Developing the follow-up schedules for women with breast cancer

Background: The follow-up care for women with breast cancer requires an understanding of disease recurrence patterns and the follow-up visit schedule should be determined according to the times when the recurrence are most likely to occur, so that preventive measure can be taken to avoid or minimize the recurrence. Objective: To model breast cancer recurrence through stochastic process with an aim to generate a hazard function for determining a follow-up schedule. Methods: We modeled the process of disease progression as the time transformed Weiner process and the first-hitting-time was used as an approximation of the true failure time. The women's "recurrence-free survival time" or a "not having the recurrence event" is modeled by the time it takes Weiner process to cross a threshold value which represents a woman experiences breast cancer recurrence event. We explored threshold regression model which takes account of covariates that contributed to the prognosis of breast cancer following development of the first-hitting time model. Using real data from SEER-Medicare, we proposed models of follow-up visits schedule on the basis of constant probability of disease recurrence between consecutive visits. Results: We demonstrated that the threshold regression based on first-hitting-time modeling approach can provide useful predictive information about breast cancer recurrence. Our results suggest the surveillance and follow-up schedule can be determined for women based on their prognostic factors such as tumor stage and others. Women with early stage of disease may be seen less frequently for follow-up visits than those women with locally advanced stages. Our results from SEER-Medicare data support the idea of risk-controlled follow-up strategies for groups of women. Conclusion: The methodology we proposed in this study allows one to determine individual follow-up scheduling based on a parametric hazard function that incorporates known prognostic factors.^

Predicting smokeless tobacco cessation in a blue -collar population

The use of smokeless tobacco products is undergoing an alarming resurgence in the United States. Several national surveys have reported a higher prevalence of use among those employed in blue-collar occupations. National objectives now target this group for health promotion programs which reduce the health risks associated with tobacco use.^ Drawn from a larger data set measuring health behaviors, this cross-sectional study tested the applicability of two related theories, the Theory of Reasoned Action (TRA) and the Theory of Planned Behavior (TPB), to smokeless tobacco (SLT) cessation in a blue-collar population of gas pipeline workers. In order to understand the determinants of SLT cessation, measures were obtained of demographic and normative characteristics of the population and specific constructs. Attitude toward the act of quitting (AACT) and subjective norm (SN) are constructs common to both models, perceived behavioral control (PBC) is unique to the TPB, and the number of past quit attempts is not contained in either model. In addition, a self-reported measure was taken of SLT use at two-month follow-up.^ The study population was comprised of all male SLT users who were field employees in a large gas pipeline company with gas compressor stations extending from Texas to the Canadian border. At baseline, 199 employees responded to the SLT portion of the survey, 118 completed some portion of the two-month follow-up, and 101 could be matched across time.^ As hypothesized, significant correlations were found between constructs antecedent to AACT and SN, although crossover effects occurred. Significant differences were found between SLT cessation intenders and non-intenders with regard to their personal and normative beliefs about quitting as well as their outcome expectancies and motivation to comply with others' beliefs. These differences occurred in the expected direction, with the mean intender score consistently higher than that of the non-intender.^ Contrary to hypothesis, AACT predicted intention to quit but SN did not. However, confirmatory of the TPB, PBC, operationalized as self-efficacy, independently contributed to the prediction of intention. Statistically significant relationships were not found between intention, perceived behavioral control, their interactive effects, and use behavior at two-month follow-up. The introduction of number of quit attempts into the logistic regression model resulted in insignificant findings for independent and interactive effects.^ The findings from this study are discussed in relation to their implications for program development and practice, especially within the worksite. In order to confirm and extend the findings of this investigation, recommendations for future research are also discussed. ^

Modelos de demanda potencial de viajeros en redes de transporte público : aplicaciones en el Metro de Madrid

Este trabajo propone una metodología basada en Sistemas de Información Geográfica para estimar la demanda de viajes en estaciones de redes de transporte público, tomando como ejemplo la red de metro de Madrid. Primero se emplea una serie de datos descriptivos para caracterizar la red, clasificar las estaciones y obtener una tipología de las mismas. Luego, con el objetivo de explicar y predecir los viajes (entradas a la red) se generan dos modelos: uno sencillo a partir de las tasas de penetración de uso del metro en función de la distancia (distance decay), y otro más complejo basado en un modelo de regresión lineal múltiple (MRLM) que incorpora variables relativas a la estación y su entorno (densidad, mezcla de usos, diseño urbano, presencia de modos competidores). Su aplicación muestra resultados alentadores, y se plantea como una alternativa a los clásicos modelos de cuatro etapas, más complejos y con un mayor coste económico.

