Abstract: A magnetorheological damper capable of providing independent linear and rotational force feedback includes two cylinders filled with magnetorheological fluid. The first cylinder is internally provided with a piston head assembly and a piston rod axially penetrating the cylinder, and the piston head assembly is provided with a coil wound with an enameled wire, and is connected to a piston rod through two rotary bearings. The piston rod is configured to drive the piston head assembly to move in a linear direction, and different damping forces can be generated in the linear direction by changing a current in the enameled wire. The second cylinder is internally provided with a stationary drum and a rotary drum that is rotatably fixed to the piston rod, which is configured to drive the rotary drum to rotate in the second cylinder, thereby squeezing the magnetorheological fluid to generate different damping forces in the rotational direction.

Abstract: An information propagation prediction method based on a sequential hypergraph neural network with co-attention fusion. The method includes three modules: a user feature learning module learning a user embedding by utilizing a graph convolutional neural network; a cascade feature learning module constructing a sequential hypergraph neural network based on equivariant diffusion to capture a complex cascade irregular connection so as to learn a cascade embedding of internal and external features of an encapsulated cascade structure; and a feature fusion and prediction module learning an interdependence between cascade features and user features by means of a co-attention mechanism so as to capture a complex relationship and interaction between the cascade features and the user features, and then calculating a possibility of potential user infection.

Abstract: Convolution-Hierarchical Deep-learning Neural Network-Tensor decomposition (C-HiDeNN-TD) has four features: (1) Tensor decomposition breaking down the whole design into small tractable problems; (2) Convolution built-in filter to increase accuracy without adding extra DoFs; (3) Convolution built-in filter can avoid checkerboard pattern; (4) Design can have arbitrary smoothness without adding extra DoFs.

Abstract: Provided are devices and methods featuring a nanoelectronic interface between graphene devices (for example, field effect transistors or FETs) and biomolecules such as proteins, which in turn provides a pathway for production of bioelectronic devices that combine functionalities of the biomolecular and inorganic components. In one exemplary application, one may functionalize graphene FETs with fluorescent proteins to yield hybrids that respond to light at wavelengths defined by the optical absorption spectrum of the protein. The devices may also include graphene in electronic communication with a bio-molecule that preferentially binds to a particular analyte.

Abstract: A cable force control method includes: establishing a friction model, and calibrating parameters; and calculating the parameters in real time, and controlling a force: identifying the parameters according to the friction model to obtain parameters of an auxiliary cable Bowden system and a power Bowden system: a friction coefficient ?a of the auxiliary cable Bowden system, and a friction coefficient ?p of the power cable Bowden system; calculating the auxiliary cable Bowden system ?a in real time according to the model and a force value of a sensor, and using same as a cable bending angle of the power cable Bowden system ?p; and obtaining an inverse control formula Fin=Fout·e?u?? according to the friction model, and bringing the power cable Bowden system ?p into the inverse control formula to serve as a feedforward controller, so as to achieve an effect of real-time force control.

Abstract: A cooktop includes a power adjustment switch with power grades, a power detection apparatus, a control apparatus, and an adjustment apparatus. The power detection apparatus for detects a power grade to determine an operation period of the power grade and a power level corresponding to the power grade and outputting operation information including the operation period and the power level. The control apparatus calculates a first valid period based on the operation information, and determines whether the first valid period exceeds a first threshold period. When affirmative, the control apparatus outputs adjustment information for adjusting the power grade to reduce the power level. The adjustment apparatus adjusts the power grade based on the adjustment information to reduce the power level. The cooktop actively detects an operating status and adjusts a power grade, to avoid dry burning and potential safety risks.

Abstract: A method for alignment calibration of an inertial measurement unit contained in a head-worn apparatus. The method includes: wearing an apparatus on the head of a user; performing a static calibration stage including determining a misalignment of a first sensitive axis of the inertial measurement unit with respect to a direction of gravity while the user holds their head statically, looks straight ahead and horizontally.

Abstract: Systems and methods for exchanging synchronization information between processing units using a synchronization network are disclosed. The disclosed systems and methods include a device including a host and associated neural processing units. Each of the neural processing units can include a command communication module and a synchronization communication module. The command communication module can include circuitry for communicating with the host device over a host network. The synchronization communication module can include circuitry enabling communication between neural processing units over a synchronization network. The neural processing units can be configured to each obtain a synchronized update for a machine learning model. This synchronized update can be obtained at least in part by exchanging synchronization information using the synchronization network. The neural processing units can each maintain a version of the machine learning model and can synchronize it using the synchronized update.

Abstract: In various embodiments, software architecture and network topology are provided to implement a decentralized distributed computing environment. In some embodiments, the novel network topology is configured as a mesh network such that individual hub devices are connected directly or indirectly with each other. An individual worker can be added to or removed from this network via connection with the hub devices without affecting the rest of the workers in the network and without user intervention or knowledge.

