Abstract: The development of therapeutics against the Zika virus (ZIKV) requires the design of molecules capable of neutralizing the virus and preventing cellular infection. Among the known ZIKV epitopes for neutralizing antibodies, the fusion loop (FL), located on the envelope (E) protein, is of particular interest as it mediates the first step of cellular infection and is highly conserved among flaviviruses. Here, small synthetic proteins were computationally designed to bind ZIKV FL with high affinity. The candidate with the highest predicted affinity was synthesized experimentally. It binds to its target epitope with high affinity, either in the context of the E protein or within the entire virus. The protein also showed cross-reactive neutralization capacity against ZIKV and Dengue virus 1-2 in vitro. X-ray crystallography was used to validate the computational design as well as to provide additional insights into the structural basis of flavivirus neutralization by targeting the FL envelope protein.

Abstract: A system for an agricultural harvester can include a support structure configured to be operably coupled with an elevator housing. A carrier can be operably coupled with the support structure. A vision-based sensor can be operably coupled with the carrier. One or more light sources can be operably coupled with the carrier. A panel can be positioned along a portion of the carrier. A cleaning system can be configured to remove debris from the panel positioned between at least one of the vision-based sensor and the one or more light sources. A computing system performs various operations. The operations can include determining a detected percentage of pixels within the data indicating debris on the panel on the panel and initiating a cleaning routine to remove at least a portion of the debris from the panel.

Abstract: A computer system for displaying sample images includes one or more processors configured to receive at least one sample image, each of the at least one sample images having been obtained by imaging a sample located in or on a sample holder using a microscope according to an imaging process; receive or generate spatial context information regarding the at least one sample image, the spatial context information having reference to the imaging process for obtaining the at least one sample image; and control a display to display the at least one sample image on the display based on the spatial context information regarding the at least one sample images.

Abstract: This invention refers to a grain flaking modular system, a grain flaking system, and a method that produces a grain flake within a predetermined specification. The grain flaking modular system comprises: valves (124); a PLC (130) connected to the valves (124); and an external optimization unit (140) connected to the PLC (130), wherein the external optimization unit (140) is configured to define a pressure reference (A). The grain flaking system (100) comprises: flaking rollers (110); and a programmable logic controller, PLC (PLC), configured to: obtain a pressure reference (A), and control a flaking pressure through the pressure reference (A) obtained. The grain flaking method comprises: obtaining (210) the pressure reference; applying (220) a flaking pressure to a flow of grains, wherein the flaking pressure is defined through the pressure reference obtained; and adjusting (230) the pressure reference.

Abstract: This invention refers to a modular system for a grain cracker, and a grain cracking system and method that generates cracked grains within a predetermined specification. The modular system comprises a motor (124); a PLC (134); and an external optimization unit (136) to drive the motor (124), based on an adjustment point (A). The grain cracking system (100) comprises: rollers (110); and a programmable logic controller, PLC (134), configured to: obtain an adjustment point (A), and control the gap between the rollers (110) from the obtained adjustment point (A). The grain cracking method comprises the steps of: obtaining (510) an adjustment point; controlling (520) the gap between the rollers; and altering (530) the adjustment point, should the characteristics of the cracked grains coming from the rollers not be compliant with the desired specifications, wherein the step of altering the adjustment point is performed continuously and automatically.

Abstract: This invention refers to a grain flaking modular system, a grain flaking system, and a method that produces a grain flake within a predetermined specification. The grain flaking modular system comprises: valves (124); a PLC (130) connected to the valves (124); and an external optimization unit (140) connected to the PLC (130), wherein the external optimization unit (140) is configured to define a pressure reference (A). The grain flaking system (100) comprises: flaking rollers (110); and a programmable logic controller, PLC (PLC), configured to: obtain a pressure reference (A), and control a flaking pressure through the pressure reference (A) obtained. The grain flaking method comprises: obtaining (210) the pressure reference; applying (220) a flaking pressure to a flow of grains, wherein the flaking pressure is defined through the pressure reference obtained; and adjusting (230) the pressure reference.