Factores que influyen en la adopción de tecnologías de conservación de suelos en el secano interior de Chile Central

El desarrollo de sistemas agrícolas sustentables es un desafío en el contexto de políticas e incentivos tendientes a la conservación de los recursos naturales, especialmente en zonas de secano. El presente estudio examina variables demográficas y productivas que influyen en la adopción de tecnologías de conservación de suelos en 90 pequeños productores del secano interior de Chile Central, en las comunas de Pencahue y Curepto. Se utilizó un modelo de regresión Probit, el cual asocia la adopción de las tecnologías con las variables: edad del agricultor, tamaño familiar, superficie predial y forma de tenencia de la tierra; presencia de: plantaciones forestales, invernaderos, aboneras, animales mayores en el predio; experiencia en comercialización del productor y participación en actividades de capacitación. El modelo seleccionado tiene un alto poder de predicción, llegando a clasificar correctamente un 92,2% de las observaciones. Los resultados econométricos muestran que la participación en actividades de extensión, la superficie predial, la presencia de plantaciones forestales y el uso de aboneras, influyen de manera positiva y significativa sobre la adopción de tecnologías conservacionistas. Resulta relevante el impacto de la capacitación sobre la adopción de tecnologías de alto grado de inversión, así como la incorporación de prácticas de conservación de bajo nivel de inversión como las aboneras.

Morphology and size of Neogloboquadrina pachyderma in the North Atlantic

The variability in size and shape of shells of the polar planktonic foraminifer Neogloboquadrina pachyderma have been quantified in 33 recent surface sediment samples throughout the northern Atlantic Ocean and correlated with the properties of the ambient surface waters. The aim of the study was to determine whether any of the morphological features could be used to reconstruct sea surface properties in the polar realm of the North Atlantic, where most paleotemperature proxies appear to fail. The analyses revealed that shell morphology is only weakly controlled by habitat properties, whereas shell size showed a strong correlation with sea surface temperature. The regression of mean shell size on sea surface temperature revealed the presence of two trends among the sinistrally coiled shells: a continuous increase in shell size with decreasing SST in sediments deposited under polar water masses and a continuous increase in shell size with increasing SST in samples from transitional waters. The second trend mirrors the trend observed for dextrally coiled shells, which are frequent in the same samples and signal the presence of N. incompta. The identical mean shell size trends among the sinistral and dextral specimens in the temperate samples confirms the results of earlier genetic studies which indicated the existence of a small but distinct proportion of opposite coiling in N. incompta, to which the sinistral shells in the temperate samples could be attributed. The linear correlation between mean shell size and sea surface temperature in the polar domain (summer SST < 9 °C) has been used to develop an empirical formula for the reconstruction of past sea surface temperatures from shell sizes in fossil samples. The standard error of the residuals of the linear regression is 2.36 °C (1 sigma), which implies a much larger error than for most paleothermometers, but enough precision to allow resolution between results by individual paleothermometers in the polar domain. The resulting regression model has been applied on two sediment cores spanning the interval from the Last Glacial Maximum (LGM) to the present day. The results from core PS1906-1 are consistent with ice-free conditions during the LGM in the Norwegian Sea. The SST estimates for the LGM inferred from N. pachyderma shell size are similar or slightly higher than those for the latest Holocene. The results do not indicate anomalously high SST during the glacial and the LGM reconstructions thus appear more consistent with the results from foraminiferal transfer functions and geochemical proxies. Both sediment cores show the highest reconstructed SST during the early Holocene insolation optimum.

Proglacial river dataset from the Akuliarusiarsuup Kuua River northern tributary, Southwest Greenland, 2008 - 2013, version 2.0

The dataset contains measurements of river stage and discharge for one sites along the Akuliarusiarsuup Kuua River's northern tributary, with 30 minute temporal resolution between June 2008 and August 2013 This river is a tributary to the Watson River discharging into Kangerlussuaq Fjord by the town of Kangerlussuaq, Southwest Greenland. Additional data of water temperature, air pressure are also provided. Compared to version 1.0 of the dataset, this dataset used a total of 36 in situ discharge observations collected between 2008 and 2012 to construct the rating curve. Furthermore, data of Station AK-004-001 between 2010-09-06T11:30 to 2010-09-07T13:30 have been removed from version 2.0 because these values were likely caused by backflow when a jokulhlaup from a large glacier dammed lake caused increased water levels in the downstreams lake. Thus, data measured at AK-004-001 between 2010-09-06T11:30 to 2010-09-07T13:30 are not representative for the AK-004 catchment.

