Guideline for constructing nutrient balance in historical agricultural systemes (and its application to three case-studies in southern Spain)

The purpose of this paper is to provide interested researchers with a simple tool to evaluate the efficacy of different methods of fertility replenishment that have accompanied and made possible the contemporary agriculture. We propose a nutrient balance model created especially to be applied to the past. In the first part of this working paper each term in the balance is defined and specified the information the user must input into the model. The second part of this paper reports on the application of this methodology based on the balances of nutrients to the evolution of Andalusian agriculture since the mid 18th Century. The nutrient balances show the effects of agrarian growth in an environmentally limited context, offering reasonable doubt regarding the medium and long-term stability of certain forms of cultivation. The balances show that in the last decades of the 19th Century, productive intensification had reached its ceiling, with livestock numbers levelling off or clearly declining. The deficits of nutrients even began to exceed the fertilisation capacity of the available livestock. The intensification applied in unfertilised rotations and crops had to be sustained through the extraction of soil reserves.Soil fertility management, Nutrient balances, Past organic agricultures, Agrarian growth, Socio-ecological transition, Agricultural change

Decentralized and collaborative machine learning framework for IoT

Decentralized machine learning has recently been proposed as a potential solution to the security issues of the canonical federated learning approach. In this paper, we propose a decentralized and collaborative machine learning framework specially oriented to resource-constrained devices, usual in IoT deployments. With this aim we propose the following construction blocks. First, an incremental learning algorithm based on prototypes that was specifically implemented to work in low-performance computing elements. Second, two random-based protocols to exchange the local models among the computing elements in the network. Finally, two algorithmics approaches for prediction and prototype creation. This proposal was compared to a typical centralized incremental learning approach in terms of accuracy, training time and robustness with very promising results.Axencia Galega de Innovación | Ref. 25/IN606D/2021/2612348Agencia Estatal de Investigación | Ref. PID2020-113795RB-C3

Experimental Study on 164 Algorithms Available in Software Tools for Solving Standard Non-Linear Regression Problems

In the specialized literature, researchers can find a large number of proposals for solving regression problems that come from different research areas. However, researchers tend to use only proposals from the area in which they are experts. This paper analyses the performance of a large number of the available regression algorithms from some of the most known and widely used software tools in order to help non-expert users from other areas to properly solve their own regression problems and to help specialized researchers developing well-founded future proposals by properly comparing and identifying algorithms that will enable them to focus on significant further developments. To sum up, we have analyzed 164 algorithms that come from 14 main different families available in 6 software tools (Neural Networks, Support Vector Machines, Regression Trees, Rule-Based Methods, Stacking, Random Forests, Model trees, Generalized Linear Models, Nearest Neighbor methods, Partial Least Squares and Principal Component Regression, Multivariate Adaptive Regression Splines, Bagging, Boosting, and other methods) over 52 datasets. A new measure has also been proposed to show the goodness of each algorithm with respect to the others. Finally, a statistical analysis by non-parametric tests has been carried out over all the algorithms and on the best 30 algorithms, both with and without bagging. Results show that the algorithms from Random Forest, Model Tree and Support Vector Machine families get the best positions in the rankings obtained by the statistical tests when bagging is not considered. In addition, the use of bagging techniques significantly improves the performance of the algorithms without excessive increase in computational times.This work was supported in part by the University of Córdoba under the project PPG2019-UCOSOCIAL-03, and in part by the Spanish Ministry of Science, Innovation and Universities under Grant TIN2015- 68454-R and Grant TIN2017-89517-P

«El Pacto Andaluz por la Naturaleza» (1985). La confluencia del movimiento campesino y el movimiento ecologista.

En los últimos años se ha desarrollado un importante debate en la Historia Ambiental acerca de lar elación entre campesinado y ecologismo, especialmente a partir de la propuesta de Guha y Martínez Alier (1997) de un Ecologismo Popular y de las críticas al mismo. En este artículo pretendemos profundizar en estas ideas a partir del análisis de la gestación y desarrollo de una de las primeras iniciativas del movimiento ecologista en España, e lPacto Andaluz por la Naturaleza, de 1985-1986.Esta iniciativa surgió de la confluencia de numerosas organizaciones ecologistas con el movimiento jornalero que representaba el Sindicato de Obreros del Campo (SOC) en la defensa de una gestión sostenible del bosque. Estas movilizaciones tuvieron como resultado la aprobación del Plan Forestal Andaluz en 1989 y la introducción, por la vía de la reclamación de mayor empleo, de valores ecologistas que venían a superar las concepciones conservacionistas hasta entonces asociadas con el ambientalismo. Esta es la historia de la confluencia entre un viejo movimiento en vías de extinción, el movimiento jornalero, y un nuevo movimiento social, el ecologista. El resultado es un buen ejemplo de la complejidad y capacidad de transformación del conflicto social.In recent years there has been an intensive debate on the relationship between peasantry and environmentalism in Environmental History. The starting point was the controversial definition of Popular Environmentalism by Ramachandra Guha and Martínez Alier (1997). In the present article we focus on these ideas through the analysis of a specific social movement, the «Andalusian Agreement for Nature» (Pacto Andaluz por la Naturaleza, 1985/1986), one of the first expressions of the Spanish green movement. The interesting feature lies in its origin. This green movement, claiming for a new sustainable use of forests, arose from the confluence of several environmentalist organizations and the traditional Peasant Union (Sindicato de Obreros del Campo). The struggles achieved a new Forest Policy (1989) adopted by the regional government, introducing new ecological values in the population beyond the traditional conservationist conception of environmentalism.This is the history of the confluence of an Old Social Movement, the peasant movement, and a New Social Movement, the green one. We consider this to be a good example for understanding the complexity and the auto‐transformation capacity of the social conflict

