Aerial Remote Sensing in Agriculture: A Practical Approach to Area Coverage and Path Planning for Fleets of Mini Aerial Robots

In this paper, a system that allows applying precision agriculture techniques is described. The application is based on the deployment of a team of unmanned aerial vehicles that are able to take georeferenced pictures in order to create a full map by applying mosaicking procedures for postprocessing. The main contribution of this work is practical experimentation with an integrated tool. Contributions in different fields are also reported. Among them is a new one-phase automatic task partitioning manager, which is based on negotiation among the aerial vehicles, considering their state and capabilities. Once the individual tasks are assigned, an optimal path planning algorithm is in charge of determining the best path for each vehicle to follow. Also, a robust flight control based on the use of a control law that improves the maneuverability of the quadrotors has been designed. A set of field tests was performed in order to analyze all the capabilities of the system, from task negotiations to final performance. These experiments also allowed testing control robustness under different weather conditions.

Drivers in adopting adaptation strategies to face increased water scarcity in agriculture. A case study in Doñana (Spain) and Makueni (Kenya)

La agricultura es uno de los sectores más afectados por el cambio climático. A pesar de haber demostrado a lo largo de la historia una gran capacidad para adaptarse a nuevas situaciones, hoy en día la agricultura se enfrenta a nuevos retos tales como satisfacer un elevado crecimiento en la demanda de alimentos, desarrollar una agricultura sostenible con el medio ambiente y reducir las emisiones de gases de efecto invernadero. El potencial de adaptación debe ser definido en un contexto que incluya el comportamiento humano, ya que éste juega un papel decisivo en la implementación final de las medidas. Por este motivo, y para desarrollar correctamente políticas que busquen influir en el comportamiento de los agricultores para fomentar la adaptación a estas nuevas condiciones, es necesario entender previamente los procesos de toma de decisiones a nivel individual o de explotación, así como los efectos de los factores que determinan las barreras o motivaciones de la implementación de medidas. Esta Tesis doctoral trata de profundizar en el análisis de factores que influyen en la toma de decisiones de los agricultores para adoptar estrategias de adaptación al cambio climático. Este trabajo revisa la literatura actual y desarrolla un marco metodológico a nivel local y regional. Dos casos de estudio a nivel local (Doñana, España y Makueni, Kenia) han sido llevados a cabo con el fin de explorar el comportamiento de los agricultores hacia la adaptación. Estos casos de estudio representan regiones con notables diferencias en climatología, impactos del cambio climático, barreras para la adaptación y niveles de desarrollo e influencia de las instituciones públicas y privadas en la agricultura. Mientras el caso de estudio de Doñana representa un ejemplo de problemas asociados al uso y escasez del agua donde se espera que se agraven en el futuro, el caso de estudio de Makueni ejemplifica una zona fuertemente amenazada por las predicciones de cambio climático, donde adicionalmente la falta de infraestructura y la tecnología juegan un papel crucial para la implementación de la adaptación. El caso de estudio a nivel regional trata de generalizar en África el comportamiento de los agricultores sobre la implementación de medidas. El marco metodológico que se ha seguido en este trabajo abarca una amplia gama de enfoques y métodos para la recolección y análisis de datos. Los métodos utilizados para la toma de datos incluyen la implementación de encuestas, entrevistas, talleres con grupos de interés, grupos focales de discusión, revisión de estudios previos y bases de datos públicas. Los métodos analíticos incluyen métodos estadísticos, análisis multi‐criterio para la toma de decisiones, modelos de optimización de uso del suelo y un índice compuesto calculado a través de indicadores. Los métodos estadísticos se han utilizado con el fin de evaluar la influencia de los factores socio‐económicos y psicológicos sobre la adopción de medidas de adaptación. Dentro de estos métodos se incluyen regresiones logísticas, análisis de componentes principales y modelos de ecuaciones estructurales. Mientras que el análisis multi‐criterio se ha utilizado con el fin de evaluar las opciones de adaptación de acuerdo a las opiniones de las diferentes partes interesadas, el modelo de optimización ha tenido como fin analizar la combinación óptima de medidas de adaptación. El índice compuesto se ha utilizado para evaluar a nivel regional la implementación de medidas de adaptación en África. En general, los resultados del estudio ponen de relieve la gran importancia de considerar diferentes escalas espaciales a la hora de evaluar la implementación de medidas de adaptación al cambio climático. El comportamiento de los agricultores es diferente