Abstract: Disclosed are a polymorph of (S)-1-(2-((S)-3-cyclopropyl-5-isopropyl-2,4-dioxoimidazolidin-1-yl)-5,6-dihydrobenzo[f]imidazo[1,2-d][1,4]oxazepin-9-yl)pyrrolidine-2-carboxamide, a composition comprising the polymorph, a use method therefor and a preparation method therefor.

Abstract: The present invention relates to the use of a medicament in treatment of a tumor disease. In particular, the present invention provides the use of a biologically active conjugate represented by formula (I) in treatment of a tumor disease. The tumor disease particularly and preferably refers to an unresectable locally advanced or metastatic solid tumor that is refractory according to existing treatment standards, including but not limited to breast cancer, gastric cancer, lung cancer, ovarian cancer, urinary tract epithelial cancer, esophageal cancer, liver cancer, colorectal cancer, cervical cancer, endometrial cancer, pancreatic cancer, and brain tumor.

Abstract: A display device and a driving method thereof. The display device includes a display substrate and at least one optical sensing unit; the display substrate includes a light-emitting region and a plurality of pixel units located in the light-emitting region; wherein the light-emitting region comprises a single-sided light-emitting region and at least one double-sided light-emitting region, and each of the pixel units in the plurality of pixel units comprises a plurality of sub-pixels; and the at least one optical sensing unit corresponds to the at least one double-sided light-emitting region from a non-display side of the display substrate, and configured to sense light emitted by the sub-pixels during operation in the at least one double-sided light-emitting region, and to provide sensing brightness information of the at least one double-sided light-emitting region to perform brightness compensation on the light-emitting region.

Abstract: A fixture for testing bending shifting of a flexible display module and a test method thereof are provided. The flexible display module includes a bending region and a first non-bending region and a second non-bending region located at two sides of the bending region, the flexible display module is bent through the bending region, and the first non-bending region or the second non-bending region has an under-screen opening; the fixture includes a first support plate and a second support plate rotatably connected, the first support plate is configured to be fixedly connected with the first non-bending region, and the second support plate is configured to be fixedly connected with the second non-bending region; the first support plate or the second support plate has a transparent region, and the transparent region is disposed for observation of shifting at the under-screen opening of the flexible display module in a bent state.

Abstract: A method and a system for predicting battery health based on distance driven on a full battery load with machine learning model are provided. The method includes: obtaining historical vehicle telematics of vehicles, wherein the historical vehicle telematics comprise at least one of the following: odometer readings, battery SOC, vehicle speed, battery-module temperatures, and battery-cell voltages; creating a distance driven model according to a relationship between a distance driven on a full battery load of vehicles and the historical vehicle telematics; obtaining a distance driven on a full battery load of a vehicle based on the distance driven model by using real-time vehicle telematics of the vehicle as model input; predicting battery health of the vehicle by comparing the obtained distance with a reference distance value.

Abstract: A distributed voltage clamping method for a 100% renewable-energy sending-end grid, including: selecting key nodes from the 100% renewable-energy sending-end grid, including their voltage levels and positions; installing a dynamic reactive power compensation device on each key node, where the dynamic reactive power compensation device is controlled by a constant alternating-current (AC) voltage effective value, and the instruction value of the constant AC voltage effective value is adjustable according to an operation mode; according to AC voltage variation of the sending-end grid under a typical working condition, judging whether the key nodes meet the checking requirements; if not, selecting more key nodes.

Abstract: A Lactobacillus paracasei and uses thereof. The Lactobacillus paracasei has a deposit number of CGMCC No. 14813. The Lactobacillus paracasei can be used for increasing the amount of an organic acid in a raw material. The Lactobacillus paracasei can be used for fermenting the raw material, where the raw material can be selected from at least one of fruits, which can increase the content of the organic acid in a fermented product.