JFML: A Java Library to Design Fuzzy Logic Systems According to the IEEE Std 1855-2016

Fuzzy logic systems are useful for solving problems in many application fields. However, these systems are usually stored in specific formats and researchers need to rewrite them to use in new problems. Recently, the IEEE Computational Intelligence Society has sponsored the publication of the IEEE Standard 1855-2016 to provide a unified and well-defined representation of fuzzy systems for problems of classification, regression, and control. The main aim of this standard is to facilitate the exchange of fuzzy systems across different programming systems in order to avoid the need to rewrite available pieces of code or to develop new software tools to replicate functionalities that are already provided by other software. In order to make the standard operative and useful for the research community, this paper presents JFML, an open source Java library that offers a complete implementation of the new IEEE standard and capability to import/export fuzzy systems in accordance with other standards and software. Moreover, the new library has associated a Website with complementary material, documentation, and examples in order to facilitate its use. In this paper, we present three case studies that illustrate the potential of JFML and the advantages of exchanging fuzzy systems among available softwareThis work was supported in part by the XXII Own Research Program (2017) of the University of Córdoba, in part by the Spanish Ministry of Economy and Competitiveness under Grants RYC-2016-19802 (Ramón y Cajal contract), TIN2017-84796-C2-1-R, TIN2014-56633-C3-3-R, TIN2014-57251-P, and TIN2015-68454-R, in part by the Andalusian Government under Grant P11-TIC-7765, in part by the Xunta de Galicia (accreditation 2016-2019), and in part by the European Union (European Regional Development Fund)

Assessment of polluted soil remediation using bacterial community tolerance to heavy metals as an indicator

The assessment of remediation on metal-polluted soils is usually focused on total and/or bioavailable metal content. However, these chemical variables do not provide direct information about reductions in heavy metals pressure on soil microorganisms. We propose the use of bacterial communities to evaluate the efficiency of three remediation techniques: crushed mussel shell (CMS) and pine bark (PB) as soil amendments and EDTA-washing. A soil sample was polluted with different doses of Cu, Ni, and Zn (separately). After 30 days of incubation, the remediation techniques were applied, and bacterial community tolerance to heavy metals determined. If bacterial communities develop tolerance, it is an indicator that the metal is exerting toxicity on them. Soil bacterial communities developed tolerance to Cu, Ni, and Zn in response to metal additions. After remediation, bacterial communities showed decreases in bacterial community tolerance to Cu, Ni, and Zn for all remediation techniques. For Cu and Ni, soil EDTA-washing showed the greatest reduction of bacterial community tolerance to Cu and Ni, respectively, while for Zn the soil amendment with PB was the most effective remediation technique. Thus, bacterial community tolerance to heavy metals successfully detect differences in the effectiveness of the three remediation techniques.Ministerio de Economía y Competitividad | Ref. CTM2015-73422-JINMinisterio de Economía, Industria y Competitividad | Ref. RYC-2016-20411Región de Murcia | Ref. 21525/EE/21Xunta de Galicia | Ref. ED401A-2020/08

Decentralised and collaborative machine learning framework for IoT

Decentralised machine learning has recently been proposed as a potential solution to the security issues of the canonical federated learning approach. In this paper, we propose a decentralised and collaborative machine learning framework specially oriented to resource-constrained devices, usual in IoT deployments. With this aim we propose the following construction blocks. First, an incremental learning algorithm based on prototypes that was specifically implemented to work in low-performance computing elements. Second, two random-based protocols to exchange the local models among the computing elements in the network. Finally, two algorithmics approaches for prediction and prototype creation. This proposal was compared to a typical centralized incremental learning approach in terms of accuracy, training time and robustness with very promising results