Abstract: A method includes determining a top of salt (TOS) surface in a seismic volume based on a crossline direction of the seismic volume and an inline direction of the seismic volume. The method also includes determining a binary mask based upon the TOS surface. The method also includes sampling seismic data in the seismic volume to obtain a training seismic slice. The method also includes sampling the binary mask to obtain a mask slice. The method also includes selecting a first coordinate in the training seismic slice to produce a first tile. The method also includes selecting a second coordinate in the mask slice to produce a second tile. The method also includes generating or updating a model of the seismic volume based upon the first tile and the second tile.

Abstract: A method includes receiving a seismic survey that includes a plurality of seismic slices. The method also includes converting the seismic slices into an embedding. The embedding includes one or more vectors. Each of the vectors includes more than 3 dimensions. The method also includes generating a plot based at least partially upon the embedding.

Abstract: A method includes receiving a seismic survey that includes a plurality of seismic slices. The method also includes converting the seismic slices into an embedding. The embedding includes one or more vectors. Each of the vectors includes more than 3 dimensions. The method also includes generating a plot based at least partially upon the embedding.

Abstract: A method for seismic surveying includes receiving a baseline dataset and a plurality of sparse monitoring datasets, generating a decimated baseline dataset by removing one or more sources, receivers, or both from the baseline dataset, generating a reconstructed baseline dataset by inputting the decimated baseline dataset into a machine learning model, generating reconstructed monitoring datasets by inputting the plurality of sparse monitoring datasets to the machine learning model, the machine learning model having been trained based on a comparison of the reconstructed baseline dataset to the baseline seismic dataset, determining accuracies for the plurality of sparse monitoring datasets by comparing the reconstructed monitoring datasets to the baseline dataset, and selecting one or more survey geometries for arranging physical sources and physical receivers in a seismic survey based at least in part on the accuracies of the plurality of sparse monitoring datasets.

Abstract: An integrated workflow is presented including a suite of data-driven technologies that aims to substantially reduce the cost of monitoring data acquisition, improve the robustness and efficiency of time-lapse data processing procedures to shorten the turnaround time of projects utilizing seismic data for monitoring sub-surface fluid reservoirs. In particular, plumes of subsurface CO2 may be monitored, including CO2 deliberately injected into the sub-surface as a sequestration technique. The workflow may include two parts: (1) cost-effective data acquisition schemes and (2) efficient data processing algorithms. The technology components in the workflow may include deep learning sparse monitoring data reconstruction and optimal acquisition survey design, deep learning deblending of simultaneous source monitoring data, time-lapse data repeatability enforcement through deep learning, and rapid CO2 plume body and property estimation directly from pre-migration monitoring data.

Abstract: A method for modeling a subsurface property for a subterranean volume of interest includes receiving input measurement data representing a subterranean volume of interest, predicting a subsurface property based at least in part on the input measurement data using a first machine learning model, predicting a subsurface property model based at least in part on the subsurface property, the input measurement data, or both, using a second machine learning model, predicting synthetic measurement data based at least in part on the subsurface property model using a third machine learning model, a physics-based model, or both, comparing the synthetic measurement data and the input measurement data, and training the first machine learning model, the second machine learning model, or both based at least in part on the comparing.

Abstract: A computer-implemented method includes receiving a test seismic dataset associated with a known truth interpretation, receiving one or more hard constraints, training a machine learning system based on the test seismic dataset, the known truth interpretation, and the one or more hard constraints, determining an error value based on the training the machine learning system, adjusting the error value based on one or more soft constraints, updating the training of the machine learning system based on the adjusted error value, receiving a second seismic dataset after the updating the training; applying the second seismic dataset to the machine learning system to generate an interpretation of the second seismic dataset, generating a seismic image representing a subterranean domain based on the interpretation of the second seismic dataset, and outputting the seismic image.