Abstract: Techniques for using enhanced logit values for classifying utterances and messages input to chatbot systems in natural language processing. A method can include a chatbot system receiving an utterance generated by a user interacting with the chatbot system and inputting the utterance into a machine-learning model including a series of network layers. A final network layer of the series of network layers can include a logit function. The machine-learning model can map a first probability for a resolvable class to a first logit value using the logit function. The machine-learning model can map a second probability for a unresolvable class to an enhanced logit value. The method can also include the chatbot system classifying the utterance as the resolvable class or the unresolvable class based on the first logit value and the enhanced logit value.

Abstract: A fastener driving machine, which comprises an energy storage unit; an impact unit used to drive the energy storage unit to store energy and withstand the energy released by the energy storage unit to drive fasteners into a workpiece; a driving mechanism connected to the impact unit; a rotating power mechanism connected to the driving mechanism to provide rotating power to the driving mechanism. The driving mechanism comprises a stationary annular gear, a crank connected to the rotating power mechanism, and at least one planetary gear which is connected to the crank in a spinning manner and revolves with the rotation of the crank relative to the annular gear, and an engaging shaft eccentrically connected to the planetary gear to push the impact unit. The planetary gear is placed in the annular gear to mesh with the annular gear.

Abstract: Techniques for out-of-domain data augmentation for training chatbot systems in natural language processing. In one particular aspect, a method is provided that includes receiving a training set of utterances for training a machine-learning model to identify one or more intents for one or more utterances, and augmenting the training set of utterances with out-of-domain (OOD) examples. The augmenting includes: generating a data set of OOD examples, filtering out OOD examples from the data set of OOD examples, determining a difficulty value for each OOD example remaining within the filtered data set of the OOD examples, and generating augmented batches of utterances comprising utterances from the training set of utterances and utterances from the filtered data set of the OOD based on the difficulty value for each OOD. Thereafter, the machine-learning model is trained using the augmented batches of utterances in accordance with a curriculum training protocol.

Abstract: The present disclosure relates to the field of GNSS and INS integrated navigation technology, and specifically discloses a GNSS and INS integrated navigation positioning method and a system thereof. To addresses the technical problem of positioning error divergence in integrated navigation systems caused by insufficient satellite visibility or strong multipath effects in GNSS denial environments, a method combining motion constraint algorithm and neural network algorithm is proposed for robustness by the present disclosure. The motion constraint algorithm is very stable, but it cannot self-adaptively adjust the constraint threshold based on the vehicle motion state. The neural network algorithm has strong flexibility, but the obtained predicted values inevitably have outliers.

Abstract: Techniques for using logit values for classifying utterances and messages input to chatbot systems in natural language processing. A method can include a chatbot system receiving an utterance generated by a user interacting with the chatbot system. The chatbot system can input the utterance into a machine-learning model including a set of binary classifiers. Each binary classifier of the set of binary classifiers can be associated with a modified logit function. The method can also include the machine-learning model using the modified logit function to generate a set of distance-based logit values for the utterance. The method can also include the machine-learning model applying an enhanced activation function to the set of distance-based logit values to generate a predicted output. The method can also include the chatbot system classifying, based on the predicted output, the utterance as being associated with the particular class.

Abstract: A rapid mining method for sandstone-type uranium resources in a uranium and coal superposed area, which relates to the technical field of mining engineering is provided. The method includes: arranging a high-density adjustable well pattern in an in-situ leaching mining area; determining a length and a position of a filter located on the in-situ leaching mining area through a digital well construction technology; and in a production stage, carrying out operations such as pumping/injection centralized filtration, intensified leaching, high-intensity extraction, high-intensity injection, and change of layout of the high-density adjustable well pattern to rapidly obtain sandstone-type uranium resources in a uranium and coal superposed area. A recovery speed of the sandstone-type uranium resources can be improved, and service life of the in-situ leaching mining area can be shortened.

