Abstract: The invention provides, in various embodiments, polypeptides (e.g., camelid antibodies and antigen binding fragments thereof) that specifically bind to Spike glycoprotein of severe acute respiratory syndrome coronavirus (e.g., SARS-CoV-2-Spike). The invention also provides, in various embodiments, fusion proteins comprising one or more of the polypeptides, polynucleotides encoding the polypeptides, vectors and host cells suitable for expressing the polypeptides, and methods for treating viral infections (e.g., COVID-19).

Abstract: A system is disclosed for de novo protein generation. The system receives a set of design condition(s) that specify target characteristics of a synthetic protein. The system defines a modular energy function as a composition of a diffusion energy component and one or more conditioner energy components. The system applies a diffusion model to determine a denoised protein backbone. In applying the diffusion model, in each sampling step: the system transforms one prior sampled state of the synthetic protein from unconstrained space into constrained space based on the one or more design conditions, denoises the prior sampled state in the constrained space, and samples a subsequent sampled stated by applying a gradient of the modular energy function to the denoised prior sampled state in the constrained space. The final sampled state is a denoised protein backbone for the synthetic protein that satisfies the set of design condition(s).

Abstract: The invention provides, in various embodiments, polypeptides that specifically bind to Spike glycoprotein of severe acute respiratory syndrome coronavirus (e.g., SARS-CoV-2-Spike). The invention also provides, in various embodiments, fusion proteins comprising one or more of the polypeptides, polynucleotides encoding the polypeptides, vectors and host cells suitable for expressing the polypeptides, and methods for treating viral infections (e.g., COVID-19).

Abstract: The invention provides, in various embodiments, polypeptides that specifically bind to Spike glycoprotein of severe acute respiratory syndrome coronavirus (e.g., SARS-CoV-2-Spike). The invention also provides, in various embodiments, fusion proteins comprising one or more of the polypeptides, polynucleotides encoding the polypeptides, vectors and host cells suitable for expressing the polypeptides, and methods for treating viral infections (e.g., COVID-19).

Abstract: The invention provides, in various embodiments, polypeptides (e.g., camelid antibodies and antigen binding fragments thereof) that specifically bind to Spike glycoprotein of severe acute respiratory syndrome coronavirus (e.g., SARS-CoV-2-Spike). The invention also provides, in various embodiments, fusion proteins comprising one or more of the polypeptides, polynucleotides encoding the polypeptides, vectors and host cells suitable for expressing the polypeptides, and methods for treating viral infections (e.g., COVID-19).

Abstract: The invention provides, in various embodiments, polypeptides that specifically bind to Spike glycoprotein of severe acute respiratory syndrome coronavirus (e.g., SARS-CoV-2-Spike). The invention also provides, in various embodiments, fusion proteins comprising one or more of the polypeptides, polynucleotides encoding the polypeptides, vectors and host cells suitable for expressing the polypeptides, and methods for treating viral infections (e.g., COVID-19).

Abstract: Disclosed herein are systems and methods to efficiently execute predictions models to identify future values associated with various nodes. A server retrieves a set of nodes and generates a primary prediction model using data aggregated based on all nodes. The server then executes various clustering algorithms in order to segment the nodes into different clusters. The server then generates a secondary (corrective) prediction model to calculate a correction needed to improve the results achieved by executing the primary prediction model for each cluster. When a node with unknown/limited data and attributes is identified, the server identifies a cluster most similar the new node and further identifies a corresponding secondary prediction model. The server then executes the primary prediction model in conjunction with the identified secondary prediction model to populate a graphical user interface with an accurate predicted future attribute for the new node.

Abstract: Disclosed herein are systems and methods to efficiently execute predictions models to identify future values associated with various nodes. A server retrieves a set of nodes and generates a primary prediction model using data aggregated based on all nodes. The server then executes various clustering algorithms in order to segment the nodes into different clusters. The server then generates a secondary (corrective) prediction model to calculate a correction needed to improve the results achieved by executing the primary prediction model for each cluster. When a node with unknown/limited data and attributes is identified, the server identifies a cluster most similar the new node and further identifies a corresponding secondary prediction model. The server then executes the primary prediction model in conjunction with the identified secondary prediction model to populate a graphical user interface with an accurate predicted future attribute for the new node.

Abstract: Disclosed herein are systems and methods to efficiently execute predictions models to identify future values associated with various nodes. The systems and methods described herein retrieve a set of nodes and execute various clustering algorithms in order to segment the nodes into different clusters. The systems and methods described herein also describe generating one or more prediction models, such as time-series models, for each cluster of nodes. When a node with unknown/limited data and attributes is identified, the methods and systems described herein first identify a cluster most similar the new node, identify a corresponding prediction model, and execute the identified prediction model to calculate future attribute of the new node.

Abstract: Disclosed herein are systems and methods to efficiently execute predictions models to identify future values associated with various nodes. The systems and methods described herein retrieve a set of nodes and execute various clustering algorithms in order to segment the nodes into different clusters. The systems and methods described herein also describe generating one or more prediction models, such as time-series models, for each cluster of nodes. When a node with unknown/limited data and attributes is identified, the methods and systems described herein first identify a cluster most similar the new node, identify a corresponding prediction model, and execute the identified prediction model to calculate future attribute of the new node.

Abstract: The invention provides a method of enhancing the effectiveness of pesticides, as well as pesticidal formulations. Furthermore, it also provides the means for the de novo rational design of pesticides. The present invention also relates to a method of screening agents for potential use in insecticides, particularly against mosquitoes.

Abstract: A system for converting a first representation of a color input image to a second representation and method for performing same are disclosed. The system includes apparatus for mapping primary axes and overprint axes of a selected color coordinate system to primary axes and overprint axes of a printer color coordinate system of the second representation, thereby to produce primary conversion tables and overprint conversion tables and apparatus for converting the first representation to the second representation utilizing the primary and overprint conversion tables. The system also includes printing apparatus for printing the second representation and for producing an output print, wherein the output print is a reproduction of the color input image within the selected color coordinate system. Furthermore, the system enables selection of operator-selected appearance parameters used to match desired printer conditions in accordance with the appearance parameters.