Seawater carbonate chemistry and carbon allocation, growth and morphology of the coccolithophore Emiliania huxleyi (calcifying strain CCMP 371) during experiments, 2011

Coccolithophores are unicellular phytoplankton that produce calcium carbonate coccoliths as an exoskeleton. Emiliania huxleyi, the most abundant coccolithophore in the world's ocean, plays a major role in the global carbon cycle by regulating the exchange of CO2 across the ocean-atmosphere interface through photosynthesis and calcium carbonate precipitation. As CO2 concentration is rising in the atmosphere, the ocean is acidifying and ammonium (NH4) concentration of future ocean water is expected to rise. The latter is attributed to increasing anthropogenic nitrogen (N) deposition, increasing rates of cyanobacterial N2 fixation due to warmer and more stratified oceans, and decreased rates of nitrification due to ocean acidification. Thus future global climate change will cause oceanic phytoplankton to experience changes in multiple environmental parameters including CO2, pH, temperature and nitrogen source. This study reports on the combined effect of elevated pCO2 and increased NH4 to nitrate (NO3) ratio (NH4/NO3) on E. huxleyi, maintained in continuous cultures for more than 200 generations under two pCO2 levels and two different N sources. Here we show that NH4 assimilation under N-replete conditions depresses calcification at both low and high pCO2, alters coccolith morphology, and increases primary production. We observed that N source and pCO2 synergistically drive growth rates, cell size and the ratio of inorganic to organic carbon. These responses to N source suggest that, compared to increasing CO2 alone, a greater disruption of the organic carbon pump could be expected in response to the combined effect of increased NH4/NO3 ratio and CO2 level in the future acidified ocean. Additional experiments conducted under lower nutrient conditions are needed prior to extrapolating our findings to the global oceans. Nonetheless, our results emphasize the need to assess combined effects of multiple environmental parameters on phytoplankton biology in order to develop accurate predictions of phytoplankton responses to ocean acidification.

Ocean acidification induces multi-generational decline in copepod naupliar production with possible conflict for reproductive resource allocation

Climate change, including ocean acidification (OA), presents fundamental challenges to marine biodiversity and sustained ecosystem health. We determined reproductive response (measured as naupliar production), cuticle composition and stage specific growth of the copepod Tisbe battagliai over three generations at four pH conditions (pH 7.67, 7.82, 7.95, and 8.06). Naupliar production increased significantly at pH 7.95 compared with pH 8.06 followed by a decline at pH 7.82. Naupliar production at pH 7.67 was higher than pH 7.82. We attribute the increase at pH 7.95 to an initial stress response which was succeeded by a hormesis-like response at pH 7.67. A multi-generational modelling approach predicted a gradual decline in naupliar production over the next 100 years (equivalent to approximately 2430 generations). There was a significant growth reduction (mean length integrated across developmental stage) relative to controls. There was a significant increase in the proportion of carbon relative to oxygen within the cuticle as seawater pH decreased. Changes in growth, cuticle composition and naupliar production strongly suggest that copepods subjected to OA-induced stress preferentially reallocate resources towards maintaining reproductive output at the expense of somatic growth and cuticle composition. These responses may drive shifts in life history strategies that favour smaller brood sizes, females and perhaps later maturing females, with the potential to profoundly destabilise marine trophodynamics.

