186 results about "Physics engine" patented technology

The invention relates to the technical field of traffic accident analysis, and discloses an intelligent analysis method for vehicle and pedestrian collision accident liability, and the method comprises the steps: firstly obtaining multi-source heterogeneous accident data, fusing a cross-platform data source through employing a federal learning framework when the data is insufficient, and reconstructing an accident scene three-dimensional coordinate system; and then, based on a multi-modal data fusion result, constructing a traffic participation entity relation topology model by using a graph neural network, and generating an accident dynamic evolution graph. Then, establishing a collision dynamics digital twin model by utilizing a physical engine, extracting a key collision feature vector, and constructing a responsibility probability distribution model based on a generative adversarial network; and optimizing a responsibility judgment strategy by adopting a double-layer reinforcement learning framework, verifying a physical simulation result through a hierarchical verification mechanism, analyzing a responsibility judgment logic chain, and finally outputting a responsibility analysis report with an interpretable label. The method can accurately and intelligently analyze the accident liability, and has good interpretability.

A physical AI-based magnetic field environment modeling method and a physical AI-based magnetic field environment modeling system are disclosed, the physical AI-based magnetic field environment modeling system comprises a data layer, a preprocessing layer, a core modeling layer and a verification and application layer, and the core modeling layer comprises a physical knowledge base and stores physical laws, material constitutive relationships and boundary conditions related to a target magnetic field environment; the model construction module is responsible for designing and constructing a main body structure of a physical AI model according to problem characteristics and a physical knowledge base; the physical AI engine represents a constructed or trained physical AI model instance, receives input and quickly outputs a predicted magnetic field value; and the model training module is responsible for training the neural network model generated by the model building module by using the preprocessed data and physical constraints in the physical knowledge base. The core innovation point of the invention lies in that a physical artificial intelligence normal form is systematically introduced and applied to the modeling process of a complex magnetic field environment, and an efficient, accurate, robust and physically consistent magnetic field modeling system is created through deep fusion of physical laws and data driven learning.

The invention discloses an underground water exploitable quantity evaluation method and system based on coupling of a physical mechanism and a neural network, and relates to the technical field of water resource management, meteorological data, surface water hydrological monitoring data, geological survey data, underground water resource development and utilization data and hydrogeological parameter data are integrated and preprocessed, and a basic data set is obtained; a three-dimensional geological model of a heterogeneous structure is constructed by utilizing a digital twin physical engine and combining drilling geological data. By introducing a digital twin technology and a numerical model, the underground water flowing process can be simulated more accurately, a digital twin physical engine is utilized to construct a heterogeneous aquifer digital model, a dynamic interaction process of surface water and underground water is embedded, and the model is enhanced through a graph neural network and a physical information neural network, so that the underground water flowing process is simulated more accurately. Errors caused by hypothesis of aquifer homogeneity, neglecting of surface water-underground water coupling process and the like of a traditional model are effectively reduced, and the accuracy of underground water exploitable quantity evaluation is improved.

The invention discloses a PICC virtuality and reality combined simulation training system and method, solves the problems that puncture simulation training is not real enough and students cannot perform intensive training aiming at a puncture technology due to the fact that an existing venipuncture simulation platform lacks necessary puncture force feedback, and belongs to the technical field of virtual training. The system is composed of a personal information management module, a simulation training terminal, a virtual model management module and a man-machine interaction module, and student operation information is collected in real time based on a multi-dimensional sensor; the virtual model management module reconstructs real anatomical structures such as blood vessels and skin of a human body through a high-precision 3D modeling technology, a physical engine is matched to provide a vivid puncture hand feeling, students can experience a scene very close to real operation, and the simulation training terminal can simulate the real operation through a force feedback technology in a virtual scene. The trainee can feel the touch similar to that of real puncture, so that the understanding of the trainee on the puncture process and the control of the trainee on the puncture strength and angle are improved.

