Narrow Results

Due to the lack of a rigorous methodology and explicit criteria to distinguish between classifiers (C) and measure words (M), previous inventories of Mandarin C's, or geti liangci 個體量詞, vary greatly. Based on the insight that an M in a Chinese [Num C/M N] phrase is semantically substantive, while a C is semantically redundant and thus does not block numeral quantification or adjectival modification to the noun, this paper further proposes that while C/M both function as a multiplicand mathematically, with Num as the multiplier, C's value is necessarily 1 and M is not, thus ~1. Cognitively, however, the semantically redundant C serves to profile an inherent semantic feature of N and thus selects a narrow class of N's. With these explicit distinctions between C and M, we then re-examine the inventory of C's put forth in 國語日報量詞典 Mandarin Daily News Dictionary of Measure Words and offer a much more reliable list of C's in Taiwan Mandarin.

This chapter discusses the major tectonic movements all over the world, including between the Mesoproterozoic and the Cenozoic eras, between the Silurian and Devonian (the first act of the Hercynian Movement including the Tianshan Movement), between the Middle and the Late Triassic, between the Jurassic and the Cretaceous, and between the Paleogene and the Neogene. In the end, the chapter touches on the evolutionary profile of representative ultra-long geological structures all over the world.

Researchers have argued that current Web modelling languages have various limitations including disconnection between business models and technical architectures and also disconnection between functional architecture and information architecture. Addressing the problem; Web Information Exchange Diagrams are developed in two flavours, WIED and WIED-UML. WIED-UML is developed to primarily address the problem of disconnection between functional architecture and information architecture. However, we argue that it, doesn’t really address the issue, because WIED-UML is developed on a set of different UML-Unified Modelling Language notations which don’t have semantic conformity with current UML metamodel. Creating transformation rules between models not conforming to common metamodel vocabulary, would not lead to an elegant solution. Hence in this paper, we propose a solution, using UML 2.0 Profile for WIED. We demonstrate it by an example and argue that it is a potential improvement of generic WIED model besides eliminating the requirement for non-standard WIED-UML.

The objective of this study is to describe the profile of multidrug-resistant (MDR) Gram-negative bacteria in a tertiary teaching hospital at North-Eastern State, Malaysia over a 3-year period (2007-2009). The organisms were identified by conventional method or/and API E or/and API NE. The antimicrobial sensitivity was determined by modified Kirby Bauer method and the sensitivity breakpoints were interpreted according to the Clinical Laboratory Standard Institute. A total of 6978 Gram negative were isolated during that period. 840 (12%) were resistant to 3rd and 4th generation cephalosporin, ciprofloxacin and piperacillin tazobactam. They were Acinetobacter spp. (69%), Klebsiella pneumoniae (14 %) and Pseudomonas aeruginosa (6%). Other organisms found to be resistant were Enterobacter spp (2%), Escherichia coli (2%), Klebsiella spp (3%) and Stenotrophomonas maltophilia (1%). Most of the MDR Gram-negative bacteria were from tracheal aspirates (35%), wound specimens (21%), blood (16%) and urine (13%). They were mostly from intensive care unit (38%) and hospitalized patient (59%). The percentage of organisms sensitive to other antibiotics were to amikacin (42%), gentamicin (14.8%), netilmicin (49.5%), cefoperazone/sulbactam (74.8%), imipenem (25.7%) and meropenem (24.6%) In conclusion, MDR Gram-negative bacteria were high in hospitalized patients, especially from surgical based department. They were mostly isolated from tracheal aspirates and wounds. Cefoperazone/sulbactam and amikacin exhibit the highest percentage of susceptibility.