Self-determination and collective responsibility in the secessionist struggle

The often violent emergence of new independent states following the end of the Cold War generated discussion about the normative grounds of territorial separatism. A number of opposing approaches surfaced debating whether and under which circumstances there is a right for a community to secede from its host country. Overwhelmingly, these studies placed emphasis on the right to secession and neglected the moral stance of secessionist movements as agents in international relations. In this book Costas Laoutides explores the collective moral agency involved in secessionist struggles offering a theoretical model for the collective responsibility of secessionist groups. Case-studies on the Kurds and the people of Moldova-Transdniestria illustrate the author’s theoretical arguments as he seeks to establish how, although the principle of self-determination was envisaged as a means of gradually bestowing political power upon the people, it never managed to realize its full potential because it was interpreted strictly within a framework of exclusionary politics of identity.

The Potential Of Kohonen Method For Classifying Rivers Focused On Regional Environmental Flow Determination With ELOHA

This article highlights the potential benefits that the Kohonen method has for the classification of rivers with similar characteristics by determining regional ecological flows using the ELOHA (Ecological Limits of Hydrologic Alteration) methodology. Currently, there are many methodologies for the classification of rivers, however none of them include the characteristics found in Kohonen method such as (i) providing the number of groups that actually underlie the information presented, (ii) used to make variable importance analysis, (iii) which in any case can display two-dimensional classification process, and (iv) that regardless of the parameters used in the model the clustering structure remains. In order to evaluate the potential benefits of the Kohonen method, 174 flow stations distributed along the great river basin “Magdalena-Cauca” (Colombia) were analyzed. 73 variables were obtained for the classification process in each case. Six trials were done using different combinations of variables and the results were validated against reference classification obtained by Ingfocol in 2010, whose results were also framed using ELOHA guidelines. In the process of validation it was found that two of the tested models reproduced a level higher than 80% of the reference classification with the first trial, meaning that more than 80% of the flow stations analyzed in both models formed invariant groups of streams.

Model selection, estimation and forecasting in VAR models with short-run and long-run restrictions

We study the joint determination of the lag length, the dimension of the cointegrating space and the rank of the matrix of short-run parameters of a vector autoregressive (VAR) model using model selection criteria. We consider model selection criteria which have data-dependent penalties for a lack of parsimony, as well as the traditional ones. We suggest a new procedure which is a hybrid of traditional criteria and criteria with data-dependant penalties. In order to compute the fit of each model, we propose an iterative procedure to compute the maximum likelihood estimates of parameters of a VAR model with short-run and long-run restrictions. Our Monte Carlo simulations measure the improvements in forecasting accuracy that can arise from the joint determination of lag-length and rank, relative to the commonly used procedure of selecting the lag-length only and then testing for cointegration.

Model selection, estimation and forecasting in VAR models with short-run and long-run restrictions

We study the joint determination of the lag length, the dimension of the cointegrating space and the rank of the matrix of short-run parameters of a vector autoregressive (VAR) model using model selection criteria. We consider model selection criteria which have data-dependent penalties as well as the traditional ones. We suggest a new two-step model selection procedure which is a hybrid of traditional criteria and criteria with data-dependant penalties and we prove its consistency. Our Monte Carlo simulations measure the improvements in forecasting accuracy that can arise from the joint determination of lag-length and rank using our proposed procedure, relative to an unrestricted VAR or a cointegrated VAR estimated by the commonly used procedure of selecting the lag-length only and then testing for cointegration. Two empirical applications forecasting Brazilian inflation and U.S. macroeconomic aggregates growth rates respectively show the usefulness of the model-selection strategy proposed here. The gains in different measures of forecasting accuracy are substantial, especially for short horizons.

