Abstract: Halogen-free, microporous polyolefin membranes are disclosed herein. The halogen-free, microporous polyolefin membranes can be manufactured using an environmentally friendly manufacturing process that includes extrusion of polymer-plasticizer mixtures followed by sheet formation and extraction of the plasticizer with a halogen-free solvent. The halogen-free solvent has a flashpoint greater than about 23° C. and an initial boiling point at least about 50° C. lower than the flashpoint of the plasticizer. The process can further be a closed loop process in which the halogen-free solvent can be reused.

Abstract: Systems and methods for integrating a gaming engine and a smart contract system in a platform are provided. The gaming engine is programmed with a software development environment and an architecture that provides a set of gaming engine services with predefined tools for digital content developers to create a set of game engine generated environments. The smart contract system programmed with smart contract services associated with transactions that are based on electronically verifiable conditions. The integration platform is programmed with an execution framework that is common to the gaming engine and to the smart contract system to integrate the smart contract services with at least one of the gaming engine and the set of game engine generated environments.

Abstract: A method for developing content for a personalized non-profit venue experience using a mobile computing device, comprising: providing an interface for management of a set of multimedia assets; receiving a mapping of multimedia assets to a set of locations on a site plan for the non-profit venue; receiving metadata for the set of multimedia assets; receiving personalized interest data indicating personal philanthropic interests of a visitor to the non-profit venue; and applying a machine learning algorithm to analyze the metadata and the personalized interest data to provide, to a mobile computing device, a selection of a multimedia asset from the set of multimedia assets for consumption by the visitor.

Abstract: An information technology platform for personalizing an experience of a visitor at a non-profit venue comprising: a network; a server in communication with the network; a mobile computing device to be carried by a visitor to a non-profit venue, wherein the platform determines personalized information about the visitor and a recommendation engine outputs a suggestion for a personalized experience to the visitor to encourage philanthropic activity related to an ongoing philanthropic campaign; and a machine learning system for learning on a training set of photographic data or video data, the learning to train the machine learning system to predict a sentiment towards the ongoing philanthropic campaign of the visitor based, at least in part, on photographic images or video images that are taken by the visitor, that are shared to the visitor, that are shared by the visitor or that include the visitor as a subject.

Abstract: An information technology platform for personalizing an experience of a visitor at a non-profit venue comprising: a network; a server in communication with the network; a mobile computing device to be carried by the visitor, the mobile computing device in communication with the server via the network, wherein the information technology platform determines personalized information about the visitor; a recommendation engine associated with the server, wherein the recommendation engine is to receive the personalized information about the visitor and to output a suggestion for a personalized experience for the visitor, wherein the information technology platform conveys the suggestion for the personalized experience to the visitor, wherein the personalized experience is to encourage philanthropic activity; and a social networking system for digital communication between the visitor and other visitors, and for sharing information or media related to the non-profit venue or to a philanthropic campaign associated wi

Abstract: An information technology platform for personalizing an experience of a visitor at a non-profit venue comprising: a network; a server in communication with the network; a mobile computing device to be carried by a visitor to a non-profit venue, wherein the platform determines personalized information about the visitor and a recommendation engine outputs a suggestion for a personalized experience to the visitor to encourage philanthropic activity related to an ongoing philanthropic campaign; and a machine learning system for learning on a training set of photographic data or video data, the learning to train the machine learning system to predict a sentiment towards the ongoing philanthropic campaign of the visitor based, at least in part, on photographic images or video images that are taken by the visitor, that are shared to the visitor, that are shared by the visitor or that include the visitor as a subject.

Abstract: Systems and methods for configuring and launching a marketplace are described. A method may include identifying an opportunity for a new marketplace, receiving marketplace opportunity data, determining configuration parameters, and determining a feasibility of implementing the new marketplace configuration. An architecture of the new marketplace may be determined, and marketplace objects configured. Data resources and their configuration in a model may be determined and the data resources connected to marketplace objects. The new marketplace may then be launched.

Abstract: A sensor kit and associated method configured for monitoring an industrial setting is disclosed. The sensor kit can include an edge device and a plurality of sensors that capture sensor data and transmit the sensor data via a self-configuring sensor kit network. At least one sensor can capture sensor measurements and output instances of sensor data, generate and output reporting packets, and transmit the reporting packets to the edge device via the self-configuring sensor kit network in accordance with a first communication protocol. The edge device receives reporting packets from the plurality of sensors via the self-configuring sensor kit network, generates a data block based on the sensor data, and transmits the data block to one or more node computing devices that collectively store a distributed ledger that is comprised of a plurality of data blocks.

Abstract: Systems and methods for configuring and launching a marketplace are described. A method may include identifying an opportunity for a new marketplace, receiving marketplace opportunity data, determining configuration parameters, and determining a feasibility of implementing the new marketplace configuration. An architecture of the new marketplace may be determined, and marketplace objects configured. Data resources and their configuration in a model may be determined and the data resources connected to marketplace objects. The new marketplace may then be launched.

Abstract: A method for monitoring an underwater industrial setting using a sensor kit having a plurality of sensors and an edge device can include receiving, by an edge processing system of the edge device, reporting packets from the plurality of sensors via a self-configuring sensor kit network. Each reporting packet can include routing data and one or more instances of sensor data. The method can further include performing one or more edge operations on the sensor data and generating one or more sensor kit packets based on the edge operations. The method can include transmitting the sensor kit packets to a backend system via a public network.

