Abstract: Example packet control methods and apparatus are described. One example method includes detecting, by a network node, a packet in a packet flow causing a congestion from an upstream node. The network node reduces a scheduling priority of the packet in the packet flow and generates a congestion isolation message, where the congestion isolation message includes description information of the packet flow. The congestion isolation message is sent to the upstream node to instruct the upstream node to reduce the scheduling priority of the packet in the packet flow.

Abstract: The present disclosure provides a method for preparing a high cohesive energy adsorbent for fluoride removal, which includes the following steps: S1. adding NaHF2—NiF·6H2O additive to SiCO ceramic powder, and sintering at a temperature of 310-330° C. for 18-22h to obtain a sintered substance; S2. grinding the sintered substance to obtain particles with a size of 2-3 mm, and mixing the particles with polyacrylonitrile to form a composite polymer; and S3. molding the composite polymer by a vacuum baking process at a temperature of 75-85° C., then performing ball milling and sieving to obtain the high cohesive energy adsorbent for fluoride removal. The high cohesive energy adsorbent for fluoride removal may be used in the adsorption and separation of the C2F6—CHF3—CClF3 mixture system, and the contents of CHF3 and CClF3 are lowered to less than 10ppmv.

Abstract: Methods, computer program products, and/or systems are provided that perform the following operations: obtaining pre-check data associated with specified data nodes; calculating outliers for each specified data node, wherein the outliers are calculated based on a unit of the pre-check data associated with each specified data node; backtracking the calculated outliers for each specified data node through an associated generating data link; selecting one or more data nodes associated with a set of largest outliers; selecting one or more data links associated with the set of largest outliers; and generating potential anomaly indications based on the one or more data nodes selected and the one or more data links selected.

Abstract: A light emitting diode includes an n-type semiconductor layer including a pit structure formed therein, active layers grown only on sidewalls of the pit structure and configured to emit light, and a p-type semiconductor layer on the active layers and at least partially in the pit structure. In one embodiment, the pit structure is characterized by a shape of an inverted pyramid. The pit structure is formed in the n-type semiconductor layer by, for example, etching the n-type semiconductor layer using an etch mask layer having apertures with slanted sidewalls, or growing the n-type semiconductor layer on a substrate through a mask layer having an array of apertures.

Abstract: The invention provides a suspended catamaran target boat, including a deck, a suspension structure and two buoyancy units, the suspension structure is connected to upper sides of the two buoyancy units, and the deck is mounted on the suspension structure; the suspension structure includes at least two suspension assemblies including an upper base, a lower base and two support rods. The support rods are hinged between the upper base and the lower base, and the upper base, the lower base and the two support rods form a four-bar linkage mechanism, where a shock absorber and a restricting mechanism are installed between the upper base and the lower base. The deck is provided with a main controller, an acceleration sensor and a heel sensor, and the main controller is respectively electrically connected with the acceleration sensor, the heel sensor and each of the restricting mechanisms of the two suspension assemblies.

Abstract: A method includes steps of: based on protein structure data, selecting a residue pair that includes a specific residue and a paired residue respectively of two wild-type protein chains of a protein complex; determining a mutant residue to substitute for the specific residue; for a target interface between the mutant residue and the paired residue, calculating an atomic distance and an atomic interaction force based on the protein structure data and amino acid structure data; and estimating binding free energy of the target interface by feeding the atomic distance, the atomic interaction force, and physicochemical information related to the specific residue and the mutant residue into a deep neural network.

Abstract: Disclosed herein are embodiments for committing changes of an image of a virtual machine-based container running on a host computer system. A starting image for a container is obtained from a guest starting folder, and while the container runs the starting image changes to the image made by the running container are captured in a guest folder that is union mounted with the guest starting folder. Another union folder, which is the union of a new host folder and the starting folder, contains the changed image which can be used for the container or transferred to a different container.

Abstract: A method includes: determining a mutation frequency for each residue in a wild-type spike protein of a specific virus; for each residue in the protein, counting a total number of contact residues related to said each residue and P antibodies based on P entries of protein structure data; for each residue in the protein, for a condition that said each residue mutates into one common amino acid residue, determining a normalized binding free energy value using a pre-established model based on the protein structure data, and determining a mutation effect score based on the mutation frequency, the total number of contact residues and the normalized binding free energy value; generating a mutation effect epitope map related to the mutation effect scores determined for all residues in the protein and all common amino acid residues; and determining, based on the map, a region in the protein as a target epitope.

Abstract: An approach is provided for optimizing a feedback-type question answering process. A training set is constructed to detect missing information of a question. A natural language generation model is trained using the missing information. The natural language generation model is executed to generate a rhetorical question. A response to the rhetorical question is combined with the question to generate an input to a language processor. A new question is generated. The new question is applied to a document library. A final answer is generated.

Abstract: Methods, apparatus, computer program products for two-phased medical diagnosis are provided. The computer-implemented method comprises, receiving, by one or more processors, data during a process of a medical diagnosis from a source of data information. The computer-implemented method also comprises extracting, by one or more processors, features from the received data. The computer-implemented method also comprises transferring, by one or more processors, the extracted features in form of feature vectors to a server via a network. The computer-implemented method further comprises obtaining, by one or more processors, a recommendation of medical diagnosis from the server, wherein the recommendation of medical diagnosis is based, at least in part, on labels determined for the feature vectors.

