Abstract: A method for preparing unrefined sustainable aviation fuel (SAF) includes: adding a catalyst to a reaction kettle, then adding a polyol solution to fill the reaction kettle; sealing the reaction kettle, introducing gas into the reaction kettle to discharge excess polyol solution and replace the atmosphere in the reaction kettle; stirring thoroughly to mix the catalyst uniformly with the polyol solution; then continuing to introduce gas into the reaction kettle to increase the internal pressure; subsequently conducting the reaction, and after the reaction is completed, collecting the upper liquid product to obtain unrefined SAF. The invention employs a one-pot method to prepare unrefined SAF, utilizing the interaction between polyols and solvents to provide H2 for the system, thereby achieving carbon chain growth and hydrodeoxygenation without the need for high-pressure H2.

Abstract: An underwater detection device includes a surface drive boat and an unmanned underwater vehicle. The surface drive boat includes: a hull; transverse attitude-stabilizing thrusters and orbit vectored thrusters arranged at the bottom of the hull; a control box arranged on the hull and electrically connected with the transverse attitude-stabilizing thrusters and the orbit vectored thrusters; a cable and a cable winding assembly arranged on the hull, the control box being connected with the unmanned underwater vehicle by the cable, the cable winding assembly being electrically connected with the control box; and a positioning assembly arranged on the hull and electrically connected with the control box.

Abstract: The invention discloses a multi-stage shock absorption and seismic resistance system for urban underground comprehensive pipe tunnels. It includes a pipe gallery tunnel and pipeline grooves. Inside the tunnel, a multi-segment active cavity with multiple arc-shaped inner cavity walls forms a pipe shape with the same axis line as the tunnel. Each inner cavity wall has a sealing elastic contact pad, ensuring a tight seal. Adjacent active cavities connect end to end, forming an inner tunnel body that extends with the pipe tunnel. The outer wall of the inner cavity is fixed to the tunnel's inner wall by a fixed frame. The pipeline groove is installed on the inner wall of the inner cavity through a telescopic frame. The inner tunnel body can swing up and down or left and right, absorbing transverse and longitudinal earthquake waves and resisting impact and collapse.

Abstract: An underwater detection device includes a surface drive boat and an unmanned underwater vehicle. The surface drive boat includes: a hull; transverse attitude-stabilizing thrusters and orbit vectored thrusters arranged at the bottom of the hull; a control box arranged on the hull and electrically connected with the transverse attitude-stabilizing thrusters and the orbit vectored thrusters; a cable and a cable winding assembly arranged on the hull, the control box being connected with the unmanned underwater vehicle by the cable, the cable winding assembly being electrically connected with the control box; and a positioning assembly arranged on the hull and electrically connected with the control box.

Abstract: A modular mechanical arm of an underwater pile foundation structure includes a modular interface disposed at one end of the transmission arm rod, a mechanical arm connecting part disposed at the other end of the transmission arm rod. The mechanical arm connecting part is separately provided with two arm frames, each of the arm frames comprises an inner arm frame and an outer arm frame, the inner arm frame and the outer arm frame are coupled by a joint, and a soft moving and cleaning part is disposed on an inner side of each of the arm frames; the modular interface is coupled with an underwater UAV interface to transmit current and a control signal, a waterproof steering gear is built in the transmission arm rod to receive the control signal.

Abstract: Provided are a data storage method, a storage device, a server and a storage medium, the method includes: obtaining, by a server, image data of different dimensions (S11); according to the association identity carried by each of the image data, determining, by the server, the image data of the different dimensions with the same association identity as association data (S12); sending the image data of the different dimensions included in the association data to target data tables of databases with different dimensions for storage, respectively (S13), wherein, the databases of different dimensions are located in the same storage apparatus, regarding the target data tables of the database of different dimensions, the table name prefixes of the target data tables are different, but the table name suffixes are the same. This method can store image data in association, meanwhile, when performing associated query, the loss of associated data can be avoided.

Abstract: The present invention discloses a preparation method of a cotton bast fiber and chitosan composite non-woven fabric for filtration and belongs to the technical field of fiber materials. The preparation method adopts steam flash explosion for pretreatment to separate cotton bast first, then a papermaking method is used for forming, finally chitosan is added to enhance the mechanical performance and improve the filtration efficiency, and a technological process is simple, environmentally friendly and suitable for industrial production. The non-woven fabric adopts lignin-rich cotton bast fibers and chitosan as raw materials, so that the non-woven fabric has good antibacterial performance. The cotton bast and chitosan used in the preparation method are both bio-based materials which can be degraded in the natural environment after use, so that burdens caused to the environment are reduced.

