Abstract: The technology disclosed relates to constructing a convolutional neural network-based classifier for variant classification. In particular, it relates to training a convolutional neural network-based classifier on training data using a backpropagation-based gradient update technique that progressively match outputs of the convolutional neutral network-based classifier with corresponding ground truth labels. The convolutional neural network-based classifier comprises groups of residual blocks, each group of residual blocks is parameterized by a number of convolution filters in the residual blocks, a convolution window size of the residual blocks, and an atrous convolution rate of the residual blocks, the size of convolution window varies between groups of residual blocks, the atrous convolution rate varies between groups of residual blocks. The training data includes benign training examples and pathogenic training examples of translated sequence pairs generated from benign variants and pathogenic variants.

Abstract: Disclosed are a system and method for processing HL7 messages. A method includes receiving, an HL7 message; storing the HL7 message in a memory; creating a data structure representation of the stored HL7 message in the memory that stores a start index and an end index of the stored HL7 message, wherein the start index indicates a beginning of the stored HL7 message and the end index indicates an end of the stored HL7 message; hierarchically creating, from the data structure representation of the stored HL7 message, one or more data structure representations in the memory that store at least one start index and at least one end index corresponding to one or more fragments in the stored HL7 message; and, modifying the stored HL7 message according to the at least one start index and a corresponding end index of the fragments in the HL7 message.

Abstract: The technology disclosed includes systems and methods to reduce overfitting of neural network-implemented models that process sequences of amino acids and accompanying position frequency matrices. The system generates supplemental training example sequence pairs, labelled benign, that include a start location, through a target amino acid location, to an end location. A supplemental sequence pair supplements a pathogenic or benign missense training example sequence pair. It has identical amino acids in a reference and an alternate sequence of amino acids. The system includes logic to input with each supplemental sequence pair a supplemental training position frequency matrix (PFM) that is identical to the PFM of the benign or pathogenic missense at the matching start and end location. The system includes logic to attenuate the training influence of the training PFMs during training the neural network-implemented model by including supplemental training example PFMs in the training data.

Abstract: Systems, computer-implemented methods, and non-transitory computer readable media are provided for determining related ontological data. The disclosed systems may be configured to receive a first ontology and a second ontology, the first ontology and the second ontology comprising hierarchically organized ontological data. The disclosed systems may also be configured to receive an indication that a first ontological datum in the first ontology is equivalent to a second ontological datum in the second ontology, and a query for ontological data related to a third ontological datum subordinate to the first ontological datum. The disclosed systems may be configured to determine a first semantic distance between the third ontological datum and a fourth ontological datum in the second ontology satisfies a semantic distance criterion, and output the fourth ontological datum based on the determination that the first semantic distance satisfies the semantic distance criterion.

Abstract: Systems and methods are provided for identifying genes with outlier expression across multiple samples, including: at least one processor; and at least one non-transitory computer readable medium containing instructions that, when executed by the at least one processor, cause the at least one processor to perform operations including: receiving gene expression data of a plurality of samples, the samples comprising gene expression values corresponding to genes; standardizing the gene expression data using the median and median absolute deviation of each gene; determining a value of a distribution statistic for the standardized gene expression observations based on a probability of outlier gene expression data; determining a null distribution of the distribution statistic using the standardized gene expression data; and outputting a significance value of the genes across the multiple samples, the significance value based on the value of the distribution statistic and the null distribution.

Abstract: Electrical power for an electrical device can be acoustically produced. A first portion of an acoustic energy can be received at a piezoelectric transducer. A first electrical energy, produced from the first portion of the acoustic energy, can be conveyed from the piezoelectric transducer and received by a circuit. A bias voltage, produced from the first electrical energy, can be conveyed from the circuit and received at a capacitive transducer. A second portion of the acoustic energy can be received at the capacitive transducer. A second electrical energy, produced from the second portion of the acoustic energy, can be conveyed from the capacitive transducer and used as the electrical power for the electrical device. A ratio of the second electrical energy to the second portion of the acoustic energy can be greater than a ratio of the first electrical energy to the first portion of the acoustic energy.

