Abstract: A preparation method of a Mn-MOF-based cold-adapted nanozyme and a preparation method thereof. The method includes: preparing a Mn(CH3COO)3·2H2O solution by fully dissolving a manganese-containing precursor Mn(CH3COO)3·2H2O in a mixed solution of an alcohol and distilled water; wherein the alcohol is ethanol or methanol; preparing a benzenetricarboxylic acid solution by fully dissolving benzenetricarboxylic acid solid in the mixed solution of the alcohol and distilled water; reacting the Mn(CH3COO)3·2H2O solution with the benzenetricarboxylic acid solution sufficiently using co-precipitation; and centrifuging and removing a supernatant to obtain the MnBTC, where the MnBTC is nano-metal-organic framework (nano-MOF) with a particle size of less than 10 nm.

Abstract: Resource optimized forwarding of classified requests to different instances of a microservice is provided. The process includes obtaining classified requests to a microservice. The classified requests are classified based on different microservice resource consumption types. Further, the method includes forwarding the classified requests to instances of the microservice with different assigned resource configurations. The forwarding is based on the different microservice resource consumption types of the classified requests.

Abstract: A data processing system obtains source textual content associated with a first writing style and target textual content associated with a second writing style and provides the source textual content as an input to a first machine learning model which analyzes the source content to determine the first writing style of the first textual content. The system provides an indication of the first writing style and the target textual content as an input to a second machine learning model which analyzes the target textual content and rewrites the target textual content according to the first writing style to output updated target textual content rewritten according to the first writing style. Some implementations utilize a single model trained to receive the source textual content, the target textual content, to determine the writing style of the source textual content and rewrite the target textual content according to the first writing style.

Abstract: The application relates to a three-section guide rail structure for a massage chair includes a backrest guide rail, a transition guide rail, and a seat guide rail. The transition guide rail is hinged and matched with both the backrest guide rail and the seat guide rail, and each rail has a toothed rack. A first pressing strip is fixed to the backrest guide rail and extends into the transition guide rail, while a second pressing strip is fixed to the seat guide rail and extends into the transition guide rail. This structure makes it easier for the massage mechanism to move between the backrest guide rail and the seat guide rail during the process of lying or lifting the seat.

Abstract: The present disclosure generally provides compounds that antagonize certain T2R taste receptors, including related uses, methods, and compositions for the reduction of bitter taste and/or the enhancement of sweet taste. In certain aspects, the disclosure provides flavored articles or flavored compositions comprising such compounds, as well as uses of such compounds to reduce the bitter taste and/or enhance the sweet taste of such flavored articles or flavored compositions.

Abstract: A system of matching segmented words to check correctness of components of a device and a method thereof are disclosed. String processing and string segmenting is performed on one of component messages of a target device and one of pieces of material data in bill of materials of the target device, to generate component key words and material key words, and the component key words and the material key words are compared with each other, and when a quantity of the matching pairs of the component key words and the material key words reaches a quantity threshold, the component message is determined to match a bill of materials. When all component messages match the bill of materials, a check for the target device is passed.

Abstract: Systems and methods are directed to generating content that is contextually relevant in a writing style of a user. In example embodiments, a plurality of logical inputs regarding a topic is received in bullet point format. A content generator generates draft content using machine learning (ML) models. The generating comprises identifying a writing style of the user by applying the plurality of logical inputs to a first ML model, determining a context and direction for the draft content using a second ML model, and based on the plurality of logical inputs, the identified writing style, and the context and direction, generating at least one paragraph of draft content in the writing style of the user that follows an outline associated with the bullet point format and comprises a same context and direction as the plurality of logical inputs. The draft content is then presented at a client device.

Abstract: An example computer implemented method can include generating feature data based on categorizing and tagging respective transactions in transaction description data, in which the feature data includes category tags specifying respective categories of discrete features and aggregated features for transactions. Each category tag defines a respective variable of a scoring model, and each respective variable has at least one value representative of a respective discrete or aggregated feature based on the transaction description data. The method can also include applying rules to the feature data to provide a first hierarchical decision, in which the rules represent underwriting criteria. The method can also include applying the scoring model to process the feature data and compute a score having a value representing a credit worthiness and/or a likelihood of loan default by the borrower and providing a second hierarchical decision.

Abstract: A method and system for picking first-break times for a seismic dataset are disclosed. The method includes generating a pre-processed seismic dataset and an initial refraction velocity model from the pre-stack seismic dataset and generating a first-break energy-enhanced seismic dataset using nonlinear beamforming applied to the pre-processed seismic dataset and the initial refraction velocity model. The methods further include estimating a refined refraction velocity model from the first-break energy-enhanced seismic dataset, and generating a post-processed seismic dataset from the refined refraction velocity model and first-break energy-enhanced seismic dataset. The methods still further include, for each pre-stack trace, determining a first-break time from the post-processed seismic dataset and the refined refraction velocity model.

Abstract: A system and method for converting a document is described. The system accesses a document comprising one or more section breaks. The system detects sections of the text document demarked by the one or more section breaks and generates a section title metadata and a section summary metadata for each section of the plurality of sections. The system inserts the section title metadata and the section summary metadata at the corresponding section breaks in the text document. The system modifies the text document into slides. Each slide being formed for each section based on the corresponding section title metadata and the section summary metadata. The system generates a presentation document based on the slides.

