Optimal Carbon Taxes for Emissions Targets in the Electricity Sector

The most dangerous effects of anthropogenic climate change can be mitigated by using emissions taxes or other regulatory interventions to reduce greenhouse gas (GHG) emissions. This paper takes a regulatory viewpoint and describes the Weighted Sum Bisection method to determine the lowest emission tax rate that can reduce the anticipated emissions of the power sector below a prescribed, regulatorily-defined target. This bi-level method accounts for a variety of operating conditions via stochastic programming and remains computationally tractable for realistically large planning test systems, even when binary commitment decisions and multi-period constraints on conventional generators are considered. Case studies on a modified ISO New England test system demonstrate that this method reliably finds the minimum tax rate that meets emissions targets. In addition, it investigates the relationship between system investments and the tax-setting process. Introducing GHG emissions taxes increases the value proposition for investment in new cleaner generation, transmission, and energy efficiency; conversely, investing in these technologies reduces the tax rate required to reach a given emissions target

Population Subset Selection for the Use of a Validation Dataset for Overfitting Control in Genetic Programming

[Abstract] Genetic Programming (GP) is a technique which is able to solve different problems through the evolution of mathematical expressions. However, in order to be applied, its tendency to overfit the data is one of its main issues. The use of a validation dataset is a common alternative to prevent overfitting in many Machine Learning (ML) techniques, including GP. But, there is one key point which differentiates GP and other ML techniques: instead of training a single model, GP evolves a population of models. Therefore, the use of the validation dataset has several possibilities because any of those evolved models could be evaluated. This work explores the possibility of using the validation dataset not only on the training-best individual but also in a subset with the training-best individuals of the population. The study has been conducted with 5 well-known databases performing regression or classification tasks. In most of the cases, the results of the study point out to an improvement when the validation dataset is used on a subset of the population instead of only on the training-best individual, which also induces a reduction on the number of nodes and, consequently, a lower complexity on the expressions.Xunta de Galicia; ED431G/01Xunta de Galicia; ED431D 2017/16Xunta de Galicia; ED431C 2018/49Xunta de Galicia; ED431D 2017/23Instituto de Salud Carlos III; PI17/0182

DoME: A Deterministic Technique for Equation Development and Symbolic Regression

Financiado para publicación en acceso aberto: Universidade da Coruña/CISUG[Abstract] Based on a solid mathematical background, this paper proposes a method for Symbolic Regression that enables the extraction of mathematical expressions from a dataset. Contrary to other approaches, such as Genetic Programming, the proposed method is deterministic and, consequently, does not require the creation of a population of initial solutions. Instead, a simple expression is grown until it fits the data. This method has been compared with four well-known Symbolic Regression techniques with a large number of datasets. As a result, on average, the proposed method returns better performance than the other techniques, with the advantage of returning mathematical expressions that can be easily used by different systems. Additionally, this method makes it possible to establish a threshold at the complexity of the expressions generated, i.e., the system can return mathematical expressions that are easily analyzed by the user, as opposed to other techniques that return very large expressions.This study is partially supported by Instituto de Salud Carlos III, grant number PI17/01826 (Collaborative Project in Genomic Data Integration (CICLOGEN) funded by the Instituto de Salud Carlos III from the Spanish National Plan for Scientific and Technical Research and Innovation 2013–2016 and the European Regional Development Funds (FEDER)—“A way to build Europe”. It was also partially supported by different grants and projects from the Xunta de Galicia [ED431D 2017/23; ED431D 2017/16; ED431G/01; ED431C 2018/49; IN845D-2020/03]. The authors thank the CyTED, Spain and each National Organism for Science and Technology for funding the IBEROBDIA project (P918PTE0409). In this regard, Spain specifically thanks the Ministry of Economy and Competitiveness for the financial support for this project through the State Program of I+D+I Oriented to the Challenges of Society 2017–2020 (International Joint Programming 2018), project (PCI2018-093284). Funding for open access charge: Universidade da Coruña/CISUGXunta de Galicia; ED431D 2017/23Xunta de Galicia; ED431D 2017/16Xunta de Galicia; ED431G/01Xunta de Galicia; ED431C 2018/49Xunta de Galicia; IN845D-2020/0

Convolutional Neural Networks for Sleep Stage Scoring on a Two-Channel EEG Signal

