Abstract: A method for producing adipic acid and cyclohexanone oxime from cyclohexane is provided. Cyclohexane and NOx undergo oxidation-nitration reaction to produce a mixture of adipic acid, nitrocyclohexane, nitrogen oxides and by-product A, from which adipic acid and nitrocyclohexane are separated. The nitrocyclohexane is catalytically hydrogenated with hydrogen to produce cyclohexanone oxime and a small amount of cyclohexylamine, where cyclohexanone oxime is collected, and the cyclohexylamine is partially oxidized with molecular oxygen to obtain cyclohexanone oxime and by-product B. Without separation, or after removing part or all of water from the reaction mixture, under the action of a catalyst, the reaction mixture undergoes hydrogenation and amination simultaneously or sequentially, or the hydrogenation alone, and separation to give cyclohexanone oxime.

Abstract: A laser radar integrated box at least includes an outer housing (A10), a lifting device (A20), a laser radar (A40), a controller (A50), and a lower cover plate (A60); the lifting device (A20), the laser radar (A40), and the controller (A50) are located between the outer housing (A10) and the lower cover plate (A60); the laser radar (A40) is located above the lifting device (A20); and the lifting device (A20) can extend or retract under the control of the controller (A50) to drive the laser radar (A40) to extend to the outside of an automobile or retract to the inside of the automobile. The laser radar integrated box can be flexibly arranged on the roof of a vehicle. Further disclosed are a cleaning device and a vehicle.

Abstract: A capsule endoscope image recognition method based on deep learning, and a device and a medium is provided. After a plurality of frames of continuously captured images are processed to form an image sequence of a specific format, multi-channel recognition is performed on the plurality of frames of images by means of a 3D convolutional neural network model, and a recognition result is then output in combination with a recognition probability of each channel, such that the image recognition precision is improved.

Abstract: The present invention relates to a built-in bio-sleeve and preparation method and use thereof. In order to provide a suitable built-in bio-sleeve material for dorsal nerve isolation surgery and penis enlargement surgery, a novel acellular allogeneic dermal matrix material is prepared in the present invention, which is manufactured into a built-in bio-sleeve for the treatment of premature ejaculation and short and small penis. The acellular allogeneic dermal matrix or the built-in bio-sleeve of the present invention is used for dorsal nerve isolation surgery, penis enlargement or lengthening surgery without cutting off the dorsal nerve, thereby avoiding the probability of psychological erectile dysfunction caused by the patient's worry about cutting off the dorsal nerve.

Abstract: Techniques are provided for assessing uniqueness of information using string-based collection frequency techniques. One method comprises obtaining multiple collections of documents from at least one data source; determining a collection frequency for a given character string based on a number of the collections comprising the given character string relative to a total number of the collections; assigning a uniqueness rating to the given character string based at least in part on a comparison of the collection frequency of the given character string to a collection frequency of one or more additional character strings in one or more of the plurality of collections; and performing an automated action using the given character string based on the assigned uniqueness rating. The automated action may comprise protecting the given character string and/or identifying the given character string as important information satisfying one or more importance criteria.

Abstract: Methods, apparatus, and processor-readable storage media for detecting security threats in storage systems using AI techniques are provided herein. An example computer-implemented method includes obtaining historical performance data and historical capacity data pertaining to one or more storage objects within a storage system; determining supervised datasets pertaining to security threat-related data and non-security threat-related data by processing at least a portion of the obtained data using a first set of AI techniques; configuring a second set of AI techniques based at least in part on the determined supervised datasets; detecting one or more security threats in connection with at least one storage object within the storage system by processing input data from the at least one storage object using the second set of AI techniques; and performing at least one automated action based at least in part on the one or more detected security threats.

Abstract: An apparatus comprises a processing device configured to obtain performance data for a plurality of workloads, to select a subset of the performance data corresponding to a subset of the plurality of workloads having a given workload type, and to generate a model characterizing an expected performance of the given workload type by analyzing the selected subset of the performance data to estimate a queuing curve characterizing the expected performance of the given workload type. The processing device is also configured, responsive to determining that a quality of the generated model is above a designated threshold quality level, to utilize the generated model to identify performance impacting events for a given workload of the given workload type and to modify provisioning of compute, storage and network resources allocated to the given workload responsive to identifying performance impacting events for the given workload of the given workload type.