Abstract: Provided are a data storage method, a storage device, a server and a storage medium, the method includes: obtaining, by a server, image data of different dimensions (S11); according to the association identity carried by each of the image data, determining, by the server, the image data of the different dimensions with the same association identity as association data (S12); sending the image data of the different dimensions included in the association data to target data tables of databases with different dimensions for storage, respectively (S13), wherein, the databases of different dimensions are located in the same storage apparatus, regarding the target data tables of the database of different dimensions, the table name prefixes of the target data tables are different, but the table name suffixes are the same. This method can store image data in association, meanwhile, when performing associated query, the loss of associated data can be avoided.

Abstract: The present invention discloses a preparation method of a cotton bast fiber and chitosan composite non-woven fabric for filtration and belongs to the technical field of fiber materials. The preparation method adopts steam flash explosion for pretreatment to separate cotton bast first, then a papermaking method is used for forming, finally chitosan is added to enhance the mechanical performance and improve the filtration efficiency, and a technological process is simple, environmentally friendly and suitable for industrial production. The non-woven fabric adopts lignin-rich cotton bast fibers and chitosan as raw materials, so that the non-woven fabric has good antibacterial performance. The cotton bast and chitosan used in the preparation method are both bio-based materials which can be degraded in the natural environment after use, so that burdens caused to the environment are reduced.

Abstract: Functionality is described herein for transforming first and second symbolic linguistic items into respective first and second continuous-valued concept vectors, using a deep learning model, such as a convolutional latent semantic model. The model is designed to capture both the local and global linguistic contexts of the linguistic items. The functionality then compares the first concept vector with the second concept vector to produce a similarity measure. More specifically, the similarity measure expresses the closeness between the first and second linguistic items in a high-level semantic space. In one case, the first linguistic item corresponds to a query, and the second linguistic item may correspond to a phrase, or a document, or a keyword, or an ad, etc. In one implementation, the convolutional latent semantic model is produced in a training phase based on click-through data.

Abstract: Functionality is described herein for transforming first and second symbolic linguistic items into respective first and second continuous-valued concept vectors, using a deep learning model, such as a convolutional latent semantic model. The model is designed to capture both the local and global linguistic contexts of the linguistic items. The functionality then compares the first concept vector with the second concept vector to produce a similarity measure. More specifically, the similarity measure expresses the closeness between the first and second linguistic items in a high-level semantic space. In one case, the first linguistic item corresponds to a query, and the second linguistic item may correspond to a phrase, or a document, or a keyword, or an ad, etc. In one implementation, the convolutional latent semantic model is produced in a training phase based on click-through data.

Abstract: Described is a technology by which software instrumentation data collected from user program sessions are analyzed to output an analysis report or the like via example methods and an architecture configured for efficient operation. A client component queries a service for analysis related information. To process the query, the service works with a data manager, and via a high dimensional analysis component may use information processed from the software instrumentation data, such as in the form of one or more inverted indexes and/or raw value files. The service may include a usage analysis component, a feature recognition component that locates features from command sequences, a user recognition component and/or a program reliability component. One or more counterpart components at the client may generate analysis reports or the like based on the query results. The client also may maintain user libraries and feature libraries to facilitate analyses.

Abstract: In a distributed system environment, a system profiling log can be used at a central server to collect and analyze log data. The log data can be used to gauge performance of software applications. In particular, the log data includes different activities (i.e., tasks) that are executed to implement the software applications. Correlation of the different activities versus a timeline is an important parameter in the system profiling log. For example, where the correlation of the different activities is represented in colored graphs at a user interface, a user may easily pinpoint a bottleneck. The bottleneck at the one or more activities may encourage the user to adopt system improvement in the distributed system environment.

Abstract: Described is a technology by which high dimensional source data corresponding to rows of records with identifiers, and columns comprising dimensions of data values, are processed into a file model for efficient access. An inverted index corresponding to any dimension is built by mapping data from raw dimension values to mapped values based on mapping entries in a dimension table. The record identifiers are arranged into subgroups based on their mapped value; a count and/or an offset may be maintained for locating each of the subgroups. The raw values for a dimension are maintained within a raw value file. For sparse data, the raw value file may be compressed, e.g., by excluding nulls and associating a record identifier with each non-null. A data manager provides access to data in the data files, such as by offering various functions, using caching for efficiency.