Evaluación del impacto en el desarrollo humano de proyectos de usos energéticos de la biomasa: el caso de Nicaragua

La falta de acceso a fuentes modernas de energía es un lastre para el desarrollo económico y social de numerosas personas en el mundo. Actualmente se calcula que aproximadamente 1400 millones de personas (20% de la población mundial) carecen de acceso a electricidad y que 2700 millones de personas (40% de la población mundial) siguen cocinando a partir de usos tradicionales de la biomasa. Partiendo de esta base se ha realizado una investigación acerca de los usos energéticos de la biomasa en el medio rural en Nicaragua, en la cual se han evaluado una serie de proyectos de este tipo. Su objetivo fundamental fue profundizar en el conocimiento sobre las distintas tecnologías usadas en este campo y ofrecer información sistematizada que permita mejorar el desempeño de proyectos futuros. Para cada uno de los proyectos y como resultado principal de la investigación, se estableció su Impacto en el Desarrollo Humano y Sostenible con la aplicación de la Herramienta S&E (Fernández, L. et al, 2011). Los resultados obtenidos gracias a esta herramienta nos han permitido realizar comparaciones en cuanto al desempeño de cada proyecto en numerosos aspectos distintos y en especial sobre que modelos de intervención generan mayor impacto en el desarrollo

D-trace estimation of a precision matrix using adaptive Lasso penalties

The accurate estimation of a precision matrix plays a crucial role in the current age of high-dimensional data explosion. To deal with this problem, one of the prominent and commonly used techniques is the ℓ1 norm (Lasso) penalization for a given loss function. This approach guarantees the sparsity of the precision matrix estimate for properly selected penalty parameters. However, the ℓ1 norm penalization often fails to control the bias of obtained estimator because of its overestimation behavior. In this paper, we introduce two adaptive extensions of the recently proposed ℓ1 norm penalized D-trace loss minimization method. They aim at reducing the produced bias in the estimator. Extensive numerical results, using both simulated and real datasets, show the advantage of our proposed estimators.We would like to thank the Associate Editor, Coordinating Editor and two anonymous referees for their helpful comments that led to an improvement of this article. We express our gratitude to Teng Zhang and Hui Zou for sharing their Matlab code that solves the L1 norm penalized D-trace loss minimization problem. Andrés M. Alonso gratefully acknowledges financial support from CICYT (Spain) Grants ECO2012-38442 and ECO2015-66593. Francisco J. Nogales and Vahe Avagyan were supported by the Spanish Government through project MTM2013-44902-P. This paper is based on the first author's dissertation submitted to the Universidad Carlos III de Madrid. At the time of publication, Vahe Avagyan is a Postdoctoral fellow at Ghent University

A study about the knowledge and use of requirements engineering standards in industry

Context. The use of standards is considered a vital part of any engineering discipline. So one could expect that standards play an important role in Requirements Engineering (RE) as well. However, little is known about the actual knowledge and use of RE-related standards in industry. Objective. In this article, we investigate to which extent standards and related artifacts such as templates or guidelines are known and used by RE practitioners. Method. To this end, we have conducted a questionnaire-based online survey. We could analyze the replies from 90 RE practitioners using a combination of closed and open-text questions. Results. Our results indicate that the knowledge and use of standards and related artifacts in RE is less widespread than one might expect from an engineering perspective. For example, about 47% of the respondents working as requirements engineers or business analysts do not know the core standard in RE, ISO/IEC/IEEE 29148. Participants in our study mostly use standards by personal decision rather than being imposed by their respective company, customer, or regulator. Beyond insufficient knowledge, we also found cultural and organizational factors impeding the widespread adoption of standards in RE. Conclusions. Overall, our results provide empirically informed insights into the actual use of standards and related artifacts in RE practice and – indirectly – about the value that the current standards create for RE practitioners.Peer ReviewedPostprint (author's final draft

A Single Scalable LSTM Model for Short-Term Forecasting of Massive Electricity Time Series