Sources and proxy potential of long chain alkyl diols in lacustrine environments

Long chain 1,13- and 1,15-alkyl diols form the base of a number of recently proposed proxies used for climate reconstruction. However, the sources of these lipids and environmental controls on their distribution are still poorly constrained. We have analyzed the long chain alkyl diol (LCD) composition of cultures of ten eustigmatophyte species, with three species from different families grown at various temperatures, to identify the effect of species composition and growth temperature on the LCD distribution. The results were compared with the LCD distribution of sixty-two lake surface sediments, and with previously reported LCD distributions from marine environments. The different families within the Eustigmatophyceae show distinct LCD patterns, with the freshwater family Eustigmataceae most closely resembling LCD distributions in both marine and lake environments. Unlike the other two eustigmatophyte families analyzed (Monodopsidaceae and Goniochloridaceae), C28 and C30 1,13-alkyl diols and C30 and C32 1,15-alkyl diols are all relatively abundant in the family Eustigmataceae, while the mono-unsaturated C32 1,15-alkyl diol was below detection limit. In contrast to the marine environment, LCD distributions in lakes did not show a clear relationship with temperature. The Long chain Diol Index (LDI), a proxy previously proposed for sea surface temperature reconstruction, showed a relatively weak correlation (R2 = 0.33) with mean annual air temperature used as an approximation for annual mean surface temperature of the lakes. A much-improved correlation (R2 = 0.74, p-value<0.001) was observed applying a multiple linear regression analysis between LCD distributions and lake temperatures reconstructed using branched tetraether lipid distributions. The obtained regression model provides good estimates of temperatures for cultures of the family Eustigmataceae, suggesting that algae belonging to this family have an important role as a source for LCDs in lacustrine environments, or, alternatively, that the main sources of LCDs are similarly affected by temperature as the Eustigmataceae. The results suggest that LCDs may have the potential to be applicable as a palaeotemperature proxy for lacustrine environments, although further calibration work is still required.

Arctic aboveground tundra biomass dynamics between 1982 and 2010

Numerous studies have evaluated the dynamics of Arctic tundra vegetation throughout the past few decades, using remotely sensed proxies of vegetation, such as the normalized difference vegetation index (NDVI). While extremely useful, these coarse-scale satellite-derived measurements give us minimal information with regard to how these changes are being expressed on the ground, in terms of tundra structure and function. In this analysis, we used a strong regression model between NDVI and aboveground tundra phytomass, developed from extensive field-harvested measurements of vegetation biomass, to estimate the biomass dynamics of the circumpolar Arctic tundra over the period of continuous satellite records (1982-2010). We found that the southernmost tundra subzones (C-E) dominate the increases in biomass, ranging from 20 to 26%, although there was a high degree of heterogeneity across regions, floristic provinces, and vegetation types. The estimated increase in carbon of the aboveground live vegetation of 0.40 Pg C over the past three decades is substantial, although quite small relative to anthropogenic C emissions. However, a 19.8% average increase in aboveground biomass has major implications for nearly all aspects of tundra ecosystems including hydrology, active layer depths, permafrost regimes, wildlife and human use of Arctic landscapes. While spatially extensive on-the-ground measurements of tundra biomass were conducted in the development of this analysis, validation is still impossible without more repeated, long-term monitoring of Arctic tundra biomass in the field.

Desintegración vertical en la industria del automóvil en España: un caso de estudio = Vertical disintegration in the automotive industry in Spain: a case study