Model selection, estimation and forecasting in VAR models with short-run and long-run restrictions

We study the joint determination of the lag length, the dimension of the cointegrating space and the rank of the matrix of short-run parameters of a vector autoregressive (VAR) model using model selection criteria. We consider model selection criteria which have data-dependent penalties as well as the traditional ones. We suggest a new two-step model selection procedure which is a hybrid of traditional criteria and criteria with data-dependant penalties and we prove its consistency. Our Monte Carlo simulations measure the improvements in forecasting accuracy that can arise from the joint determination of lag-length and rank using our proposed procedure, relative to an unrestricted VAR or a cointegrated VAR estimated by the commonly used procedure of selecting the lag-length only and then testing for cointegration. Two empirical applications forecasting Brazilian in ation and U.S. macroeconomic aggregates growth rates respectively show the usefulness of the model-selection strategy proposed here. The gains in di¤erent measures of forecasting accuracy are substantial, especially for short horizons.

Model selection, estimation and forecasting in VAR models with short-run and long-run restrictions

We study the joint determination of the lag length, the dimension of the cointegrating space and the rank of the matrix of short-run parameters of a vector autoregressive (VAR) model using model selection criteria. We suggest a new two-step model selection procedure which is a hybrid of traditional criteria and criteria with data-dependant penalties and we prove its consistency. A Monte Carlo study explores the finite sample performance of this procedure and evaluates the forecasting accuracy of models selected by this procedure. Two empirical applications confirm the usefulness of the model selection procedure proposed here for forecasting.

Some notes about the determination of current account equilibrium real exchange rate and the relation between real exchange rate and productive specialization

The objective of these notes is to present a simple mathematical model of the determination of current account real exchange rate as defined by Bresser-Pereira (2010); i.e. the real exchange rate that guarantees the inter temporal equilibrium of balance of payments and to show the relation between Real Exchange rate and Productive Specialization at theoretical and empirical level.

Temporal variability of soil CO2 emission after conventional and reduced tillage described by an exponential decay in time model

A quantificação do impacto das práticas de preparo sobre as perdas de carbono do solo é dependente da habilidade de se descrever a variabilidade temporal da emissão de CO2 do solo após preparo. Tem sido sugerido que as grandes quantidades de CO2 emitido após o preparo do solo podem servir como um indicador das modificações nos estoques de carbono do solo em longo termo. Neste trabalho é apresentado um modelo de duas partes baseado na temperatura e na umidade do solo e que inclui um termo exponencial decrescente do tempo que é eficiente no ajuste das emissões intermediárias após preparo: arado de disco seguido de uma passagem com a grade niveladora (convencional) e escarificador de arrasto seguido da passagem com rolo destorroador (reduzido). As emissões após o preparo do solo são descritas utilizando-se estimativa não linear com um coeficiente de determinação (R²) tão alto quanto 0.98 após preparo reduzido. Os resultados indicam que nas previsões da emissão de CO2 após o preparo do solo é importante considerar um termo exponencial decrescente no tempo após preparo.

Short-term temporal changes of soil carbon losses after tillage described by a first-order decay model

Tillage stimulates soil carbon (C) losses by increasing aeration, changing temperature and moisture conditions, and thus favoring microbial decomposition. In addition, soil aggregate disruption by tillage exposes once protected organic matter to decomposition. We propose a model to explain carbon dioxide (CO2) emission after tillage as a function of the no-till emission plus a correction due to the tillage disturbance. The model assumes that C in the readily decomposable organic matter follows a first-order reaction kinetics equation as: dC(sail)(t)/dt = -kC(soil)(t) and that soil C-CO2 emission is proportional to the C decay rate in soil, where C-soil(t) is the available labile soil C (g m(-2)) at any time (t). Emissions are modeled in terms soil C available to decomposition in the tilled and non-tilled plots, and a relationship is derived between no-till (F-NT) and tilled (F-Gamma) fluxes, which is: F-T = a1F(NT)e(-a2t), where t is time after tillage. Predicted and observed fluxes showed good agreement based on determination coefficient (R-2), index of agreement and model efficiency, with R-2 as high as 0.97. The two parameters included in the model are related to the difference between the decay constant (k factor) of tilled and no-till plots (a(2)) and also to the amount of labile carbon added to the readily decomposable soil organic matter due to tillage (a,). These two parameters were estimated in the model ranging from 1.27 and 2.60 (a(1)) and - 1.52 x 10(-2) and 2.2 x 10(-2) day(-1) (a(2)). The advantage is that temporal variability of tillage-induced emissions can be described by only one analytical function that includes the no-till emission plus an exponential term modulated by tillage and environmentally dependent parameters. (C) 2008 Elsevier B.V. All rights reserved.

