Abstract: Solar power systems and methods utilize DC power transmission and centralized power inversion. The solar power systems include a photovoltaic (PV) bus system and a fixed bus system. The PV system utilizes a control mode handoff control method, which includes determining that a local maximum power point tracking (MPPT) control is enabled; in response to determining that the local MPPT control is enabled, starting an MPPT mode timer; performing local MPPT; determining that the MPPT mode timer is greater than a predetermined period; and, in response to determining that the MPPT mode timer is greater than a predetermined period, handing off MPPT control to the next MPPT controller. The distributed MPPT control method may include sequential MPPT control, adaptive ?V MPPT control, and/or power limiting control. The fixed bus system includes PV string-level MPPT controllers and a fixed DC input central inverter or multiple fixed DC modular inverters.

Abstract: A method for generating a layout of a Josephson junction array includes obtaining an original script, in which geometric and action parameters are defined in the original script, the geometric parameters comprise a first structural parameter and a second structural parameter, the action parameters comprise an initial position parameter and a connection parameter; obtaining a first parameter value, a second parameter value, an initial position value, and a connection parameter value; in the original script, respectively assigning the first parameter value, the second parameter value, the initial position value, and the connection parameter value to the first structural parameter, the second structural parameter, the initial position parameter, and the connection parameter, so as to obtain a target script; and performing the target script to obtain a layout of a Josephson junction array having multiple connected Josephson junctions.

Abstract: A method may include detecting an occurrence of a logistic exception during a fulfilment cycle of an order. An impact of the logistic exception may be determined based on a tracking model having a plurality of interconnected tracking objects. The plurality of interconnected tracking objects may include a first tracking object corresponding to the order, a second tracking object corresponding to an order item included in the order, a third tracking object corresponding to a delivery order item corresponding to the order item, a fourth tracking object corresponding to a first delivery order including the delivery order item, and a fifth tracking object corresponding to a transport event including the delivery order. One or more of the plurality of interconnected tracking objects may be updated based at least on the impact of the logistic exception. Related systems and computer program products are also provided.

Abstract: Split-cell and multi-panel photovoltaic backtracking control systems and methods allow for increased total power generation during low sun elevation conditions by shading a percentage of panel modules, thereby allowing for a lower angle of incidence on unshaded modules. The control systems and methods involve determining a sun elevation angle, a traditional backtracking angle, a split-cell or multi-panel backtracking angle, a single-cell or single-panel relative light transmission (RLT) based on the single-cell or single-panel backtracking angle, and a split-cell or multi-panel RLT based on the split-cell or multi-panel backtracking angle. If twice the single-cell or single-panel RLT is greater than the split-cell or multi-panel RLT, the split-cell or multi-panel backtracking angle is used; otherwise, the single-cell or single-panel backtracking angle is used.

Abstract: Solar power systems and methods utilize DC power transmission and centralized power inversion. The solar power systems include a photovoltaic (PV) bus system and a fixed bus system. The PV system utilizes a control mode handoff control method, which includes determining that a local maximum power point tracking (MPPT) control is enabled; in response to determining that the local MPPT control is enabled, starting an MPPT mode timer; performing local MPPT; determining that the MPPT mode timer is greater than a predetermined period; and, in response to determining that the MPPT mode timer is greater than a predetermined period, handing off MPPT control to the next MPPT controller. The distributed MPPT control method may include sequential MPPT control, adaptive ?V MPPT control, and/or power limiting control. The fixed bus system includes PV string-level MPPT controllers and a fixed DC input central inverter or multiple fixed DC modular inverters.

Abstract: The present disclosure relates to a cargo protection method, device and system, and a non-transitory computer-readable storage medium, relating to the technical field of unmanned aerial vehicles. The method of the present disclosure includes: determining whether an unmanned aerial vehicle is in a falling state or not according to a current acceleration in a vertical direction of the unmanned aerial vehicle and a current vertical distance from the unmanned aerial vehicle to the ground; and opening at least one airbag in a cargo hold of the unmanned aerial vehicle in a case where the unmanned aerial vehicle is in the falling state to protect a cargo in the cargo hold.