Abstract: Systems and techniques are provided for a power receiver circuit. A power generating mechanism may include power generating elements that may generate alternating current signals. Rectifier circuit may include rectifiers that may generate a direct current signal from an alternating current signal, and diodes. Group circuits that may connect groups of rectifier circuits in electrical circuits to combine the direct current signals from the rectifier circuits in a group into a single direct current signal. A step down converter may be connected to the group circuits. The step down converter may convert a direct current signal to a direct current signal of a target voltage level. An output switch may be connected to the step down converter. A linear regulator may be connected to the step down converter. A microcontroller may be connected to the linear regulator and the output switch and may control the output switch.

Abstract: Embodiments of the disclosure provide a method and system of interpreting HL7 segments of an HL7 message. The method includes: electronically obtaining and interpreting a grammar definition to determine a prescribed hierarchy of HL7 segment definitions; creating a resulting segment hierarchy data structure, the resulting segment hierarchy data structure comprising a top segment; performing steps: (a) obtaining an HL7 segment from a plurality of HL7 segments in the HL7 message, (b) determining a parent-child relationship for the HL7 segment, and (c) adding the HL7 segment to the resulting segment hierarchy data structure; and, continuing to perform steps (a), (b), and (c) on remaining HL7 segments of the plurality of HL7 segments until all HL7 segments of the HL7 message have been added to the resulting segment hierarchy data structure.

Abstract: The technology disclosed relates to constructing a convolutional neural network-based classifier for variant classification. In particular, it relates to training a convolutional neural network-based classifier on training data using a backpropagation-based gradient update technique that progressively match outputs of the convolutional network network-based classifier with corresponding ground truth labels. The convolutional neural network-based classifier comprises groups of residual blocks, each group of residual blocks is parameterized by a number of convolution filters in the residual blocks, a convolution window size of the residual blocks, and an atrous convolution rate of the residual blocks, the size of convolution window varies between groups of residual blocks, the atrous convolution rate varies between groups of residual blocks. The training data includes benign training examples and pathogenic training examples of translated sequence pairs generated from benign variants and pathogenic variants.

Abstract: The disclosure provides a processing method, device and system for data of a distributed storage system. The method includes: acquiring a first schema structure of target data and a second schema structure of source data; and processing the source data into structural data of the first schema structure according to the first schema structure and the second schema structure. The disclosure solves a problem that a data schema structure in a distributed storage system in related arts is inflexible to be described. There is a beneficial effect of improving description flexibility of the data schema structure so as to improve data processing efficiency.

Abstract: The technology disclosed includes systems and methods to reduce overfitting of neural network-implemented models that process sequences of amino acids and accompanying position frequency matrices. The system generates supplemental training example sequence pairs, labelled benign, that include a start location, through a target amino acid location, to an end location. A supplemental sequence pair supplements a pathogenic or benign missense training example sequence pair. It has identical amino acids in a reference and an alternate sequence of amino acids. The system includes logic to input with each supplemental sequence pair a supplemental training position frequency matrix (PFM) that is identical to the PFM of the benign or pathogenic missense at the matching start and end location. The system includes logic to attenuate the training influence of the training PFMs during training the neural network-implemented model by including supplemental training example PFMs in the training data.

Abstract: The technology disclosed relates to constructing a convolutional neural network-based classifier for variant classification. In particular, it relates to training a convolutional neural network-based classifier on training data using a backpropagation-based gradient update technique that progressively match outputs of the convolutional network network-based classifier with corresponding ground truth labels. The convolutional neural network-based classifier comprises groups of residual blocks, each group of residual blocks is parameterized by a number of convolution filters in the residual blocks, a convolution window size of the residual blocks, and an atrous convolution rate of the residual blocks, the size of convolution window varies between groups of residual blocks, the atrous convolution rate varies between groups of residual blocks. The training data includes benign training examples and pathogenic training examples of translated sequence pairs generated from benign variants and pathogenic variants.

Abstract: There is provided an overvoltage protection circuit including: a comparator configured to compare a DC voltage supplied to a first load by a power generator with a first value set based on an upper limit of an operating voltage of the first load; a storage element configured to be charged with a portion of a current generated by the power generator; and a switch configured to change a flow of the current so that: when the DC voltage is higher than the first value, the portion of the current is supplied to the storage element and a second load coupled to the storage element in parallel, and when the DC voltage is less than or equal to the first value, the storage element supplies the second load with power.

