Determinantes del precio del derecho de emisión europeo

[ES] Diversos estudios han investigado sobre los posibles determinantes del precio del derecho de emisión europeo. En este trabajo de fin de grado se pretende analizar qué factores influyen en el precio de este producto financiero y de qué manera lo hacen, además de comprobar posibles cambios en el funcionamiento del mercado. La metodología utilizada para llevar a cabo este análisis se basa principalmente en el modelo de regresión lineal general. A diferencia de otros estudios existentes, la muestra utilizada va desde 2008 hasta 2015, por lo que incluye la segunda fase (2008-2012) de este mercado de derechos de emisión y la tercera (2013-2015), lo que permite analizar las posibles diferencias de funcionamiento del mercado entre ambas fases. Los resultados obtenidos sostienen la existencia de este cambio estructural de manera que en la segunda fase los factores más influyentes son el gas natural y el petróleo, mientras que en la tercera fase el comportamiento del mercado cambia drásticamente de forma que el carbón parece ser el factor más influyente.

A Microdata Analysis Approach to Transport Infrastructure Maintenance

Maintenance of transport infrastructure assets is widely advocated as the key in minimizing current and future costs of the transportation network. While effective maintenance decisions are often a result of engineering skills and practical knowledge, efficient decisions must also account for the net result over an asset's life-cycle. One essential aspect in the long term perspective of transport infrastructure maintenance is to proactively estimate maintenance needs. In dealing with immediate maintenance actions, support tools that can prioritize potential maintenance candidates are important to obtain an efficient maintenance strategy. This dissertation consists of five individual research papers presenting a microdata analysis approach to transport infrastructure maintenance. Microdata analysis is a multidisciplinary field in which large quantities of data is collected, analyzed, and interpreted to improve decision-making. Increased access to transport infrastructure data enables a deeper understanding of causal effects and a possibility to make predictions of future outcomes. The microdata analysis approach covers the complete process from data collection to actual decisions and is therefore well suited for the task of improving efficiency in transport infrastructure maintenance. Statistical modeling was the selected analysis method in this dissertation and provided solutions to the different problems presented in each of the five papers. In Paper I, a time-to-event model was used to estimate remaining road pavement lifetimes in Sweden. In Paper II, an extension of the model in Paper I assessed the impact of latent variables on road lifetimes; displaying the sections in a road network that are weaker due to e.g. subsoil conditions or undetected heavy traffic. The study in Paper III incorporated a probabilistic parametric distribution as a representation of road lifetimes into an equation for the marginal cost of road wear. Differentiated road wear marginal costs for heavy and light vehicles are an important information basis for decisions regarding vehicle miles traveled (VMT) taxation policies. In Paper IV, a distribution based clustering method was used to distinguish between road segments that are deteriorating and road segments that have a stationary road condition. Within railway networks, temporary speed restrictions are often imposed because of maintenance and must be addressed in order to keep punctuality. The study in Paper V evaluated the empirical effect on running time of speed restrictions on a Norwegian railway line using a generalized linear mixed model.

