Sublingual sufentanil for postoperative pain relief: first clinical experiences

Contains fulltext : 191947.pdf (publisher's version ) (Open Access

The Effect of Social Mixing Controls on the Spread of Smallpox - A Two-Level Model

Health Care Management Science, V. 8, No. 4, pp 277-289.Responding to a possible bioterror attack of Smallpox has become a major concern to governments, local public officials and health authorites. This concern has been reflected in numerous studies that model and evaluate possible response strategies. Many of these studies consider only vaccination policies and assume homogeneous mixing, where all instances of contacts in the population are equally like;y. Such a mixing pattern is rather unlikely to represent population interaction in a modern urban setting, which typically is separated into households on the one hand, and into daily meeting sites such as schools and offices on the other hand. In this paper we develop a two-level social interaction model where an individual moves back and forth between home and a daily meeting site, possibly passing through a general meeting site such as mass transit systems or other crowded areas. Based on the model, we evaluate the effect of social mixing controls, situational awareness of the public health system and mass vaccination on the spread of smallpox. It is shown that mixing controls and alertness of the response system may have a significant impact on the spread of the epidemic. Some policy recommendations are discussed

The Potential of Learned Index Structures for Index Compression

Inverted indexes are vital in providing fast key-word-based search. For every term in the document collection, a list of identifiers of documents in which the term appears is stored, along with auxiliary information such as term frequency, and position offsets. While very effective, inverted indexes have large memory requirements for web-sized collections. Recently, the concept of learned index structures was introduced, where machine learned models replace common index structures such as B-tree-indexes, hash-indexes, and bloom-filters. These learned index structures require less memory, and can be computationally much faster than their traditional counterparts. In this paper, we consider whether such models may be applied to conjunctive Boolean querying. First, we investigate how a learned model can replace document postings of an inverted index, and then evaluate the compromises such an approach might have. Second, we evaluate the potential gains that can be achieved in terms of memory requirements. Our work shows that learned models have great potential in inverted indexing, and this direction seems to be a promising area for future research