En los años recientes se ha producido un rápido crecimiento del comercio internacional en productos semielaborados que son diseñados, producidos y ensamblados en diferentes localizaciones a lo largo de diferentes países, debido principalmente a los siguientes motivos: el desarrollo de las tecnologías de la información, la reducción de los costes de transporte, la liberalización de los mercados de capitales, la armonización de factores institucionales, la integración económica regional que implica la reducción y la eliminación de las barreras al comercio, el desarrollo económico de los países emergentes, el uso de economías de escala, así como una desregulación del comercio internacional. Todo ello ha incrementado la competencia a nivel mundial en los mercados y ha posibilitado a las compañías tener más facilidad de acceso a potenciales mercados, así como a la adquisición de capacidades y conocimientos en otros países y a la realización de alianzas estratégicas internacionales con terceros, creando un entorno con mayor incertidumbre y más exigente para las compañías que componen una industria, y que tiene consecuencias directas en las operaciones de las compañías y en la organización de su producción. Las compañías, para adaptarse, ser competitivas y beneficiarse de este nuevo escenario globalizado y más competitivo, han externalizado partes del proceso productivo hacia proveedores especializados, creando un nuevo mercado intermedio que divide el proceso productivo, anteriormente integrado en las compañías que conforman una industria, entre dos conjuntos de empresas especializadas en esa industria. Dicho proceso suele ocurrir conservando la industria en que tiene lugar, los mismos servicios y productos, la tecnología empleada y las compañías originales que la conformaban previamente a la desintegración vertical. Todo ello es así debido a que es beneficioso tanto para las compañías originales de la industria como para las nuevas compañías de este mercado intermedio por diversos motivos. La desintegración vertical en una industria tiene unas consecuencias que la transforman completamente, así como la forma de operar de las compañías que la integran, incluso para aquellas que permanecen verticalmente integradas. Una de las características más importantes de esta desintegración vertical en una industria es la posibilidad que tiene una compañía de adquirir a una tercera la primera parte del proceso productivo o un bien semielaborado, que posteriormente será finalizado por la compañía adquiriente con la práctica del outsourcing; así mismo, una compañía puede realizar la primera parte del proceso productivo o un bien semielaborado, que posteriormente será finalizado por una tercera compañía con la práctica de la fragmentación. El principal objetivo de la presente investigación es el estudio de los motivos, los facilitadores, los efectos, las consecuencias y los principales factores significativos, microeconómicos y macroeconómicos, que desencadenan o incrementan la práctica de la desintegración vertical en una industria; para ello, la investigación se divide en dos líneas completamente diferenciadas: el estudio de la práctica del outsourcing y, por otro lado, el estudio de la fragmentación por parte de las compañías que componen la industria del automóvil en España, puesto que se trata de una de las industrias más desintegradas verticalmente y fragmentadas, y este sector posee una gran importancia en la economía del país. En primer lugar, se hace una revisión de la literatura existente relativa a los siguientes aspectos: desintegración vertical, outsourcing, fragmentación, teoría del comercio internacional, historia de la industria del automóvil en España y el uso de las aglomeraciones geográficas y las tecnologías de la información en el sector del automóvil. La metodología empleada en cada uno de ellos ha sido diferente en función de la disponibilidad de los datos y del enfoque de investigación: los factores microeconómicos, utilizando el outsourcing, y los factores macroeconómicos, empleando la fragmentación. En el estudio del outsourcing, se usa un índice basado en las compras externas sobre el valor total de la producción. Así mismo, se estudia su correlación y significación con las variables económicas más importantes que definen a una compañía del sector del automóvil, utilizando la técnica estadística de regresión lineal. Aquellas variables relacionadas con la competencia en el mercado, la externalización de las actividades de menor valor añadido y el incremento de la modularización de las actividades de la cadena de valor, han resultado significativas con la práctica del outsourcing. En el estudio de la fragmentación se seleccionan un conjunto de factores macroeconómicos, comúnmente usados en este tipo de investigaciones, relacionados con las principales magnitudes económicas de un país, y un conjunto de factores macroeconómicos, no comúnmente usados en este tipo de investigaciones, relacionados con la libertad económica y el comercio internacional de un país. Se emplea un modelo de regresión logística para identificar qué factores son significativos en la práctica de la fragmentación. De entre todos los factores usados en el modelo, los relacionados con las economías de escala y los costes de servicio han resultado significativos. Los resultados obtenidos de los test estadísticos realizados en el modelo de regresión logística han resultado satisfactorios; por ello, el modelo propuesto de regresión logística puede ser considerado sólido, fiable y versátil; además, acorde con la realidad. De los resultados obtenidos en el estudio del outsourcing y de la fragmentación, combinados conjuntamente con el estado del arte, se concluye que el principal factor que desencadena la desintegración vertical en la industria del automóvil es la competencia en el mercado de vehículos. Cuanto mayor es la demanda de vehículos, más se reducen los beneficios y la rentabilidad para sus fabricantes. Estos, para ser competitivos, diferencian sus productos de la competencia centrándose en las actividades que mayor valor añadido aportan al producto final, externalizando las actividades de menor valor añadido a proveedores especializados, e incrementando la modularidad de las actividades de la cadena de valor. Las compañías de la industria del automóvil se especializan en alguna o varias de estas actividades modularizadas que, combinadas con el uso de factores facilitadores como las economías de escala, las tecnologías de la información, las ventajas de la globalización económica y la aglomeración geográfica de una industria, incrementan y motivan la desintegración vertical en la industria del automóvil, desencadenando la coespecialización en dos sectores claramente diferenciados: el sector de fabricantes de vehículos y el sector de proveedores especializados. Cada uno de ellos se especializa en unas actividades y en unos productos o servicios específicos de la cadena de valor, lo cual genera las siguientes consecuencias en la industria del automóvil: se reducen los costes de transacción en los productos o servicios intercambiados; se incrementan la relación de dependencia entre fabricantes de vehículos y proveedores especializados, provocando un aumento en la cooperación y la coordinación, acelerando el proceso de aprendizaje, posibilitando a ambos adquirir nuevas capacidades, conocimientos y recursos, y creando nuevas ventajas competitivas para ambos; por último, las barreras de entrada a la industria del automóvil y el número de compañías se ven alteradas cambiando su estructura. Como futura línea de investigación, los fabricantes de vehículos tenderán a centrarse en investigar, diseñar y comercializar el producto o servicio, delegando el ensamblaje en manos de nuevos especialistas en la materia, el contract manufacturer; por ello, sería conveniente investigar qué factores motivantes o facilitadores existen y qué consecuencias tendría la implantación de los contract manufacturer en la industria del automóvil. 