Abstract: Described herein are compounds of Formula I, wherein the variables are defined herein, their use as HSD17B13 inhibitors and/or degraders, pharmaceutical compositions containing such compounds and their use to treat, for example, NAFLD and NASH.

Abstract: A method, computer system, and computer program product are provided for peer risk benchmarking. Customer data for a first network is obtained, wherein the customer data comprises a role of one or more network devices in the first network and a plurality of risk reports corresponding to the one or more network devices, and wherein each risk report is associated with a particular dimension of a plurality of dimensions of risk for the one or more network devices. A network profile image is generated by processing the plurality of risk reports. A generative adversarial network generates a synthetic network profile image from the network profile image, wherein the synthetic network profile image does not include the customer data. A second network is evaluated using the synthetic network profile image to identify differences between the first network and the second network.

Abstract: Disclosed are a sample analysis apparatus and method which include: obtaining a first light signal by irradiating a first test sample from blood and a first-channel reagent to differentiate neutrophils, eosinophils, lymphocytes, and monocytes; obtaining a second light signal from a second test sample from the blood and a second-channel reagent; counting the nucleated red blood cells and lymphocytes based on the second light signal; determining accuracy of the lymphocyte result from the first test sample; and if inaccurate, correcting the lymphocyte result based on the lymphocyte result of the second test sample.

Abstract: Disclosed are a sample analysis apparatus and a sample analysis method. The method includes: obtaining a leukocyte measurement mode for a test sample, the method having a plurality of leukocyte measurement modes, each of which includes at least a reaction time, and different leukocyte measurement modes having different reaction times; determining a reaction time for the current sample to be tested; controlling the sample to be tested to react with the reagent, to prepare a test sample for detecting leukocytes; and controlling to detect the test sample for detecting leukocytes, to obtain detection data of leukocyte classification.

Abstract: A method, computer system, and computer program product are provided for peer risk benchmarking. Customer data for a first network is obtained, wherein the customer data comprises a role of one or more network devices in the first network and a plurality of risk reports corresponding to the one or more network devices, and wherein each risk report is associated with a particular dimension of a plurality of dimensions of risk for the one or more network devices. A network profile image is generated by processing the plurality of risk reports. A generative adversarial network generates a synthetic network profile image from the network profile image, wherein the synthetic network profile image does not include the customer data. A second network is evaluated using the synthetic network profile image to identify differences between the first network and the second network.

Abstract: A method, computer system, and computer program product are provided for peer risk benchmarking. Customer data for a first network is obtained, wherein the customer data comprises a role of one or more network devices in the first network and a plurality of risk reports corresponding to the one or more network devices, and wherein each risk report is associated with a particular dimension of a plurality of dimensions of risk for the one or more network devices. A network profile image is generated by processing the plurality of risk reports. A generative adversarial network generates a synthetic network profile image from the network profile image, wherein the synthetic network profile image does not include the customer data. A second network is evaluated using the synthetic network profile image to identify differences between the first network and the second network.

Abstract: A method, computer system, and computer program product are provided for mitigating network risk. A plurality of risk reports corresponding to a plurality of network devices in a network are processed to determine a multidimensional risk score for the network. The plurality of risk reports are analyzed using a semantic analysis model to identify one or more factors that contribute to the multidimensional risk score. One or more actions are determined using a trained learning model to mitigate one or more dimensions of the multidimensional risk score. The outcomes of applying the one or more actions are presented to a user to indicate an effect of each of the one or more actions on the multidimensional risk score for the network.

Abstract: A method, computer system, and computer program product are provided for peer risk benchmarking. Customer data for a first network is obtained, wherein the customer data comprises a role of one or more network devices in the first network and a plurality of risk reports corresponding to the one or more network devices, and wherein each risk report is associated with a particular dimension of a plurality of dimensions of risk for the one or more network devices. A network profile image is generated by processing the plurality of risk reports. A generative adversarial network generates a synthetic network profile image from the network profile image, wherein the synthetic network profile image does not include the customer data. A second network is evaluated using the synthetic network profile image to identify differences between the first network and the second network.

Abstract: A method, computer system, and computer program product are provided for peer risk benchmarking. Customer data for a first network is obtained, wherein the customer data comprises a role of one or more network devices in the first network and a plurality of risk reports corresponding to the one or more network devices, and wherein each risk report is associated with a particular dimension of a plurality of dimensions of risk for the one or more network devices. A network profile image is generated by processing the plurality of risk reports. A generative adversarial network generates a synthetic network profile image from the network profile image, wherein the synthetic network profile image does not include the customer data. A second network is evaluated using the synthetic network profile image to identify differences between the first network and the second network.

