Abstract: A two-phase cold plate includes a base, an upper cover, a heat exchange cavity and a cooling fin module. The upper cover is installed on the base, the heat exchange cavity is formed between the base and the upper cover, and the cooling fin module is installed in the heat exchange cavity. The upper cover includes at least one nozzle module and a plurality of two-phase fluid channels. The two-phase fluid channels are respectively located on both sides of the nozzle module, and the nozzle module sprays a heat dissipating fluid to the cooling fin module, and the heat dissipating fluid flows along the cooling fin module to the two-phase fluid channels on both sides of the cooling fin module to cool the cooling fin module.

Abstract: A capacitor structure for a power semiconductor device includes a semiconductor substrate, an isolation insulating layer having a ring-shape and including an outer periphery and an inner periphery defining an opening region, a first electrode disposed on the isolation insulating layer, a dielectric layer disposed on the first electrode, and a second electrode disposed on the dielectric layer.

Abstract: A coolant distribution unit includes a casing, a control module, a power supply module, a heat exchange module, an integrated pipe, and a fluid driving module. The power supply module is electrically connected to the control module, the integrated pipe includes a plurality of inlets and an outlet to collect and output a cooled working fluid, the fluid driving module is electrically connected to the control module and the power supply module, and the fluid driving module is in fluid communication with the heat exchange module. The control module, power supply module, heat exchange module, integrated pipe, and fluid driving module are all arranged in the casing.

Abstract: A capacitor structure for a power semiconductor device includes a semiconductor substrate, an isolation insulating layer having a ring-shape and including an outer periphery and an inner periphery defining an opening region, a first electrode disposed on the isolation insulating layer, a dielectric layer disposed on the first electrode, and a second electrode disposed on the dielectric layer.

Abstract: A method for manufacturing an ultra-thin glass substrate includes: providing a glass base material preset with n substrate areas and a skeleton area surrounding the substrate areas; at least forming an etching protection layer on an upper surface and a lower surface of each substrate area of the glass base material, respectively; at least etching the skeleton area of the glass base material to separate the substrate areas from the glass base material, and form a stress dissipation edge along an edge of each substrate area; and removing the etching protection layer to get independent glass substrates. A method for manufacturing a display panel is also disclosed. An aim is to prevent quality of the ultra-thin glass substrate from damage caused by scribing wheel cutting or laser cutting, therefore the quality of the ultra-thin glass substrate is improved.

Abstract: A method for manufacturing ultra-thin glass substrates and a method for manufacturing a display panel are provided, including: providing a glass base material preset with n substrate areas and a skeleton area surrounding the substrate areas, wherein n is greater than or equal to 1; at least forming an etching protection layer, wherein, each etching protection layer includes a main area and at least one thinned area extending along a preset bending path; at least etching the skeleton area of the glass base material to separate the substrate areas from the glass base material, forming at least one bending stress dissipation groove, and forming a stress dissipation edge along an edge of each substrate area; removing the etching protection layer to get independent glass substrates having the bending stress dissipation groove. The method improves bending performance along the preset bending path.

Abstract: A method for manufacturing ultra-thin glass substrates and a method for manufacturing a display panel are provided. The method for manufacturing ultra-thin glass substrates includes: providing a glass base material preset with n substrate areas and a skeleton area surrounding the substrate areas; at least forming an etching protection layer on each substrate area of the glass base material; immersing the glass base material in a reaction chamber having etching medium; after the edge of each substrate area is etched to form the stress dissipation edge and the substrate areas are separated from the glass base material, the substrate areas falling down by gravity and falling into the basket; pulling the basket out of the reaction chamber to get the substrate areas separated from the glass base material; removing the etching protection layer to get independent glass substrates.

Abstract: Aspects of the invention include a computer-implemented method by executing, via a processor, a bottleneck model training process for microservices in a microservice system, wherein for each of the microservices the bottleneck model training process filters out a subset of training data based at least in part on a current situation setting. Building, via the processor, a bottleneck indicator model for each of the microservices using information from the bottleneck model training process, convergence points for an expected response time. Executing, via the processor, a bottleneck identification process for providing system alerts when a bottleneck is identified, wherein the bottleneck identification process uses analysis to monitor a data stream according to the bottleneck indicator model which uses the convergence points for response times.

Abstract: In an approach, a processor obtains a first set of training samples, one of the training samples including values of a plurality of performance indicators of a target system observed at a historical point in time. A processor determines whether the first set of training samples are qualified for training a prediction model, the prediction model predicting an operational status of the target system at a target point in time based on values of the plurality of performance indicators observed at the target point in time. A processor, in response to determining that the first set of training samples are qualified for training the prediction model, trains, the prediction model based on the first set of training samples.

Abstract: A method for manufacturing an ultra-thin glass substrate includes: providing a glass base material preset with n substrate areas and a skeleton area surrounding the substrate areas; at least forming an etching protection layer on an upper surface and a lower surface of each substrate area of the glass base material, respectively; at least etching the skeleton area of the glass base material to separate the substrate areas from the glass base material, and form a stress dissipation edge along an edge of each substrate area; and removing the etching protection layer to get independent glass substrates. A method for manufacturing a display panel is also disclosed. An aim is to prevent quality of the ultra-thin glass substrate from damage caused by scribing wheel cutting or laser cutting, therefore the quality of the ultra-thin glass substrate is improved.

