Abstract: Disclosed are derivatives of icariin. Disclosed are compounds having Formula I-VIII as defined herein. Methods of using these compounds for the treatment of cancer and inflammation are also disclosed.

Abstract: The present invention concerns compounds, compositions containing these compounds, and methods of using these compounds and compositions as inhibitors of Stat3 signaling, Stat3 dimerization, Stat3-DNA binding, Stat5-DNA binding, and/or aberrant cell growth in vitro or in vivo, e.g., as anti-cancer agents for treatment of cancer, such as breast cancer. The compounds of the invention include, but are not limited to, NSC 74859 (S3I-201), NSC 42067, NSC 59263, NSC 75912, NSC 11421, NSC 91529, NSC 263435, and pharmaceutically acceptable salts and analogs of the foregoing. Other non-malignant diseases characterized by proliferation of cells that may be treated using the compounds of the invention, but are not limited to, cirrhosis of the liver; graft rejection; restenosis; and disorders characterized by a proliferation of T cells such as autoimmune diseases, e.g., type 1 diabetes, lupus and multiple sclerosis.

Abstract: Systems for dynamically controlling data transmissions are provided. In some examples, a system may receive data from one or more computer systems. Data associated with an event may be extracted and the extracted data may be compared to one or more machine learning datasets to determine a likelihood that an issue associated with a computer system may occur. The system may determine whether the likelihood is greater than a predetermined threshold. If so, a modification to avoid the potential issue or mitigate an impact may be identified. The modification may be transmitted to and executed by the computer system to modify one or more aspects of the computer system. In some examples, one or more efficiency modifications may be identified based on the comparison of the extracted data to the machine learning datasets. The identified efficiency modification may be transmitted to and executed by the computer system to modify one or more aspects of the computer system.

Abstract: A system, computer program product, and method are provided to automate a framework for knowledge graph based persistence of data, and to resolve temporal changes and uncertainties in the knowledge graph. Natural language understanding, together with one or more machine learning models (MLMs), is used to extract data from unstructured information, including entities and entity relationships. The extracted data is populated into a knowledge graph. As the KG is subject to change, the KG is used to create new and retrain existing machine learning models (MLMs). Weighting is applied to the populated data in the form of veracity value. Blockchain technology is applied to the populated data to ensure reliability of the data and to provide auditability to assess changes to the data.

Abstract: A method for authenticating to a network comprising a plurality of Internet of Things (“IoT”) devices is provided. The method may include using a mobile telephone apparatus, a wrist-worn apparatus and a head-worn apparatus to monitor the level of at least one of a wearer's pulse, body temperature, voice, gait and/or other biorhythmic indicator. One of the aforementioned apparatus may operate as a hub apparatus. The method may further include using the hub apparatus to assign a federated biometric marker based at least in part on the first, second and third biometric markers. The method may also include using artificial intelligence to monitor for one or more outliers with respect to historical monitoring. Each of the one or more outliers may include a magnitude that exceeds a security threshold difference between the current magnitude and the historically monitored magnitude.

Abstract: Disclosed are derivatives of icariin. Disclosed are compounds having Formula I-V as defined herein. Methods of using these compounds for the treatment of cancer and inflammation are also disclosed.

Abstract: A system, computer program product, and method are provided to automate a framework for knowledge graph based persistence of data, and to resolve temporal changes and uncertainties in the knowledge graph. Natural language understanding, together with one or more machine learning models (MLMs), is used to extract data from unstructured information, including entities and entity relationships. The extracted data is populated into a knowledge graph. As the KG is subject to change, the KG is used to create new and retrain existing machine learning models (MLMs). Weighting is applied to the populated data in the form of veracity value. Blockchain technology is applied to the populated data to ensure reliability of the data and to provide auditability to assess changes to the data.

Abstract: A method for authenticating to a network comprising a plurality of Internet of Things (“IoT”) devices is provided. The method may include using a mobile telephone apparatus, a wrist-worn apparatus and a head-worn apparatus to monitor the level of at least one of a wearer's pulse, body temperature, voice, gait and/or other biorhythmic indicator. One of the aforementioned apparatus may operate as a hub apparatus. The method may further include using the hub apparatus to assign a federated biometric marker based at least in part on the first, second and third biometric markers. The method may also include using artificial intelligence to monitor for one or more outliers with respect to historical monitoring. Each of the one or more outliers may include a magnitude that exceeds a security threshold difference between the current magnitude and the historically monitored magnitude.

Abstract: A system, computer program product, and method are provided to automate a framework for knowledge graph based persistence of data, and to resolve temporal changes and uncertainties in the knowledge graph. Natural language understanding, together with one or more machine learning models (MLMs), is used to extract data and a data relationship from structured and/or unstructured data, create an entry in the KG and selectively store the extracted data and data relationship in the KG, assign a veracity value to the stored data, create an asset value entry in a corresponding BC ledger, and store a BC identifier with the KG entry.

Abstract: The present approach relates to independently tracking individual progress of campaign-related activities part of a campaign respectively associated with a plurality of individuals. Embodiments disclosed herein include marking as complete a campaign-related activity in response to completion of the campaign-related activity by a first set of individuals, marking as incomplete an outstanding campaign-related activity in response to determining that a second set of individuals has not engaged with or completed the outstanding campaign-related activity, and then assigning subsequent campaign-related content to the individual based on whether the campaign-related activity was completed or not. For example, the second set of individuals who have not completed the campaign-related activity may each be sent a reminder notification, such as an email reminder, while the first set of individuals who have completed the campaign-related activity may receive a subsequent campaign-related content for completion.

