Abstract: This invention provides methods and systems for enhancement of protein production from mammalian cell lines in a drug inducible manner. The methods described herein can be used to generate a protein production cell line wherein the gene coding the protein product of interest is inserted into specific safe harbor loci (SHL) within the cell's genome and the gene copy number is induced to amplify by the use of an antibiotic inducer. The method enables for the conditional activation of the drug inducible transposase. The drug inducible gene amplification method described herein effectively functions as a molecular dial: combining drug-inducible homologous recombination and conditional gene activation to fine-tune gene amplification in mammalian systems.

Abstract: Numerous examples are disclosed of verification circuitry and associated methods in an artificial neural network. In one example, a system comprises a vector-by-matrix multiplication array comprising a plurality of non-volatile memory cells arranged in rows and columns, the non-volatile memory cells respectively capable of storing one of N possible levels corresponding to one of N possible currents, and a plurality of output blocks to receive current from respective columns of the vector-by-matrix multiplication array and generate voltages during a verify operation of the vector-by-matrix multiplication and generate digital outputs during a read operation of the vector-by-matrix multiplication.

Abstract: Techniques are provided for using context tags in named-entity recognition (NER) models. In one particular aspect, a method is provided that includes receiving an utterance, generating embeddings for words of the utterance, generating a regular expression and gazetteer feature vector for the utterance, generating a context tag distribution feature vector for the utterance, concatenating or interpolating the embeddings with the regular expression and gazetteer feature vector and the context tag distribution feature vector to generate a set of feature vectors, generating an encoded form of the utterance based on the set of feature vectors, generating log-probabilities based on the encoded form of the utterance, and identifying one or more constraints for the utterance.

Abstract: A computer-implemented method of training a student machine learning system comprises receiving data indicating execution of an expert, determining one or more actions performed by the expert during the execution and a corresponding state-action Jacobian, and training the student machine learning system using a linear-feedback-stabilized policy. The linear-feedback-stabilized policy may be based on the state-action Jacobian. Also a neural network system for representing a space of probabilistic motor primitives, implemented by one or more computers. The neural network system comprises an encoder configured to generate latent variables based on a plurality of inputs, each input comprising a plurality of frames, and a decoder configured to generate an action based on one or more of the latent variables and a state.

Abstract: A computer-implemented method of training a student machine learning system comprises receiving data indicating execution of an expert, determining one or more actions performed by the expert during the execution and a corresponding state-action Jacobian, and training the student machine learning system using a linear-feedback-stabilized policy. The linear-feedback-stabilized policy may be based on the state-action Jacobian. Also a neural network system for representing a space of probabilistic motor primitives, implemented by one or more computers. The neural network system comprises an encoder configured to generate latent variables based on a plurality of inputs, each input comprising a plurality of frames, and a decoder configured to generate an action based on one or more of the latent variables and a state.

Abstract: A computer-implemented method of training a student machine learning system comprises receiving data indicating execution of an expert, determining one or more actions performed by the expert during the execution and a corresponding state-action Jacobian, and training the student machine learning system using a linear-feedback-stabilized policy. The linear-feedback-stabilized policy may be based on the state-action Jacobian. Also a neural network system for representing a space of probabilistic motor primitives, implemented by one or more computers. The neural network system comprises an encoder configured to generate latent variables based on a plurality of inputs, each input comprising a plurality of frames, and a decoder configured to generate an action based on one or more of the latent variables and a state.

Abstract: A container having the ability to preserve contents is disclosed. The container can have a seal with a viewer, which can bend light, which will enable a user to better view the contents of the container while it is sealed. The container can also have a receptacle that can be filled with different items for better storage of the contents. The container having a viewer can also have a receptacle that allows the user to still see through the viewer to the contents.

Abstract: A computer-implemented method of training a student machine learning system comprises receiving data indicating execution of an expert, determining one or more actions performed by the expert during the execution and a corresponding state-action Jacobian, and training the student machine learning system using a linear-feedback-stabilized policy. The linear-feedback-stabilized policy may be based on the state-action Jacobian. Also a neural network system for representing a space of probabilistic motor primitives, implemented by one or more computers. The neural network system comprises an encoder configured to generate latent variables based on a plurality of inputs, each input comprising a plurality of frames, and a decoder configured to generate an action based on one or more of the latent variables and a state.

Abstract: The present invention relates to a coating composition producible from at least one yttrium-containing precursor, a solvent A, and a solvent B, which is different from the solvent A, the ratio of the vapor pressure of the solvent A at 20° C. to the vapor pressure of solvent B at 20° C. being p A p B ? 10 , to methods for producing it, and to its use.

Abstract: The invention relates to radiation curable silicone-epoxy resins, coating compositions containing said resins and to the use of these coating compositions for producing protection or dielectric layers in semiconductor elements.

Abstract: The present invention relates to metal oxide precursors comprising i) at least one metal atom selected from the group consisting of In, Ga, Zn and Sn, ii) at least one non-photocrosslinkable ligand and iii) at least one photocrosslinkable ligand, to liquid coating compositions comprising the precursors, and to their use.

Abstract: The invention relates to ammoniacal formulations comprising a) at least one hydroxozinc compound and b) at least one compound of an element of the 3rd primary group, to the use thereof, to a method using said formulations to produce layers comprising ZnO and to electronic components produced using same.

Abstract: The present invention relates to indium alkoxide compounds preparable by reacting an indium trihalide InX3 where X=F, Cl, Br, I with a secondary amine of the formula R?2NH where R?=alkyl, in a molar ratio of 8:1 to 20:1 in relation to the indium trihalide, in the presence of an alcohol of the generic formula ROH where R=alkyl, to a process for preparation thereof and to the use thereof for production of indium oxide-containing or (semi)conductive layers.

Abstract: A computer has a processor and nontransitory memory. The computer receives a list of search keywords to propose to a search engine. For search keywords that are too infrequently used to have historical data to estimate keyword performance, the computer computes linguistic similarity between the sparse-data keyword to other keywords that have sufficient historical keyword performance data to permit a statistically sound estimate for keyword performance. The estimates are submitted to a search engine, and updated by grouping the sparse-data keywords into groups, including at least a high-performing group and a low-performing group, and reallocating budget from the keywords of the low-performing group to keywords of the high-performing group, by reducing estimates for keywords of the low-performing group and increasing estimates of keywords of the high-performing group.

Abstract: The present invention relates to a coating composition producible from at least one yttrium-containing precursor, a solvent A, and a solvent B, which is different from the solvent A, the ratio of the vapour pressure of the solvent A at 20° C. to the vapour pressure of solvent B at 20° C. being p A p B ? 10 , to methods for producing it, and to its use.

Abstract: The present invention relates to halogenated indium oxo alkoxides of the generic formula In7O2(OH)(OR)12X4(ROH)x where R=C1-C15-alkyl, C1-C15-alkenyl, C1-C15-alkynyl, C1-C15-alkoxyalkyl, C6-C15-aryl- or C7-C15-alkoxyaryl, X?F, Cl, Br, I and x=0 to 10, to processes for preparation thereof and to use thereof.

Abstract: The present invention relates to a novel thin film transistor (TFT) comprising a substrate (100) with a gate electrode layer (101) deposited and patterned thereon and a gate insulator layer (102) deposited on the gate electrode layer and the substrate, characterized in that the transistor further comprises (i) a carrier injection layer (103) arranged above the gate insulator layer, (ii) a source/drain (S/D) electrode layer (104) deposited on the carrier injection layer, and (iii) a semiconductor layer (106), methods for the production of such novel TFTs, devices comprising such TFTs, and to the use of such TFTs.