Economic reforms, growth and employment: labour markets in Latin America and the Caribbean

Includes bibliography

Structural change and productivity growth, 20 years later: old problems, new opportunities

Includes bibliography

Open regionalism in Asia Pacific and Latin America: a survey of the literature

Includes bibliography

Job losses, multinationals and globalization: the anatomy of disempowerment

Includes bibliography

The evolution of world income inequality: assessing the impact of globalization

Includes bibliography

Globalization and liberalization: the impact on developing countries

Includes bibliography

Open regionalism and economic integration

Includes bibliography

Globalization and restructuring the energy sector in Latin America

Includes bibliography

Structural change and productivity growth 20 years later: old problems, new opportunities. Summary

Includes bibliography

Regional integration in Latin America, globalization and South-South trade

Includes bibliography

Brazil’s Northeast Financing Constitutional Fund: Differentiated effects on municipal economic growth

This article investigates the effects of the investments made by the Northeast Financing Constitutional Fund (FNE) on the economic growth of that region's municipalities in the decade of 2000. To that end, it uses an empirical framework based on growth models that make it possible to form convergence clubs according to the municipalities' initial development level. The results corroborate the empirical strategy and reveal the existence of four groups of municipalities, in which investment flows through the FNE have different effects on growth. In general, the FNE produces positive and significant effects in most municipalities of the Northeast, except for those whose gross domestic product (GDP) per capita was either very low or very high at the start of the decade, in which case its effects are not significant.

Pseudechis guttatus venom proteome: Insights into evolution and toxin clustering

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Scalable Web Server Clustering Technologies

The exponential growth of the Internet, coupled with the increasing popularity of dynamically generated content on the World Wide Web, has created the need for more and faster Web servers capable of serving the over 100 million Internet users. Server clustering has emerged as a promising technique to build scalable Web servers. In this article we examine the seminal work, early products, and a sample of contemporary commercial offerings in the field of transparent Web server clustering. We broadly classify transparent server clustering into three categories.

Identification of protein expression signatures in gastric carcinomas using clustering analysis

Background and Aim: The identification of gastric carcinomas (GC) has traditionally been based on histomorphology. Recently, DNA microarrays have successfully been used to identify tumors through clustering of the expression profiles. Random forest clustering is widely used for tissue microarrays and other immunohistochemical data, because it handles highly-skewed tumor marker expressions well, and weighs the contribution of each marker according to its relatedness with other tumor markers. In the present study, we e identified biologically- and clinically-meaningful groups of GC by hierarchical clustering analysis of immunohistochemical protein expression. Methods: We selected 28 proteins (p16, p27, p21, cyclin D1, cyclin A, cyclin B1, pRb, p53, c-met, c-erbB-2, vascular endothelial growth factor, transforming growth factor [TGF]-beta I, TGF-beta II, MutS homolog-2, bcl-2, bax, bak, bcl-x, adenomatous polyposis coli, clathrin, E-cadherin, beta-catenin, mucin (MUC) 1, MUC2, MUC5AC, MUC6, matrix metalloproteinase [ MMP]-2, and MMP-9) to be investigated by immunohistochemistry in 482 GC. The analyses of the data were done using a random forest-clustering method. Results: Proteins related to cell cycle, growth factor, cell motility, cell adhesion, apoptosis, and matrix remodeling were highly expressed in GC. We identified protein expressions associated with poor survival in diffuse-type GC. Conclusions: Based on the expression analysis of 28 proteins, we identified two groups of GC that could not be explained by any clinicopathological variables, and a subgroup of long-surviving diffuse-type GC patients with a distinct molecular profile. These results provide not only a new molecular basis for understanding the biological properties of GC, but also better prediction of survival than the classic pathological grouping.

Site- and species-specific responses of forest growth to climate across the European continent

Aim To evaluate the climate sensitivity of model-based forest productivity estimates using a continental-scale tree-ring network. Location Europe and North Africa (30–70° N, 10° W–40° E). Methods We compiled close to 1000 annually resolved records of radial tree growth for all major European tree species and quantified changes in growth as a function of historical climatic variation. Sites were grouped using a neural network clustering technique to isolate spatiotemporal and species-specific climate response patterns. The resulting empirical climate sensitivities were compared with the sensitivities of net primary production (NPP) estimates derived from the ORCHIDEE-FM and LPJ-wsl dynamic global vegetation models (DGVMs). Results We found coherent biogeographic patterns in climate response that depend upon (1) phylogenetic controls and (2) ambient environmental conditions delineated by latitudinal/elevational location. Temperature controls dominate forest productivity in high-elevation and high-latitude areas whereas moisture sensitive sites are widespread at low elevation in central and southern Europe. DGVM simulations broadly reproduce the empirical patterns, but show less temperature sensitivity in the boreal zone and stronger precipitation sensitivity towards the mid-latitudes. Main conclusions Large-scale forest productivity is driven by monthly to seasonal climate controls, but our results emphasize species-specific growth patterns under comparable environmental conditions. Furthermore, we demonstrate that carry-over effects from the previous growing season can significantly influence tree growth, particularly in areas with harsh climatic conditions – an element not considered in most current-state DGVMs. Model–data discrepancies suggest that the simulated climate sensitivity of NPP will need refinement before carbon-cycle climate feedbacks can be accurately quantified.