Abstract: This disclosure provides a cooperative path planning method and device for automatic control aerocraft and aerocraft system. The method includes: determining the current evaluation index of each selected point according to its current position, the target position of the aerocraft and the position of obstacles in the selected area; updating the adjustment displacement of each selected point according to its adjustment displacement, current position and historical optimal position, as well as the global optimal position; updating the current position of each selected point according to its current position and the updated adjustment displacement; after the current position is updated for a set number of times, selecting the position corresponding to the optimal evaluation index from the current positions and global optimal position of all selected points as the next waypoint of the aerocraft.

Abstract: A computer-implemented method, system, and computer program product are provided for enhanced search strategies. The method includes selecting, by a processor device, known candidate sources related to a search topic. The method also includes ranking, by the processor device, keyphrase candidates from the known candidate sources according to inter-topic weighting. The method additionally includes assembling, by the processor device, a search string of a predetermined number of top ranked keyphrase candidates. The method further includes generating, by the processor device, new candidate sources from a candidate source repository responsive to the search string. The method also includes defining, by the processor device, a candidate source pool by the known candidate sources and the new candidate sources to reduce user search times on computer interface devices.

Abstract: A machine learning based medical data classification method is provided. The method includes: a medical data classification request including medical record information is received; a preset medical term base is obtained, and word segmentation is performed on the medical record information according to medical terms in the medical term base to obtain multiple text vectors; features of the multiple text vectors are extracted to obtain multiple text vectors and corresponding feature dimension values; a target classifier is trained with multiple pieces of medical data, and the multiple text vectors and the corresponding feature dimension values are traversed and calculated; until a target node corresponding to the multiple text vectors is traversed, class probabilities corresponding to the multiple text vectors are calculated according to the target node, and a class result corresponding to the medical record information is obtained according to the class probabilities and is pushed to a terminal.

Abstract: Systems and methods having friction reducer compositions for use in subterranean treatment fluids are presented. An embodiment is a method comprising: (A) forming a treatment fluid comprising: an aqueous base fluid, a friction reducer, and an alkaline buffering agent, wherein the treatment fluid has a pH in the range of about 7 to about 10; and (B) injecting the treatment fluid into a wellbore penetrating at least a portion of a subterranean formation at a pressure sufficient to create or enhance one or more fractures within the subterranean formation.

Abstract: The application discloses a method for knowledge extraction based on TextCNN, comprising: S10, collecting first training data, and constructing a character vector dictionary and a word vector dictionary; S20, constructing a first convolutional neural network, and training the first convolutional neural network based on a first optimization algorithm, the first convolutional neural network comprises a first embedding layer, a first multilayer convolution, and a first softmax function connected in turn; S30, constructing a second convolutional neural network, and training the second convolutional neural network based on a second optimization algorithm, the second convolutional neural network comprises a second embedding layer, a second multilayer convolution, a pooling layer, two fully-connected layers and a second softmax function, the second embedding layer connected in turn; S40, extracting a knowledge graph triple of the to-be-predicted data according to an entity tagging prediction output by the first trai

Abstract: Patient treatment may be optimized using Recurrent Neural Network (RNN) based state simulation and Reinforcement learning (RL) techniques to simulate future states and actions. A RNN state simulator and a RL action generator may be trained using patient data such as historical states and actions. The RL action generator may be optimized by applying the RNN state simulator to simulating future states and applying the RL action generator to generate recommended actions based on the simulated future states. This process may be iteratively performed until a computational convergence is reached by the RL action generator which may indicate that the RL action generator has been optimized. A patient state may be fed into the optimized RL action generator to generate an optimal recommended treatment action.

Abstract: An online system maintains an identity graph having links between different types of user identifying information (e.g., email addresses, phone numbers, user identifiers) describing various users of the online system. Based on information received from various sources describing relationships between different types of user identifying information describing a user, the online system generates confidence values for each link between different types of user identifying information. In some embodiments, a confidence value accounts for an amount of time since information describing a relationship between different types of user identifying information was received from a source.

Abstract: A memory management method is provided according to the invention. The method includes: reading a physical unit and updating a read count of the physical unit; scanning the physical unit if the updated read count is not less than a read count threshold; and adjusting the read count threshold according to the read count and a read error bit. Therefore, a data unit that needs to be scanned can be determined to reduce unnecessary data scanning.

Abstract: The present disclosure provides a method for adjusting a position of a photosensitive chip of an image acquisition device. The method may include determining a first symmetrical axis and a second symmetrical axis of the photosensitive chip. The first symmetrical axis may divide the photosensitive chip into a first portion and a second portion, and the second symmetrical axis may divide the photosensitive chip into a third portion and a fourth portion. The method may further include adjusting the position of the photosensitive chip from an initial position to an adjusted position. When the photosensitive chip is at the adjusted position, a first image resolution corresponding to the first portion may be substantially equal to a second image resolution corresponding to the second portion, and a third image resolution corresponding to the third portion may be substantially equal to a fourth image resolution corresponding to the fourth portion.