Abstract: A system for an agricultural harvester can include one or more processors and one or more non-transitory computer-readable media. The one or more non-transitory computer-readable media collectively store a machine-learned model configured to receive data associated with one or more harvest-related conditions for an agricultural harvester and process the data to determine a first harvest-related parameter associated with an infeed volume of harvest material for the agricultural harvester and instructions that, when executed by the one or more processors, configure the computing system to perform operations. The operations can include obtaining the data associated with one or more harvest-related conditions, inputting the data into the machine-learned model, and receiving a first value for the harvest-related parameter as a first output of the machine-learned model.

Abstract: A system for an agricultural harvester includes a chopper assembly configured to separate a harvested material into debris and stalk. A primary extractor is configured to remove debris from the harvester. A sensor system is configured to capture data associated with harvested material conditions downstream of the primary extractor. A computing system includes one or more processors and one or more non-transitory computer-readable media that collectively store instructions that, when executed by the one or more processors, configure the computing system to perform operations. The operations include obtaining the data associated with the associated harvested material conditions downstream of the primary extractor, determining a current foliage ratio based on the data, determining an error between the current foliage ratio to a desired foliage ratio, and generating a harvest-related parameter of the primary extractor based at least in part on the error.

Abstract: Systems, methods, and computer-readable storage media for responding to a query using a neural network and natural language processing. If necessary, the system can request disambiguation, then parse the query using a trained machine-learning classifier, resulting in at least one of an identified subject or an identified domain of the text query. The system can determine if the user is authorized to retrieve answers to the query and, if so, retrieve factual data associated with the query. The system can then retrieve a response template, and fill in the template with the retrieved facts. The system can then determine, by executing a machine comprehension model on the filled response template, a probable readability token, portion of text, of at least a portion of the filled response template and, upon identifying that the probable readability is above a threshold, reply to the text query with the at least a portion of the filled response template.

Abstract: A computer-implemented method for determining a value for at least three setting parameters by means of an input unit in the form of a graphical user interface with an input cursor positionable in an input area is provided. At least two of the at least three setting parameters can be set independently of one another. The method includes determining a position of the input cursor within the input area; determining a coordinate of the position of the input cursor for each particular setting parameter of the at least three setting parameters as a function of a distance in each case of the position of the input cursor from at least one coordinate origin allocated to the particular setting parameter; and determining a value for each particular setting parameter of the at least three setting parameters as a function of the coordinate determined for each particular setting parameter.

Abstract: A microscope control arrangement for operating a focusing device adapted to adjust a relative focus position of an objective in relation to a sample along an optical axis, including a display device configured to display a graphical user interface for receiving a user input and at least one processor configured to control the microscope focusing device and the display device for updating the graphical user interface in response to the user input, wherein the processor is configured to cause the graphical user interface to display a focus control interface including a graphical focus range element indicating a predetermined focus range and a graphical z-position pointer indicating a current z-position within the predetermined focus range, and wherein the graphical z-position pointer is movable along the graphical focus range element responsive to the user input to adjust the relative focus position to the current z-position indicated by the graphical z-position pointer.

Abstract: A system for providing study plans to a user includes a topic catalog storing multiple topics and multiple keywords associated with each topic. The system also includes a plan generator configured to receive multiple sample study plans, each sample study plan having one or more resources, each resource having one or more portions, and each portion being assigned a duration. The plan generator uses the sample study plans and the topic catalog to train a topic model to identify which topics are associated with each resource, resulting in a trained topic model. The plan generator receives a profile of a student from a user, the profile having one or more selected topics the student desires to study and further having multiple preferences associated with the student.

Abstract: Systems, methods, and computer-readable storage media for responding to a query using a neural network and natural language processing. If necessary, the system can request disambiguation, then parse the query using a trained machine-learning classifier, resulting in at least one of an identified subject or an identified domain of the text query. The system can determine if the user is authorized to retrieve answers to the query and, if so, retrieve factual data associated with the query. The system can then retrieve a response template, and fill in the template with the retrieved facts. The system can then determine, by executing a machine comprehension model on the filled response template, a probable readability token, portion of text, of at least a portion of the filled response template and, upon identifying that the probable readability is above a threshold, reply to the text query with the at least a portion of the filled response template.

