There is high demand for computational tools that can automatically label tweets (Twitter messages) as having positive or negative sentiment, but great effort and expense would be required to build a large enough hand-labeled training corpus on which to apply standard machine learning techniques. Going beyond current keyword-based heuristic techniques, this paper uses emoticons (e.g. ':)' and ':(') to collect a large training set with noisy labels using little human intervention and trains a Maximum Entropy classifier on that training set. Results on two hand-labeled test corpora are compared to various baselines and a keyword-based heuristic approach, with the machine learned classifier significantly outperforming both. / text

The standard ensemble filtering schemes such as Ensemble Kalman Filter (EnKF) and Sequential Monte Carlo (SMC) do not properly represent states of low priori probability when the number of samples is too small and the dynamical system is high dimensional system with highly non-Gaussian statistics. For example, when the standard ensemble methods are applied to two well-known simple, but highly nonlinear systems such as a one-dimensional stochastic diffusion process in a double-well potential and the well-known three-dimensional chaotic dynamical system of Lorenz, they produce erroneous results to track transitions of the systems from one state to the other.In this dissertation, a set of new parametric resampling methods are introduced to overcome this problem. The new filtering methods are motivated by a general H-theorem for the relative entropy of Markov stochastic processes. The entropy-based filters first approximate a prior distribution of a given system by a mixture of Gaussians and the Gaussian components represent different regions of the system. Then the parameters in each Gaussian, i.e., weight, mean and covariance are determined sequentially as new measurements are available. These alternative filters yield a natural generalization of the EnKF method to systems with highly non-Gaussian statistics when the mixture model consists of one single Gaussian and measurements are taken on full states.In addition, the new filtering methods give the quantities of the relative entropy and log-likelihood as by-products with no extra cost. We examine the potential usage and qualitative behaviors of the relative entropy and log-likelihood for the new filters. Those results of EnKF and SMC are also included. We present results of the new methods on the applications to the above two ordinary differential equations and one partial differential equation with comparisons to the standard filters, EnKF and SMC. These results show that the entropy-based filters correctly track the transitions between likely states in both highly nonlinear systems even with small sample size N=100.

Priority based scheduling disciplines are widely used by existing computer operating systems. However, the mathematical analysis and modelling of these systems present great difficulties since priority schedulling is not compatible with exact product form solutions of queueing network models (QNM's). It is therefore, necessary to employ credible approximate techniques for solving QNM's with priority classes. The principle of maximum entropy (ME) is a method of inference for estimating a probability distribution given prior information in the form of expected values. This principle is applied, based on marginal utilisation, mean queue length and idle state probability constraints, to characterise new product-form approximations for general open and closed QNM's with priority (preemptive-resume, non-preemtive head-of-line) and non-priority (first-come-first-served, processor-sharing, last-come-first-served with, or without preemtion) servers. The ME solutions are interpreted in terms of a decomposition of the original network into individual stable GIG11 queueing stations with assumed renewal arrival processes. These solutions are implemented by making use of the generalised exponential (GE) distributional model to approximate the interarrival-time and service-time distributions in the network. As a consequence the ME queue length distribution of the stable GE/GEzl priority queue, subject to mean value constraints obtained via classical queueing theory on bulk queues, is used as a 'building block' together with corresponding universal approximate flow formulae for the analysis of general QNM's with priorities. The credibility of the ME method is demonstrated with illustrative numerical examples and favourable comparisons against exact, simulation and other approximate methods are made.

In this study the maximum entropy formalism [JAYN 57] is suggested as an alternative theory for general queueing systems of computer performance analysis. The motivation is to overcome some of the problems arising in this field and to extend the scope of the results derived in the context of Markovian queueing theory. For the M/G/l model a unique maximum entropy solution., satisfying locALl balance is derived independent of any assumptions about the service time distribution. However, it is shown that this solution is identical to the steady state solution of the underlying Marko-v process when the service time distribution is of the generalised exponential (CE) type. (The GE-type distribution is a mixture of an exponential term and a unit impulse function at the origin). For the G/M/1 the maximum entropy solution is identical in form to that of the underlying Markov process, but a GE-type distribution still produces the maximum overall similar distributions. For the GIG11 model there are three main achievements: first, the spectral methods are extended to give exaft formulae for the average number of customers in the system for any G/G/l with rational Laplace transform. Previously, these results are obtainable only through simulation and approximation methods. (ii) secondly, a maximum entropy model is developed and used to obtain unique solutions for some types of the G/G/l. It is also discussed how these solutions can be related to the corresponding stochastic processes. (iii) the importance of the G/GE/l and the GE/GE/l for the analysis of general networks is discussed and some flow processes for these systems are characterised. For general queueing networks it is shown that the maximum entropy solution is a product of the maximum entropy solutions of the individual nodes. Accordingly, existing computational algorithms are extended to cover general networks with FCFS disciplines. Some implementations are suggested and a flow algorithm is derived. Finally, these results are iised to improve existing aggregation methods. In addition, the study includes a number of examples, comparisons, surveys, useful comments and conclusions.

