Abstract: Methods and systems are presented for providing a computer platform that manages the impacts of government regulations on existing software processes of an online service provider. A regulation document is obtained from a government agency. The regulation document is processed, and legal obligations relevant to an online service provider are extracted from the regulation document. An ensemble machine learning model is used to recommend, for each of the legal obligations, software controls that can be implemented within one or more software processes of the online service provider to mitigate a risk of the legal obligations. The ensemble machine learning model may include an attribute-based model and a text-based model. An explainable visual interface is provided to present the recommended software controls and context that indicates to a user how the software controls are determined for the legal obligations.

Abstract: Disclosed is an efficient nitrogen and phosphorus removal process system for mariculture tail water treatment. The process system comprises a physical filtering device, an efficient biological treatment unit, a flocculation sedimentation tank, a sand filtering tank, a clean water tank and a sludge tank, wherein the physical filtering device, the efficient biological treatment unit, the flocculation sedimentation tank, the sand filtering tank and the clean water tank are sequentially connected; the physical filtering device, the efficient biological treatment unit, the flocculation sedimentation tank and the sand filtering tank are all connected with the sludge tank through pipelines, and the physical filtering device and the sand filtering tank are both connected with the clean water tank through pipelines.

Abstract: Methods and systems are presented for providing a computer platform that manages the impacts of government regulations on existing software processes of an online service provider. A regulation document is obtained from a government agency. The regulation document is processed, and legal obligations relevant to an online service provider are extracted from the regulation document. An ensemble machine learning model is used to recommend, for each of the legal obligations, software controls that can be implemented within one or more software processes of the online service provider to mitigate a risk of the legal obligations. The ensemble machine learning model may include an attribute-based model and a text-based model. An explainable visual interface is provided to present the recommended software controls and context that indicates to a user how the software controls are determined for the legal obligations.

Abstract: Methods and systems are presented for providing a computer platform that manages the impacts of government regulations on existing software processes of an online service provider. A regulation document is obtained from a government agency. The regulation document is processed, and legal obligations relevant to an online service provider are extracted from the regulation document. An ensemble machine learning model is used to recommend, for each of the legal obligations, software controls that can be implemented within one or more software processes of the online service provider to mitigate a risk of the legal obligations. The ensemble machine learning model may include an attribute-based model and a text-based model. An explainable visual interface is provided to present the recommended software controls and context that indicates to a user how the software controls are determined for the legal obligations.

Abstract: Methods and systems are presented for providing a computer platform that manages the impacts of government regulations on existing software processes of an online service provider. A regulation document is obtained from a government agency. The regulation document is processed, and legal obligations relevant to an online service provider are extracted from the regulation document. An ensemble machine learning model is used to recommend, for each of the legal obligations, software controls that can be implemented within one or more software processes of the online service provider to mitigate a risk of the legal obligations. The ensemble machine learning model may include an attribute-based model and a text-based model. An explainable visual interface is provided to present the recommended software controls and context that indicates to a user how the software controls are determined for the legal obligations.

Abstract: Methods and systems are presented for providing a computer platform that manages the impacts of government regulations on existing software processes of an online service provider. A regulation document is obtained from a government agency. The regulation document is processed, and legal obligations relevant to an online service provider are extracted from the regulation document. An ensemble machine learning model is used to recommend, for each of the legal obligations, software controls that can be implemented within one or more software processes of the online service provider to mitigate a risk of the legal obligations. The ensemble machine learning model may include an attribute-based model and a text-based model. An explainable visual interface is provided to present the recommended software controls and context that indicates to a user how the software controls are determined for the legal obligations.

Abstract: The disclosure discloses isolated polynucleotides and polypeptides, and recombinant DNA constructs useful for conferring improved tolerance in plants to insect pests; compositions (such as plants or seeds) comprising these recombinant DNA constructs; and methods utilizing these recombinant DNA constructs. The recombinant DNA constructs comprise a polynucleotide operably linked to a promoter that is functional in a plant, wherein said polynucleotides encode insect tolerance polypeptides.

Abstract: Isolated polynucleotides and polypeptides, and recombinant DNA constructs useful for conferring improved nitrogen use efficiency and/or drought tolerance and/or cold tolerance; compositions (such as plants or seeds) comprising these recombinant DNA constructs; and methods utilizing these recombinant DNA constructs are disclosed. The recombinant DNA constructs comprise a polynucleotide operably linked to a promoter that is functional in a plant, wherein said polynucleotides encode low nitrogen tolerance polypeptides.

Abstract: The disclosure discloses isolated polynucleotides and polypeptides, and recombinant DNA constructs useful for conferring improved tolerance in plants to insect pests; compositions (such as plants or seeds) comprising these recombinant DNA constructs; and methods utilizing these recombinant DNA constructs. The recombinant DNA constructs comprise a polynucleotide operably linked to a promoter that is functional in a plant, wherein said polynucleotides encode insect tolerance polypeptides.

Abstract: The disclosure discloses isolated polynucleotides and polypeptides, and recombinant DNA constructs useful for conferring improved tolerance in plants to insect pests; compositions (such as plants or seeds) comprising these recombinant DNA constructs; and methods utilizing these recombinant DNA constructs. The recombinant DNA constructs comprise a polynucleotide operably linked to a promoter that is functional in a plant, wherein said polynucleotides encode insect tolerance polypeptides.

Abstract: Isolated polynucleotides and polypeptides, and recombinant DNA constructs useful for conferring improved nitrogen use efficiency and/or drought tolerance and/or cold tolerance; compositions (such as plants or seeds) comprising these recombinant DNA constructs; and methods utilizing these recombinant DNA constructs are disclosed. The recombinant DNA constructs comprise a polynucleotide operably linked to a promoter that is functional in a plant, wherein said polynucleotides encode low nitrogen tolerance polypeptides.