Abstract: An electrosurgical forceps includes first and second shaft members pivotably coupled to one another via a pivot member such that pivoting of the first and second shaft members between spaced-apart and approximated positions pivots jaw members thereof between open and closed positions. A knife is translatable between retracted and extended positions. A knife deployment mechanism is operably coupled to the first shaft member and includes at least one trigger and at least one linkage coupling the at least one trigger with the knife such that pivoting of the at least one trigger relative to the first shaft member translates the knife between the retracted and extended positions. A knife lockout biased towards a locked position inhibits distal translation of the knife. The knife lockout is movable from the locked position to an unlocked position upon approximation of the jaw members to permit distal translation of the knife.

Abstract: A surface cleaning apparatus includes a recovery tank, a suction nozzle in fluid communication with the recovery tank, and a suction source in fluid communication with the suction nozzle and the recovery tank to generate a working air path to transport debris-containing fluid including air and liquid from the suction nozzle into the recovery tank. An air/liquid separator can be provided within the recovery tank for separating liquid from air in the debris-containing fluid.

Abstract: A knife configured for use with an electrosurgical forceps having curved jaw members and a method of manufacturing the same. The knife includes a distal body having an inner side and an outer side, a first etching on the outer side of the distal body defining a distal cutting edge and a second etching on the outer side of the distal body extending along a portion of a length of the distal body to define relatively protruded and relatively recessed surfaces extending along a portion of the length of the distal body on the outer side thereof.

Abstract: Security and access control is provided for sensor devices, the data captured by sensor devices, and the results of processing and analyzing that data. In one aspect, SceneData related to a Scene is requested from a sensor-side technology stack and at least some of the SceneData is secured, for example by encryption. Different SceneData can be secured separately and at different levels of security, thus providing fine-grained security of the SceneData. In yet another aspect, data security is implemented by a separate privacy management system. In yet another aspect, sensor devices themselves are secured against external network threats. The sensor device includes an execution environment and a separate network management layer that secures the execution environment against threats from the external network. In one implementation, the sensor device is partitioned into a trusted region and a non-trusted region, and the network security stack is implemented in the trusted region.

Abstract: An organic light emitting diode (OLED) display includes a pixelated OLED display panel and a color-correction component disposed on the pixelated OLED display panel. The pixelated OLED display panel has a ratio of blue-to-red color mixing weights at 30 degrees of ?030, and a ratio of blue-to-red color mixing weights at 45 degrees of ?045, where ?045??030?1.05 and 1.5??045?1.1. The color-correction component is configured such that a ratio of blue-to-red color mixing weights at 45 degrees of the display is ?45 and a ratio of blue-to-red color mixing weights at 30 degrees of the display is ?30, where ?045?0.1??45?2.1??045 and ?030?0.05??30?2.05??030. Methods of making OLED displays are described.

Abstract: Compositions and methods are provided for making rat pluripotent and totipotent cells, including rat embryonic stem (ES) cells. Compositions and methods for improving efficiency or frequency of germline transmission of genetic modifications in rats are provided. Such methods and compositions comprise an in vitro culture comprising a feeder cell layer and a population of rat ES cells or a rat ES cell line, wherein the in vitro culture conditions maintain pluripotency of the ES cell and comprises a media having mouse leukemia inhibitory factor (LIF) or an active variant or fragment thereof. Various methods of establishing such rat ES cell lines are further provided. Methods of selecting genetically modified rat ES cells are also provided, along with various methods to generate a transgenic rat from the genetically modified rat ES cells provided herein. Various kits and articles of manufacture are further provided.

Abstract: A surface cleaning apparatus includes a recovery tank, a suction nozzle in fluid communication with the recovery tank, and a suction source in fluid communication with the suction nozzle and the recovery tank to generate a working air path to transport debris-containing fluid including air and liquid from the suction nozzle into the recovery tank. An air/liquid separator can be provided within the recovery tank for separating liquid from air in the debris-containing fluid.