This thesis describes the application of a wide variety of data processing methods, in particular the Maximum Entropy Method (MEM), to data from Nuclear Magnetic Resonance (NMR) experiments. Chapter 1 provides a brief introduction to NMR and to data processing, which is developed in chapter 2. NMR is described in terms of the classical model due to Bloch, and the principles of conventional (Fourier transform) data processing developed. This is followed by a description of less conventional techniques. The MEM is derived on several grounds, and related to both Bayesian reasoning and Shannon information theory. Chapter 3 describes several methods of evaluating the quality of NMR spectra obtained by a variety of data processing techniques; the simple criterion of spectral appearance is shown to be completely unsatisfactory. A Monte Carlo method is described which allows several different techniques to be compared, and the relative advantages of Fourier transformation and the MEM are assessed. Chapter 4 describes in vivo NMR, particularly the application of the MEM to data from Phase Modulated Rotating Frame Imaging (PMRFI) experiments. In this case the conventional data processing is highly unsatisfactory, and MEM processing results in much clearer spectra. Chapter 5 describes the application of a range of techniques to the estimation and removal of splittings from NMR spectra. The various techniques are discussed using simple examples, and then applied to data from the amino acid iso-leucine. The thesis ends with five appendices which contain historical and philosophical notes, detailed calculations pertaining to PMRFI spectra, and a listing of the MEM computer program.

There has been in the past and still is controversy over the genesis of the third heart sound (S3). Recent studies, strongly suggest that S3 is a manifestation of a sudden intrinsic limitation in the expansion of the left ventricle. The thesis has aimed to explore that hypothesis further using combined echocardiographic and spectral analysis techniques. Spectral analysis was carried out via conventional fast fourier transform methods and the maximum entropy method. The efficacy of these techniques, in relation to clinical and scientific application, was explored further. Briefly discussed was the application of autoregressive-moving average (ARMA) modelling for spectral analysis of S3, in relation to further work. Following is a brief synopsis of the thesis: CHAPTER 1 This gives an historical and general introduction to heart sound analysis. Discussed briefly is the physiology of the heart and heart sounds and the diagnostic implications of S3 analysis. CHAPTER 2 Here is discussed the instrumentation system used and phonocardiographic and echocardiographic data aquisition. Data preprocessing and storage is also covered. CHAPTER 3 In this chapter the application of a FFT method and correlation of resultant spectral parameters with echocardiographic parameters is reported. CHAPTER 4 The theoretical development of the maximum entropy technique (based on published papers and expanded) is discussed here. Numerical experiments with the method and associated problems are also discussed. CHAPTER 5 The MEM is applied to the spectral analysis of S3 and compared with the FFT method. Correlation analysis of MEM derived spectral parameters with echocardiograhic data is performed. CHAPTER 6 Here ARMA modelling and application to further work is discussed. An ARMA model from the maxixum entropy coefficients is derived. The application of this model to the deconvolution of the chest wall transfer function is discussed as an approach for further work. / Thesis (M.Sc.)--School of Mathematical Sciences, 1989.

Thesis (Ph. D.)--Ohio State University, 2008. / Title from first page of PDF file. Includes bibliographical references (p. 140-150).

Thesis (M.Phil.) - University of St Andrews, April 2008.