The Effect of Climate Variability on Main Components of Cow Milk in Iran

The main purpose of this study is to assess the relationship between six bioclimatic indices for cattle (temperature humidity (THI), environmental stress (ESI), equivalent temperature (ESI), heat load (HLI), modified heat load (HLInew) and respiratory rate predictor(RRP)) and fundamental milk components (fat, protein, and milk yield) considering uncertainty. The climate parameters used to calculate the climate indices were taken from the NASA-Modern Era Retrospective-Analysis for Research and Applications (NASA-MERRA) reanalysis from 2002 to 2010. Cow milk data were considered for the same period from April to September when cows use natural pasture, with possibility for cows to choose to stay in the barn or to graze on the pasture in the pasturing system. The study is based on a linear regression analysis using correlations as a summarizing diagnostic. Bootstrapping is used to represent uncertainty estimation through resampling in the confidence intervals. To find the relationships between climate indices (THI, ETI, HLI, HLInew, ESI and RRP) and main components of cow milk (fat, protein and yield), multiple liner regression is applied. The least absolute shrinkage selection operator (LASSO) and the Akaike information criterion (AIC) techniques are applied to select the best model for milk predictands with the smallest number of climate predictors. Cross validation is used to avoid over-fitting. Based on results of investigation the effect of heat stress indices on milk compounds separately, we suggest the use of ESI and RRP in the summer and ESI in the spring. THI and HLInew are suggested for fat content and HLInew also is suggested for protein content in the spring season. The best linear models are found in spring between milk yield as predictands and THI, ESI,HLI, ETI and RRP as predictors with p-value < 0.001 and R2 0.50, 0.49. In summer, milk yield with independent variables of THI, ETI and ESI show the highest relation (p-value < 0.001) with R2 (0.69). For fat and protein the results are only marginal. It is strongly suggested that new and significant indices are needed to control critical heat stress conditions that consider more predictors of the effect of climate variability on animal products, such as sunshine duration, quality of pasture, the number of days of stress (NDS), the color of skin with attention to large black spots, and categorical predictors such as breed, welfare facility, and management system. This methodology is suggested for studies investigating the impacts of climate variability/change on food quality/security, animal science and agriculture using short term data considering uncertainty or data collection is expensive, difficult, or data with gaps.

Impedancias basales registradas durante la denervación renal por radiofrecuencia en pacientes con hipertensión arterial resistente

Objetivo: Determinar diferencias en las impedancias basales registradas durante los procedimientos de denervación renal por radiofrecuencia de los pacientes sometidos a este procedimiento en la Fundación Cardioinfantil de Bogotá durante los años 2012 a 2015. Materiales y métodos: Estudio observacional, analítico de corte retrospectivo, donde se analizaron todas las impedancias basales medidas durante los procedimientos de denervación renal, buscando diferencias significativas entre los segmentos de las arterias intervenidas, estratificados en proximal, medio distal y superior, lateral, inferior u ostial. Con seguimiento a los pacientes a tres, seis y doce meses en cuanto a presión arterial de consultorio. Resultados: Se evaluaron 150 puntos de denervación renal exitosos, correspondientes a 23 arterias renales de 11 procedimientos. La mediana de edad fue 56 años. Al realizar un modelo de regresión lineal no se encontró ninguna diferencia estadísticamente significativa entre las impedancias de ninguno de los segmentos de las arterias ni sitios anatómicos. Se documentó disminución de presión arterial sistólica a tres meses, seis meses y doce meses de 14 mmHg (RIQ 10-33mmHg), 21 mmHg (RIQ 12-42mmHg) y 19 mmHg (RIQ 11-42 mmHg) respectivamente

Comportamiento metabólico, fisiológico y electrocardiográfico en trabajadores expuestos a altas temperaturas en una empresa líder en la explotación y coquización del carbón en Boyacá, Colombia, 2016