This is a pre-print of an article published in Soft Computing. The final authenticated version is available online at: https://doi.org/10.1007/s00500-019-04174-1[Abstract] Sleeping problems have become one of the major diseases all over the world. To tackle this issue, the basic tool used by specialists is the Polysomnogram, which is a collection of different signals recorded during sleep. After its recording, the specialists have to score the different signals according to one of the standard guidelines. This process is carried out manually, which can be highly time consuming and very prone to annotation errors. Therefore, over the years, many approaches have been explored in an attempt to support the specialists in this task. In this paper, an approach based on convolutional neural networks is presented, where an in-depth comparison is performed in order to determine the convenience of using more than one signal simultaneously as input. Additionally, the models were also used as parts of an ensemble model to check whether any useful information can be extracted from signal processing a single signal at a time which the dual-signal model cannot identify. Tests have been performed by using a well-known dataset called expanded sleep-EDF, which is the most commonly used dataset as benchmark for this problem. The tests were carried out with a leave-one-out cross-validation over the patients, which ensures that there is no possible contamination between training and testing. The resulting proposal is a network smaller than previously published ones, but which overcomes the results of any previous models on the same dataset. The best result shows an accuracy of 92.67% and a Cohen’s Kappa value over 0.84 compared to human experts.Instituto de Salud Carlos III; PI17/01826Xunta de Galicia; ED431D 2017/23Xunta de Galicia; ED431D 2017/16Xunta de Galicia; ED431G/0

Procesos de alteración y paleosuelos ligados a la sedimentación miocena del NE. de Segovia, depresión del Duero

Se ha realizado un análisis mineral6gico y micromorfol6gico en la zona de confluencia de las partes distales de los sistemas de abanicos aluviales miocenos procedentes de los relieves de Somosierra- Ayllón, al SE., y de Honrubia, al NO. En él, se constatan diferencias entre los procesos edhficos que afectaron a uno y otro sistema, asi como en los grados de evolución de los perfiles edhficos. Los depósitos procedentes de Honrubia se caracterizan por los frecuentes episodios de  encostramiento, a los que se asocia la presencia de esmectitas o de palygorskita en función del menor o mayor grado evolutivo y del menor o mayor confinamiento. Los depósitos del sistema de abanicos aluviales de Somosierra-Ayllón están, generalmente, menos afectados por las alteraciones edáficos, a consecuencia de la mayor intensidad de los procesos sedimentarios. Las interrupciones del depósito sólo dieron lugar a la formación de palygorskita. En los medios lagunares ubicados en la unión nororiental de ambos sistemas tuvo lugar el desarrollo de fases silicatadas ricas en magnesio: sepiolita y esmectitas hipermagnesianas. Por último, la silicificación responde a una cementación tardia en un medio desconfinado, o bien a un reemplazamiento del sustrato en medio confinado (nódulos de silex)

Extended van Royen-Weisskopf formalism for lepton-antilepton meson decay widths within non-relativistic quark models

The classical van Royen-Weisskopf formula for the decay width of a meson into a lepton-antilepton pair is modified in order to include non-zero quark momentum contributions within the meson as well as relativistic effects. Besides, a phenomenological electromagnetic density for quarks is introduced. The meson wave functions are obtained from two different models: a chiral constituent quark model and a quark potential model including instanton effects. The modified van Royen-Weisskopf formula is found to improve systematically the results for the widths, giving an overall good description of all known decays.Comment: 22 pages, 3 figures, RevTex, epsfig. To be published in Nucl. Phys.

Un estudio de evaluación sobre el tratamiento de las isometrías en el segundo ciclo de la eso en galicia

El objeto de este artículo es presentar un análisis cuantitativo y cualitativo de las respuestas, de una muestra representativa de alumnos de 2º ciclo de la ESO de la comunidad gallega, a una serie de ítems relacionados con las isometrías del plano. Los resultados presentados en este trabajo han sido además confrontados con las directrices del currículo ofi cial como guía propuesta por la Administración Educativa, con el desarrollo que se hace de estas directrices en los libros de texto más utilizados en las aulas gallegas y, por último, con la particular visión que el docente tiene de ese tema concreto de las matemáticas y su repercusión sobre el proceso de enseñanza-aprendizaje de las transformaciones geométricas en el plano.The aim of this article is to present a quantitative and qualitative analysis of the answers from a representative sample of ESO second cycle students in the Galician community to a series of items connected with the isometries of the plane. The results presented in this paper have been compared with the official curriculum rules as a proposed guide by the educative administration, with the developement of these rules in the most used text books in Galician classrooms and, finally, with the particular view of teachers of this specific topic of Mathematics and its consequences on the teaching/learning process of geometric transformations on the plane