Experimental ocean acidification alters the allocation of metabolic energy

Energy is required to maintain physiological homeostasis in response to environmental change. Although responses to environmental stressors frequently are assumed to involve high metabolic costs, the biochemical bases of actual energy demands are rarely quantified. We studied the impact of a near-future scenario of ocean acidification [800 µatm partial pressure of CO2 (pCO2)] during the development and growth of an important model organism in developmental and environmental biology, the sea urchin Strongylocentrotus purpuratus. Size, metabolic rate, biochemical content, and gene expression were not different in larvae growing under control and seawater acidification treatments. Measurements limited to those levels of biological analysis did not reveal the biochemical mechanisms of response to ocean acidification that occurred at the cellular level. In vivo rates of protein synthesis and ion transport increased 50% under acidification. Importantly, the in vivo physiological increases in ion transport were not predicted from total enzyme activity or gene expression. Under acidification, the increased rates of protein synthesis and ion transport that were sustained in growing larvae collectively accounted for the majority of available ATP (84%). In contrast, embryos and prefeeding and unfed larvae in control treatments allocated on average only 40% of ATP to these same two processes. Understanding the biochemical strategies for accommodating increases in metabolic energy demand and their biological limitations can serve as a quantitative basis for assessing sublethal effects of global change. Variation in the ability to allocate ATP differentially among essential functions may be a key basis of resilience to ocean acidification and other compounding environmental stressors.

Seawater carbonate chemistry and resource allocation and extracellular acid-base status in the sea urchin Strongylocentrotus droebachiensis during experiments, 2012

Anthropogenic CO2 emission will lead to an increase in seawater pCO2 of up to 80-100 Pa (800-1000 µatm) within this century and to an acidification of the oceans. Green sea urchins (Strongylocentrotus droebachiensis) occurring in Kattegat experience seasonal hypercapnic and hypoxic conditions already today. Thus, anthropogenic CO2 emissions will add up to existing values and will lead to even higher pCO2 values >200 Pa (>2000 µatm). To estimate the green sea urchins' potential to acclimate to acidified seawater, we calculated an energy budget and determined the extracellular acid base status of adult S. droebachiensis exposed to moderately (102 to 145 Pa, 1007 to 1431 µatm) and highly (284 to 385 Pa, 2800 to 3800 µatm) elevated seawater pCO2 for 10 and 45 days. A 45 - day exposure to elevated pCO2 resulted in a shift in energy budgets, leading to reduced somatic and reproductive growth. Metabolic rates were not significantly affected, but ammonium excretion increased in response to elevated pCO2. This led to decreased O:N ratios. These findings suggest that protein metabolism is possibly enhanced under elevated pCO2 in order to support ion homeostasis by increasing net acid extrusion. The perivisceral coelomic fluid acid-base status revealed that S. droebachiensis is able to fully (intermediate pCO2) or partially (high pCO2) compensate extracellular pH (pHe) changes by accumulation of bicarbonate (maximum increases 2.5 mM), albeit at a slower rate than typically observed in other taxa (10 day duration for full pHe compensation). At intermediate pCO2, sea urchins were able to maintain fully compensated pHe for 45 days. Sea urchins from the higher pCO2 treatment could be divided into two groups following medium-term acclimation: one group of experimental animals (29%) contained remnants of food in their digestive system and maintained partially compensated pHe (+2.3 mM HCO3), while the other group (71%) exhibited an empty digestive system and a severe metabolic acidosis (-0.5 pH units, -2.4 mM HCO3). There was no difference in mortality between the three pCO2 treatments. The results of this study suggest that S. droebachiensis occurring in the Kattegat might be pre-adapted to hypercapnia due to natural variability in pCO2 in its habitat. We show for the first time that some echinoderm species can actively compensate extracellular pH. Seawater pCO2 values of >200 Pa, which will occur in the Kattegat within this century during seasonal hypoxic events, can possibly only be endured for a short time period of a few weeks. Increases in anthropogenic CO2 emissions and leakages from potential sub-seabed CO2 storage (CCS) sites thus impose a threat to the ecologically and economically important species S. droebachiensis.

Allocation efficiency in China : an extension of the dynamic Olley-Pakes productivity decomposition

This paper develops a quantitative measure of allocation efficiency, which is an extension of the dynamic Olley-Pakes productivity decomposition proposed by Melitz and Polanec (2015). The extended measure enables the simultaneous capture of the degree of misallocation within a group and between groups and parallel to capturing the contribution of entering and exiting firms to aggregate productivity growth. This measure empirically assesses the degree of misallocation in China using manufacturing firm-level data from 2004 to 2007. Misallocation among industrial sectors has been found to increase over time, and allocation efficiency within an industry has been found to worsen in industries that use more capital and have firms with relatively higher state-owned market shares. Allocation efficiency among three ownership sectors (state-owned, domestic private, and foreign sectors) tends to improve in industries wherein the market share moves from a less-productive state-owned sector to a more productive private sector.