The invention discloses an electric locomotive three-dimensional digital-analog simulation teaching system constructed based on an unreal engine technology, and relates to the technical field of electric locomotive teaching. Comprising a three-dimensional model construction module which is used for generating a hierarchical three-dimensional model of electric locomotive equipment through combination of polygon modeling and parametric modeling; and the physical engine interaction module is integrated with an unreal engine physical system and is configured to process the real-time solution of the locomotive kinetic parameter equation set. According to the method, a highly accurate three-dimensional model is created by combining polygon modeling and parametric modeling on the complex equipment of the electric locomotive, the model can support detailed level-of-detail rendering so as to adapt to different observation distances, and in the physical engine interaction module, the model can be applied to the physical engine interaction module. Through the train longitudinal dynamics calculation unit, the traction transmission simulation unit and the braking system modeling unit, the system can simulate non-linear changes in the wheel-rail contact force, traction motor torque transmission and tread braking process in real time, so that various dynamic effects can be visually displayed in the teaching process.

The invention discloses an equipment disassembly sequence automatic generation and verification method based on a physical engine, which belongs to the technical field of equipment disassembly, and realizes component physical attribute and dynamic connection constraint loading by acquiring an equipment three-dimensional model and initializing a physical engine simulation environment. And in the physical engine simulation environment, iteratively evaluating the feasibility of the disassembly operation, accurately capturing physical behaviors such as gravity and collision, and identifying disassembly obstruction and preset operation to generate candidate operation. A path search algorithm is utilized to intelligently explore and generate a creative disassembly sequence, and the limitation of traditional artificial experience and a static method is overcome. Through a multi-dimensional nonlinear total cost function, factors such as the number of disassembly steps, collision risks, tool replacement and accessibility and the like are comprehensively quantified, and an optimal solution considering efficiency, safety and operation convenience is verified and selected.

The invention provides a mixed reality industrial simulation training system which is composed of a space fusion perception unit, a multi-physics field simulation unit, a cooperative training management unit and a self-adaptive teaching engine. The space fusion sensing unit is composed of a real-time environment modeling and positioning subsystem and a physical interaction detection algorithm, and the real-time environment modeling and positioning subsystem dynamically constructs a three-dimensional space coordinate system of a real industrial scene through a visual sensor array and a radio frequency scanning device; generating a pose matrix of the virtual equipment model in the perspective display interface; the physical interaction detection algorithm realizes contact force feedback between virtual and real objects based on dynamic solution of collision volume, and when an operator triggers a virtual switch through a handheld controller, a real equipment control signal is synchronously driven; the multi-physics field simulation unit comprises a physical engine core module and a fault injection interface.

The invention relates to the technical field of computer graphics and artificial intelligence, and discloses a meta-universe digital human generation method and system based on deep learning, and the method comprises the steps: constructing a neural radiation field human body model through multi-view video data, and learning a user behavior sequence mode; collecting sparse sensor data of the head and the hands of the user and generating a preliminary whole-body skeleton posture; calculating contact force feedback when the digital human interacts with the virtual environment through a differentiable physical engine; utilizing a reinforcement learning algorithm to optimize postures to meet physical constraints; performing multi-objective optimization and quality evaluation on the generated attitude; according to the method, the digital human postures which have personalized features and can naturally interact with the environment can be generated by using the consumer-level equipment, and the meta-universe interaction experience is improved.

The invention provides a meta-universe scene rapid construction method and system based on a modular engine, and relates to the technical field of meta universe, and the method comprises the steps: obtaining a creation instruction of a user for a meta-universe scene, and calling a corresponding scene rendering module from a preset modular engine library according to scene type information; performing feature extraction and scene layering on scene environment parameters based on a scene intelligent analysis model of deep learning, and analyzing the scene environment parameters into a plurality of scene function layers with a progressive hierarchical relationship; and calling a physical engine module, an illumination rendering module and an environment special effect module to construct a scene. Through the modular engine and the intelligent analysis model, rapid establishment of the meta-universe scene is realized, the scene establishment efficiency is improved, and the scene reality sense and the interaction experience are enhanced.

The invention belongs to the field of software testing and defect detection, focuses on reliability verification of a physical simulation engine, is suitable for scenes depending on physical simulation, such as robot simulation, automatic driving testing, unmanned aerial vehicle control, education and scientific research, and particularly relates to a variation-based physical simulation engine defect detection method. Potential defects of core modules of collision detection, mechanical calculation, dynamics and the like are efficiently found through a variation test method. According to the method, a feature library is constructed through static library API analysis and AST / IR code analysis, test code expansion is performed by utilizing a large model, a test driver adaptive to a specific data type is generated, a physical semantic constraint mutation seed is combined, a test is executed through libFuzzer, defect and coverage rate data are analyzed, a use case selection strategy is optimized, and the test efficiency is improved. Defects of core modules such as collision detection and dynamic solution are efficiently detected, and the test pertinence and efficiency are improved.