Abstract: A method, computer program product and computer system to provide topic guide during document drafting is provided. A processor retrieves at least one section of text from a document. A processor receives a target topic for the document. A processor extracts at least one local topic from the at least one section of text. A processor generates a semantic network comprising the at least one local topic and the target topic. A processor determines a deviation value for the at least one local topic based on a distance between the at least one local topic and the target topic in the semantic network. A processor, in response to the deviation value exceeding a threshold value, alerts a user that the at least one section of text from the document is off-topic from the target topic.

Abstract: A sensor enclosure comprises a cover and a structure. The structure can be encased by the cover. The structure comprises a frame, a ring, and one or more anchoring posts. The frame can be configured to mount one or more sensors. The ring, disposed peripherally to the frame, can be operatively coupled to the cover. The ring can include a drainage ring plate that drains rainwater accumulated on the cover away from the sensor enclosure. The one or more anchoring posts, disposed underneath the frame and the ring, can be used to anchor the sensor enclosure to a vehicle.

Abstract: A method, computer program product, and computer system for repairing a Dockerfile. Library versions containing initial version numbers of libraries are extracted from the Dockerfile. A Monte Carlo tree search (MCTS) is executed, using the extracted library versions as input, which generates a tree that includes multiple levels populated with noses. Each node in a level represents the generic library name of a library version in the Dockrerfile and an associated randomly selected version number. At least one of the randomly selected version numbers associated with at least one node in a level differs from the initial version number associated with a versionf. A best successful installation path is selected from the at least one successful installation path. The Dockerfile is repaired by inserting randomly selected version numbers into Dockerfile as replacements for some of the initial version numbers.

Abstract: A computer-implemented method, according to one embodiment, includes: receiving an image having characters that correspond to a language, and using a text recognition algorithm to determine a first language believed to correspond to the characters. A first confidence level associated with the first language is also computed, and a determination is made as to whether the first confidence level associated with the first language is outside a predetermined range. In response to determining that the first confidence level associated with the first language is not outside the predetermined range, the first language is output as the given language. The text recognition algorithm is trained using a simple shallow neural network and a generated mixed language corpus. The generated mixed language corpus is formed by: randomly sampling libraries having vocabulary and/or characters therein, and combining the randomly sampled vocabulary and/or characters to form the generated mixed language corpus.

Abstract: A computer-implemented method for implementing face recognition includes obtaining a face recognition model trained on labeled face data, separating, using a mixture of probability distributions, a plurality of unlabeled faces corresponding to unlabeled face data into a set of one or more overlapping unlabeled faces that include overlapping identities to those in the labeled face data and a set of one or more disjoint unlabeled faces that include disjoint identities to those in the labeled face data, clustering the one or more disjoint unlabeled faces using a graph convolutional network to generate one or more cluster assignments, generating a clustering uncertainty associated with the one or more cluster assignments, and retraining the face recognition model on the labeled face data and the unlabeled face data to improve face recognition performance by incorporating the clustering uncertainty.

Abstract: A failure analysis system identifies a root cause of a failure (or other health issue) in a virtualized computing environment and provides a recommendation for remediation. The failure analysis system uses a model-based reasoning (MBR) approach that involves building a model describing the relationships/dependencies of elements in the various layers of the virtualized computing environment, and the model is used by an inference engine to generate facts and rules for reasoning to identify an element in the virtualized computing environment that is causing the failure. Then, then the failure analysis system uses a decision tree analysis (DTA) approach to perform a deep diagnosis of the element, by traversing a decision tree that was generated by combining the rules for reasoning provided by the MBR approach, in conjunction with examining data collected by health monitors. The result of the DTA approach is then used to generate the recommendation for remediation.

Abstract: A light emitting diode structure comprising a p-type region an n-type region; and a light emitting region for recombination of carriers injectable by the p-type region and the n-type region, wherein at least one of the n-type region and the p-type region is at least partially formed in a via passing through the light emitting region, wherein the via defines the perimeter of a light emitting surface of at least one pixel.

Abstract: An electronic equipment assembly has an interconnect including columns of signal conductors, connectors mounted to the columns of signal conductors, and a chassis coupled with the interconnect. The chassis provides slots that guide resource devices into engagement with the connectors mounted to the columns of signal conductors to enable the interconnect to electronically access the resource devices. At least one column of the columns of signal conductors of the interconnect is a multi-function column. Each multi-function column is constructed and arranged to electronically access different types of resource devices through a respective connector mounted to that multi-function column.

Abstract: A computer-implemented method for implementing face recognition includes receiving training data including a plurality of augmented images each corresponding to a respective one of a plurality of input images augmented by one of a plurality of variations, splitting a feature embedding generated from the training data into a plurality of sub-embeddings each associated with one of the plurality of variations, associating each of the plurality of sub-embeddings with respective ones of a plurality of confidence values, and applying a plurality of losses including a confidence-aware identification loss and a variation-decorrelation loss to the plurality of sub-embeddings and the plurality of confidence values to improve face recognition performance by learning the plurality of sub-embeddings.

Abstract: New and/or improved coatings for porous substrates, including battery separators or separator membranes, and/or coated porous substrates, including coated battery separators, and/or batteries or cells including such coatings or coated separators, and/or related methods including methods of manufacture and/or of use thereof are disclosed. Also, new or improved coatings for porous substrates, including battery separators, which comprise at least a polymeric binder and heat-resistant particles with or without additional additives, materials or components, and/or to new or improved coated porous substrates, including battery separators, where the coating comprises at least a polymeric binder and heat-resistant particles with or without additional additives, materials or components are disclosed.