Abstract: Methods and systems are described for detecting and reporting a vulnerability fix in a code repository. A commit obtained from the code repository is preprocessed to generate file-level token sequences each representing a file-level code change for respective files. Respective file-level code change embedding vectors are generated by inputting each file-level token sequence into a transformer model, each file-level code change embedding vector being a vector representation of the file-level code change for the respective file. The file-level code change embedding vectors are combined into a commit-level code change embedding vector that represents all code changes contained in the commit. A predicted commit-level vulnerability fix score is generated by inputting the commit-level code change embedding vector into a classifier. A vulnerability fix report is outputted, containing an identification of the commit and the predicted commit-level vulnerability fix score.

Abstract: A method, an apparatus, a device, and a medium for image generation are provided. In one method, a diffusion model is obtained, the diffusion model is an image generation model and describes an association relationship between a prompt and an image generated based on the prompt. Based on a predetermined division parameter, a plurality of steps associated with the diffusion model is divided into a first set of steps and a second set of steps. Based on a current step of the diffusion model, the first set of steps, and the second set of steps, a guidance parameter for distilling the diffusion model into a target model is determined, the guidance parameter represents an association relationship between a prompt and an image associated with the diffusion model. The diffusion model is distilled into the target model based on the guidance parameter.

Abstract: The embodiments of the present disclosure provide a neural network model structure determining method and apparatus, a device, a medium and a product. The neural network model structure determining method includes: determining, based on a preset neural network model architecture search algorithm, at least one candidate neural network model; predicting, based on a preset Central Processing Unit (CPU) utilization prediction model, a runtime CPU utilization for each candidate neural network model, so as to obtain a predicted value of CPU utilization; and determining, based on at least one predicted value of CPU utilization, a target neural network model structure among structures of the at least one candidate neural network model.

Abstract: There is described a method and a computer-readable medium for training a neural network. A section of computer code is divided into a plurality of computer code parts. A first change sample is generated comprising a first original segment of computer code and a first modified segment of computer code, the first change sample comprising at least one of the plurality of computer code parts. A second change sample is generated comprising a second original segment of computer code and a second modified segment of computer code. A loss function is calculated based on the first change sample and the second change sample. The neural network is trained by minimizing the loss function.

Abstract: A method, system, apparatus, and computer-readable storage medium for detecting vulnerabilities in computer code. A computer processor calculates a function change log of a section of the computer code, the function change log comprising at least one intermediate change between a first version of the section of computer code and a second version of the section of computer code, the section of the computer code being similar to a computer-code vulnerability, and the first version is a version prior to the second version. The computer processor determines whether the section of the computer code comprises the computer-code vulnerability based on a similarity between the function change log and a fix change log, the fix change log comprising at least one code change for fixing the computer-code vulnerability.

Abstract: A method, system, apparatus, and computer-readable storage medium for detecting vulnerabilities in computer code. A computer processor calculates a first change between a first version of a section of the computer code and a second version of the section of the computer code, the section of the computer code being similar to a computer-code vulnerability, and the second version is a version prior to the first version. The computer processor determines whether the section of the computer code comprises the computer-code vulnerability based on a similarity between the first change and a second change, the second change being a change between the computer-code vulnerability and a fix for the computer-code vulnerability.

Abstract: A chip packaging method and a chip packaging structure are provided. The method includes: providing a carrier and wafers, where at least one wafer is different from others; cutting each wafer to form chips; selecting target chips from the chips to form chipsets, and fixing functional surfaces of the chipsets to the carrier; forming a first plastic encapsulation layer on a side of the chipsets away from the carrier and removing the carrier; forming silicon interposer plates and bonding the silicon interposer plates to the chipsets; cutting the silicon interposer plates and the chipsets to form chip micro-modules each of which includes one chipset; fixing a side of the silicon interposer plates to the carrier and forming a second plastic encapsulation layer on a side of the chip micro-modules away from the carrier; and removing the carrier and cutting the second plastic encapsulation layer, to form independent packaging structures.

Abstract: A fan-out chip packaging method and a fan-out chip packaging structure are provided. The method includes: providing a carrier, silicon wafers, and chips; forming conductive connection structures on the silicon wafers respectively to form silicon interposer plates; cutting each silicon interposer plate respectively to obtain silicon interposer sub-plates; selecting target silicon interposer sub-plates from the silicon interposer sub-plates according to preset packaging requirements, and fixing the target silicon interposer sub-plates on the carrier; forming a first plastic encapsulation layer on a side of the target silicon interposer sub-plates away from the carrier; and interconnecting the chips to the target silicon interposer sub-plates. The conductive connection structures on at least one silicon interposer plate are different from the conductive connection structures on other silicon interposer plates.

Abstract: A chip packaging method and chip packaging structure are provided. The method includes: providing a substrate, a plurality of silicon wafers, and a plurality of chips; forming a plurality of sets of conductive connection structures on the plurality of silicon wafers respectively to form a plurality of silicon interposer plates; where at least one of the plurality of silicon interposer plates is different from other silicon interposer plates of the plurality of silicon interposer plates; cutting the plurality of silicon interposer plates respectively to obtain a plurality of silicon interposer blocks; selecting a plurality of target silicon interposer blocks from the plurality of silicon interposer blocks, and fixing the plurality of target silicon interposer blocks on the substrate; and interconnecting and arranging the plurality of chips on corresponding target silicon interposer blocks of the plurality of target silicon interposer blocks respectively.

