Abstract: The present description relates to the field of geological exploration, and discloses a method and system for extracting features of logging while drilling and drilling-time logging based on Unet dual-channel output, aiming at solving the problem that the prior art 5 cannot integrate various types of information for lithology classification.

Abstract: A method for growing bulk boron arsenide (BA) crystals, the method comprising utilizing a seeded chemical vapor transport (CVT) growth mechanism to produce single BAs crystals which are used for further CVT growth, wherein a sparsity of nucleation centers is controlled during the further CVT growth. Also disclosed are bulk BAs crystals produced via the method.

Abstract: An apparatus and method for preparing high-purity spherical magnesium and/or high-purity magnesium powder are provided. The apparatus includes a vertical furnace body, a heating zone, and a condensing zone, where a periphery of the condensing zone is provided with a first thermal insulation device and a second thermal insulation device sequentially from bottom to top, and each of the first thermal insulation device and the second thermal insulation device is removably arranged; the periphery of the condensing zone is further provided with a liquid cooling device; a gas inlet and a gas outlet are formed in the condensing zone; and an inner wall of the condensing zone is provided with an arrangement structure configured to arrange a collection device. A heating temperature of a material and condensation conditions in the condensing zone are controlled to make an evaporated magnesium vapor condensed on the collection device in the condensing zone.

Abstract: An automatic analyzing apparatus according to an embodiment of the present disclosure includes a reagent storage, a reaction vessel, a placement part, and a wiring fixing part. On the placement part, at least one of the reagent storage and the reaction vessel is placed. The wiring fixing part is attached to the bottom face side of the placement part, while a wiring connected to at least one of the reagent storage and the reaction vessel is fixed to the bottom face side of the wiring fixing part. It is possible to pull out the wiring fixing part.

Abstract: A display panel includes a main body and binding pins. In an embodiment, the main body includes a display region and a first non-display region. In an embodiment, the display region includes a first display region and a second display region, the first display region and the second display region each includes first signal lines, the first non-display region includes a first connecting line and a second connecting line. In an embodiment, the binding pins are electrically connected to the first signal lines through the first connecting line. In an embodiment, the display region further includes a third connecting line extending from the second display region to the first display region, and the first signal lines in the second display region are electrically connected to the plurality of binding pins through the first connecting line and the second connecting line.

Abstract: A pixel driving circuit and a display panel are provided. The pixel driving circuit includes a data writing module, a data conversion module, and a current driving module. The data writing module is electrically connected to a first node and configured to transmit a data signal to the first node. The data conversion module is electrically connected to the first node, a second node, and a modulation signal source, and configured to generate a current driving control signal, and to output the current driving control signal to the second node. The current driving module is electrically connected to the second node, a light-emitting control wire, and a light-emitting device, and configured to control the light-emitting device to emit light. An effective pulse of the current driving control signal has different pulse widths in different gray-scale states.

Abstract: Disclosed are a Nested Named Entity Recognition method based on part-of-speech awareness, system, device and storage medium therefor. The method uses a BiLSTM model to extract a feature of text word data in order to obtain a text word depth feature, and each text word of text to be recognized is initialized into a corresponding graph node, and a text heterogeneous graph of the text to be recognized is constructed according to a preset part-of-speech path, the text word data of the graph nodes is updated by an attention mechanism, and the features of all graph nodes of the text heterogeneous graph are extracted using the BiLSTM model, and a nested named entity recognition result is obtained after decoding and annotating. The present disclosure can recognize ordinary entities and nested entities accurately and effectively, and enhance the performance and advantages of the nested named entity recognition model.

Abstract: The present invention belongs to the field of environment monitoring, particularly relates to a CO2 storage state networking monitoring device, system and method with multi-information fusion. The present invention comprises: obtaining orientation electrical signal data and real-time pressure signals, analyzing a fluid flowing state at a view of a pressure sensor through the real-time pressure signals, and obtaining a CO2 flowing state through the orientation electrical signal data; and obtaining a CO2 regional storage state by combining an orientation CO2 content, a CO2 flowing state and the fluid flowing condition at the view of the pressure sensor. By combining accurate short-range CO2 boundary monitoring of orientation electrodes with long-range monitoring of pressure sensors to achieve a wide range of CO2 flowing state monitoring, the present invention can observe more data with higher reliability and effectively aims at the problem of strong inter-well heterogeneity.

Abstract: A detection circuit, a driving circuit, and a display panel and a driving method therefor are provided. The detection circuit includes an acquisition circuit and a processing circuit. The acquisition circuit includes a test transistor and an energy storage element, where, for the test transistor, a control end is configured to be coupled to the data signal terminal, a first end is configured to be written with a detection signal, and a second end is coupled to the energy storage element; and a structural characteristic of the test transistor is identical to a structural characteristic of the driving transistor. The processing circuit is coupled to the second end of the test transistor, and configured to detect a voltage at the second end of the test transistor as a detection voltage and regulate the data signal according to the detection voltage.

Abstract: A multi-modal pre-training model acquisition method, an electronic device and a storage medium, which relate to the fields of deep learning and natural language processing, are disclosed. The method may include: determining, for each image-text pair as training data, to-be-processed fine-grained semantic word in the text; masking the to-be-processed fine-grained semantic words; and training the multi-modal pre-training model using the training data with the fine-grained semantic words masked.

