Chickpeas from a Chilean Region Affected by a Climate-Related Catastrophe: Effects of Water Stress on Grain Yield and Flavonoid Composition

The Valparaiso region in Chile was decreed a zone affected by catastrophe in 2019 as a consequence of one of the driest seasons of the last 50 years. In this study, three varieties (‘Alfa-INIA’, ‘California-INIA’, and one landrace, ‘Local Navidad’) of kabuli-type chickpea seeds produced in 2018 (control) and 2019 (climate-related catastrophe, hereafter named water stress) were evaluated for their grain yield. Furthermore, the flavonoid profile of both free and esterified phenolic extracts was determined using liquid chromatography-mass spectrometry, and the concentration of the main flavonoid, biochanin A, was determined using liquid chromatography with diode array detection. The grain yield was decreased by up to 25 times in 2019. The concentration of biochanin A was up to 3.2 times higher in samples from the second season (water stress). This study demonstrates that water stress induces biosynthesis of biochanin A. However, positive changes in the biochanin A concentration are overshadowed by negative changes in the grain yield. Therefore, water stress, which may be worsened by climate change in the upcoming years, may jeopardize both the production of chickpeas and the supply of biochanin A, a bioactive compound that can be used to produce dietary supplements and/or nutraceuticals.     

Code2vect: An efficient heterogenous data classifier and nonlinear regression technique

The aim of this paper is to present a new classification and regression algorithm based on Artificial Intelligence. The main feature of this algorithm, which will be called Code2Vect, is the nature of the data to treat: qualitative or quantitative and continuous or discrete. Contrary to other artificial intelligence techniques based on the “Big-Data,” this new approach will enable working with a reduced amount of data, within the so-called “Smart Data” paradigm. Moreover, the main purpose of this algorithm is to enable the representation of high-dimensional data and more specifically grouping and visualizing this data according to a given target. For that purpose, the data will be projected into a vectorial space equipped with an appropriate metric, able to group data according to their affinity (with respect to a given output of interest). Furthermore, another application of this algorithm lies on its prediction capability. As it occurs with most common data-mining techniques such as regression trees, by giving an input the output will be inferred, in this case considering the nature of the data formerly described. In order to illustrate its potentialities, two different applications will be addressed, one concerning the representation of high-dimensional and categorical data and another featuring the prediction capabilities of the algorithm.     

Neutral nido-heteroboranes with non ionisable hydrogen as arenes in coordination

Designed ligands have been synthesised to produce the first arene-like metallacarborane. For arene-like coordination the number of electronegative elements on the coordinating site must be kept to a minimum. Choosing ligands with bulky substituents on the heteroatom allows easy rearrangement and arene-like coordination. This is more hampered the higher the number of hetereoatoms to be re-located.     

Scattering of a relativistic scalar particle by a cusp potential

We solve the Klein–Gordon equation in the presence of a spatially one-dimensional cusp potential. The scattering solutions are obtained in terms of Whittaker functions and the condition for the existence of transmission resonances is derived. We show the dependence of the zero-reflection condition on the shape of the potential. In the low-momentum limit, transmission resonances are associated with half-bound states. We express the condition for transmission resonances in terms of the phase shifts.     

A procedure for the evaluation of vibrations induced by the passing of a train and its application to real railway traffic

In recent years, ground vibrations have become an important issue due to the growing awareness of the society about environmental living conditions. In this way, vibrations caused by trains running near houses or workplaces are considered disturbing for residents. Within this framework, this paper presents a procedure to estimate the vibration path caused by the passing of a train. In order to achieve this, the equations which describe the physical phenomenon are set in the frequency and wavenumber domain and solved by using the Fourier Transform. The obtained analytical solution is transformed back into the time and space domain by means of the Fourier series. The obtained theoretical results are compared with experimental measurements carried out in the Madrid–Barcelona High Speed Line in order to analyse the performance of this procedure.     

Synthesis of core‐shell structured carboxylated microparticles with a straightforward procedure and their evaluation as a polymer support

Poly(trimethylolpropane trimethacrylate) microspheres with a narrow size distribution were obtained by precipitation polymerization. They were subsequently modified by surface grafting with acrylic acid in a polar ethanol–water reaction medium, without stabilizer, yielding core‐shell particles with diameters in the micrometer range. The resulting polymeric material was characterized by SEM and potentiometric titration, FTIR spectroscopy, and thermal analysis. It was shown that the particle characteristics (size, size distribution, and functionality) obtained by this straightforward procedure can be controlled by modifying the synthesis parameters (monomer concentration, agitation rate, and temperature). The high functionality, the chemical and physico‐mechanical stability, as well as the possibility to control the performances of the resulting polymeric materials by synthesis allow its applications in various areas. Envisaging separation and catalysis domains, Cu(II), Cd(II), and Cr(III) uptake capacity from aqueous solutions was investigated under noncompetitive conditions as a function of synthesized particle functionality, time, and pH range. It was also found that the addition of the carboxylated microparticles to polyethylene stabilized with α‐tocopherol improved the thermo‐oxidative behaviour of the polymeric material. © 2005 Wiley Periodicals, Inc. J Polym Sci Part A: Polym Chem 43: 5889–5898, 2005     

An algorithm for ordinal sorting based on ELECTRE with categories defined by examples

This work proposes a Progressive Assisted Sorting Algorithm (PASA) based on a multicriteria evaluation ELECTRE-type method. The purpose of the PASA is to aid a decision maker to progressively sort a set of alternatives into a set of categories, which we considered are ordered (ordinal sorting), following a consistency principle. We consider the principle that if an alternative outranks (is as good as) a second one, then it must belong to the same category or to a better category. The set of alternatives already sorted by the decision maker will implicitly define the categories, and will constrain the range of categories where other alternatives may be sorted. We show how the same idea may be used in an aggregation/disaggregation approach, considering some parameters of ELECTRE are not fixed a priori, but are constrained only by the examples provided. In this context, we establish a “convex-shape property” stating that the range of possible categories for an alternative is always an interval of categories. A discussion contrasting this approach with ELECTRE TRI is included in the conclusions.