Pasture degradation modifies the water and carbon cycles of the Tibetan highlands

The Tibetan Plateau has a significant role with regard to atmospheric circulation and the monsoon in particular. Changes between a closed plant cover and open bare soil are one of the striking effects of land use degradation observed with unsustainable range management or climate change, but experiments investigating changes of surface properties and processes together with atmospheric feedbacks are rare and have not been undertaken in the world's two largest alpine ecosystems, the alpine steppe and the Kobresia pygmaea pastures of the Tibetan Plateau. We connected measurements of micro-lysimeter, chamber, 13C labelling, and eddy covariance and combined the observations with land surface and atmospheric models, adapted to the highland conditions. This allowed us to analyse how three degradation stages affect the water and carbon cycle of pastures on the landscape scale within the core region of the Kobresia pygmaea ecosystem. The study revealed that increasing degradation of the Kobresia turf affects carbon allocation and strongly reduces the carbon uptake, compromising the function of Kobresia pastures as a carbon sink. Pasture degradation leads to a shift from transpiration to evaporation while a change in the sum of evapotranspiration over a longer period cannot be confirmed. The results show an earlier onset of convection and cloud generation, likely triggered by a shift in evapotranspiration timing when dominated by evaporation. Consequently, precipitation starts earlier and clouds decrease the incoming solar radiation. In summary, the changes in surface properties by pasture degradation found on the highland have a significant influence on larger scales.

Automated composite depth scale reconstruction of ODP Leg 138 and 154 sites

A composite section, which reconstructs a continuous stratigraphic record from cores of multiple nearby holes, and its associated composite depth scale are important tools for analyzing sediment recovered from a drilling site. However, the standard technique for creating composite depth scales on drilling cruises does not correct for depth distortion within each core. Additionally, the splicing technique used to create composite sections often results in a 10-15% offset between composite depths and measured drill depths. We present a new automated compositing technique that better aligns stratigraphy across holes, corrects depth offsets, and could be performed aboard ship. By analyzing 618 cores from seven Ocean Drilling Program (ODP) sites, we estimate that ?80% of the depth offset in traditional composite depth scales results from core extension during drilling and extraction. Average rates of extension are 12.4 ± 1.5% for calcareous and siliceous cores from ODP Leg 138 and 8.1 ± 1.1% for calcareous and clay-rich cores from ODP Leg 154. Also, average extension decreases as a function of depth in the sediment column, suggesting that elastic rebound is not the dominant extension mechanism.

(Table 4) Concentrations of radionuclides in waters of the Barents and Kara Seas in August 2003

A methodology of experimental simulation of state of spent nuclear fuel that occurs on the sea floor due to some catastrophes or dumping is developed. Data on long-term (more than 2000 days) experiments on estimation of 85Kr and 137Cs release rate from spent nuclear fuel (fragments of irradiated UO2 pellets) were firstly obtained; these estimates prove correctness of a hypothesis offered by us in early 1990s concerning to earlier 85Kr release (by one order of magnitude higher than that of 137Cs) as compared to other fission fragments in case of loss of integrity of fuel containment as a result of corrosion on the sea floor. A method and technique of onboard 85Kr and 137Cs sampling and extraction (as well as sampling of tritium, product of triple 235U fission) and their radiometric analysis at coastal laboratories are developed. Priority data on 85Kr background in bottom layers of the Barents and Kara Seas and 137Cs and 3H in these seas (state of 2003) are presented. Models necessary for estimation of dilution of fission products of spent nuclear fuel and their transport on the floor in accident and dumping regions are developed. An experimental method for examination of state of spent nuclear fuel on the sea floor (one expedition each 2-3 years) by 85Kr release into environment (a leak tracer) is proposed; this release is an indicator of destruction of fuel containment and release of products of spent nuclear fuel in case of 235UO2 corrosion in sea water.

