Abstract: Systems, apparatuses, and methods are described for a dynamic network identification to facilitate a selection of a desired audio. A premises (e.g., a public bar) may have a plurality of display devices (e.g., television screens) outputting videos associated with a plurality of content items (e.g., television programs). A computing device may assign an audio data of each of the content items to be transmitted over a separate wireless network. A user may be able to listen to the audio of a desired content item by causing a user device to join a wireless network assigned to transmit an audio data of the desired content item. The wireless network may be reused to transmit a different audio data. A network identifier of the wireless network may be renamed to indicate the different audio data. The network identifier may be based on metadata associated with a content item.

Abstract: A robotic surgical system is disclosed for AI-guided neoplasm resection using multimodal imaging and machine learning. The system comprises a robotic manipulator with sub-millimeter precision and intraoperative imaging modules, including hyperspectral imaging. A data acquisition module integrates preoperative imaging (CT, MRI, PET, ultrasound, X-ray) with real-time surgical data via an image fusion engine to form a co-registered anatomical model. An AI engine analyzes spectral and anatomical data to differentiate tissue types and updates a dynamic resection path. A control unit autonomously adjusts the robotic trajectory in real-time. A visualization interface overlays tumor margins and surgical guidance for enhanced precision. The system further includes surgeon feedback integration, fatigue monitoring, and adaptive learning through historical and live procedure data, supporting autonomous and semi-autonomous operation across diverse surgical applications.

Abstract: A robotic surgical system includes a robotic manipulator configured to perform surgical procedures under direct surgeon control. A surgical camera system captures real-time intraoperative video. An external imaging interface receives multimodal imaging data, including preoperative and intraoperative data from at least one of magnetic resonance imaging (MRI), computed tomography (CT), ultrasound, and fluoroscopy.

Abstract: A robotic surgical system network includes a plurality of robotic surgical systems. Each system includes robotic arms, sensors, a surgeon console, and a control system with an integrated AI module. A network interface is associated with robotic surgical system and provides secure data communication. A central or distributed data repository securely stores surgical data aggregated from the robotic surgical systems. The surgical data includes at least one of procedural data, sensor readings, imaging data, AI decision logs, surgical outcomes, or user interaction data. A training module utilizes aggregated surgical data to train or update AI models for the robotic surgical systems using unsupervised learning, transfer learning, or federated learning techniques. A cybersecurity module implements security measures for data transmission and system access, the measures comprising at least one of encryption, multi-factor authentication, or real-time threat detection.

Abstract: A robotic surgical system includes a control processor, surgeon console, and one or more robotic instruments. A procedure tracking module monitors surgical instrument activity, surgeon commands, imaging data, and system logs in real-time. An artificial intelligence (AI)-driven workflow optimization engine comprises at least one trained machine learning model and a data processing subsystem. The engine analyzes intraoperative data to detect inefficiencies or deviations from optimized surgical sequences and generates real-time workflow recommendations based on procedural urgency, risk assessment, and surgeon-specific behavior. A multimodal interface presents these recommendations via visual, auditory, or haptic cues and captures surgeon feedback for continuous AI refinement.

Abstract: The invention relates to a batch process for preparing a polyether alcohol P having a hydroxyl number of greater than 115 mg KOH/g by reacting starter compound S1 and starter compound S2, which starter compounds have one active hydrogen atom or a plurality of active hydrogen atoms, with one or more alkylene oxides in the presence of a composite metal cyanide complex catalyst, comprising a) forming a starter mixture comprising starter compound S1 and the catalyst and activating the catalyst by adding more than 10 wt.

Abstract: A urinary catheter system includes one or more sensors positioned in an interior of a catheter tube and positioned to be in contact with patient's urine An artificial intelligence system has an AI system with an AI engine. A plurality of machine learning algorithms are used with a machine learning model. The machine learning model processes the sensor data using constructive learning to train the machine learning model to distinguish between clean and noisy data of the sensor data, and uses labeled data with a known noise level to classify the sensor data as either clean or noisy, allowing for the removal of one or more noisy data points from a sensor data dataset. The AI system splits the sensor data into a training set and a testing set with the training used to train and the testing set for analysis of the sensor data. Cryptography algorithms that at least a portion of one or more of the sensor data.

