Interaction dynamics in small networks of nonlinear elements

We study a small circuit of coupled nonlinear elements to investigate general features of signal transmission through networks. The small circuit itself is perceived as building block for larger networks. Individual dynamics and coupling are motivated by neuronal systems: We consider two types of dynamical modes for an individual element, regular spiking and chattering and each individual element can receive excitatory and/or inhibitory inputs and is subjected to different feedback types (excitatory and inhibitory; forward and recurrent). Both, deterministic and stochastic simulations are carried out to study the input-output relationships of these networks. Major results for regular spiking elements include frequency locking, spike rate amplification for strong synaptic coupling, and inhibition-induced spike rate control which can be interpreted as a output frequency rectification. For chattering elements, spike rate amplification for low frequencies and silencing for large frequencies is characteristic

Distributed Extremum-Seeking Control with Applications to High-Altitude Balloons

The real-time optimization of large-scale systems is a difficult problem due to the need for complex models involving uncertain parameters and the high computational cost of solving such problems by a decentralized approach. Extremum-seeking control (ESC) is a model-free real-time optimization technique which can estimate unknown parameters and can optimize nonlinear time-varying systems using only a measurement of the cost function to be minimized. In this thesis, we develop a distributed version of extremum-seeking control which allows large-scale systems to be optimized without models and with minimal computing power. First, we develop a continuous-time distributed extremum-seeking controller. It has three main components: consensus, parameter estimation, and optimization. The consensus provides each local controller with an estimate of the cost to be minimized, allowing them to coordinate their actions. Using this cost estimate, parameters for a local input-output model are estimated, and the cost is minimized by following a gradient descent based on the estimate of the gradient. Next, a similar distributed extremum-seeking controller is developed in discrete-time. Finally, we consider an interesting application of distributed ESC: formation control of high-altitude balloons for high-speed wireless internet. These balloons must be steered into a favourable formation where they are spread out over the Earth and provide coverage to the entire planet. Distributed ESC is applied to this problem, and is shown to be effective for a system of 1200 ballons subjected to realistic wind currents. The approach does not require a wind model and uses a cost function based on a Voronoi partition of the sphere. Distributed ESC is able to steer balloons from a few initial launch sites into a formation which provides coverage to the entire Earth and can maintain a similar formation as the balloons move with the wind around the Earth.

Measuring the sustainability of a national economy. The application of three measures of sustainability to Ireland

An assessment of the sustainability of the Irish economy has been carried out using three methodologies, enabling comparison and evaluation of the advantages and disadvantages of each, and potential synergies among them. The three measures chosen were economy-wide Material Flow Analysis (MFA), environmentally extended input-output (EE-IO) analysis and the Ecological Footprint (EF). The research aims to assess the sustainability of the Irish economy using these methods and to draw conclusions on their effectiveness in policy making both individually and in combination. A theoretical description discusses the methods and their respective advantages and disadvantages and sets out a rationale for their combined application. The application of the methods in combination has provided insights into measuring the sustainability of a national economy and generated new knowledge on the collective application of these methods. The limitations of the research are acknowledged and opportunities to address these and build on and extend the research are identified. Building on previous research, it is concluded that a complete picture of sustainability cannot be provided by a single method and/or indicator.

Physical model parameter optimisation for calibrated emulation of the Dallas Rangemaster Treble Booster guitar pedal

In this work we explore optimising parameters of a physical circuit model relative to input/output measurements, using the Dallas Rangemaster Treble Booster as a case study. A hybrid metaheuristic/gradient descent algorithm is implemented, where the initial parameter sets for the optimisation are informed by nominal values from schematics and datasheets. Sensitivity analysis is used to screen parameters, which informs a study of the optimisation algorithm against model complexity by fixing parameters. The results of the optimisation show a significant increase in the accuracy of model behaviour, but also highlight several key issues regarding the recovery of parameters.

Use of a Neural Network to Predict Strength and Optimum Compositions of Natural Alumina-Silica-Based Geopolymers

In order to predict compressive strength of geopolymers prepared from alumina-silica natural products, based on the effect of Al 2 O 3 /SiO 2, Na 2 O/Al 2 O 3, Na 2 O/H 2 O, and Na/[Na+K], more than 50 pieces of data were gathered from the literature. The data was utilized to train and test a multilayer artificial neural network (ANN). Therefore a multilayer feedforward network was designed with chemical compositions of alumina silicate and alkali activators as inputs and compressive strength as output. In this study, a feedforward network with various numbers of hidden layers and neurons were tested to select the optimum network architecture. The developed three-layer neural network simulator model used the feedforward back propagation architecture, demonstrated its ability in training the given input/output patterns. The cross-validation data was used to show the validity and high prediction accuracy of the network. This leads to the optimum chemical composition and the best paste can be made from activated alumina-silica natural products using alkaline hydroxide, and alkaline silicate. The research results are in agreement with mechanism of geopolymerization.