Abstract: Methods for processing data using information gained from examining biological materials identifies and characterized probes for Single Nucleotide Polymorphisms and identifies Off Target Variants.

Abstract: The present invention provides medicaments for use in treating and methods of treating T-cell acute lymphoblas-leukemia, acute lymphoblastic leukemia, chronic lymphoblastic leukemia, acute myelogenous leukemia, chronic myelogenous leukemia, erythroleukemia, triple negative breast cancer, breast cancer, ovarian cancer, melanoma, Sung cancer, non small-cell lung cancer, pancreatic cancer, glioblastoma, colorectal cancer, head and neck cancer, cervical cancer, prostate cancer, liver cancer, oral squamous cell carcinoma, skin cancer, medul!ob!astoma, hepatocellular carcinoma, intrahepatic and extrahepatic cholangiocarcinoma, desmoid tumor, soft tissue sarcoma, or adenoid cystic carcinoma in a patient comprising combination therapy with 4,4,4-tri-fluoro-N-[(1S)-2˜[[(7S)-5-(2-hydroxyemyl)-6-oxo-7H-pyrido [23- d][3]benzazepin-7-yl ]amino]-1-methyl-2-oxo-ethyljbutanamide, or a pharmaceutically acceptable salt or hydrate thereof, and a PD-1 or a PD-L1 inhibitor selected from pembrolizumab, nivolumab, atezolizumab, dur

Abstract: A power supply apparatus includes, a power generating circuit that converts energy to power and output a voltage of the power, a first switch installed on either or both of a pair of power lines, a first switch control circuit that controls the first switch based on the level of the voltage, a second switch installed on a branched line coupled to the pair of power lines, a second switch control circuit that controls the second switch based on the level of the voltage, and controls the second switch so that the second switch is repeatedly turned on and off when a power storage circuit is charged with power generated by the power generating circuit, and the power storage circuit installed on the branched line and coupled to the power generating circuit when the first switch and the second switch are set to ON states.

Abstract: An apparatus for detecting conductance parameter of high protein body fluid sample is provided. The apparatus includes at least one liquid collection element, and at least two electrodes horizontally aligned in the liquid collection element. Also provided are methods for detecting dehydration in a subject, comprising the steps of measuring the conductance parameter of the saliva of the subject.

Abstract: The technology disclosed relates to constructing a convolutional neural network-based classifier for variant classification. In particular, it relates to training a convolutional neural network-based classifier on training data using a backpropagation-based gradient update technique that progressively match outputs of the convolutional network network-based classifier with corresponding ground truth labels. The convolutional neural network-based classifier comprises groups of residual blocks, each group of residual blocks is parameterized by a number of convolution filters in the residual blocks, a convolution window size of the residual blocks, and an atrous convolution rate of the residual blocks, the size of convolution window varies between groups of residual blocks, the atrous convolution rate varies between groups of residual blocks. The training data includes benign training examples and pathogenic training examples of translated sequence pairs generated from benign variants and pathogenic variants.

Abstract: The technology disclosed relates to constructing a convolutional neural network-based classifier for variant classification. In particular, it relates to training a convolutional neural network-based classifier on training data using a backpropagation-based gradient update technique that progressively match outputs of the convolutional network network-based classifier with corresponding ground truth labels. The convolutional neural network-based classifier comprises groups of residual blocks, each group of residual blocks is parameterized by a number of convolution filters in the residual blocks, a convolution window size of the residual blocks, and an atrous convolution rate of the residual blocks, the size of convolution window varies between groups of residual blocks, the atrous convolution rate varies between groups of residual blocks. The training data includes benign training examples and pathogenic training examples of translated sequence pairs generated from benign variants and pathogenic variants.

Abstract: A method of treating an inflammatory disorder in a subject, comprising administering to the subject in need thereof a nucleic acid molecule for inhibiting the expression of Hom-1. Specifically, the nucleic acid molecule is an RNAi agent or an antisense morpholino oligonucleotide. Further disclosed is a method of selecting a therapeutic for an inflammatory disorder in a subject, or monitoring the efficacy of a therapeutic for an inflammatory disorder in a subject, comprising detecting the expression level of Hom-1 in an inflamed tissue sample obtained from the subject.