TOWARDS MORE SOCIALLY RESPONSIBLE COCOA TRADE

Cocoa is a classic Third World cash crop. It is produced mostly by small, poor farmers in Africa, while its products - chocolate and sun tan oil - are consumed by rich consumers in North America and Europe. A few West African economies are highly dependent on foreign exchange earned from cocoa sales. It has therefore been targeted by Oxfam's Fair Trade initiative, and IITA's Sustainable Tree Crops Program (STCP) is launching an effort of become more aligned with consumer's social preferences. The most obvious dimension to addressing consumer demand for cocoa products is to insure provision of high quality products, which has become problematic since structural adjustment programs have dismantled the African parastatals governing cocoa production and exports. Cocoa production would also likely meet requirements for organic certification in many instances, but legitimately obtaining that certification would be costly. Cocoa also offers several dimensions through which consumers might, by their market choices, insure more socially responsible outcomes. Both the STCP and Fair Trade initiatives focus on the potential for poverty alleviation and on achieving sustainable development for poor African farmers. Those farmers are stewards of the rain forest, and their production decisions can determine whether cocoa remains a rain forest friendly crop, so global environmental impacts can also be influenced by cocoa markets. The most recent, most widely publicized, and most intractable issue to hit the cocoa market is the allegation that child labor may be used on those poor African cocoa farms. The first objective of this paper will be to describe this situation, and the problems of cocoa markets, focusing on what has been happening in Africa. Particular attention will be paid to the problems of implementing structural adjustment reforms, and the increasing role played by multi-national processors as they backward integrate into the African marketing systems. Then the Fair Trade and STCP initiatives will be described. Finally, a conceptual examination of marketing systems between the African cocoa farm and the chocolate manufacturer, emphasizing institutional arrangements, is used to assess the likely success of these initiatives in achieving their social goals.Institutional and Behavioral Economics, International Relations/Trade,

Mining Web Dynamics for Search

Billions of web users collectively contribute to a dynamic web that preserves how information sources and descriptions change over time. This dynamic process sheds light on the quality of web content, and even indicates the temporal properties of information needs expressed via queries. However, existing commercial search engines typically utilize one crawl of web content (the latest) without considering the complementary information concealed in web dynamics. As a result, the generated rankings may be biased due to the efficiency of knowledge on page or hyperlink evolution, and the time-sensitive facet within search quality, e.g., freshness, has to be neglected. While previous research efforts have been focused on exploring the temporal dimension in retrieval process, few of them showed consistent improvements on large-scale real-world archival web corpus with a broad time span.We investigate how to utilize the changes of web pages and hyperlinks to improve search quality, in terms of freshness and relevance of search results. Three applications that I have focused on are: (1) document representation, in which the anchortext (short descriptive text associated with hyperlinks) importance is estimated by considering its historical status; (2) web authority estimation, in which web freshness is quantified and utilized for controlling the authority propagation; and (3) learning to rank, in which freshness and relevance are optimized simultaneously in an adaptive way depending on query type. The contributions of this thesis are: (1) incorporate web dynamics information into critical components within search infrastructure in a principled way; and (2) empirically verify the proposed methods by conducting experiments based on (or depending on) a large-scale real-world archival web corpus, and demonstrated their superiority over existing state-of-the-art

Underwater noise studies in the Gulf of Lions region. Anthropogenic contributions to underwater noise due to maritime traffic and offshore windfarm operation

En el marco del proyecto MSPMED se ha llevado a cabo un caso de estudio transfronterizo entre España y Francia en relación al estado de los ecosistemas, el desarrollo de la eólica marina y el ruido submarino,. Este deliverable analiza cómo podría ser el impacto del ruido submarino producido por el tráfico marítimo y la eólica marina en el componente pelágico

Final Report DE-EE0005380: Assessment of Offshore Wind Farm Effects on Sea Surface, Subsurface and Airborne Electronic Systems

Offshore wind energy is a valuable resource that can provide a significant boost to the US renewable energy portfolio. A current constraint to the development of offshore wind farms is the potential for interference to be caused by large wind farms on existing electronic and acoustical equipment such as radar and sonar systems for surveillance, navigation and communications. The US Department of Energy funded this study as an objective assessment of possible interference to various types of equipment operating in the marine environment where offshore wind farms could be installed. The objective of this project was to conduct a baseline evaluation of electromagnetic and acoustical challenges to sea surface, subsurface and airborne electronic systems presented by offshore wind farms. To accomplish this goal, the following tasks were carried out: (1) survey electronic systems that can potentially be impacted by large offshore wind farms, and identify impact assessment studies and research and development activities both within and outside the US, (2) engage key stakeholders to identify their possible concerns and operating requirements, (3) conduct first-principle modeling on the interactions of electromagnetic signals with, and the radiation of underwater acoustic signals from, offshore wind farms to evaluate the effect of such interactions on electronic systems, and (4) provide impact assessments, recommend mitigation methods, prioritize future research directions, and disseminate project findings. This report provides a detailed description of the methodologies used to carry out the study, key findings of the study, and a list of recommendations derived based the findings

