Abstract: Personalized machine learning systems and methods are provided to predict the collective response of a patient's CD8+ T cells by modeling positive and negative selection processes. For each individual patient, HLA-I self peptides were used as negative selection, and allele-matched immunogenic T cell epitopes as positive selection. The negative and positive peptides were used to train a binary classification model, which was then applied to predict the immunogenicity of candidate neoantigens of that patient.

Abstract: The present systems and methods introduce deep learning to de novo peptide sequencing from tandem mass spectrometry data, and in particular mass spectrometry data obtained by data-independent acquisition. The systems and methods achieve improvements in sequencing accuracy over existing systems and methods and enables complete assembly of novel protein sequences without assisting databases. To sequence peptides from mass spectrometry data obtained by data-independent acquisition, precursor profiles representing intensities of one or more precursor ion signals associated with a precursor retention time and fragment ion spectra representing signals from fragment ions and fragment retention times are fed into a neural network.

Abstract: The present systems and methods are directed to de novo identification of peptide sequences from tandem mass spectrometry data. The systems and methods uses unconverted mass spectrometry data from which features are extracted. Using unconverted mass spectrometry data reduces the loss of information and provides more accurate sequencing of peptides. The systems and methods combine deep learning and neural networks to sequencing of peptides.

Abstract: Disclosed herein is a scalable onboarding system and methods for efficiently onboarding one or more new partner channels into credit product company's system. The onboarding system and methods may create, use, and test different types of logic: core logic and partner-specific logic. The core logic may be logic that performs common functions among the partner channels, and the partner-specific logic may be logic that performs partner-specific functions. The partner-specific logic may originate from modular and customizable logic, modified to include partner-specific branding elements, functions, and configurations. Each time a new partner channel is onboarded into the credit product company's system, in some embodiments, only the partner-specific logic may need to be created and tested. This allows new partner channels to be quickly added without requiring new logic be written for each new partner channel.

Abstract: The present systems and methods introduce deep learning to de novo peptide sequencing from tandem mass spectrometry data. The systems and methods achieve improvements in sequencing accuracy over existing systems and methods and enables complete assembly of novel protein sequences without assisting databases. The present systems and methods are re-trainable to adapt to new sources of data and provides a complete end-to-end training and prediction solution, which is advantageous given the growing massive amount of data. The systems and methods combine deep learning and dynamic programming to solve optimization problems.

Abstract: Examples described herein relate to a packet processing device. In some examples, the packet processing device includes multiple processors and data plane circuitry. In some examples, a first processor of the multiple processors is to perform a first control plane, a second processor of the multiple processors is to perform a second control plane, and the first and second control planes are to communicate through an interface and wherein the first control plane is to discover capabilities of data plane circuitry and configure operation of the data plane circuitry by the interface.

Abstract: The present disclosure provides isolated binding molecules that bind to and activates CD137, vectors comprising a nucleic acid molecules encoding an amino acid sequence of the binding molecules, host cells containing the vectors, methods of making the binding molecules, pharmaceutical compositions containing the binding molecules, and methods of using such antibodies, antibody fragments and derivatives and polypeptides, including methods of treating a disease requiring stimulation of immune responses including cancer.

Abstract: A process for operating a thermal or catalytic cracking unit is described. The process entails generating a product that includes cracked hydrocarbon vapor and solid coke-particles from a heavy hydrocarbon input. The product is communicated towards a fractionator and a quench liquid is introduced into the product for creating a two-phase flow of cracked hydrocarbon vapor and the quench liquid with solid coke-particles entrained in the quench liquid. The two-phase flow is introduced into the fractionator and the cracked hydrocarbon vapor are separated from the quench liquid and the solid coke-particles entrained therein by gravity separation. The two-phase flow can reduce or remove the requirement of a wash zone within the fractionator. A recirculation loop is included in a wash-zone circulation system. The recirculation loop bypasses one or more spray headers of the wash zone and returns to a first end of the wash-zone circulation system.

Abstract: The present systems and methods are directed to de novo identification of peptide sequences from tandem mass spectrometry data. The systems and methods uses unconverted mass spectrometry data from which features are extracted. Using unconverted mass spectrometry data reduces the loss of information and provides more accurate sequencing of peptides. The systems and methods combine deep learning and neural networks to sequencing of peptides.

Abstract: The present systems and workflows identify neoantigens for cancer immunotherapy by introducing deep learning to de novo peptide sequencing from tandem mass spectrometry data. The systems and workflow allows for patient specific identification of neoantigens for personalized immunotherapy.

Abstract: Methods and systems for determining amino acid sequence of a polypeptide or protein from mass spectrometry data is provided, using a weighted de Bruijn graph. Extracted and purified protein is cleaved into a mixture of peptide and then analyzed using mass spectrometry. A list of peptide sequences is derived from mass spectrometry fragment data by de novo sequencing, and amino acid confidence scores are determined from peak fragment ion intensity. A weighted de Bruijn graph is constructed for the list of peptide sequences having node weights defined by k?1 mer confidence scores. At least one contig is assembled from the de Bruijn graph by identifying node weights having the highest k?1 mer confidence scores.

