Abstract: Systems, devices, and methods are discussed for limiting exposure of internal network operations beyond the boundary of a secure network.

Abstract: A three-dimensional reservoir based on three-dimensional volatile memristors and a method for manufacturing the same. In the three-dimensional reservoir, a memory layer, a select layer, and an electrode layer in each via form a memristor which is a reservoir unit. The three-dimensional reservoir is formed based on a stacking structure and multiple vias. The three-dimensional reservoir is constructed by using virtual nodes generated from dynamic characteristics of the three-dimensional memristors. An interfacial memristor is first constructed, and its volatility is verified through electric tests. A vertical three-dimensional array is manufactured based on the volatile memristor. A dynamic characteristic of the memristor is adjusted through a Schottky barrier. Different layers in the three-dimensional reservoir correspond to different reservoirs, which are constructed by controlling memristors in the different layers, respectively.

Abstract: Systems, devices, and methods are discussed for limiting exposure of internal network operations beyond the boundary of a secure network.

Abstract: A temporal-aware or permutation-dependent Graph Neural Network (GNN) is disclosed. The example GNN is implemented by combining temporal-awareness with multi-layer neighborhood aggregation to further provide the GNN with inductive capabilities with respect to generating embeddings of a dynamic graph, all without creating multiple time snapshots of the graph. By using a temporal-aware message pass scheme involving a temporal-aware and permutation-dependent GNN, a set of temporal-aware local neighborhood aggregator functions may be effective trained and used for generating embeddings for unknow nodes and for providing more accurate embeddings for subsequent prediction tasks.

Abstract: A device for simulating carbon dioxide storage in a deep saline aquifer, including a CO2 gas source, first and second valves, first and second pressure pumps, first, second and third pressure gauges, a water storage tank, a simulation box, a first flow meter, a gas-liquid separator, a recycling tank, a microcomputer-display assembly, a structure plate, core holders, an injection pipeline, a connection pipeline, a baffle, a piezometer, a second flow meter, a heater, a lifter and an acoustic logging tool. The CO2 gas source, the first valve, the first pressure pump and the first pressure gauge for gas injection. The water storage tank, a second pressure pump and a second pressure gauge for water injection. The second valve, the third pressure gauge, the first flow meter, the gas-liquid separator and the recycling tank form an output pipeline.

Abstract: A device may receive source compound simplified molecular-input line-entry (SMILE) data, target compound SMILE data, and a latent space representing compounds, and may project the source compound SMILE data and the target compound SMILE data into the latent space to generate a source compound tensor and a target compound tensor, respectively. The device may process the source compound tensor, with one or more pretrained models, to determine a reward for the source compound tensor, and may determine, based on the reward, a direction and a magnitude to move in the latent space from the source compound tensor. The device may move the direction and the magnitude in the latent space to a new compound tensor, and may determine whether the new compound tensor matches the target compound tensor. The device may return a policy based on the new compound tensor matching the target compound tensor.

Abstract: A device may receive a knowledge graph and SMILE data identifying compounds, and may train embeddings based on the knowledge graph. The device may generate graph embeddings for the SMILE data based on the embeddings, and may encode the SMILE data into a latent space. The device may combine the graph embeddings and the latent space to generate a combined latent-embedding space, and may decode the combined latent-embedding space to generate decoded SMILE data. The device may utilize the decoded SMILE data to train an encoder, and may process source SMILE data, with the trained encoder, to generate a source combined latent-embedding space. The device may search the source combined latent-embedding space to identify new SMILE data, and may decode the new SMILE data to generate decoded new SMILE data. The device may evaluate the decoded new SMILE data to identify particular SMILE data associated with a new compound.

Abstract: A device for simulating carbon dioxide storage in a deep saline aquifer, including a CO2 gas source, first and second valves, first and second pressure pumps, first, second and third pressure gauges, a water storage tank, a simulation box, a first flow meter, a gas-liquid separator, a recycling tank, a microcomputer-display assembly, a structure plate, core holders, an injection pipeline, a connection pipeline, a baffle, a piezometer, a second flow meter, a heater, a lifter and an acoustic logging tool. The CO2 gas source, the first valve, the first pressure pump and the first pressure gauge for gas injection. The water storage tank, a second pressure pump and a second pressure gauge for water injection. The second valve, the third pressure gauge, the first flow meter, the gas-liquid separator and the recycling tank form an output pipeline.

Abstract: The application provides methods for designing a pre-activated arch expander, methods and systems for manufacturing a pre-activated arch expander, and pre-activated arch expanders. The method for designing a pre-activated arch expander includes: determining a target arch expansion parameter based on a digital model of an initial dental jaw in an initial dental arch form; determining a digital model of a target dental jaw in a target dental arch form based on the digital model of the initial dental jaw and the target arch expansion parameter; and designing a digital model of a pre-activated arch expander based on the target arch expansion parameter and the digital model of the target dental jaw.

Abstract: A battery case and a battery are provided. The battery case includes a case body. The case body is formed by a sheet-shaped plate being bent and welded. The plate has a first end and a second end. After the case body is bent, the first end is welded to the second end, a welding position at which the first end is welded to the second end is compressed to form an explosion-proof recess.

Abstract: Systems, devices, and methods are discussed for limiting exposure of internal network operations beyond the boundary of a secure network.