Abstract: The present disclosure provides a kit and method for constructing a long-acting depression animal model. The present disclosure adopts Bacille Calmette-Guerin (BCG) (or Mycobacterium bovis (M bovis)) and low-dose pertussis toxin (PTX) for combined induction, which greatly reduces modeling cost. A mouse model constructed by the method of the present disclosure can clearly distinguish a time interval of pathological behaviors from a time interval of depression-like behaviors and has prominent face validity and predictive validity. The method of the present disclosure is simple and convenient and does not require a large number of tedious daily operations as the depression model construction by chronic unpredictable stress, chronic restraint stress, social defeat, mother-child separation, or the like. The mouse model of the present disclosure can provide a valuable long-term intervention window for research on antidepressant therapy.

Abstract: The present disclosure provides a kit and method for constructing a long-acting depression animal model. The present disclosure adopts Bacille Calmette-Guerin (BCG) (or Mycobacterium bovis (M. bovis)) and low-dose pertussis toxin (PTX) for combined induction, which greatly reduces modeling cost. A mouse model constructed by the method of the present disclosure can clearly distinguish a time interval of pathological behaviors from a time interval of depression-like behaviors and has prominent face validity and predictive validity. The method of the present disclosure is simple and convenient and does not require a large number of tedious daily operations as the depression model construction by chronic unpredictable stress, chronic restraint stress, social defeat, mother-child separation, or the like. The mouse model of the present disclosure can provide a valuable long-term intervention window for research on antidepressant therapy.

Abstract: A method for interpreting seismic data includes receiving seismic data that represents a subterranean volume, and generating inline probability values and crossline probability values using a first machine learning technique. The first machine learning technique is trained to identify one or more vertical fault lines in a seismic volume based on the seismic data. The method includes generating a merged data set by combining the inline probability values and the crossline probability values, training a second machine learning technique based on a subset of labeled horizontal planes from the merged data set, the second machine learning technique trained to identify horizontal fault lines from the seismic volume, and generating a representation of the seismic volume based on the second machine learning technique, the representation including an indication of a three-dimensional fault structure within the seismic volume.

Abstract: A computer-implemented method includes receiving a test seismic dataset associated with a known truth interpretation, receiving one or more hard constraints, training a machine learning system based on the test seismic dataset, the known truth interpretation, and the one or more hard constraints, determining an error value based on the training the machine learning system, adjusting the error value based on one or more soft constraints, updating the training of the machine learning system based on the adjusted error value, receiving a second seismic dataset after the updating the training; applying the second seismic dataset to the machine learning system to generate an interpretation of the second seismic dataset, generating a seismic image representing a subterranean domain based on the interpretation of the second seismic dataset, and outputting the seismic image.

Abstract: The present disclosure discloses a visualized screening method for an Aspergillus recombinant strain with multigene editing and belongs to the technical field of gene engineering. CRISPR-Cas9 is used in the disclosure to cleave spore color change-related genes and a target gene in Aspergillus at the same time, such that editing of the target gene is visualized and an Aspergillus niger strain with multigene editing can be rapidly and efficiently screened out through spore phenotypes. Through different combinations of visualized genes and non-phenotypic change genes, rapid screening of the strain with multigene editing and simultaneous screening of multiple visualized genes are realized, and use of resistance genes in industrial strains is reduced.

Abstract: The disclosure provides an application of an anthocyanin extract in preparing a pharmaceutical composition for preventing and treating cardiac toxicity induced by Anthracyclines and the pharmaceutical composition, wherein the pharmaceutical composition comprises an effective dose of the anthocyanin extract; and the anthocyanin extract refers to an extract obtained from mature fruits of a zygophyllaceous nitraria plant and having a total anthocyanin content greater than 700 mg CGE/g and a total antioxidant capacity greater than 200 mg TE/g. Cytobiology and molecular biology studies prove that the anthocyanin extract has obvious protection effect to cardiomyocyte toxicity damage induced by anthracyclines and may be used for preventing and alleviating cardiotoxicity of an antharcyclines anticancer drug, thereby expanding a clinical application of the antharcyclines anticancer drug and relieving toxic and side effects brought by the antharcyclines anticancer drug to a patient and pain of a chemotherapy patient.