entre lugares considerados a una escala local relativamente pequeña, por lo que la generalización de los patrones del comportamiento a escalas regionales o globales resulta relativamente compleja. Los resultados obtenidos han permitido identificar factores determinantes tanto socioeconómicos como psicológicos y calcular su efecto sobre la adopción de medidas de adaptación. Además han proporcionado una mejor comprensión del distinto papel que desempeñan los cinco tipos de capital (natural, físico, financiero, social y humano) en la implementación de estrategias de adaptación. Con este trabajo se proporciona información de gran interés en los procesos de desarrollo de políticas destinadas a mejorar el apoyo de la sociedad a tomar medidas contra el cambio climático. Por último, en el análisis a nivel regional se desarrolla un índice compuesto que muestra la probabilidad de adoptar medidas de adaptación en las regiones de África y se analizan las causas que determinan dicha probabilidad de adopción de medidas. ABSTRACT Agriculture is and will continue to be one of the sectors most affected by climate change. Despite having demonstrated throughout history a great ability to adapt, agriculture today faces new challenges such as meeting growing food demands, developing sustainable agriculture and reducing greenhouse gas emissions. Adaptation policies planned on global, regional or local scales are ultimately implemented in decision‐making processes at the farm or individual level so adaptation potentials have to be set within the context of individual behaviour and regional institutions. Policy instruments can play a formative role in the adoption of such policies by addressing incentives/disincentives that influence farmer’s behaviour. Hence understanding farm‐level decision‐making processes and the influence of determinants of adoption is crucial when designing policies aimed at fostering adoption. This thesis seeks to analyse the factors that influence decision‐making by farmers in relation to the uptake of adaptation options. This work reviews the current knowledge and develops a methodological framework at local and regional level. Whilst the case studies at the local level are conducted with the purpose of exploring farmer’s behaviour towards adaptation the case study at the regional level attempts to up‐scale and generalise theory on adoption of farmlevel adaptation options. The two case studies at the local level (Doñana, Spain and Makueni, Kenya) encompass areas with different; climates, impacts of climate change, adaptation constraints and limits, levels of development, institutional support for agriculture and influence from public and private institutions. Whilst the Doñana Case Study represents an area plagued with water‐usage issues, set to be aggravated further by climate change, Makueni Case study exemplifies an area decidedly threatened by climate change where a lack of infrastructure and technology plays a crucial role in the uptake of adaptation options. The proposed framework is based on a wide range of approaches for collecting and analysing data. The approaches used for data collection include the implementation of surveys, interviews, stakeholder workshops, focus group discussions, a review of previous case studies, and public databases. The analytical methods include statistical approaches, multi criteria analysis for decision‐making, land use optimisation models, and a composite index based on public databases. Statistical approaches are used to assess the influence of socio‐economic and psychological factors on the adoption or support for adaptation measures. The statistical approaches used are logistic regressions, principal component analysis and structural equation modelling. Whilst a multi criteria analysis approach is used to evaluate adaptation options according to the different perspectives of stakeholders, the optimisation model analyses the optimal combination of adaptation options. The composite index is developed to assess adoption of adaptation measures in Africa. Overall, the results of the study highlight the importance of considering various scales when assessing adoption of adaptation measures to climate change. As farmer’s behaviour varies at a local scale there is elevated complexity when generalising behavioural patterns for farmers at regional or global scales. The results identify and estimate the effect of most relevant socioeconomic and psychological factors that influence adoption of adaptation measures to climate change. They also provide a better understanding of the role of the five types of capital (natural, physical, financial, social, and human) on the uptake of farm‐level adaptation options. These assessments of determinants help to explain adoption of climate change measures and provide helpful information in order to design polices aimed at enhancing societal support for adaptation policies. Finally the analysis at the regional level develops a composite index which suggests the likelihood of the regions in Africa to adopt farm‐level adaptation measures and analyses the main causes of this likelihood of adoption.

