Abstract: Disclosed are integrated systems and methods that utilize a network of DFOS sensors installed on power lines, communication networks, and transportation systems, which continuously monitor infrastructures and provide real-time data. This data is collected, processed, and analyzed, and used to identify any affected areas of infrastructure and assess severity of any damage. Prioritization and resource allocation is performed and uses this analysis to prioritize restoration efforts and allocate resources such as repair crews, equipment, and materials to areas with a highest priority.

Abstract: Wireless communications systems and methods related to communicating control information are provided. A method of wireless communication performed by a first sidelink user equipment (UE) may include transmitting, to a second sidelink UE, a first sidelink synchronization block (S-SSB) in a scheduled S-SSB slot, performing a first listen-before-talk (LBT) procedure in an unlicensed frequency band, and transmitting, to the second sidelink UE, a second S-SSB in a slot before a next scheduled S-SSB slot based on the first LBT procedure being unsuccessful.

Abstract: Methods and systems for acoustic sensing include determining sensing locations along a fiber to generate a beam pattern that is directed to an acoustic source. An optical pulse is transmitted on the fiber. Optical phase of backscattering light is measured from the sensing locations on the fiber. An output signal is generated by combining the measured optical phase according to the beam pattern.

Abstract: Disclosed are integrated systems and operating methods that provide an integrated security system for substation monitoring and detection that effectively combines the strengths of distributed acoustic sensing, drones, and security cameras for comprehensive protection. The integrated system comprises a DAS system configured to monitor vibrations and acoustic signals along the length of fiber optic cables, one or more drones equipped with advanced sensors for aerial surveillance, and a plurality of security cameras installed throughout the substation to capture real-time video feeds and provide visual confirmation of activities. A central control system integrates and analyzes data from the DAS system, drones, and security cameras, and utilizes a novel, advanced algorithm, named Substation Security Analytics (SSA), specifically designed for the unique challenges associated with substation security monitoring and detection.

Abstract: Methods and systems for anomaly detection include measuring time-series data about a system using an optical sensing system. The time-series data is adapted to natural language data. One or more anomaly detection models are selected based on the natural language data and a task. An anomaly is detected in the system using the selected one or more anomaly detection models. A corrective action is performed responsive to the anomaly.

Abstract: Systems and methods include collecting vibration data along an optical fiber cable using distributed acoustic sensing (DAS). The collected vibration data is preprocessed to separate the vibration data into at least two mixtures. The at least two mixtures are combined into a mixture of mixtures. The mixture of mixtures is separated into a plurality of estimated source signals using a separation model. The separation model is trained using an unsupervised loss computed between the estimated source signals and the at least two mixtures.

Abstract: Systems and methods include calibrating physical parameters of acoustic data using a deterministic model related to hardware configurations that generated the acoustic data to provide an intermediate layer of data. The intermediate layer of data is then calibrated using environmental factors related to the acoustic data by employing machine learning to provide a multichannel data output. A loss is optimized between the multichannel data output and multichannel distributed-optic fiber sensing (DFOS) data to train a hybrid transfer model to translate between DFOS data and acoustic data.

Abstract: Disclosed are systems and methods directed to a frequency analysis approach to transformer status monitoring using distributed fiber optic sensing to monitor a phase delay of a 120 Hz vibrational signal and determining an angular difference between a designated point and a reference point. Operationally, systems and methods according to aspects of the present disclosure identify phase delay patterns of a single transformer from its vibrational humming and combined vibrational signals of multiple transformers.

Abstract: Systems and methods for a risk mitigation system for electrical power grids. To mitigate risks such as natural destructive forces, collected risk data and EPG data can be fused to obtain fused data. The vulnerability metric and fragility metric of the EPG based on risk profiles generated from the fused data can be predicted with a physics-informed neural network (PINN) trained with the fused data. EPG threat metrics can be developed by integrating the vulnerability metric, fragility metric, and the risk profiles into an integrated score that determines the probability of failure of the EPG caused by natural destructive forces. The present embodiments can perform a corrective action with an automated helper to mitigate the risks to the EPG caused by the natural destructive forces determined from the EPG threat metrics.

Abstract: Disclosed are displacement sensors constructed from optical fibers having a long elongation with low-cost ToF sensors that advantageously do not suffer the infirmities of the art. The ToF sensor and the optical fiber ends that launch and receive light are packaged such that no ambient light affects measurements, and the structure is protected from contamination which eliminates optical degradation. With multi-point measurement capabilities and the low-cost features of ToF sensors, many displacement sensors can be arranged in a mesh to map out displacements over a large area and over all directions for civil and/or geotechnical structures. Wireless or other communications mechanisms may be employed in conjunction with our novel sensors to send real time measurement data to a central office for real time monitoring and analysis.

Abstract: Integrated DFOS systems and methods for 3D gunshot, localization, and tracking utilizing Artificial Intelligence enhanced (AI-enhanced) systems and methods for infrastructure security including electrical substations. Our systems and methods provide a comprehensive solution for substation security enhancement, integrating 3D gunshot localization, real-time tracking, and AI-driven analysis. Utilizing Distributed Acoustic Sensing (DAS) technology, our systems and methods precisely detect and triangulate the origin of gunshots in three-dimensional space. The trajectory of a bullet is determined, providing insights into the direction and potential target within the substation. Al algorithms discern between various acoustic events and provide identification of genuine threats. Upon detecting a potential gunshot, our system automatically correlates related acoustic events, such as the noise of a nearby vehicle, offering context and aiding in threat assessment.

