meningitis, pneumonia, and sepsis in newborns and young infants (age < 60 days) are the main causes of childhood mortality in developing countries. even though streptococcus pneumonia is the most commonly detected microorganism in pediatric bacterial meningitis, it is rare in newborn infants. the following article reports a case of pneumococcal meningitis that was detected early in a newborn in...

October 12, 2017 is World Arthritis Day (http://www. worldarthritisday.org). First observed in 1996, World Arthritis Day serves as a focus for organizations and individuals to work toward increasing awareness of arthritis and other rheumatic conditions worldwide. In the United States, 54 million adults (1) have some form of arthritis or other rheumatic condition. By 2040, the number of adults w...

Over the past 2 decades, shrimp aquaculture in Thailand has been impacted by white spot disease (WSD) caused by white spot syndrome virus (WSSV). Described here are results of a survey of 157 intensive shrimp farms in Chanthaburi province, Thailand, to identify potential farm management and location risk factors associated with the occurrence of WSD outbreaks. Logistic regression analysis of th...

Knowledge-based Word sense Disambiguation (WSD) methods heavily depend on knowledge. Therefore enriching knowledge is one of the most important issues in WSD. This paper proposes a novel idea of combining WordNet and ConceptNet for WSD. First, we present a novel method to automatically disambiguate the concepts in ConceptNet; and then we enrich WordNet with large amounts of semantic relations f...

Word Sense Disambiguation (WSD) is a task of identifying correct sense of a given word especially when it has multiple meanings. WSD acts as a foundation to many AI applications such as Data Mining, Information Retrieval and Machine Translation. It has drawn much interest in the last decade and much improved results are being obtained. For WSD we require a knowledge-base, using which we can res...

Statistical machine translation (SMT) systems use local cues from n-gram translation and language models to select the translation of each source word. Such systems do not explicitly perform word sense disambiguation (WSD), although this would enable them to select translations depending on the hypothesized sense of each word. Previous attempts to constrain word translations based on the result...

Word-sense disambiguation (WSD) is the process of finding the correct meaning of words that have multiple meanings. The unsupervised WSD algorithm is the type of WSD algorithm that leverages an external source of knowledge to guide the disambiguation process. The unsupervised WSD algorithm type is attracting more interest in the biomedical domain because of its implementation practicality, espe...