Confusion and uncertainty in credit markets

Includes bibliography

Reducing Legal Uncertainty: A Challenge for Subregional Integration in Latin America and the Caribbean

Despite the recovery in intraregional trade over the past three years, intra-group trade, that is trade within the Southern Common Market (MERCOSUR), the Andean Community (CAN) and the Central American Common Market (CACM), remains much weaker than that observed within similar groups in other regions of the world. This weakness is due essentially to the serious lack of complementarity in the process of eliminating tariff barriers (see chapter 3 of Latin America and the Caribbean in the World Economy 2004: Trends 2005, and the study on regional integration entitled: "América Latina y El Caribe: La integración regional en la hora de las definiciones", which is due to be published shortly and which updates basic information for the year 2005). The reasons include (a) weak institutional capacities; (b) the lack of macroeconomic coordination; (c) inadequate infrastructure and d) the lack of depth in integration-related trade disciplines.  This edition of the Bulletin reviews the mechanisms for dispute settlement within Mercosur, the Andean Community and CACM with a view to drawing conclusions on the extent to which they are used. In order to reform such mechanisms, consideration should be given to the creation of a single dispute settlement mechanism which would replicate the procedures and regulations of the World Trade Organization (WTO).

Prevalence and genotyping of hepatitis C virus in blood donors in the state of Pará, Northern Brazil

Given the scarcity of epidemiological information on hepatitis C virus (HCV) infection in Northern Brazil, we determined the prevalence and genotypic frequency in blood donors in the state of Pará (PA). Blood samples from all of the blood donors at the Fundação HEMOPA (blood bank of PA) from 2004-2006 were screened for the presence of antibodies to anti-HCV and samples seroreactive to anti-HCV were further tested for HCV RNA using real-time PCR. In total, 116 HCV-RNA samples were genotyped, based on maximum likelihood phylogenetic analyses, using BioEdit, Modelgenerator, PHYML and FigTree software. The population consisted of 242,726 volunteers who donated blood from 2004-2006; the most common subgroup was males between the ages of 18-29 years old (37.30%). Within the whole group, 1,112 blood donors (0.46%) had indeterminate or positive serology; among these, 28.78% were males whose ages ranged from 18-29 years. A diagnosis of chronic HCV infection was confirmed for 304 donors (60.20% males; 66.45% were 30-49 years old), resulting in a prevalence of HCV RNA in 0.13% of the samples (304 of 242,726). HCV genotyping revealed a high frequency of genotype 1 (108/116) followed by genotype 3 (8/116). This study found HCV infection to be relatively infrequent in PA; genotype 1 was most commonly isolated. This information can help guide prevention and control policies aimed at efficient diagnosis and control measures.

Genomic divergence of zebu and taurine cattle identified through high-density SNP genotyping

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

Evaluation of ERIC-PCR as Genotyping Method for Corynebacterium pseudotuberculosis Isolates

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

The first molecular phylogeny of Chilodontidae (Teleostei: Ostariophysi: Characiformes) reveals cryptic biodiversity and taxonomic uncertainty

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Amazon forest biomass density maps: tackling the uncertainty in carbon emission estimates

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

A Fuzzy Goal Programming model for solving aggregate production-planning problems under uncertainty: A case study in a Brazilian sugar mill

This paper proposes a Fuzzy Goal Programming model (FGP) for a real aggregate production-planning problem. To do so, an application was made in a Brazilian Sugar and Ethanol Milling Company. The FGP Model depicts the comprehensive production process of sugar, ethanol, molasses and derivatives, and considers the uncertainties involved in ethanol and sugar production. Decision-makings, related to the agricultural and logistics phases, were considered on a weekly-basis planning horizon to include the whole harvesting season and the periods between harvests. The research has provided interesting results about decisions in the agricultural stages of cutting, loading and transportation to sugarcane suppliers and, especially, in milling decisions, whose choice of production process includes storage and logistics distribution. (C)2014 Elsevier B.V. All rights reserved.

