Establishing social statistical databases for evidenced-based social policy formulation in the Caribbean

Includes bibliography

The use of databases of social and gender statistics in the development of policies and programmes

The unavailability of data to inform policy planning and formulation has been repeatedly cited as the main challenge to economic and social progress in the Caribbean. Furthermore, even in instances when data is produced, broader gaps exist between its production and eventual use for evidence-based policy formulation. Owing to those challenges, this report explores the use of databases of social and gender statistics in the development of policies and programmes in the Caribbean subregion. The report offers a general appraisal of databases against two main considerations: (i) maximizing the use of existing databases in relevant policies and programmes; and (ii) bridging the gaps in data availability of relevant statistical databases and their analyses. The assessment entailed an inventory of social and gender databases maintained by data producers in the region and analysis of the extent to which the databases are used for policy formulation. To that end, a literature search as well as consultations with a number of knowledgeable persons active in the field of statistics and data provision was conducted. Based on the review, a set of recommendations were produced to improve current practices within the region with respect evidence based policy formulation.

Effects of therapeutic approach on the neonatal evolution of very low birth weight infants with patent ductus arteriosus

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Products for the treatment of inflammatory bowel disease: a patent review (2013-2014)

Introduction: Inflammatory bowel disease (IBD) consists of Crohn's disease, ulcerative colitis and an unspecific IBD. The unclear etiology of IBD is a limiting factor that complicates the development of new pharmacological treatments and explains the high frequency of refractory patients to current drugs, including both conventional and biological therapies. In view of this, recent progress on the development of novel patented products to treat IBD was reviewed.Areas covered: Evaluation of the patent literature during the period 2013 - 2014 focused on chemical compounds, functional foods and biological therapy useful for the treatment of IBD.Expert opinion: Majority of the patents are not conclusive because they were based on data from unspecific methods not related to intestinal inflammation and, when related to IBD models, few biochemical and molecular evaluations that could be corroborating their use in human IBD were presented. On the other hand, methods and strategies using new formulations of conventional drugs, guanylyl cyclase C peptide agonists, compounds that influence anti-adhesion molecules, mAbs anti-type I interferons and anti-integrin, oligonucleotide antisense Smad7, growth factor neuregulin 4 and functional foods, particularly fermented wheat germ with Saccharomyces cerevisiae, are promising products for use in the very near future.

Using Economics Experiments to Understand Patent Licensing Behavior

To successfully compete in today’s globalized economy, agribusiness firms need to innovate. Innovation enables firms to produce new and/or differentiated products/services that satisfy specialized consumer demands, and enables firms to generate cost reducing processes to out-compete rivals in domestic and international food markets. Firms will engage in innovative activities if they are able to recoup research and development (R&D) costs and capture innovation rents, so it is critical that they are able to identify the optimal strategies of protecting and profiting from their innovations.

QuMinS: fast and scalable querying, mining and summarizing multi-modal databases

Given a large image set, in which very few images have labels, how to guess labels for the remaining majority? How to spot images that need brand new labels different from the predefined ones? How to summarize these data to route the user’s attention to what really matters? Here we answer all these questions. Specifically, we propose QuMinS, a fast, scalable solution to two problems: (i) Low-labor labeling (LLL) – given an image set, very few images have labels, find the most appropriate labels for the rest; and (ii) Mining and attention routing – in the same setting, find clusters, the top-'N IND.O' outlier images, and the 'N IND.R' images that best represent the data. Experiments on satellite images spanning up to 2.25 GB show that, contrasting to the state-of-the-art labeling techniques, QuMinS scales linearly on the data size, being up to 40 times faster than top competitors (GCap), still achieving better or equal accuracy, it spots images that potentially require unpredicted labels, and it works even with tiny initial label sets, i.e., nearly five examples. We also report a case study of our method’s practical usage to show that QuMinS is a viable tool for automatic coffee crop detection from remote sensing images.

Gender classification in large databases

[EN]In this paper, we address the challenge of gender classi - cation using large databases of images with two goals. The rst objective is to evaluate whether the error rate decreases compared to smaller databases. The second goal is to determine if the classi er that provides the best classi cation rate for one database, improves the classi cation results for other databases, that is, the cross-database performance.