A simple and non-destructive model for individual leaf area estimation in citrus

Introduction. Leaf area is often related to plant growth, development, physiology and yield. Many non-destructive models have been proposed for leaf area estimation of several plant genotypes, demonstrating that leaf length, leaf width and leaf area are closely correlated. Thus, the objective of our study was to develop a reliable model for leaf area estimation from linear measurements of leaf dimensions for citrus genotypes. Materials and methods. Leaves of citrus genotypes were harvested, and their dimensions (length, width and area) were measured. Values of leaf area were regressed against length, width, the square of length, the square of width and the product (length x width). The most accurate equations, either linear or second-order polynomial, were regressed again with a new data set; then the most reliable equation was defined. Results and discussion. The first analysis showed that the variables length, width and the square of length gave better results in second-order polynomial equations, while the linear equations were more suitable and accurate when the width and the product (length x width) were used. When these equations were regressed with the new data set, the coefficient of determination (R(2)) and the agreement index 'd' were higher for the one that used the variable product (length x width), while the Mean Absolute Percentage Error was lower. Conclusion. The product of the simple leaf dimensions (length x width) can provide a reliable and simple non-destructive model for leaf area estimation across citrus genotypes.

DETERMINATION of THE INDIRECT ORIENTATION of ORBITAL PUSHBROOM IMAGES USING CONTROL STRAIGHT LINES

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

A Discussion Related to Orbit Determination Using Nonlinear Sigma Point Kalman Filter

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

Determination of the photoinduced birefringence and of the refractive index by Brewster method of epoxy resin doped with CdS

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Investigation about the copper adsorption on the chloropropylsilica gel surface modified with a nanostructured dendrimer DAB-Am-16: an analytical application for determination of copper in different samples

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

Rat model of depending prostaglandin renal state: Effect of ketoprofen

Introduction .The renal prostaglandins (PGs), vasodilators, preserve kidney function during increased activity of the renin-angiotensin system or renal sympathetic nerves (renal PG-dependent state [RPGD]). Ketoprofen (Ket) inhibits cyclooxygenase and, therefore, the synthesis of PGs. The aim of this study was to determine, in the rat, the action of Ket in the renal histology and function in a RPGD state (stress of anesthesia and hemorrhage). Material and Methods . Twenty male Wistar rats, anesthetized with sodium pentobarbital, were randomly divided into two groups: G1-control ( n = 10) and G2-Ket ( n = 10) submitted to arterial hemorrhage of 30% of volemia (estimated as 6% of body weight) three times (10% each 10 min), 65 min after anesthesia. G2 animals received Ket, 1.5 mg. kg -1 , venously, 5 min after anesthesia and 60 min before the first hemorrhage moment (first moment of the study [M1]). Medium arterial pressure (MAP), rectal temperature (T), and heart rate were monitored. G1 and G2 received para-aminohippurate sodium (PAH) and iothalamate sodium (IOT) solutions during the entire experimental time in order to determine clearance of PAH (effective renal plasma flow [ERPF]) and clearance of IOT (glomerular filtration rate [GFR]) without urine collection (determination of blood concentrations of PAH and IOT through the high-performance liquid chromatography), filtration fraction (FF), and renal vascular resistance (RVR). The animals were sacrificed in M3, 30 min after the third hemorrhage (M2) moment, and the kidneys and blood collected during the hemorrhage periods were utilized for histological study and determinations of hematocrit (Ht), serum creatinine (S Cr ), ERPF, GFR, FF, and RVR, respectively. Results . There were significant reductions of MAP, T, and Ht and a significant increase of S Cr . During the experiment, ERPF and GFR did not change, but ERPF was always higher in G1 than in G2. Ket did not alter FF, which increased in G1 over the duration of experiment. The Ket group had significantly higher RVR than the control group. The histology verified that both G1 and G2 were similar for tubular dilation and necrosis, but they were significantly different for tubular degeneration: G1 > G2. Conclusion . The changes observed in kidney histology probably were determined by hemorrhage and hypotension. Ket inhibited the synthesis of PGs and diminished tubular degeneration.