Abstract: Provided are a pharmaceutical composition of (S)-ketorolac and a preparation method therefor, which belong to the technical field of pharmaceutical preparations. The pharmaceutical composition includes (S)-ketorolac or a pharmaceutically acceptable salt thereof, a stabilizer, a pH-adjusting agent, and an excipient, and the dosage form of the pharmaceutical composition is preferably lyophilized powder injection. The lyophilized powder injection prepared herein has optical purity of an active ingredient greater than or equal to 95% after being stored under long-term stability test conditions for 6 months and optical purity of an active ingredient greater than or equal to 90% after being stored under accelerated stability test conditions for 6 months. The lyophilized powder injection has important use in the preparation of non-steroidal anti-inflammatory drugs with analgesic, anti-inflammatory, antipyretic effects.

Abstract: Generally, the present disclosure is directed to user interface understanding. More particularly, the present disclosure relates to training and utilization of machine-learned models for user interface prediction and/or generation. A machine-learned interface Nprediction model can be pre-trained using a variety of pre-training tasks for eventual downstream task training and utilization (e.g., interface prediction, interface generation, etc.).

Abstract: Techniques for using enhanced logit values for classifying utterances and messages input to chatbot systems in natural language processing. A method can include a chatbot system receiving an utterance generated by a user interacting with the chatbot system and inputting the utterance into a machine-learning model including a series of network layers. A final network layer of the series of network layers can include a logit function. The machine-learning model can map a first probability for a resolvable class to a first logit value using the logit function. The machine-learning model can map a second probability for a unresolvable class to an enhanced logit value. The method can also include the chatbot system classifying the utterance as the resolvable class or the unresolvable class based on the first logit value and the enhanced logit value.

Abstract: Techniques for using logit values for classifying utterances and messages input to chatbot systems in natural language processing. A method can include a chatbot system receiving an utterance generated by a user interacting with the chatbot system. The chatbot system can input the utterance into a machine-learning model including a set of binary classifiers. Each binary classifier of the set of binary classifiers can be associated with a modified logit function. The method can also include the machine-learning model using the modified logit function to generate a set of distance-based logit values for the utterance. The method can also include the machine-learning model applying an enhanced activation function to the set of distance-based logit values to generate a predicted output. The method can also include the chatbot system classifying, based on the predicted output, the utterance as being associated with the particular class.

Abstract: Techniques are disclosed herein for objective function optimization in target based hyperparameter tuning. In one aspect, a computer-implemented method is provided that includes initializing a machine learning algorithm with a set of hyperparameter values and obtaining a hyperparameter objective function that comprises a domain score for each domain that is calculated based on a number of instances within an evaluation dataset that are correctly or incorrectly predicted by the machine learning algorithm during a given trial. For each trial of a hyperparameter tuning process: training the machine learning algorithm to generate a machine learning model, running the machine learning model in different domains using the set of hyperparameter values, evaluating the machine learning model for each domain, and once the machine learning model has reached convergence, outputting at least one machine learning model.

Abstract: Methods are provided for improving performance of a computing system used to model potential crop yield. In one example embodiment, a computer-implemented method includes generating a model of potential crop yield, as a function of planting date and relative maturity based, at least in part, on one or more relative maturity maps, one or more planting date maps, and one or more actual production history maps, and storing the model in a memory of the server computer system. The method also includes receiving, via an interface at a field manager computing device, a selection of a particular field and computing, from the model of potential crop yield, a potential yield for the particular field based, at least in part, on a planting date for the particular field, a relative maturity value, and values representing actual production history for the particular field.

Abstract: Techniques are disclosed herein for continuous hyperparameter tuning with automatic domain weight adjustment based on periodic performance checkpoints. In one aspect, a method is provided that includes initializing a machine learning algorithm with a set of hyperparameter values and obtaining a hyperparameter objective function that is defined at least in part on a plurality of domains of a search space that is associated with the machine learning algorithm. For each trial of a hyperparameter tuning process: running the machine learning algorithm in different domains using the set of hyperparameter values, periodically checking a performance of the machine learning algorithm in the different domains based on the hyperparameter objective function; and continuing hyperparameter tuning with a new set of hyperparameter values after automatically adjusting the domain weights according to a regression status of the different domains.