Assessing the dynamics of terms of trade in a model of cumulative causation and structural change

ABSTRACT The motivation for this paper stems from the steady decline in the share of consumer expenditures on goods produced in the global south, coupled with the (empirically ambiguous) Singer/Prebisch hypothesis that this can be explained by a secular decline in the southern terms of trade. Drawing on these sources of inspiration, the paper sets out to study the dynamics of the terms of trade using a multi-sector growth model based on the principle of cumulative causation. The upshot is a North-South model of growth and trade in which the evolution of the terms of trade depends on differential rates of productivity growth in different sectors of the economy - and in which terms of trade dynamics may not be the best guide as to whether or not there is an uneven development problem.

Use of Poisson spatiotemporal regression models for the Brazilian Amazon Forest: malaria count data

INTRODUCTION: Malaria is a serious problem in the Brazilian Amazon region, and the detection of possible risk factors could be of great interest for public health authorities. The objective of this article was to investigate the association between environmental variables and the yearly registers of malaria in the Amazon region using Bayesian spatiotemporal methods. METHODS: We used Poisson spatiotemporal regression models to analyze the Brazilian Amazon forest malaria count for the period from 1999 to 2008. In this study, we included some covariates that could be important in the yearly prediction of malaria, such as deforestation rate. We obtained the inferences using a Bayesian approach and Markov Chain Monte Carlo (MCMC) methods to simulate samples for the joint posterior distribution of interest. The discrimination of different models was also discussed. RESULTS: The model proposed here suggests that deforestation rate, the number of inhabitants per km², and the human development index (HDI) are important in the prediction of malaria cases. CONCLUSIONS: It is possible to conclude that human development, population growth, deforestation, and their associated ecological alterations are conducive to increasing malaria risk. We conclude that the use of Poisson regression models that capture the spatial and temporal effects under the Bayesian paradigm is a good strategy for modeling malaria counts.

An analysis of the spatiotemporal distribution of American cutaneous leishmaniasis in counties located along road and railway corridors in the State of Maranhao, Brazil

Introduction The incidence of American cutaneous leishmaniasis (ACL) is increasing in Latin America, especially in Brazil, where 256,587 cases were confirmed in the last decade. Methods This study used a Bayesian model to examine the spatial and temporal distribution of ACL cases between 2000 and 2009 in 61 counties of State of Maranhão located along the three main road and railway corridors. Results During the study period, 13,818 cases of ACL were recorded. There was a significant decrease in the incidence of ACL in the ten study years. The recorded incidence rate ranged from 7.36 to 241.45 per 100,000 inhabitants. The relative risk increased in 77% of the counties, decreased in 18% and was maintained in only five counties. Conclusions Although there was a decreased incidence of the disease, ACL was present in all of the examined municipalities, thus maintaining the risk of contracting this illness.

Sensitivity of the Amazon biome to high resolution climate change projections

ABSTRACT: Despite the reduction in deforestation rate in recent years, the impact of global warming by itself can cause changes in vegetation cover. The objective of this work was to investigate the possible changes on the major Brazilian biome, the Amazon Rainforest, under different climate change scenarios. The dynamic vegetation models may simulate changes in vegetation distribution and the biogeochemical processes due to climate change. Initially, the Inland dynamic vegetation model was forced with initial and boundary conditions provided by CFSR and the Eta regional climate model driven by the historical simulation of HadGEM2-ES. These simulations were validated using the Santarém tower data. In the second part, we assess the impact of a future climate change on the Amazon biome by applying the Inland model forced with regional climate change projections. The projections show that some areas of rainforest in the Amazon region are replaced by deciduous forest type and grassland in RCP4.5 scenario and only by grassland in RCP8.5 scenario at the end of this century. The model indicates a reduction of approximately 9% in the area of tropical forest in RCP4.5 scenario and a further reduction in the RCP8.5 scenario of about 50% in the eastern region of Amazon. Although the increase of CO2 atmospheric concentration may favour the growth of trees, the projections of Eta-HadGEM2-ES show increase of temperature and reduction of rainfall in the Amazon region, which caused the forest degradation in these simulations.