Climate Change, Water Scarcity in Agriculture and The Country-Level Economic Impacts. A Multimarket Analysis

Climate Change, Water Scarcity in Agriculture and the Country-Level Economic Impacts. A Multimarket Analysis. Abstract: Agriculture could be one of the most vulnerable economic sectors to the impacts of climate change in the coming decades. Considering the critical role that water plays for agricultural production, any shock in water availability will have great implications for agricultural production, land allocation, and agricultural prices. In this paper, an Agricultural Multimarket model is developed to analyze climate change impacts in developing countries, accounting for the uncertainty associated with the impacts of climate change. The model has a structure flexible enough to represent local conditions, resource availability, and market conditions. The results suggest different economic consequences of climate change depending on the specific activity, with many distributional effects across regions

Effect of nano-Si2O and nano-Al2O3 on cement mortars for use in agriculture and livestock production

The effect of nano-silica, nano-alumina and binary combinations on surface hardness, resistance to abrasion and freeze-thaw cycle resistance in cement mortars was investigated. The Vickers hardness, the Los Angeles coefficient (LA) and the loss of mass in each of the freeze–thaw cycles to which the samples were subjected were measured. Four cement mortars CEM I 52.5R were prepared, one as control, and the other three with the additions: 5% nano-Si, 5% nano-Al and mix 2.5% n-Si and 2.5% n-Al. Mortars were tested at 7, 28 and 90 d of curing to determine compression strength, total porosity and pore distribution by mercury intrusion porosimetry (MIP) and the relationship between the CSH gel and Portlandite total by thermal gravimetric analysis (TGA). The capillary suction coefficient and an analysis by a scanning electron microscope (SEM) was made. There was a large increase in Vickers surface hardness for 5% n-Si mortar and a slight increase in resistance to abrasion. No significant difference was found between the mortars with nano-particles, whose LA was about 10.8, classifying them as materials with good resistance to abrasion. The microstructure shows that the addition of n-Si in mortars refines their porous matrix, increases the amount of hydrated gels and generates significant changes in both Portlandite and Ettringite. This produced a significant improvement in freeze–thaw cycle resistance. The effect of n-Al on mortar was null or negative with respect to freeze–thaw cycle resistance.

Self-similar motion of laser fusion plasmas. Absorption in an unbounded plasma

The one-dimensional motion generated in a cold, infinite, uniform plasma of density na by the absorption, in a certain plane, of a linear pulse of energy per unit time and area = 4>0t/r, 0< t< r, is considered, the analysis allows for thermal conduction and viscosity of ions and electrons, their energy exchange, and an electron heat flux limiter The resulting motion is self-similar and governed by a single nondimensional parameter a«(n0 2T/0)2/3 Detailed asymptotic results are obtained for both a < l and a > l , the general behavior of the solution for arbitrary a is discussed The analysis can be extended to the case of a plasma initially occupying a half-space, and throws light on how to optimize the hydrodynamics of laser fusion plasmas Known approximate results corresponding to motion of a plasma submitted to constant irradiation (<()) are recovered in the present work under appropriate limiting processes

An example of integration between en economic and an hydrologic model in the framework of water resource management problems

Growing scarcity, increasing demand and bad management of water resources are causing weighty competition for water and consequently managers are facing more and more pressure in an attempt to satisfy users? requirement. In many regions agriculture is one of the most important users at river basin scale since it concentrates high volumes of water consumption during relatively short periods (irrigation season), with a significant economic, social and environmental impact. The interdisciplinary characteristics of related water resources problems require, as established in the Water Framework Directive 2000/60/EC, an integrated and participative approach to water management and assigns an essential role to economic analysis as a decision support tool. For this reason, a methodology is developed to analyse the economic and environmental implications of water resource management under different scenarios, with a focus on the agricultural sector. This research integrates both economic and hydrologic components in modelling, defining scenarios of water resource management with the goal of preventing critical situations, such as droughts. The model follows the Positive Mathematical Programming (PMP) approach, an innovative methodology successfully used for agricultural policy analysis in the last decade and also applied in several analyses regarding water use in agriculture. This approach has, among others, the very important capability of perfectly calibrating the baseline scenario using a very limited database. However one important disadvantage is its limited capacity to simulate activities non-observed during the reference period but which could be adopted if the scenario changed. To overcome this problem the classical methodology is extended in order to simulate a more realistic farmers? response to new agricultural policies or modified water availability. In this way an economic model has been developed to reproduce the farmers? behaviour within two irrigation districts in the Tiber High Valley. This economic model is then integrated with SIMBAT, an hydrologic model developed for the Tiber basin which allows to simulate the balance between the water volumes available at the Montedoglio dam and the water volumes required by the various irrigation users.

Automatic segmentation of relevant textures in agricultural images

One important issue emerging strongly in agriculture is related with the automatization of tasks, where the optical sensors play an important role. They provide images that must be conveniently processed. The most relevantimage processing procedures require the identification of green plants, in our experiments they come from barley and corn crops including weeds, so that some types of action can be carried out, including site-specific treatments with chemical products or mechanical manipulations. Also the identification of textures belonging to the soil could be useful to know some variables, such as humidity, smoothness or any others. Finally, from the point of view of the autonomous robot navigation, where the robot is equipped with the imaging system, some times it is convenient to know not only the soil information and the plants growing in the soil but also additional information supplied by global references based on specific areas. This implies that the images to be processed contain textures of three main types to be identified: green plants, soil and sky if any. This paper proposes a new automatic approach for segmenting these main textures and also to refine the identification of sub-textures inside the main ones. Concerning the green identification, we propose a new approach that exploits the performance of existing strategies by combining them. The combination takes into account the relevance of the information provided by each strategy based on the intensity variability. This makes an important contribution. The combination of thresholding approaches, for segmenting the soil and the sky, makes the second contribution; finally the adjusting of the supervised fuzzy clustering approach for identifying sub-textures automatically, makes the third finding. The performance of the method allows to verify its viability for automatic tasks in agriculture based on image processing