Objetivo: Establecer la relación entre la exposición ocupacional a altas temperaturas o sobrecarga térmica con el comportamiento fisiológico, metabólico y electrocardiográfico. Métodos: estudio de corte transversal, donde se incluyeron dos grupos (expuesto y no expuesto a altas temperaturas) en una empresa minera, en el departamento de Boyacá, Colombia, en el año 2016. El número de participantes fue de 160 trabajadores del género masculino, grupo expuesto (n=86) y grupo no expuesto (n=74). La exposición ocupacional a sobrecarga térmica se evaluó con el índice de temperatura de globo y bulbo húmedo (TGBH), el comportamiento fisiológico con el índice de costo cardiaco relativo (ICCR) con mediciones de frecuencia cardiaca (FC), el comportamiento metabólico con la determinación del colesterol total (CT), colesterol de alta densidad (C-HDL), colesterol de baja densidad (C-LDL), triglicéridos (TG) y glicemia basal (GL). Las alteraciones electrocardiográficas con la toma de Electrocardiograma de 12 derivaciones. También fueron evaluadas variables antropométricas, tensión arterial, hábitos y antecedentes de enfermedad cardiovascular en ambos grupos. Resultados: incrementos significativos del ICCR (p<0.001) y la carga física (p<0.001) fueron encontrados en los trabajadores expuestos a altas temperaturas. Los índices lipídicos y glicemia, así como los antecedentes personales cardiovasculares, IMC, consumo de cigarrillo y consumo de alcohol, no mostraron significancia. El antecedente familiar de ACV (p=0.043) y el EKG alterado (p=0.011) mostraron una asociación significativa con la exposición a altas temperaturas. El modelo de regresión lineal múltiple explicó la relación entre el incremento del ICCR y la exposición a altas temperaturas (β=4,213, IC 95%: 1.57,6.85) ajustado por variables fisiológicas y electrocardiográficas. Conclusiones: La exposición ocupacional a altas temperaturas, presenta asociación con las alteraciones cardiovasculares a nivel fisiológico y electrocardiográfico, aumentando el ICCR y la carga física de trabajo (GE trabajo).

Solastalgia y conductas pro-ambientales en un conflicto socioambiental por la construcción de una hidroeléctrica

Introducción: La construcción de megaproyectos hídricos implica una reconfiguración territorial donde se ven afectadas las fuentes de agua dulce, la biodiversidad terrestre y acuática, y los asentamientos humanos que colindan con dichas construcciones. Objetivo: estimar la asociación entre las conductas proambientales con la solastalgia entre las personas que se encuentran ejerciendo un proceso de resistencia social contra la Central Hidrosogamoso en el departamento de Santander, Colombia. Metodología: se utilizó un diseño de estudio transversal en el que se entrevistaron integrantes y no integrantes de grupos ambientalistas de las zonas de influencia del proyecto. Se realizó un análisis descriptivo de las variables sociodemográficas de los dos grupos de comparación presentando frecuencias absolutas y relativas y diferencias significativas por medio de la prueba ji cuadrado, exacta de Fisher y U de Mann Whitney. Se utilizó un modelo de regresión lineal múltiple en el que la variable dependiente fue el puntaje de solastalgia y las variables independientes fueron las escalas de las conductas proambientales: altruismo, austeridad, equidad, conducta ecológica, deliberación, indignación y aprecio por lo natural, además, se ajustó por algunas variables sociodemográficas de interés. Resultados: los grupos comparados presentaron diferencias importantes en cuanto a la zona de procedencia, condiciones económicas y organización social. El incremento de 5 puntos en la escala del sentimiento de indignación incrementó 0.98 la escala de solastalgia (IC95%: 0.19; 1.78). Las personas sin pareja estable tuvieron 3.02 puntos menos de solastalgia comparadas con personas casadas o en unión libre (IC95%: -4.96; -1.44), mientras que aquellas con alto nivel educativo obtuvieron 2.02 puntos menos que las personas con primaria y bachillerato (IC95%: -3.99; -0.06). Un modelo alterno mostró que no pertenecer a un grupo ambientalista disminuye en 2.29 puntos la solastalgia, comparado con pertenecer a un grupo (IC95%: -4.31; -0.28),. Conclusión: posiblemente las motivaciones por las cuales los actores involucrados se resisten a las transformaciones territoriales ocasionadas por la construcción de las represas son más un reflejo de la condición socioeconómica que de la preocupación de los actores por el daño del medio ambiente y además, esta resistencia es un fenómeno que se limita a aquellos que están afectados directamente en el área de influencia del proyecto

Coordinated Scheduling of Wind-Thermal Gencos in Day-Ahead Markets

This paper presents a stochastic mixed-integer linear programming approach for solving the self-scheduling problem of a price-taker thermal and wind power producer taking part in a pool-based electricity market. Uncertainty on electricity price and wind power is considered through a set of scenarios. Thermal units are modeled by variable costs, start-up costs and technical operating constraints, such as: ramp up/down limits and minimum up/down time limits. An efficient mixed-integer linear program is presented to develop the offering strategies of the coordinated production of thermal and wind energy generation, aiming to maximize the expected profit. A case study with data from the Iberian Electricity Market is presented and results are discussed to show the effectiveness of the proposed approach.