Read More: http://ascelibrary.org/doi/abs/10.1061/(ASCE)MT.1943-5533.0000829

Optimización de la Entrada Salida mediante librerías y lenguajes paralelos

Uno de los grandes retos de la HPC (High Performance Computing) consiste en optimizar el subsistema de Entrada/Salida, (E/S), o I/O (Input/Output). Ken Batcher resume este hecho en la siguiente frase: "Un supercomputador es un dispositivo que convierte los problemas limitados por la potencia de cálculo en problemas limitados por la E/S" ("A Supercomputer is a device for turning compute-bound problems into I/O-bound problems") . En otras palabras, el cuello de botella ya no reside tanto en el procesamiento de los datos como en la disponibilidad de los mismos. Además, este problema se exacerbará con la llegada del Exascale y la popularización de las aplicaciones Big Data. En este contexto, esta tesis contribuye a mejorar el rendimiento y la facilidad de uso del subsistema de E/S de los sistemas de supercomputación. Principalmente se proponen dos contribuciones al respecto: i) una interfaz de E/S desarrollada para el lenguaje Chapel que mejora la productividad del programador a la hora de codificar las operaciones de E/S; y ii) una implementación optimizada del almacenamiento de datos de secuencias genéticas. Con más detalle, la primera contribución estudia y analiza distintas optimizaciones de la E/S en Chapel, al tiempo que provee a los usuarios de una interfaz simple para el acceso paralelo y distribuido a los datos contenidos en ficheros. Por tanto, contribuimos tanto a aumentar la productividad de los desarrolladores, como a que la implementación sea lo más óptima posible. La segunda contribución también se enmarca dentro de los problemas de E/S, pero en este caso se centra en mejorar el almacenamiento de los datos de secuencias genéticas, incluyendo su compresión, y en permitir un uso eficiente de esos datos por parte de las aplicaciones existentes, permitiendo una recuperación eficiente tanto de forma secuencial como aleatoria. Adicionalmente, proponemos una implementación paralela basada en Chapel.

Una Estimación del Impacto del Gasto en Atención a la Dependencia en Andalucía

La atención a la dependencia es, sin lugar a dudas, uno de los grandes retos de futuro de las sociedades que envejecen aceleradamente, al que España y Andalucía no sólo no son ajenos, sino que presentan rasgos que lo amplifican. Sin embargo, es un fenómeno que adolece de importantes lagunas de información, fundamentalmente la carencia de una perspectiva integral que conecte la realidad social, el cambio económico, y la necesidad de transformación de los modelos de bienestar en general y de cuidados en particular, el gasto necesario para su desarrollo y el impacto económico asociado; enfoque holístico que se adopta en este trabajo. Dentro del marco expuesto el objetivo principal del trabajo es cuantificar el impacto en términos de actividad, empleo y retorno fiscal, así como la relación entre la prestación recibida y las características de los dependientes, que permita avanzar en la consideración de este gasto social como una inversión. Para la estimación de los impactos se ha utilizado el Marco Input-Output de Andalucía (MIOAN) de 2010. No obstante, para calcular los incrementos de renta generados por los requerimientos producidos, se ha endogeneizado la demanda de consumo, esto ha implicado construir expresamente para este cálculo una matriz ampliada de Leontief, procediendo a una estimación especifica de la fila adicional ampliada. Finalmente para estimar la relación entre prestación y características de los dependientes se han construido distintos modelos logísticos binarios, y un modelo multinomial. Desarrollado el trabajo de investigación y cuantificado el impacto, la conclusión fundamental no es sólo fuerte efecto arrastre del gasto en dependencia en la actividad y el empleo , sino que se produce en el marco de un cambio irreversible que sitúa a los Cuidados de Larga Duración asociados a la dependencia con un papel central en el contexto de la evolución del Estado el Bienestar. En concreto se ha verificado que: • Andalucía realiza un elevado gasto en atención a la dependencia, 1314 millones de euros, un 85 % del cual total es público y un 15 % privado, y que este gasto genera un fuerte impacto en la economía andaluza, pues su contribución a los grandes agregados macroeconómicos de Andalucía es de un 0,9 % del PIB, superior al impulso de demanda que supone el gasto en atención a la dependencia. • La atención a la dependencia ha mostrado una elevada capacidad de generación de empleo, más de 40.000 empleos, muy concentrado además en personas de difícil inserción en el mercado laboral, mujeres maduras de cualificación media-baja y con poca experiencia acreditable en sector formal de la atención. • La relación entre usuarios, gasto, e impacto para las trasferencias y los servicios muestra un modelo en escalera que caracteriza un sistema de universalización de coste medio con impacto moderado. Un modelo en el que las transferencias suponen el 50 % de los atendidos, el 30 % del gasto y el 20 % del impacto. • El retorno fiscal generado por la dependencia es muy elevado, casi del 45%. • El esfuerzo financiero, tanto bruto como neto, descontado el retorno vía impuestos que obtiene de cada administración, es muy asimétrico lo que puede generar un efecto desincentivador del desarrollo de un modelo con más servicios frente a transferencias. • Las características de los dependientes condicionan la prestación que parece ajustarse a los la características personales y de grado de discapacidad más que las socioeconómicas.