IDRA (IDeal Resource Allocation): Computing ideal speedups in parallel logic programming

We present a technique to estimate accurate speedups for parallel logic programs with relative independence from characteristics of a given implementation or underlying parallel hardware. The proposed technique is based on gathering accurate data describing one execution at run-time, which is fed to a simulator. Alternative schedulings are then simulated and estimates computed for the corresponding speedups. A tool implementing the aforementioned techniques is presented, and its predictions are compared to the performance of real systems, showing good correlation.

IDRA (IDeal Resource Allocation): A tool for computing ideal speedups

Performance studies of actual parallel systems usually tend to concéntrate on the effectiveness of a given implementation. This is often done in the absolute, without quantitave reference to the potential parallelism contained in the programs from the point of view of the execution paradigm. We feel that studying the parallelism inherent to the programs is interesting, as it gives information about the best possible behavior of any implementation and thus allows contrasting the results obtained. We propose a method for obtaining ideal speedups for programs through a combination of sequential or parallel execution and simulation, and the algorithms that allow implementing the method. Our approach is novel and, we argüe, more accurate than previously proposed methods, in that a crucial part of the data - the execution times of tasks - is obtained from actual executions, while speedup is computed by simulation. This allows obtaining speedup (and other) data under controlled and ideal assumptions regarding issues such as number of processor, scheduling algorithm and overheads, etc. The results obtained can be used for example to evalúate the ideal parallelism that a program contains for a given model of execution and to compare such "perfect" parallelism to that obtained by a given implementation of that model. We also present a tool, IDRA, which implements the proposed method, and results obtained with IDRA for benchmark programs, which are then compared with those obtained in actual executions on real parallel systems.

Leveraging heterogeneity for energy minimization in data centers

Energy consumption in data centers is nowadays a critical objective because of its dramatic environmental and economic impact. Over the last years, several approaches have been proposed to tackle the energy/cost optimization problem, but most of them have failed on providing an analytical model to target both the static and dynamic optimization domains for complex heterogeneous data centers. This paper proposes and solves an optimization problem for the energy-driven configuration of a heterogeneous data center. It also advances in the proposition of a new mechanism for task allocation and distribution of workload. The combination of both approaches outperforms previous published results in the field of energy minimization in heterogeneous data centers and scopes a promising area of research.

Iterative bit- and power allocation in correlated MIMO systems

In this contribution a novel iterative bit- and power allocation (IBPA) approach has been developed when transmitting a given bit/s/Hz data rate over a correlated frequency non-selective (4× 4) Multiple-Input MultipleOutput (MIMO) channel. The iterative resources allocation algorithm developed in this investigation is aimed at the achievement of the minimum bit-error rate (BER) in a correlated MIMO communication system. In order to achieve this goal, the available bits are iteratively allocated in the MIMO active layers which present the minimum transmit power requirement per time slot.

Proactive and reactive thermal aware optimization techniques to minimize the environmental impact of data centers