Abstract: A robotic surgical system is disclosed incorporating artificial intelligence (AI)-driven haptic feedback to enhance surgical precision and safety. The system includes a surgeon console, robotic arms with surgical tools, imaging devices, and sensors configured to acquire intraoperative data. A processor executes an AI model trained to infer anatomical context and generate haptic control parameters. A haptic feedback interface delivers force, vibration, shear, or thermal stimuli, while a controller applies haptic signals in real time with latency below 50 milliseconds. Feedback is dynamically modulated according to AI-inferred interaction classifications. The system utilizes real-time data, including video, imaging, force, and biometric inputs, to support intraoperative decision-making, trajectory refinement, and surgeon performance assessment.

Abstract: A batch process for preparing a polyether alcohol P having a hydroxyl number of greater than 115 mg KOH/g. The process starts by a) forming a starter mixture comprising starter compound S1 and a composite metal cyanide complex catalyst and activating the catalyst by adding an alkylene oxide, followed by b) continuously adding an alkylene oxide; and c) continuously adding starter compound S2.; No alkylene oxide is added between steps a) and b), and the continuous addition of alkylene oxide in step b) is not interrupted before the total weight of alkylene oxide needed to prepare polyether alcohol P has been added; step c) is stopped before step b) is stopped and once less than 80% of the total weight of alkylene oxide needed to prepare polyether alcohol P has been added in step b).

Abstract: A robotic surgical system includes a surgeon consol coupled to a patient console and coupled to one or more surgical instruments. The surgeon consol is used by a surgeon to perform a surgical procedure. A surgeon computer is coupled to or at the surgeon console. The surgeon consol is coupled to the one or more surgical instruments (manipulators). A surgical robot is coupled to a robotic surgery control system and a feedback loop. The feedback loop monitors and collects data from one or more sensors used to provide feedback to the robotic surgical system. An AI system has an AI architecture that uses input data for producing an AI model. A surgical robot is coupled to a robotic surgical control system that is coupled to or includes: the feedback loop, and the artificial intelligence AI system.

Abstract: A robotic surgical system, a surgeon console operatively coupled to a patient console and one or more surgical instruments. A surgeon computer is coupled to or integrated with the surgeon console, the surgeon computer further operatively connected to the one or more surgical instruments; A surgical robot is coupled to a robotic surgery control system and a feedback loop. The robotic surgery control system includes or is coupled to an artificial intelligence (AI) system. A feedback loop is further configured to receive performance-related data from the one or more sensors, the data analyzed by the robotic surgery control system or the AI system to dynamically adjust the robotic system's operation as needed. A data extraction module retrieves, from the robotic surgery control system or the AI system, one or more programmed steps executed by the surgeon for positioning at least one of the surgical instruments during the surgical procedure.

Abstract: A robotic surgical system is disclosed that integrates a simulation module, artificial intelligence (AI), and a multimodal sensor array to enhance intraoperative decision-making and execution. The system generates a dynamic, patient-specific digital twin representing anatomical, physiological, and thermal data, continuously updated during surgery. Real-time sensor inputs, including force feedback, imaging, and biomarkers, are analyzed by an AI module to characterize tissue conditions, predict responses, and guide tool trajectories. The system adapts tool movement based on AI confidence scoring, margin proximity, and predictive modeling. A visualization interface overlays augmented insights onto live surgical views. The platform enables surgeon-specific and population-based learning, real-time feedback, and intraoperative handoff based on biometric or performance indicators. Embedded modules provide simulation, planning, deviation tracking, and control adjustment.

Abstract: A robotic surgical system is configured to provide dynamic legal and ethical compliance. A control processor executes surgical procedures based on artificial intelligence (AI)-generated guidance. A compliance module is associated with the control processor and configured to: receive jurisdiction-specific surgical requirements and patient-specific consent data room external or internal sources; monitor surgical actions and AI-generated decisions in real time; analyze decision pathways using rule-based logic, predictive models, or both to detect potential legal or ethical conflicts; and initiate at least one of: issuing a conflict alert, inhibiting automated execution of the decision, or prompting a confirmation action by a human operator. A policy ingestion component interprets compliance directives expressed in natural or semi-structured language, including regulatory standards, institutional protocols, and cultural norms.