(Appendix 1-4) Geochemistry, desorption methods, TOC, TC, and mineral content of different settings

Sorption of volatile hydrocarbon gases (VHCs) to marine sediments is a recognized phenomenon that has been investigated in the context of petroleum exploration. However, little is known about the biogeochemistry of sorbed methane and higher VHCs in environments that are not influenced by thermogenic processes. This study evaluated two different extraction protocols for sorbed VHCs, used high pressure equipment to investigate the sorption of methane to pure clay mineral phases, and conducted a geochemical and mineralogical survey of sediment samples from different oceanographic settings and geochemical regimes that are not significantly influenced by thermogenic gas. Extraction of sediments under alkaline conditions yielded higher concentrations of sorbed methane than the established protocol for acidic extraction. Application of alkaline extraction in the environmental survey revealed the presence of substantial amounts of sorbed methane in 374 out of 411 samples (91%). Particularly high amounts, up to 2.1 mmol kg**-1 dry sediment, were recovered from methanogenic sediments. Carbon isotopic compositions of sorbed methane suggested substantial contributions from biogenic sources, both in sulfate-depleted and sulfate-reducing sediments. Carbon isotopic relationships between sorbed and dissolved methane indicate a coupling of the two pools. While our sorption experiments and extraction conditions point to an important role for clay minerals as sorbents, mineralogical analyses of marine sediments suggest that variations in mineral composition are not controlling variations in quantities of sorbed methane. We conclude that the distribution of sorbed methane in sediments is strongly influenced by in situ production.

How does credit access affect children's time allocation? Evidence from rural India

Using a unique dataset obtained from rural Andhra Pradesh, India that contains direct observations of household access to credit and detailed time use, results of this study indicate that credit market failures lead to a substantial reallocation of time used by children for activities such as schooling, household chores, remunerative work, and leisure. The negative effects of credit constraints on schooling amount to a 60% decrease of average schooling time. However, the magnitude of decrease due to credit constraints is about half that of the increase in both domestic and remunerative child labor, the other half appearing to come from a reduction in leisure.

No insulation : politics and technocracy's troubled trajectory

Technocracy often holds out the promise of rational, disinterested decision-making. Yet states look to technocracy not just for expert inputs and calculated outcomes but to embed the exercise of power in many agendas, policies and programs. Thus, technocracy operates as an appendage of politically constructed structures and configurations of power, and highly placed technocrats cannot be 'mere' backroom experts who supply disinterested rational-technical solutions in economic planning, resource allocation and social distribution, which are inherently political. This paper traces the trajectories of technocracy in conditions of rapid social transformation, severe economic restructuring, or political crises - when the technocratic was unavoidably political.

Development of land rental market and its effect on household farming in rural China : an empirical study in Zhejiang Province

This paper investigates the impact of land rental market development on the efficiency of labor allocation and land utilization in rural China. To test the hypothesis that the shadow wage of a rent-in household with limited off-farm opportunities will increase with the development of a land rental market for households, a statistical comparison between the shadow wage and the estimated market wage was conducted. The results showed that the shadow wage for both rent-in households and non-rent-in households was significantly lower than the market wage, but that the wage for the rent-in households was statistically higher than that for non-rent-in households in Fenghua and Deqing, the two counties surveyed in this study. In addition, the estimated marginal product of farmland for rent-in households was statistically higher than the actual land rent that those households paid, while a null hypothesis that the actual rental fee accepted by rent-out households is equivalent to the marginal product of farmland for those households was not rejected in Fenghua county where land transactions by mutual agreement were more prevalent. These results indicate that the development of the land rental market facilitates the efficiency of labor allocation and farmland utilization in rural China.

Backward-bending of labor supply function and free riders

It seems like that backward- bending of labor supply function can be observed in Central Asian Countries such as Uzbekistan and Kazakhstan. People’s basic needs of life are satisfied and they do not increase labor supplies even if wage increases. It is possible to find some cases in which slowdowns increase, when a manager in a firm enforces penalties for workers have slowdowns. This phenomenon occurs because a worker prefers the position of equilibrium on the labor supply function always in the upper direction. This article explains the increase of free-riders by penalties and how to avoid them.