The invention discloses a mechanical arm simulation system supporting industrial quality inspection, which relates to the technical field of industrial automation and comprises a multi-physics field simulation engine module, a digital twin interface module, a defect sample library module and a cooperative control module. According to the method, traditional entity mechanical arm debugging is replaced by rigid body dynamics simulation based on a physical engine, loss and production line shutdown caused by repeated trial and error of equipment are avoided, rapid construction of the digital twin environment of the production line is achieved by means of an efficient CAD model conversion process and a lightweight loading technology, and high-fidelity optical simulation is achieved through a parameterized defect model library and high-fidelity optical simulation. Various common industrial defects and complex optical effects are covered, the modeling bottleneck of a quality inspection scene is broken through, real-time closed-loop interaction of visual inspection and motion control is realized by using thread separation and an efficient communication technology, and the recognition robustness of a visual algorithm to tiny defects is guaranteed; the reliability of algorithm verification is improved through the quantitative output of algorithm performance indexes and the comprehensive test of extreme working conditions by the simulation system.

The invention relates to the technical field of robot control, in particular to a cross-modal perceptual driving body robot compliance control system which comprises the steps that a sensor is adopted to synchronously collect environment information, multi-source data bias is eliminated through a space-time alignment algorithm, a radial basis function neural network is adopted to analyze multi-modal fusion features, and a multi-modal model is obtained; human operation intention probability distribution is extracted to decompose a task into a path planning layer and a motion control layer, a collision-free trajectory is generated through an RRT algorithm, a high-fidelity physical engine is adopted to construct a virtual interaction scene, and robot learning results are shared through federal learning. According to the method, the problems of inaccurate perception, incoordination between intention recognition and interaction control, difficulty in control strategy verification, slow new task adaptation and difficulty in multi-robot learning result sharing caused by multi-source data deviation and large multi-modal semantic difference of the body robot in a complex environment are solved.

The invention discloses a coal mine robot cluster-oriented virtual entity synchronous mapping method. The method comprises the following steps of: constructing a virtual entity synchronous mapping system consisting of a coal mine robot cluster physical entity, a coal mine robot cluster virtual entity, coal mine robot cluster twin data, cluster service application and information interaction; a coal mine robot cluster is used as a physical entity object, an OPC UA communication protocol is used for data collection, the collected data is processed, a virtual entity is driven in a script mode based on a Unity 3D physical engine, and therefore a virtual-real mapping channel is established; converting various non-standardized data structures of the robot cluster into standardized data structures; data of the heterogeneous robot are collected and transmitted through standardization of various communication protocols, and the data are used for driving the virtual entity model. The method has the advantage of performing synchronous mapping on the virtual entities so as to facilitate intelligent management and control.

The invention discloses a neurosurgical operation virtual simulation training system based on multi-modal data fusion, and relates to the technical field of operation simulation. The data acquisition and preprocessing module acquires data such as images and force feedback, and standardized storage is performed after filtering and registration; the multi-modal data fusion module performs weighted fusion on the data by using an attention algorithm to generate a three-dimensional model; the virtual operation scene construction module generates a high-fidelity environment through ray tracing and a physical engine; the surgical operation interaction simulation module realizes accurate interaction through positioning tracking and force feedback; the training evaluation and feedback module quantifies operation performance and provides guidance; and the system management and iteration module guarantees operation and supports data updating and optimization. According to the method, a high-reality scene is constructed through multi-modal fusion, interaction and multi-dimensional evaluation help skill improvement, dynamic difficulty and personalized paths are adaptive to different users, collaborative training and privacy data collaboration are supported, operation training standardization is promoted, and the risk of errors in an operation is reduced.