Abstract: The present systems and methods introduce deep learning to de novo peptide sequencing from tandem mass spectrometry data, and in particular mass spectrometry data obtained by data-independent acquisition. The systems and methods achieve improvements in sequencing accuracy over existing systems and methods and enables complete assembly of novel protein sequences without assisting databases. To sequence peptides from mass spectrometry data obtained by data-independent acquisition, precursor profiles representing intensities of one or more precursor ion signals associated with a precursor retention time and fragment ion spectra representing signals from fragment ions and fragment retention times are fed into a neural network.

Abstract: The present systems and methods introduce deep learning to de novo peptide sequencing from tandem mass spectrometry data. The systems and methods achieve improvements in sequencing accuracy over existing systems and methods and enables complete assembly of novel protein sequences without assisting databases. The present systems and methods are re-trainable to adapt to new sources of data and provides a complete end-to-end training and prediction solution, which is advantageous given the growing massive amount of data. The systems and methods combine deep learning and dynamic programming to solve optimization problems.

Abstract: A process for operating a thermal or catalytic cracking unit is described, The process entails generating a product that includes cracked hydrocarbon vapor and solid coke-particles from a heavy hydrocarbon input. The product is communicated towards a fractionator and a quench liquid is introduced into the product for creating a two-phase flow of cracked hydrocarbon vapor and the quench liquid with solid coke-particles entrained in the quench liquid. The two-phase flow is introduced into the fractionator and the cracked hydrocarbon vapor are separated from the quench liquid and the solid coke-particles entrained therein by gravity separation. The two-phase flow can reduce or remove the requirement of a wash zone within the fractionator. A recirculation loop is included in a wash-zone circulation system. The recirculation loop bypasses one or more spray headers of the wash zone and returns to a first end of the wash-zone circulation system.

Abstract: Methods and systems for determining amino acid sequence of a polypeptide or protein from mass spectrometry data is provided, using a weighted de Bruijn graph. Extracted and purified protein is cleaved into a mixture of peptide and then analyzed using mass spectrometry. A list of peptide sequences is derived from mass spectrometry fragment data by de novo sequencing, and amino acid confidence scores are determined from peak fragment ion intensity. A weighted de Bruijn graph is constructed for the list of peptide sequences having node weights defined by k?1 mer confidence scores. At least one contig is assembled from the de Bruijn graph by identifying node weights having the highest k-1 mer confidence scores.

Abstract: This disclosure allows parties to virtualize prospective and existing financial instruments (including derivative and other analogous complex financial instruments) and other data set into one or more computer software applications via a user authoring software toolkit, and to upload such one or more virtualized instrument to a cloud hosting environment (or analogous online storage ecosystem) for further sharing of such virtualized instruments with interested parties over a communications network where other market participants may engage with the cloud hosting environment and search for, download, and review such virtualized instruments. Further, the Disclosure allows for downloading parties and authors to communicate directly and to do such “peer to peer” communications on an anonymous, partially anonymous, or non-anonymous basis, and have such communications be secure and/or encrypted.

Abstract: The Financial Instrument Discovery, Transparency, Communication, and Trading Facilitation invention allows parties to virtualize prospective and existing financial instruments (including derivative and other analogous complex financial instruments) into one or more computer software applications via a user authoring software toolkit, and to upload such one or more virtualized instrument to a cloud hosting environment (or analogous online storage ecosystem) for further sharing of such virtualized instruments with interested parties over a communications network where other market participants may engage with the cloud hosting environment and search for, download, and review such virtualized instruments. Further, the Invention allows for downloading parties and authors to communicate directly and to do such “peer to peer” communications on an anonymous, partially anonymous, or non-anonymous basis, and have such communications be secure and/or encrypted.

Abstract: A preconnectorized outdoor cable streamlines the deployment of optical waveguides into the last mile of an optical network. The preconnectorized outdoor cable includes a cable and at least one plug connector. The plug connector is attached to a first end of the cable, thereby connectorizing at least one optical waveguide. The cable has at least one optical waveguide, at least one tensile element, and a cable jacket. Various cable designs such as figure-eight or flat cables may be used with the plug connector. In preferred embodiments, the plug connector includes a crimp assembly having a crimp housing and a crimp band. The crimp housing has two half-shells being held together by the crimp band for securing the at least one tensile element. When fully assembled, the crimp housing fits into a shroud of the preconnectorized cable. The shroud aides in mating the preconnectorized cable with a complimentary receptacle.

Abstract: A multi-operational amplifier system comprises a plurality of operational amplifiers and a controller to configure the plurality of operational amplifiers. The operational amplifiers may be selectively configured to operate individually or in combination with other of the operational amplifiers. The operational amplifiers may have different common node inputs. In one aspect, the different inputs may be selected from groups of PMOS, N-type NMOS and NZ NMOS inputs. The operational amplifiers may include the different inputs that are arranged as differential pairs.

Abstract: A loopback device utilizing bend insensitive optical fiber to facilitate deployment of a connectorized fiber optic distribution cable through small-diameter conduit. A loopback device utilizing bend insensitive optical fiber for use within an optical network to route optical signals transmitted downstream along one or more optical fibers back upstream along the same or other optical fibers for the purpose of the determining the integrity of the downstream and upstream optical paths from a single upstream location. A loopback device including one or more bend insensitive optical fibers, a multi-fiber loopback ferrule and a dust cap for sealing engaging a connector plug attached to a distribution cable or a tether of a pre-engineered distribution cable assembly prior to installation of the distribution cable.