Abstract: An auxiliary implementation method and apparatus for online prediction using a machine learning model. The method comprises: setting up an online data storage system and an offline data storage system, the online data storage system being used for storing at least part of the data used for implementing feature calculation in an online environment and the offline data storage system being used for storing at least part of the data used for implementing feature calculation in an offline environment (S110); respectively storing data in the online data storage system and the offline data storage system (S120); and, in response to an online prediction request, acquiring at least part of the data needed for online feature calculation from the online data storage system (S130).

Abstract: A packet processing method includes generating, by a processor of a network device, a first encoding task based on M original packets in a to-be-processed first data stream, where M is a positive integer, and where the first encoding task instructs to encode the M original packets; and performing, by a target hardware engine of the network device and based on the first encoding task, forward error correction (FEC) encoding on the M original packets to obtain R redundant packets, where R is a positive integer.

Abstract: A method of preparing a piezoelectric single crystal with high piezoelectricity and near- perfect transparency. The method includes depositing electrodes on two opposition surfaces of a piezoelectric single crystal which is a ferroelectric crystal; AC-poling the piezoelectric single crystal through the electrodes by repeatedly changing polarity of an AC electric field; and after polarization, removing the electrodes on the two opposition surfaces of the piezoelectric single crystal and then depositing Ag nanowire or indium tin oxide (ITO) as electrodes on the two opposition surfaces of the piezoelectric single crystal. Repeatedly changing the polarity of the polarized electric field can increase the domain size of the ferroelectric crystal, or reduce the domain wall density of the domain structure, thereby improving the transparency of the piezoelectric single crystal having high piezoelectric.

Abstract: Embodiments of this application disclose a chunking method and an apparatus for implementing the method. According to the method provided in the embodiments of this application, a first data segment of a first length may be determined starting from a header of a to-be-chunked data flow, a data distribution characteristic of the first data segment is determined based on character values of all characters in the first data segment, and then a chunking position is determined for different data distribution characteristics by using different methods. In this way, a data flow can be better chunked, so as to enhance a deduplication effect.

Abstract: A method and apparatus are disclosed for managing a measurement device based on a blockchain, which is applied to node devices in a blockchain network. The method can include obtaining device state data of the measurement device at various stages in the life cycle of the measurement device; constructing a target transaction based on the obtained device state data, and then sending the target transaction to other node devices in the blockchain network to perform consensus processing on the target transaction; and storing, when a consensus of the target transaction is reached, the target transaction into a distributed ledger of the blockchain network, wherein the target transaction stored in the distributed ledger of the blockchain network is used for life cycle management of the measurement device.

Abstract: A cycling detection method, an electronic device, and a computer-readable storage medium are provided. The cycling detection method includes: obtaining an acceleration signal and an angular velocity signal collected by a wearable device of a user's foot, and analyzing a time-domain feature of the acceleration signal, a frequency-domain feature of the acceleration signal, a time-domain feature of the angular velocity signal, and/or a frequency-domain feature of the angular velocity signal; filtering the acceleration signal and the angular velocity signal to obtain a target acceleration signal and a target angular velocity signal of the user's cycling if it is determined, based on an analysis result, that a current status of the user is a cycling state; and determining a behavior feature of the user's cycling based on the target acceleration signal and the target angular velocity signal, where the behavior feature includes a cadence feature and a foot posture feature.

Abstract: The present disclosure relates to a method and apparatus for displaying page contents, and relates to the field of displaying page contents. The display method includes: displaying a current image content in a content browsing page, wherein the current image content is a first content in a content stream; displaying relevant text information of the current image content in response to an interaction performed by a content browsing user; during the display process of the relevant text information, in response to an interaction performed again by the content browsing user, displaying a second content different from the first content in the content stream.

Abstract: An air supply assembly for a refrigerator, includes: an air duct cover plate defining, together with a refrigerator liner, an air supply space and configured to isolate the air supply space from a storage space in a compartment of the refrigerator, and a centrifugal wind wheel arranged in the air supply space, and axially sucking air in and blowing the air out towards a peripheral side, wherein a plurality of air return ports are provided in the air duct cover plate to allow air in the storage space to enter the air supply space; and the centrifugal wind wheel abuts against an inner side of the air duct cover plate and is configured to suck air in from a rear side thereof, such that air entering the air supply space via the air return ports is sucked in from the rear side of the centrifugal wind wheel.

Abstract: Systems and methods for reservoir modeling use reservoir simulation and production data to predict future production for one or more wells. The system receives static data of a reservoir or well, receives dynamic data of the reservoir or well, and processes the static data and the dynamic data to generate a reservoir model. For instance, the static data and dynamic data can be used to generate a Voronoi grid, which is used to create a spatio-temporal dataset representing time steps for a focal well and offset wells. The reservoir model can predict reservoir performance, field development, production metrics, and operation metrics. By using one or more Machine Learning (ML) models, the systems disclosed herein can determined reservoir physics in minutes and replicate the physical properties calculated by more complex and computationally intensive reservoir modeling.