Abstract: The present disclosure relates to the technical field of natural language understanding, and provides a method, a terminal and a medium for generating a text based on a self-encoding neural network. The method includes: obtaining a text word vector and a classification requirement of a statement to be input; reversely inputting the text word vector into a trained self-encoding neural network model to obtain a hidden feature of an intermediate hidden layer of the self-encoding neural network model; modifying the hidden feature according to a preset classification scale and the classification requirement; defining the modified hidden feature as the intermediate hidden layer of the self-encoding neural network model, and reversely generating a word vector corresponding to an input layer of the self-encoding neural network model by the intermediate hidden layer; and generating the corresponding text, according to the generated word vector.

Abstract: The application discloses an intelligent data analysis method and device, a computer device, and a storage medium. The intelligent data analysis method includes that: a public opinion factor obtained and a public opinion index carrying a time label are taken as first portrait data (S40); original sample data is obtained based on the first portrait data and medical data; the original sample data is cleaned to obtain sample data to be processed (S50); lag processing is performed on the sample data to be processed to obtain lag sample data (S60); feature expansion is performed on the lag sample data to obtain target sample data (S70); and an improved multi-granularity cascading random forest algorithm is used to train the target sample data to obtain a target forecast model (S80); the improved multi-granularity cascading random forest algorithm includes a pooling layer, which is used for retaining data features (S90).

Abstract: Methods for treating subterranean formations are provided. In one embodiment, the methods comprise providing a treatment fluid comprising an aqueous base fluid and a surfactant comprising an ethoxylated amine or derivative thereof; introducing the treatment fluid into a wellbore penetrating at least a portion of a subterranean formation; and producing fluids from the wellbore during or subsequent to introducing the treatment fluid into the wellbore.

Abstract: The present invention relates to pharmaceutical compositions of ramelteon and methods of use thereof. More specifically, the present invention relates to pharmaceutical compositions of ramelteon for use in the treatment of insomnia and jet lag by transmucosal administration. The present invention achieved faster onset of pharmacological effects by delivery of low dosage of ramelteon via intranasal or sublingual routes, as compared to conventional oral tablet administration.

Abstract: A method for image stitching is provided. The method may include obtaining a reference image of a first portion of a subject and a target image of a second portion of the subject, and determining at least one pair of feature points based on a preliminary registration accuracy. The first and second portions may at least partially overlap with each other. Each pair may include a reference feature point in the reference image and a target feature point in the target image that matches the reference feature point. For each pair, the method may further include determining an updated pair of feature points based on a superior registration accuracy higher than the preliminary registration accuracy and a neighboring region of the target feature point of the pair. The method may further include generating a stitched image based on the at least one updated pair.

Abstract: A method may include obtaining a breast image of an object that is acquired by an imaging device; determining a projection curve based on the breast image; determining a first valley point and a second valley point of the projection curve; determining a peak point of the projection curve based the first valley point and the second valley point of the projection curve; determining a first valley location, a second valley location, and a peak location in the breast image based on the peak point, the first valley point, and the second valley point of the projection curve; and determining a breast region in the breast image based on the first valley location, the second valley location, and the peak location.

Abstract: A mitochondrion-targeting protein nanoparticle, containing related information such as an amino acid sequence thereof, a coding nucleic acid sequence, and a vector and a host expression bacterium for the coding nucleic acid. Under the induction of metal ions, the self-assembled protein nanoparticle mentioned above can be obtained by an Escherichia coli expression system. The protein nanoparticle can be applied in cancer diagnosis and treatment. Compared with existing mitochondrion-targeting small molecules (such as TPP and MPP), the protein nanoparticle can achieve properties of tumor enrichment, mitochondrion targeting, increasing of ROS content in cells, induction of cell apoptosis, inhibiting tumor growth, etc.

Abstract: A method may include: preparing or providing an aqueous fluid containing iron ions; screening at least one iron control agent against the aqueous fluid; selecting at least one iron control agent and iron control agent concentration based at least in part on the step of screening; and preparing a fracturing fluid comprising an aqueous base fluid and the at least one iron control agent wherein a concentration of the iron control agent in the fracturing fluid is greater than or equal to the selected iron control agent concentration.

Abstract: A method of preparing a fracturing fluid comprising: preparing or providing an aqueous fluid containing iron ions; screening a plurality of friction reducers against the aqueous fluid wherein the plurality of friction reducers are anionic, cationic, nonionic, amphoteric, or combinations thereof; selecting at least one friction reducer from the plurality of friction reducers based at least in part on the step of screening; and preparing a fracturing fluid including the at least one friction reducer.

Abstract: A method of training a random forest model, an electronic device and a storage medium. The method of training the random forest model includes analyzing, by a system of controlling model training, whether model training conditions are met or not; if the model training conditions are met, determining whether reconstructive training needs to be carried out on the random forest model or not; if the reconstructive training needs to be carried out on the random forest model, carrying out the reconstructive training on the random forest model by using sample data; if the reconstructive training does not need to be carried out on the random forest model, carrying out corrective training on the random forest model by using the sample data.

Abstract: Compositions and methods of using of such compositions to, for example, inhibit shale are provided. In one embodiment, the methods include introducing an additive including a cationic clay stabilizer and an anionic clay stabilizer into a treatment fluid; and introducing the treatment fluid into a wellbore penetrating at least a portion of a subterranean formation. In some embodiments, the methods include introducing an additive including a cationic shale inhibitor and an anionic shale inhibitor into a treatment fluid; and introducing the treatment fluid into a wellbore penetrating at least a portion of a subterranean formation.