Real-time image processing for crop/weed discrimination in maize fields

This paper presents a computer vision system that successfully discriminates between weed patches and crop rows under uncontrolled lighting in real-time. The system consists of two independent subsystems, a fast image processing delivering results in real-time (Fast Image Processing, FIP), and a slower and more accurate processing (Robust Crop Row Detection, RCRD) that is used to correct the first subsystem's mistakes. This combination produces a system that achieves very good results under a wide variety of conditions. Tested on several maize videos taken of different fields and during different years, the system successfully detects an average of 95% of weeds and 80% of crops under different illumination, soil humidity and weed/crop growth conditions. Moreover, the system has been shown to produce acceptable results even under very difficult conditions, such as in the presence of dramatic sowing errors or abrupt camera movements. The computer vision system has been developed for integration into a treatment system because the ideal setup for any weed sprayer system would include a tool that could provide information on the weeds and crops present at each point in real-time, while the tractor mounting the spraying bar is moving

Conceptual framework for the design, implementation and validation of psychomotor skills’ assessment systems in minimally invasive surgery

Las técnicas de cirugía de mínima invasión (CMI) se están consolidando hoy en día como alternativa a la cirugía tradicional, debido a sus numerosos beneficios para los pacientes. Este cambio de paradigma implica que los cirujanos deben aprender una serie de habilidades distintas de aquellas requeridas en cirugía abierta. El entrenamiento y evaluación de estas habilidades se ha convertido en una de las mayores preocupaciones en los programas de formación de cirujanos, debido en gran parte a la presión de una sociedad que exige cirujanos bien preparados y una reducción en el número de errores médicos. Por tanto, se está prestando especial atención a la definición de nuevos programas que permitan el entrenamiento y la evaluación de las habilidades psicomotoras en entornos seguros antes de que los nuevos cirujanos puedan operar sobre pacientes reales. Para tal fin, hospitales y centros de formación están gradualmente incorporando instalaciones de entrenamiento donde los residentes puedan practicar y aprender sin riesgos. Es cada vez más común que estos laboratorios dispongan de simuladores virtuales o simuladores físicos capaces de registrar los movimientos del instrumental de cada residente. Estos simuladores ofrecen una gran variedad de tareas de entrenamiento y evaluación, así como la posibilidad de obtener información objetiva de los ejercicios. Los diferentes estudios de validación llevados a cabo dan muestra de su utilidad; pese a todo, los niveles de evidencia presentados son en muchas ocasiones insuficientes. Lo que es más importante, no existe un consenso claro a la hora de definir qué métricas son más útiles para caracterizar la pericia quirúrgica. El objetivo de esta tesis doctoral es diseñar y validar un marco de trabajo conceptual para la definición y validación de entornos para la evaluación de habilidades en CMI, en base a un modelo en tres fases: pedagógica (tareas y métricas a emplear), tecnológica (tecnologías de adquisición de métricas) y analítica (interpretación de la competencia en base a las métricas). Para tal fin, se describe la implementación práctica de un entorno basado en (1) un sistema de seguimiento de instrumental fundamentado en el análisis del vídeo laparoscópico; y (2) la determinación de la pericia en base a métricas de movimiento del instrumental. Para la fase pedagógica se diseñó e implementó un conjunto de tareas para la evaluación de habilidades psicomotoras básicas, así como una serie de métricas de movimiento. La validación de construcción llevada a cabo sobre ellas mostró buenos resultados para tiempo, camino recorrido, profundidad, velocidad media, aceleración media, economía de área y economía de volumen. Adicionalmente, los resultados obtenidos en la validación de apariencia fueron en general positivos en todos los grupos considerados (noveles, residentes, expertos). Para la fase tecnológica, se introdujo el EVA Tracking System, una solución para el seguimiento del instrumental quirúrgico basado en el análisis del vídeo endoscópico. La precisión del sistema se evaluó a 16,33ppRMS para el seguimiento 2D de la herramienta en la imagen; y a 13mmRMS para el seguimiento espacial de la misma. La validación de construcción con una de las tareas de evaluación mostró buenos resultados para tiempo, camino recorrido, profundidad, velocidad media, aceleración media, economía de área y economía de volumen. La validación concurrente con el TrEndo® Tracking System por su parte presentó valores altos de correlación para 8 de las 9 métricas analizadas. Finalmente, para la fase analítica se comparó el comportamiento de tres clasificadores supervisados a la hora de determinar automáticamente la pericia quirúrgica en base a la información de movimiento del instrumental, basados en aproximaciones lineales (análisis lineal discriminante, LDA), no lineales (máquinas de soporte vectorial, SVM) y difusas (sistemas adaptativos de inferencia neurodifusa, ANFIS). Los resultados muestran que en media SVM presenta un comportamiento ligeramente superior: 78,2% frente a los 71% y 71,7% obtenidos por ANFIS y LDA respectivamente. Sin