Procesos de alteración y paleosuelos ligados a la sedimentación miocena del NE. de Segovia, depresión del Duero

Se ha realizado un análisis mineral6gico y micromorfol6gico en la zona de confluencia de las partes distales de los sistemas de abanicos aluviales miocenos procedentes de los relieves de Somosierra- Ayllón, al SE., y de Honrubia, al NO. En él, se constatan diferencias entre los procesos edhficos que afectaron a uno y otro sistema, asi como en los grados de evolución de los perfiles edhficos. Los depósitos procedentes de Honrubia se caracterizan por los frecuentes episodios de  encostramiento, a los que se asocia la presencia de esmectitas o de palygorskita en función del menor o mayor grado evolutivo y del menor o mayor confinamiento. Los depósitos del sistema de abanicos aluviales de Somosierra-Ayllón están, generalmente, menos afectados por las alteraciones edáficos, a consecuencia de la mayor intensidad de los procesos sedimentarios. Las interrupciones del depósito sólo dieron lugar a la formación de palygorskita. En los medios lagunares ubicados en la unión nororiental de ambos sistemas tuvo lugar el desarrollo de fases silicatadas ricas en magnesio: sepiolita y esmectitas hipermagnesianas. Por último, la silicificación responde a una cementación tardia en un medio desconfinado, o bien a un reemplazamiento del sustrato en medio confinado (nódulos de silex)

Machine Learning Analysis of TCGA Cancer Data

[Abstract] In recent years, machine learning (ML) researchers have changed their focus towards biological problems that are difficult to analyse with standard approaches. Large initiatives such as The Cancer Genome Atlas (TCGA) have allowed the use of omic data for the training of these algorithms. In order to study the state of the art, this review is provided to cover the main works that have used ML with TCGA data. Firstly, the principal discoveries made by the TCGA consortium are presented. Once these bases have been established, we begin with the main objective of this study, the identification and discussion of those works that have used the TCGA data for the training of different ML approaches. After a review of more than 100 different papers, it has been possible to make a classification according to following three pillars: the type of tumour, the type of algorithm and the predicted biological problem. One of the conclusions drawn in this work shows a high density of studies based on two major algorithms: Random Forest and Support Vector Machines. We also observe the rise in the use of deep artificial neural networks. It is worth emphasizing, the increase of integrative models of multi-omic data analysis. The different biological conditions are a consequence of molecular homeostasis, driven by both protein coding regions, regulatory elements and the surrounding environment. It is notable that a large number of works make use of genetic expression data, which has been found to be the preferred method by researchers when training the different models. The biological problems addressed have been classified into five types: prognosis prediction, tumour subtypes, microsatellite instability (MSI), immunological aspects and certain pathways of interest. A clear trend was detected in the prediction of these conditions according to the type of tumour. That is the reason for which a greater number of works have focused on the BRCA cohort, while specific works for survival, for example, were centred on the GBM cohort, due to its large number of events. Throughout this review, it will be possible to go in depth into the works and the methodologies used to study TCGA cancer data. Finally, it is intended that this work will serve as a basis for future research in this field of study.This work was supported by the “Collaborative Project in Genomic Data Integration (CICLOGEN)” PI17/01826 funded by the Carlos III Health Institute from the Spanish National plan for Scientific and Technical Research and Innovation 2013–2016 and the European Regional Development Funds (FEDER)—“A way to build Europe.” and the General Directorate of Culture, Education and University Management of Xunta de Galicia (Ref. ED431D 2017/16), the “Galician Network for Colorectal Cancer Research” (Ref. ED431D 2017/23) and Competitive Reference Groups (Ref. ED431C 2018/49). CITIC, as Research Center accredited by Galician University System, is funded by “Consellería de Cultura, Educación e Universidades from Xunta de Galicia”, supported in an 80% through ERDF Funds, ERDF Operational Programme Galicia 2014–2020, and the remaining 20% by “Secretaría Xeral de Universidades” (Grant ED431G 2019/01). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscriptXunta de Galicia; ED431D 2017/16Xunta de Galicia; ED431D 2017/23Xunta de Galicia; ED431C 2018/49Xunta de Galicia; ED431G 2019/0