The invention discloses a simulation test method and system for an unmanned aerial vehicle control algorithm, relates to the field of intelligent system simulation test, and can solve the defects of an unmanned aerial vehicle simulation system in high real scene rendering and physical engine precision at the present stage. The method solves the problems that the real characteristics of a visual sensor and a flight platform cannot be accurately simulated, the performance of an algorithm in a complex real scene is difficult to effectively evaluate, and the adaptability of the algorithm to a hardware environment is difficult to verify, and comprises the following steps: constructing a high-trueness virtual environment according to scene requirements and rigid body dynamics simulation requirements of an unmanned aerial vehicle simulation test; constructing a simulation model according to the physical motion characteristics of the unmanned aerial vehicle hardware and the performance of the sensing equipment; importing the simulation model into a high-reality virtual environment, and performing parameter setting on the simulation model; and testing and verifying a control algorithm of the unmanned aerial vehicle based on the high-trueness virtual environment and the simulation model completed by parameter setting. The method is used for performing simulation test and verification on the control algorithm of the unmanned aerial vehicle.

The invention relates to the technical field of data processing, in particular to an AR-based live broadcast real-time interaction system and method, and the system comprises a motion capture device, an environment perception device, a dual-host processing module, a virtual-real fusion module, an interaction response module, a data distribution module and an AR display terminal. And the double hosts parse the action data and the environment data in parallel and simulate a physical feedback track of a virtual element in combination with a physical engine, so that low-delay response of an interaction instruction is realized. And the virtual-real fusion module adopts a timestamp synchronization mechanism to align the rendered picture and the anchor picture after green screen matting, and eliminates edge sawteeth through image morphological processing to generate high-precision fusion streaming media data. And the AR display terminal projects the virtual elements to real scene space coordinates by adopting an optical superposition technology, so that an anchor previews a virtual-real fusion effect in real time. According to the invention, the dynamic interaction capability and shadow consistency of the virtual elements and the real scene are improved, and the immersive experience of the live scene is optimized.

The invention discloses a real-time software deformation interaction method based on a physical engine in an environment. The real-time software deformation interaction method comprises the following steps: S1, establishing a virtual environment and a software model; s2, constructing an interactive perception and collision detection network; s3, receiving and analyzing a multi-modal interaction instruction; s4, real-time deformation calculation based on a physical engine; s5, performing multi-user collaborative state synchronization and rendering feedback; and S6, carrying out fault state simulation on the software object. According to the method, real-time and high-precision simulation of software deformation is realized through deep fusion of software dynamics calculation of a physical engine and an interaction instruction stream, and through hierarchical physical attribute binding and client prediction, the network synchronization data volume is greatly reduced while the millimeter-level deformation precision is ensured, so that the network synchronization efficiency is improved. And low-delay and high-consistency experience under multi-person cooperative operation is ensured.

The invention discloses a method, a system and a computer program product for generating a three-dimensional video. The method comprises the following steps of: receiving text input which comprises content describing a dynamic scene; a three-dimensional video generation process is interactively supervised through three intelligent agents, and the intelligent agents autonomously decide and execute actions conforming to physical rules in a three-dimensional environment through a physical perception intelligent agent module on the basis of a physical engine and a motion planning algorithm; meanwhile, action coherence is ensured through a time sequence optimization module; and the consistency of the generated content and the input description is ensured through the semantic verification module. Automatic generation of a dynamic scene is realized through intelligent agent simulation, high-quality three-dimensional video content can be interactively created, and the method can be widely applied to the fields of virtual reality, game development, movie and television special effects and the like. In addition, the invention further provides a corresponding generation device, a computer storage medium and an electronic equipment implementation scheme.

The invention discloses a virtual hand grabbing method and system for mixed reality interaction, which is based on a hinge proxy hand model, utilizes a hand tracking device and a physical engine, and fuses hand key point tracking data and a force closing algorithm, and is a grabbing method which is based on physical simulation, is real-time and efficient and does not need to predefine object information. High-precision and real-time hand-object interaction is realized, a virtual hand observed by a user in a mixed reality picture is effectively prevented from penetrating through a virtual object, and the interaction experience in VR / AR equipment is remarkably improved. Moreover, the method supports the real-time adjustment of the dynamic grabbing gesture based on the surface of the object, and is suitable for various VR / AR devices.

A method of grasp generation for a robot includes searching within a configuration space of a robot hand model for robot hand configurations to engage an object model with a grasp type. The method includes generating a set of candidate grasps based on the robot hand configurations. Grasping of the object model with the robot hand model is simulated in a physics engine using simulated grasps generated based on a given candidate grasp. A simulated grasp is assigned a score based on a response of the object model to an applied wrench disturbance when the object is engaged with the simulated grasp. The method includes generating a set of feasible grasps for the given candidate grasp based on the respective simulated grasps having a score above a score threshold at a target wrench disturbance.