Abstract: A robotic surgical system is disclosed that integrates real-time surgeon behavior monitoring, biometric feedback, and adaptive AI-based decision support to enhance intraoperative performance and post-procedural analysis. The system includes a user behavior monitoring module to track surgeon interaction patterns, a biometric data aggregator collecting inputs such as heart rate variability, electrodermal activity, and eye tracking, and a feedback modulation engine operatively coupled to an AI inference engine. A phase classifier evaluates surgical criticality based on tool telemetry and contextual signals, enabling the system to dynamically escalate, suppress, or defer feedback. Surgeon-specific profiles guide system behavior across procedures, while a summary dashboard provides insights into feedback efficacy and surgeon responsiveness.

Abstract: A robotic surgical system incorporates artificial intelligence to enhance intraoperative performance and surgical decision-making. The system includes a surgeon console, one or more robotic arms, and a control module with an AI-driven model generalization engine. The AI engine leverages cross-procedure transfer learning, enabling it to apply models trained on one type of surgery to others exhibiting latent procedural similarity. Intraoperative data including endoscopic video, robotic arm kinematics, force and haptic feedback, biometric signals, and audio commands is analyzed to support real-time guidance, anomaly detection, and adaptive control. The system comprises modules for surgical planning, predictive analytics, autonomous task execution, and surgeon fatigue monitoring. Feedback from multimodal sensors informs dynamic trajectory adjustment and surgical decision support. Continuous learning from both historical and live surgical data refines the AI model over time.

Abstract: A robotic surgical system includes a surgeon console coupled to a patient console. The surgeon console is coupled to a surgical robot and one or more robotic surgical instruments. A robotic surgery control system is coupled to a feedback loop. The control system includes an artificial intelligence (AI) architecture configured to process intraoperative input data, and generate an AI model for positioning the surgical instruments during a surgical procedure. A deviation detection module is configured to identify intraoperative discrepancies between a predefined surgical action sequence and an actual robotic execution using deviation thresholds based on one or more of: trajectory variance, motion drift, or multimodal image inconsistency. The deviation detection module employs a trained machine learning model to enhance sensitivity to context-specific deviations without triggering autonomous inference chains.

Abstract: The invention relates to a batch process for preparing a polyether alcohol P having a hydroxyl number of equal to or lower than 115 mg KOH/g by reacting starter compound S1 and starter compound S2, which starter compounds have one active hydrogen atom or a plurality of active hydrogen atoms, with one or more alkylene oxides in the presence of a composite metal cyanide complex catalyst, comprising a) forming a starter mixture comprising starter compound S1 and the catalyst and activating the catalyst by adding an alkylene oxide, followed by b) continuously adding an alkylene oxide; and c) continuously adding starter compound S2; wherein no alkylene oxide is added between steps a) and b), and the continuous addition of alkylene oxide in step b) is not interrupted before the total weight of alkylene oxide needed to prepare polyether alcohol P has been added; and step c) starts before step b).

Abstract: A robotic surgical system includes a robotic instrument coupled to a controller and configured to interact with biological tissue. A physiologic sensing subsystem has one or more sensors configured to detect real-time physiological parameters. The sensors include at least one of: tissue oxygenation sensors, perfusion sensors, bioimpedance sensors, or neural conductivity sensors.

Abstract: The invention relates to a batch process for preparing a polyether alcohol P having a hydroxyl number of equal to or lower than 115 mg KOH/g by reacting starter compound S1 and starter compound S2, which starter compounds have one active hydrogen atom or a plurality of active hydrogen atoms, with one or more alkylene oxides in the presence of a composite metal cyanide complex catalyst, comprising a) forming a starter mixture comprising starter compound S1 and the catalyst, followed by b) continuously adding an alkylene oxide; and c) continuously adding starter compound S2; wherein no alkylene oxide is added in step a) or between steps a) and b), and the continuous addition of alkylene oxide in step b) is not interrupted before the total weight of alkylene oxide needed to prepare polyether alcohol P has been added; and step c) starts before step b).

Abstract: Anti-parasitic compounds and uses thereof. Compounds comprising a C-terminal peptide adjuvant conjugated to an N-terminal peptide antigen via a protease-cleavable linker, said peptide adjuvant comprising a peptide analog of C5a, wherein said peptide antigen comprises an antigenic epitope of a parasitic organism, such as T. gondii. Methods of therapeutic or prophylactic treatment of a parasitic infections.