Abstract: Disclosed herein are methods and compositions useful for the treatment of Autism Spectrum Disorder (ASD). The methods and compositions include combination therapy with probiotics and oxytocin (OXT), resulting in a therapeutic synergy that exerts beneficial effects on ASD symptoms. The methods and compositions provide improvements in several measurable parameters including but not limited to: measured clinical index for ASD core symptoms, gut microbiome profile, and levels of OXT and inflammatory markers in the blood.

Abstract: Embodiments are directed to security analysis agents. Events associated with a computing environment may be provided. Prompt fragments may be determined based on the events. A prompt may be generated for a large language model (LLM) based on a prompt template and the prompt fragments such that the prompt fragments may be included in the prompt and provided to the LLM. Actions for evaluating the events may be determined based on the LLM response. These actions may be executed to evaluate the events. Portions of the response that correspond to the prompt fragments may be determined. A performance score may be determined for each prompt fragment based on its corresponding portion of the response such that the prompt may be modified to exclude a portion of the prompt fragments that have a performance score less than a threshold value.

Abstract: A lubricator control system includes a lubricator, an Internet-of-things platform, and an application server. The lubricator is configured to communicate with the application server in a long-distance and low-power consumption wireless communication mode, the lubricator is configured to communicate with the Internet-of-things platform via 5G-NB-IoT communication and to send target information to the Internet-of-things platform in the long-distance and low-power consumption wireless communication mode, and the Internet-of-things platform is configured to send the target information to the application server. In addition, the application server is configured to receive the target information and to send corresponding target response information to the Internet-of-things platform, and the Internet-of-things platform is configured to send the target response information to the lubricator via 5G-NB-IoT communication in the long-distance and low-power consumption wireless communication mode.

Abstract: Disclosed herein are methods and compositions useful for the treatment of subjects suffering from Prader-Willi Syndrome (PWS). The methods include administering compositions comprising probiotics, such as Lactobacillus reuteri (L. reuteri) and Bifidobacterium animalis subsp. lactis (B. lactis) to subjects in need thereof.

Abstract: A lubricator control method includes reading current configuration information including periodic oil filling time and periodic reporting time, controlling a lubricator to wake up from a sleep state to perform an oil filling task when the periodic oil filling time is reached, controlling the lubricator to switch to the sleep state after the oil filling task ends normally or an abnormal alarm is provided, controlling the lubricator to wake up from the sleep state to perform a data reporting task through a wireless network when the periodic reporting time is reached, controlling the lubricator to switch to the sleep state after the data reporting task is completed.

Abstract: A lubricator control system includes a lubricator, a LoRa gateway, an Internet of Things platform and an application server. The lubricator is configured to communicate with the application server in a long-distance and low-power consumption wireless communication mode and to communicate with the Internet of Things platform based on a LoRaWan communication protocol and to send target information to the LoRa gateway. The LoRa gateway is configured to forward the target information to the Internet of Things platform, and the Internet of Things platform is configured to send the target information to the application server. The application server is configured to receive the target information and to send corresponding target response information to the Internet of Things platform. The Internet of Things platform is configured to send the target response information to the LoRa gateway, and the LoRa gateway is configured to forward the target response information to the lubricator.

Abstract: Embodiments are directed monitoring network traffic using network monitoring computers. Activity associated with a document in a network may be determined based on the network traffic. A profile may be generated based on a summarization of the activity associated with the document such that the profile may be stored in a data store that stores other profiles. Similar profiles may be determined based on a classification of each profile in the data store based on similarities between the profile and the other profiles in the data store. In response to determining similar profiles, locations in the network associated with documents that correspond to the similar profiles may be determined. Locations may be classified based on the activity, the similar profiles and access policies. In response to portions of the locations being classified as inconsistent with the access policies may be reported.

Abstract: Embodiments are directed monitoring network traffic using network monitoring computers. Activity associated with a document in a network may be determined based on the network traffic. A profile may be generated based on a summarization of the activity associated with the document such that the profile may be stored in a data store that stores other profiles. Similar profiles may be determined based on a classification of each profile in the data store based on similarities between the profile and the other profiles in the data store. In response to determining similar profiles, locations in the network associated with documents that correspond to the similar profiles may be determined. Locations may be classified based on the activity, the similar profiles and access policies. In response to portions of the locations being classified as inconsistent with the access policies may be reported.

Abstract: Embodiments are directed to monitoring network traffic using network monitoring computers (NMCs). NMCs may determine requests provided to a server based on a first portion of network traffic. NMCs may determine suspicious requests based on characteristics of the provided requests. NMCs may employ the characteristics of the suspicious requests to provide correlation information that is associated with the suspicious requests. NMCs may determine dependent actions associated with the server based on a second portion of the network traffic and the correlation information. And, in response to determining anomalous activity associated with the evaluation of the dependent actions, NMCs may provide reports associated with the anomalous activity.

Abstract: Embodiments are directed to monitoring network traffic using network monitoring computers (NMCs). Two or more network segments coupled by a traffic forwarding device (TFD) may be monitored. External network addresses and internal network addresses may be determined based on encrypted network traffic exchanged between external endpoints and the TFD and internal network traffic exchanged between internal endpoints and the TFD. Metrics associated with the external network addresses or the internal network addresses may be determined based on the monitoring. Correlation scores may be provided for the external network addresses and the internal network addresses based on of a correlation model, the metrics, or the other metrics. If a correlation score associated with an external network address and an internal network address exceeds a threshold value, the external network address and the internal network address may be associated with each other based on the correlation score.