The invention relates to the technical field of property management, and discloses an intelligent property management platform and management method combined with AI scene simulation, and the platform comprises a dynamic scene twinning engine which is used for constructing a community total-factor digital twinning body fusing the state of Internet of Things equipment, user behaviors and environment data in real time, and carrying out the dynamic simulation through a physical engine, the model comprises a scene slice and a self-feedback twinborn model; the multi-modal data fusion layer adopts an event-driven data pipeline and is used for correlation analysis of multi-source heterogeneous data; and the decision tree is used for carrying out self-evolution decision making based on a dynamic twin simulation result, and a decision confidence attenuation model is introduced into the decision tree. According to the invention, the bottleneck of passive response in traditional property management is changed, a dynamic scene twin engine is constructed in a foreseeing manner, the property management is converted from a passive operation and maintenance mode depending on manpower and regular inspection into a mode capable of predicting equipment faults in advance and actively providing services, and the intelligence and foreseeing level of the property management is improved.

The invention relates to the technical field of robots, and discloses a dexterous hand adaptive control method and device for multi-agent collaborative reinforcement learning, and the method comprises the steps: constructing a simulation environment comprising a multi-degree-of-freedom bionic dexterous hand and a target object through a physical engine; on the basis of multi-finger cooperative kinematics characteristics of the bionic dexterous hand, a linkage rule used for constraining actions of all fingers is generated; configuring each finger as an independent agent, constraining each finger action by adopting a multi-agent near-end strategy optimization algorithm in combination with a linkage rule, and training a multi-finger collaborative grabbing strategy model; and the trained collaborative grabbing strategy model is deployed to an entity bionic dexterous hand control system, a control instruction is generated by collecting sensor data in real time, and the bionic dexterous hand is driven to execute self-adaptive grabbing operation according to the control instruction. Multi-finger cooperative self-adaptive grabbing of the bionic dexterous hand can be achieved, and the precision and stability of grabbing in a high-degree-of-freedom scene and the adaptability to the dynamic environment are improved.

The invention discloses a multi-robot intelligent collaborative simulation training system based on an augmented reality technology, and relates to the technical field of intelligent warehousing and logistics automation. An AR dynamic obstacle generation technology breaks through static limitation of a traditional simulation scene, sudden interference such as container collapse, temporary forbidding and the like is simulated through a physical engine, and real-time simulation is achieved. A training strategy is directly exposed to a high-simulation risk environment; a topology potential field decision-making mechanism is introduced to quantify course conflicts and distance threats into a repulsive force field in a unified mode, a course Gaussian modulation item accurately filters non-direct collision targets, and the oscillation defect of a traditional potential field method is avoided. According to the path entropy calculation, the conflict probability is analyzed through direction density distribution, gradient adjustment is forcibly activated when the entropy of a narrow channel exceeds a threshold value, the chain reaction of high-density deadlock is restrained from the source, and the group path fluency is guaranteed.

A system and method for adaptive ideation and innovation management using graph-based similarity computation and real-time social facilitation are disclosed, and the system may include a plurality of client devices operated by a human user and one or more AI Agents. The system may further include a computing platform running a Precompute Similarity Engine that may be configured to embed and index idea objects, precompute similarity clusters, and generate candidate merge or purge operations together with diversity and novelty signals; and running a Social Physics Engine that may be configured to monitor human user and machine participant (AI agent) interactions, compute group metrics, and issue digital facilitation interventions. The Precompute Similarity Engine and the Social Physics Engine may operate in an interdependent feedback loop such that diversity and novelty signals guide the generation of digital facilitation interventions that are communicated via the network to the plurality of client devices and the one or more AI Agents.

A device may convert a motion dataset to a compatible representation for use in a physics engine, wherein the physics engine includes a physics simulator and inverse dynamics network. The device may further downsample the motion dataset to obtain keyframes for motion generation and forming a downsampled motion dataset. The device may further execute a deep generative model based on the downsampled motion dataset to generate a first generated motion. The device may further execute the physics engine by feeding pairs of consecutive keyframes into the physics simulator and the inverse dynamics network to generate a second generated motion. The device may further combine the first generated motion and the second generated motion to form a combined generated motion, wherein the combined generated motion is generated by executing the physics engine with the first generated motion. The device may further generate a simulated motion video from the combined generated motion.

