Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating customized recommendations for environmentally-conscious cloud computing frameworks for replacing computing resources of existing datacenters. One of the methods involves receiving, through a user interface presented on a display of a computing device, data regarding a user's existing datacenter deployment and the user's preferences for the new cloud computing framework, generating one or more recommendations for environmentally-conscious cloud computing frameworks based on the received data, and presenting such recommendations through the user interface for the user's review and consideration.

Abstract: A system and method for target material retrieval and processing, the system comprising: an adaptor configured to interface with a capture region of a capture substrate for capturing particles in single-particle format within a set of wells, wherein the adaptor comprises a first region configured to interface with the capture region, a second region, and a cavity extending from the first region to the second region; and a support structure coupled to the adaptor and providing a set of operation modes for movement of the adaptor relative to the capture substrate. The system enables methods for magnetic and/or other force-based methods of retrieval of target material (e.g., derived from single cells).

Abstract: This disclosure provides a machine learning technique to predict a protein characteristic. A first training set is created that includes, for multiple proteins, a target feature, protein sequences, and other information about the proteins. A first machine learning model is trained and then used to identify which of the features are relevant as determined by feature importance or causal relationships to the target feature. A second training set is created with only the relevant features. Embeddings generated from the protein sequences are also added to the second training set. The second training set is used to train a second machine learning model. The first and second machine learning models may be any type of regressors. Once trained, the second machine learning model is used to predict a value for the target feature for an uncharacterized protein. The model of this disclosure provides 91% accuracy in predicting an ideal digestibility score.

Abstract: This disclosure provides a data-driven and scalable method to discover cause-and-effect relationships in data from natural systems that include sparse data sets. This technique can learn a causal graph from heterogenous data sources by combining embeddings from real data and embeddings from simulated data generated by process-based models. The causal graph is used for what-if analysis in out-of-distribution settings. One application is understanding the factors that affect soil carbon. A causal model created by these techniques can be used to discover cause-and-effect relationships that affect soil carbon. This model has applications such as forecasting soil carbon for a future time point to help inform farm practices. Farm practices, like tilling, may be modified in response to predictions provided by the model.

Abstract: A deep learning system is used to predict crop characteristics from inputs that include crop variety features, environmental features, and field management features. The deep learning system includes domain-specific modules for each category of features. Some of the domain-specific modules are implemented as convolutional neural networks (CNN) while others are implemented as fully-connected neural networks. Interactions between different domains are captured with cross attention between respective embeddings. Embeddings from the multiple domain-specific modules are concatenated to create a deep neural network (DNN). The prediction generated by the DNN is a characteristic of the crop such as yield, height, or disease resistance. The DNN can be used to select a crop variety for planting in a field. For a crop that is planted, the DNN may be used to select a field management technique.

Abstract: The techniques disclosed herein enable systems to optimize generation and dispatch of renewable energies using data-driven models. In many contexts, a renewable energy system is collocated with a local consumer such as a datacenter, a smart building, and so forth. The objective of the renewable energy system is to meet local power needs while participating in various energy markets of differing trading frequencies. To optimally manage the renewable energy system, a data-driven model is configured to analyze current conditions and generate policies to control renewable energy system operations. For instance, the model can retrieve current market prices, generation capacity, costs associated with generating energy, and so forth. Based on the collected information, the model can generate a policy that maximizes revenue obtained by the renewable energy system while meeting local demand. Through many iterations, the model can determine a realistically optimal policy for managing the renewable energy system.

Abstract: The systems and methods provide assistance in employee interactions. The systems and methods automatically schedule meetings between a manager and a report in response to changes in human resource data. The systems and methods track the meetings between the manager and the report during a time period and obtain meeting minutes for the meetings. The systems and methods analyze the meeting minutes and automatically generate feedback based on the analysis of the meeting minutes. The feedback is provided to the report or the manager.

Abstract: Systems and methods for evaluating attributes in supply chain management is disclosed. The system may receive data from a set of data sources corresponding to a supply chain associated with at least a product, pre-process the data based on integration of the data from each of the set of data sources, generate supply chain data based on the integrated data, analyze, via an orchestration engine, the supply chain data to assess an impact of the supply chain data on the supply chain, predict, via the orchestration engine, a state associated with a purchase event of the product in the supply chain, and generate a resolution flow to be executed in the supply chain for managing the predicted state associated with the purchase event of the product.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating customized recommendations for environmentally-conscious cloud computing frameworks for replacing computing resources of existing datacenters. One of the methods involves receiving, through a user interface presented on a display of a computing device, data regarding a user's existing datacenter deployment and the user's preferences for the new cloud computing framework, generating one or more recommendations for environmentally-conscious cloud computing frameworks based on the received data, and presenting such recommendations through the user interface for the user's review and consideration.