Synthetic Circuits for Feedback and Detection in Bacteria

Synthetic biology, by co-opting molecular machinery from existing organisms, can be used as a tool for building new genetic systems from scratch, for understanding natural networks through perturbation, or for hybrid circuits that piggy-back on existing cellular infrastructure. Although the toolbox for genetic circuits has greatly expanded in recent years, it is still difficult to separate the circuit function from its specific molecular implementation. In this thesis, we discuss the function-driven design of two synthetic circuit modules, and use mathematical models to understand the fundamental limits of circuit topology versus operating regimes as determined by the specific molecular implementation. First, we describe a protein concentration tracker circuit that sets the concentration of an output protein relative to the concentration of a reference protein. The functionality of this circuit relies on a single negative feedback loop that is implemented via small programmable protein scaffold domains. We build a mass-action model to understand the relevant timescales of the tracking behavior and how the input/output ratios and circuit gain might be tuned with circuit components. Second, we design an event detector circuit with permanent genetic memory that can record order and timing between two chemical events. This circuit was implemented using bacteriophage integrases that recombine specific segments of DNA in response to chemical inputs. We simulate expected population-level outcomes using a stochastic Markov-chain model, and investigate how inferences on past events can be made from differences between single-cell and population-level responses. Additionally, we present some preliminary investigations on spatial patterning using the event detector circuit as well as the design of stationary phase promoters for growth-phase dependent activation. These results advance our understanding of synthetic gene circuits, and contribute towards the use of circuit modules as building blocks for larger and more complex synthetic networks.

Self-defeating austerity? Assessing the impact of fiscal consolidations on unemployment

The great recession of 2008/2009 has had a huge impact on unemployment and public finances in most advanced countries, and these impacts were magnified in the southern Euro area countries by the sovereign debt crisis of 2010/2011. The fiscal consolidation imposed by the European Union on highly indebted countries was based on the assumptions of the so-called expansionary austerity. However, the reality so far shows proof to the contrary, and the results of this paper support the opposing view of a self- defeating austerity. Based on the input-output relations of the productive system, an unemployment rate/budget balance trade-off equation is derived, as well as the impact of a strong fiscal consolidation based on social transfers and the notion of neutral budget balance. An application to the Portuguese case confirms the huge costs of a strong fiscal consolidation, both in terms of unemployment and social policy regress, and it allows one to conclude that too much consolidation in one year makes consolidation more difficult in the following year.

Foreign direct investment determinants revisited in the context of global value chains

In this paper, we aim at contributing to the new field of research that intends to bring up-to-date the tools and statistics currently used to look to the current reality given by Global Value Chains (GVC) in international trade and Foreign Direct Investment (FDI). Namely, we make use of the most recent data published by the World Input-Output Database to suggest indicators to measure the participation and net gains of countries by being a part of GVC; and use those indicators in a pooled-regression model to estimate determinants of FDI stocks in Organization for Economic Co-operation and Development (OECD)-member countries. We conclude that one of the measures proposed proves to be statistically significant in explaining the bilateral stock of FDI in OECD countries, meaning that the higher the transnational income generated between two given countries by GVC, taken as a proxy to the participation of those countries in GVC, the higher one could expect the FDI entering those countries to be. The regression also shows the negative impact of the global financial crisis that started in 2009 in the world’s bilateral FDI stocks and, additionally, the particular and significant role played by the People’s Republic of China in determining these stocks.