Bidding strategy of wind-thermal energy producers

This paper presents a stochastic mixed-integer linear programming approach for solving the self-scheduling problem of a price-taker thermal and wind power producer taking part in a pool-based electricity market. Uncertainty on electricity price and wind power is considered through a set of scenarios. Thermal units are modelled by variable costs, start-up costs and technical operating constraints, such as: forbidden operating zones, ramp up/down limits and minimum up/down time limits. An efficient mixed-integer linear program is presented to develop the offering strategies of the coordinated production of thermal and wind energy generation, having as a goal the maximization of profit. A case study with data from the Iberian Electricity Market is presented and results are discussed to show the effectiveness of the proposed approach.

Variation in myogenic differentiation 1 mRNA abundance is associated with beef tenderness in Nelore cattle.

The myogenic differentiation 1 gene (MYOD1) has a key role in skeletal muscle differentiation and composition through its regulation of the expression of several muscle-specific genes. We first used a general linear mixed model approach to evaluate the association of MYOD1 expression levels on individual beef tenderness phenotypes. MYOD1 mRNA levels measured by quantitative polymerase chain reactions in 136 Nelore steers were significantly associated (P ? 0.01) with Warner?Bratzler shear force, measured on the longissimus dorsi muscle after 7 and 14 days of beef aging. Transcript abundance for the muscle regulatory gene MYOD1 was lower in animals with more tender beef. We also performed a coexpression network analysis using whole transcriptome sequence data generated from 30 samples of longissimus muscle tissue to identify genes that are potentially regulated by MYOD1. The effect of MYOD1 gene expression on beef tenderness may emerge from its function as an activator of muscle-specific gene transcription such as for the serum response factor (C-fos serum response element-binding transcription factor) gene (SRF), which determines muscle tissue development, composition, growth and maturation.

Analysis of COVID-related symptoms from a database of Italian tweets

Twitter is a highly popular social media which on one hand allows information transmission in real time and on the other hand represents a source of open access homogeneous text data. We propose an analysis of the most common self-reported COVID symptoms from a dataset of Italian tweets to investigate the evolution of the pandemic in Italy from the end of September 2020 to the end of January 2021. After manually filtering tweets actually describing COVID symptoms from the database - which contains words related to fever, cough and sore throat - we discuss usefulness of such filtering. We then compare our time series with the daily data of new hospitalisations in Italy, with the aim of building a simple linear regression model that accounts for the delay which is observed from the tweets mentioning individual symptoms to new hospitalisations. We discuss both the results and limitations of linear regression given that our data suggests that the relationship between time series of symptoms tweets and of new hospitalisations changes towards the end of the acquisition.

Prevention of binge drinking in young adolescents through the promotion of a balanced level of psychological well-being: be-dry

