Abstract: Isolated Rhodococcus ruber, a product derived from the Rhodococcus ruber (in particular, a product derived from the Rhodococcus ruber cell wall), a method for preparing the product derived from the Rhodococcus ruber, and use of the product derived from the Rhodococcus ruber in prevention and/or treatment of lichen planus. The product derived from the Rhodococcus ruber effectively reduce the erosion area of lichen planus and relieve pain.

Abstract: Isolated Rhodococcus ruber, a product derived from the Rhodococcus ruber (in particular, a product derived from the Rhodococcus ruber cell wall), a method for preparing the product derived from the Rhodococcus ruber, and use of the product derived from the Rhodococcus ruber in prevention and/or treatment of lichen planus. The product derived from the Rhodococcus ruber effectively reduce the erosion area of lichen planus and relieve pain.

Abstract: Disclosed is a use of a cell wall skeleton of isolated Rhodococcus ruber or a composition containing the same for preparing a human papillomavirus infection treatment drug. The cell wall skeleton of Rhodococcus ruber isolated from Rhodococcus ruber was stored and preserved at China General Microbiological Culture Collection Center, No. 1, West Beichen Road, Chaoyang District, Beijing on Mar. 22, 2019 with accession number CGMCC 17431.

Abstract: A use of a cell wall or a cell wall skeleton of Rhodococcus ruber in preparing a drug for treating a thermal injury. The thermal injury comprises a burn, a scald and a chemical burn. Applying the Rhodococcus ruber product to a subject has a good therapeutic effect on a thermal injury and has no side effects.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed to improve feature engineering efficiency. An example method disclosed herein includes retrieving a log file in a first file format, the log file containing feature occurrence data, generating a first unit operation based on the first file format to extract the feature occurrence data from the log file to a string, the first unit operation associated with a first metadata tag, generating second unit operations to identify respective features from the feature occurrence data, the second unit operations associated with respective second metadata tags, and generating a first sequence of the first metadata tag and the second metadata tags to create a first vector output file of the feature occurrence data.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed to facilitate electronic data security. An example apparatus includes a data storage including a memory adjusted to store data organized according to a data table including columns identifying a first data record and a first security tag associated with the first data record. In the example apparatus, retrieval of data from the data storage involves a bit operation comparing the first security tag with a first privilege tag. In the example apparatus, the data storage provides the first data record when the bit operation comparing the first security tag with the first privilege tag has a non-zero result, and the data storage does not provide the first data record when the bit operation comparing the first security tag with the first privilege tag has a zero result.

Abstract: A malicious object detection system for use in managed runtime environments includes a check circuit to receive call information generated by an application, such as an Android application. A machine learning circuit coupled to the check circuit applies a machine learning model to assess the information and/or data included in the call and detect the presence of a malicious object, such as malware or a virus, in the application generating the call. The machine learning model may include a global machine learning model distributed across a number of devices, a local machine learning model based on use patterns of a particular device, or combinations thereof. A graphical user interface management circuit halts execution of applications containing malicious objects and generates a user perceptible output.

Abstract: Technology for switching from a wireless local area network (WLAN) to a wireless wide area network (WWAN) is disclosed. A multi-radio access technology (multi-RAT) user equipment (UE) can receive WLAN-specific dedicated physical random access channel (PRACH) allocation information from an evolved node B (eNB) to enable the multi-RAT UE to perform an inter-RAT WLAN-to-WWAN handover. The multi-RAT UE can initiate the inter-RAT WLAN-to-WWAN handover at the multi-RAT UE by performing random access with the eNB using the WLAN-specific dedicated PRACH allocation information.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed to improve feature engineering efficiency.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed to facilitate electronic data security. An example apparatus includes a data storage including a memory adjusted to store data organized according to a data table including columns identifying a first data record and a first security tag associated with the first data record. In the example apparatus, retrieval of data from the data storage involves a bit operation comparing the first security tag with a first privilege tag. In the example apparatus, the data storage provides the first data record when the bit operation comparing the first security tag with the first privilege tag has a non-zero result, and the data storage does not provide the first data record when the bit operation comparing the first security tag with the first privilege tag has a zero result.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed to improve feature engineering efficiency. An example method disclosed herein includes retrieving a log file in a first file format, the log file containing feature occurrence data, generating a first unit operation based on the first file format to extract the feature occurrence data from the log file to a string, the first unit operation associated with a first metadata tag, generating second unit operations to identify respective features from the feature occurrence data, the second unit operations associated with respective second metadata tags, and generating a first sequence of the first metadata tag and the second metadata tags to create a first vector output file of the feature occurrence data.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed to improve feature engineering efficiency.