Abstract: Display panel and electronic device are provided. The display panel includes a display area and a non-display area at least partially surrounding the display area. The display panel includes: a plurality of signal lines, extending along a first direction and located in the display area, the display area including a first display area and a second display area disposed adjacent to the first display area along a second direction, the display area including a first side extending along the first direction, and the first display area located between the first side and the second display area; first signal connection lines, extending through the display area along a first non-display area on a side of the display area to a second non-display area on the other side of the display area, the first non-display area including a bonding area; and second signal connection lines, extending along the second non-display area.

Abstract: A computer-implemented method, system and computer program product for improving understandability of text by a user. A final word vector for each word in a sentence of a document is computed, such as by averaging a first word vector and a second word vector for that word. Furthermore, elements of a user portrait are vectorized. A distance is then computed between a vector for each word in the sentence and a vectorized element in the user's portrait which is summed to form an evaluation result for the element. An evaluation result is also formed for every other element in the user's portrait by performing such a computation step. A “final evaluation result” is then generated corresponding to the evaluation results for every element in the user's portrait. The document is then transformed in response to the final evaluation result indicating a lack of understanding of the sentence by the user.

Abstract: The present invention belongs to the field of geological exploration and specifically relates to the fault characterization method and system for precise navigation of deep oil and gas based on image fusion, aiming to solve the problem that faults in deep formations are difficult to characterize with conventional seismic interpretation methods. The present invention includes: obtaining amplitude gradient images by calculating amplitude gradient vectors; calculating dip attribute images based on the enhanced seismic data; fusing gradient amplitude attribute fault confidence region with dip angle attribute data volume that defines the fault position through a hierarchical wavelet transform method to obtain a superimposed fault attribute map; dividing bead-like structures based on superimposed fault attribute maps; calculating the score of branch fault data points based on the center point position of bead-like structures, and dividing and analyzing the dominant fault areas.

Abstract: A method for training generative network, a method for generating near-infrared image and device. The method includes: obtaining a training sample set, in which the set includes near-infrared image samples and visible-light image samples; obtaining an adversarial network to be trained, in which the generative network of the adversarial network is configured to generate each near-infrared image according to an input visible-light image, the discrimination network of the adversarial network is configured to determine whether an input image is real or generated; constructing a first objective function according to a first distance between each generated near-infrared image and the corresponding near-infrared image sample in an image space and a second distance between each generated near-infrared image and the corresponding near-infrared image sample in a feature space; performing an adversarial training on the adversarial network with the set based on optimizing a value of the first objective function.

Abstract: The invention belongs to the field of environmental monitoring, and in particular relates to a method for optimally selecting a carbon storage site based on multi-frequency band seismic data.

Abstract: The present invention provides a processing method and device for data of a well site test based on a knowledge graph. The processing method for the data of the well site test based on the knowledge graph comprises: carrying out format identification on received historical data of the well site test to generate format identification results; establishing a mind map according to the format identification results; generating the knowledge graph of the data of the well site test according to the mind map; and processing the historical data of the well site test and new data of the well site test according to the knowledge graph.

Abstract: The present invention belongs to the field of treatment for data identification and recording carriers, and specifically relates to a method and system for analyzing filling for a karst reservoir based on spectrum decomposition and machine learning, which aims to solve the problems that by adopting the existing petroleum exploration technology, the reservoir with fast lateral change cannot be predicted, and the development characteristics of a carbonate cave type reservoir in a large-scale complex basin cannot be identified. The method comprises: acquiring data of standardized logging curves; obtaining a high-precision 3D seismic amplitude data body by mixed-phase wavelet estimation and maximum posteriori deconvolution and enhancing diffusion filtering. According to the method and the system, the effect of identifying the development characteristics of the carbonate karst cave type reservoir in the large-scale complex basin can be achieved, and the characterization precision is improved.

Abstract: A mechanism is provided in a data processing system for hybrid cloud management. The mechanism generates hybrid cloud storage features and hybrid cloud environment factors. The mechanism performs a dynamic confidence method on the hybrid cloud features based on the hybrid cloud environment factors using a deep learning model to generate a hybrid cloud storage profile. The mechanism performing model optimization on the deep learning model and generating a files-storage matrix. The mechanism generates a hybrid cloud file profile based on the hybrid cloud storage profile and the files-storage matrix. The mechanism generates a target file matrix based on the hybrid cloud storage profile and the hybrid cloud file profile. The mechanism stores files based on the target file matrix.

Abstract: The present disclosure belongs to the field of geological prospecting and particularly relates to an intelligent real-time updating method and system for a stratigraphic framework with geosteering-while-drilling, aiming to solve the problems of insufficient precision in position and dipping angle of a stratigraphic framework due to differences in parameters measured by different instruments for well logging and mud logging while drilling.

Abstract: The present disclosure belongs to the field of capture, utilization, and storage of carbon dioxide, particularly relates to a method and system for intelligently identifying a carbon storage box based on a GAN network, and aims at solving the problem that the analysis accuracy of a fault zone area in the prior art is insufficient. The method comprises the steps: delineating seismic waveform data of a stable sedimentary area through a GAN network, and removing seismic waveform data points in the fault zone area; obtaining a stable sedimentary background seismic waveform data invertomer; obtaining a three-dimensional wave impedance prediction data volume; making a difference to obtain an abnormal wave impedance data volume; retaining abnormal wave impedance data of fault-karst in the three-dimensional variance attribute volume to obtain a fault-karst wave impedance data volume; and then obtaining a carbon storage box interpretation model.