A comparison of the yaw constraining performance of SCARA-tau parallel manipulator variants via screw theory

The SCARA-Tau parallel manipulator was derived with the objective to overcome the limited workspace-to-footprint ratio of the DELTA parallel manipulator while maintaining its many benefits. The SCARA-Tau family has later been extended and a large number of variants have been proposed. In this paper, we analyse four of these variants, which together encompass the main differences between all the proposed SCARA-Tau manipulators. The analysed manipulator variants utilise an identical arrangement of five of the six linkages connecting the actuated arms and the manipulated platform and exhibit the same input-output Jacobian. The normalised reciprocal product between the wrench of the sixth linkage and the twist of the platform occurring without this linkage provides a measure on how effectively the sixth linkage constrains the manipulated platform. A comparison of the manipulator variants with respect to this measure demonstrates each variants suitability for specific applications.

Rock slope stability analyses using extreme learning neural network and terminal steepest descent algorithm

The analysis of rock slope stability is a classical problem for geotechnical engineers. However, for practicing engineers, proper software is not usually user friendly, and additional resources capable of providing information useful for decision-making are required. This study developed a convenient tool that can provide a prompt assessment of rock slope stability. A nonlinear input-output mapping of the rock slope system was constructed using a neural network trained by an extreme learning algorithm. The training data was obtained by using finite element upper and lower bound limit analysis methods. The newly developed techniques in this study can either estimate the factor of safety for a rock slope or obtain the implicit parameters through back analyses. Back analysis parameter identification was performed using a terminal steepest descent algorithm based on the finite-time stability theory. This algorithm not only guarantees finite-time error convergence but also achieves exact zero convergence, unlike the conventional steepest descent algorithm in which the training error never reaches zero.

Inter-industry analysis and monetary policy evaluations in the Korean flow of funds accounts

This study mainly aims to provide an inter-industry analysis through the subdivision of various industries in flow of funds (FOF) accounts. Combined with the Financial Statement Analysis data from 2004 and 2005, the Korean FOF accounts are reconstructed to form "from-whom-to-whom" basis FOF tables, which are composed of 115 institutional sectors and correspond to tables and techniques of input–output (I–O) analysis. First, power of dispersion indices are obtained by applying the I–O analysis method. Most service and IT industries, construction, and light industries in manufacturing are included in the first quadrant group, whereas heavy and chemical industries are placed in the fourth quadrant since their power indices in the asset-oriented system are comparatively smaller than those of other institutional sectors. Second, investments and savings, which are induced by the central bank, are calculated for monetary policy evaluations. Industries are bifurcated into two groups to compare their features. The first group refers to industries whose power of dispersion in the asset-oriented system is greater than 1, whereas the second group indicates that their index is less than 1. We found that the net induced investments (NII)–total liabilities ratios of the first group show levels half those of the second group since the former's induced savings are obviously greater than the latter.

Undermined climate policies : a study on the impact of regulatory and financial discrimination across heterogeneous firms in China

Firms in China within the same industry but with different ownership and size have very different production functions and can face very different emission regulations and financial conditions. This fact has largely been ignored in most of the existing literature on climate change. Using a newly augmented Chinese input–output table in which information about firm size and ownership are explicitly reported, this paper employs a dynamic computable general equilibrium (CGE) model to analyze the impact of alternative climate policy designs with respect to regulation and financial conditions on heterogeneous firms. The simulation results indicate that with a business-as-usual regulatory structure, the effectiveness and economic efficiency of climate policies is significantly undermined. Expanding regulation to cover additional firms has a first-order effect of improving efficiency. However, over-investment in energy technologies in certain firms may decrease the overall efficiency of investments and dampen long-term economic growth by competing with other fixed-capital investments for financial resources. Therefore, a market-oriented arrangement for sharing emission reduction burden and a mechanism for allocating green investment is crucial for China to achieve a more ambitious emission target in the long run.

Productivity growth and the structure of production

In this study, interactions between potential hierarchical value chains existing in the production structure and industry-wise productivity growths are sought. We applied generalized Chenery-Watanabe heuristics for matrix linearity maximization to triangulate the input-output incidence matrix for both Japan and the Republic of Korea, finding the potential directed flow of values spanning the industrial sectors of the basic (disaggregated) industry classifications for both countries. Sector specific productivity growths were measured by way of the Trönquvist index, using the 2000-2005 linked input-output tables for both Japan and Korea.