Abstract: Compositions and methods are provided for modifying a rat genomic locus of interest using a large targeting vector (LTVEC) comprising various endogenous or exogenous nucleic acid sequences as described herein. Compositions and methods for generating a genetically modified rat comprising one or more targeted genetic modifications in their germline are also provided. Compositions and methods are provided which comprise a genetically modified rat or rat cell comprising a targeted genetic modification in the rat interleukin-2 receptor gamma locus, the rat ApoE locus, the rat Rag2 locus, the rat Rag1 locus and/or the rat Rag2/Rag1 locus. The various methods and compositions provided herein allows for these modified loci to be transmitted through the germline.

Abstract: An approach to sensor data is based on scenes. One aspect concerns a computer-implemented method for specifying and obtaining a variety of sensor data and processed sensor data related to a scene. The method incorporates a Scene-based API that uses SceneModes and SceneData. An application requesting sensor data communicates a SceneMode to a group of one or more sensor devices and/or sensor modules via the Scene-based API. The SceneMode determines the SceneData to be captured or provided by the sensor group, which typically includes different types of sensor data related to the Scene and also further processed or analyzed data. The application receives the SceneData from the sensor group via the Scene-based API, with the SceneData organized into SceneShots which are samples of the Scene.

Abstract: A multi-layer technology stack includes a sensor layer including image sensors, a device layer, and a cloud layer, with interfaces between the layers. A method to curate different custom workflows for multiple applications include the following. Requirements for custom sets of data packages for the applications is received. The custom set of data packages include sensor data packages (e.g., SceneData) and contextual metadata packages that contextualize the sensor data packages (e.g., SceneMarks). Based on the received requirements and capabilities of components in the technology stack, the custom workflow for that application is deployed. This includes a selection, configuration and linking of components from the technology stack. The custom workflow is implemented in the components of the technology stack by transmitting workflow control packages directly and/or indirectly via the interfaces to the different layers.

Abstract: A multi-layer technology stack includes a sensor layer including image sensors, a device layer, and a cloud layer, with interfaces between the layers. A method to curate different custom workflows for multiple applications include the following. Requirements for custom sets of data packages for the applications is received. The custom set of data packages include sensor data packages (e.g., SceneData) and contextual metadata packages that contextualize the sensor data packages (e.g., SceneMarks). Based on the received requirements and capabilities of components in the technology stack, the custom workflow for that application is deployed. This includes a selection, configuration and linking of components from the technology stack. The custom workflow is implemented in the components of the technology stack by transmitting workflow control packages directly and/or indirectly via the interfaces to the different layers.

Abstract: A multi-layer technology stack includes a sensor layer including image sensors, a device layer, and a cloud layer, with interfaces between the layers. A method to curate different custom workflows for multiple applications include the following. Requirements for custom sets of data packages for the applications is received. The custom set of data packages include sensor data packages (e.g., SceneData) and contextual metadata packages that contextualize the sensor data packages (e.g., SceneMarks). Based on the received requirements and capabilities of components in the technology stack, the custom workflow for that application is deployed. This includes a selection, configuration and linking of components from the technology stack. The custom workflow is implemented in the components of the technology stack by transmitting workflow control packages directly and/or indirectly via the interfaces to the different layers.

Abstract: An approach to sensor data is based on scenes. One aspect concerns a computer-implemented method for specifying and obtaining a variety of sensor data and processed sensor data related to a scene. The method incorporates a Scene-based API that uses SceneModes and SceneData. An application requesting sensor data communicates a SceneMode to a group of one or more sensor devices and/or sensor modules via the Scene-based API. The SceneMode determines the SceneData to be captured or provided by the sensor group, which typically includes different types of sensor data related to the Scene and also further processed or analyzed data. The application receives the SceneData from the sensor group via the Scene-based API, with the SceneData organized into SceneShots which are samples of the Scene.