Relational and Allegorical Semantics for Constraint Logic Programming

El cálculo de relaciones binarias fue creado por De Morgan en 1860 para ser posteriormente desarrollado en gran medida por Peirce y Schröder. Tarski, Givant, Freyd y Scedrov demostraron que las álgebras relacionales son capaces de formalizar la lógica de primer orden, la lógica de orden superior así como la teoría de conjuntos. A partir de los resultados matemáticos de Tarski y Freyd, esta tesis desarrolla semánticas denotacionales y operacionales para la programación lógica con restricciones usando el álgebra relacional como base. La idea principal es la utilización del concepto de semántica ejecutable, semánticas cuya característica principal es el que la ejecución es posible utilizando el razonamiento estándar del universo semántico, este caso, razonamiento ecuacional. En el caso de este trabajo, se muestra que las álgebras relacionales distributivas con un operador de punto fijo capturan toda la teoría y metateoría estándar de la programación lógica con restricciones incluyendo los árboles utilizados en la búsqueda de demostraciones. La mayor parte de técnicas de optimización de programas, evaluación parcial e interpretación abstracta pueden ser llevadas a cabo utilizando las semánticas aquí presentadas. La demostración de la corrección de la implementación resulta extremadamente sencilla. En la primera parte de la tesis, un programa lógico con restricciones es traducido a un conjunto de términos relacionales. La interpretación estándar en la teoría de conjuntos de dichas relaciones coincide con la semántica estándar para CLP. Las consultas contra el programa traducido son llevadas a cabo mediante la reescritura de relaciones. Para concluir la primera parte, se demuestra la corrección y equivalencia operacional de esta nueva semántica, así como se define un algoritmo de unificación mediante la reescritura de relaciones. La segunda parte de la tesis desarrolla una semántica para la programación lógica con restricciones usando la teoría de alegorías—versión categórica del álgebra de relaciones—de Freyd. Para ello, se definen dos nuevos conceptos de Categoría Regular de Lawvere y _-Alegoría, en las cuales es posible interpretar un programa lógico. La ventaja fundamental que el enfoque categórico aporta es la definición de una máquina categórica que mejora e sistema de reescritura presentado en la primera parte. Gracias al uso de relaciones tabulares, la máquina modela la ejecución eficiente sin salir de un marco estrictamente formal. Utilizando la reescritura de diagramas, se define un algoritmo para el cálculo de pullbacks en Categorías Regulares de Lawvere. Los dominios de las tabulaciones aportan información sobre la utilización de memoria y variable libres, mientras que el estado compartido queda capturado por los diagramas. La especificación de la máquina induce la derivación formal de un juego de instrucciones eficiente. El marco categórico aporta otras importantes ventajas, como la posibilidad de incorporar tipos de datos algebraicos, funciones y otras extensiones a Prolog, a la vez que se conserva el carácter 100% declarativo de nuestra semántica. ABSTRACT The calculus of binary relations was introduced by De Morgan in 1860, to be greatly developed by Peirce and Schröder, as well as many others in the twentieth century. Using different formulations of relational structures, Tarski, Givant, Freyd, and Scedrov have shown how relation algebras can provide a variable-free way of formalizing first order logic, higher order logic and set theory, among other formal systems. Building on those mathematical results, we develop denotational and operational semantics for Constraint Logic Programming using relation algebra. The idea of executable semantics plays a fundamental role in this work, both as a philosophical and technical foundation. We call a semantics executable when program execution can be carried out using the regular theory and tools that define the semantic universe. Throughout this work, the use of pure algebraic reasoning is the basis of denotational and operational results, eliminating all the classical non-equational meta-theory associated to traditional semantics for Logic Programming. All algebraic reasoning, including execution, is performed in an algebraic way, to the point we could state that the denotational semantics of a CLP program is directly executable. Techniques like optimization, partial evaluation and abstract interpretation find a natural place in our algebraic models. Other properties, like correctness of the implementation or program transformation are easy to check, as they are carried out using instances of the general equational theory. In the first part of the work, we translate Constraint Logic Programs to binary relations in a modified version of the distributive relation algebras used by Tarski. Execution is carried out by a rewriting system. We prove adequacy and operational equivalence of the semantics. In the second part of the work, the relation algebraic approach is improved by using allegory theory, a categorical version of the algebra of relations developed by Freyd and Scedrov. The use of allegories lifts the semantics to typed relations, which capture the number of logical variables used by a predicate or program state in a declarative way. A logic program is interpreted in a _-allegory, which is in turn generated from a new notion of Regular Lawvere Category. As in the untyped case, program translation coincides with program interpretation. Thus, we develop a categorical machine directly from the semantics. The machine is based on relation composition, with a pullback calculation algorithm at its core. The algorithm is defined with the help of a notion of diagram rewriting. In this operational interpretation, types represent information about memory allocation and the execution mechanism is more efficient, thanks to the faithful representation of shared state by categorical projections. We finish the work by illustrating how the categorical semantics allows the incorporation into Prolog of constructs typical of Functional Programming, like abstract data types, and strict and lazy functions.

