includes multiple layers each generating a set of activation values. An initial layer (and optionally additional layers) receives an input latent vector, and a final layer outputs an image generated based on the input latent vector. The data that is input to each layer (other than the initial layer) is referred to as data in an intermediate latent space. The data in the intermediate latent space includes activation values (e.g., generated by the previous layer or modified using various techniques) and optionally a latent vector. The generative neural network control system modifies the intermediate latent space to achieve various different effects when generating a new image.

Abstract: A target image is projected into a latent space of generative model by determining a latent vector by applying a gradient-free technique and a class vector by applying a gradient-based technique. An image is generated from the latent and class vectors, and a loss function is used to determine a loss between the target image and the generated image. This determining of the latent vector and the class vector, generating an image, and using the loss function is repeated until a loss condition is satisfied. In response to the loss condition being satisfied, the latent and class vectors that resulted in the loss condition being satisfied are identified as the final latent and class vectors, respectively. The final latent and class vectors are provided to the generative model and multiple weights of the generative model are adjusted to fine-tune the generative model.