Abstract: A method, an apparatus, a device, a medium for generating an image are provided. In a method, a first machine learning model is obtained, the first machine learning model being obtained based on a reference image having a first resolution. The first machine learning model is fine-tuned to a second machine learning model by a fine-tuning plug-in that is obtained based on a reference image having the second resolution. A target image is generated based on a target prompt by a second machine learning model, the target image having a resolution and image content specified by the target prompt. With the example implementations of the disclosure, the fine-tuning plug-in may obtain knowledge related to generating an image(s) with a further resolution(s), so that the second machine learning model may generate images with different resolutions in a more accurate and effective manner.

Abstract: The invention relates to an electrochemically active powder comprising particles containing a compound represented by formula AaMm(XO4)n wherein A comprises an alkaline metal; M comprises at least one transition metal and optionally at least one non-transition metal; and X is chosen among S, P and Si; wherein 0<a?3.2; 1?m?2; and 1?n?3; wherein said particles are at least partially coated with a layer comprising a carbonaceous material, said carbonaceous material comprising a highly ordered graphite, wherein said highly ordered graphite has a ratio (I1360/I1580) of a peak intensity (I1360) at 1360 cm?1 to a peak intensity (I1580) at 1580 cm?1, obtained by Raman spectrum analysis, of at most 3.05.

Abstract: A lubricity improver composition for fuel oil composition contains a dicarboxylic acid monoester represented by the formula (I) as component A, and a C8-24 long-chain fatty acid, its polyol ester or a mixture thereof as component B. The total amount of component A and component B is 70-100 wt %, based on the total weight of the composition. The mass ratio of component A to component B is 9:1 to 1:9.

Abstract: A lubricity modifier for fuels contain a dicarboxylic acid monoester compound represented by formula (I). In formula (I), R1 represents a single bond, a substituted or unsubstituted C2-6 divalent alkenyl group, or a group having a structure of —R3—R4—R5—; R2 represents a substituted or unsubstituted C1-40 hydrocarbyl group; R3 and R5 each independently represents a single bond, or a substituted or unsubstituted C1-3 divalent alkyl group; and R4 represents a substituted or unsubstituted C3-12 divalent alicyclic group.

Abstract: A lubricity improver composition for fuel oil composition contains a dicarboxylic acid monoester represented by the formula (I) as component A, and a C8-24 long-chain fatty acid, its polyol ester or a mixture thereof as component B. The total amount of component A and component B is 70-100 wt %, based on the total weight of the composition. The mass ratio of component A to component B is 9:1 to 1:9.

Abstract: The present disclosure relates to a prediction method and system for an initiation volume of a debris flow slope source. The prediction method includes: dividing a debris flow source slope to be predicted into soil columns; determining a positional relationship between a selected central soil column and six adjacent soil columns around; calculating a most unfavorable sliding surface of the soil column and an unbalanced force on the sliding surface according to an upper bound theorem of a limit analysis; determining whether the most unfavorable sliding surface is unstable; determining a mode and a size of a force exerted by an unstable soil column on a surrounding soil column according to a break status of a connection bond of a lateral tensile stress of the central soil column; and finally determining whether the soil column is fluidized, and predicting an initiation volume of the debris flow source slope.

Abstract: This application discloses a precoding method and apparatus, and an information transmission method and apparatus, and relates to the field of communications technologies, to help improve overall performance of a plurality of data streams corresponding to a same codeword. The precoding method includes: decomposing a channel matrix into a product of a matrix Q, a matrix R, and a matrix PH, where the matrix PH is a conjugate transpose matrix of a matrix P, both the matrix Q and the matrix P are unitary matrices, and the matrix R is an upper triangular matrix; and precoding to-be-sent data based on the matrix P.

Abstract: Methods and systems are described for detecting and reporting a vulnerability fix in a code repository. A commit obtained from the code repository is preprocessed to generate file-level token sequences each representing a file-level code change for respective files. Respective file-level code change embedding vectors are generated by inputting each file-level token sequence into a transformer model, each file-level code change embedding vector being a vector representation of the file-level code change for the respective file. The file-level code change embedding vectors are combined into a commit-level code change embedding vector that represents all code changes contained in the commit. A predicted commit-level vulnerability fix score is generated by inputting the commit-level code change embedding vector into a classifier. A vulnerability fix report is outputted, containing an identification of the commit and the predicted commit-level vulnerability fix score.

Abstract: Methods and devices are described for detecting code clones in a software program. The source code of the software program is processed into a group of n-gram representations. A clone index is generated for each respective code portion defined in the normalized source code, where each clone index includes a feature vector encoding features of the respective code portion based on the n-gram representations corresponding to the respective code portion. Comparison of the clone indexes is used to detect a code clone, based on matching the feature vectors of the clone indexes.

Abstract: Communication method and apparatus provide a network device sends a first signal to a first terminal device on a first resource element; the network device receives a fourth signal on a second resource element, where the second resource element and the first resource element at least partially overlap or are adjacent to each other; and the network device sends downlink data by using a first beamforming BF weight, where the first BF weight is obtained based on signal processing performed on the fourth signal, and an operation amount of the signal processing is less than an operation amount of matrix inversion or matrix decomposition. An air interface is used as a calculation resource to reduce calculation complexity of a baseband.

Abstract: The invention relates to an electrochemically active powder comprising particles containing a compound represented by formula AaMm(XO4)n wherein A comprises an alkaline metal; M comprises at least one transition metal and optionally at least one non-transition metal; and X is chosen among S, P and Si; wherein 0<a?3.2; 1?m?2; and 1?n?3; wherein said particles are at least partially coated with a layer comprising a carbonaceous material, said carbonaceous material comprising a highly ordered graphite, wherein said highly ordered graphite has a ratio (I1360/I1580) of a peak intensity (I1360) at 1360 cm?1 to a peak intensity (I1580) at 1580 cm?1, obtained by Raman spectrum analysis, of at most 3.05.