A produção de alimentos no mundo está condicionada à oferta e ao consumo de fertilizantes inorgânicos, obtidos de fontes naturais não renováveis. Existe um limite entrópico para o atendimento das necessidades crescentes de alimentos. A sustentabilidade da dinâmica dos sistemas agrícolas dependerá da adequação da produção de alimentos à quantidade de recursos naturais disponíveis. No presente trabalho nós testamos essa sustentabilidade, procurando analisar a eficiência do uso de fertilizantes inorgânicos na produção de soja, um dos alimentos básicos nas cadeias alimentares globais, segundo uma abordagem da bioeconomia fundamentada na termodinâmica. Com base nos dados de produção e área cultivada de soja no Brasil, como disponibilizados pelo Instituto Brasileiro de Geografia e Estatística (IBGE), desenvolveu-se um modelo analítico baseado em programação matemática e no princípio de máxima entropia para estimar o uso de fertilizantes por extrato de área cultivada, bem como os respectivos custos totais de produção. Neste trabalho estimou-se a eficiência termodinâmica do uso de fertilizantes e a eficiência econômica da produção de soja nos diferentes extratos de área de produção. Para avaliar essas eficiências utilizou-se um conceito de retorno constante de produtividade da terra (RCP). Esse indicador define o rendimento relativo por hectare da produção de soja nos diferentes extratos de área. Assim, analisando o caso da produção de soja brasileira, verificou-se que no ano de 2008 o aumento de preços das matérias-primas para produzir fertilizantes levou a uma queda no seu respectivo consumo global. A partir dessa observação, procurou-se identificar os fundamentos da tomada de decisão do produtor de soja relativa ao emprego dos fertilizantes no Brasil. Verificou-se que o produtor de soja brasileiro decide as quantidades de fertilizantes que vai empregar, baseando-se na expectativa do lucro da respectiva safra. Os resultados apontam que essa decisão leva a um emprego ineficiente de fertilizantes inorgânicos entre os diferentes extratos de área, principalmente nos extratos inferiores a 20 hectares, em relação a produtores com área superior a 2500 hectares. Essa ineficiência relativa se dá devido ao fato de que, embora a taxa de aplicação de fertilizantes por hectare apresente diferenças pouco significativas entre os extratos de área, as respectivas produtividades são evidentemente distintas. A produtividade da terra em soja é menor nos extratos até 20 hectares, quando comparada à produtividade nos extratos superiores, ocorrendo casos em que essa diferença venha a ser até de duas toneladas de soja por hectare. No período de 1975 a 2011, anos selecionados para este estudo, outros extratos menores, mas superiores a 20 hectares, também apresentaram menor eficiência em relação ao uso de fertilizantes em comparação aos extratos superiores a 2500 hectares. Em relação à respectiva eficiência econômica, verificou-se que os custos de fertilizantes por tonelada de soja são similares entre os extratos, sugerindo-se uma homogeneidade em termos de estrutura de comercialização dos fertilizantes, o que acaba por impactar na lucratividade relativa da produção de soja. Os custos totais de produção refletem também a estrutura tecnológica adotada em cada extrato de área. Ao utilizar-se o conceito de RCP, verifica-se que extratos abaixo de 500 hectares possuem uma menor eficiência econômica quando comparadas com os extratos acima de 2500 hectares. Esses resultados indicam a necessidade de uma escala mínima de produção para o produtor manter-se competitivo do ponto de vista econômico. Desses resultados, e aproveitando-se a modelagem desenvolvida por este estudo, foram derivados alguns cenários pertinentes ao cultivo de soja no Brasil, relativos à produção, área, produtividade e uso de fertilizantes, bem como os custos de produção associados. O modelo desenvolvido para estimar as quantidades de fertilizantes inorgânicos utilizados pelos diferentes extratos de área, relativos à produção de soja, tem como principal característica oferecer a possibilidade de testar-se hipóteses sobre produção, área, produtividade e uso de fertilizantes. Esse modelo pode ser uma ferramenta de apoio à decisão, tanto para gestores de investimentos públicos na agricultura, quanto para a gestão nas unidades de produção agrícola. Os resultados deste presente trabalho sugerem que na produção de soja brasileira o uso de fertilizantes inorgânicos está desconectado de determinantes tecnológicos agronômicos, assim como está dissociado de questões relativas à segurança alimentar ou da sustentabilidade ambiental. Isso porque a tomada de decisão sobre o uso de fertilizantes inorgânicos na agricultura ignora a termodinâmica do processo produtivo como um todo. Para que a produção de soja no Brasil seja efetivamente eficiente e sustentável, do ponto de vista bioeconômico, ou seja, integrador das dimensões econômica, agronômica e termodinâmica, é necessário levar-se em consideração de que são imprescindíveis extratos de produção agrícola de áreas superiores, que contenham uma certa área mínima para a produção de soja, e que se redesenhe com propriedade as tecnologias empregadas nos seus respectivos sistemas de produção, levando-se em conta o limite entrópico da disponibilidade de fertilizantes inorgânicos no