Abstract: The disclosure provides a method of preparing chiral metacyclophanes. The method involves palladium-catalyzed cross-coupling of a meta-substituted aryl group with base and a chiral ligand. The disclosure also provides metacyclophane compounds, which include diaryl and monoaryl macrocycles.

Abstract: Implementations relate to generating and using multimodal embeddings. In various implementations, first modality data may be obtained and encoded into first modality embedding(s) using a trained first modality encoder that is stored in memory of edge-based client device(s). Second modality data may be obtained and encoded into second modality embedding(s) using a trained second modality encoder that is also stored in the memory of the edge-based client device(s). The first and second modality embeddings may be processed using an edge-based multimodal LLM that is also stored locally in memory of the edge-based client device(s) to generate a multimodal contextual embedding, which may be provided to a remote server that hosts a central LLM, e.g., in conjunction with a natural language input provided by the user. Information generated using the central LLM, responsive to the natural language input, may be received from the remote server.

Abstract: A processor decompresses a compressed data vector into an original data vector. The processor includes an execution circuit, which receives a decompress instruction that includes two input operands and an output operand. The input operands indicate an address of the compressed data vector in a memory, and the output operand indicates the vector register for storing the original data vector after decompression. The execution circuit executes the decompress instruction to decompress the compressed data vector. When executing the decompress instruction, the execution circuit performs the following operations: read a mask value from the mask register, the mask value being a binary sequence indicating zero positions in the original data vector; generate a selection signal based on the mask value; and generate the original data vector by applying the selection signal to a selection switch that receives the compressed data vector as input.

Abstract: Implementations relate to leveraging large language model(s) (LLMs) and vision language model(s) (VLMs) to facilitate human-to-computer dialogs. In various implementations, one or more digital images may be processed using one or more VLMs to generate VLM output indicative of a state of an environment. An LLM prompt may be assembled based on the VLM output and a natural language input. The LLM prompt may be processed using one or more LLMs to generate content that is responsive to the natural language input. The content that is responsive to the natural language input may subsequently be rendered at one or more output devices.

Abstract: A method for preparing a hole transport layer of a perovskite solar cell, comprises S11, providing a conductive substrate; and S12: doping silver, gallium, selenium and sulfur with each other on the conductive substrate to obtain a hole transport layer. The present disclosure further provides a hole transport layer of a perovskite solar cell and a perovskite solar cell.

Abstract: Some implementations described herein provide techniques and apparatuses for improving a uniformity of a flow of a gas across a semiconductor substrate in an etch tool. The etch tool includes an exhaust port located at a bottom center of a chamber of the etch tool. The etch tool further includes a flow-control subsystem that includes an impeller and a thermal component. As a result of the flow-control subsystem varying a rotational velocity of the impeller, and/or an amount of heat transferred from the thermal component, the uniformity of the flow of the gas across the semiconductor substrate may be improved. In this way, a uniformity of an etching rate may be increased and contamination defects due to a clustering of particulates may be decreased, resulting in an increase in a yield of semiconductor product fabricated using the etch tool.

Abstract: A TCAM comprises a plurality of first search lines, a plurality of second search lines, a plurality of memory cell strings and one or more current sensing units. The memory cell strings comprise a plurality of memory cells. Each of the memory cells is coupled to one of the first search lines and one of the second search lines. The current sensing units, coupled to the memory cell strings. In a search operation, a determination that whether any of the data stored in the memory cell strings matches a data string to be searched is made according to whether the one or more current sensing units detect current from the memory cell strings, or according to the magnitude of the current flowing out from the memory cell strings detected by the one or more current sensing units.

Abstract: Disclosed is a 3D architecture of ternary content-addressable memory (TCAM), comprising a first transistor layer, a second transistor layer, a third transistor layer and a fourth transistor layer. The first transistor layer and the second transistor layer are disposed on a first plane. The third transistor layer and the fourth transistor layer are respectively stacked on the first transistor layer and the second transistor layer in a second direction perpendicular to the first plane. Two of the first transistor layer, the second transistor layer, the third transistor layer and the fourth transistor layer are a first transistor and a second transistor of a first memory cell of the TCAM. The other two of the first transistor layer, the second transistor layer, the third transistor layer and the fourth transistor layer are a first transistor and a second transistor of a second memory cell of the TCAM.

Abstract: A TCAM comprises a plurality of first search lines, a plurality of second search lines, a plurality of memory cell strings and one or more current sensing units. The memory cell strings comprise a plurality of memory cells. Each of the memory cells is coupled to one of the first search lines and one of the second search lines. The current sensing units, coupled to the memory cell strings. In a search operation, a determination that whether any of the data stored in the memory cell strings matches a data string to be searched is made according to whether the one or more current sensing units detect current from the memory cell strings, or according to the magnitude of the current flowing out from the memory cell strings detected by the one or more current sensing units.

Abstract: Disclosed is a 3D architecture of ternary content-addressable memory (TCAM), comprising a first transistor layer, a second transistor layer, a third transistor layer and a fourth transistor layer. The first transistor layer and the second transistor layer are disposed on a first plane. The third transistor layer and the fourth transistor layer are respectively stacked on the first transistor layer and the second transistor layer in a second direction perpendicular to the first plane. Two of the first transistor layer, the second transistor layer, the third transistor layer and the fourth transistor layer are a first transistor and a second transistor of a first memory cell of the TCAM. The other two of the first transistor layer, the second transistor layer, the third transistor layer and the fourth transistor layer are a first transistor and a second transistor of a second memory cell of the TCAM.