This article belongs to the Special Issue Forecasting in Electricity Markets with Big Data and Artificial Intelligence.Most electricity systems worldwide are deploying advanced metering infrastructures to collect relevant operational data. In particular, smart meters allow tracking electricity load consumption at a very disaggregated level and at high frequency rates. This data opens the possibility of developing new forecasting models with a potential positive impact on electricity systems. We present a general methodology that can process and forecast many smart-meter time series. Instead of using traditional and univariate approaches, we develop a single but complex recurrent neural-network model with long short-term memory that can capture individual consumption patterns and consumptions from different households. The resulting model can accurately predict future loads (short-term) of individual consumers, even if these were not included in the original training set. This entails a great potential for large-scale applications as once the single network is trained, accurate individual forecast for new consumers can be obtained at almost no computational cost. The proposed model is tested under a large set of numerical experiments by using a real-world dataset with thousands of disaggregated electricity consumption time series. Furthermore, we explore how geo-demographic segmentation of consumers may impact the forecasting accuracy of the model.The authors gratefully acknowledge the financial support from the Spanish government through projects MTM2017-88979-P and PID2019-108311GB-I00/AEI/10.13039/501100011033, and from Fundación Iberdrola through “Ayudas a la Investigación en Energía y Medio Ambiente 2018”

NTRC Plays a Crucial Role in Starch Metabolism, Redox Balance, and Tomato Fruit Growth

NADPH-thioredoxin reductase C (NTRC) forms a separate thiol-reduction cascade in plastids, combining both NADPHthioredoxin reductase and thioredoxin activities on a single polypeptide. While NTRC is an important regulator of photosynthetic processes in leaves, its function in heterotrophic tissues remains unclear. Here, we focus on the role of NTRC in developing tomato (Solanum lycopersicum) fruits representing heterotrophic storage organs important for agriculture and human diet. We used a fruit-specific promoter to decrease NTRC expression by RNA interference in developing tomato fruits by 60% to 80% compared to the wild type. This led to a decrease in fruit growth, resulting in smaller and lighter fully ripe fruits containing less dry matter and more water. In immature fruits, NTRC downregulation decreased transient starch accumulation, which led to a subsequent decrease in soluble sugars in ripe fruits. The inhibition of starch synthesis was associated with a decrease in the redox-activation state of ADP-Glc pyrophosphorylase and soluble starch synthase, which catalyze the first committed and final polymerizing steps, respectively, of starch biosynthesis. This was accompanied by a decrease in the level of ADP-Glc. NTRC downregulation also led to a strong increase in the reductive states of NAD(H) and NADP(H) redox systems. Metabolite profiling of NTRC-RNA interference lines revealed increased organic and amino acid levels, but reduced sugar levels, implying that NTRC regulates the osmotic balance of developing fruits. These results indicate that NTRC acts as a central hub in regulating carbon metabolism and redox balance in heterotrophic tomato fruits, affecting fruit development as well as final fruit size and qualit

Impacto de los cambios tecnológicos en los modelos de negocios de las industrias de cultura y ocio en España - El caso de los museos y clubes de fútbol

En una primera instancia puede resultar sorprendente tratar en el mismo artículo organizaciones tan diferentes como los museos y los clubes de futbol. Sin embargo, en una mirada de más detalle se puede ver que ambas organizaciones cuentan con una relación muy estrecha en el plano emocional con sus seguidores. A partir de esta relación se analizan los múltiples cambios tecnológicos que pueden afectar a este sector, considerando los posibles efectos en modelos de negocio de éxito que se puedan adoptar en el futuro. El articulo culmina con una reflexión sobre las alternativas que el sector puede adoptar para continuar evolucionando sus modelos de negocio aprovechando los cambios tecnológicos identificados

Meta-DiSc 2.0:a web application for meta-analysis of diagnostic test accuracy data