Abstract: A malicious object detection system for use in managed runtime environments includes a check circuit to receive call information generated by an application, such as an Android application. A machine learning circuit coupled to the check circuit applies a machine learning model to assess the information and/or data included in the call and detect the presence of a malicious object, such as malware or a virus, in the application generating the call. The machine learning model may include a global machine learning model distributed across a number of devices, a local machine learning model based on use patterns of a particular device, or combinations thereof. A graphical user interface management circuit halts execution of applications containing malicious objects and generates a user perceptible output.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed to facilitate electronic data security. An example apparatus includes a data storage including a memory adjusted to store data organized according to a data table including columns identifying a first data record and a first security tag associated with the first data record. In the example apparatus, retrieval of data from the data storage involves a bit operation comparing the first security tag with a first privilege tag. In the example apparatus, the data storage provides the first data record when the bit operation comparing the first security tag with the first privilege tag has a non-zero result, and the data storage does not provide the first data record when the bit operation comparing the first security tag with the first privilege tag has a zero result.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed to improve feature engineering efficiency. An example method disclosed herein includes retrieving a log file in a first file format, the log file containing feature occurrence data, generating a first unit operation based on the first file format to extract the feature occurrence data from the log file to a string, the first unit operation associated with a first metadata tag, generating second unit operations to identify respective features from the feature occurrence data, the second unit operations associated with respective second metadata tags, and generating a first sequence of the first metadata tag and the second metadata tags to create a first vector output file of the feature occurrence data.

Abstract: A malicious object detection system for use in managed runtime environments includes a check circuit to receive call information generated by an application, such as an Android application. A machine learning circuit coupled to the check circuit applies a machine learning model to assess the information and/or data included in the call and detect the presence of a malicious object, such as malware or a virus, in the application generating the call. The machine learning model may include a global machine learning model distributed across a number of devices, a local machine learning model based on use patterns of a particular device, or combinations thereof. A graphical user interface management circuit halts execution of applications containing malicious objects and generates a user perceptible output.

Abstract: Systems and methods to support intra-application flow prioritization are disclosed herein. User equipment (UE) may be configured to communicatively couple to an Evolved Universal Terrestrial Radio Access Network (E-UTRAN) Node B (eNB). The eNB may transmit packets from the UE to an evolved packet core (EPC), which may transmit schedule packets to an application function (AF) via a network. The AF may provide classification information and prioritization information for a plurality of intra-application flows transmitted between the AF and the UE. The EPC may classify uplink and/or downlink traffic into the intra-application flows and mark and/or schedule the traffic based on the prioritization information. Absolute and/or modular length, payload values, and/or packet type may be used to classify the traffic into the intra-application flows.

Abstract: Technology for switching from a wireless local area network (WLAN) to a wireless wide area network (WWAN) is disclosed. A multi-radio access technology (multi-RAT) user equipment (UE) can receive WLAN-specific dedicated physical random access channel (PRACH) allocation information from an evolved node B (eNB) to enable the multi-RAT UE to perform an inter-RAT WLAN-to-WWAN handover. The multi-RAT UE can initiate the inter-RAT WLAN-to-WWAN handover at the multi-RAT UE by performing random access with the eNB using the WLAN-specific dedicated PRACH allocation information.

Abstract: A malicious object detection system for use in managed runtime environments includes a check circuit to receive call information generated by an application, such as an Android application. A machine learning circuit coupled to the check circuit applies a machine learning model to assess the information and/or data included in the call and detect the presence of a malicious object, such as malware or a virus, in the application generating the call. The machine learning model may include a global machine learning model distributed across a number of devices, a local machine learning model based on use patterns of a particular device, or combinations thereof. A graphical user interface management circuit halts execution of applications containing malicious objects and generates a user perceptible output.

Abstract: Systems and methods to support intra-application flow prioritization are disclosed herein. User equipment (UE) may be configured to communicatively couple to an Evolved Universal Terrestrial Radio Access Network (E-UTRAN) Node B (eNB). The eNB may transmit packets from the UE to an evolved packet core (EPC), which may transmit schedule packets to an application function (AF) via a network. The AF may provide classification information and prioritization information for a plurality of intra-application flows transmitted between the AF and the UE. The EPC may classify uplink and/or downlink traffic into the intra-application flows and mark and/or schedule the traffic based on the prioritization information. Absolute and/or modular length, payload values, and/or packet type may be used to classify the traffic into the intra-application flows.