Abstract: Embodiments are directed to monitoring network traffic using network monitoring computers (NMCs). Networks may be configured to protect servers using centralized security protocols. Centralized security protocols may depend on centralized control provided by authentication control servers. If a client intends to access protected servers it may communicate with the authentication control server to obtain keys that enable it to access the requested servers. NMCs may monitor network traffic the centralized security protocol to collect metrics associated with the control servers, clients, or resource servers.

Abstract: Embodiments are directed to monitoring network traffic using network monitoring computers (NMCs). Metrics may be determined based on monitoring network traffic associated with a plurality of entities each associated with a profile that includes the metrics for each entity. Beaconing metrics associated with beaconing activity may be determined based on the metrics. The profile of each entity may be compared with the beaconing metrics to determine the entities that may be engaged in beaconing activity. The entities may be characterized based on beaconing activity such that the beaconing activity includes communication with endpoints associated with the third parties, employing communication protocols associated with the third-parties, or exchanging payloads consistent with the beaconing activity. Reports that include information associated with the entities and its beaconing activity may be generated.

Abstract: Embodiments are directed to monitoring network traffic using a monitoring engine that monitors network traffic in networks to provide metrics. An inference engine may provide activity profiles based on portions of the network traffic where each activity profile includes features associated with the portions of network traffic. The inference engine may determine other activity profiles correlated with the activity profiles based on correlation models such that the determination of the other activity profiles occurs prior to monitoring an occurrence of other portions of the network traffic. The inference engine may modify monitoring actions of the monitoring engine based on the other activity profiles. The inference engine may provide reports based on the portions of the network traffic, the activity profiles, the other portions of the network traffic, or the other activity profiles.

Abstract: Embodiments are directed to monitoring network traffic using network monitoring computers (NMCs). Two or more network segments coupled by a traffic forwarding device (TFD) may be monitored. External network addresses and internal network addresses may be determined based on encrypted network traffic exchanged between external endpoints and the TFD and internal network traffic exchanged between internal endpoints and the TFD. Metrics associated with the external network addresses or the internal network addresses may be determined based on the monitoring. Correlation scores may be provided for the external network addresses and the internal network addresses based on of a correlation model, the metrics, or the other metrics. If a correlation score associated with an external network address and an internal network address exceeds a threshold value, the external network address and the internal network address may be associated with each other based on the correlation score.

Abstract: Embodiments are directed to monitoring network traffic using network monitoring computers (NMCs). Networks may be configured to protect servers using centralized security protocols. Centralized security protocols may depend on centralized control provided by authentication control servers. If a client intends to access protected servers it may communicate with the authentication control server to obtain keys that enable it to access the requested servers. NMCs may monitor network traffic the centralized security protocol to collect metrics associated with the control servers, clients, or resource servers.

Abstract: Embodiments are directed to monitoring network traffic. A monitoring engine may monitor network traffic associated with a plurality of entities in networks to provide metrics. And provide a device relation model based on the plurality of entities, the network traffic, and the metrics. An inference engine may associate each entity in the plurality of entities with an importance score based on the device relation model and the metrics such that each importance score is associated with a significance of an entity to operations of the networks. An alert engine may generate a plurality of alerts associated with the plurality of entities based on the metrics. And provide one or more alerts from the plurality of alerts to one or more users based on one or more ranked importance scores associated with one or more entities.

Abstract: Embodiments are directed to monitoring network traffic to determine users and assets based on the network traffic. A user role model may assign a user role and provide a role confidence score for the users based on network traffic associated with the users. An asset model may assign an asset type and provide an asset confidence score the assets based on network traffic associated with the assets. The users may be associated with assets based on the network traffic. The role confidence scores provided for the users may be modified based on the asset type assigned to assets associated with the users. The asset confidence score provided for the assets may be modified based on the user role assigned to the users associated with the assets. A report that includes information about the user roles and the asset types may be provided.

Abstract: Embodiments are directed to monitoring network traffic using network monitoring computers (NMCs). Two or more network segments coupled by bridge devices may be monitored by NMCs. The bridge devices may modify network traffic passed from one network segment to another network segment. Flows in network segments may be determined based on monitored network traffic associated with the network segments. Other flows in other network segments may be determined based on other monitored network traffic associated with the other network segments. A correlation score for two or more flows in different network segments may be provided based on a correlation model. Two or more related flows may be determined based on a value of the correlation score of the two or more related flows located in different network segments. A report that includes information about the two or more related flows may be provided.

Abstract: Embodiments are directed to monitoring network traffic using network monitoring computers (NMCs). Networks may be configured to protect servers using centralized security protocols. Centralized security protocols may depend on centralized control provided by authentication control servers. If a client intends to access protected servers it may communicate with the authentication control server to obtain keys that enable it to access the requested servers. NMCs may monitor network traffic the centralized security protocol to collect metrics associated with the control servers, clients, or resource servers.