Abstract: Methods, systems and apparatus, including computer programs encoded on computer storage medium, for training a neurosymbolic data imputation system on training data inputs in a domain to impute missing data in a data input from the data domain. In one aspect a method includes, for each training data input, adding random noise to missing fields of the training data input; generating an embedding data input for the training data input using concept embeddings from the domain; processing the noisy data input and the embedding data input through a correlation network to obtain correlation data; applying attention to the noisy training data input and the correlation data to generate a combined data input; processing, by an autoencoder, the combined data input to obtain a decoded data output; computing a difference between the decoded data output and the training data input; and updating parameters of the data imputation system using the difference.

Abstract: A device may generate a synthetic knowledge graph based on a true knowledge graph, may partition the synthetic knowledge graph into a set of synthetic data partitions, and may determine, using a plurality of teacher models, an aggregated prediction. The aggregated prediction may be based on individual predictions from corresponding individual teacher models included in the plurality of teacher models. The device may determine, using a student model and based on the synthetic knowledge graph and noise, a student prediction. The student model may be trained based on historical synthetic knowledge graphs and historical aggregated predictions associated with the plurality of teacher models. The device may determine an error metric based on the aggregated prediction and the student prediction, and may perform an action associated with the synthetic knowledge graph based on the error metric.

Abstract: A device processes a knowledge graph to select a set of triples and generates a first class based on the set of triples. The device determines a quantity of quasi-identifier attributes in the first class and compares the quantity to a predefined parameter. The device embeds the knowledge graph to generate an embedding space representation, identifies a second class, and determines a first quantity of nodes in the first class and the second class. The device compares the first quantity to the predefined parameter and identifies a third class. The device determines a second quantity of nodes in the first class and the third class and compares the second quantity to the predefined parameter. The device merges the second class or the third class with the first class, based on the comparisons, to generate anonymized nodes for the knowledge graph.

Abstract: A device may generate a synthetic knowledge graph based on a true knowledge graph, may partition the synthetic knowledge graph into a set of synthetic data partitions, and may determine, using a plurality of teacher models, an aggregated prediction. The aggregated prediction may be based on individual predictions from corresponding individual teacher models included in the plurality of teacher models. The device may determine, using a student model and based on the synthetic knowledge graph and noise, a student prediction. The student model may be trained based on historical synthetic knowledge graphs and historical aggregated predictions associated with the plurality of teacher models. The device may determine an error metric based on the aggregated prediction and the student prediction, and may perform an action associated with the synthetic knowledge graph based on the error metric.

Abstract: Disclosed is a method of preparing a flexible deformable photonic crystal material for structural health monitoring, comprising the following steps: washing a grating master template; preparing and assembling a mold; obtaining an assembled mold by printing a three-dimensional mold comprising an upper die and a lower die by use of a 3D printing device and installing the grating master template on the three-dimensional mold; obtaining a polydimethylsiloxane (PDMS) one-dimensional photonic crystal film by replicating a one-dimensional grating structure of a surface of the grating master template by pouring PDMS into the assembled mold; finally, obtaining the PDMS one-dimensional photonic crystal film with a one-dimensional photonic crystal structure on a middle surface and protrusion structures at both ends by demolding, wherein the PDMS one-dimensional photonic crystal film is the flexible deformable photonic crystal material.

Abstract: Disclosed is a method of preparing a flexible deformable photonic crystal material for structural health monitoring, comprising the following steps: washing a grating master template; preparing and assembling a mold; obtaining an assembled mold by printing a three-dimensional mold comprising an upper die and a lower die by use of a 3D printing device and installing the grating master template on the three-dimensional mold; obtaining a polydimethylsiloxane (PDMS) one-dimensional photonic crystal film by replicating a one-dimensional grating structure of a surface of the grating master template by pouring PDMS into the assembled mold; finally, obtaining the PDMS one-dimensional photonic crystal film with a one-dimensional photonic crystal structure on a middle surface and protrusion structures at both ends by demolding, wherein the PDMS one-dimensional photonic crystal film is the flexible deformable photonic crystal material.

Abstract: The present invention provides a use of IGF-1 in the preparation of medicaments for preventing and/or treating liver tumors, relating to the technological field of prevention and treatment of hepatocarcinoma. In embodiments of the present invention, experiments are carried out on mice, demonstrating that over-expression of IGF-1 in hepatocytes induces the apoptosis of cancerous cells indirectly, and inhibits the occurrence and development of liver tumors; high level of IGF-1 significantly promotes the function of thymus, delays the degeneration of thymus, and does not cause the dysfunction of thymus; high level of IGF-1 significantly promotes the function of spleen T lymphocyte; high level of IGF-1 significantly enhances the number and activity of tumor infiltrating T lymphocytes; long-term over-expression of IGF-1 does not significantly promote the incidence of tumors in all organs and tissues in mice, indicating the safety of high IGF-1 level in the body.

Abstract: A mold with cavities for nanoimprint lithography and a method of imprinting the same. The mold is a one-piece structure, including an upper mold and a lower mold which are welded together. The upper mold is evenly provided with a plurality of stepped holes. A plurality of grooves are provided at an upper surface of the lower mold. Both ends of each groove are respectively connected to an external high-pressure water pump and an external vacuum pump via pipelines. An airtight cavity is additionally provided at the interior of the mold to form a negative pressure in the cavity by vacuumizing during the imprint process. In the demolding, a crack is formed at the interface between the mold and the imprint resist by using water pressure and expands to the entire interface for the demolding of the imprinted structure.