embargo las diferencias estadísticas medidas entre los tres no fueron demostradas significativas. En general, esta tesis doctoral corrobora las hipótesis de investigación postuladas relativas a la definición de sistemas de evaluación de habilidades para cirugía de mínima invasión, a la utilidad del análisis de vídeo como fuente de información y a la importancia de la información de movimiento de instrumental a la hora de caracterizar la pericia quirúrgica. Basándose en estos cimientos, se han de abrir nuevos campos de investigación que contribuyan a la definición de programas de formación estructurados y objetivos, que puedan garantizar la acreditación de cirujanos sobradamente preparados y promocionen la seguridad del paciente en el quirófano. Abstract Minimally invasive surgery (MIS) techniques have become a standard in many surgical sub-specialties, due to their many benefits for patients. However, this shift in paradigm implies that surgeons must acquire a complete different set of skills than those normally attributed to open surgery. Training and assessment of these skills has become a major concern in surgical learning programmes, especially considering the social demand for better-prepared professionals and for the decrease of medical errors. Therefore, much effort is being put in the definition of structured MIS learning programmes, where practice with real patients in the operating room (OR) can be delayed until the resident can attest for a minimum level of psychomotor competence. To this end, skills’ laboratory settings are being introduced in hospitals and training centres where residents may practice and be assessed on their psychomotor skills. Technological advances in the field of tracking technologies and virtual reality (VR) have enabled the creation of new learning systems such as VR simulators or enhanced box trainers. These systems offer a wide range of tasks, as well as the capability of registering objective data on the trainees’ performance. Validation studies give proof of their usefulness; however, levels of evidence reported are in many cases low. More importantly, there is still no clear consensus on topics such as the optimal metrics that must be used to assess competence, the validity of VR simulation, the portability of tracking technologies into real surgeries (for advanced assessment) or the degree to which the skills measured and obtained in laboratory environments transfer to the OR. The purpose of this PhD is to design and validate a conceptual framework for the definition and validation of MIS assessment environments based on a three-pillared model defining three main stages: pedagogical (tasks and metrics to employ), technological (metric acquisition technologies) and analytical (interpretation of competence based on metrics). To this end, a practical implementation of the framework is presented, focused on (1) a video-based tracking system and (2) the determination of surgical competence based on the laparoscopic instruments’ motionrelated data. The pedagogical stage’s results led to the design and implementation of a set of basic tasks for MIS psychomotor skills’ assessment, as well as the definition of motion analysis parameters (MAPs) to measure performance on said tasks. Validation yielded good construct results for parameters such as time, path length, depth, average speed, average acceleration, economy of area and economy of volume. Additionally, face validation results showed positive acceptance on behalf of the experts, residents and novices. For the technological stage the EVA Tracking System is introduced. EVA provides a solution for tracking laparoscopic instruments from the analysis of the monoscopic video image. Accuracy tests for the system are presented, which yielded an average RMSE of 16.33pp for 2D tracking of the instrument on the image and of 13mm for 3D spatial tracking. A validation experiment was conducted using one of the tasks and the most relevant MAPs. Construct validation showed significant differences for time, path length, depth, average speed, average acceleration, economy of area and economy of volume; especially between novices and residents/experts. More importantly, concurrent validation with the TrEndo® Tracking System presented high correlation values (>0.7) for 8 of the 9 MAPs proposed. Finally, the analytical stage allowed comparing the performance of three different supervised classification strategies in the determination of surgical competence based on motion-related information. The three classifiers were based on linear (linear discriminant analysis, LDA), non-linear (support vector machines, SVM) and fuzzy (adaptive neuro fuzzy inference systems, ANFIS) approaches. Results for SVM show slightly better performance than the other two classifiers: on average, accuracy for LDA, SVM and ANFIS was of 71.7%, 78.2% and 71% respectively. However, when confronted, no statistical significance was found between any of the three. Overall, this PhD corroborates the investigated research hypotheses regarding the definition of MIS assessment systems, the use of endoscopic video analysis as the main source of information and the relevance of motion analysis in the determination of surgical competence. New research fields in the training and assessment of MIS surgeons can be proposed based on these foundations, in order to contribute to the definition of structured and objective learning programmes that guarantee the accreditation of well-prepared professionals and the promotion of patient safety in the OR.

