Abstract: Disclosed is a method of preparing glufosinate, and specifically a method of preparing glufosinate represented by formula (1) or its salt or enantiomer, or a mixture of its enantiomers in any ratio, comprising a step of hydrolyzing a compound of formula (III) to generate a compound of formula (1). Due to a distinctive reaction mechanism adopted in the method of the present disclosure, a halogenated hydrocarbon by-product in the Michaelis-Arbuzov reaction can be avoided and thus the destructive impact of the halogenated hydrocarbon by-product on ozone in the aerosphere can be prevented. Accordingly, the equipment and engineering investments required for the separation, purification, and collection of the foregoing by-product are eliminated, and the potential environmental and safety hazards brought by the foregoing by-product are also avoided.

Abstract: In embodiments of the present disclosure, there is provided an approach for fact checking based on semantic graphs. According to embodiments of the present disclosure, after obtaining a text to be fact checked, a plurality of evidence sentences related to the text are retrieved from an evidence database. Then, semantic graphs of the text and the evidence sentences are constructed based on the semantic analysis, and a veracity of a statement in the text can be determined based on the semantic graphs. Embodiments of the present disclosure propose a graph-based reasoning approach for fact checking, and use the constructed semantic graphs to facilitate verification of the truthfulness of the text, thereby improving the accuracy for fact checking.

Abstract: Provided are anti-AREG antibodies or immunoreactive fragments thereof for the treatment, diagnosis or prophylaxis of fibrotic diseases, including but not limited to renal fibrosis, hepatic fibrosis, pulmonary fibrosis, in particular, IPF. Polynucleotides or nucleic acid molecules encoding the antibodies, expression vectors, host cells and methods for making the antibodies are also provided. The anti-AREG antibodies specifically bind to AREG and block the function of AREG, through binding residues that locate in the EGF like domain.

Abstract: The present invention relates to a method for constructing an animal model of pulmonary fibrosis, in particular, idiopathic pulmonary fibrosis (IPF), the constructed animal model using the said method, and a method for screening the candidate drugs for treating pulmonary fibrosis, in particular, idiopathic pulmonary fibrosis (IPF).

Abstract: Provided is a drug target for idiopathic pulmonary fibrosis, and the use thereof. The drug target is AREG signaling in AT2 cells of the lung. The drug target can be used to screen drugs for treating and/or preventing pulmonary fibrosis, in particular, idiopathic pulmonary fibrosis (IPF) of animals and human beings.

Abstract: The invention relates to prosthesis for treating pulmonary fibrosis, in particular, idiopathic pulmonary fibrosis (IPF), and a method for treating pulmonary fibrosis, in particular, idiopathic pulmonary fibrosis (IPF).

Abstract: A method for cleaning data stored in a database, the method comprising providing a set of fixing rules. Each fixing rule incorporates a set of attribute values that capture an error in a plurality of semantically related attribute values, and a deterministic correction which is operable to replace one of the set of attribute values with a correct attribute value to correct the error. The method further comprises comparing at least two of the fixing rules with one another to check that the error correction carried out by one fixing rule is consistent with the error correction carried out by another fixing rule.

Abstract: The optimized inequality join method is a method for joining relational tables on input inequality conditions. The optimized inequality join method is a relatively fast inequality join method using permutation arrays to store positional information for sorted attributed values. Additionally, space efficient bit arrays are used to enable optimization, such as Bloom filter indices, thus providing faster computation of the join results. The method may be used, for example, for joining various inequalities associated with a variety of measured environmental conditions for raising an alarm when certain conditions are met.

Abstract: The optimized inequality join method is a method for joining relational tables on input inequality conditions. The optimized inequality join method is a relatively fast inequality join method using permutation arrays to store positional information for sorted attributed values. Additionally, space efficient bit arrays are used to enable optimization, such as Bloom filter indices, thus providing faster computation of the join results. The method may be used, for example, for joining various inequalities associated with a variety of measured environmental conditions for raising an alarm when certain conditions are met.

Abstract: A method for cleaning data stored in a database which utilises a data fixing rule. The data fixing rule comprises a set of attribute values that capture an error in a plurality of semantically related attribute values. The data fixing rule also comprises a deterministic correction which is operable to replace one of the set of attribute values with a correct attribute value to correct the error. The method comprises applying the data fixing rule to the database to detect if the set of attribute values that captures the error is stored in the database and, if the set of attribute values is detected, the method applies the deterministic correction to correct the error in the attribute values.

Abstract: A method for cleaning data stored in a database, the method comprising providing a set of fixing rules. Each fixing rule incorporates a set of attribute values that capture an error in a plurality of semantically related attribute values, and a deterministic correction which is operable to replace one of the set of attribute values with a correct attribute value to correct the error. The method further comprises comparing at least two of the fixing rules with one another to check that the error correction carried out by one fixing rule is consistent with the error correction carried out by another fixing rule.

Abstract: An apparatus, system, and method are disclosed for modeling and optimizing an enterprise application system. The apparatus, in one embodiment, is configured to determine the system processing capacity and workload characteristics. The apparatus is further configured to determine optimization parameters, including the system processor utilization, minimum job acquiring rates for data entry points of the system, and software component multi-parallelism recommendations. A method is disclosed, in one embodiment, to report the optimization parameters and to implement the optimization parameters within the system during run-time.

Abstract: A method, apparatus and article of manufacture, implementing the method, of sizing hardware for software. An event arrival rate is determined. At least one processor system that has a benchmarked event processing rate greater than or equal to the event arrival rate is selected.