Abstract: A genetic testing method including obtaining a to-be-processed genetic sequence, where an average number of gene fragments corresponding to each position in the genetic sequence is less than or equal to a preset threshold; performing signature extraction on the genetic sequence, and obtaining a gene signature; enhancing the gene signature, and obtaining an enhanced signature corresponding to the gene signature; and testing the genetic sequence based on the enhanced signature, and obtaining a testing result. Based on the technical solutions, signature extraction is performed on the genetic sequence, and the gene signature is obtained; the gene signature is then enhanced, and the enhanced signature is obtained; and then the genetic sequence is tested based on the enhanced signature, and the testing result is obtained. In this way, not only is genetic testing precision ensured, but also data processing costs and the quantity of processed data are further effectively reduced.

Abstract: The present disclosures provide a genome feature extraction method, a disease prediction method, an apparatus and a device. The feature extraction method includes: obtaining a gene segment to be processed, the gene segment including a base quality; determining a confidence level corresponding to the gene segment based on the base quality; and performing a feature extraction operation on the gene segment based on the confidence level corresponding to the gene segment to obtain gene features of the gene segment. The embodiments effectively achieve an effective integration of the base quality into the gene features without increasing the dimensionality of data. In this way, not only the mode of implementation is simple and reliable and the completeness of extraction of gene features is ensured, but also the operation efficiency of an extraction operation on the gene features is improved.

Abstract: Methods, apparatuses, devices and systems for genetic testing and model training are provided. A genetic testing method includes: obtaining genetic data to be processed, an average number of genetic segments corresponding to each position in the genetic data to be processed being less than or equal to a preset threshold; inputting the genetic data to be processed into a feature generation network layer for performing a feature extraction operation to obtain genetic features corresponding to the genetic data to be processed and enhanced features corresponding to the genetic features; and inputting the genetic data to be processed and the enhanced features into a genetic identification network layer for performing a genetic testing operation to obtain a testing result.

Abstract: Solar power systems and methods utilize DC power transmission and centralized power inversion. The solar power systems include a photovoltaic (PV) bus system and a fixed bus system. The PV system utilizes a control mode handoff control method, which includes determining that a local maximum power point tracking (MPPT) control is enabled; in response to determining that the local MPPT control is enabled, starting an MPPT mode timer; performing local MPPT; determining that the MPPT mode timer is greater than a predetermined period; and, in response to determining that the MPPT mode timer is greater than a predetermined period, handing off MPPT control to the next MPPT controller. The distributed MPPT control method may include sequential MPPT control, adaptive ?V MPPT control, and/or power limiting control. The fixed bus system includes PV string-level MPPT controllers and a fixed DC input central inverter or multiple fixed DC modular inverters.

Abstract: Processing genetic data is disclosed including inputting data, the data corresponding to source data for gene sequencing on a sample, receiving a selected data processing technique, performing, using the selected data processing technique, gene sequencing processing on the inputted data based on the pathogen genome of a predetermined pathogen to obtain a data processing result, the data processing result indicating whether the sample includes the predetermined pathogen, and presenting the data processing result.

Abstract: Split-cell and multi-panel photovoltaic backtracking control systems and methods allow for increased total power generation during low sun elevation conditions by shading a percentage of panel modules, thereby allowing for a lower angle of incidence on unshaded modules. The control systems and methods involve determining a sun elevation angle, a traditional backtracking angle, a split-cell or multi-panel backtracking angle, a single-cell or single-panel relative light transmission (RLT) based on the single-cell or single-panel backtracking angle, and a split-cell or multi-panel RLT based on the split-cell or multi-panel backtracking angle. If twice the single-cell or single-panel RLT is greater than the split-cell or multi-panel RLT, the split-cell or multi-panel backtracking angle is used; otherwise, the single-cell or single-panel backtracking angle is used.