Abstract: According to one or more embodiments of the present invention a computer-implemented method includes receiving a transaction-data for a transaction that occurs in a particular time-interval. The method further includes comparing a set of parameters from the transaction-data with a performance profile associated with the particular time-interval. The method further includes based on determining that the transaction is a deviant transaction, forwarding the transaction-data to a first data collector. The method further includes based on determining that the transaction is a conventional transaction, forwarding the transaction-data to a second data collector.

Abstract: A computer-implemented method for recommending a monitoring interval in provided. A non-limiting example of the computer-implemented method includes receiving, by a processor, monitoring data at an initial monitoring interval and calculating, by the processor, a set of aggregation data from the monitoring data including a first subset of aggregation data at a first interval of the initial monitoring interval. The method calculates, by the processor, a first density score for the first subset of aggregation data and a first indicator score for the first subset of aggregation data and provides, by the processor, the first interval as a recommended interval when the first density score does not exceed a density threshold and the first indicator threshold does not exceed an indicator threshold.

Abstract: Embodiments include cognitive control of runtime resource monitoring scope. Aspects include obtaining historical data for each of a plurality of metrics for a computer system and calculating, based on the historical data, an anomaly relationship score for each of the plurality of metrics. Aspects also include calculating, based on the historical data, a sensitivity score for each of the plurality of metrics and determining a priority score for each of the plurality of metrics based upon a weighted combination of the anomaly relationship score and the priority score. Aspects further include receiving real-time data for each of the plurality of metrics and presenting a subset of the real-time data to a user, the subset created by selecting one or more of the plurality of metrics based on the priority score of each of the plurality of metrics.

Abstract: Embodiments include cognitive control of runtime resource monitoring scope. Aspects include obtaining historical data for each of a plurality of metrics for a computer system and calculating, based on the historical data, an anomaly relationship score for each of the plurality of metrics. Aspects also include calculating, based on the historical data, a sensitivity score for each of the plurality of metrics and determining a priority score for each of the plurality of metrics based upon a weighted combination of the anomaly relationship score and the priority score. Aspects further include receiving real-time data for each of the plurality of metrics and presenting a subset of the real-time data to a user, the subset created by selecting one or more of the plurality of metrics based on the priority score of each of the plurality of metrics.

Abstract: Aspects of the invention include detecting and predicting application performance. A non-limiting example computer-implemented method includes receiving source code and generating a first model of the source code by labeling a word of the source code. The computer implemented method optimizes the first model of the source code by assembling the first model of the source code with a plurality of models generated by a model generation module into a second model of the source code and extracts at least two basic features from the second model of the source code. The computer-implemented method provides an estimated performance of the source code based on historical data of the basic features extracted from the second model of the source code.

Abstract: A computer system to detect data alerts includes a data preprocessing system and a data analysis system. The data preprocessing system obtains system data of the computer system, generates predicted data based on the system data, and generates differential data indicating a difference between the system data and the predicted data. The data analysis is in signal communication with the data preprocessing system and determines that the differential data is one of expected event or an anomaly event in response to adding at least one new value from the differential data to the predicted data.

Abstract: The present invention provides a device or medical device comprising a graphene coating. Particularly, the graphene coating features substantially high transmittance, biointegrity and biocompatibility.

Abstract: Techniques for data storage strategy determination are described herein. An aspect includes determining a plurality of file classifications for files that are stored in a data storage system based on performance history data of a disaster recovery (DR) system of the data storage system. Another aspect includes determining classification records and performance records for the DR system based on the plurality of file classifications. Another aspect includes determining an information loss based on the performance records. Another aspect includes determining a total cost savings based on the classification records. Another aspect includes determining a recommended recovery time objective (RTO)/recovery point objective (RPO) strategy based on the information loss and the total cost savings. Another aspect includes implementing the recommended RTO/RPO strategy in the DR system.

Abstract: In an approach, a processor obtains a first set of training samples, one of the training samples including values of a plurality of performance indicators of a target system observed at a historical point in time. A processor determines whether the first set of training samples are qualified for training a prediction model, the prediction model predicting an operational status of the target system at a target point in time based on values of the plurality of performance indicators observed at the target point in time. A processor, in response to determining that the first set of training samples are qualified for training the prediction model, trains, the prediction model based on the first set of training samples.

Abstract: Techniques for data storage strategy determination are described herein. An aspect includes determining a plurality of file classifications for files that are stored in a data storage system based on performance history data of a disaster recovery (DR) system of the data storage system. Another aspect includes determining classification records and performance records for the DR system based on the plurality of file classifications. Another aspect includes determining an information loss based on the performance records. Another aspect includes determining a total cost savings based on the classification records. Another aspect includes determining a recommended recovery time objective (RTO)/recovery point objective (RPO) strategy based on the information loss and the total cost savings. Another aspect includes implementing the recommended RTO/RPO strategy in the DR system.