Los Centros de Datos se encuentran actualmente en cualquier sector de la economía mundial. Están compuestos por miles de servidores, dando servicio a los usuarios de forma global, las 24 horas del día y los 365 días del año. Durante los últimos años, las aplicaciones del ámbito de la e-Ciencia, como la e-Salud o las Ciudades Inteligentes han experimentado un desarrollo muy significativo. La necesidad de manejar de forma eficiente las necesidades de cómputo de aplicaciones de nueva generación, junto con la creciente demanda de recursos en aplicaciones tradicionales, han facilitado el rápido crecimiento y la proliferación de los Centros de Datos. El principal inconveniente de este aumento de capacidad ha sido el rápido y dramático incremento del consumo energético de estas infraestructuras. En 2010, la factura eléctrica de los Centros de Datos representaba el 1.3% del consumo eléctrico mundial. Sólo en el año 2012, el consumo de potencia de los Centros de Datos creció un 63%, alcanzando los 38GW. En 2013 se estimó un crecimiento de otro 17%, hasta llegar a los 43GW. Además, los Centros de Datos son responsables de más del 2% del total de emisiones de dióxido de carbono a la atmósfera. Esta tesis doctoral se enfrenta al problema energético proponiendo técnicas proactivas y reactivas conscientes de la temperatura y de la energía, que contribuyen a tener Centros de Datos más eficientes. Este trabajo desarrolla modelos de energía y utiliza el conocimiento sobre la demanda energética de la carga de trabajo a ejecutar y de los recursos de computación y refrigeración del Centro de Datos para optimizar el consumo. Además, los Centros de Datos son considerados como un elemento crucial dentro del marco de la aplicación ejecutada, optimizando no sólo el consumo del Centro de Datos sino el consumo energético global de la aplicación. Los principales componentes del consumo en los Centros de Datos son la potencia de computación utilizada por los equipos de IT, y la refrigeración necesaria para mantener los servidores dentro de un rango de temperatura de trabajo que asegure su correcto funcionamiento. Debido a la relación cúbica entre la velocidad de los ventiladores y el consumo de los mismos, las soluciones basadas en el sobre-aprovisionamiento de aire frío al servidor generalmente tienen como resultado ineficiencias energéticas. Por otro lado, temperaturas más elevadas en el procesador llevan a un consumo de fugas mayor, debido a la relación exponencial del consumo de fugas con la temperatura. Además, las características de la carga de trabajo y las políticas de asignación de recursos tienen un impacto importante en los balances entre corriente de fugas y consumo de refrigeración. La primera gran contribución de este trabajo es el desarrollo de modelos de potencia y temperatura que permiten describes estos balances entre corriente de fugas y refrigeración; así como la propuesta de estrategias para minimizar el consumo del servidor por medio de la asignación conjunta de refrigeración y carga desde una perspectiva multivariable. Cuando escalamos a nivel del Centro de Datos, observamos un comportamiento similar en términos del balance entre corrientes de fugas y refrigeración. Conforme aumenta la temperatura de la sala, mejora la eficiencia de la refrigeración. Sin embargo, este incremente de la temperatura de sala provoca un aumento en la temperatura de la CPU y, por tanto, también del consumo de fugas. Además, la dinámica de la sala tiene un comportamiento muy desigual, no equilibrado, debido a la asignación de carga y a la heterogeneidad en el equipamiento de IT. La segunda contribución de esta tesis es la propuesta de técnicas de asigación conscientes de la temperatura y heterogeneidad que permiten optimizar conjuntamente la asignación de tareas y refrigeración a los servidores. Estas estrategias necesitan estar respaldadas por modelos flexibles, que puedan trabajar en tiempo real, para describir el sistema desde un nivel de abstracción alto. Dentro del ámbito de las aplicaciones de nueva generación, las decisiones tomadas en el nivel de aplicación pueden tener un impacto dramático en el consumo energético de niveles de abstracción menores, como por ejemplo, en el Centro de Datos. Es importante considerar las relaciones entre todos los agentes computacionales implicados en el problema, de forma que puedan cooperar para conseguir el objetivo común de reducir el coste energético global del sistema. La tercera contribución de esta tesis es el desarrollo de optimizaciones energéticas para la aplicación global por medio de la evaluación de los costes de ejecutar parte del procesado necesario en otros niveles de abstracción, que van desde los nodos hasta el Centro de Datos, por medio de