Abstract: Methods, systems, and apparatuses for blockchain-based unexpected data detection are described herein. In some arrangements, a node within a decentralized peer-to-peer (e.g., P2P) network may receive a plurality of network function requests corresponding to the decentralized network. The node may analyze the plurality of network function requests to identify whether the requests included unexpected data and/or irregular data, and/or are associated with flagged wallets and/or smart contracts.

Abstract: The present invention relates to a process for recovering and purifying resveratrol produced by microbial fermentation. More particularly, the present invention relates to a process for recovering and purifying resveratrol produced by yeast fermentation.

Abstract: Methods, systems, and apparatuses for blockchain-based unexpected data detection are described herein. In some arrangements, a node within a decentralized peer-to-peer (e.g., P2P) network may receive a plurality of network function requests corresponding to the decentralized network. The node may analyze the plurality of network function requests to identify whether the requests included unexpected data and/or irregular data, and/or are associated with flagged wallets and/or smart contracts.

Abstract: Methods and systems for using block chain technology to verify transaction data are described herein. A computing platform may receive data about events related to transactions, personal or corporate information, supply chains, and other relevant information about a person or corporate entity. The event information may be received, aggregated, and processed to determine metadata about the person or corporate entity. The metadata may indicate, for example, a trustworthiness of the person or corporate entity for various purposes. Such event information and/or metadata may be stored as transactions in a block chain that may be accessible by counterparties to a potential transaction involving the person or corporate entity. The automated event processing computing platform may further use automated techniques to implement smart transactions between the person/entity and counterparty based on the trust metadata.

Abstract: Methods and systems for using block chain technology to verify transaction data are described herein. A computing platform may receive data about events related to transactions, personal or corporate information, supply chains, and other relevant information about a person or corporate entity. The event information may be received, aggregated, and processed to determine metadata about the person or corporate entity. The metadata may indicate, for example, a trustworthiness of the person or corporate entity for various purposes. Such event information and/or metadata may be stored as transactions in a block chain that may be accessible by counterparties to a potential transaction involving the person or corporate entity. The automated event processing computing platform may further use automated techniques to implement smart transactions between the person/entity and counterparty based on the trust metadata.

Abstract: A system, computer program product, and method are provided to automate a framework for knowledge graph based persistence of data, and to resolve temporal changes and uncertainties in the knowledge graph. Natural language understanding, together with one or more machine learning models (MLMs), is used to extract data from unstructured information, including entities and entity relationships. The extracted data is populated into a knowledge graph. As the KG is subject to change, the KG is used to create new and retrain existing machine learning models (MLMs). Weighting is applied to the populated data in the form of veracity value. Blockchain technology is applied to the populated data to ensure reliability of the data and to provide auditability to assess changes to the data.

Abstract: A method for authenticating to a network comprising a plurality of Internet of Things (“IoT”) devices is provided. The method may include using a mobile telephone apparatus, a wrist-worn apparatus and a head-worn apparatus to monitor the level of at least one of a wearer's pulse, body temperature, voice, gait and/or other biorhythmic indicator. One of the aforementioned apparatus may operate as a hub apparatus. The method may further include using the hub apparatus to assign a federated biometric marker based at least in part on the first, second and third biometric markers. The method may also include using artificial intelligence to monitor for one or more outliers with respect to historical monitoring. Each of the one or more outliers may include a magnitude that exceeds a security threshold difference between the current magnitude and the historically monitored magnitude.

Abstract: A system, computer program product, and method are provided to automate a framework for knowledge graph based persistence of data, and to resolve temporal changes and uncertainties in the knowledge graph. Natural language understanding, together with one or more machine learning models (MLMs), is used to extract data and a data relationship from structured and/or unstructured data, create an entry in the KG and selectively store the extracted data and data relationship in the KG, assign a veracity value to the stored data, create an asset value entry in a corresponding BC ledger, and store a BC identifier with the KG entry.

Abstract: A system, computer program product, and method are provided to automate a framework for knowledge graph based persistence of data, and to resolve temporal changes and uncertainties in the knowledge graph. Natural language understanding, together with one or more machine learning models (MLMs), is used to extract data from unstructured information, including entities and entity relationships. The extracted data is populated into a knowledge graph. As the KG is subject to change, the KG is used to create new and retrain existing machine learning models (MLMs). Weighting is applied to the populated data in the form of veracity value. Blockchain technology is applied to the populated data to ensure reliability of the data and to provide auditability to assess changes to the data.

Abstract: A system, computer program product, and method are provided to automate a framework for knowledge graph based persistence of data, and to resolve temporal changes and uncertainties in the knowledge graph. Natural language understanding, together with one or more machine learning models (MLMs), is used to extract data from unstructured information, including entities and entity relationships. The extracted data is populated into a knowledge graph. As the KG is subject to change, the KG is used to create new and retrain existing machine learning models (MLMs). Weighting is applied to the populated data in the form of veracity value. Blockchain technology is applied to the populated data to ensure reliability of the data and to provide auditability to assess changes to the data.