Abstract: A cable force control method includes: establishing a friction model, and calibrating parameters; and calculating the parameters in real time, and controlling a force: identifying the parameters according to the friction model to obtain parameters of an auxiliary cable Bowden system and a power Bowden system: a friction coefficient ?a of the auxiliary cable Bowden system, and a friction coefficient ?p of the power cable Bowden system; calculating the auxiliary cable Bowden system ?a in real time according to the model and a force value of a sensor, and using same as a cable bending angle of the power cable Bowden system ?; and obtaining an inverse control formula Fin=Fout·e?u?? according to the friction model, and bringing the power cable Bowden system ?p into the inverse control formula to serve as a feedforward controller, so as to achieve an effect of real-time force control.

Abstract: A Hierarchical Deep Learning Neural Networks-Artificial Intelligence system for data processing, comprising a data collection module collecting data; an analyzing component extracting at least one feature from the data, and processing the extracted at least one feature to produce at least one reduced feature; and a learning component producing at least one mechanistic equation based on the at least one reduced feature.

Abstract: A calibration and verification system for a directional sensor, including an industrial control computer and a directional sensor, wherein the industrial control computer is connected to a sensor signal acquisition system, a first triaxial Helmholtz coil and a second triaxial Helmholtz coil, respectively, wherein a heating calibration turntable is disposed in the first triaxial Helmholtz coil and configured to heat and calibrate the directional sensor, and wherein a high-precision inclination and azimuth test turntable is disposed in the second triaxial Helmholtz coil and configured to verify the directional sensor.

Abstract: A method for operating a gas sensor device, which is equipped with at least one gas-sensitive electrical sensor resistor, a heating element for the controlled heating of the sensor resistor, a detection element for detecting the resistance value of the sensor resistor, and a signal processing element for processing measuring signals. In the method, measurements are carried out in time intervals, in which the resistance value of the sensor resistor is detected as a measuring signal, and the sensor resistor is heated for each measurement, the heating element being operated discontinuously in heating intervals and each measurement being assigned a heating interval. Measurements are automatically carried out in predefinable time intervals, and additional measurements are initiatable at arbitrary times. The duration of the heating intervals assigned to the individual measurements being selected as a function of the time interval to the preceding heating interval.

Abstract: An evaluation device and method for orientation estimation for two sensor units arranged on an object. The method including: ascertaining a sensor transformation matrix from a first sensor coordinate system fixed to a first sensor unit into a second sensor coordinate system fixed to a second sensor unit; transforming a first acceleration vector measured using the first sensor unit into the second sensor coordinate system; and defining a first axis {tilde over (x)} located in the second sensor coordinate system, corresponds to a first coordinate x of an object coordinate system extending through the first sensor unit and the second sensor unit, the object coordinate system being fixed to the object, based on the second angular velocity vector, its time derivative, and a difference vector between a second acceleration vector measured using the second sensor unit minus the first acceleration vector transferred into the second sensor coordinate system.

Abstract: A multi-gate HEMT includes at least two gates, with at least one recessed the same depth or at a deeper depth in a barrier layer than at least one other gate. Recessing a gate decreases the thickness of the barrier layer beneath the gate, reducing a density of high mobility carriers in a two-dimensional electron gas layer (2DEG) conductive channel formed at the heterojunction of a barrier layer and a buffer layer below the recessed gate. The recessed gate can increase gate control of the 2DEG conductive channel. The multi-gate HEMT has at least one gate recessed the same depth or a deeper depth into the buffer layer than another gate, which forms at least two different turn-on voltages for different gates. This can achieve improvement of transconductance linearity and a positive shift of the threshold voltage.

Abstract: Systems and methods for exchanging synchronization information between processing units using a synchronization network are disclosed. The disclosed systems and methods include a device including a host and associated neural processing units. Each of the neural processing units can include a command communication module and a synchronization communication module. The command communication module can include circuitry for communicating with the host device over a host network. The synchronization communication module can include circuitry enabling communication between neural processing units over a synchronization network. The neural processing units can be configured to each obtain a synchronized update for a machine learning model. This synchronized update can be obtained at least in part by exchanging synchronization information using the synchronization network. The neural processing units can each maintain a version of the machine learning model and can synchronize it using the synchronized update.

Abstract: In various embodiments, software architecture and network topology are provided to implement a decentralized distributed computing environment. In some embodiments, the novel network topology is configured as a mesh network such that individual hub devices are connected directly or indirectly with each other. An individual worker can be added to or removed from this network via connection with the hub devices without affecting the rest of the workers in the network and without user intervention or knowledge.