Abstract: Methods, systems, apparatuses, and computer-readable storage mediums described herein are directed to determining and recommending an optimal compute resource configuration for a cloud-based resource (e.g., a server, a virtual machine, etc.) for migrating a customer to the cloud. The embodiments described herein utilize a statistically robust approach that makes recommendations that are more flexible (elastic) and account for the full distribution of the amount of resource usage. Such an approach is utilized to develop a personalized rank of relevant recommendations to a customer. To determine which compute resource configuration to recommend to the customer, the customer's usage profile is matched to a set of customers that have already migrated to the cloud. The compute resource configuration that reaches the performance most similar to the performance of the configurations utilized by customers in the matched set is recommended to the user.

Abstract: A cooling apparatus is provided. An external cooling fluid flows into an external inlet opening from an external inlet pipe and passes through a heat exchanger to flow out of an external outlet opening to an external outlet pipe. An internal cooling fluid flows into an internal inlet pipe from the server and flows into an internal inlet opening from the internal inlet pipe and passes through the heat exchanger for heat exchange with the external cooling fluid to flow out of an internal outlet opening to an internal outlet pipe. A hot-swap pump has a pump main body, an inlet anti-leakage pipe, an outlet anti-leakage pipe and a hot-swap connector. The inlet anti-leakage pipe includes an inlet connector and an inlet anti-leakage valve. The outlet anti-leakage pipe includes an outlet connector and an outlet anti-leakage valve. The hot-swap connector is electrically connected to the pump main body.

Abstract: The present disclosure describes a semiconductor device includes a substrate, a buffer layer on the substrate, and a stacked fin structure on the buffer layer. The buffer layer can include germanium, and the stacked fin structure can include a semiconductor layer with germanium and tin. The semiconductor device further includes a gate structure wrapped around a portion of the semiconductor layer and an epitaxial structure on the buffer layer and in contact with the semiconductor layer. The epitaxial structure includes germanium and tin.

Abstract: A semiconductor device includes a first layer that includes a first semiconductor material disposed on a semiconductor substrate, and a second layer of a second semiconductor material disposed on the first layer. The semiconductor substrate includes Si. The first semiconductor material and the second semiconductor material are different. The second semiconductor material is formed of an alloy including a first element and Sn. A surface region of an end portion of the second layer at both ends of the second layer has a higher concentration of Sn than an internal region of the end portion of the second layer. The surface region surrounds the internal region.

Abstract: The present disclosure describes a semiconductor device includes a substrate, a buffer layer on the substrate, and a stacked fin structure on the buffer layer. The buffer layer can include germanium, and the stacked fin structure can include a semiconductor layer with germanium and tin. The semiconductor device further includes a gate structure wrapped around a portion of the semiconductor layer and an epitaxial structure on the buffer layer and in contact with the semiconductor layer. The epitaxial structure includes germanium and tin.

Abstract: A method and an apparatus for processing Bitmap data are provided by the embodiments of the present disclosure. The method for processing Bitmap data includes: dividing a Bitmap region in a disk into a plurality of partitions in advance and setting an update region in the disk; obtaining a respective amount of dirty data corresponding to each of the plurality of partitions in memory in response to a condition for writing back to the disk being satisfied; finding multiple second partitions with an amount of dirty data satisfying to be merged into the update region from the plurality of partitions according to the respective amount of dirty data corresponding to each of the plurality of partitions; and recording dirty data corresponding to the multiple second partitions in the memory into the update region in the disk through one or more I/O operations after merging.

Abstract: A device comprises a gate structure, n-type source/drain features, p-type source/drain features, an NFET channel, and a PFET channel. The gate structure is over a substrate. The n-type source/drain features are on opposite first and second sides of the gate structure, respectively. The p-type source/drain features are on opposite third and fourth sides of the gate structure, respectively. The NFET channel extends within the gate structure and connects the n-type source/drain features. The PFET channel extends within the gate structure and connects the p-type source/drain features. The NFET channel and the PFET channel are vertically spaced apart by the gate structure.

Abstract: A computing system automatically manages error reports. Each error report specifies an error that occurred within a subsystem of the computing system. A received error report is added into a root cause grouping. Each root cause grouping contains error reports having error types traceable to a same root cause. A deployment time at which the subsystem corresponding to the error report was deployed within the computing system is determined. A severity score for the root cause grouping is generated as a function of the deployment time. The severity score inversely correlates to a time period length between the deployment time and the occurrence time of the error. The root cause grouping is assigned to a ranked error container of a plurality of ranked error containers based on the generated severity score. Each ranked error container contains root cause groupings having severity scores within a specified score range.

Abstract: A p-aminobenzoic acid-producing microorganism is provided. The p-aminobenzoic acid-producing microorganism is obtained by a method for preparing a p-aminobenzoic acid-producing microorganism. The method for preparing a p-aminobenzoic acid-producing microorganism includes (a) performing an acclimation process on a source microorganism with at least one sulfonamide antibiotic to obtain at least one acclimatized microorganism and (b) screening out at least one p-aminobenzoic acid-producing microorganism from the at least one acclimatized microorganism, wherein the at least one p-aminobenzoic acid-producing microorganism has a higher p-aminobenzoic acid titer than the source microorganism.

