Discrete Fourier Transform Improves the Prediction of the Electronic Properties of Molecules in Quantum Machine Learning

High-throughput approximations of quantum mechanics calculations and combinatorial experiments have been traditionally used to reduce the search space of possible molecules, drugs and materials. However, the interplay of structural and chemical degrees of freedom introduces enormous complexity, which the current state-of-the-art tools are not yet designed to handle. The availability of large molecular databases generated by quantum mechanics (QM) computations using first principles open new venues for data science to accelerate the discovery of new compounds. In recent years, models that combine QM with machine learning (ML) known as QM/ML models have been successful at delivering the accuracy of QM at the speed of ML. The goals are to develop a framework that will accelerate the extraction of knowledge and to get insights from quantitative process-structure-property-performance relationships hidden in materials data via a better search of the chemical compound space, and to infer new materials with targeted properties. In this study, we show that by integrating well-known signal processing techniques such as discrete Fourier transform in the QM/ML pipeline, the outcomes can be significantly improved in some cases. We also show that the spectrogram of a molecule may represent an interesting molecular visualization tool.Comment: 4 pages, 3 figures, 2 tables. Accepted to present at 32nd IEEE Canadian Conference in Electrical Engineering and Computer Scienc

La presencia gallega en la historia de la economía cubana

El trabajo aborda de forma sintética la participación e influencia del gallego en el ideario cubano. El objetivo planteado fue analizar desde una perspectiva histórica la influencia gallega en la economía cubana. La metodología empleada fue la realización de un análisis retrospectivo y transversal de la influencia gallega en la vida económica y social de Cuba. Tanto el objetivo planteado como la metodología, unida a otras técnicas de investigación nos permiten plantear como principales resultados, que la presencia gallega llegó a casi todo las ramas de la industria y los servicios de la vida social y económica cubana, con una participación destacada en los sectores tabacalero y servicios (pequeñas bodegas o abastos de venta a la población). Se muestran algunos de los exponentes del sector tabacalero y como muchos de ellos llegaron a transformar esta industria, de los bodegueros se especifica como supieron socializar con su carismático carácter en las zonas donde se radicaban. Se detalla como el gallego luego de obtener una fortuna se vio afectado por las medidas adoptadas por del gobierno revolucionario. Finalmente se concluye que resulta difícil escribir la historia económica, política y social de Cuba sin que en ella no se encuentre inmerso un gallego

The Strategies of Ultranationalist Discourse: This Is England and Brexit

A speech given by the skinhead Combo in the film This is England (2006) provides the ground for an analysis of far-right nationalism. This article uses Critical Discourse Analysis and the idea of the nation as a discursive construct to explain Combo’s strategies to gain dominance over his gang by means of rhetoric, body language, building up an ethos based on Christian and epic mythologies with ethnic connotations, drawing boundaries, and discrediting and excluding his opponents. These strategies are then compared to those of the UKIP leader Nigel Farage in his “Brexit victory” speech delivered in June 2016, which was based on a mystification of territorial boundaries, symbolic allusions to a defensive war, and a verbal construction of an ideally independent nation and a promising future. Thus, the article argues that analysis of a scene from the film set in the Thatcherite Britain of 1983 can still illuminate the articulation of later nationalist discourses

Fuzzy heterogeneous neural networks for signal forecasting

Fuzzy heterogeneous neural networks are recently introduced models based on neurons accepting heterogeneous inputs (i.e. mixtures of numerical and non-numerical information possibly with missing data) with either crisp or imprecise character, which can be coupled with classical neurons. This paper compares the effectiveness of this kind of networks with time-delay and recurrent architectures that use classical neuron models and training algorithms in a signal forecasting problem, in the context of finding models of the central nervous system controllers.Peer ReviewedPostprint (author's final draft

Fuzzy heterogeneous neurons for imprecise classification problems

In the classical neuron model, inputs are continuous real-valued quantities. However, in many important domains from the real world, objects are described by a mixture of continuous and discrete variables, usually containing missing information and uncertainty. In this paper, a general class of neuron models accepting heterogeneous inputs in the form of mixtures of continuous (crisp and/or fuzzy) and discrete quantities admitting missing data is presented. From these, several particular models can be derived as instances and different neural architectures constructed with them. Such models deal in a natural way with problems for which information is imprecise or even missing. Their possibilities in classification and diagnostic problems are here illustrated by experiments with data from a real-world domain in the field of environmental studies. These experiments show that such neurons can both learn and classify complex data very effectively in the presence of uncertain information.Peer ReviewedPostprint (author's final draft

Assessing the influence of global climate and anthropogenic activities on the water balance of an andean lake

ABSTRACT: Tropical regions along the Andean Cordillera face an uncertain future as mountain lakes and snow peaks ex- hibit receding trends associated with factors such as climatic precursors and local anthropogenic activities. Tota, the largest mountain lake in the Colombian Andes, exemplifies the role played by these factors on the lake's hydrologic evolution. A monthly water balance in Tota Lake was performed using available hydro- logical information from 1958 to 2007 to address interannual and multiannual level fluctuations associated with human activities and climatic precursors. The balance shows that net water uses fluctuated around 2 m3/s during this period with a pattern that, although constrained during years of severe decline in lake levels, is able to explain most of the multiannual decaying trend of 1.5 cm/year in the last 50 years. The lake’s naturalized levels were used to determine the influence of climate precursors on the lake evolution. Using Multichannel Singular Spectrum Analysis (M-SSA), significant five-year ENSO and 20-year PDO related quasi-oscillations were detected, explaining 54% of the variance associated with mean annual naturalized level fluctuations. ENSO is markedly in-phase with lake levels, with critical declines associated with low precipitation and high evaporation rates during El Niño years, whereas the PDO signal exhibits a phase op-position with lake levels, with low naturalized levels during a positive PDO phase and high levels during a negative PDO phase (an important result to consider given the current cooling trend of the PDO signal)

Characterization of Quantum Derived Electronic Properties of Molecules: A Computational Intelligence Approach

Series: Lecture Notes in Computer Scienc

The VEX-93 environment as a hybrid tool for developing knowledge systems with different problem solving techniques

The paper describes VEX-93 as a hybrid environment for developing knowledge-based and problem solver systems. It integrates methods and techniques from artificial intelligence, image and signal processing and data analysis, which can be mixed. Two hierarchical levels of reasoning contains an intelligent toolbox with one upper strategic inference engine and four lower ones containing specific reasoning models: truth-functional (rule-based), probabilistic (causal networks), fuzzy (rule-based) and case-based (frames). There are image/signal processing-analysis capabilities in the form of programming languages with more than one hundred primitive functions. User-made programs are embeddable within knowledge basis, allowing the combination of perception and reasoning. The data analyzer toolbox contains a collection of numerical classification, pattern recognition and ordination methods, with neural network tools and a data base query language at inference engines's disposal. VEX-93 is an open system able to communicate with external computer programs relevant to a particular application. Metaknowledge can be used for elaborate conclusions, and man-machine interaction includes, besides windows and graphical interfaces, acceptance of voice commands and production of speech output. The system was conceived for real-world applications in general domains, but an example of a concrete medical diagnostic support system at present under completion as a cuban-spanish project is mentioned. Present version of VEX-93 is a huge system composed by about one and half millions of lines of C code and runs in microcomputers under Windows 3.1.Postprint (published version