Abstract: The invention relates to a fulvestrant intermediate and a preparation method thereof. Specifically, the invention relates to a compound shown as a formula V and a preparation method thereof, and R1 is hydrogen or a hydroxyl protecting group. The invention also relates to a preparation method for the synthesis of fulvestrant from the compound as shown in the formula V. The method has the advantages of short reaction steps, mild and safe reaction conditions, high selectivity, simplicity and convenience in operation and purification, high synthesis efficiency and the like, and is suitable for large-scale production.

Abstract: Disclosed in the present invention are a camptothecin derivative intermediate, and a preparation method therefor and the use thereof. The structural formula of the camptothecin derivative intermediate of the present invention is as shown in formula (I), and the definition of each substituent is as described in the description and claims. The intermediate (I) of the present invention can be used for preparing an intermediate (III), and can be further used for preparing exatecan and a derivative thereof. The preparation method of the present invention has the advantages of cheap and easily available raw materials, a novel method and simple route, mild conditions, a high yield, few by-products, suitability for scale-up synthesis and industrial production, etc.

Abstract: Disclosed are a camptothecin compound as shown in general formula (I), and a preparation method therefor and a use thereof, the definition of each group being as set forth in the description. The compound of the present invention has good antitumor activity and good application prospects.

Abstract: A system trains models to generate embeddings that represent likelihoods associated with features. For example, an embedding may be generated for users and pages such that a user's embedding represents how likely a user is to comment on a given page. Initially, memory space for storing each embedding may be overprovisioned. The system monitors the embeddings for a feature as they are generated and recalculated over time. If the system detects that a particular index value is never updated for embeddings of that feature, then the system may remove that value from the feature embeddings. This allows the array lengths of embeddings to be customized to the particular features they represent, saving memory space. The system may further use related information to identify pooling functions that are most effective for particular features, to identify similarities between entities, and to provide insight into how the feature data influences neural network layers.

Abstract: A preprocessing module of a neural network has a first input and second input. The module generates multiple, different first latent vector representations of its first input, and multiple, different second latent vector representations of its second input. The module then models pairwise interactions between every unique pairwise combination of the first and second latent vector representations. The module then produces an intermediate output by combining the results of the modeled pairwise interactions.

Abstract: In one embodiment, a method includes a preprocessing stage of a neural network model, where the preprocessing stage includes first and second preprocessing modules. Each of the two modules has first input that may receive a dense input and a second input that may receive a sparse input. Each module generates latent vector representations of their respective first and second inputs, and combine the latent vectors with the original first input to define an intermediate output. The intermediate output of the first module is fed into the first input of the second module.

Abstract: The present invention provides a compound as shown in general formulas (I) or (II) and a pharmaceutically acceptable salt, an isomer or a mixture form thereof, a solvate, a polymorph, a stable isotope derivative, or a prodrug of the same. The compound of the present invention has CDK kinase inhibitory activity and can be used in treating a disease related to CDK kinase, such as a cancer.

Abstract: A preprocessing module of a neural network has a first input and second input. The module generates multiple, different first latent vector representations of its first input, and multiple, different second latent vector representations of its second input. The module then models pairwise interactions between every unique pairwise combination of the first and second latent vector representations. The module then produces an intermediate output by combining the results of the modeled pairwise interactions.

Abstract: In one embodiment, a method includes a preprocessing stage of a neural network model, where the preprocessing stage includes first and second preprocessing modules. Each of the two modules has first input that may receive a dense input and a second input that may receive a sparse input. Each module generates latent vector representations of their respective first and second inputs, and combine the latent vectors with the original first input to define an intermediate output. The intermediate output of the first module is fed into the first input of the second module.

Abstract: A telephony system (10) for communication over a network includes a kernel space (110), a media express processor operating environment (120) for providing a set of software facilities for task synchronization, and a user space (130). The kernel space includes a board support package (111), a ucLinux module (112), a digital signal processor interface module (113), a transfer control protocol/Internet protocol (TCP/IP) stack (114) for performing TCP/IP, and a real-time transport protocol/real-time transport control protocol module (115). The user space includes a digital signal processor manager (132), an H.323/session initiation protocol (H.323/SIP) stack (133) for performing H.323 protocol or SIP, a system managing module (134), an event dispatcher (135), a line state machine (136), a call manager (137), a call logging module (138), and a directory module (139) for storing, editing, searching and removing contact information of users.

Abstract: A telephony system (10) for communication over a network includes a kernel space (110), a media express processor operating environment (120) for providing a set of software facilities for task synchronization, and a user space (130). The kernel space includes a board support package (111), a ucLinux module (112), a digital signal processor interface module (113), a transfer control protocol/Internet protocol (TCP/IP) stack (114) for performing TCP/IP, and a real-time transport protocol/real-time transport control protocol module (115). The user space includes a digital signal processor manager (132), an H.323/session initiation protocol (H.323/SIP) stack (133) for performing H.323 protocol or SIP, a system managing module (134), an event dispatcher (135), a line state machine (136), a call manager (137), a call logging module (138), and a directory module (139) for storing, editing, searching and removing contact information of users.