Abstract: A method includes determining a top of salt (TOS) surface in a seismic volume based on a crossline direction of the seismic volume and an inline direction of the seismic volume. The method also includes determining a binary mask based upon the TOS surface. The method also includes sampling seismic data in the seismic volume to obtain a training seismic slice. The method also includes sampling the binary mask to obtain a mask slice. The method also includes selecting a first coordinate in the training seismic slice to produce a first tile. The method also includes selecting a second coordinate in the mask slice to produce a second tile. The method also includes generating or updating a model of the seismic volume based upon the first tile and the second tile.

Abstract: The disclosure provides an application of an anthocyanin extract in preparing a pharmaceutical composition for preventing and treating cardiac toxicity induced by Anthracyclines and the pharmaceutical composition, wherein the pharmaceutical composition comprises an effective dose of the anthocyanin extract; and the anthocyanin extract refers to an extract obtained from mature fruits of a zygophyllaceous nitraria plant and having a total anthocyanin content greater than 700 mg CGE/g and a total antioxidant capacity greater than 200 mg TE/g. Cytobiology and molecular biology studies prove that the anthocyanin extract has obvious protection effect to cardiomyocyte toxicity damage induced by anthracyclines and may be used for preventing and alleviating cardiotoxicity of an antharcyclines anticancer drug, thereby expanding a clinical application of the antharcyclines anticancer drug and relieving toxic and side effects brought by the antharcyclines anticancer drug to a patient and pain of a chemotherapy patient.

Abstract: An integrated circuit for driving high-voltage LED lamps is applied to a rectified alternative current (AC) power and a plurality of LED stacks. The integrated circuit includes a control unit, a plurality of current-clamping units which electrically connect to the control unit and the LED stacks respectively, and a plurality of current-sensing units which electrically connect to the current-clamping units and the control unit. When the rectified power is switched on, the current-sensing unit constantly monitors the electrical current flowing through the respective current-clamping unit and feeds back the monitored data to the control unit. The control unit sequentially switches on or off the current-clamping units according to the combinatorial logic state of the monitored data.

Abstract: A structure for adjusting backlight brightness of an electronic apparatus includes an indicator cover with an optical window and a light detecting circuit board. The indicator cover with an optical window has a window disposed thereon. The light detecting circuit board is installed in the indicator cover with an optical window and disposed correspondingly to the window. In addition, the light detecting circuit board is electrically connected to the backlight module of the electronic apparatus and has a light detecting circuit disposed thereon. The light detecting circuit has a control unit, a light emitting unit, a driving unit, and a storage unit. The light emitting unit has a light emitting component inside the indicator cover and an ambient light detecting unit.

Abstract: An integrated circuit for driving high-voltage LED lamps is applied to a rectified alternative current (AC) power and a plurality of LED stacks. The integrated circuit includes a control unit, a plurality of current-clamping units which electrically connect to the control unit and the LED stacks respectively, and a plurality of current-sensing units which electrically connect to the current-clamping units and the control unit. When the rectified power is switched on, the current-sensing unit constantly monitors the electrical current flowing through the respective current-clamping unit and feeds back the monitored data to the control unit. The control unit sequentially switches on or off the current-clamping units according to the combinatorial logic state of the monitored data.

Abstract: A method is disclosed for determining a fault surface in a formation, comprising: determining a first plurality of crosscorrelation values for a 3D Volume associated, respectively, with a corresponding first plurality of 3D Volumes, and selecting a first minimum one of the first plurality of crosscorrelation values, a first derived fault segment corresponding to the first minimum one of the first plurality of crosscorrelation values, the first derived fault segment approximately lying on the fault surface and tending to determine the fault surface in the formation.

Abstract: A method is disclosed for determining a fault surface in a formation, comprising: determining a first plurality of crosscorrelation values for a 3D Volume associated, respectively, with a corresponding first plurality of 3D Volumes, and selecting a first minimum one of the first plurality of crosscorrelation values, a first derived fault segment corresponding to the first minimum one of the first plurality of crosscorrelation values, the first derived fault segment approximately lying on the fault surface and tending to determine the fault surface in the formation.