mundo. / Food production worldwide is conditioned to supply and consumption of inorganic fertilizers that are obtained from nonrenewable natural sources. The satisfaction of the increasing food needs is limited by an entropic threshold. Therefore, sustainability of the agricultural systems’ dynamics will depend on the adequacy of food production to the amount of available natural resources. In this paper, we examine such sustainability, seeking to analyze the efficiency of the inorganic fertilizers’ use in the production of soybean, one of the basic foods from the global food chain, according to a bioeconomic approach grounded on thermodynamics. Based on data on the soybean production and cultivated areas in Brazil, made available by the Brazilian Institute of Geography and Statistics (IGBE, from the Brazilian Portuguese: “Instituto Brasileiro de Geografia e Estatística”), we have developed an analytical model, which is based on mathematical programing and on the generalized maximum entropy principle, to estimate the use of fertilizers per level of cultivated land, as well as its full production costs. In this paper, we have estimated the efficiency of thermodynamics regarding the use of fertilizers and the economical efficiency of soybean production in different levels of cultivated land. To evaluate such efficiencies, a concept of constant return on land productivity (RCP, from the Brazilian Portuguese: “Retorno Constante de Produtividade”) has been used. This indicator defines the yield per hectare of soybean production in different levels of cultivated land. Thus, analyzing the case of Brazilian soybean production, it’s been asserted that during 2008 the increased price of raw materials used to produce fertilizers lead to a decline in its global consumption. From that observation, we have sought to identify the reasons behind soybean producers’ decision-making regarding the use of fertilizers in Brazil. We’ve discovered that Brazilian soybean producers decide on the amount of fertilizers they will use based on the expectations of profit regarding that particular crop. Results indicate that such decision leads to an inefficient use of inorganic fertilizers per different levels of cultivated land, mainly on portions lower than 20 hectares, from producers holding a field over 2500 hectares. Such relative inefficiency occurs due to the fact that, although the fertilizer’s usage rate per hectare shows little significant differences between producers, their yields are clearly distinct. The soil productivity of soybean is lower in portions up to 20 hectares in comparison to productivity on higher levels of cultivated land and there are instances where such difference is up to two tons of soybean per hectare. From 1975 to 2011, the period selected for this particular study, other smaller levels of cultivated land which were higher than 20 hectares, also evidenced a lower efficiency with regard to the use of fertilizers in comparison to levels higher than 2500 hectares. Regarding their economic efficiency, evidence showed that the costs of fertilizers per ton are similar between levels of cultivated land, suggesting homogeneity in terms of the fertilizers trading structure, resulting in an impact on the relative yielding of soybean production. Total production costs also reflect the technological structure adopted in each level of cultivated land. By applying the concept of RCP, it’s been ascertained that levels lower than 500 hectares have a lower economic efficiency when compared to levels higher than 2500 hectares. Such results indicate the need for a minimal production scale in order for the producer to keep their competitiveness, from an economic perspective. From these results, and taking advantage of the modeling developed for this study, some sceneries pertaining the soybean culture in Brazil have been derived that relate to production, area, yield, and use of fertilizers, as well as related production costs. The model developed to estimate the amounts of inorganic fertilizers used in soybean production, in different levels of cultivated land, holds as its main feature the fact that it allows for the testing of hypothesis on production, area, yield, and use of fertilizers. Such a model can be used as a decision-making supporting tool, both for public agricultural investment managers and for managing the agricultural production units (farms). This paper’s results suggest that, in Brazilian soybean production, the use of inorganic fertilizers is disconnected from agronomic technological determiners and dissociated from food safety and environmental sustainability issues. That happens because decision-making on agricultural use of fertilizers overlooks the thermodynamics of the productive process as a whole. In order for the soybean production in Brazil to be effectively efficient and sustainable, from the bioeconomic point of view, i.e., integrating the economic, agricultural, and thermodynamic dimensions, it is necessary to consider that they are fundamental portions of agricultural production in bigger areas, which contain a minimal area for the production of soybean, and to properly redesign the technologies applied in their production systems, taking into account the entropic threshold of availability of inorganic fertilizers in the world.