The invention discloses an unmanned tower crane dynamic simulation method and system based on a virtual simulation technology, and relates to the technical field of intelligent construction. Comprising the following steps: constructing an unmanned tower crane BIM model and collecting point cloud data, and establishing a simulation model based on the unmanned tower crane BIM model and the point cloud data; developing a customized physical engine based on the simulation model, and constructing a multi-body dynamic model; constructing a three-dimensional wind field model, adjusting parameters, performing climate coupling simulation with the multi-body dynamic model, and obtaining structure response data under different wind fields; constructing an unmanned tower crane path planning model, and generating and executing an unmanned tower crane motion path in combination with the wind field parameters and the structure response data; running state data are obtained and visualized, and multi-dimensional risk monitoring is carried out on the path execution process according to the running state data. According to the method, the problems of scene distortion, rough simulation and risk missed judgment in the existing unmanned tower crane virtual rehearsal are solved, and the authenticity and effectiveness of the virtual rehearsal are improved.

The invention provides an automatic test and quality evaluation system for game development. The system improves the diversity of test coverage and the precision of physical logic error detection. Firstly, a collision recovery coefficient and an initial random seed are collected through a physical engine bottom layer interface, and a standard physical parameter set is constructed; secondly, generating a test case set by adopting disturbance offset and a random trigger mechanism, and realizing scene disturbance simulation; and finally, performing difference analysis on a test result by calculating time sequence data such as a period, event response time and a frame rendering interval, and automatically correcting physical parameters and a trigger sequence based on feedback to realize closed-loop optimization. According to the method, three types of data including a periodic sequence, an event response timestamp sequence and a frame rendering interval sequence are introduced, a frame-level physical logic consistency criterion is established, and the problems of abnormal performance fluctuation, event delay and frame imbalance are finely captured through a combined judgment mechanism of a difference index and a tolerance threshold.

Methods, device and data stream are provided to initiate an extended reality application that uses a physics engine. The scene description comprises behavior data based on triggers. At least one trigger is a collision trigger that is activated in case of a collision between two objects described in nodes of the scene graph of the scene description. The scene description comprises, at the node level, a description of how the object of a given node has to be considered by the physics engine in order to optimize the use of memory and processing resources. A node is of one of three categories: to be ignored by the physics engine, to be considered only for collision or to be considered for a full physics simulation. At the starting, the physics engine is initialized according to these categories and the extended reality application is started in the best conditions.

The invention discloses a cavity robot real-time control method based on a dynamic safety boundary and a related device. The method comprises the following steps: establishing a dynamic security rule base, and activating corresponding constraints in real time according to organization characteristics obtained by sensor fusion; the fusion state information is converted into a symbol track in a discrete time step, and a timed automaton is used for online detection whether the current security constraint is met or not; if not, sampling under a model prediction control framework to generate a control sequence, predicting a track through a physical engine, then verifying point by point by using a safety rule, retaining a passing track, and selecting the track with the highest score as a new motion path; and analyzing the path into a speed instruction, and driving the robot to execute after passing through an impedance control loop and Lie group projection. According to the method, through safety rule dynamic updating and closed-loop verification, the collision risk in the operation is remarkably reduced, and the operation safety and real-time performance of the cavity robot are improved.

The present invention provides a camera layout method in three-dimensional reconstruction of ship waves based on numerical simulation, which relates to the field of ship and ocean engineering, and includes the following steps: by parameterizing the virtual camera in the physical engine, a mathematical model of a single virtual camera posture is obtained, and the mathematical model of the single virtual camera posture is uniformly defined for multiple cameras to obtain a parameterized camera layout mathematical model; for the mathematical model of the camera layout and the parallax angle of the camera layout, the camera layout scheme is obtained in combination with the influence of the camera layout on the sparse reconstruction and dense reconstruction of ship waves when the viewing distance is changed. The present invention parameterizes the posture of a single camera and establishes a unified mathematical model to describe the layout of multiple cameras. Based on the camera layout, a better camera layout scheme is obtained, and the accuracy of the three-dimensional reconstruction of ship waves and the number of spatial points under the camera layout scheme are significantly improved.