BACKGROUND: Diagnostic evidence of the accuracy of a test for identifying a target condition of interest can be estimated using systematic approaches following standardized methodologies. Statistical methods for the meta-analysis of diagnostic test accuracy (DTA) studies are relatively complex, presenting a challenge for reviewers without extensive statistical expertise. In 2006, we developed Meta-DiSc, a free user-friendly software to perform test accuracy meta-analysis. This statistical program is now widely used for performing DTA meta-analyses. We aimed to build a new version of the Meta-DiSc software to include statistical methods based on hierarchical models and an enhanced web-based interface to improve user experience. RESULTS: In this article, we present the updated version, Meta-DiSc 2.0, a web-based application developed using the R Shiny package. This new version implements recommended state-of-the-art statistical models to overcome the limitations of the statistical approaches included in the previous version. Meta-DiSc 2.0 performs statistical analyses of DTA reviews using a bivariate random effects model. The application offers a thorough analysis of heterogeneity, calculating logit variance estimates of sensitivity and specificity, the bivariate I-squared, the area of the 95% prediction ellipse, and the median odds ratios for sensitivity and specificity, and facilitating subgroup and meta-regression analyses. Furthermore, univariate random effects models can be applied to meta-analyses with few studies or with non-convergent bivariate models. The application interface has an intuitive design set out in four main menus: file upload; graphical description (forest and ROC plane plots); meta-analysis (pooling of sensitivity and specificity, estimation of likelihood ratios and diagnostic odds ratio, sROC curve); and summary of findings (impact of test through downstream consequences in a hypothetical population with a given prevalence). All computational algorithms have been validated in several real datasets by comparing results obtained with STATA/SAS and MetaDTA packages. CONCLUSION: We have developed and validated an updated version of the Meta-DiSc software that is more accessible and statistically sound. The web application is freely available at www.metadisc.es

Optimizing subject design, timing, and focus in a diversity of engineering courses through the use of a low-cost Arduino shield

This paper describes the design, implementation and evaluation of a novel circuitry that extends the popular Arduino UNO microcontroller board to facilitate multiple educational activities in engineering courses. In particular, the aim of this board, the UMA-AEB, is to minimize the overhead that is usually imposed on the students before they can conduct the actual exercises, yet retain the valuable experiences that could otherwise not be acquired with simulated experiments or inflexible electronic training-benches.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech. This work has been supported by the University of Málaga (Spain) through the educational innovation project PIE-15-093 “Innovación en el trabajo en laboratorio de una diversidad de asignaturas de ingeniería mediante el diseño y aplicación de una extensión de la plataforma de hardware abierto Arduino”

A versatile CMOS transistor array IC for the statistical characterization of time-zero variability, RTN, BTI, and HCI

© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Statistical characterization of CMOS transistor variability phenomena in modern nanometer technologies is key for accurate end-of-life prediction. This paper presents a novel CMOS transistor array chip to statistically characterize the effects of several critical variability sources, such as time-zero variability (TZV), random telegraph noise (RTN), bias temperature instability (BTI), and hot-carrier injection (HCI). The chip integrates 3136 MOS transistors of both pMOS and nMOS types, with eight different sizes. The implemented architecture provides the chip with a high level of versatility, allowing all required tests and attaining the level of accuracy that the characterization of the above-mentioned variability effects requires. Another very important feature of the array is the capability of performing massively parallel aging testing, thus significantly cutting down the time for statistical characterization. The chip has been fabricated in a 1.2-V, 65-nm CMOS technology with a total chip area of 1800 x 1800 µm².Peer ReviewedPostprint (author's final draft

Social development benefits of hydroelectricity CDM projects in Brazil

In recent years, the concept of sustainable development has become increasingly recognized and important. Within organizations, sustainable development is often portrayed as a balancing act, and requires a combination of three elements to be considered: economy, environment, and society. Traditionally, organizational management research has been focused on economical and environmental fronts. However, social aspects are also important for organizations, especially those in emerging and developing countries. The goal of this paper is to investigate the potential of Clean Development Mechanism (CDM) projects to deliver social benefits in Brazil?s hydroelectricity sector. The investigation involved the assessment of 46 registered hydro CDM projects under the Kyoto Protocol in terms of their potential impact on the envisaged social development goals. Two case studies were also examined. Results indicate that organizations managing hydroelectric initiatives in Brazil can provide the pathway towards achieving a number of important social benefits. Successful projects were found to have good community involvement and were managed by both cooperative ventures and money making corporations. The research also identified several challenges that are hindering hydro CDM projects from delivering more social benefits, and enabled a number of recommendations to be extracted for the organizations facing these challenges