A produção de alimentos no mundo está condicionada à oferta e ao consumo de fertilizantes inorgânicos, obtidos de fontes naturais não renováveis. Existe um limite entrópico para o atendimento das necessidades crescentes de alimentos. A sustentabilidade da dinâmica dos sistemas agrícolas dependerá da adequação da produção de alimentos à quantidade de recursos naturais disponíveis. No presente trabalho nós testamos essa sustentabilidade, procurando analisar a eficiência do uso de fertilizantes inorgânicos na produção de soja, um dos alimentos básicos nas cadeias alimentares globais, segundo uma abordagem da bioeconomia fundamentada na termodinâmica. Com base nos dados de produção e área cultivada de soja no Brasil, como disponibilizados pelo Instituto Brasileiro de Geografia e Estatística (IBGE), desenvolveu-se um modelo analítico baseado em programação matemática e no princípio de máxima entropia para estimar o uso de fertilizantes por extrato de área cultivada, bem como os respectivos custos totais de produção. Neste trabalho estimou-se a eficiência termodinâmica do uso de fertilizantes e a eficiência econômica da produção de soja nos diferentes extratos de área de produção. Para avaliar essas eficiências utilizou-se um conceito de retorno constante de produtividade da terra (RCP). Esse indicador define o rendimento relativo por hectare da produção de soja nos diferentes extratos de área. Assim, analisando o caso da produção de soja brasileira, verificou-se que no ano de 2008 o aumento de preços das matérias-primas para produzir fertilizantes levou a uma queda no seu respectivo consumo global. A partir dessa observação, procurou-se identificar os fundamentos da tomada de decisão do produtor de soja relativa ao emprego dos fertilizantes no Brasil. Verificou-se que o produtor de soja brasileiro decide as quantidades de fertilizantes que vai empregar, baseando-se na expectativa do lucro da respectiva safra. Os resultados apontam que essa decisão leva a um emprego ineficiente de fertilizantes inorgânicos entre os diferentes extratos de área, principalmente nos extratos inferiores a 20 hectares, em relação a produtores com área superior a 2500 hectares. Essa ineficiência relativa se dá devido ao fato de que, embora a taxa de aplicação de fertilizantes por hectare apresente diferenças pouco significativas entre os extratos de área, as respectivas produtividades são evidentemente distintas. A produtividade da terra em soja é menor nos extratos até 20 hectares, quando comparada à produtividade nos extratos superiores, ocorrendo casos em que essa diferença venha a ser até de duas toneladas de soja por hectare. No período de 1975 a 2011, anos selecionados para este estudo, outros extratos menores, mas superiores a 20 hectares, também apresentaram menor eficiência em relação ao uso de fertilizantes em comparação aos extratos superiores a 2500 hectares. Em relação à respectiva eficiência econômica, verificou-se que os custos de fertilizantes por tonelada de soja são similares entre os extratos, sugerindo-se uma homogeneidade em termos de estrutura de comercialização dos fertilizantes, o que acaba por impactar na lucratividade relativa da produção de soja. Os custos totais de produção refletem também a estrutura tecnológica adotada em cada extrato de área. Ao utilizar-se o conceito de RCP, verifica-se que extratos abaixo de 500 hectares possuem uma menor eficiência econômica quando comparadas com os extratos acima de 2500 hectares. Esses resultados indicam a necessidade de uma escala mínima de produção para o produtor manter-se competitivo do ponto de vista econômico. Desses resultados, e aproveitando-se a modelagem desenvolvida por este estudo, foram derivados alguns cenários pertinentes ao cultivo de soja no Brasil, relativos à produção, área, produtividade e uso de fertilizantes, bem como os custos de produção associados. O modelo desenvolvido para estimar as quantidades de fertilizantes inorgânicos utilizados pelos diferentes extratos de área, relativos à produção de soja, tem como principal característica oferecer a possibilidade de testar-se hipóteses sobre produção, área, produtividade e uso de fertilizantes. Esse modelo pode ser uma ferramenta de apoio à decisão, tanto para gestores de investimentos públicos na agricultura, quanto para a gestão nas unidades de produção agrícola. Os resultados deste presente trabalho sugerem que na produção de soja brasileira o uso de fertilizantes inorgânicos está desconectado de determinantes tecnológicos agronômicos, assim como está dissociado de questões relativas à segurança alimentar ou da sustentabilidade ambiental. Isso porque a tomada de decisão sobre o uso de fertilizantes inorgânicos na agricultura ignora a termodinâmica do processo produtivo como um todo. Para que a produção de soja no Brasil seja efetivamente eficiente e sustentável, do ponto de vista bioeconômico, ou seja, integrador das dimensões econômica, agronômica e termodinâmica, é necessário levar-se em consideração de que são imprescindíveis extratos de produção agrícola de áreas superiores, que contenham uma certa área mínima para a produção de soja, e que se redesenhe com propriedade as tecnologias empregadas nos seus respectivos sistemas de produção, levando-se em conta o limite entrópico da disponibilidade de fertilizantes inorgânicos no