Quantum coherence and uncertainty in the anisotropic XY chain

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

A note on model uncertainty in linear regression

We consider model selection uncertainty in linear regression. We study theoretically and by simulation the approach of Buckland and co-workers, who proposed estimating a parameter common to all models under study by taking a weighted average over the models, using weights obtained from information criteria or the bootstrap. This approach is compared with the usual approach in which the 'best' model is used, and with Bayesian model averaging. The weighted predictor behaves similarly to model averaging, with generally more realistic mean-squared errors than the usual model-selection-based estimator.

Candida albicans: genotyping methods and clade related phenotypic characteristics

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

Fuzzy rule-based system for evaluation of uncertainty transaction in cassava chain

A fuzzy ruled-based system was developed in this study and resulted in an index indicating the level of uncertainty related to commercial transactions between cassava growers and their dealers. The fuzzy system was developed based on Transaction Cost Economics approach. The fuzzy system was developed from input variables regarding information sharing between grower and dealer on “Demand/purchase Forecasting”, “Production Forecasting” and “Production Innovation”. The output variable is the level of uncertainty regarding the transaction between seller and buyer agent, which may serve as a system for detecting inefficiencies. Evidences from 27 cassava growers registered in the Regional Development Offices of Tupa and Assis, São Paulo, Brazil, and 48 of their dealers supported the development of the system. The mathematical model indicated that 55% of the growers present a Very High level of uncertainty, 33% present Medium or High. The others present Low or Very Low level of uncertainty. From the model, simulations of external interferences can be implemented in order to improve the degree of uncertainty and, thus, lower transaction costs.

Strategies for single nucleotide polymorphism (SNP) genotyping to enhance genotype imputation in Gyr (Bos indicus) dairy cattle: Comparison of commercially available SNP chips

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Accounting for uncertainty in ecological analysis: the strengths and limitations of hierarchical statistical modeling

Analyses of ecological data should account for the uncertainty in the process(es) that generated the data. However, accounting for these uncertainties is a difficult task, since ecology is known for its complexity. Measurement and/or process errors are often the only sources of uncertainty modeled when addressing complex ecological problems, yet analyses should also account for uncertainty in sampling design, in model specification, in parameters governing the specified model, and in initial and boundary conditions. Only then can we be confident in the scientific inferences and forecasts made from an analysis. Probability and statistics provide a framework that accounts for multiple sources of uncertainty. Given the complexities of ecological studies, the hierarchical statistical model is an invaluable tool. This approach is not new in ecology, and there are many examples (both Bayesian and non-Bayesian) in the literature illustrating the benefits of this approach. In this article, we provide a baseline for concepts, notation, and methods, from which discussion on hierarchical statistical modeling in ecology can proceed. We have also planted some seeds for discussion and tried to show where the practical difficulties lie. Our thesis is that hierarchical statistical modeling is a powerful way of approaching ecological analysis in the presence of inevitable but quantifiable uncertainties, even if practical issues sometimes require pragmatic compromises.

Seeking a Second Opinion: Uncertainty in Disease Ecology

Analytical methods accounting for imperfect detection are often used to facilitate reliable inference in population and community ecology. We contend that similar approaches are needed in disease ecology because these complicated systems are inherently difficult to observe without error. For example, wildlife disease studies often designate individuals, populations, or spatial units to states (e.g., susceptible, infected, post-infected), but the uncertainty associated with these state assignments remains largely ignored or unaccounted for. We demonstrate how recent developments incorporating observation error through repeated sampling extend quite naturally to hierarchical spatial models of disease effects, prevalence, and dynamics in natural systems. A highly pathogenic strain of avian influenza virus in migratory waterfowl and a pathogenic fungus recently implicated in the global loss of amphibian biodiversity are used as motivating examples. Both show that relatively simple modifications to study designs can greatly improve our understanding of complex spatio-temporal disease dynamics by rigorously accounting for uncertainty at each level of the hierarchy.