Understanding citizen science and environmental monitoring: final report on behalf of UK Environmental Observation Framework

Citizen science can broadly be defined as the involvement of volunteers in science. Over the past decade there has been a rapid increase in the number of citizen science initiatives. The breadth of environmental-based citizen science is immense. Citizen scientists have surveyed for and monitored a broad range of taxa, and also contributed data on weather and habitats reflecting an increase in engagement with a diverse range of observational science. Citizen science has taken many varied approaches from citizen-led (co-created) projects with local community groups to, more commonly, scientist-led mass participation initiatives that are open to all sectors of society. Citizen science provides an indispensable means of combining environmental research with environmental education and wildlife recording. Here we provide a synthesis of extant citizen science projects using a novel cross-cutting approach to objectively assess understanding of citizen science and environmental monitoring including: 1. Brief overview of knowledge on the motivations of volunteers. 2. Semi-systematic review of environmental citizen science projects in order to understand the variety of extant citizen science projects. 3. Collation of detailed case studies on a selection of projects to complement the semi-systematic review. 4. Structured interviews with users of citizen science and environmental monitoring data focussing on policy, in order to more fully understand how citizen science can fit into policy needs. 5. Review of technology in citizen science and an exploration of future opportunities

Incorporating stochastic analysis in wind turbine design: data-driven random temporal-spatial parameterization and uncertainty quantification

Wind turbines reliability is affected by stochastic factors in the turbulent inflow and wind turbine structures. On one hand, the variability in wind dynamics and the inherent stochastic structures result in random loads on wind turbine rotor and tower. On the other hand, the inherent structural uncertainties caused by imperfect control of manufacturing process introduce unpredictable failures and decreases wind generators availability. Therefore, to improve reliability, it is important to incorporate the variability in wind dynamics, and the inherent stochastic structures in analyzing and designing the next generation wind-turbines. In order to perform stochastic analysis on wind turbine, there are several improvements need to be made. Current stochastic wind turbine analyses are mostly based on incomplete turbulence input models. These models either failed to account for temporal variation of the stochastic wind field or unable to preserve spatial coherence which is a very important property that describes turbulence structure. On the subject of modeling wind turbine, most commonly used wind turbine design code is based on stead, lumped component blade models which lack the ability to describe the complex 3D fluid-structure interaction (FSI); which is essential to provide precise blade stress distribution and deformation details. Finally, when it comes to analyzing simulation results, most of existing work are done by analyzing the time response of wind turbine, without looking at the stochastic nature of performance of wind turbines, and its relationship between stochastic sources in turbulent inflow and turbine structure. In this work, we first develop a data driven temporal and spatial decomposition (TSD), which is capable of modeling any given large wind data set, to construct a low-dimensional yet realistic stochastic wind flow model. Results of several numerical examples on the TSD model show good consistency between given measured data and simulated synthetic turbulence. After that, a stochastic simulation based on TSD simulated full-field turbulence and a simplified wind turbine model is performed. The result of this analysis shows the adequacy of using TSD as turbulence simulation tool as well as the random nature of wind turbines\u27 performance. Finally, a stochastic analysis on a full scale 3D rich-structural wind turbine model with stochastic composite material properties is performed. With a given steady wind load, the model gives the deformation and the stress distribution of the blades. Critical regions that are most likely to have stress larger than design strength of the material were identified. Failure analysis is then performed based Tsai-Wu failure criterion

Xcompact3D: An open-source framework for solving turbulence problems on a Cartesian mesh

Xcompact3D is a Fortran 90–95 open-source framework designed for fast and accurate simulations of turbulent flows, targeting CPU-based supercomputers. It is an evolution of the flow solver Incompact3D which was initially designed in France in the mid-90’s for serial processors to solve the incompressible Navier–Stokes equations. Incompact3D was then ported to parallel High Performance Computing (HPC) systems in the early 2010’s. Very recently the capabilities of Incompact3D have been extended so that it can now tackle more flow regimes (from incompressible flows to compressible flows at low Mach numbers), resulting in the design of a new user-friendly framework called Xcompact3D. The present manuscript presents an overview of Xcompact3D with a particular focus on its functionalities, its ready-to-run simulations and a few case studies to demonstrate its impact

Microreact: visualizing and sharing data for genomic epidemiology and phylogeography

