Assessing impacts of Common Agricultural Policy changes on regional use patterns with a decision support system. An application in Southern Portugal

This paper discusses research aiming at assessing Common Agricultural Policy impacts on agriculture and forestry. For this purpose an approach is developed that includes a linear programming model to estimate the Positive Mathematical Programming production cost function coefficients of current agricultural– forestry activities. It further includes a heuristic — simulated annealing — to generate solutions for each policy scenario. This model base approach is integrated within a decision support system (DSS) for testing purposes. The DSS further encompasses a relational database that stores agricultural–forestry technical and economic data and a geographic information system that stores topological data of regional farm-type land units. The DSS Graphical User Interface provides tabular and geographical reporting capabilities. Results are discussed for an application to the Alentejo region in Southern Portugal. Results demonstrate the usefulness and relevance of the proposed approach to assess the impact of changes in prices and in agricultural policy on land use patterns and on forestr

Generate disaggregated soil allocation data using a minimum cross entropy model

Montado ecosystem in the Alentejo Region, south of Portugal, has enormous agro-ecological and economics heterogeneities. A definition of homogeneous sub-units among this heterogeneous ecosystem was made, but for them is disposal only partial statistical information about soil allocation agro-forestry activities. The paper proposal is to recover the unknown soil allocation at each homogeneous sub-unit, disaggregating a complete data set for the Montado ecosystem area using incomplete information at sub-units level. The methodological framework is based on a Generalized Maximum Entropy approach, which is developed in thee steps concerning the specification of a r order Markov process, the estimates of aggregate transition probabilities and the disaggregation data to recover the unknown soil allocation at each homogeneous sub-units. The results quality is evaluated using the predicted absolute deviation (PAD) and the “Disagegation Information Gain” (DIG) and shows very acceptable estimation errors

Enhanced thermo-spin effects in iron-oxide/metal multilayers

Since the discovery of the spin Seebeck effect (SSE), much attention has been devoted to the study of the interaction between heat, spin, and charge in magnetic systems. The SSE refers to the generation of a spin current upon the application of a thermal gradient and detected by means of the inverse spin Hall effect. Conversely, the spin Peltier effect (SPE) refers to the generation of a heat current as a result of a spin current induced by the spin Hall effect. Here we report a strong enhancement of both the SSE and SPE in Fe3O4/Pt multilayered thin films at room temperature as a result of an increased thermo-spin conversion efficiency in the multilayers. These results open the possibility to design thin film heterostructures that may boost the application of thermal spin currents in spintronics

A New Type of Supramolecular Fluid Based on H₂O-Alkylammonium/Phosphonium Solutions

Here we show that by adjusting the concentration of tetrabutyl ammonium and phosphonium salts in water (approximate to 1.5-2.0 m), hydrophobic solvation triggers the formation of a unique, highly incompressible supramolecular liquid, with a dynamic structure similar to clathrates, involving essentially all H2O molecules of the solvent. Despite the increasing local order, the thermal diffusivity, and compressibility of these supramolecular liquids is strongly decreased with respect to bulk water due to slower relaxation dynamics. The results presented in this paper open an avenue to design a new family of supramolecular fluids, stable under atmospheric conditions, which can find important technological applications in energy storage and conversion

Temperature dependence of the spin Seebeck effect in [Fe3O4/Pt]n multilayers

We report temperature dependent measurements of the spin Seebeck effect (SSE) in multilayers formed by repeated growth of a Fe3O4/Pt bilayer junction. The magnitude of the observed enhancement of the SSE, relative to the SSE in the single bilayer, shows a monotonic increase with decreasing the temperature. This result can be understood by an increase of the characteristic length for spin current transport in the system, in qualitative agreement with the recently observed increase in the magnon diffusion length in Fe3O4 at lower temperatures. Our result suggests that the thermoelectric performance of the SSE in multilayer structures can be further improved by careful choice of materials with suitable spin transport properties

Spin Seebeck effect in insulating epitaxial ¿-Fe2O3 thin films

We report the fabrication of high crystal quality epitaxial thin films of maghemite (¿-Fe2O3), a classic ferrimagnetic insulating iron oxide. Spin Seebeck effect (SSE) measurements in ¿-Fe2O3/Pt bilayers as a function of sample preparation conditions and temperature yield a SSE coefficient of 0.5(1) µV/K at room temperature. Dependence on temperature allows us to estimate the magnon diffusion length in maghemite to be in the range of tens of nanometers, in good agreement with that of conducting iron oxide magnetite (Fe3O4), establishing the relevance of spin currents of magnonic origin in magnetic iron oxides

SpectraNet–53: A deep residual learning architecture for predicting soluble solids content with VIS–NIR spectroscopy

This work presents a new deep learning architecture, SpectraNet-53, for quantitative analysis of fruit spectra, optimized for predicting Soluble Solids Content (SSC, in Brix). The novelty of this approach resides in being an architecture trainable on a very small dataset, while keeping a performance level on-par or above Partial Least Squares (PLS), a time-proven machine learning method in the field of spectroscopy. SpectraNet-53 performance is assessed by determining the SSC of 616 Citrus sinensi L. Osbeck 'Newhall' oranges, from two Algarve (Portugal) orchards, spanning two consecutive years, and under different edaphoclimatic conditions. This dataset consists of short-wave near-infrared spectroscopic (SW-NIRS) data, and was acquired with a portable spectrometer, in the visible to near infrared region, on-tree and without temperature equalization. SpectraNet-53 results are compared to a similar state-of-the-art architecture, DeepSpectra, as well as PLS, and thoroughly assessed on 15 internal validation sets (where the training and test data were sampled from the same orchard or year) and on 28 external validation sets (training/test data sampled from different orchards/years). SpectraNet-53 was able to achieve better performance than DeepSpectra and PLS in several metrics, and is especially robust to training overfit. For external validation results, on average, SpectraNet-53 was 3.1% better than PLS on RMSEP (1.16 vs. 1.20 Brix), 11.6% better in SDR (1.22 vs. 1.10), and 28.0% better in R2 (0.40 vs. 0.31).project NIBAP ALG-01-0247-FEDER-037303, project OtiCalFrut ALG-010247-FEDER-033652info:eu-repo/semantics/publishedVersio