Abstract: Methods, apparatus, and processor-readable storage media for automatically determining sizing configurations for storage components using machine learning techniques are provided herein. An example computer-implemented method includes obtaining multiple items of input related to at least one storage component; determining a set of storage component sizing configurations by processing at least a portion of the multiple items of input using a first set of one or more machine learning techniques comprising at least one deep learning technique; identifying a subset of the storage component sizing configurations by processing at least a portion of the determined set of storage component sizing configurations using a second set of one or more machine learning techniques; and performing one or more automated actions based at least in part on the identified subset of storage component sizing configurations.

Abstract: Methods, apparatus, and processor-readable storage media for detecting security threats in storage systems using AI techniques are provided herein. An example computer-implemented method includes obtaining historical performance data and historical capacity data pertaining to one or more storage objects within a storage system; determining supervised datasets pertaining to security threat-related data and non-security threat-related data by processing at least a portion of the obtained data using a first set of AI techniques; configuring a second set of AI techniques based at least in part on the determined supervised datasets; detecting one or more security threats in connection with at least one storage object within the storage system by processing input data from the at least one storage object using the second set of AI techniques; and performing at least one automated action based at least in part on the one or more detected security threats.

Abstract: Techniques are provided for assessing uniqueness of information using string-based collection frequency techniques. One method comprises obtaining multiple collections of documents from at least one data source; determining a collection frequency for a given character string based on a number of the collections comprising the given character string relative to a total number of the collections; assigning a uniqueness rating to the given character string based at least in part on a comparison of the collection frequency of the given character string to a collection frequency of one or more additional character strings in one or more of the plurality of collections; and performing an automated action using the given character string based on the assigned uniqueness rating. The automated action may comprise protecting the given character string and/or identifying the given character string as important information satisfying one or more importance criteria.

Abstract: Methods, apparatus, and processor-readable storage media for automatically determining sizing configurations for storage components using machine learning techniques are provided herein. An example computer-implemented method includes obtaining multiple items of input related to at least one storage component; determining a set of storage component sizing configurations by processing at least a portion of the multiple items of input using a first set of one or more machine learning techniques comprising at least one deep learning technique; identifying a subset of the storage component sizing configurations by processing at least a portion of the determined set of storage component sizing configurations using a second set of one or more machine learning techniques; and performing one or more automated actions based at least in part on the identified subset of storage component sizing configurations.

Abstract: The present invention relates to a built-in bio-sleeve and preparation method and use thereof. In order to provide a suitable built-in bio-sleeve material for dorsal nerve isolation surgery and penis enlargement surgery, a novel acellular allogeneic dermal matrix material is prepared in the present invention, which is manufactured into a built-in bio-sleeve for the treatment of premature ejaculation and short and small penis. The acellular allogeneic dermal matrix or the built-in bio-sleeve of the present invention is used for dorsal nerve isolation surgery, penis enlargement or lengthening surgery without cutting off the dorsal nerve, thereby avoiding the probability of psychological erectile dysfunction caused by the patient's worry about cutting off the dorsal nerve.

Abstract: LKB1 mutation status and/or expression, YES expression and phosphorylation level; and/or CD24 expression are employed to predict melanoma prognosis and response to therapeutics. Inhibitors (including targeted inhibitors) of SRC family kinases (especially YES) are employed to treat melanoma.

Abstract: A carbon nanotube-based solar cell and fabricating method thereof are provided. The method is achieved by applying carbon nanotube film (1) photoelectric conversion material and an upper electrode simultaneously. The method improves photoelectric conversion efficiency and life time of the solar cell, the fabricating method of the solar cell is simple, and the fabricating cost is low.

Abstract: A method of processing a video sequence is provided. The video sequence includes a plurality of video frames, wherein each of the plurality of video frames includes a plurality of macroblocks. Further, each of the plurality of macroblocks includes a plurality of pixels. The method includes determining energy values for pixels in a first macroblock and a second macroblock, determining a respective attenuation factor for each of the plurality of pixels in the first macroblock and determining a modified intensity value for each of the plurality of pixels in the first macroblock based on the respective attenuation factor for each of the plurality of pixels in the first macroblock, a respective intensity value of each of the plurality of pixels in the first macroblock and a mean intensity value of the first macroblock.