Visualization is frequently used to aid our interpretation of complex datasets. Within microbial genomics, visualizing the relationships between multiple genomes as a tree provides a framework onto which associated data (geographical, temporal, phenotypic and epidemiological) are added to generate hypotheses and to explore the dynamics of the system under investigation. Selected static images are then used within publications to highlight the key findings to a wider audience. However, these images are a very inadequate way of exploring and interpreting the richness of the data. There is, therefore, a need for flexible, interactive software that presents the population genomic outputs and associated data in a user-friendly manner for a wide range of end users, from trained bioinformaticians to front-line epidemiologists and health workers. Here, we present Microreact, a web application for the easy visualization of datasets consisting of any combination of trees, geographical, temporal and associated metadata. Data files can be uploaded to Microreact directly via the web browser or by linking to their location (e.g. from Google Drive/Dropbox or via API), and an integrated visualization via trees, maps, timelines and tables provides interactive querying of the data. The visualization can be shared as a permanent web link among collaborators, or embedded within publications to enable readers to explore and download the data. Microreact can act as an end point for any tool or bioinformatic pipeline that ultimately generates a tree, and provides a simple, yet powerful, visualization method that will aid research and discovery and the open sharing of datasets

Epidemic spreading : the role of host mobility and transportation networks

In recent years, the increasing availability of computer power has enabled both to gather an unprecedented amount of data depicting the global interconnections of the modern society and to envision computational tools able to tackle the analysis and the modeling of dynamical pro- cesses unfolding on such a complex reality. In this perspective, the quantitative approach of Physics is catalyzing the growth of new interdisciplinary fields aimed at the understanding of complex techno-socio-ecological systems. By recognizing the crucial role of host mobility in the dissemination of infectious diseases and by leveraging on a network science approach to handle the large scale datasets describing the global interconnectivity, in this thesis we present a theo- retical and computational framework to simulate epidemics of emerging infectious diseases in real settings. In particular we will tackle two different public health related issues. First, we present a Global Epidemic and Mobility model (GLEaM) that is designed to simulate the spreading of an influenza-like illness at the global scale integrating real world-wide mobility data. The 2009 H1N1 pandemic demonstrated the need of mathematical models to provide epidemic forecasts and to assess the effectiveness of different intervention policies. In this perspective we present the results achieved in real time during the unfolding of the epidemic and a posteriori analysis on travel related mitigation strategies and model validation. The second problem that we address is related to the epidemic spreading on evolving networked systems. In particular we analyze a detailed dataset of livestock movements in order to characterize the temporal correlations and the statistical properties governing the system. We then study an infectious disease spreading, in order to characterize the vulnerability of the system and to design novel control strategies. This work is an interdisciplinary approach that merges statistical physics techniques, complex and multiscale system analysis in the context of hosts mobility and computational epidemiology.Ces dernières années, la puissance croissante des ordinateurs a permis a` la fois de rassembler une quantité sans précédent de données décrivant la société moderne et d’envisager des outils numériques capables de s’attaquer a` l’analyse et la modélisation les processus dynamiques qui se déroulent dans cette réalité complexe. Dans cette perspective, l’approche quantitative de la physique est un des catalyseurs de la croissance de nouveaux domaines interdisciplinaires visant a` la compréhension des systèmes complexes techno-sociaux. Dans cette thèse, nous présentons dans cette thèse un cadre théorique et numérique pour simuler des épidémies de maladies infectieuses émergentes dans des contextes réalistes. Dans ce but, nous utilisons le rôle crucial de la mobilité des agents dans la diffusion des maladies infectieuses et nous nous appuyons sur l’ étude des réseaux complexes pour gérer les ensembles de données à grande échelle décrivant les interconnexions de la population mondiale. En particulier, nous abordons deux différents probl`emes de sant ́e publique. Tout d’abord, nous consid ́erons la propagation d’une ́epid ́emie au niveau mondial, et pr ́esentons un mod`ele de mobilit ́e (GLEAM) conc ̧u pour simuler la propagation d’une maladie de type grippal a` l’ ́echelle globale, en int ́egrant des donn ́ees r ́eelles de mobilit ́e dans le monde entier. La derni`ere pand ́emie de grippe H1N1 2009 a d ́emontr ́e la n ́ecessit ́e de mod`eles math ́ematiques pour fournir des pr ́evisions ́epid ́emiques et ́evaluer l’efficacit ́e des politiques d’interventions. Dans cette perspective, nous pr ́esentons les r ́esultats obtenus en temps r ́eel pendant le d ́eroulement de l’ ́epid ́emie, ainsi qu’une analyse a posteriori portant sur les strat ́egies de lutte et sur la validation du mod`ele. Le deuxi`eme probl`eme que nous abordons est li ́e a` la propagation de l’ ́epid ́emie sur des syst`emes en r ́eseau d ́ependant du temps. En particulier, nous analysons des donn ́ees d ́ecrivant les mouvements du b ́etail en Italie afin de caract ́eriser les corr ́elations temporelles et les propri ́et ́es statistiques qui r ́egissent ce syst`eme. Nous étudions ensuite la propagation d’une maladie infectieuse, en vue de caractériser la vulnérabilité du syst`eme et de concevoir des strat ́egies de controˆle. Ce travail est une approche interdisciplinaire qui combine les techniques de la physique statistique et de l’analyse des syst`emes complexes dans le contexte de la mobilit ́e des agents et de l’ ́epid ́emiologie num ́erique