1.1. ABSTRACT In recent years there has been a rapid growth of international trade in semi-finished products designed, produced and assembled in different locations across different countries, mainly due to the following reasons: development of information technologies, reduction of transportation costs, liberalisation of capital markets, harmonisation of institutional factors, regional economic integration, which involves the reduction and elimination of trade barriers, economic development of emerging countries, use of economies of scale and deregulation of international trade. All these factors have increased competition in markets at a global level and have allowed companies to gain easier access to potential markets and to the acquisition of skills and knowledge in other countries, as well as to the completion of international strategic alliances with third parties, thus creating a more demanding and uncertain environment for these companies constituting an industry, which has a direct impact on the companies' operations and the organization of their production. In order to adapt, be competitive and benefit from this new and more competitive global scenario, companies have outsourced some parts of their production process to specialist suppliers, generating a new intermediate market which divides the production process, previously integrated in the companies that made up the industry, into two sets of companies specialized in that industry. This process often occurs while preserving the industry where it takes place, its same services and products, the technology used and the original companies that formed it prior to vertical disintegration. This is because it is beneficial for both the industry's original companies and the companies belonging to this new intermediate market, for various reasons. Vertical disintegration has consequences which completely transform the industry where it takes place as well as the modus operandi of the companies that are part of it, even of those who remain vertically integrated. One of the most important features of vertical disintegration of an industry is the possibility for a company to acquire from a third one the first part of the production process or a semi-finished product, which will then be finished by the acquiring company through the practice of outsourcing; also, a company can perform the first part of the production process or a semi-finish product, which will then be completed by a third company through the practice of fragmentation. The main objective of this research is to study the motives, facilitators, effects, consequences and major significant microeconomic and macroeconomic factors that trigger or increase the practice of vertical disintegration in a certain industry; in order to do so, research is divided into two completely differentiated lines: on the one hand, the study of the practise of outsourcing and, on the other, the study of fragmentation by companies constituting the automotive industry in Spain, since this is one of the most vertically disintegrated and fragmented industries and this particular sector is of major significance in this country's economy. First, a review is made of the existing literature, on the following aspects: vertical disintegration, outsourcing, fragmentation, international trade theory, history of the automobile industry in Spain and the use of geographical agglomeration and information technologies in the automotive sector. The methodology used for each of these aspects has been different depending on the availability of data and the research approach: the microeconomic factors, using outsourcing, and the macroeconomic factors, using fragmentation. In the study on outsourcing, an index is used based on external purchases in relation to the total value of production. Likewise, their significance and correlation with the major economic variables that define an automotive company are studied, using the statistical technique of linear regression. Variables related to market competition, outsourcing of lowest value-added activities and increased modularisation of the activities of the value chain have turned out to be significant with the practice of outsourcing. In the study of fragmentation, a set of macroeconomic factors commonly used for this type of research, is selected, related to the main economic indicators of a country, as well as a set of macroeconomic factors, not commonly used for this type of research, which are related to economic freedom and the international trade of a certain country. A logistic regression model is used to identify which factors are significant in the practice of fragmentation. Amongst all factors used in the model, those related to economies of scale and service costs have turned out to be significant. The results obtained from the statistical tests performed on the logistic regression model have been successful; hence, the suggested logistic regression model can be considered to be solid, reliable and versatile; likewise, it is in line with reality. From the results obtained in the study of outsourcing and fragmentation, combined with the state of the art, it is concluded that the main factor that triggers vertical disintegration in the automotive industry is competition within the vehicle market. The greater the vehicle demand, the lower the earnings and profitability for manufacturers. These, in order to be competitive, differentiate their products from the competition by focusing on those activities that contribute with the highest added value to the final product, outsourcing the lower valueadded activities to specialist suppliers, and increasing the modularity of the activities of the value chain. Companies in the automotive industry specialize in one or more of these modularised activities which, combined with the use of enabling factors such as economies of scale, information technologies, the advantages of economic globalisation and the geographical agglomeration of an industry, increase and encourage vertical disintegration in the automotive industry, triggering co-specialization in two clearly distinct sectors: the sector of vehicle manufacturers and the specialist suppliers sector. Each of them specializes in certain activities and specific products or services of the value chain, generating the following consequences in the automotive industry: reduction of transaction costs of the goods or services exchanged; growth of the relationship of dependency between vehicle manufacturers and specialist suppliers, which causes an increase in cooperation and coordination, accelerates the learning process, enables both to acquire new skills, knowledge and resources, and creates new competitive advantages for both; finally, barriers to entry the automotive industry and the number of companies are altered, changing their structure. As a future line of research, vehicle manufacturers will tend to focus on researching, designing and marketing the product or service, delegating the assembly in the hands of new specialists in the field, the contract manufacturer; for this reason, it would be useful to investigate what motivating or facilitating factors exist in this respect and what consequences would the implementation of contract manufacturers have in the automotive industry.