técnicas de balanceo de carga. Como resumen, el trabajo presentado en esta tesis lleva a cabo contribuciones en el modelado y optimización consciente del consumo por fugas y la refrigeración de servidores; el modelado de los Centros de Datos y el desarrollo de políticas de asignación conscientes de la heterogeneidad; y desarrolla mecanismos para la optimización energética de aplicaciones de nueva generación desde varios niveles de abstracción. ABSTRACT Data centers are easily found in every sector of the worldwide economy. They consist of tens of thousands of servers, serving millions of users globally and 24-7. In the last years, e-Science applications such e-Health or Smart Cities have experienced a significant development. The need to deal efficiently with the computational needs of next-generation applications together with the increasing demand for higher resources in traditional applications has facilitated the rapid proliferation and growing of data centers. A drawback to this capacity growth has been the rapid increase of the energy consumption of these facilities. In 2010, data center electricity represented 1.3% of all the electricity use in the world. In year 2012 alone, global data center power demand grew 63% to 38GW. A further rise of 17% to 43GW was estimated in 2013. Moreover, data centers are responsible for more than 2% of total carbon dioxide emissions. This PhD Thesis addresses the energy challenge by proposing proactive and reactive thermal and energy-aware optimization techniques that contribute to place data centers on a more scalable curve. This work develops energy models and uses the knowledge about the energy demand of the workload to be executed and the computational and cooling resources available at data center to optimize energy consumption. Moreover, data centers are considered as a crucial element within their application framework, optimizing not only the energy consumption of the facility, but the global energy consumption of the application. The main contributors to the energy consumption in a data center are the computing power drawn by IT equipment and the cooling power needed to keep the servers within a certain temperature range that ensures safe operation. Because of the cubic relation of fan power with fan speed, solutions based on over-provisioning cold air into the server usually lead to inefficiencies. On the other hand, higher chip temperatures lead to higher leakage power because of the exponential dependence of leakage on temperature. Moreover, workload characteristics as well as allocation policies also have an important impact on the leakage-cooling tradeoffs. The first key contribution of this work is the development of power and temperature models that accurately describe the leakage-cooling tradeoffs at the server level, and the proposal of strategies to minimize server energy via joint cooling and workload management from a multivariate perspective. When scaling to the data center level, a similar behavior in terms of leakage-temperature tradeoffs can be observed. As room temperature raises, the efficiency of data room cooling units improves. However, as we increase room temperature, CPU temperature raises and so does leakage power. Moreover, the thermal dynamics of a data room exhibit unbalanced patterns due to both the workload allocation and the heterogeneity of computing equipment. The second main contribution is the proposal of thermal- and heterogeneity-aware workload management techniques that jointly optimize the allocation of computation and cooling to servers. These strategies need to be backed up by flexible room level models, able to work on runtime, that describe the system from a high level perspective. Within the framework of next-generation applications, decisions taken at this scope can have a dramatical impact on the energy consumption of lower abstraction levels, i.e. the data center facility. It is important to consider the relationships between all the computational agents involved in the problem, so that they can cooperate to achieve the common goal of reducing energy in the overall system. The third main contribution is the energy optimization of the overall application by evaluating the energy costs of performing part of the processing in any of the different abstraction layers, from the node to the data center, via workload management and off-loading techniques. In summary, the work presented in this PhD Thesis, makes contributions on leakage and cooling aware server modeling and optimization, data center thermal modeling and heterogeneityaware data center resource allocation, and develops mechanisms for the energy optimization for next-generation applications from a multi-layer perspective.