Abstract: Security and access control is provided for sensor devices, the data captured by sensor devices, and the results of processing and analyzing that data. In one aspect, SceneData related to a Scene is requested from a sensor-side technology stack and at least some of the SceneData is secured, for example by encryption. Different SceneData can be secured separately and at different levels of security, thus providing fine-grained security of the SceneData. In yet another aspect, data security is implemented by a separate privacy management system. In yet another aspect, sensor devices themselves are secured against external network threats. The sensor device includes an execution environment and a separate network management layer that secures the execution environment against threats from the external network. In one implementation, the sensor device is partitioned into a trusted region and a non-trusted region, and the network security stack is implemented in the trusted region.

Abstract: An approach to sensor data is based on scenes. One aspect concerns a computer-implemented method for specifying and obtaining a variety of sensor data and processed sensor data related to a scene. The method incorporates a Scene-based API that uses SceneModes and SceneData. An application requesting sensor data communicates a SceneMode to a group of one or more sensor devices and/or sensor modules via the Scene-based API. The SceneMode determines the SceneData to be captured or provided by the sensor group, which typically includes different types of sensor data related to the Scene and also further processed or analyzed data. The application receives the SceneData from the sensor group via the Scene-based API, with the SceneData organized into SceneShots which are samples of the Scene.

Abstract: Automated discovery of the relative positioning of a network of cameras that view a physical environment. The automated discovery is based on comparing TimeLines for the cameras. The TimeLines are time-stamped data relating to the camera's view, for example a sequence of time stamps and corresponding images captured by a camera at those time stamps. In one approach, the relative positioning is represented by a proximity graph of nodes connected by edges. The nodes represent spaces in the physical environment, and each edge between two nodes represents a pathway between the spaces represented by the two nodes.

Abstract: Security and access control is provided for sensor devices, the data captured by sensor devices, and the results of processing and analyzing that data. In one aspect, SceneData related to a Scene is requested from a sensor-side technology stack and at least some of the SceneData is secured, for example by encryption. Different SceneData can be secured separately and at different levels of security, thus providing fine-grained security of the SceneData. In yet another aspect, data security is implemented by a separate privacy management system. In yet another aspect, sensor devices themselves are secured against external network threats. The sensor device includes an execution environment and a separate network management layer that secures the execution environment against threats from the external network. In one implementation, the sensor device is partitioned into a trusted region and a non-trusted region, and the network security stack is implemented in the trusted region.

Abstract: The present disclosure overcomes the limitations of the prior art by providing approaches to marking points of interest in scenes. In one aspect, a Scene of interest is identified based on SceneData provided by a sensor-side technology stack that includes a group of one or more sensor devices. The SceneData is based on a plurality of different types of sensor data captured by the sensor group, and typically requires additional processing and/or analysis of the captured sensor data. A SceneMark marks the Scene of interest or possibly a point of interest within the Scene.

Abstract: A multi-layer technology stack includes a sensor layer including image sensors, a device layer, and a cloud layer, with interfaces between the layers. Each layer contains multiple nodes. A method to develop contextual understanding of related events detected by the nodes includes the following. Sensor nodes capture sensor data, including multiple image sensors capturing images. Various nodes receive sensor data and/or metadata packages from other nodes, analyze the received data for events, and generate and/or augment metadata packages describing the detected events. The analysis includes image understanding. Events that are related are identified, based on the metadata packages describing the events. A contextual understanding of the related events is developed, based on analysis of the metadata packages describing the events.

Abstract: Automated discovery of the relative positioning of a network of cameras that view a physical environment. The automated discovery is based on comparing TimeLines for the cameras. The TimeLines are time-stamped data relating to the camera's view, for example a sequence of time stamps and corresponding images captured by a camera at those time stamps. In one approach, the relative positioning is represented by a proximity graph of nodes connected by edges. The nodes represent spaces in the physical environment, and each edge between two nodes represents a pathway between the spaces represented by the two nodes.