Modelling seed germination in forest tree species through survival analysis. The Pinus pinea L. case study

The direct application of existing models for seed germination may often be inadequate in the context of ecology and forestry germination experiments. This is because basic model assumptions are violated and variables available to forest managers are rarely used. In this paper, we present a method which addresses the aforementioned shortcomings. The approach is illustrated through a case study of Pinus pinea L. Our findings will also shed light on the role of germination in the general failure of natural regeneration in managed forests of this species. The presented technique consists of a mixed regression model based on survival analysis. Climate and stand covariates were tested. Data for fitting the model were gathered from a 5-year germination experiment in a mature, managed P. pinea stand in the Northern Plateau of Spain in which two different stand densities can be found. The model predictions proved to be unbiased and highly accurate when compared with the training data. Germination in P. pinea was controlled through thermal variables at stand level. At microsite level, low densities negatively affected the probability of germination. A time-lag in the response was also detected. Overall, the proposed technique provides a reliable alternative to germination modelling in ecology/forestry studies by using accessible/ suitable variables. The P. pinea case study highlights the importance of producing unbiased predictions. In this species, the occurrence and timing of germination suggest a very different regeneration strategy from that understood by forest managers until now, which may explain the high failure rate of natural regeneration in managed stands. In addition, these findings provide valuable information for the management of P. pinea under climate-change conditions.

Control by ATR-FTIR of surface treatment of cork stoppers and its effect on their mechanical performance

Fourier transform infrared (FTIR) spectroscopy was applied to determine the type of surface treatment and dose used on cork stoppers and to predict the friction between stopper and bottleneck. Agglomerated cork stoppers were finished with two different doses and using two surface treatments: P (paraffin and silicone), 15 and 25 mg/stopper, and S (only silicone), 10 and 15 mg/stopper. FTIR spectra were recorded at five points for each stopper by attenuated total reflectance (ATR). Absorbances at 1,010, 2,916, and 2,963 cm -1 were obtained in each spectrum. Discriminant analysis techniques allowed the treatment, and dose applied to each stopper to be identified from the absorbance values. 91.2% success rates were obtained from individual values and 96.0% from the mean values of each stopper. Spectrometric data also allowed treatment homogeneity to be determined on the stopper surface, and a multiple regression model was used to predict the friction index (If = Fe/Fc) (R 2 = 0.93)