Optimal water allocation in shortage situations as applied to an irrigation community.

This work studies the most beneficial way of allocating water in an irrigation community in water shortage situations. Therefore, it proposes that the irrigation surface area be divided into homogeneous zones, each with a beneficial relationship with respect to the water applied. The mathematical formula that enables one to obtain the optimal quota for the users or irrigation community as a whole has been found for individual relations of a quadratic or power type, and these have yielded different and complementary characteristics. Dimensionless variables have been used to display the results, and to compare with other alternative allocation rules such as the proportional rule, referencing the situation without water restrictions. As a result, for each water shortage situation, the water that is allocated to each user is obtained, together with the losses in individual income and the losses for the community as a whole. Furthermore, a proposal is put forth for establishing the marginal benefit from the water available, which could be of interest in enabling each community to analyze whether it is in its best interest to invest in increasing the resource, or to sell the resource to other users. Finally, an example is given to demonstrate how the method works and to show that, when the differences between the production schemes are considered, the differences in benefit reduction between the proportional allocation and the optimal allocation are also sizeable. Read More: http://ascelibrary.org/doi/abs/10.1061/(ASCE)IR.1943-4774.0000667

Analysis of pattern recognition and dimensionality reduction techniques for odor biometrics

In this paper, we analyze the performance of several well-known pattern recognition and dimensionality reduction techniques when applied to mass-spectrometry data for odor biometric identification. Motivated by the successful results of previous works capturing the odor from other parts of the body, this work attempts to evaluate the feasibility of identifying people by the odor emanated from the hands. By formulating this task according to a machine learning scheme, the problem is identified with a small-sample-size supervised classification problem in which the input data is formed by mass spectrograms from the hand odor of 13 subjects captured in different sessions. The high dimensionality of the data makes it necessary to apply feature selection and extraction techniques together with a simple classifier in order to improve the generalization capabilities of the model. Our experimental results achieve recognition rates over 85% which reveals that there exists discriminatory information in the hand odor and points at body odor as a promising biometric identifier.

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

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.

The unpredictability paradox: review of empirical comparisons of randomised and non-randomised clinical trials

Objective To summarise comparisons of randomised clinical trials and non-randomised clinical trials, trials with adequately concealed random allocation versus inadequately concealed random allocation, and high quality trials versus low quality trials where the effect of randomisation could not be separated from the effects of other methodological manoeuvres.

Shifting Responsibilities for EU Roma Citizens: The 2010 French affair on Roma evictions and expulsions continued. CEPS Paper in Liberty and Security in Europe No. 55, June 2013

Despite the ultimatum delivered in October 2010 to the French government by Viviane Reding, Vice-President of the European Commission, to adapt its national immigration law ‘to the letter’ of the Citizens Directive 2004/38, the country has continued to evict and expel Romanian and Bulgarian nationals of Roma origin. This paper examines the state of affairs with respect to France’s policy on eviction and expulsion of Roma and assesses the way in which the controversy has developed and can be understood from the perspective of citizenship of the EU. On the basis of an examination of the subsequent responses by the European Commission and the EU member states involved, as well as of a recent bilateral agreement concluded between France and Romania on the reintegration of families of Romanian citizens belonging to the Roma minority who have exercised their freedom to move, the paper suggests that there has been a paradigm shift in the priorities driving EU policy responses and politics. This shift has led to an ethnicisation of citizenship of the Union, where ethnicity increasingly plays a decisive role in the allocation and attribution of responsibility to secure and safeguard the union freedoms.