Abstract: Methods, systems, and computer program products are provided for creating a resource management testing environment. An initial population of databases is established in a database ring, having an in initial count of databases and different types of databases that are determined based on an initial database population model. The initial population model receives ring classification information for the database ring from a ring grouping model. A sequence of database population-change events is generated based on a model, to change the population of the databases over time in the ring. An orchestration framework performs testing of resource manager operations based on the model-defined initial population of databases and the model-defined populations of databases changed over time. Model-defined resource usage metrics for each database are utilized to test the resource manager operations. Resource usage metrics and database add/drop events of a production system are used to train the models.

Abstract: Aspects of the present disclosure provide a method for training a predictor that predicts performance of a plurality of machine learning (ML) models on platforms. For example, the method can include converting each of the ML models into a plurality of instructions or the instructions and a plurality of intermediate representations (IRs). The method can also include simulating execution of the instructions corresponding to each of the ML models on a platform and generating instruction performance reports. Each of the instruction performance reports can be associated with performance of the instructions corresponding to one of the ML models that are executed on the platform. The method can also include training the predictor with the instructions or the IRs as learning features and the instruction performance reports as learning labels, compiling the predictor into a library file, and storing the library file in a storage device.

Abstract: Methods, systems, and computer program products are provided for creating a resource management testing environment. An initial population of databases is established in a database ring, having an in initial count of databases and different types of databases that are determined based on an initial database population model. The initial population model receives ring classification information for the database ring from a ring grouping model. A sequence of database population-change events is generated based on a model, to change the population of the databases over time in the ring. An orchestration framework performs testing of resource manager operations based on the model-defined initial population of databases and the model-defined populations of databases changed over time. Model-defined resource usage metrics for each database are utilized to test the resource manager operations. Resource usage metrics and database add/drop events of a production system are used to train the models.

Abstract: A computing system automatically manages error reports. Each error report specifies an error that occurred within a subsystem of the computing system. A received error report is added into a root cause grouping. Each root cause grouping contains error reports having error types traceable to a same root cause. A deployment time at which the subsystem corresponding to the error report was deployed within the computing system is determined. A severity score for the root cause grouping is generated as a function of the deployment time. The severity score inversely correlates to a time period length between the deployment time and the occurrence time of the error. The root cause grouping is assigned to a ranked error container of a plurality of ranked error containers based on the generated severity score. Each ranked error container contains root cause groupings having severity scores within a specified score range.

Abstract: A semiconductor device includes a first layer that includes a first semiconductor material disposed on a semiconductor substrate, and a second layer of a second semiconductor material disposed on the first layer. The semiconductor substrate includes Si. The first semiconductor material and the second semiconductor material are different. The second semiconductor material is formed of an alloy including a first element and Sn. A surface region of an end portion of the second layer at both ends of the second layer has a higher concentration of Sn than an internal region of the end portion of the second layer. The surface region surrounds the internal region.

Abstract: A lotion composition is provided. The lotion composition includes a) about 1% to about 90%, by weight, of a rheology structurant; and a b) carrier.

Abstract: The present invention relates to a silicon dioxide composite particle with far-infrared radioactivity, which is formed by the hydrolysis, condensation and polymerization of an organic silane precursor having the structure of the formula (I) with a tetra-alkoxysilane. The high stability of organic silane precursor compounds and the low biotoxicity of silicon dioxide composite particles make the present far-infrared radioactive silicon dioxide composite particles of great potential for extensive use in related bio-products.

Abstract: A semiconductor device includes a first layer that includes a first semiconductor material disposed on a semiconductor substrate, and a second layer of a second semiconductor material disposed on the first layer. The semiconductor substrate includes Si. The first semiconductor material and the second semiconductor material are different. The second semiconductor material is formed of an alloy including a first element and Sn. A surface region of an end portion of the second layer at both ends of the second layer has a higher concentration of Sn than an internal region of the end portion of the second layer. The surface region surrounds the internal region.

Abstract: A cooling apparatus is provided. An external cooling fluid flows into an external inlet opening from an external inlet pipe and passes through a heat exchanger to flow out of an external outlet opening to an external outlet pipe. An internal cooling fluid flows into an internal inlet pipe from the server and flows into an internal inlet opening from the internal inlet pipe and passes through the heat exchanger for heat exchange with the external cooling fluid to flow out of an internal outlet opening to an internal outlet pipe. A hot-swap pump has a pump main body, an inlet anti-leakage pipe, an outlet anti-leakage pipe and a hot-swap connector. The inlet anti-leakage pipe includes an inlet connector and an inlet anti-leakage valve. The outlet anti-leakage pipe includes an outlet connector and an outlet anti-leakage valve. The hot-swap connector is electrically connected to the pump main body.