Variation of PM2.5 concentrations in relation to street washing activities

Several studies conducted in urban areas have pointed out that road dust resuspension contributes significantly to PM concentration levels. Street washing is one of the methods proposed to reduce resuspended road dust contributions to ambient PM concentrations. As resuspended particles are mainly found in the coarse mode, published studies investigating the effects of street washing have focused on PM10 size fraction. As the PM2.5 mass fraction of particles originating from mechanical abrasion processes may still be significant we conducted a study in order to evaluate the effects of street washing on the mitigation of resuspension of fine particles. The PM2.5 mass concentration data were examined and integrated with the occurrence of street washing activities. In addition, the effect of the meteorological variability, traffic flow and street washing activities, on ambient PM2.5 levels was valuated by means of a multivariate regression model. The results revealed that traffic low is the most important factor that controls PM2.5 hourly concentrations while street washing activities did not influence fine particle mass levels.

Bases metodológicas para un sistema de apoyo a la selección de especies en la restauración de la vegetación

RESUMEN El apoyo a la selección de especies a la restauración de la vegetación en España en los últimos 40 años se ha basado fundamentalmente en modelos de distribución de especies, también llamados modelos de nicho ecológico, que estiman la probabilidad de presencia de las especies en función de las condiciones del medio físico (clima, suelo, etc.). Con esta tesis se ha intentado contribuir a la mejora de la capacidad predictiva de los modelos introduciendo algunas propuestas metodológicas adaptadas a los datos disponibles actualmente en España y enfocadas al uso de los modelos en la selección de especies. No siempre se dispone de datos a una resolución espacial adecuada para la escala de los proyectos de restauración de la vegetación. Sin embrago es habitual contar con datos de baja resolución espacial para casi todas las especies vegetales presentes en España. Se propone un método de recalibración que actualiza un modelo de regresión logística de baja resolución espacial con una nueva muestra de alta resolución espacial. El método permite obtener predicciones de calidad aceptable con muestras relativamente pequeñas (25 presencias de la especie) frente a las muestras mucho mayores (más de 100 presencias) que requería una estrategia de modelización convencional que no usara el modelo previo. La selección del método estadístico puede influir decisivamente en la capacidad predictiva de los modelos y por esa razón la comparación de métodos ha recibido mucha atención en la última década. Los estudios previos consideraban a la regresión logística como un método inferior a técnicas más modernas como las de máxima entropía. Los resultados de la tesis demuestran que esa diferencia observada se debe a que los modelos de máxima entropía incluyen técnicas de regularización y la versión de la regresión logística usada en las comparaciones no. Una vez incorporada la regularización a la regresión logística usando penalización, las diferencias en cuanto a capacidad predictiva desaparecen. La regresión logística penalizada es, por tanto, una alternativa más para el ajuste de modelos de distribución de especies y está a la altura de los métodos modernos con mejor capacidad predictiva como los de máxima entropía. A menudo, los modelos de distribución de especies no incluyen variables relativas al suelo debido a que no es habitual que se disponga de mediciones directas de sus propiedades físicas o químicas. La incorporación de datos de baja resolución espacial proveniente de mapas de suelo nacionales o continentales podría ser una alternativa. Los resultados de esta tesis sugieren que los modelos de distribución de especies de alta resolución espacial mejoran de forma ligera pero estadísticamente significativa su capacidad predictiva cuando se incorporan variables relativas al suelo procedente de mapas de baja resolución espacial. La validación es una de las etapas fundamentales del desarrollo de cualquier modelo empírico como los modelos de distribución de especies. Lo habitual es validar los modelos evaluando su capacidad predictiva especie a especie, es decir, comparando en un conjunto de localidades la presencia o ausencia observada de la especie con las predicciones del modelo. Este tipo de evaluación no responde a una cuestión clave en la restauración de la vegetación ¿cuales son las n especies más idóneas para el lugar a restaurar? Se ha propuesto un método de evaluación de modelos adaptado a esta cuestión que consiste en estimar la capacidad de un conjunto de modelos para discriminar entre las especies presentes y ausentes de un lugar concreto. El método se ha aplicado con éxito a la validación de 188 modelos de distribución de especies leñosas orientados a la selección de especies para la restauración de la vegetación en España. Las mejoras metodológicas propuestas permiten mejorar la capacidad predictiva de los modelos de distribución de especies aplicados a la selección de especies en la restauración de la vegetación y también permiten ampliar el número de especies para las que se puede contar con un modelo que apoye la toma de decisiones. SUMMARY During the last 40 years, decision support tools for plant species selection in ecological restoration in Spain have been based on species distribution models (also called ecological niche models), that estimate the probability of occurrence of the species as a function of environmental predictors (e.g., climate, soil). In this Thesis some methodological improvements are proposed to contribute to a better predictive performance of such models, given the current data available in Spain and focusing in the application of the models to selection of species for ecological restoration. Fine grained species distribution data are required to train models to be used at the scale of the ecological restoration projects, but this kind of data are not always available for every species. On the other hand, coarse grained data are available for almost every species in Spain. A recalibration method is proposed that updates a coarse grained logistic regression model using a new fine grained updating sample. The method allows obtaining acceptable predictive performance with reasonably small updating sample (25 occurrences of the species), in contrast with the much larger samples (more than 100 occurrences) required for a conventional modeling approach that discards the coarse grained data. The choice of the statistical method may have a dramatic effect on model performance, therefore comparisons of methods have received much interest in the last decade. Previous studies have shown a poorer performance of the logistic regression compared to novel methods like maximum entropy models. The results of this Thesis show that the observed difference is caused by the fact that maximum entropy models include regularization techniques and the versions of logistic regression compared do not. Once regularization has been added to the logistic regression using a penalization procedure, the differences in model performance disappear. Therefore, penalized logistic regression may be considered one of the best performing methods to model species distributions. Usually, species distribution models do not consider soil related predictors because direct measurements of the chemical or physical properties are often lacking. The inclusion of coarse grained soil data from national or continental soil maps could be a reasonable alternative. The results of this Thesis suggest that the performance of the models slightly increase after including soil predictors form coarse grained soil maps. Model validation is a key stage of the development of empirical models, such as species distribution models. The usual way of validating is based on the evaluation of model performance for each species separately, i.e., comparing observed species presences or absence to predicted probabilities in a set of sites. This kind of evaluation is not informative for a common question in ecological restoration projects: which n species are the most suitable for the environment of the site to be restored? A method has been proposed to address this question that estimates the ability of a set of models to discriminate among present and absent species in a evaluation site. The method has been successfully applied to the validation of 188 species distribution models used to support decisions on species selection for ecological restoration in Spain. The proposed methodological approaches improve the predictive performance of the predictive models applied to species selection in ecological restoration and increase the number of species for which a model that supports decisions can be fitted.