Abstract: A method, computer system, and computer program product are provided for peer risk benchmarking. Customer data for a first network is obtained, wherein the customer data comprises a role of one or more network devices in the first network and a plurality of risk reports corresponding to the one or more network devices, and wherein each risk report is associated with a particular dimension of a plurality of dimensions of risk for the one or more network devices. A network profile image is generated by processing the plurality of risk reports. A generative adversarial network generates a synthetic network profile image from the network profile image, wherein the synthetic network profile image does not include the customer data. A second network is evaluated using the synthetic network profile image to identify differences between the first network and the second network.

Abstract: A method, computer system, and computer program product are provided for network risk analysis. A plurality of risk reports relating to a network device in a network are obtained, wherein each risk report is associated with a particular dimension of a plurality of dimensions of risk for the network device in the network. A count of the plurality of risk reports is determined for each dimension of the plurality of dimensions of risk. A regression model is applied to determine a risk value for the network device in the network based on the count of the plurality of risk reports for each dimension and based a role of the network device in the network.

Abstract: A device for removing and preventing paraffin by using electric heating generated from skin effect-based natural gas electricity and an application thereof are disclosed, and the device comprises a natural gas collection portion, a natural gas electricity generation portion and a device for removing and preventing paraffin by using electric heating powered by the natural gas electricity generation portion; the natural gas collection portion is used to collect and separate natural gases discharged from a wellbore; the natural gas electricity generation portion generates electricity with natural gases. The power source required by the electric heating of the steel armored cable of the present invention comes from the natural gas electricity generation portion, and the air source required by the natural gas electricity generation portion can be obtained directly from the associated gases extracted from an oil well.

Abstract: Modulators of Wnt activity, e.g., Wnt inhibitors, that act on TIKI proteins and inhibit TIKI-mediated cleavage of Wnt proteins, as well as methods of identifying such modulators and methods of use thereof.

Abstract: Modulators of Wnt activity, e.g., Wnt inhibitors, that act on TIKI proteins and inhibit TIKI-mediated cleavage of Wnt proteins, as well as methods of identifying such modulators and methods of use thereof.

Abstract: The present invention relates to a continuous process for the preparation of an aminonitrile comprising the stages of: a) formation of the aminonitrile by reaction between an alkenyl nitrile, mixed with aminonitrile, and a monoamine introduced in molar excess with respect to the alkenyl nitrile; b) separation of the unreacted monoamine and the aminonitrile; c) reaction between the monoamine separated during stage b) and all or part of the alkenyl nitrile in order to form a mixture of aminonitrile and of unreacted alkenyl nitrile, with the alkenyl nitrile being introduced in molar excess with respect to the said monoamine; d) transfer of the mixture of aminonitrile and alkenyl nitrile resulting from stage c) to the reaction of stage a), and e) in the case where only a portion of the alkenyl nitrile is introduced during stage c), introduction of the remaining molar amount of alkenyl nitrile into the mixture of stage d).

Abstract: Modulators of Wnt activity, e.g., Wnt inhibitors, that act on TIKI proteins and inhibit TIKI-mediated cleavage of Wnt proteins, as well as methods of identifying such modulators and methods of use thereof.

Abstract: The present disclosure discloses a device and a method for measuring gas chemical solvent absorption and desorption reaction heat. The device comprises an outer casing; an metal guard inner shell; a reactor; a pressure sensor; a thermal insulation material between the outer casing and the metal guard inner shell; guard electric heaters provided respectively in an upper portion and a lower portion of an outer periphery of the metal guard inner shell; a glass fiber thermal insulation layer between the inner metal guard shell and the reactor; temperature thermocouples provided in the glass fiber thermal insulation layer; a glass fiber board provided in a lower portion of an outer periphery of the reactor; main electric heaters between the glass fiber board and the reactor; a liquid inlet pipe and a gas discharge pipe; a temperature thermistor, a liquid discharge pipe; a data acquisition board; a computer; and a power supply.

Abstract: The present invention relates to a continuous process for the preparation of an aminonitrile comprising the stages of: a) formation of the aminonitrile by reaction between an alkenyl nitrile, mixed with aminonitrile, and a monoamine introduced in molar excess with respect to the alkenyl nitrile; b) separation of the unreacted monoamine and the aminonitrile; c) reaction between the monoamine separated during stage b) and all or part of the alkenyl nitrile in order to form a mixture of aminonitrile and of unreacted alkenyl nitrile, with the alkenyl nitrile being introduced in molar excess with respect to the said monoamine; d) transfer of the mixture of aminonitrile and alkenyl nitrile resulting from stage c) to the reaction of stage a), and e) in the case where only a portion of the alkenyl nitrile is introduced during stage c), introduction of the remaining molar amount of alkenyl nitrile into the mixture of stage d).

Abstract: This invention relates to Tiki1 and Tiki2 proteins and nucleic acids, cells expressing the same, and methods for identifying compounds that modulate Tiki1/2 activity for use in the treatment of osteoporosis or cellular proliferative disorders.