Sustainability of irrigated farming systems in a Tunisian region: A recursive stochastic programming analysis

The aim of this study was to evaluate the sustainability of farm irrigation systems in the Cébalat district in northern Tunisia. It addressed the challenging topic of sustainable agriculture through a bio-economic approach linking a biophysical model to an economic optimisation model. A crop growth simulation model (CropSyst) was used to build a database to determine the relationships between agricultural practices, crop yields and environmental effects (salt accumulation in soil and leaching of nitrates) in a context of high climatic variability. The database was then fed into a recursive stochastic model set for a 10-year plan that allowed analysing the effects of cropping patterns on farm income, salt accumulation and nitrate leaching. We assumed that the long-term sustainability of soil productivity might be in conflict with farm profitability in the short-term. Assuming a discount rate of 10% (for the base scenario), the model closely reproduced the current system and allowed to predict the degradation of soil quality due to long-term salt accumulation. The results showed that there was more accumulation of salt in the soil for the base scenario than for the alternative scenario (discount rate of 0%). This result was induced by applying a higher quantity of water per hectare for the alternative as compared to a base scenario. The results also showed that nitrogen leaching is very low for the two discount rates and all climate scenarios. In conclusion, the results show that the difference in farm income between the alternative and base scenarios increases over time to attain 45% after 10 years.

Wheel-Rail Contact Forces in High-Speed Simply Supported Bridges at Resonance

The response of high-speed bridges at resonance, particularly under flexural vibrations, constitutes a subject of research for many scientists and engineers at the moment. The topic is of great interest because, as a matter of fact, such kind of behaviour is not unlikely to happen due to the elevated operating speeds of modern rains, which in many cases are equal to or even exceed 300 km/h ( [1,2]). The present paper addresses the subject of the evolution of the wheel-rail contact forces during resonance situations in simply supported bridges. Based on a dimensionless formulation of the equations of motion presented in [4], very similar to the one introduced by Klasztorny and Langer in [3], a parametric study is conducted and the contact forces in realistic situations analysed in detail. The effects of rail and wheel irregularities are not included in the model. The bridge is idealised as an Euler-Bernoulli beam, while the train is simulated by a system consisting of rigid bodies, springs and dampers. The situations such that a severe reduction of the contact force could take place are identified and compared with typical situations in actual bridges. To this end, the simply supported bridge is excited at resonace by means of a theoretical train consisting of 15 equidistant axles. The mechanical characteristics of all axles (unsprung mass, semi-sprung mass, and primary suspension system) are identical. This theoretical train permits the identification of the key parameters having an influence on the wheel-rail contact forces. In addition, a real case of a 17.5 m bridges traversed by the Eurostar train is analysed and checked against the theoretical results. The influence of three fundamental parameters is investigated in great detail: a) the ratio of the fundamental frequency of the bridge and natural frequency of the primary suspension of the vehicle; b) the ratio of the total mass of the bridge and the semi-sprung mass of the vehicle and c) the ratio between the length of the bridge and the characteristic distance between consecutive axles. The main conclusions derived from the investigation are: The wheel-rail contact forces undergo oscillations during the passage of the axles over the bridge. During resonance, these oscillations are more severe for the rear wheels than for the front ones. If denotes the span of a simply supported bridge, and the characteristic distance between consecutive groups of loads, the lower the value of , the greater the oscillations of the contact forces at resonance. For or greater, no likelihood of loss of wheel-rail contact has been detected. The ratio between the frequency of the primary suspension of the vehicle and the fundamental frequency of the bridge is denoted by (frequency ratio), and the ratio of the semi-sprung mass of the vehicle (mass of the bogie) and the total mass of the bridge is denoted by (mass ratio). For any given frequency ratio, the greater the mass ratio, the greater the oscillations of the contact forces at resonance. The oscillations of the contact forces at resonance, and therefore the likelihood of loss of wheel-rail contact, present a minimum for approximately between 0.5 and 1. For lower or higher values of the frequency ratio the oscillations of the contact forces increase. Neglecting the possible effects of torsional vibrations, the metal or composite bridges with a low linear mass have been found to be the ones where the contact forces may suffer the most severe oscillations. If single-track, simply supported, composite or metal bridges were used in high-speed lines, and damping ratios below 1% were expected, the minimum contact forces at resonance could drop to dangerous values. Nevertheless, this kind of structures is very unusual in modern high-speed railway lines.

Molecular basis of salt tolerance in Physcomitrella Patens model plant: potassium homeostasis and physiological roles of chx transporters