Abstract: A computing system is provided comprising a processor and a memory storing instructions executable by the processor. The instructions are executable to, during a run-time phase, receive run-time input data that includes time series data indicating a state of a graph network at each of a series of time steps. The graph network includes a plurality of nodes, and at least one edge connecting pairs of the nodes. The run-time input data is input into a trained graph neural network to thereby cause the graph neural network to output a predicted state of the graph network at one or more future time steps.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating customized recommendations for environmentally-conscious cloud computing frameworks for replacing computing resources of existing datacenters. One of the methods involves receiving, through a user interface presented on a display of a computing device, data regarding a user's existing datacenter deployment and the user's preferences for the new cloud computing framework, generating one or more recommendations for environmentally-conscious cloud computing frameworks based on the received data, and presenting such recommendations through the user interface for the user's review and consideration.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating customized recommendations for environmentally-conscious cloud computing frameworks for replacing computing resources of existing datacenters. One of the methods involves receiving, through a user interface presented on a display of a computing device, data regarding a user's existing datacenter deployment and the user's preferences for the new cloud computing framework, generating one or more recommendations for environmentally-conscious cloud computing frameworks based on the received data, and presenting such recommendations through the user interface for the user's review and consideration.

Abstract: Techniques of implementing partition level operations with concurrent activities are disclosed. A first operation can be performed on a first partition of a table of data. The first partition can be one of a plurality of partitions of the table, where each partition has a plurality of rows. A first partition level lock can be applied to the first partition for a period in which the first operation is being performed on the first partition, thereby preventing any operation other than the first operation from being performed on the first partition during the period the first partition level lock is being applied to the first partition. A second operation can be performed on a second partition of the table at a point in time during which the first operation is being performed on the first partition.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating customized recommendations for environmentally-conscious cloud computing frameworks for replacing computing resources of existing datacenters. One of the methods involves receiving, through a user interface presented on a display of a computing device, data regarding a user's existing datacenter deployment and the user's preferences for the new cloud computing framework, generating one or more recommendations for environmentally-conscious cloud computing frameworks based on the received data, and presenting such recommendations through the user interface for the user's review and consideration.

Abstract: Implementations of the present disclosure include receiving, by the cloud migration platform, user input indicating a type of case for cloud migration planning, the type including one of an abstract case and a detailed case, in response to receiving the type of case, selectively initiating, by the cloud migration platform, a discovery process for generating discovery data representative of infrastructure assets and application assets of the enterprise network, processing the discovery data through a sub-set of engines of a set of engines of the cloud migration platform, the sub-set of engines providing output including cloud platform selection data, application disposition data, target architecture data, bill of materials (BOM) data, and application remediation data, and generating, by a cloud migration planning engine of the cloud migration platform and based on the output, a cloud migration plan including an application sequence plan for migrating applications to one or more cloud platforms.

Abstract: In some examples, data classification and modelling based application compliance analysis may include generating, for application data for an application, and based on data laws, a knowledge graph schema that is used to generate an instantiated knowledge graph. Based on a plurality of data sources, domain knowledge and patterns, and the instantiated knowledge graph, classified data may be generated to generate an annotated knowledge graph. Based on the annotated knowledge graph, an indication of applicable sovereign laws and compliance related to the application data for the application may be generated. Based on the annotated knowledge graph and the applicable sovereign laws and compliance related to the application data for the application, a sovereign cloud strategy related to the application data for the application may be generated. Further, the sovereign cloud strategy may be applied to the application data for the application.

Abstract: Systems, methods, and computer-implemented products are provided that collect user file event notifications in real-time and optimizes the collected file event notifications by recognizing file event sets and pruning certain file events from the event sets. The optimized file event notification information is then indexed on an index server. The file's content information (e.g., sensitive information) and the file's metadata are independently collected and indexed and stored on the index server. The information from the optimized file event notifications, the file's content information, and the file's metadata are co-related to each other and presented in a file activity audit report.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating customized recommendations for environmentally-conscious cloud computing frameworks for replacing computing resources of existing datacenters. One of the methods involves receiving, through a user interface presented on a display of a computing device, data regarding a user's existing datacenter deployment and the user's preferences for the new cloud computing framework, generating one or more recommendations for environmentally-conscious cloud computing frameworks based on the received data, and presenting such recommendations through the user interface for the user's review and consideration.

Abstract: A flexible implantable electrode arrangement includes an electrically insulating carrier structure of a first polymer material, an electrically conductive layer, and an electrically insulating cover layer of a second polymer material. The electrically conductive layer includes an electrically conductive carbon fiber layer. The electrically conductive layer integrally forms an implantable electrode, a conductor track connected to the implantable electrode, and a contact pad. The electrically insulating cover layer at least partially covers the electrically conductive layer.

Abstract: Implementations of the present disclosure include receiving, by the cloud migration platform, user input indicating a type of case for cloud migration planning, the type including one of an abstract case and a detailed case, in response to receiving the type of case, selectively initiating, by the cloud migration platform, a discovery process for generating discovery data representative of infrastructure assets and application assets of the enterprise network, processing the discovery data through a sub-set of engines of a set of engines of the cloud migration platform, the sub-set of engines providing output including cloud platform selection data, application disposition data, target architecture data, bill of materials (BOM) data, and application remediation data, and generating, by a cloud migration planning engine of the cloud migration platform and based on the output, a cloud migration plan including an application sequence plan for migrating applications to one or more cloud platforms.