Abstract: A smart adjustment system is provided, which may include a cloud computing device and a data acquisition device. The cloud computing device may include a neural network model saving the model data of machine tools, and the estimated increase percentages of each machine tool in different cutting parameters. The data acquisition device may receive the model data of a target machine tool. The could computing device may compare the model data of the target machine tool with the model data of the machine tools via the neural network model in order to calculate an estimated cutting parameter with an estimated increase percentage and control the target machine tool to perform a machining process by the estimated cutting parameter.

Abstract: A portable machine health monitoring system, applied for diagnosing a machine in operation, includes an installation device and a portable monitoring box. The installation device includes a plurality of sensing assemblies and a plurality of connecting assemblies. Each of the plurality of sensing assemblies is connected with the corresponding connecting assembly. Each of the plurality of connecting assemblies mounts the corresponding sensing assembly in a non-destructive manner onto a detected position on the machine. Each of the plurality of sensing assemblies is used for detecting a motion signal at the corresponding detected position on the machine in operation. The portable monitoring box, connected with the installation device, includes an analysis module for receiving the motion signal and further for calculating a health status information according to the detected motion signal.

Abstract: A device in a data processing system for training machine learning models receives a transaction and forwards it to at least one of a plurality of integrated control action models that use outputs of one model as inputs to other models. The models are machine learning models jointly trained for taking each control action of a plurality of control actions on the transaction to maximize an objective function based on probabilities of the control actions matching corresponding target control actions. The machine learning models include a risk model that outputs risk prediction information for a first control action that indicates whether or not to initiate processing of the transaction. The device further receives the risk prediction information from the risk model, and executes at least the first control action based on the risk prediction information.

Abstract: A device in a data processing system for training machine learning models receives a transaction and forwards it to at least one of a plurality of integrated control action models that use outputs of one model as inputs to other models. The models are machine learning models jointly trained for taking each control action of a plurality of control actions on the transaction to maximize an objective function based on probabilities of the control actions matching corresponding target control actions. The machine learning models include a risk model that outputs risk prediction information for a first control action that indicates whether or not to initiate processing of the transaction. The device further receives the risk prediction information from the risk model, and executes at least the first control action based on the risk prediction information.

Abstract: A smart adjustment system is provided, which may include a cloud computing device and a data acquisition device. The cloud computing device may include a neural network model saving the model data of machine tools, and the estimated increase percentages of each machine tool in different cutting parameters. The data acquisition device may receive the model data of a target machine tool. The could computing device may compare the model data of the target machine tool with the model data of the machine tools via the neural network model in order to calculate an estimated cutting parameter with an estimated increase percentage and control the target machine tool to perform a machining process by the estimated cutting parameter.

Abstract: Disclosed are a method and apparatus for detecting the content of oleic acid by optical fiber, and manufacturing method of the apparatus. By the principle of Surface Plasmon Resonance (SPR), a metal layer in a sensing region excites an analyte of oleic acid to produce a plasmon resonance, and a physical property of the plasmon resonance such as a resonant wavelength is measured to define the concentration of oleic acid of the analyte, so that the present invention can measure the concentration of oleic acid accurately and quickly to reduce the time and cost of detecting the oleic acid effectively, so as to improve the efficiency of detecting the oleic acid.

Abstract: The present invention relates to an annular scanning device for optical tomography scanning and imaging system, which comprises a carrying base, a rotating member, a plurality of optical channel modules, and a driving module. The rotating member is disposed on the carrying base. The plurality of optical channel modules are disposed annularly on the rotating member and connected to the rotating member. When the driving module drives the rotating member to rotate, a plurality of optical channel assemblies of the plurality of optical channel modules move towards or away from the center of the rotating member for adjusting the distance between the plurality of optical channel assemblies and an object under test.

Abstract: Methods and systems for efficient retrieval of neighboring measurement values in order to enable fast execution of rule-based error correction are disclosed. In one aspect, a method for data normalization using multi-key sorting is disclosed. In some embodiments, the method includes receiving, by a data organization engine, a set of uncorrected data including corresponding neighboring data. In various embodiments, the data organization engine organizes the uncorrected data by construction of a directed acyclic graph (DAG), where the DAG includes a plurality of nodes. In some embodiments, the data organization engine may traverse the plurality of nodes to retrieve the corresponding neighboring data. Upon retrieval of the neighboring data, a rule-based correction engine may correct the uncorrected data utilizing the retrieved corresponding neighboring data.

Abstract: The present invention relates to an annular scanning device for optical tomography scanning and imaging system, which comprises a carrying base, a rotating member, a plurality of optical channel modules, and a driving module. The rotating member is disposed on the carrying base. The plurality of optical channel modules are disposed annularly on the rotating member and connected to the rotating member. When the driving module drives the rotating member to rotate, a plurality of optical channel assemblies of the plurality of optical channel modules move towards or away from the center of the rotating member for adjusting the distance between the plurality of optical channel assemblies and an object under test.

Abstract: Methods and systems for efficient retrieval of neighboring measurement values in order to enable fast execution of rule-based error correction are disclosed. In one aspect, a method for data normalization using multi-key sorting is disclosed. In some embodiments, the method includes receiving, by a data organization engine, a set of uncorrected data including corresponding neighboring data. In various embodiments, the data organization engine organizes the uncorrected data by construction of a directed acyclic graph (DAG), where the DAG includes a plurality of nodes. In some embodiments, the data organization engine may traverse the plurality of nodes to retrieve the corresponding neighboring data. Upon retrieval of the neighboring data, a rule-based correction engine may correct the uncorrected data utilizing the retrieved corresponding neighboring data.