El suelo salino impone un estrés abiótico importante que causa graves problemas en la agricultura ya que la mayoría de los cultivos se ven afectados por la salinidad debido a efectos osmóticos y tóxicos. Por ello, la contaminación y la escasez de agua dulce, la salinización progresiva de tierras y el aumento exponencial de la población humana representan un grave problema que amenaza la seguridad alimentaria mundial para las generaciones futuras. Por lo tanto, aumentar la tolerancia a la salinidad de los cultivos es un objetivo estratégico e ineludible para garantizar el suministro de alimentos en el futuro. Mantener una óptima homeostasis de K+ en plantas que sufren estrés salino es un objetivo importante en el proceso de obtención de plantas tolerantes a la salinidad. Aunque el modelo de la homeostasis de K+ en las plantas está razonablemente bien descrito en términos de entrada de K+, muy poco se sabe acerca de los genes implicados en la salida de K+ o de su liberación desde la vacuola. En este trabajo se pretende aclarar algunos de los mecanismos implicados en la homeostasis de K+ en plantas. Para ello se eligió la briofita Physcomitrella patens, una planta no vascular de estructura simple y de fase haploide dominante que, entre muchas otras cualidades, hacen que sea un modelo ideal. Lo más importante es que no sólo P. patens es muy tolerante a altas concentraciones de Na+, sino que también su posición filogenética en la evolución de las plantas abre la posibilidad de estudiar los cambios claves que, durante el curso de la evolución, se produjeron en las diversas familias de los transportadores de K+. Se han propuesto varios transportadores de cationes como candidatos que podrían tener un papel en la salida de K+ o su liberación desde la vacuola, especialmente miembros de la familia CPA2 que contienen las familias de transportadores KEA y CHX. En este estudio se intenta aumentar nuestra comprensión de las funciones de los transportadores de CHX en las células de las plantas usando P. patens, como ya se ha dicho. En esta especie, se han identificado cuatro genes CHX, PpCHX1-4. Dos de estos genes, PpCHX1 y PpCHX2, se expresan aproximadamente al mismo nivel que el gen PpACT5, y los otros dos genes muestran una expresión muy baja. La expresión de PpCHX1 y PpCHX2 en mutantes de Escherichia coli defectivos en el transporte de K+ restauraron el crecimiento de esta cepa en medios con bajo contenido de K+, lo que viii sugiere que la entrada de K+ es energizada por un mecanismo de simporte con H+. Por otra parte, estos transportadores suprimieron el defecto asociado a la mutación kha1 en Saccharomyces cerevisiae, lo que sugiere que podrían mediar un antiporte en K+/H+. La proteína PpCHX1-GFP expresada transitoriamente en protoplastos de P. patens co-localizó con un marcador de Golgi. En experimentos similares, la proteína PpCHX2-GFP localizó aparentemente en la membrana plasmática y tonoplasto. Se construyeron las líneas mutantes simples de P. patens ΔPpchx1 y ΔPpchx2, y también el mutante doble ΔPpchx2 ΔPphak1. Los mutantes simples crecieron normalmente en todas las condiciones ensayadas y mostraron flujos de entrada normales de K+ y Rb+; la mutación ΔPpchx2 no aumentó el defecto de las plantas ΔPphak1. En experimentos a largo plazo, las plantas ΔPpchx2 mostraron una retención de Rb+ ligeramente superior que las plantas silvestres, lo que sugiere que PpCHX2 promueve la transferencia de Rb+ desde la vacuola al citosol o desde el citosol al medio externo, actuando en paralelo con otros transportadores. Sugerimos que transportadores de K+ de varias familias están involucrados en la homeostasis de pH de orgánulos ya sea mediante antiporte K+/H+ o simporte K+-H+.ix ABSTRACT Soil salinity is a major abiotic stress causing serious problems in agriculture as most crops are affected by it. Moreover, the contamination and shortage of freshwater, progressive land salinization and exponential increase of human population aggravates the problem implying that world food security may not be ensured for the next generations. Thus, a strategic and an unavoidable goal would be increasing salinity tolerance of plant crops to secure future food supply. Maintaining an optimum K+ homeostasis in plants under salinity stress is an important trait to pursue in the process of engineering salt tolerant plants. Although the model of K+ homeostasis in plants is reasonably well described in terms of K+ influx, very little is known about the genes implicated in K+ efflux or release from the vacuole. In this work, we aim to clarify some of the mechanisms involved in K+ homeostasis in plants. For this purpose, we chose the bryophyte plant Physcomitrella patens, a nonvascular plant of simple structure and dominant haploid phase that, among many other characteristics, makes it an ideal model. Most importantly, not only P. patens is very tolerant to high concentrations of Na+, but also its phylogenetic position in land plant evolution opens the possibility to study the key changes that occurred in K+ transporter families during the course of evolution. Several cation transporter candidates have been proposed to have a role in K+ efflux or release from the vacuole especially members of the CPA2 family which contains the KEA and CHX transporter families. We intended in this study to increase our understanding of the functions of CHX transporters in plant cells using P. patens, in which four CHX genes have been identified, PpCHX1-4. Two of these genes, PpCHX1 and PpCHX2, are expressed at approximately the same level as the PpACT5 gene, but the other two genes show an extremely low expression. PpCHX1 and PpCHX2 restored growth of Escherichia coli mutants on low K+-containing media, suggesting they mediated K+ uptake that may be energized by symport with H+. In contrast, these genes suppressed the defect associated to the kha1 mutation in Saccharomyces cerevisiae, which suggest that they might mediate K+/H+ antiport. PpCHX1-GFP protein transiently expressed in P. patens protoplasts co-localized with a Golgi marker. In similar experiments, the PpCHX2-GFP protein appeared to localize to tonoplast and plasma x membrane. We constructed the ΔPpchx1 and ΔPpchx2 single mutant lines, and the ΔPpchx2 ΔPphak1 double mutant. Single mutant plants grew normally under all the conditions tested and exhibited normal K+ and Rb+ influxes; the ΔPpchx2 mutation did not increase the defect of ΔPphak1 plants. In long-term experiments, ΔPpchx2 plants showed a slightly higher Rb+ retention than wild type plants, which suggests that PpCHX2 mediates the transfer of Rb+ from either the vacuole to the cytosol or from the cytosol to the external medium in parallel with other transporters. We suggest that K+ transporters of several families are involved in the pH homeostasis of organelles by mediating either K+/H+ antiport or K+-H+ symport.