Associations, causation and model in psychiatry

This paper discusses models, associations and causation in psychiatry. The different types of association (linear, positive, negative, exponential, partial, U shaped relationship, hidden and spurious) between variables involved in mental disorders are presented as well as the use of multiple regression analysis to disentangle interrelatedness amongst multiple variables. A useful model should have internal consistency, external validity and predictive power; be dynamic in order to accommodate new sound knowledge; and should fit facts rather than they other way around. It is argued that whilst models are theoretical constructs they also convey a style of reasoning and can change clinical practice. Cause and effect are complex phenomena in that the same cause can yield different effects. Conversely, the same effect can have a different range of causes. In mental disorders and human behaviour there is always a chain of events initiated by the indirect and remote cause; followed by intermediate causes; and finally the direct and more immediate cause. Causes of mental disorders are grouped as those: (i) which are necessary and sufficient; (ii) which are necessary but not sufficient; and (iii) which are neither necessary nor sufficient, but when present increase the risk for mental disorders.

Effects of Non-Susceptible Hosts on the Infection with Trypanosoma cruzi of the Vector Triatoma infestans: an Experimental Model

We tested experimentally the effects of the presence of non-susceptible hosts on the infection with Trypanosoma cruzi of the vector Triatoma infestans. The experiment consisted in two treatments: with chickens, including two chickens (non-susceptible hosts) and two infected guinea pigs (susceptible hosts), and without chickens, including only two infected guinea pigs. The hosts were held unrestrained in individual metal cages inside a closed tulle chamber. A total of 200 uninfected T. infestans third instar nymphs were liberated in each replica, collected on day 14, and examined for infection and blood meal sources on day 32-36. The additional presence of chickens relative to infected guinea pigs: (a) significantly modified the spatial distribution of bugs; (b) increased significantly the likelihoods of having a detectable blood meal on any host and molting to the next instar; (c) did not affect the bugs' probability of death by predation; and (d) decreased significantly the overall percentage of T. infestans infected with T. cruzi. The bugs collected from inside or close to the guinea pigs' cages showed a higher infection rate (71-88%) than those collected from the chickens' cages (22-32%). Mixed blood meals on chickens and guinea pigs were detected in 12-21% of bugs. Although the presence of chickens would decrease the overall percentage of infected bugs in short term experiments, the high rate of host change of T. infestans would make this difference fade out if longer exposure times had been provided.

Geoecological drivers of cerrado heterogeneity and 13C natural abundance in oxisols after land-use change

The 13C natural abundance technique was applied to study C dynamics after land-use change from native savanna to Brachiaria, Pinus, and Eucalyptus in differently textured Cerrado Oxisols. But due to differences in the d13C signatures of subsoils under native savanna and under introduced species, C substitution could only be calculated based on results of cultivated soils nearby. It was estimated that after 20 years, Pinus C had replaced only 5 % of the native C in the 0-1.2 m layer, in which substitution was restricted to the top 0.4 m. Conversely, after 12 years, Brachiaria had replaced 21 % of Cerrado C to a depth of 1.2 m, where substitution decreased only slightly throughout the entire profile. The high d13C values in the subsoils of the cultivated sites led to the hypothesis that the natural vegetation there had been grassland rather than Cerrado sensu stricto, in spite of the comparable soil and site characteristics and the proximity of the studied sites. The hypothesis was tested using aerial photographs of 1964, which showed that the cultivated sites were located on a desiccated runoff head. The vegetation shift to a grass-dominated savanna formation might therefore have occurred in response to waterlogging and reduced soil aeration. A simple model was developed thereof, which ascribes the different Cerrado formations mainly to the plant-available water content and soil aeration. Soil fertility is considered of minor significance only, since at the studied native savanna sites tree density was independent of soil texture or nutrient status.

Modeling changes in organic carbon stocks for distinct soils in southeastern brazil after four eucalyptus rotations using the century model