mundo. / Food production worldwide is conditioned to supply and consumption of inorganic fertilizers that are obtained from nonrenewable natural sources. The satisfaction of the increasing food needs is limited by an entropic threshold. Therefore, sustainability of the agricultural systems’ dynamics will depend on the adequacy of food production to the amount of available natural resources. In this paper, we examine such sustainability, seeking to analyze the efficiency of the inorganic fertilizers’ use in the production of soybean, one of the basic foods from the global food chain, according to a bioeconomic approach grounded on thermodynamics. Based on data on the soybean production and cultivated areas in Brazil, made available by the Brazilian Institute of Geography and Statistics (IGBE, from the Brazilian Portuguese: “Instituto Brasileiro de Geografia e Estatística”), we have developed an analytical model, which is based on mathematical programing and on the generalized maximum entropy principle, to estimate the use of fertilizers per level of cultivated land, as well as its full production costs. In this paper, we have estimated the efficiency of thermodynamics regarding the use of fertilizers and the economical efficiency of soybean production in different levels of cultivated land. To evaluate such efficiencies, a concept of constant return on land productivity (RCP, from the Brazilian Portuguese: “Retorno Constante de Produtividade”) has been used. This indicator defines the yield per hectare of soybean production in different levels of cultivated land. Thus, analyzing the case of Brazilian soybean production, it’s been asserted that during 2008 the increased price of raw materials used to produce fertilizers lead to a decline in its global consumption. From that observation, we have sought to identify the reasons behind soybean producers’ decision-making regarding the use of fertilizers in Brazil. We’ve discovered that Brazilian soybean producers decide on the amount of fertilizers they will use based on the expectations of profit regarding that particular crop. Results indicate that such decision leads to an inefficient use of inorganic fertilizers per different levels of cultivated land, mainly on portions lower than 20 hectares, from producers holding a field over 2500 hectares. Such relative inefficiency occurs due to the fact that, although the fertilizer’s usage rate per hectare shows little significant differences between producers, their yields are clearly distinct. The soil productivity of soybean is lower in portions up to 20 hectares in comparison to productivity on higher levels of cultivated land and there are instances where such difference is up to two tons of soybean per hectare. From 1975 to 2011, the period selected for this particular study, other smaller levels of cultivated land which were higher than 20 hectares, also evidenced a lower efficiency with regard to the use of fertilizers in comparison to levels higher than 2500 hectares. Regarding their economic efficiency, evidence showed that the costs of fertilizers per ton are similar between levels of cultivated land, suggesting homogeneity in terms of the fertilizers trading structure, resulting in an impact on the relative yielding of soybean production. Total production costs also reflect the technological structure adopted in each level of cultivated land. By applying the concept of RCP, it’s been ascertained that levels lower than 500 hectares have a lower economic efficiency when compared to levels higher than 2500 hectares. Such results indicate the need for a minimal production scale in order for the producer to keep their competitiveness, from an economic perspective. From these results, and taking advantage of the modeling developed for this study, some sceneries pertaining the soybean culture in Brazil have been derived that relate to production, area, yield, and use of fertilizers, as well as related production costs. The model developed to estimate the amounts of inorganic fertilizers used in soybean production, in different levels of cultivated land, holds as its main feature the fact that it allows for the testing of hypothesis on production, area, yield, and use of fertilizers. Such a model can be used as a decision-making supporting tool, both for public agricultural investment managers and for managing the agricultural production units (farms). This paper’s results suggest that, in Brazilian soybean production, the use of inorganic fertilizers is disconnected from agronomic technological determiners and dissociated from food safety and environmental sustainability issues. That happens because decision-making on agricultural use of fertilizers overlooks the thermodynamics of the productive process as a whole. In order for the soybean production in Brazil to be effectively efficient and sustainable, from the bioeconomic point of view, i.e., integrating the economic, agricultural, and thermodynamic dimensions, it is necessary to consider that they are fundamental portions of agricultural production in bigger areas, which contain a minimal area for the production of soybean, and to properly redesign the technologies applied in their production systems, taking into account the entropic threshold of availability of inorganic fertilizers in the world.