Dynamic Soil-Structure Interaction in Bridge Abutments

Strong motion obtained in instrumental short-span bridges show the importance of the abutments in the dynamic response of the whole structure. Many models have been used in order to take into account the influence of pier foundations although no reliable ones have been used to analyse the abutment performance. In this work three-dimensional Boundary Element models in frequency domain have been proposed and dimensionless dynamic stiffness of standard bridge abutments have been obtained.

Farm nitrogen balances in six European landscapes as an indicator for nitrogen losses and basis for improved management.

Improved management of nitrogen (N) in agriculture is necessary to achieve a sustainable balance between the production of food and other biomass, and the unwanted effects of N on water pollution, greenhouse gas emissions, biodiversity deterioration and human health. To analyse farm N-losses and the complex interactions within farming systems, efficient methods for identifying emissions hotspots and evaluating mitigation measures are therefore needed. The present paper aims to fill this gap at the farm and landscape scales. Six agricultural landscapes in Poland (PL), the Netherlands (NL), France (FR), Italy (IT), Scotland (UK) and Denmark (DK) were studied, and a common method was developed for undertaking farm inventories and the derivation of farm N balances, N surpluses and for evaluating uncertainty for the 222 farms and 11 440 ha of farmland included in the study. In all landscapes, a large variation in the farm N surplus was found, and thereby a large potential for reductions. The highest average N surpluses were found in the most livestock-intensive landscapes of IT, FR, and NL; on average 202 ± 28, 179 ± 63 and 178 ± 20 kg N ha−1 yr−1, respectively. All landscapes showed hotspots, especially from livestock farms, including a special UK case with large-scale landless poultry farming. Overall, the average N surplus from the land-based UK farms dominated by extensive sheep and cattle grazing was only 31 ± 10 kg N ha−1 yr−1, but was similar to the N surplus of PL and DK (122 ± 20 and 146 ± 55 kg N ha−1 yr−1, respectively) when landless poultry farming was included. We found farm N balances to be a useful indicator for N losses and the potential for improving N management. Significant correlations to N surplus were found, both with ammonia air concentrations and nitrate concentrations in soils and groundwater, measured during the period of N management data collection in the landscapes from 2007–2009. This indicates that farm N surpluses may be used as an independent dataset for validation of measured and modelled N emissions in agricultural landscapes. No significant correlation was found with N measured in surface waters, probably because of spatial and temporal variations in groundwater buffering and biogeochemical reactions affecting N flows from farm to surface waters. A case study of the development in N surplus from the landscape in DK from 1998–2008 showed a 22% reduction related to measures targeted at N emissions from livestock farms. Based on the large differences in N surplus between average N management farms and the most modern and N-efficient farms, it was concluded that additional N-surplus reductions of 25–50%, as compared to the present level, were realistic in all landscapes. The implemented N-surplus method was thus effective for comparing and synthesizing results on farm N emissions and the potentials of mitigation options. It is recommended for use in combination with other methods for the assessment of landscape N emissions and farm N efficiency, including more detailed N source and N sink hotspot mapping, measurements and modelling.

Probabilistic analysis of water availability for agriculture and associated crop net margins.

Rising water demands are difficult to meet in many regions of the world. In consequence, under meteorological adverse conditions, big economic losses in agriculture can take place. This paper aims to analyze the variability of water shortage in an irrigation district and the effect on farmer?s income. A probabilistic analysis of water availability for agriculture in the irrigation district is performed, through a supply-system simulation approach, considering stochastically generated series of stream-flows. Net margins associated to crop production are as well estimated depending on final water allocations. Net margins are calculated considering either single-crop farming, either a polyculture system. In a polyculture system, crop distribution and water redistribution are calculated through an optimization approach using the General Algebraic Modeling System (GAMS) for several scenarios of irrigation water availability. Expected net margins are obtained by crop and for the optimal crop and water distribution. The maximum expected margins are obtained for the optimal crop combination, followed by the alfalfa monoculture, maize, rice, wheat and finally barley. Water is distributed as follows, from biggest to smallest allocation: rice, alfalfa, maize, wheat and barley.