Soil organic matter (SOM) plays an important role in carbon (C) cycle and soil quality. Considering the complexity of factors that control SOM cycling and the long time it usually takes to observe changes in SOM stocks, modeling constitutes a very important tool to understand SOM cycling in forest soils. The following hypotheses were tested: (i) soil organic carbon (SOC) stocks would be higher after several rotations of eucalyptus than in low-productivity pastures; (ii) SOC values simulated by the Century model would describe the data better than the mean of observations. So, the aims of the current study were: (i) to evaluate the SOM dynamics using the Century model to simulate the changes of C stocks for two eucalyptus chronosequences in the Rio Doce Valley, Minas Gerais State, Brazil; and (ii) to compare the C stocks simulated by Century with the C stocks measured in soils of different Orders and regions of the Rio Doce Valley growing eucalyptus. In Belo Oriente (BO), short-rotation eucalyptus plantations had been cultivated for 4.0; 13.0, 22.0, 32.0 and 34.0 years, at a lower elevation and in a warmer climate, while in Virginópolis (VG), these time periods were 8.0, 19.0 and 33.0 years, at a higher elevation and in a milder climate. Soil samples were collected from the 0-20 cm layer to estimate C stocks. Results indicate that the C stocks simulated by the Century model decreased after 37 years of poorly managed pastures in areas previously covered by native forest in the regions of BO and VG. The substitution of poorly managed pastures by eucalyptus in the early 1970´s led to an average increase of C of 0.28 and 0.42 t ha-1 year-1 in BO and VG, respectively. The measured C stocks under eucalyptus in distinct soil Orders and independent regions with variable edapho-climate conditions were not far from the values estimated by the Century model (root mean square error - RMSE = 20.9; model efficiency - EF = 0.29) despite the opposite result obtained with the statistical procedure to test the identity of analytical methods. Only for lower soil C stocks, the model over-estimated the C stock in the 0-20 cm layer. Thus, the Century model is highly promising to detect changes in C stocks in distinct soil orders under eucalyptus, as well as to indicate the impact of harvest residue management on SOM in future rotations.

Maize leaf development under climate change scenarios

The objective of this work was to simulate maize leaf development in climate change scenarios at Santa Maria, RS, Brazil, considering symmetric and asymmetric increases in air temperature. The model of Wang & Engel for leaf appearance rate (LAR), with genotype-specific coefficients for the maize variety BRS Missões, was used to simulate tip and expanded leaf accumulated number from emergence to flag leaf appearance and expansion, for nine emergence dates from August 15 to April 15. LAR model was run for each emergence date in 100-year climate scenarios: current climate, and +1, +2, +3, +4 and +5°C increase in mean air temperature, with symmetric and asymmetric increase in daily minimum and maximum air temperature. Maize crop failure due to frost decreased in elevated temperature scenarios, in the very early and very late emergence dates, indicating a lengthening in the maize growing season in warmer climates. The leaf development period in maize was shorter in elevated temperature scenarios, with greater shortening in asymmetric temperature increases, indicating that warmer nights accelerate vegetative development in maize.

CO2-response function of radiation use efficiency in rice for climate change scenarios

The objective of this work was to evaluate a generalized response function to the atmospheric CO2 concentration [f(CO2)] by the radiation use efficiency (RUE) in rice. Experimental data on RUE at different CO2 concentrations were collected from rice trials performed in several locations around the world. RUE data were then normalized, so that all RUE at current CO2 concentration were equal to 1. The response function was obtained by fitting normalized RUE versus CO2 concentration to a Morgan-Mercer-Flodin (MMF) function, and by using Marquardt's method to estimate the model coefficients. Goodness of fit was measured by the standard deviation of the estimated coefficients, the coefficient of determination (R²), and the root mean square error (RMSE). The f(CO2) describes a nonlinear sigmoidal response of RUE in rice, in function of the atmospheric CO2 concentration, which has an ecophysiological background, and, therefore, renders a robust function that can be easily coupled to rice simulation models, besides covering the range of CO2 emissions for the next generation of climate scenarios for the 21st century.

Climate change and future scenarios for palisade grass production in the state of São Paulo, Brazil

The objective of this work was to analyze future scenarios for palisade grass yield subjected to climate change for the state of São Paulo, Brazil. An empirical crop model was used to estimate yields, according to growing degree-days adjusted by one drought attenuation factor. Climate data from 1963 to 2009 of 23 meteorological stations were used for current climate conditions. Downscaled outputs of two general circulation models were used to project future climate for the 2013-2040 and 2043-2070 periods, considering two contrasting scenarios of temperature and atmospheric CO2 concentration increase (high and low). Annual dry matter yield should be from 14 to 42% higher than the current one, depending on the evaluated scenario. Yield variation between seasons (seasonality) and years is expected to increase. The increase of dry matter accumulation will be higher in the rainy season than in the dry season, and this result is more evident for soils with low-water storage capacity. The results varied significantly between regions (<10% to >60%). Despite their higher climate potential, warmer regions will probably have a lower increase in future forage production.

