Background: Surgical mortality data are collected routinely in high-income countries, yet virtually no low-or middle-income countries have outcome surveillance in place. The aim was prospectively to collect worldwide mortality data following emergency abdominal surgery, comparing findings across countries with a low, middle or high Human Development Index (HDI).Methods: This was a prospective, multicentre, cohort study. Self-selected hospitals performing emergency surgery submitted prespecified data for consecutive patients from at least one 2-week interval during July to December 2014. Postoperative mortality was analysed by hierarchical multivariable logistic regression.

Figure A1 depicts an overview of the coevolution process controlled by the proposed HCGA algorithm. The Level II (high-level) population consists of individuals representing the feasible values of the application parameters. The Level I (low-level) populations represent two sets of system parameters (i.e., two species). One of the low-level populations represents the system parameters that drive the sentiment analysis process, whereas the second low-level population represents the system parameters that control the business relation mining process. The HCGA algorithm controls the evolutionary processes among all of the populations. At the end of the coevolution process, a set of near-optimal application parameter values and low-level NLP features (e.g., the use of specific sentiment lexicons) with respect to a particular M&A situation are obtained to refine the M&A target scoring function (i.e., the decision support mechanism).

No abstract

No abstract

This work proposes a novel approach to translate Chinese to Taiwanese sign language and to synthesize sign videos. An aligned bilingual corpus of Chinese and Taiwanese Sign Language (TSL) with linguistic and signing information is also presented for sign language translation. A two-pass alignment in syntax level and phrase level is developed to obtain the optimal alignment between Chinese sentences and Taiwanese sign sequences. For sign video synthesis, a scoring function is presented to develop motion transition-balanced sign videos with rich combinations of intersign transitions. Finally, the maximum a posteriori (MAP) algorithm is employed for sign video synthesis based on joint optimization of two-pass word alignment and intersign epenthesis generation. Several experiments are conducted in an educational environment to evaluate the performance on the comprehension of sign expression. The proposed approach outperforms the IBM Model 2 in sign language translation. Moreover, deaf students perceived sign videos generated by the proposed method to be satisfactory.