Abstract: Use of pentoxifylline (PTX) in preparation of a medicament for repairing endothelial glycocalyx damage, and belongs to the technical field of medicine. A chlorine-induced endothelial glycocalyx damage model is established. After the endothelial glycocalyx damage model is successfully established, the PTX is intraperitoneally injected into a rat with endothelial glycocalyx damage. The result shows that the PTX effectively repairs shedding of glycosaminoglycans and syndecans in the endothelial glycocalyx damage and significantly downregulates the expression of inflammatory factors including tumor necrosis factor alpha (TNF-?), interleukin-6 (IL-6), and matrix metallopeptidase 13 (MMP-13). Therefore, the PTX can effectively repair the endothelial glycocalyx damage, providing a new theoretical basis for repairing the endothelial glycocalyx damage. Furthermore, with high safety, the PTX has the prospect of being developed into the medicament for repairing the endothelial glycocalyx damage.

Abstract: This application provides a communication method, a terminal device, and a storage medium. The communication method includes: A first terminal device performs a Wi-Fi P2P service in response to a first operation of a user, where the first terminal device uses a first channel to perform the Wi-Fi P2P service, and a bandwidth of the first channel is a maximum bandwidth supported by the first terminal device, and is 80 MHz or 160 MHz. When detecting that a signal-to-noise ratio and/or a channel load of the first channel meet a first preset condition, the first terminal device switches from the first channel to a second channel to perform the Wi-Fi P2P service, where a bandwidth of the second channel is 20 MHz or 40 MHz.

Abstract: A mechanism is provided for automatically detecting, diagnosing, transporting, and repairing devices having failed during burn-in testing. Embodiments provide a system that monitors devices undergoing burn-in testing and detecting when a device or a component within a device fails the burn-in test. Embodiments can then alert burn-in-rack monitor personnel of the device failure. Embodiments can concurrently determine the nature of the failure applying a machine learning-based prediction model against log files associated with the failed device. The diagnosis along with a recommended repair strategy can be provided to the repair center as an aid in accelerating the repair process. In addition, the diagnosis can be used to order parts for the repair from a parts depot. In this manner, embodiments can reduce the time for detection, diagnosis, and repair of the failed device.

Abstract: A method of age and gender estimation, comprising receiving an input image, detecting a facial image within the input image, estimating a head pose based on a set of facial image intensities of the facial image, wherein the head pose is expressed as a yaw, a pitch and a roll, determining whether the yaw, the pitch and the roll of the head pose is less than a predetermined threshold, aligning the facial image if the yaw, the pitch and the roll of the head pose are less than the predetermined threshold and predicting an age and a gender of the aligned facial image.

Abstract: A chip detection device, a chip detection system and a control method. The chip detection device includes a support plate (100), a probe holder (110) disposed on an upper part of the support plate (100), a detection platform, and a first driving device (120) connected to the probe holder (110). The chip detection system includes a cabinet (600), which is internally provided with a chip detection device, a controller, a loading manipulator (910), an unloading manipulator (920), a chip tray bracket (700) disposed on a side of the loading manipulator (910), and a distribution tray (800) disposed on a side of the unloading manipulator (920). According to the chip detection device, the chip detection system and the control method, during the rotation of the turntable (200), the filling, detection and classification of the chips are all controlled to be automatically completed under the control of an automatic control program, which greatly improves the efficiency of the chip detection.

Abstract: The disclosed embodiments provide a system for processing data. During operation, the system obtains labels for entities found in portions of text in a first set of jobs. Next, the system inputs the portions of text and the labels as training data for a machine learning model. The system then applies the machine learning model to a second set of jobs to generate predictions of additional entities in additional portions of text in the second set of jobs. Finally, the system creates, based on the predictions, an index containing mappings of the additional entities to subsets of the second set of jobs in which the additional entities are found.

Abstract: Techniques for incorporating sequence encoders into machine-learned models where the sequence encoders operate on bag of words (BOW) input are provided. Tokens that are associated with online activities of an entity are identified. Machine-learned embeddings that correspond to the tokens are identified. Based on one or more ordering criteria that are independent of the temporal occurrence of the online activities of the entity, an order of the machine-learned embeddings is determined. Based on the order, the machine-learned embeddings are inputted to a sequence encoder that generates output. Based on the output, a machine learned model that includes the sequence encoder generates a score. A content item is selected based on the score. The content item is transmitted over a computer network to a computing device.

Abstract: Described herein is machine learning model comprising a neural network that is trained to generate a ranking score for an online job posting. The neural network takes as input a variety of input features, including at least a first input feature that is an encoded representation of a search query as generated by a first Transformer encoder, an encoded representation of a job title as generated by a second Transformer encoder, and an encoded representation of a company name as generated by a third Transformer encoder. Once a plurality of online job postings are ranked, some subset of the plurality are presented in a user interface, ordered based on their respective ranking scores.

Abstract: Hydrocarbon exploration and extraction can be facilitated using machine-learning models. For example, a system described herein can receive seismic data indicating locations of geological bodies in a target area of a subterranean formation. The system can provide the seismic data as input to a trained machine-learning model for determining whether the target area of the subterranean formation includes one or more types of geological bodies. The system can receive an output from the trained machine-learning model indicating whether or not the target area of the subterranean formation includes the one or more types of geological bodies. The system can then execute one or more processing operations for facilitating hydrocarbon exploration or extraction based on the seismic data and the output from the trained machine-learning model.