Perceived Health, Physical Activity and Sport among the Elderly of Spain

Purpose: It determines if participating in sports and/or physical activity influences perceived health among the elderly. Basic procedures: Data were drawn from a population subsample of subjects aged 65 - 79 years old that took part in a survey conducted in 2008 by the IESA-CSIC. A regression model was performed with perceived health status with the dependent variable and sociodemographic characteristics and physical activity as independent variables. Results: Physical activity is closely associated to per-ceived health, although sport has little influence on this relationship. Conclusions: Doing exercise or feeling that one is physically active makes the elderly feel better about their health status. However, this age group practises few sports and sport is not found to have an important or constant influence on self-perceived health status among the elderly.

Modelling uncertainty of flood quantile estimation at ungauged sites by Bayesian networks

Prediction at ungauged sites is essential for water resources planning and management. Ungauged sites have no observations about the magnitude of floods, but some site and basin characteristics are known. Regression models relate physiographic and climatic basin characteristics to flood quantiles, which can be estimated from observed data at gauged sites. However, these models assume linear relationships between variables Prediction intervals are estimated by the variance of the residuals in the estimated model. Furthermore, the effect of the uncertainties in the explanatory variables on the dependent variable cannot be assessed. This paper presents a methodology to propagate the uncertainties that arise in the process of predicting flood quantiles at ungauged basins by a regression model. In addition, Bayesian networks were explored as a feasible tool for predicting flood quantiles at ungauged sites. Bayesian networks benefit from taking into account uncertainties thanks to their probabilistic nature. They are able to capture non-linear relationships between variables and they give a probability distribution of discharges as result. The methodology was applied to a case study in the Tagus basin in Spain.