Incubation period of Hemileia vastatrix in coffee plants in Brazil simulated under climate change

Risk analysis of climate change on plant diseases has great importance for agriculture since it allows the evaluation of management strategies to minimize future damages. This work aimed to simulate future scenarios of coffee rust (Hemileia vastatrix) epidemics by elaborating geographic distribution maps using a model that estimates the pathogen incubation period and the output from three General Circulation Models (CSIRO-Mk3.0, INM-CM3.0, and MIROC3.2.medres). The climatological normal from 1961-1990 was compared with that of the decades 2020s, 2050s and 2080s using scenarios A2 and B1 from the IPCC. Maps were prepared with a spatial resolution of 0.5 × 0.5 degrees of latitude and longitude for ten producing states in Brazil. The climate variables used were maximum and minimum monthly temperatures. The maps obtained in scenario A2 showed a tendency towards a reduction in the incubation period when future scenarios are compared with the climatological normal from 1961-1990. A reduction in the period was also observed in scenario B1, although smaller than that in scenario A2.

Climate risk in maize crop in the northeastern of Brazil based on climate change scenarios

This study evaluates the impacts of climate change on the agricultural zoning of climatic risk in maize crop cultivated in the Northeastern of Brazil, based on the Intergovernmental Panel on Climate Change (IPCC) reports. The water balance model, combined with geospatial technologies, was used to identify areas of the study region where the crops could suffer yield restrictions due to climate change. The data used in the study were the time series of rainfall with at least 30 years of daily data, crop coefficients, potential evapotranspiration and duration of the crop cycle. The scenarios of the increasing of air temperature used in the simulations were of 1.5ºC, 3ºC and 5ºC. The sowing date of maize crop from January to March appears to be less affected by warming scenarios than the sowing in November and December or April and May.

Evaluation of a model for induction of periodontal disease in dogs

There are several methods for inducing periodontal disease in animal models, being the bone defect one of the most reported. This study aimed to evaluate this model, through clinical, radiographic, tomographic and histological analyzes, thus providing standardized data for future regenerative works. Twelve dogs were subjected to the induction protocol. In a first surgical procedure, a mucoperiosteal flap was made on the buccal aspect of the right third and fourth premolars and a defect was produced exposing the furcation and mesial and distal roots, with dimensions: 5mm coronoapical, 5mm mesiodistal, and 3mm buccolingual. Periodontal ligament and cementum were curetted and the defect was filled with molding polyester, which was removed after 21 days on new surgical procedure. Clinical and radiographic examinations were performed after the two surgeries and before the collection of parts for dental tomography and histological analysis. All animals showed grade II furcation exposure in both teeth. Clinical attachment level increased after induction. Defect size did not change for coronoapical and buccolingual measurements, while mesiodistal size was significantly higher than at the time of defect production. Radiographic analysis showed decreased radiopacity and discontinuity of lamina dura in every tooth in the furcation area. The horizontal progression of the disease was evident in micro-computed tomography and defect content in the histological analysis. Therefore, it is concluded that this method promotes the induction of periodontal disease in dogs in a standardized way, thus being a good model for future work.

A temperature predicting model for manufacturing processes requiring coiling

A model for predicting temperature evolution for automatic controling systems in manufacturing processes requiring the coiling of bars in the transfer table is presented. Although the method is of a general nature, the presentation in this work refers to the manufacturing of steel plates in hot rolling mills. The predicting strategy is based on a mathematical model of the evolution of temperature in a coiling and uncoiling bar and is presented in the form of a parabolic partial differential equation for a shape changing domain. The mathematical model is solved numerically by a space discretization via geometrically adaptive finite elements which accomodate the change in shape of the domain, using a computationally novel treatment of the resulting thermal contact problem due to coiling. Time is discretized according to a Crank-Nicolson scheme. Since the actual physical process takes less time than the time required by the process controlling computer to solve the full mathematical model, a special predictive device was developed, in the form of a set of least squares polynomials, based on the off-line numerical solution of the mathematical model.