This doctoral thesis presents a project carried out in secondary schools located in the city of Ferrara with the primary objective of demonstrating the effectiveness of an intervention based on Well-Being Therapy (Fava, 2016) in reducing alcohol use and improving lifestyles. In the first part (chapters 1-3), an introduction on risky behaviors and unhealthy lifestyle in adolescence is presented, followed by an examination of the phenomenon of binge drinking and of the concept of psychological well-being. In the second part (chapters 4-6), the experimental study is presented. A three-arm cluster randomized controlled trial including three test periods was implemented. The study involved eleven classes that were randomly assigned to receive well-being intervention (WBI), lifestyle intervention (LI) or not receive intervention (NI). Results were analyzed by linear mixed model and mixed-effects logistic regression with the aim to test the efficacy of WBI in comparison with LI and NI. AUDIT-C total score increased more in NI in comparison with WBI (p=0.008) and LI (p=0.003) at 6-month. The odds to be classified as at-risk drinker was lower in WBI (OR 0.01; 95%CI 0.01–0.14) and LI (OR 0.01; 95%CI 0.01–0.03) than NI at 6-month. The odds to use e-cigarettes at 6-month (OR 0.01; 95%CI 0.01–0.35) and cannabis at post-test (OR 0.01; 95%CI 0.01–0.18) were less in WBI than NI. Sleep hours at night decreased more in NI than in WBI (p = 0.029) and LI (p = 0.006) at 6-month. Internet addiction scores decreased more in WBI (p = 0.003) and LI (p = 0.004) at post-test in comparison with NI. Conclusions about the obtained results, limitations of the study, and future implications are discussed. In the seventh chapter, the data of the project collected during the pandemic are presented and compared with those from recent literature.

Risk assessment to improve food safety along different food chains

The great challenges of today pose great pressure on the food chain to provide safe and nutritious food that meets regulations and consumer health standards. In this context, Risk Analysis is used to produce an estimate of the risks to human health and to identify and implement effective risk-control measures. The aims of this work were 1) describe how QRA is used to evaluate the risk for consumers health, 2) address the methodology to obtain models to apply in QMRA; 3) evaluate solutions to mitigate the risk. The application of a QCRA to the Italian milk industry enabled the assessment of Aflatoxin M1 exposure, impact on different population categories, and comparison of risk-mitigation strategies. The results highlighted the most sensitive population categories, and how more stringent sampling plans reduced risk. The application of a QMRA to Spanish fresh cheeses evidenced how the contamination of this product with Listeria monocytogenes may generate a risk for the consumers. Two risk-mitigation actions were evaluated, i.e. reducing shelf life and domestic refrigerator temperature, both resulting effective in reducing the risk of listeriosis. A description of the most applied protocols for data generation for predictive model development, was provided to increase transparency and reproducibility and to provide the means to better QMRA. The development of a linear regression model describing the fate of Salmonella spp. in Italian salami during the production process and HPP was described. Alkaline electrolyzed water was evaluated for its potential use to reduce microbial loads on working surfaces, with results showing its effectiveness. This work showed the relevance of QRA, of predictive microbiology, and of new technologies to ensure food safety on a more integrated way. Filling of data gaps, the development of better models and the inclusion of new risk-mitigation strategies may lead to improvements in the presented QRAs.

Comparison of Different Concentrated Solar Power Collector Designs and Development of a Linear Fresnel Solar Collector Model

Concentrated solar power (CSP) is a renewable energy technology, which could contribute to overcoming global problems related to pollution emissions and increasing energy demand. CSP utilizes solar irradiation, which is a variable source of energy. In order to utilize CSP technology in energy production and reliably operate a solar field including thermal energy storage system, dynamic simulation tools are needed in order to study the dynamics of the solar field, to optimize production and develop control systems. The object of this Master’s Thesis is to compare different concentrated solar power technologies and configure a dynamic solar field model of one selected CSP field design in the dynamic simulation program Apros, owned by VTT and Fortum. The configured model is based on German Novatec Solar’s linear Fresnel reflector design. Solar collector components including dimensions and performance calculation were developed, as well as a simple solar field control system. The preliminary simulation results of two simulation cases under clear sky conditions were good; the desired and stable superheated steam conditions were maintained in both cases, while, as expected, the amount of steam produced was reduced in the case having lower irradiation conditions. As a result of the model development process, it can be concluded, that the configured model is working successfully and that Apros is a very capable and flexible tool for configuring new solar field models and control systems and simulating solar field dynamic behaviour.