Abstract: The disclosed embodiments provide a system for performing sequence modeling for searches. During operation, the system obtains a sequence of jobs associated with activity by a member of an online system. Next, the system applies a word embedding model of a set of job histories to attributes of individual jobs in the sequence of jobs to produce embeddings for the individual jobs. The system then generates a set of power means from the embeddings. Finally, the system outputs the set of power means as an encoded representation of the sequence of jobs, wherein the set of power means is used in generating job recommendations related to the member.

Abstract: Methods, systems, and computer programs are presented for improved search methods based on career transition embeddings. One method includes an operation for generating career transition vectors for members of an online service, each career transition vector comprising identifiers associated with the career transitions of each member. The method further includes operations for performing a similarity analysis of the career transition vectors to generate an embedding vector for each identifier, detecting access of a first member to a job search user interface, and selecting one or more top embedding vectors based on one or more embedding vectors of the first member. One or more search starters associated with the one or more top embedding vectors are generated, and the one or more search starters are presented on the job search user interface.

Abstract: A mechanism is provided for automatically detecting, diagnosing, transporting, and repairing devices having failed during burn-in testing. Embodiments provide a system that monitors devices undergoing burn-in testing and detecting when a device or a component within a device fails the burn-in test. Embodiments can then alert burn-in-rack monitor personnel of the device failure. Embodiments can concurrently determine the nature of the failure applying a machine learning-based prediction model against log files associated with the failed device. The diagnosis along with a recommended repair strategy can be provided to the repair center as an aid in accelerating the repair process. In addition, the diagnosis can be used to order parts for the repair from a parts depot. In this manner, embodiments can reduce the time for detection, diagnosis, and repair of the failed device.

Abstract: The invention discloses a multi-language mixed speech recognition method, which belongs to the technical field of speech recognition; the method comprises: step S1, configuring a multi-language mixed dictionary including a plurality of different languages; step S2, performing training according to the multi-language mixed dictionary and multi-language speech data including a plurality of different languages to form an acoustic recognition model; step S3, performing training according to multi-language text corpus including a plurality of different languages to form a language recognition model; step S4, forming the speech recognition system by using the multi-language mixed dictionary, the acoustic recognition model and the language recognition model; and subsequently, recognizing mixed speech by using the speech recognition system, and outputting a corresponding recognition result.

Abstract: Hydrocarbon exploration and extraction can be facilitated using machine-learning models. For example, a system described herein can receive seismic data indicating locations of geological bodies in a target area of a subterranean formation. The system can provide the seismic data as input to a trained machine-learning model for determining whether the target area of the subterranean formation includes one or more types of geological bodies. The system can receive an output from the trained machine-learning model indicating whether or not the target area of the subterranean formation includes the one or more types of geological bodies. The system can then execute one or more processing operations for facilitating hydrocarbon exploration or extraction based on the seismic data and the output from the trained machine-learning model.

Abstract: Methods, systems, and computer programs are presented for improved search methods based on career transition embeddings. One method includes an operation for generating career transition vectors for members of an online service, each career transition vector comprising identifiers associated with the career transitions of each member. The method further includes operations for performing a similarity analysis of the career transition vectors to generate an embedding vector for each identifier, detecting access of a first member to a job search user interface, and selecting one or more top embedding vectors based on one or more embedding vectors of the first member. One or more search starters associated with the one or more top embedding vectors are generated, and the one or more search starters are presented on the job search user interface.

Abstract: The disclosed embodiments provide a system for selecting recommendations based on title transition embeddings. During operation, the system obtains a word embedding model of a set of job histories. Next, the system calculates similarities between pairs of the embeddings produced by the word embedding model from attributes associated with titles in the set of job histories. The system then identifies, based on the similarities, job titles with high similarity to a current title of the candidate. Finally, the system outputs the job titles for use in selecting job recommendations for the candidate.

Abstract: The disclosed embodiments provide a system for processing data. During operation, the system obtains labels for entities found in portions of text in a first set of jobs. Next, the system inputs the portions of text and the labels as training data for a machine learning model. The system then applies the machine learning model to a second set of jobs to generate predictions of additional entities in additional portions of text in the second set of jobs. Finally, the system creates, based on the predictions, an index containing mappings of the additional entities to subsets of the second set of jobs in which the additional entities are found.

Abstract: The disclosed embodiments provide a system for performing sequence modeling for searches. During operation, the system obtains a sequence of jobs associated with activity by a member of an online system. Next, the system applies a word embedding model of a set of job histories to attributes of individual jobs in the sequence of jobs to produce embeddings for the individual jobs. The system then generates a set of power means from the embeddings. Finally, the system outputs the set of power means as an encoded representation of the sequence of jobs, wherein the set of power means is used in generating job recommendations related to the member.

Abstract: It provides a method for predicting the risk of an adverse pregnancy or neonatal outcome for a pregnant subject by detecting the elevated level of bacteria from one or more selected bacterial taxa (e.g., genera or species). A kit useful for such a method is also provided. In addition, it provides a method for determining the risk of having advanced cervical dilation and/or premature cervical shortening based on differentially abundant bacterial taxa.

Abstract: The disclosed embodiments provide a system for recommending jobs based on title transition embeddings. During operation, the system obtains a word embedding model of job histories of members of an online network. Next, the system applies the word embedding model to a first set of attributes associated with a title of a candidate to produce a first embedding. The system also applies the word embedding model to a second set of attributes associated with a job title of a job to produce a second embedding. The system then calculates a similarity between the first and second embeddings. Finally, the system outputs the similarity for use in recommending the job to the candidate.