Stability and sensitivity analysis of Be-CoDiS, an epidemiological model to predict the spread of human diseases between countries. Validation with data from the 2014-16 West African Ebola Virus Disease epidemic.

Ebola virus disease is a lethal human and primate disease that requires a particular attention from the international health authorities due to important recent outbreaks in some Western African countries and isolated cases in European and North-America continents. Regarding the emergency of this situation, various decision tools, such as mathematical models, were developed to assist the authorities to focus their efforts in important factors to eradicate Ebola. In a previous work, we have proposed an original deterministic spatial-temporal model, called Be-CoDiS (Between-Countries Disease Spread), to study the evolution of human diseases within and between countries by taking into consideration the movement of people between geographical areas. This model was validated by considering numerical experiments regarding the 2014-16 West African Ebola Virus Disease epidemic. In this article, we propose to perform a stability analysis of Be-CoDiS. Our first objective is to study the equilibrium states of simplified versions of this model, limited to the cases of one an two countries, and to determine their basic reproduction ratios. Then, in order to give some recommendations for the allocation of resources used to control the disease, we perform a sensitivity analysis of those basic reproduction ratios regarding the model parameters. Finally, we validate the obtained results by considering numerical experiments based on data from the 2014-16 West African Ebola Virus Disease epidemic.

A hydrological–economic model for sustainable groundwater use in sparse-data drylands: Application to the Amtoudi Oasis in southern Morocco, northern Sahara

A hydrological–economic model is introduced to describe the dynamics of groundwater-dependent economics (agriculture and tourism) for sustainable use in sparse-data drylands. The Amtoudi Oasis, a remote area in southern Morocco, in the northern Sahara attractive for tourism and with evidence of groundwater degradation, was chosen to show the model operation. Governing system variables were identified and put into action through System Dynamics (SD) modeling causal diagrams to program basic formulations into a model having two modules coupled by the nexus ‘pumping’: (1) the hydrological module represents the net groundwater balance (G) dynamics; and (2) the economic module reproduces the variation in the consumers of water, both the population and tourists. The model was operated under similar influx of tourists and different scenarios of water availability, such as the wet 2009–2010 and the average 2010–2011 hydrological years. The rise in international tourism is identified as the main driving force reducing emigration and introducing new social habits in the population, in particular concerning water consumption. Urban water allotment (PU) was doubled for less than a 100-inhabitant net increase in recent decades. The water allocation for agriculture (PI), the largest consumer of water, had remained constant for decades. Despite that the 2-year monitoring period is not long enough to draw long-term conclusions, groundwater imbalance was reflected by net aquifer recharge (R) less than PI + PU (G < 0) in the average year 2010–2011, with net lateral inflow from adjacent Cambrian formations being the largest recharge component. R is expected to be much less than PI + PU in recurrent dry spells. Some low-technology actions are tentatively proposed to mitigate groundwater degradation, such as: wastewater capture, treatment, and reuse for irrigation; storm-water harvesting for irrigation; and active maintenance of the irrigation system to improve its efficiency.

The Reallocation of Agricultural Labour across Sectors: An Empirical Strategy for Micro Data. Factor Markets Working Document No. 45, May 2013

This paper presents an empirical methodology for studying the reallocation of agricultural labour across sectors from micro data. Whereas different approaches have been employed in the literature to better understand the mobility of labour, looking at the determinants to exit farm employment and enter off-farm activities, the initial decision of individuals to work in agriculture, as opposed to other sectors, has often been neglected. The proposed methodology controls for the selectivity bias, which may arise in the presence of a non-random sample of the population, in this context those in agricultural employment, which would lead to biased and inconsistent estimates. A 3-step multivariate probit with two selection and one outcome equations constitutes the selected empirical approach to explore the determinants of farm labour to exit agriculture and switch occupational sector. The model can be used to take into account the different market and production structures across European member states on the allocation of agricultural labour and its adjustments.

Measuring competitiveness in Europe: resource allocation, granularity and trade. Bruegel Blueprint Series Volume XVIV, January 2016

One of the most important lessons learned during the 2008-09 financial crisis was that the informational toolbox on which policymakers base their decisions about competitiveness became outdated in terms of both data sources and data analysis. The toolbox is particularly outdated when it comes to tapping the potential of micro data for the analysis of competitiveness – a serious problem given that it is firms, rather than countries that compete on global markets.

Guidance for state water monitoring and wasteload allocation programs.

Mode of access: Internet.