Abstract: Train a text-to-image machine learning model by using a training dataset. The training dataset includes images and respective natural language descriptions of those images. The training causes the text-to-image machine learning model to be overfit on the training dataset. Store the trained overfit text-to-image machine learning model. Submit a given natural language description to the stored overfit text-to-image machine learning model. In response to the submitting, receive as output from the overfit text-to-image learning machine learning model an output image. The output image is a reproduction of a corresponding image from the training dataset and corresponds to the submitted natural language description.

Abstract: Polypeptides, proteins, and chimeric antigen receptors (CARs) that specifically bind to human mesothelin582-598 (IP-NGYLVLDLSMQEALS) (SEQ ID NO: 1) are disclosed. Anti-mesothelin binding moieties, nucleic acids, recombinant expression vectors, host cells, populations of cells, pharmaceutical compositions, and conjugates relating to the poly peptides, proteins, and CARS are disclosed. Methods of reducing mesothelin shed from cell membranes, methods of detecting the presence of cancer, and methods of treating or preventing cancer are also disclosed.

Abstract: Provided is a recombinant KOD polymerase, which is the following A) or B): the polymerase shown in A) is a protein having DNA polymerase activity that is obtained by modifying amino acid residues in at least one of the following 18 positions in a wild-type KOD DNA polymerase amino acid sequence: 675th, 385th, 710th, 674th, 735th, 736th, 606th, 709th, 347th, 349th, 590th, 676th, 389th, 589th, 680th, 384th, 496th and 383rd; the polymerase described by B) is a protein having DNA polymerase activity that is derived from A) by adding a tag sequence to an end of the amino acid sequence of the protein shown in A).

Abstract: Validity of a trained artificial intelligence model is verified. The verifying the validity includes generating a training dataset from the trained artificial intelligence model using reverse data generation of the trained artificial intelligence model. The training dataset generated using the reverse data generation is compared with a test dataset used to evaluate the trained artificial intelligence model. The comparing is to determine a relationship between the training dataset that was generated and the test dataset. Data from the test dataset determined to have a predefined relationship with the training dataset is removed to obtain a new test dataset. The new test dataset is used to verify the validity of the trained artificial intelligence model.

Abstract: Disclosed herein are methods for treating cancers in a subject. The method includes determining the plasma level of arginine in the subject, followed by administering to the subject an arginine deprivation therapy alone or in combination with an anti-cancer agent based on the determined plasma level of arginine. According to some embodiments of the present disclosure, the anti-cancer agent is selected from the group consisting of FOLFOX, docetaxel, cisplatin, pemetrexed, pembrolizumab, and a combination thereof.

Abstract: A diesel fuel additive includes a cetane number improver and an at least one organometallic combustion catalyst in solution and/or at least one metal-oxide combustion catalyst in suspension.

Abstract: This application provides an electrode sheet and an electrochemical device. The electrode sheet includes a current collector and a functional coating located on at least one surface of the current collector. The functional coating includes a first coating, a second coating and an active material layer that are sequentially stacked on a surface of the current collector. The first coating includes a conductive agent, a binder and a first functional filler, and the second coating includes a conductive agent, a binder and a second functional filler. A mass ratio of the binder in the first coating to the first coating is a1, a mass ratio of the binder in the second coating to the second coating is a2, and a mass ratio of the binder in the active material layer to the active material layer is a3, and a1>a2>a3.

Abstract: A distributor includes: an outer housing; a direct current charging interface, an electronic control terminal interface, and a battery terminal interface disposed in the outer housing. A first contactor and a second contactor are connected between the electronic control terminal interface and the battery terminal interface. A third contactor and a pre-charge resistor form a pre-charge branch. A fourth contactor is connected between the direct current charging interface and the battery terminal interface; a fifth contactor is connected between a negative terminal of the direct current charging interface and a negative terminal of the battery terminal interface; and the five contactors and a pre-charge resistor are disposed in the outer housing.

Abstract: A solvent-free resin composition and uses thereof are provided. The resin composition includes: (A) a maleic acid-modified liquid hydrocarbon resin; (B) a first filler having a D50 particle size of 1 ?m to 4 ?m; and (C) a second filler having a D50 particle size of 5 ?m to 10 ?m. The solvent-free resin composition can be used to fill the holes of printed circuit boards.

Abstract: A resin composition and uses thereof are provided. The resin composition includes: (A) an epoxy resin; (B) a bismaleimide resin; and (C) a first flame retardant having a structure of formula (I): Wherein Ar is a C3 to C18 heteroaryl or a C6 to C18 aryl; R1 is H or a C1 to C18 alkyl; and R2 and R3 are independently H, a C1 to C18 alkyl, a C3 to C18 heteroaryl, or a C6 to C18 aryl.

Abstract: The present invention provides therapeutic and diagnostic methods and compositions for cancer (e.g., bladder cancer (e.g., UC) or kidney cancer (e.g., RCC)). The invention provides methods of identifying an individual having a cancer who is likely to respond to treatment with an anti-cancer therapy comprising a PD-L1 axis binding antagonist, methods for selecting a therapy for an individual having a cancer, methods of identifying an individual having a cancer who is less likely to respond to treatment with an anti-cancer therapy comprising a PD-L1 axis binding antagonist monotherapy, methods of monitoring the response of an individual having a cancer to treatment with an anti-cancer therapy comprising a PD-L1 axis binding antagonist, and methods of treating an individual having cancer, based on expression levels of a biomarker of the invention (e.g., one or more genes set forth in any one of Tables 1-7, e.g., IL8).

Abstract: A method for making a bi-metallic electrocatalyst produces a non-platinum group metal (non-PGM), bimetallic oxide crystalline catalyst showing low overpotential in both oxygen evolution reactions (OER) and oxygen reduction reactions (ORR) in a metal-air battery and/or fuel cell applications. The bimetallic oxide is formed to be in electrical communication with a catalyst support particle, and with the catalyst support particle, in turn, in electrical communication with an air-permeable electrode. A metal-air storage cell, optionally configured as part of a battery, includes a bi-metallic electrocatalyst. An electrical management system includes a metal-air storage cell.

Abstract: Disclosed herein are methods and kits for identifying responsiveness or non-responsiveness of a cancer subject to arginine deprivation therapy. The method includes determining the presence of a G/G genotype of rs13338697 of the target nucleic acid in a biological sample derived from the subject by use of a polymerase chain reaction (PCR)-based method, in which the presence of the G/G genotype of rs13338697 of the target nucleic acid is an indication that the subject is responsive to the arginine deprivation therapy.