Abstract: A sensor kit that is configured for monitoring an industrial setting includes an edge device and a plurality of sensors that capture sensor data and transmit the sensor data via a self-configuring sensor kit network. At least one sensor can capture sensor measurements and output instances of sensor data, generate and output reporting packets, and transmit the reporting packets to the edge device via the self-configuring sensor kit network in accordance with a first communication protocol. The edge device receives reporting packets from the plurality of sensors via the self-configuring sensor kit network and transmits sensor kit packets to a backend system via a public network, wherein the sensor kit packets are based on a compressed block of media content frames indicative of the sensor data.

Abstract: Systems and associated methods for monitoring an industrial setting using sensor kits in communication with a backend system via a communication gateway are disclosed. Each sensor kit can have a set of sensors that are registered to respective industrial settings and configured to monitor physical characteristics of the industrial settings. The communication gateway can communicate instances of sensor values from the sensor kits to a backend system. The backend system can process the instances of sensor values to monitor the industrial setting, wherein upon receiving registration data for a sensor kit to an industrial setting, the backend system automatically configures and populates a dashboard for an owner or operator of the industrial setting, wherein the dashboard provides monitoring information that is based on the instances of sensor values for the industrial setting.

Abstract: A method for monitoring an industrial setting using a sensor kit having a plurality of sensors and an edge device including a processing system can include receiving, by the processing system, reporting packets from one or more respective sensors of the plurality of sensors, wherein each reporting packet includes routing data and one or more instances of sensor data; generating, by the processing system, a block of media content frames, wherein each media content frame includes a plurality of frame values, each frame value being indicative of a respective instance of sensor data; compressing, by the processing system, the block of media content frames using a media codec to obtain a compressed block; generating, by the processing system, one or more server kit packets based on the compressed block; and transmitting, by the processing system, the one or more server kit packets to a backend system via a public network.

Abstract: A system can include a backend system and a sensor kit configured to monitor an industrial setting. The sensor kit can include an edge device and a plurality of sensors that capture sensor data and transmit the sensor data via a self-configuring sensor kit network. At least one sensor can capture sensor measurements and output instances of sensor data, generate and output reporting packets, and transmit the reporting packets to the edge device via the self-configuring sensor kit network in accordance with a first communication protocol. The edge device receives reporting packets from the plurality of sensors via the self-configuring sensor kit network and transmits sensor kit packets to the backend system via a public network. The backend system can include a processing system and a storage system, where the processing system performs backend operations on the sensor data and the storage systems stores the sensor data.

Abstract: A system and associated method configured for monitoring an industrial setting is disclosed. The sensor kit can include an edge device and a plurality of sensors that capture sensor data and transmit the sensor data via a self-configuring sensor kit network. At least one sensor can capture sensor measurements and output instances of sensor data, generate and output reporting packets, and transmit the reporting packets to the edge device via the self-configuring sensor kit network in accordance with a first communication protocol. The edge device receives reporting packets from the plurality of sensors via the self-configuring sensor kit network, generates a data block based on the sensor data, and transmits the data block to one or more node computing devices that collectively store a distributed ledger that is comprised of a plurality of data blocks.

Abstract: An industrial plant operation management platform integrating a set of executive digital twins that take data from an intelligent data and networking pipeline to provide role-specific features, including AI-enabled expert agent features and enhanced collaboration features, and salient views of the entities and workflows of an industrial plant operation, thereby enabling executives to monitor and control entities and workflows to an unprecedented degree at appropriate levels of granularity and using familiar taxonomies and decision-making frameworks.

Abstract: A value chain system that provides recommendations for designing a logistics system generally includes a machine learning system that trains machine-learned models that output logistics design recommendations based on training data sets that each respectively defines one or more features of a respective logistic system and an outcome relating to the respective logistics system; an artificial intelligence system that receives a request for a logistics system design recommendation and determines the logistics system design recommendation based on one or more of the machine-learned models and the request; and a digital twin system that generates an environment digital twin of a logistics environment that incorporates the logistics system design recommendation, and one or more physical asset digital twins of physical assets. The digital twin system executes a simulation based on the logistics environment digital twin, the one or more physical asset digital twins.

Abstract: A value chain system that provides recommendations for designing a logistics system generally includes a machine learning system that trains machine-learned models that output logistics design recommendations based on training data sets that each respectively defines one or more features of a respective logistic system and an outcome relating to the respective logistics system; an artificial intelligence system that receives a request for a logistics system design recommendation and determines the logistics system design recommendation based on one or more of the machine-learned models and the request; and a digital twin system that generates an environment digital twin of a logistics environment that incorporates the logistics system design recommendation, and one or more physical asset digital twins of physical assets. The digital twin system executes a simulation based on the logistics environment digital twin, the one or more physical asset digital twins.

Abstract: A value chain system that provides recommendations for designing a logistics system generally includes a machine learning system that trains machine-learned models that output logistics design recommendations based on training data sets that each respectively defines one or more features of a respective logistic system and an outcome relating to the respective logistics system; an artificial intelligence system that receives a request for a logistics system design recommendation and determines the logistics system design recommendation based on one or more of the machine-learned models and the request; and a digital twin system that generates an environment digital twin of a logistics environment that incorporates the logistics system design recommendation, and one or more physical asset digital twins of physical assets. The digital twin system executes a simulation based on the logistics environment digital twin, the one or more physical asset digital twins.

Abstract: A value chain system that provides recommendations for designing a logistics system generally includes a machine learning system that trains machine-learned models that output logistics design recommendations based on training data sets that each respectively defines one or more features of a respective logistic system and an outcome relating to the respective logistics system; an artificial intelligence system that receives a request for a logistics system design recommendation and determines the logistics system design recommendation based on one or more of the machine-learned models and the request; and a digital twin system that generates an environment digital twin of a logistics environment that incorporates the logistics system design recommendation, and one or more physical asset digital twins of physical assets. The digital twin system executes a simulation based on the logistics environment digital twin, the one or more physical asset digital twins.