Abstract: A p-aminobenzoic acid-producing microorganism is provided. The p-aminobenzoic acid-producing microorganism is obtained by a method for preparing a p-aminobenzoic acid-producing microorganism. The method for preparing a p-aminobenzoic acid-producing microorganism includes (a) performing an acclimation process on a source microorganism with at least one sulfonamide antibiotic to obtain at least one acclimatized microorganism and (b) screening out at least one p-aminobenzoic acid-producing microorganism from the at least one acclimatized microorganism, wherein the at least one p-aminobenzoic acid-producing microorganism has a higher p-aminobenzoic acid titer than the source microorganism.

Abstract: Translating applications to a target language includes extracting program integrated information (PII) to be translated and creating translation context datasets based on interpretation of accessibility information associated with particular strings of PII. Translation pairs include PII and corresponding context datasets for context-based translation of application components. A two-stage index contains PII strings for first stage lookup and context datasets for distinguishing duplicate PII strings as a second stage lookup. Real-time translation is facilitated by the two-stage index, which is established by translation pairs and resulting translations.

Abstract: A method for identifying hard-coded strings in source code is disclosed. In one embodiment, such a method parses source code and associated localization resource files to identify hard-coded strings and their associated context. The method provides a confidence score for each hard-coded string that indicates whether the hard-coded string is translatable or non-translatable. Based on the confidence score for each hard-coded string, the method transforms each hard-coded string into a single equivalence word. The method then prepares training data by tagging the hard-coded strings in the source code and associated localization resource files as one of translatable and non-translatable. The method then trains a parts-of-speech (POS) tagging model using the training data. At runtime, the method fetches potential hard-coded strings and tags each hard-coded string as one of translatable and non-translatable using the POS tagging model. A corresponding system and computer program product are also disclosed.

Abstract: The present invention provides a preparation method for a fluorine-free water repellent, comprising (A) a homogenization step in which the raw materials are mixed in single step to obtain a mixture; and (B) a polymerization step to react said mixture into said water repellent. The operation of the present method is simple, and the water repellent produced has the advantage of high stability and high washing durability.

Abstract: The present invention provides a preparation method for a fluorine-free water repellent, comprising (A) a homogenization step in which the raw materials are mixed in single step to obtain a mixture; and (B) a polymerization step to react said mixture into said water repellent. The operation of the present method is simple, and the water repellent produced has the advantage of high stability and high washing durability.

Abstract: This invention discloses a solvent-based fluorinated water and oil repellent and process for producing the same. Said fluorinated water and oil repellent comprises 20˜50% (w/w) blocked polyfluorourethane compound and 50˜80% (w/w) solvent; its reaction agents include fluoroalcohol compound, diisocyanate or polymeric isocyanate compound, cross-linking agent, blocking agent, and solvent. The process for synthesizing the blocked polyfluorourethane is by bulk polymerization.