Abstract: Disclosed is a deep learning and language model enhanced system and method for wind turbine monitoring using distributed fiber optic sensing (DL-LM-DFOS) which combines advantages of distributed fiber optic sensing with the power of deep learning and large language models. Our system and method automatically learns and extracts useful features from raw sensor data, detects complex patterns indicating potential issues, and incorporates and learns from a wide range of data, including textual data such as maintenance logs, operational notes, or alarm messages. As a result, our inventive system and method provide comprehensive, efficient, and predictive monitoring of wind turbines.

Abstract: Systems and methods for cable inspection using optical fiber sensing includes a hardware processor and a memory storing a computer program which, when executed by the hardware processor, causes the hardware processor to collect data from a fiber optic cable and analyze the data with a distributed fiber optic sensing (DFOS) system. Losses and anomalies and their locations are identified in the cable. An alert is generated based on the losses and anomalies.

Abstract: Disclosed are integrated systems and methods providing intelligent anomaly detection for DFOS systems and applications, the systems and methods utilizing a natural language processing model, such as ChatGPT, to generate real-time alerts with actionable recommendations and potential consequences based on detected anomalies. Our innovative solution—OptiSenseGPT—solves problems left uncured by traditional methods by delivering easily understandable alerts in natural language, enabling timely response by relevant personnel. Our integrated OptiSenseGPT systems and methods disclosed provide context-aware recommendations and consequences, enhancing decision-making and improving overall performance and safety of a monitored infrastructure or environment. Our OptiSenseGPT systems and methods advantageously provide integration of natural language processing; context-aware recommendations; presentation of potential consequences; adaptability and customization; and seamless integration.

Abstract: Provided herein are small molecule compounds and methods inhibiting human sulfotransferase 1A3 (SULT1A3) using these small molecule compounds. Methods of manufacturing and treatment are also disclosed.

Abstract: Computer implemented methods, systems, and computer program products include program code executing on a processor(s) obtains queries from sources via a query interface. The program code analyzes the queries to obtain attributes of the queries. The program code applies a trained classifier to the attributes to classify the queries into finite categories based on a predicted usage of a given resource type exceeding a pre-determined threshold and an anticipated execution duration for each query. The program code determines, based on the finite categories of the one or more queries and resource configurations of resources comprising the database service, which resource of the resources can efficiently execute each query of the one or more queries. The program code schedules each query of the one or more queries for execution by the determined resources.

Abstract: A method for time synchronization using distributed fiber optic sensing (DFOS) that employs several trusted time beacons that are attached to the DFOS sensing fiber which in turn is connected to the DFOS interrogator. The beacons transmit their signal via two different mediums, (1) wirelessly to sensor nodes in the coverage area, and (2) through vibrations on fiber to the DFOS/DAS system located at a trusted area such as the central office. Wireless broadcast to nearby sensors includes a timestamp and beacon ID. All the sensors in the field use one of the beacons in their vicinity (the one with the strongest signal) as their time reference and send the data back with the corresponding beacon index.

Abstract: Disclosed are systems and methods directed to a MIMO method that detects and localizes an object without requiring the object to emit a sound. Operationally, multiple speakers generate tone signals at different frequencies, while multiple acoustic sensors demodulate the complex amplitude of each frequency. By monitoring the feature variation of the relative phase (or intensity) vector from the complex amplitude, our method detects or localizes movement of the object. For large-scale applications, a fiber-optic system and method that employs distributed acoustic sensing (DAS) in which an optical fiber is used as one or more acoustic sensors located at points along the length of the optical fiber. A single DAS system provides numerous sensors using only a single optical fiber thereby enabling perfect synchronization and centralized signal processing. Notably, with such a DAS arrangement, cost and complexity is significantly reduced, while privacy is preserved.

Abstract: Various embodiments of the teachings herein include a workflow construction method. An example includes: receiving function block node addition and connection operations from a GUI on the basis of function block type graphs, wherein each function block node implements a service operation; and constructing a behavior tree corresponding to one workflow in response to the function block node addition and connection operations. Each function block type graph comprises: a function block name, a function block header, a link input port and a link output port, an input data chunk and an output data chunk, a data input port and a data output port, and a function block body. The function block node addition operation comprises a dragging operation.

Abstract: Disclosed are systems, methods, and structures that mitigate accumulative error in relative-measurement DFOS by employing, for each segment of the DFOS arrangement that records a certain number of an earlier estimation of each spatial segment. A predictive model in each buffer learns trends from the recorded history and predicts an output from the previous history. The reference is also updated using the prediction from the buffer. Systems, methods, and structures according to the present disclosure include the buffer structure that records a certain number of earlier estimations for each segment, a predictive model in each buffer that predicts the output of each segment according to the earlier estimations, reference updates using the prediction from the buffer tracker and workflow of real-time data processing with the buffer structure and tracker.