Abstract: The present disclosure relates to a cargo protection method, device and system, and a non-transitory computer-readable storage medium, relating to the technical field of unmanned aerial vehicles. The method of the present disclosure includes: determining whether an unmanned aerial vehicle is in a falling state or not according to a current acceleration in a vertical direction of the unmanned aerial vehicle and a current vertical distance from the unmanned aerial vehicle to the ground; and opening at least one airbag in a cargo hold of the unmanned aerial vehicle in a case where the unmanned aerial vehicle is in the falling state to protect a cargo in the cargo hold.

Abstract: Techniques and systems are disclosed for generating and implementing operational status classification extensions to determine multivariate rankings of network elements. A management system includes components that poll network elements to collect operational information such as performance metrics for operationally associated network elements. In response to detecting an operational event based on the operational information, the system includes components for generating training data and processing the training data to generate operational status classifier components.

Abstract: Techniques and systems are disclosed for implementing program extensions. A plugin is instantiated from a class definition object and a plugin interface template. The plugin interface template is a markup language object describing and internally associated with the class definition object. The instantiating includes reading the plugin interface template to determine the template-to-object association and, based on the association, the class definition object and the plugin interface template are stored within a execution memory space of a plugin interface. A plugin interface executes the plugin including in response to a data collection request specifying a plugin ID and one or more input data parameters and one or more method parameters, accessing one or more method objects that are specified by a script language method object defined by the class and that correspond to the method parameters, and executing at least one of the one or more method objects using the input data parameters.

Abstract: Methods, systems, and program products for processing API queries are disclosed. In some embodiments, in response to a data request that is received from a user interface and that includes a first query and one or more extension references, an application modifies the data request by replacing a first extension reference of the one or more extension references with a query post-processing script. In response to receiving the modified data request, an intermediate service transacts the first query with a first data source having a network address included in the modified data request to obtain a first query result. The intermediate service executes the query post-processing script based, at least in part, on the first query result.

Abstract: For each of a plurality of time intervals over which metric data is collected from periodic polling of a network of devices, a determination is made of whether metric data of the time interval satisfies a criterion for normal data values defined for a metric corresponding to the metric data. The metric data is marked as anomaly data, in response to determining that the metric data does not satisfy the criterion defined for the metric corresponding to the metric data of the time interval. The metric data is marked as normal data, in response to determining that the metric data satisfies the criterion defined for the metric corresponding to the metric data of the time interval. The metric data marked as normal data is stored in a first database, and the metric data marked as anomaly data and corresponding time intervals in a second database.

Abstract: A data collection workflow architecture can streamline data collection from a heterogeneous network and leverage plug-ins of various technologies for data collection from the heterogeneous network. The data collection workflow architecture uses a workflow definition which is an abstracted series of data collection tasks. The workflow definition expresses the data collection tasks at a level abstracted away from the underlying implementation to increase the ease and efficiency of managing and maintaining data collections on a heterogeneous network. A workflow engine transforms each of the higher level expressions of data collections tasks into task definitions that can be passed to a plug-in engine. The task definition can be considered the abstracted process level expression of a data collection task with variable values injected into it.

Abstract: Runtime data maintained in memory of an executing application is often inaccessible except through functions defined in an application programming interface (API) for the application. As a result, a user or software needs to have knowledge of the API and have access to the internal API functions of the application to access or manipulate the runtime data. To enable easier to access runtime data of an executing application, a query system can be implemented that allows for runtime data to be accessed using a common query language instead of application specific APIs. The query system allows for constructing a query which is submitted to a query engine executing alongside an application. The query engine translates or maps terms in the query to API functions defined for accessing the runtime data of the application. The query engine executes scripts to invoke the API functions for carrying out a received query.

Abstract: A data validation system receives sets of performance metrics captured by a first monitoring system and a second monitoring system that are monitoring the same components within a data center. The data validation system pairs each set of performance metrics from the first monitoring system to a set of performance metrics from the second monitoring system that are of the same type and related to a same component. The data validation system then normalizes each of the paired sets of performance metrics so that a similarity score for each of the paired sets can be determined. The similarity score is based on a cosine similarity of a paired set of performance metrics multiplied by a ratio of the average value of each of the paired set of performance metrics.