Abstract: Intelligent management of employee sabbaticals is provided. An analysis of a profile of an employee requesting a sabbatical along with historical data and profiles corresponding to other employees of an employer is performed using an artificial intelligence component. Proposed sabbatical plan options for the employee are generated using the artificial intelligence component based on the analysis of the profile of the employee and the historical data and profiles corresponding to the other employees of the employer. Selections from the proposed sabbatical plan options by the employee are received via a sabbatical planner graphical user interface displayed on a client device of the employee. A sabbatical plan for the employee is generated using the artificial intelligence component based on the selections from the proposed sabbatical plan options by the employee. A set of action steps corresponding to the sabbatical for the employee is performed.

Abstract: Aspects map values of skills data for candidates to skills metadata representations stored within a metadata repository that includes skills metadata representation data dimensions for other candidates; filter via machine learning a top-trending subset of job classifications that have better career opportunity values from a universe of job classifications defined within the repository dimensional data values; determine via machine learning career path viability values for the top-trending subset job classifications as a function of strength of match to candidate dimensional values; project likely future values of mapped candidate values at the end of a future time period within a simulated work market scenario; and prioritize the top-trending subset job classifications as potential career paths for candidates as a function of the career path viability values and the projected future values of the dimensional data mapped for the candidates within the repository.

Abstract: Aspects map, without association to job description data, candidate skills and activity data values to a metadata representation within a metadata repository; determine, without association to the job description data, via a machine learning process, a plurality of employability values for the candidate for top-trending jobs as a function of strength of match of the mapped activity and skills values to respective skills and activity data values that are associated within the repository to top-trending jobs without association to values of the job description data that are associated to the top trending jobs; generate a prioritized subset of the top trending jobs that omits jobs that have employability values failing to meet a minimum threshold employability value; and drive a graphical user interface display to present the prioritized subset of the top trending jobs to the candidate ranked as a function of their determined employability values.

Abstract: Aspects identify target dimensional data value items via machine learning that are most strongly correlated to successful hires for job opportunities within employment data that are similar to a new job opportunity. In response to determining that the target item value for a candidate is deficient to qualify for the new job opportunity, aspects engage the candidate in an automated artificial intelligence chat bot agent interview process that acquires interview audio and image response data from the candidate; extract data relevant to the target item from interview audio and image data; determine an objective value for the target item as a function of the extracted data; and qualify the candidate for suitability for the new job opportunity as a function of resume data mapped to the metadata representation of the candidate and the objective value determined for the target item.

Abstract: Aspects map candidate resume data values to a resume metadata representation of the candidate defined by data dimensions stored within a metadata repository that includes resume metadata representation data dimensions of a plurality of candidates; learn via a machine learning process different trending demand values for job classifications within the dimensional data as a function of employment data; identify via the machine learning process an upwardly trending job position skill missing from the candidate data dimensions and most likely to match a current skill set of the candidate; add the identified skill to the first candidate data dimensions; and generate a resume for the first candidate as a function of the first candidate data dimensions to include the added skill.

Abstract: Aspects of the present invention provide devices that analyze employee health by determining a probability from reported measures of variances to normal work hours for at least one measure of expected employee health that includes expected sick leave or expected termination, and displaying the determined probability of expected employee health on a display device.

Abstract: A thrust generator developed for use in vehicles in general such as bicycles, motorcycles, motor cars and aircraft, as well as for other uses such as in wheelchairs, elevators or any other objects that require movement and/or fluctuation, the movement generator including a circular element having two portions of differing radius, in which an upper portion has a substantially semicircular circumference and a lower portion is substantially semi-elliptical, thereby establishing a circuit through which move peripheral sliding elements of equal weight and mass that rotate about a circular element in circular movements that provide different speeds to the sliding elements as a function of the stretch they are moving on, generating a directional vector and moving the unit and keeping it in movement or suspended in the air in a state of fluctuation and/or in a state of simultaneous fluctuation with movements, using the principles of centrifugal force.